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ACKNOWLEDGEMENTS
I would like to thank my major advisor, Dr. Pam Cox Jutte, for unending support,
guidance, and encouragement during the many phases of my graduate career. Although
there aren’t enough words to express it here, I will simply state that without her, I know
this thesis would have never been. In addition, I would like to thank committee
members, Drs. Laura Kracker, Cass Runyon, and Bob Van Dolah, for many thought
provoking discussions and helpful comments on this thesis. Their input and insights have
provided direction that has shaped this project. Many others have also helped me gather,
develop, analyze, and present this data: Mr. George Riekerk, Ms. Lynn Zimmerman, the
South Carolina Estuarine and Coastal Assessment Program crew, Mr. William Roumillat,
Dr. John Fauth, Dr. Allan Strand, Dr. Lesa Meng, Ms. Gretchen Hay, Dr. George
Sedberry, and Marine Resources Library staff. Each person has made various
contributions that were pillars for this research.
This project definitely would not have been possible if it were not for funding
from the College of Charleston, NASA Experimental Program to Stimulate Competitive
Research (EPSCoR) Program, South Carolina Department of Natural Resources, U.S.
Fish and Wildlife, Joanna Deep Water Fellowship, U.S. Environmental Protection
Agency, RGII Technologies, and National Oceanic and Atmospheric Administration.
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I would also like to thank Dr. Chip Biernbaum, Dr. Scott France, Mr. Robert
Martore, Ms. Peko Tsuji, and the South Carolina Department of Natural Resources
Artificial Reef group for their time and effort on a previous project. Their enthusiasm for
planning and developing a field intensive project was very much incorporated into this
thesis and has also made me a better scientist.
I would like to acknowledge the support that I got from the Grice Marine
Laboratory family that has definitely helped me in more ways than I can describe during
my graduate career. Finally, I would like to thank my family and friends for providing
me love and laughter. Many people have been with me through thick and thin, including
Elizabeth Jones, Mark Renshaw, and Bohdan Kot. I truly have been blessed to have so
many cheerleaders in my corner.
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TABLE OF CONTENTS
ACKNOWLEDGEMENTS………………………………………………………….... ii
TABLE OF CONTENTS................................................................................................. iv
LIST OF FIGURES……………………………………………………………………. vii
LIST OF TABLES…………………………………………………………………....... ix
ABSTRACT……………………………………………………………………………. xi
INTRODUCTION……………………………………………………………............... 1
METHODS AND MATERIALS……………………………………………………..... 8
Sampling design and procedures……………………………………………..... 8
Candidate fish metrics………………………………………………................. 11
Life history metrics…………………………………………………………….. 13
Ecological and trophic metrics……………………………………………......... 14
Tolerance metrics………………………………………………………………. 15
Community structure metrics…………………………………………………... 19
Determining environmental quality…………………………………………..... 20
Water quality……………….………………………….…….................. 20
Sediment quality……………………………………………………...... 21
Upland quality………………………………………………….............. 22
Overall quality…………………………………………………............. 23
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METHODS AND MATERIALS (continued)
Physical features……………………………………………………………….. 24
Development of the estuarine biotic integrity (EBI) index…………………….. 25
One-way analyses.................................................................................... 26
Stepwise discriminant analyses...…………….…………………………26
Previous studies………………………………………………………... 28
Composite and single metric analyses…………………………………. 28
Application and validation of the EBI index…………………………………... 29
Median analyses………………………………………………………... 29
Discriminant analyses………………...………….…………………….. 30
Evaluation and selection of the EBI index............….………………….………. 32
Stations with excellent environmental quality…………………………………. 33
RESULTS………………………………………………………………………............ 34
Environmental quality and physical features....................................................... 34
Fish community………………………………………………………………... 38
Development of the estuarine biotic integrity (EBI) index…………………….. 40
One-way analyses.................................................................................... 40
Stepwise discriminant analyses................................................................41
Previous studies....................................................................................... 42
Composite and single metric analyses..................................................... 43
Application of the EBI index – Median analyses................................................ 46
EBI index Ax............................................................................................ 46
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RESULTS (continued)
EBI index Bx............................................................................................ 47
EBI index Cx............................................................................................ 49
EBI index Dx............................................................................................ 49
EBI index Ex............................................................................................ 52
Application of the EBI index – Discriminant analyses........................................ 52
EBI index Ax............................................................................................ 52
EBI index Bx............................................................................................ 54
EBI index Cx............................................................................................ 55
EBI index Dx............................................................................................ 56
EBI index Ex............................................................................................ 57
Evaluation and selection of the final EBI index……………………………….. 58
Stations with excellent environmental quality……………………..................... 62
DISCUSSION.................................................................................................................. 63
Environmental quality and physical features....................................................... 63
Fish community................................................................................................... 67
Development and evaluation of the final EBI index............................................ 70
Future directions and recommendations.............................................................. 77
SUMMARY AND CONCLUSIONS.............................................................................. 86
LITERATURE CITED.................................................................................................... 89
FIGURES......................................................................................................................... 187
TABLES.......................................................................................................................... 205
APPENDICES................................................................................................................. 230
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LIST OF FIGURES
Figure 1. Array of 97 tidal creek stations sampled in 1999-2002 used in the current study,
chosen from the larger South Carolina Estuarine Coastal Assessment Program
(SCECAP) sampling array..…………………………......................................... 187
Figure 2. Flowchart of methods for developing and evaluating an estuarine biotic
integrity (EBI) index for South Carolina tidal creeks.………………………..... 189
Figure 3. The two creeks that contained one marginal station located upstream relative to
one good station located downstream: a) Kiawah River and b) May River.…... 191
Figure 4. Box-plots of nine of the 73 candidate fish metrics that were significantly
different between good and marginal stations sampled in 1999-2001 (Wilcoxon
test, Dunn-Sidak test, k=73, α=0.10, p<0.0014).………………………............ 193
Figure 5. Total misclassification rates of EBI indices A1,2 and B1,2, based on the median
or discriminant analyses………………............................................................... 195
Figure 6. Total misclassification rates for all EBI indices developed in the current study,
based on the median or discriminant analyses…………………………............. 197
Figure 7. Good and marginal station misclassification rates for all EBI indices developed
in the current study, based on the median analyses.……………….................... 199
Figure 8. Good and marginal station misclassification rates for all EBI indices developed
in the current study, based on discriminant analyses........................................... 201
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Figure 9. Estuarine biotic integrity (EBI) scores of marginal and good stations, calculated
by a) EBI index A3, b) EBI index C2, c) EBI index C3, d) EBI index D2, and e)
EBI index D6 (final EBI index)............................................................................203
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LIST OF TABLES
Table 1. Critical values of water, sediment, and upland quality parameters that were used
to classify 97 stations sampled in 1999-2002 for the South Carolina Estuarine and
Coastal Assessment Program (SCECAP) as good, marginal, or poor................. 205
Table 2. Fish metrics that described life history, ecological and trophic composition,
tolerance, and community structure (italicized metrics were not included as
candidate fish metrics in statistical analyses).……............................................. 207
Table 3. Average values (±1 standard deviation) of water, sediment, upland, and physical
parameters for marginal, good, and excellent stations sampled in 1999-2002.... 210
Table 4. Environmental and physical parameters of two creeks (May and Kiawah Rivers)
that each contained one good and one marginal station.…………………......... 212
Table 5. Average value (±1 standard deviation) of the 21 fish metrics selected by the one-
way analyses, stepwise discriminant analyses, or previous studies for marginal,
good, and excellent stations.....……………….................................................... 214
Table 6. Summary of the 21 fish metrics included for each EBI index evaluated (boxed
X=not used in discriminant analyses)..………………........................................ 216
Table 7. Fish metrics that were significantly different between good and marginal stations
sampled in 1999-2001 (Wilcoxon test, Dunn-Sidak test, 61 stations=good, 8
stations=marginal, α=0.10, k=73, p<0.0014)...................................................... 218
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Table 8. Significant fish metrics selected by stepwise discriminant analyses, using a
subset of 50 candidate metrics and stations sampled in 1999-2001 (61
stations=good; 8 stations=marginal; p<0.15)....................................................... 220
Table 9. Significant fish metrics selected by stepwise discriminant analyses, using a
subset of 50 candidate metrics and stations sampled in 1999-2002 (87
stations=good; 9 stations=marginal, p<0.15)....................................................... 222
Table 10. Subset of fish metrics that were used in previously developed estuarine biotic
integrity indices (Deegan et al. 1997; Meng et al. 2002).……………………... 224
Table 11. Twenty-one candidate fish metrics that were selected by statistical analyses or
by previous studies.…………….......................................................................... 226
Table 12. Nine fish metrics that were used in the final EBI index (EBI index D6)……. 228
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ABSTRACT
Large-scale environmental monitoring studies require a great amount of time and energy
to complete. Often, a more efficient method to monitor environmental condition is to
concentrate on biological communities. Fish communities are desirable environmental
indicators due to their ability to directly integrate physical, chemical, and biological
conditions. Data collected in tidal creeks for the South Carolina Estuarine and Coastal
Assessment Program (SCECAP) during the 1999-2002 sampling seasons were used to
determine the relationship between environmental quality and fish community measures.
Statistical analyses, previous studies, and ecological concepts directed the selection of
fish metrics that were the best discriminators of environmental quality. Potential
multimetric estuarine biotic integrity (EBI) indices used combinations of fish metrics to
calculate a single score to predict environmental quality. Station classification results
using median analyses were more conservative in having low error rates for classifying
marginal stations, while results from discriminant analyses were most useful in
determining the final EBI index that could discriminate between marginal and good
stations without error. The final EBI index developed and evaluated for South Carolina
tidal creeks used metrics that described fish life history, ecological composition,
tolerance, and community structure. These metrics were sensitive in determining
environmental quality as described by water, sediment, and upland quality parameters,
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and should be among the primary metrics considered for the development of future
indices. The final EBI index presented in the current study should be considered as an
index in the developmental stage, due to the low number of marginal stations available
and the lack of a true validation dataset. While the final EBI index did not prove to be a
perfect tool for assessing environmental quality in South Carolina’s tidal creeks, it can
serve as a point of departure for continuing development of future indices. This study
was the first effort in South Carolina to develop and evaluate an estuarine index of biotic
integrity using the fish community and was an important first step in understanding the
relationships between fish metrics and environmental quality in tidal creeks.
INTRODUCTION
The United States (US) Water Pollution Control Act of 1972, an amendment to
the Clean Water Act originally implemented in 1948, prompted biological assessment for
the restoration and maintenance of the biotic integrity of surface waters. The standard
definition for biotic integrity was established as “the capability of supporting and
maintaining a balanced, integrated, adaptive community of organisms having a species
composition, diversity, and functional organization comparable to that of natural habitat
of the region” (Karr and Dudley 1981). This definition is supported by the US
Environmental Protection Agency (EPA; Ohio EPA 1988; USEPA 1988) and has
influenced many ecological studies of least impacted and developed habitats.
Environmental parameters, such as dissolved oxygen, pH, sediment composition,
and human disturbances, can greatly affect the species composition of biological
communities in a given area. Since large-scale studies of an ecosystem require a great
amount of time and energy, many have recognized that concentrating on biological
communities is a more efficient method to monitor overall environmental condition (e.g.,
Chandler 1970; Winner et al. 1980; Ohio EPA 1988; Ramm 1988; Hughes 1989; Simon
and Lyons 1995; Yoder and Rankin 1998). For example, biological communities in
estuaries have been shown to predictably respond to anthropogenic pollution (e.g.,
Pearson and Rosenberg 1978; Leppakoski 1977; Wilson and Jeffrey 1987; Crawford et
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al. 1994; Hartwell et al. 1997; Hyland et al. 1999; Schimmel et al. 1999). Both fish and
macroinvertebrate communities are desirable indicators, reflecting the quality of the
environment by directly integrating physical, chemical, and biological conditions
(Berkman 1986; Ohio EPA 1988; Cairns et al. 1993; Yoder and Rankin 1995; Cranston
et al. 1996; Mebane 2001). Historically, macroinvertebrates have been popular indicators
for surveying conditions because they incorporate various trophic levels, cannot escape
adverse environmental conditions quickly, and are highly sensitive to environmental
changes (Perry et al. 1984; Ohio EPA 1988; USEPA 1988; Rosenberg and Resh 1993;
Chessman 1995). Fish are also sensitive to environmental changes, and are arguably
more easily understood by the public as economically and recreationally important
organisms (Hocutt 1981; Karr 1981; Berkman et al. 1986; Karr et al. 1986; USEPA
1988; Harris 1995; Blaber 1999; Hughes and Oberdoff 1999). As a result, many
investigations have considered fish communities as the prime environmental indicator or
as a supplement to macroinvertebrate community studies (Ohio EPA 1988; USEPA 1988;
Yoder and Rankin 1995; Snyder et al. 1999).
Gammon (1976) proposed a multi-parameter method to profile water quality
using four measures (number of species, relative density, biomass, and diversity) of the
fish community in an Index of well-being (Iwb). However, some fish communities may
not reflect environmental degradation in the Iwb if a measurement of high biomass,
associated as a positive trait, was dominated by tolerant species (Yoder and Smith 1999).
Consequently, Karr (1981) proposed an index of biotic integrity (IBI) using fish
community metrics that included the presence of intolerant species, richness and
composition of tolerant species, and the representation of different trophic levels. Each
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metric was rated (5=slight deviation from the undisturbed condition, 3=moderate
deviation, and 1=strong deviation from the undisturbed condition). Sites were scored by
the sum of the ratings, and the score placed each site into a category that explained its
relative condition (excellent, good, fair, poor, very poor; Karr 1981; Karr et al. 1986).
Validation studies have demonstrated that the multimetric index approach
proposed by Karr (1981) was more effective for environmental assessment than relying
solely upon independent metrics (Angermeier and Schlosser 1987; Karr et al. 1987; Ohio
EPA 1988; Fausch et al. 1990; Hughes 1989, Karr 1991; Harris 1994; Barbour et al.
1995; Yoder and Rankin 1995; Lyons et al. 1996; Deegan et al. 1997; Boulton 1999) or
multivariate analyses (Fausch et al. 1990; Hughes and Noss 1992; Fore et al., 1996; Van
Dolah et al. 1999). An independent metric, such as species diversity, may produce
misleading interpretations of the environment. For example, Gray (1976) found a grossly
polluted estuary and other less polluted estuaries to have comparable species diversity, a
metric that was popularly associated with ecosystem health. On the other hand,
multivariate analyses (e.g., clustering and ordination) enable the interactions among
many variables to be considered while being objective (Zar 1984), and have been used
successfully for communities with a limited amount of variables (Clarke 1993; Rosen
1995). However, fish and invertebrate community assessments involve many variables
that may increase the complexity and decrease the power (the probability to reject a false
null hypothesis) in multivariate analyses (Zar 1984; Fausch et al. 1990; Fore et al. 1996;
Reynoldson et al. 1997; Van Dolah et al. 1999).
The multimetric index approach shows a clear reflection of relationships among
many variables that are simple to repeat and understand (Fausch et al. 1990; Fore et al.
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1994; Hughes and Noss 1992; Gerritsen 1995; Fore et al. 1996; Karr and Chu 1997; Van
Dolah et al. 1999). However, the development and practical application of an index
depends greatly on the amount of knowledge available to resource managers on the
physical habitat quality, water quality, and natural fish community composition
(Bramblett and Fausch 1991; Fausch et al. 1984; Karr 1999). Key factors that contribute
to the accuracy and effectiveness of an index are: consistent sampling methods, high
quality data, and the identification of metrics that are closely related to environmental
quality (Angermeier and Karr 1986; Fausch et al. 1990; Karr 1999).
The IBI developed by the multimetric approach has been approved by the USEPA
(1988) to be used to monitor freshwater quality and the IBI continues to be modified as
numerous new indices are produced regionally inside and outside of the US (e.g., Saylor
and Scott 1987; Miller et al. 1988; Steedman 1988; Plafkin et al. 1989; Hughes 1989;
Hughes et al. 1998; Roth et al. 1998; Kleynhans 1999). Modified fish IBIs have
expanded from the mid-western US to Canada and the northern regions of the US, but the
technique has not yet become a popular application in the southeastern US (Hughes 1989;
Simon and Lyons 1995). In South Carolina, stream water quality monitoring programs
are well established (Perry et al. 1984), but the biocriteria of fish and invertebrate
communities used in biological assessment programs are still in the developmental stage
(Southerland and Stribling 1995; Yoder and Rankin 1998). Paller et al. (1996) developed
a modified IBI for fish communities in South Carolina coastal plain streams 2-15 m wide.
However, an IBI modified for small streams cannot be directly applied to larger water
bodies because stream width and depth are the greatest influences on the fish community
structure (Fausch et al. 1984; Paller 1994; Hay 2001).
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Along with many of the modified IBIs, the original IBI (Karr et al. 1986) was
developed for fish communities inhabiting freshwater streams and few multimetric
indices have been applied directly to estuaries. Estuaries are ecosystems classified as
semi-enclosed areas where freshwater and seawater mixes (Pritchard 1955), including
tidal creeks, marshes, and bays. Beginning in 1983, US federal programs targeted
estuaries to evaluate estuarine health by gathering baseline physical, hydrological, and
biological data and information on anthropogenic and natural resources (Alexander and
Monaco 1994; USEPA 2001, 2004). Many smaller scale estuarine assessments have used
individual metrics (e.g., Gray 1976; Harrel and Hall 1991; Crawford et al. 1994) or
benthic macroinvertebrates indices (e.g., Engle et al. 1994; Fore et al 1996; Weisberg et
al. 1997; Van Dolah et al. 1999) to determine estuarine quality.
Fish communities have been used to develop multimetric estuarine biotic integrity
indices to determine the status of estuaries in the northeastern US (Deegan et al. 1993,
1997; Meng et al. 2002). In particular, Deegan et al. (1993, 1997) developed an estuarine
biotic integrity index (EBI) that has been validated as a useful tool to monitor
anthropogenic change in the Massachusetts region (Chun et al. 1996; Deegan et al. 1997;
Hughes et al. 2002). The EBI included fish metrics, similar to Karr et al. (1986), which
were significantly different between areas of different habitat quality.
Fish metrics that were used or suggested in the development of other estuarine
indices of biotic integrity (Thompson and Fitzhugh 1986; Deegan et al. 1993, 1997;
Guillen 2000; Meng et al. 2002) were evaluated as candidate metrics for the current
study. Candidate metrics described fish in four broad categories: life history, trophic and
ecological composition, tolerance, and community structure. Fish life history metrics
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characterize fish based on the habitat that they use to develop as juveniles, to spawn, and
to inhabit for the majority of their life. Trophic and ecological composition metrics
define fish based on diet and feeding behavior, as well as where fish reside relative to the
water column. Tolerance metrics are a measure of relative sensitivity of species to
environmental conditions and include metrics such as salinity independent fish
(Weinstein 1979), resilient fish (Musick 1999; Froese and Pauly 2000), and taxonomic
designation. Community structure metrics include fish density, species richness, species
evenness, species diversity, and species dominance. Statistical tests indicated
preliminary metrics that were strong discriminators of environmental quality, while
ecological principles guided the final selection of candidate metrics that were useful in a
multimetric index.
The current study is the first to use fish metrics to develop and evaluate an
estuarine biotic integrity (EBI) index for South Carolina tidal creeks. A benthic index of
biotic integrity (B-IBI) was successfully developed in South Carolina estuaries using
benthic macroinvertebrates in large tidal rivers (tidally influenced rivers with detectable
tides >2.5 cm; area >260 km2, and length/width aspect ratio >20), as well as areas that
contained more open water (area >2.6 km2 and length/width aspect ratio <20; Hyland et
al. 1998; Van Dolah et al. 1999). Although the B-IBI was developed to assess sediment
quality in the Carolinian Province (Hyland et al. 1998; Van Dolah et al. 1999), the
environmental conditions in tidal creek habitats vary greatly from large tidal rivers and
open water areas. Tidal creeks (defined in the current study as creeks <100 m wide) are
smaller bodies of water than tidal rivers or open water, and can provide an early
indication of habitat stress because they are the first point of entry for upland runoff
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(Holland et al. 1997; Sanger et al. 1999a, 1999b; Van Dolah et al. 2000). As part of a
statewide monitoring program, Van Dolah et al. (2002) compared South Carolina tidal
creeks (also defined as creeks <100 m wide) and open water stations and found
significant differences in water quality parameters, sediment quality parameters, and
density and biomass of fish and crustacean species. Based on these findings, Van dolah
et al. (2002) suggested that tidal creeks should be evaluated as separate habitats from
open water bodies.
The current study used the tidal creek fish community to develop and evaluate an
EBI index and to determine if: 1) fish communities adequately reflect the biotic integrity
of creek habitats based on specific environmental parameters and 2) using the EBI index
is an effective method for managers to determine critical sites to rehabilitate, monitor,
and protect. The development of the EBI index used results from one-way analyses,
stepwise discriminant analyses, previous studies (Deegan et al. 1997; Meng et al. 2002),
and ecological principles to incorporate many parameters into a single multimetric index.
The evaluation of the EBI index involved median analysis and discriminant analysis. The
current study was the first to use fish communities as a tool to discern estuarine biotic
integrity when evaluating the quality of estuarine habitats in South Carolina.
MATERIALS AND METHODS
Sampling design and procedures
Sample collection for the current study was completed in 1999-2002 through the
South Carolina Estuarine and Coastal Monitoring Program (SCECAP; Van Dolah et al.
2002; Van Dolah et al. 2004a). SCECAP is an interagency program developed by the
South Carolina Department of Natural Resources (SCDNR) and the South Carolina
Department of Health and Environmental Control (SCDHEC), and a partner in the United
States Environmental Protection Agency (USEPA) National Coastal Assessment program
and Coastal 2000 program. Field sampling design and sampling procedures for the
current study followed SCECAP protocols (Van Dolah et al. 2002).
During 1999-2002, SCECAP selected approximately 30 South Carolina tidal
creek stations to sample each year, with stations located in water bodies that had widths
of less than 100 m from marsh bank to marsh bank. Tidal creeks were defined using one
or more of the following geographic information system (GIS) coverages: United States
Geological Survey (USGS) 1994 hydrography digital line graphs (DLG), National
Wetland Inventory (NWI) 1989 and 1994 databases, digital 7.5’ topographic quadrangle
maps (1994), and the Coastal Change Analysis Program (CCAP) 1995 database.
Additional stations were located in deeper open water sites, such as harbors, sounds, and
large tidal rivers, but these data were not analyzed in the current study. To reduce the
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effect of biological variation due to salinity (Weinstein 1979), only stations with salinities
greater than 18 ppt were selected for the current study, which excluded ten stations from
analysis.
Stations were located within the coastal zone extending from the saltwater–
freshwater interface to near the mouth of each estuarine drainage basin, and extending
from the Little River Inlet at the South Carolina-North Carolina border to the Wright
River near the South Carolina-Georgia border (Figure 1). Some portions of the state’s
coastal waters that were too shallow to sample at low tide were excluded from the station
selection process. Stations were part of a larger array of stations selected using a
probability-based, random tessellation, stratified sampling design (Stevens 1997; Stevens
and Olsen 1999), with new station locations picked each year for SCECAP. Five non-
random stations sampled in 2001 and 2002 were also included: three stations (MR1-01-T,
MR3-03-T, and MR3-04-T) were sampled in the May River, a tidal creek area that is
currently experiencing increased development pressure (Van Dolah et al. 2004b), and
two stations (NT01598 and NT02301) were sampled in Shem Creek, a highly developed
tidal creek area.
Tidal creek stations were sampled during the day, at low tide, during June through
August of 1999-2002. At low tide, fish are forced out of the shallow marsh banks into
subtidal channels where they can be sampled. The majority of fish that take advantage of
South Carolina estuaries for food, spawning grounds, and nursery grounds usually
migrate into the estuaries beginning in the spring and reside there through the summer
(Shealy et al. 1974; Cain and Dean 1976; Wenner et al. 1981, 1984, 1991; Allen and
Barker 1990). Natural stresses in estuaries, such as low dissolved oxygen levels and high
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temperatures, are more common during the summer season. The effects of anthropogenic
stress on biological communities in estuarine systems would be most apparent during the
summer if natural stresses are already present. Therefore, sampling during the summer
season maximized the likelihood of detecting anthropogenic stress acting on the estuarine
fish community (Deegan et al. 1997).
A subset of water and sediment parameters collected for SCECAP were selected
for the current study based on their ability to distinguish among stations based on
differing levels of development and anthropogenic disturbance (Table 1; Appendix A).
At each station, a datasonde was deployed for at least 25 hours to continuously collect
salinity, temperature, dissolved oxygen, and pH at 15-minute intervals. Near-surface
water samples were collected in bottles and used to determine biological oxygen demand,
fecal coliform bacteria concentration, total nitrogen, and total phosphorus (SCDHEC
1997, 1998b). Sediment samples were collected using a 0.04 m2 Young grab. Sediments
were analyzed for inorganic and organic contaminants by the National Oceanic and
Atmospheric Administration – National Ocean Service Center for Coastal Environmental
Health and Biomolecular Research (NOAA-NOS CCEHBR; Van Dolah et al. 2002).
Physical features, such as latitude/longitude, and average depth at each station were also
collected using a geological positioning system (GPS) and depth finder, respectively
(Appendix B).
Two standardized 0.25 km replicate tows were made at each station using a 4-
seam bottom trawl (5.5 m foot rope, 4.6 m head rope, and 2 cm bar mesh throughout).
All animals were sorted to the lowest practical taxonomic level, counted, and checked for
gross pathologies, deformities or external parasites. Fish and crustaceans were measured
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to the nearest 1.0 cm, and when a species’ abundance exceeded 25 individuals, a
subsample of 25 individuals from that species was measured. Species identification and
measurements from random trawls were checked by a quality assurance and quality
control program approved by the USEPA National Coastal Assessment Program.
Although crustaceans and squid were found in trawls, only fish data were used in the
current study. Mean fish abundances were corrected for the total area swept (Krebs
1972; Appendix C):
Area swept (A) =
Candidate fish metrics
The first step to developing and evaluating an estuarine biotic integrity (EBI)
index was to compile fish community metrics (Figure 2). Metrics describing fish life
history, ecological and trophic composition, relative fish tolerance, and community
structure were compiled using literature and past observations of local fish experts (Table
2; Appendices D.1-5). Several candidate life history metrics evaluated in the current
study described estuarine/tidal creek nursery fish, estuarine dependent fish, estuarine/tidal
creek spawning fish, and estuarine/tidal creek residents. Candidate ecological and
trophic metrics evaluated in the current study were benthic fish, benthic feeders,
herbivores, carnivores, predators, and detritivores. Tolerance metrics considered in the
current study included salinity independent fish (Weinstein 1979), resilient (Musick
1999; Froese and Pauly 2000), and taxonomic designation such as flatfish, flounder,
sciaenids, bay anchovy, and shad. Complete profiles were created for all but five metrics
(tidal creek nursery fish, tidal creek spawning fish, tidal creek resident, salinity
Distance (D) x 0.6 Head rope length (H) 10,000 m2 ha-1
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independent fish, and resilient fish) because detailed ecological and tolerance data were
not available for all taxa. A conservative approach was used for these five metrics when
data were not available by leaving taxa as unclassified (blank value; Appendices D.1-5).
All metrics were calculated for two replicate trawls and averaged for each station
(Appendices E.1-4; SAS Institute 2002b). All candidate life history, ecological and
trophic composition, and tolerance metrics described the fish community in three ways:
1) density of fish, 2) percent of fish, and 3) number of taxa. Community structure metrics
included overall density, overall number of taxa, dominance of the most abundant taxon,
dominance of the two most abundant taxa, dominance of the three most abundant taxa,
the number of taxa that composed 90% of the total abundance, the number of taxa that
composed 95% of the total abundance, species diversity, species evenness, and species
richness. Formulas included:
(1) Berger-Parker Dominance d (Berger and Parker 1970) =
where Nmax=number of individuals of either the most abundant taxon, the
two most abundant taxa, or the three most abundant taxa, and
Ntotal=total number of individuals in a sample
(2) Shannon-Wiener Species Diversity H' (Shannon 1948) =
where N=total number of individuals in a sample, and
ni=the number of individuals in the ith taxa
(3) Pielou’s Species Evenness J' (Pielou 1966) =
where H'=Shannon-Wiener index, and
S=total number of taxa in the sample
H' Log S
(N log2 N) - Σ(ni log2 ni) N
Nmax Nt
x 100
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(4) Margalef’s Species Richness D (Margalef 1958) =
where S=total number of taxa in the sample, and
N=total number of individuals in the sample
Species diversity (H'), species evenness (J'), and species richness (D) were not
transformed for any analyses. The density of individuals and the number of species data
were log transformed (ln[x+1]), while percents were converted to proportions and arcsine
transformed (arcsin√x; Zar 1984). Non-transformed data were analyzed
nonparametrically when statistical tests were available, as transformations were not
successful in normalizing all data (Shapiro-Wilk test, p<0.05; Zar 1984).
Life history metrics
Fish life history metrics provided information on the life stage and the amount of
time that a fish spends in an estuary. Costa and Cabral (1999) found that pollution in an
estuary caused a decrease in the abundances of juvenile fish that used the estuary as a
nursery. Fish living in adverse environmental conditions have also been found to have
decreased fecundity and offspring survival, ultimately leading to decreased abundances
(Kime 1995). Diadromous and estuarine-dependent fish have high energy and oxygen
demands during migration (Leonard 1997) and may be more sensitive to degraded
conditions than fish that reside in the estuary for their entire life cycle. Furthermore,
Chittenden (1969) and Ellis et al. (1947) found that repeat estuarine spawners were
especially prone to decreased abundances when pollution was high and dissolved oxygen
was low.
(S-1) ln N
- 14 -
All of the candidate life history metric values evaluated for the current study were
expected to decrease in response to environmental degradation, except for the metrics
describing estuarine resident and tidal creek resident fish (Table 2). Resident fish species
may migrate within the estuary or tidal creek, but do not spend any part of their life cycle
in coastal areas (i.e., offshore, nearshore, surf zone). Long-term effects of degraded
environmental conditions may eventually lead to lowered abundances of resident fish
species. However, resident fish species are expected to dominate the fish community
because initial changes in the environmental quality will result in decreased abundances
of transient fish species, such as estuarine dependent fish, that have higher demands for
resources.
Ecological and trophic metrics
Ecological and trophic metrics integrated information on fish spatial distribution
and community interactions, indicating the degree to which a fish is exposed to poor
quality conditions. Benthic fish and benthic feeders have contaminant levels in their
tissues that are comparable to those found in the sediment they inhabit (Koli et al. 1977;
Yannai and Sachs 1978; McCain et al. 1996), which may lead to many negative lethal
and sublethal health effects (Sindermann 1995). Adverse environmental conditions may
also cause decreased prey quality as well as quantity for benthic feeders (Wedemeyer et
al. 1984; Meng et al. 2001; Swan and Palmer 2000). Some benthic feeders accumulate
contaminants at a higher rate when exposed to contaminated sediments because
contaminants are available through consumption of contaminated prey, as well as
absorption through the skin and gills (DiPinto and Coull 1997). Furthermore, most
- 15 -
benthic estuarine fish and benthic feeders are able to detect and avoid hypoxic bottom
waters (dissolved oxygen <1 mg/L; Pihl et al. 1991; Wannamaker and Rice 2000).
Additionally, piscivorous fish and other top predators are more sensitive to degraded
environmental quality than invertivores, herbivores, or omnivores because of the effects
from bioaccumulation and biomagnification of toxic chemicals, and populations of top
predators respond negatively to decreased environmental quality (e.g., Koli et al. 1977;
Yannai and Sachs 1978; Karr et al. 1986; Paller et al. 1996; Ganasan and Hughes 1998;
Guillen 2000; Mol et al. 2001; Wilcox et al. 2002).
All of the candidate ecological and trophic metric values evaluated for the current
study were expected to decrease in response to environmental degradation, except for
herbivores (Table 2). Since carnivores are more sensitive to contaminants based on their
food resources, relatively high abundances and number of species of herbivores are
expected in degraded areas. Although the omnivore metric values were not evaluated
because it was found to be redundant with the carnivore and herbivore metrics, it was
also expected to increase because omnivorous fish are less sensitive to degraded
conditions. Likewise, values of the pelagic metric were expected to increase in degraded
conditions because pelagic fish are less sensitive than benthic fish. The pelagic fish
metric was also excluded in statistical analyses because it correlated completely with the
benthic fish metric after fish were categorized as being either pelagic or benthic.
Tolerance metrics
An organisms’ tolerance to stress has often been included as a metric in indices
for freshwater quality (e.g., Karr 1981; Karr et al. 1986; Fausch et al. 1984; Angermeier
- 16 -
and Karr 1986; Leonard and Orth 1986; Miller et al. 1988; Schleiger 2000), but tolerance
remains a difficult metric to define when comparing across species in other ecological
systems, such as estuaries. Although standardized methods to determine the effects of
single and multiple stressors on different species are not well established, information on
physiological functions, growth, and survival after exposure to stressor(s) is available. A
review of literature provided supplemental information on South Carolina tidal creek fish
species and was used in the current to compile metrics describing fish tolerance.
The ability of fish to be independent of salinity may allow for greater
opportunities to exploit areas from which salinity dependent fish are restricted.
Weinstein (1979) studied fish tolerance in shallow marsh habitats and tidal creeks in
North Carolina and found that certain species were distributed independently of salinity.
Weinstein (1979) categorized dominant fishes found in North Carolina tidal creeks, seven
of which were found in South Carolina tidal creeks. Out of the seven South Carolina
species that Weinstein (1979) studied, six were defined as “salinity independent” and one
was defined as “salinity dependent” (Appendix D.3). Fish found in tidal creeks that
Weinstein (1979) did not study or had termed as salinity dependent were categorized in
the current study as “not salinity independent.” For the current study, the number of
salinity independent fish was not expected to be significantly different among stations
because of an a priori adjustment of sampled stations due to salinity (stations with
salinities less than 18 ppt were not included in analyses). Salinity independent fish was
still included as a candidate metric that would increase in value with lowered
environmental quality because intrinsic physiological and behavioral differences in
- 17 -
salinity independent taxa may result in advantages for tolerating the stress of
environmental degradation (Table 2).
Another tolerance metric, resilient fish, was derived from a review by Musick
(1999) on the capacity of certain marine animals (fish, turtles, birds, whales) to withstand
exploitation. Musick (1999) suggested that animals with low intrinsic rates of increase
(r) and low growth coefficients (k) were less resilient. Marine animals that had known
growth rates (k) were categorized by Musick (1999) as having high, medium, low, or no
resilience. Twenty-three fishes found in South Carolina tidal creeks belonged to families
categorized by Musick (1999). In the current study, twenty-one fish species were defined
as being “resilient” (having high or medium resilience), and two fish species were
defined as being “not resilient” (having low or no resilience; Appendix D.3; Musick
1999; Froese and Pauly 2000). As a conservative approach, fish that were defined as
“not resilient” also included any fish not included in that Musick’s (1999) study. The
resilient metric profiled tidal creek fishes by identifying fish that are highly resilient to
fishing pressure and, therefore, might be expected to be capable of withstanding the stress
of environmental conditions (Table 2).
Additional candidate tolerance metrics included flatfish (fishes that belong to the
Bothidae, Cynoglossidae, or Soleidae families) and flounders (recreationally important
flatfish) because they incorporate life history, ecology and trophic behaviors that make
them sensitive to pollution. The abundances of flatfish and flounders have been used as
indicators of environmental quality in a variety of studies (e.g., Murchelano and Wolke
1985; Nelson et al. 1991a; Sindermann 1994; Araujo et al. 2000; Meng et al. 2001, Meng
et al. 2002). High concentrations of contaminants in the sediment impair reproduction
- 18 -
and suppress the immune systems of many flatfish, leading to increased incidence of
disease and decreased abundances (Pulsford 1995; Johnson et al. 1998). Flounders not
only have relatively high rates of contaminant uptake (Rogers et al. 1992), but are also
subject to added fishing pressure due to their status as recreationally important species.
The potential of flounders to be overfished increases the population’s vulnerability to
pollution (Sindermann 1996). Therefore, the flounder and flatfish metric values were
expected to decrease with degraded environmental quality (Table 2).
The life history, ecology and trophic behaviors of fish in the family Sciaenidae
make them sensitive to pollution and habitat degradation, and therefore they were
included as a candidate tolerance metric for evaluation. Most juvenile sciaenids are
dependent on tidal creeks as critical habitats after migrating from offshore areas.
Sciaenid presence within an estuary may indicate that a habitat is in good condition, since
they are commonly found in zones with high dissolved oxygen (>10 mg/L; Gelwick et al.
2001). Guillen (2000) suggested that high numbers of sciaenids, in an index of biotic
integrity developed for the Galveston Bay, indicated excellent habitat condition. Values
for the sciaenid metric were expected to decrease with environmental degradation (Table
2).
Bay anchovy and shad were also included as tolerance metrics. These species
have lower rates of contaminant bioaccumulation and biomagnification because they are
filter feeders that consume short-lived planktonic prey at the bottom of the food chain.
Bechtel and Copeland (1970) found that bay anchovy dominance was related to
anthropogenic stress in the Galveston Bay. Thompson and Fitzhugh (1986) and Guillen
(2000) have recommended the use of high abundances of bay anchovy as an indication of
- 19 -
degradation in an index of biotic integrity for Galveston Bay. Guillen (2000) also has
recommended the use of shad as an alternative metric when bay anchovies are not
present. For the current study, bay anchovy (Anchoa mitchilli) and shad (Alosa
sapidissima and Dorosoma sp.) were evaluated as candidate tolerance metrics because
they are relatively insensitive to environmental degradation and are expected to be
present in high numbers in degraded conditions (Table 2).
Community structure metrics
Community structure metrics that describe species composition have been
historically used as individual tools to assess environmental quality (Gray 2000).
Although many studies have cautioned against the use of an individual community
structure metric as the only indicator of environmental quality (e.g., Livingston 1976;
Angermeier and Schlosser 1987; Fausch et al. 1990; Van Dolah et al. 1999), community
structure metrics have been useful when studied in conjunction with other metrics
describing the fish community, life history, ecological, trophic, and/or tolerance (see
Deegan et al. 1993, 1997; Meng et al. 2002). Decreased water quality of estuaries has
been found to correspond to decreased fish species diversity, richness, and evenness (e.g.,
Bechtel and Copeland 1970; Gray 1989; Tzeng and Wang 1992; Scott and Hall 1997).
Deegan et al. (1993, 1997) observed an increase in the number of species, the abundance
of fish, and dominance with increased habitat quality and successfully incorporated these
metrics into an index of biotic integrity for estuaries in Massachusetts. Meng et al.
(2002) also observed that overall abundance and species diversity, along with other fish
metrics, were useful in determining differences in habitat quality. The density of
- 20 -
individuals, number of taxa, dominance, number of taxa that composed 90% of the total
abundance, number of taxa that composed 95% of the total abundance, species richness,
species evenness, and species diversity were included in the current study as candidate
community metrics.
All of the candidate community structure metric values evaluated for the current
study were expected to decrease in response to environmental degradation, except for the
metrics describing dominance (Table 2). In the current study, the dominance value
explains the percent of the total abundance that is composed of the most abundant fish
taxon or taxa. High dominance values, or low variety of fish taxa, may be a result of
degraded conditions if tolerant fish are highly abundant and more sensitive fish are not
present. Therefore, an increase in the dominance value is expected in response to
environmental degradation (Table 2).
Determining environmental quality
Water quality
Six parameters were used to determine water quality in this study, including
dissolved oxygen, biological oxygen demand, fecal coliform bacteria concentration, total
nitrogen, total phosphorus, and pH. At each station, average levels of dissolved oxygen,
biological oxygen demand, fecal coliform bacteria, total nitrogen, and phosphorus were
scored: 1=poor, either exceeded state water quality standards or the 90th percentile of
SCDHEC’s historical database, 3=marginal, either exceeded an intermediate water
quality standard or the 75th percentile of SCDHEC’s historical database, and 5=good,
either did not exceed state water quality standards or the 75th percentile of SCDHEC’s
- 21 -
historical database (Table 1; Appendix F; SCDHEC 1998a, 2001). Average values for
pH were scored similarly, but good and marginal criteria were determined with pH values
measured for SCECAP in polyhaline (18-30 ppt) and euhaline (>25 ppt) tidal creeks and
open water estuarine stations during 1999-2000, instead of SCDHEC’s historical
database (Van Dolah et al. 2002). Criteria for poor pH values were determined by using
the SCDHEC standard for degraded pH conditions in polyhaline waters (Table 1; Van
Dolah et al. 2002). It should be noted that the SCDHEC historical database on water
quality was primarily obtained from larger open water bodies and these values were used
because, to date, no criteria specific to tidal creeks exist.
After scoring the six water quality parameters, average water quality scores were
calculated for each station, using a procedure similar to that described by Van Dolah et
al. (2002). Missing data were regarded as blank values and overall water quality was
averaged with the number of parameters available. Raw averages were adjusted with the
same criteria that were used to adjust overall average quality (see Table 1), as discussed
later in this section, to facilitate comparisons between water, sediment, and upland
quality: 1=poor, 3=marginal, and 5=good (Appendix F). However, raw averages were
ultimately used to calculate overall environmental quality averages, not adjusted scores
because an adjustment process was used in the final calculation of overall environmental
quality
Sediment quality
The Effects Range Median – Quotient (ERM-Q) score was the only sediment
quality parameter used to define sediment quality in this study. The ERM-Q score
- 22 -
represented the overall contaminant exposure of trace metals and organic compounds in
the sediment (Hyland et al. 1999), and was calculated by dividing the measured
concentrations of 24 contaminants by their Effects Range-Median (ER-M) value (i.e.,
caused adverse effects in more than 50% of the studies; Long et al. 1995). The ERM-Q
values were scored: 1=poor or high risk of observing degraded benthic communities,
3=marginal or moderate risk of observing degraded benthic communities, and 5=good or
low risk of observing degraded benthic communities (Table 1; Appendix G; Hyland et al.
1999; Van Dolah et al. 2002).
Upland quality
Land use and land cover data of the area surrounding each station were obtained
from NWI 1989 and 1994 databases, categorized using the Anderson classification
system (Anderson et al. 1976; US Fish and Wildlife 1989, 1994; ESRI 1998). To date,
there is no standardized method that describes significant effects on environmental
quality based on the amount of physically altered land, although impervious surface has
been shown to be a useful tool (e.g., Karr and Chu 1999; Holland et al. 1997; Lerberg et
al. 2000; Elvidge et al. 2004; Holland et al. 2004). For this study, physically altered land
was defined as land categorized as residential or cropland/pasture (agricultural) within a
100 m buffer zone of the station. Residential and agricultural areas are usually associated
with increased amounts of surface water runoff and are sources of contaminants that
include chemicals and high amounts of nitrogen and phosphorus. The presence of urban
and industrial areas within a 500 m buffer zone of each station was also quantified, but
found to be rare. Therefore, urban and industrial areas were not investigated in the
- 23 -
current study. Some stations that were sampled for SCECAP could not be analyzed for
land use and land cover because they were located in creeks that were not well-defined in
the NWI database, or located in creeks that were not at least 1,000 m in length (1999,
n=2; 2000, n=2; 2001, n=5; 2002, n=3). Stations where land use and land cover could
not be quantified were eliminated from further analyses.
The percent of upland that was categorized as residential or agricultural was
calculated for each station (ESRI 1998). However, this percentage indicated low levels
of physical alteration from residential or agricultural development (average=2%).
Therefore, the presence/absence of physical alteration (i.e., residential or agricultural
development) within a 100 m buffer zone was used to determine upland quality. Final
upland quality was scored: 2=marginal-poor, presence of physical alteration, and 5=good,
no physical alteration).
Overall environmental quality
For stations sampled in 1999-2001, the effects of individual and average scores
from combined water, sediment, and upland quality parameters on the fish community
were compared. Comparisons were made in an effort to eliminate the environmental
parameters that had little to no effect on the fish community from being incorporated into
the final calculation of overall environmental quality. Individual environmental
parameters that showed the greatest amount of variability in the fish community
(quantified as the number of fish metrics with significant differences among poor,
marginal, and good stations) included pH, dissolved oxygen, and physical alteration
(Kruskal-Wallis test, Dunn-Sidak test, k=73, p<0.0007). None of the environmental
- 24 -
parameters was able to distinguish significant differences for every fish metric tested
when used individually. A number of combinations and subsets of water, sediment, and
upland parameters were used to classify stations as good, marginal, or poor based on the
average scores of water, sediment, and upland quality. Most combinations did not
classify any station as poor and most of the combinations classified the majority of
stations as good.
Based on these analyses, environmental quality was defined to include parameters
that reflect anthropogenic stress and were essentially associated with environmental
habitat important to biological communities, including fish. The overall environmental
quality of stations was equally dependent on water, sediment, and upland quality,
determined by the overall average of the water quality score, the sediment quality score,
and the upland quality score (Table 1; Appendix G). Raw overall averages were
adjusted: <2.334=poor, 2.334 - <3.667=marginal, and ≥3.667=good (Table 1).
The environmental quality of 97 tidal creek stations sampled in 1999-2002 was
evaluated. Eighty-seven stations were classified as good, nine were marginal, and one
station was classified as poor. Since only one station was classified as poor, efforts were
focused on developing an estuarine biotic integrity index (EBI) that could distinguish
between the good and marginal stations.
Physical features
Additional features were examined for all stations using GIS coverages to
determine if physical habitat characteristics were similar among tidal creeks (Appendix
B; ESRI 1998; Hay 2001; Jutte et al. 2004). Using a hydrography DLG (USGS 1994),
- 25 -
the average width of the tidal creek was calculated by averaging the distance of five lines
drawn perpendicular to the banks of the creek that intersected points located: 1) at the
station, 2) 250 m upstream of the station, 3) 250 m downstream of the station, 4) 500 m
upstream of the station, and 5) 500 m downstream of the station. The width to depth
(W/D) ratio was calculated by dividing the average width of the tidal creek by the
average depth that was collected on site, at each station, with a depth finder. Sinuosity,
or the bending and curving path of the tidal creek, was calculated by measuring the
distance of a straight line that connected a point located 500 m upstream with a point
located 500 m downstream. Shorter distances between the two points indicated high
levels of sinuosity, or curviness. The number of rivulets, or small streams draining into
the tidal creek, was quantified within a 500 m buffer zone of the station by using digital
orthophoto quarter-quadrangle (DOQQ) images for each station (USGS 1994, 1999).
Stations that were contained in the same creek were also compared with regards to
relative location within the creek (upstream or downstream), overall environmental
quality, and fish community composition.
Development of the estuarine biotic integrity (EBI) index
The selection of a subset of metrics to develop candidate EBI indices was the
second step to developing and evaluating an EBI index (Figure 2). Five approaches were
used to select fish metrics: 1) one-way analysis, 2) stepwise discriminant analysis, 3)
metrics selected by previous studies, 4) metrics selected by a composite of approaches,
and 5) individual metrics historically used as indicators of environmental quality.
- 26 -
One-way analyses
The first of three approaches used for the development of the EBI index used one-
way analyses to evaluate which set of the 73 candidate metrics that described the fish
community by fish density, percent of fish, and number of taxa that most strongly
distinguished between good and marginal environmental quality (SAS Institute 2002a;
Appendices E.1-4). One-way analyses, such as analysis of variance (ANOVA), t-test,
and Wilcoxon test, have been used successfully in other similar studies to select metrics
for developing indices of biotic integrity (e.g., Deegan et al. 1993, 1997; Scott and Hall
1997; Schubauer-Berigan et al. 2000). In the current study, EBI indices developed with
metrics selected by one-way analyses were designated with an “A” prefix (i.e., EBI index
Ax).
Although stations were sampled independently, fish community data were not
normally distributed (Shapiro-Wilkes test, p<0.05). Therefore, the Wilcoxon test, a
nonparametric one-way analysis that ranks variables and compares the medians of groups
to determine if there are significant differences, was used. Since multiple one-way
comparisons did not account for additive errors, it was necessary to adjust the critical
value (α) to reduce the probability of committing a Type I error. The Dunn-Sidak test
was used to adjust the significance level (critical α'=1 – [1 - α] 1/k, where k=the number
of independent significance tests; Sokal and Rohlf 1995).
Stepwise discriminant analyses
Stepwise discriminant analysis was the second approach used to select metrics
that were strong indicators of environmental quality (SAS Institute 2002b). A subset of
- 27 -
50 candidate metrics that described the fish community based on the density of
individuals and the number of taxa was included (Appendices E.1-4). Metrics based on
percent abundance were not found to be strong discriminators for environmental quality
after results from the one-way analyses and were eliminated from subsequent
discriminant analyses to avoid collinearity of the variables. The metrics describing shad
(Alosa sapidissima and Dorosoma sp.) density and the number of shad taxa were also
eliminated to avoid collinearity. In the current study, EBI indices developed with metrics
selected by stepwise discriminant analyses were designated with a “B” prefix (i.e., EBI
index Bx).
Stepwise discriminant analysis accounted for multiple comparisons of variables
that were dependent, redundant, and/or highly correlated (Khattree and Naik 2000).
Since fish metrics were not distributed normally (Shapiro-Wilkes test, p<0.05) and
covariance matrices were not equal between good and marginal stations (Bartlett’s
correction, χ2=24.95, p=0.05), results from stepwise discriminant analyses were regarded
with caution. Forward selection chose variables one at a time using squared partial
correlations, the Wilk’s lambda, and the partial F ratio; variables were selected for the
smallest lambda or the largest F, and the selection process ended when all of the
remaining variables did not meet the criteria (F-test=0.15; Klecka 1980; SAS Institute
2002b). For example, the first step selected the most discriminatory variable based on the
F-test criteria, and each additional step selected variables that were the best
discriminatory variable when combined with the already selected variable(s). It has been
cautioned that stepwise discriminant analysis does not always select for the best
combination of variables that can predict differences (Klecka 1980; Hawkins 1982).
- 28 -
However, every possible combination would have to be tried to select the optimum set of
variables and this is not always feasible when evaluating large numbers of variables.
Therefore, selection of variables from a stepwise discriminant analysis was considered to
be a good compromise worth investigating.
Previous studies
Indices and metrics suggested from previous estuarine studies (Deegan et al.
1993, 1997; Meng et al. 2002) were included to determine the transferability of biotic
integrity indices and metrics from other regions and biological systems. In this study,
metrics selected by Deegan et al. (1997), metrics selected by Meng et al. (2002), and all
metrics from both of these studies were used in the development and application of three
additional EBI indices. In the current study, EBI indices developed with metrics selected
by previous studies were designated with a “C” prefix (i.e., EBI index Cx).
Composite and single metric analyses
The methods of selecting metrics for inclusion in indices for composite and single
metric analyses were more subjective than the other approaches previously mentioned.
In order to determine if selecting metrics by using one approach (one-way analyses,
stepwise discriminant analyses, or previous studies) was better than using a combination
of the three approaches, composite indices were developed. Metrics that were predicted
as indicators of environmental quality, based on the expert knowledge of the local fish
community metrics, were included in composite indices. In the current study, eight
composite EBI indices, designated with a “D” prefix (i.e., EBI index Dx), included a
- 29 -
combination of metrics selected by one-way analyses, stepwise discriminant analyses,
previous studies, and ecological principles. In addition, community structure metrics
(density of individuals, number of taxa, species diversity) were selected for three single
metric EBI indices to determine if environmental quality could be predicted accurately by
using individual metrics. In the current study, individual EBI metrics were designated
with an “E” prefix and labeled as an index for consistency (i.e., EBI index Ex).
Application of the EBI index
At the initiation of this study, stations sampled in 1999-2001 for SCECAP were
planned for the development of an EBI index, while stations sampled in 2002 were set
aside for application and validation of the EBI index. However, when the EBI index was
not successfully validated after application to the original data set, combined data from
1999-2002 were used to develop the final EBI index.
The application of the metrics selected for 22 candidate EBI indices was the third
step to developing and evaluating an EBI index (Figure 2). All candidate EBI indices
were applied with two approaches: 1) median analysis and 2) discriminant analysis.
Median analyses
The median analysis used in this study followed the multimetric approach from
previously developed biotic indices (e.g., Van Dolah et al. 1999; Meng et al. 2002;
Weisberg et al. 1997). Stations with good environmental quality were set aside to be
analyzed (1999-2001, n=61; 2002, n=26; 1999-2002, n=87). The 50th percentile (median
value) of each selected metric for good stations was used as the critical value between
- 30 -
good and marginal environmental quality. If the fish metric’s average or median value
for good stations was lower than the average or median value for marginal stations, then a
score of 5 was given to each fish metric that was below the determined critical value,
while a score of 0 was given to each fish metric that was above the determined critical
value. If the fish metric’s average or median value for good stations was higher than the
average or median value for marginal stations, then a score of 5 was given to each fish
metric that was above the determined critical value, while a score of 0 was given to each
fish metric that was below the determined critical value. All metric scores were summed
for an EBI score and the maximum EBI score for each index was 5i, where i=the number
of metrics used for the index. Scores that were less than half of the maximum value
indicated marginal environmental quality while scores that were equal to or more than
half the maximum value indicated good environmental quality.
Indices that were developed with 1999-2001 data used the median value of each
fish metric as the critical value, and were based on 61 good stations. These critical values
were applied to three data sets: 1) 1999-2001 stations, 2) 2002 stations, and 3) 1999-2002
stations. Indices that were developed with the combined 1999-2002 data used the median
value of each fish metric as the critical value, based on 87 good stations, and were
applied only to the 1999-2002 data set.
Discriminant analyses
Discriminant analysis was the second approach used for the application of the
developed EBI indices. Assumptions of discriminant analyses included normality of
variables, homoscedasticity (equal covariance matrices), and non-collinearity of
- 31 -
variables. However, a nonparametric discriminant analysis was applied to circumvent
problems associated with violating these assumptions. When variables in an index were
collinear, a correlation matrix was examined and the most highly correlated variable was
not entered into the analysis. Preliminary tests included a multivariate analysis of
variance (MANOVA) to determine if there were differences in the selected metrics with
environmental quality and a Bartlett's modification of the likelihood ratio test to examine
the homogeneity of the within-group covariance matrices (Morrison 1976; Anderson
1984; SAS Institute 2000b). Although the MANOVA was relatively robust with
variables that were not normal if the sample size was large (>20 for each category;
Mertler and Vannatta 2002), sample sizes were unequal and the sample size for marginal
stations was small (1999-2001, n=8; 1999-2002, n=9). Furthermore, the Bartlett’s test
was not robust to deviations from normality (Khattree and Naik 2000). Therefore, results
from the MANOVA and Bartlett’s test were regarded with caution. When the Bartlett’s
test did not show a significant difference (p>0.10) between covariance matrices, the
matrices were pooled for classification and a linear discriminant analysis was used
(Morrison 1976; SAS Institute 2000b). When the Chi-square test showed a significant
difference (p<0.10) between covariance matrices, the individual within-group covariance
matrices were used for classification and a quadratic discriminant analysis was used
(Morrison 1976; SAS Institute 2000b). Nonparametric discriminant analysis used the
kernel method to transform nonparametric data with a kernel function and a smoothing
parameter (radius; Simonoff 1996; Khatree and Naik 2000). Since there was no
universally accepted standard kernel function or smoothing parameter available (Hawkins
1982; Khatree and Naik 2000), five kernel functions (uniform, normal, Epanechnikov,
- 32 -
biweight, triweight) and all possible smoothing parameters (1-10) were considered (SAS
2000b). A final standard kernel and smoothing parameter (normal and 1, respectively)
were chosen for comparison because these standards were applicable and feasible for all
indices and minimized the overall mean squared error.
Discriminant analysis used the Fisher’s approach of generalized square distances
to determine discriminant functions and estimated error rates by cross-validation (Khatree
and Naik 2000). Cross-validation (leave-one-out procedure) was used to decrease the
misclassification rate by minimizing the predicted residual sum of squares (Lachenbruch
1967; Lachenbruch and Mickey 1968; SAS Institute 2000b). Cross-validation was
similar to the jackknife and bootstrap procedures, where observations were left out one at
a time and fitted to the model until all observations were left out. The resulting error
rates were calculated using all models to combine into a larger sample size (Chernick
1999).
Indices that were developed using 1999-2001 data were applied to two data sets:
1) 1999-2001 stations, and 2) 1999-2002 stations. A discriminant analysis was not
applicable for a data set limited to 2002 stations because there was only one marginal
station found (degree of freedom was less than one). Indices that were developed using
the combined 1999-2002 data were applied only to the 1999-2002 data set.
Evaluation and selection of the EBI index
Evaluation and selection of the final EBI index were the last two steps to
developing and evaluating an EBI index (Figure 2). After the median and discriminant
analyses were used to classify stations, the EBI indices that had the lowest
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misclassification rate for good, marginal, and all stations were evaluated as candidates for
the final EBI index. For each of the selected EBI indices, fish metrics were scored 5 or 0,
using the same values and criteria established by the multimetric median analysis. EBI
scores were calculated by averaging fish metric scores for each index. EBI scores for all
stations were then plotted to determine if a new criteria, other than medians, was needed
to predict environmental quality of stations (good vs. marginal). New criteria, or
threshold values, were established based on EBI score ranges that could determine
environmental quality with low rates of error. The final EBI index was selected based on
its ability to predict environmental quality without error, using the new criteria and the
EBI score.
Stations with excellent environmental quality
Stations sampled in 1999-2002 where all water, sediment, and upland quality
parameters scored as good were analyzed a posteriori and categorized as excellent
stations. Average values of environmental parameters and physical features were
compared between stations classified as good and excellent. Stations predicted to have
good environmental quality by the EBI index were also compared to excellent stations.
Finally, the median (50th percentile) value for all excellent stations was calculated for
select fish metrics to determine conservative critical values that indicate high
environmental quality in South Carolina tidal creeks.
RESULTS
Environmental quality and physical features
Average values for water and upland quality parameters were comparable
between marginal stations and the one station that was classified as poor (NT02301).
Exceptions included a higher average fecal coliform bacteria concentration and ERM-Q
value (1600 col/100mL and 0.1113, respectively) at NT02301 when compared to the
maximum value observed at marginal stations (Appendix A). Since NT02301 was the
only station classified as poor, a criterion could not be established for poor stations.
Therefore, NT02301 was eliminated from all further statistical analyses.
For the 96 good and marginal stations in 1999-2002, overall average values for
individual water quality parameters were high for pH (7.54) and dissolved oxygen (4.31
mg/L), while biological oxygen demand (1.28 mg/L), total nitrogen (0.615 mg/L), total
phosphorus (0.0888 mg/L), and fecal coliform bacteria concentration (32.4 col/100 mL)
were low when compared to the criteria used for the current study (Table 1; Appendix A).
On average, all six water quality parameters for 1999-2002 were individually scored as
good (Appendix F). Using the adjusted average water quality score, 78 stations were
classified as good, 18 stations were marginal, and none was classified as poor. The
overall average water quality of South Carolina tidal creeks was good for stations
sampled in 1999-2001, 2002, and for the combined 1999-2002 data (Appendix F). It
- 35 -
should be noted that adjusted scores were not used to calculate overall environmental
quality and were presented here to facilitate comparisons among sediment and upland
quality.
The average sediment contaminant level was low (Effects Range-Median
Quotient [ERM-Q] score=0.0130) when compared to the criteria used for the current
study (Table 1; Hyland et al. 1999), and there were no missing ERM-Q values for the 96
good and marginal stations sampled in 1999-2002 (Appendix A). The overall average
sediment quality of South Carolina tidal creek stations sampled in 1999-2002 was good,
based on the ERM-Q score. Seventy-seven stations classified as good, 19 stations
classified as marginal, and no stations classified as poor (Appendix G).
The average percent of land that was physically altered was very low (2%) at
good and marginal stations sampled in 1999-2002 when compared to the criteria
developed for the current study, and there were no missing upland quality values (Table
1; Appendix A). The overall average upland quality of South Carolina tidal creek
stations sampled in 1999-2002 was good, based on the presence/absence of physical
alteration within a 100 m buffer zone. Seventy-four stations were classified as good and
22 stations were not good (Appendix G).
Using the overall environmental criteria developed for this study (Table 1), 91%
of stations sampled in 1999-2002 were classified as good (Appendix G). For stations
sampled in 1999-2001, 61 stations were classified as good, eight stations were classified
as marginal, and none were classified as poor. For stations sampled in 2002, 26 stations
were classified as good, one station was classified as marginal, and one station was
classified as poor.
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The ranges, maximum, minimum, and average values for physical features
(temperature, salinity, width, depth, width/depth ratio, sinuosity, rivulets) measured at all
stations sampled in 1999-2002, reflected highly dynamic environments characteristic of
tidal creeks and estuaries (Appendix B). The number of rivulets for one station
(RT02160) was the only physical feature that was unattainable and was regarded as
blank. RT02160 was located in an area surrounded by mudflats and the number of
rivulets was difficult to assess from aerial photographs and the National Wetland
Inventory database.
Stations were initially split into two data sets as stations sampled in 1999-2001 for
development and 2002 for application purposes. Data were also analyzed using all
stations sampled in 1999-2002 (Table 3). There was no significant difference in good
and marginal stations sampled in 1999-2001, 2002, or in 1999-2002 with respect to all
water quality, sediment quality, or most physical features (Wilcoxon test, Dunn-Sidak
test, k=19, p>0.0027). For the 1999-2001 and 1999-2002 data sets, marginal stations
were more shallow than good stations (Wilcoxon test, Dunn-Sidak test, k=19, p<0.0027).
For the 1999-2001, 2002, and 1999-2002 data sets, there was a higher percentage of
physically altered land at marginal stations than at good stations (Wilcoxon test, Dunn-
Sidak test, k=19, p<0.0027).
When all 96 good and marginal stations were analyzed geographically, nine
creeks contained more than one station. Each of the nine creeks contained two stations
that were within 2.5 km of each other, and the 18 stations were identified as being located
either upstream or downstream in relation to each other (Appendix B). Seven creeks
contained two stations that were both classified as good while two creeks contained one
- 37 -
station that was classified as good and the other as marginal. For all nine pairs of
stations, none of the 73 candidate fish metrics were significantly different between the
station located upstream and the stations located downstream (Wilcoxon test, Dunn Sidak
test, p>0.0014).
The two creeks that contained two stations differing in environmental quality
were located in the Kiawah River (RT00542 and RT99004; Figure 3a) and May River
(MR1-01-T and RT01602; Figure 3b). Although the small sample size may not allow
statistical tests to detect differences because of a lack of power, preliminary comparisons
between marginal and good stations were included (Table 4). The marginal stations had
slightly lower numbers for pH, dissolved oxygen, ERM-Q values, salinity, width, depth,
width/depth ratio, sinuosity, and rivulets. On the other hand, marginal stations had
slightly higher numbers for biological oxygen demand and sinuosity when compared to
good stations. However, for each pair of good and marginal stations, none of the water
quality, sediment quality, and physical features were significantly different between good
and marginal stations (analysis of variance [ANOVA], p>0.05; SAS Institute 2002a).
More obvious differences between good and marginal stations located in the
Kiawah and May Rivers were with respect to the year of sampling, location of the station
within the tidal creek (upstream or downstream), and upland quality. For both pairs, the
good station was sampled the year before the marginal station, located downstream, and
the upland was not physically altered within a 100 m buffer (Figure 3; Table 4). The
marginal station was sampled a year later, located upstream, and the upland was
physically altered (Figure 3; Table 4). However, when the percent of physically altered
- 38 -
land within the total 100 m buffer area was compared between the paired marginal and
good stations, there was no significant difference (ANOVA, p>0.10).
Fish community
A total of 53 fish taxa were collected at the 96 tidal creek stations sampled from
1999-2002 (Appendix C). The five most common species were spot (Leiostomus
xanthurus), silver perch (Bairdiella chrysoura), pinfish (Lagodon rhomboides), bay
anchovy (Anchoa mitchilli), and hogchoker (Trinectes maculates). These species
comprised 79% of the total abundance sampled for the current study, with spot
contributing to 24% of the total abundance, silver perch contributing 22%, and smaller
percentages of pinfish (14%), bay anchovy (14%), and hogchoker (4%). No fish were
found to have gross pathologies, deformities, or external parasites.
For good and marginal stations, 60 fish species were profiled with seven life
history metrics, eight ecological and trophic metrics, and seven tolerance metrics
(Appendices D.1-5). Fish that were identified to taxonomic categories above the species
level included Blennidae, Citharichthys sp., Eucinostomus sp., and Menticirrhus sp. Fish
species that were within these higher taxonomic categories that were likely to be present
in tidal creek habitats were also profiled (n=7).
Preliminary comparisons showed that most (n=46) of the average and/or median
fish metric values were higher for marginal stations when compared to good stations
(Tables 2 and 5; Appendices E.1-4). Exceptions to this trend included several metrics
based on the percent abundances of fish (bay anchovy, benthic fish, benthic feeder,
detritivore, estuarine nursery fish, estuarine spawner, flatfish, flounder, herbivore, shad,
- 39 -
and the sum of bay anchovy and shad), density of fish (flatfish, flounder, herbivore, and
shad), and number of taxa (flatfish, flounder, herbivore, and shad). In addition, the
average and/or median values of species evenness and the three metrics describing
dominance at good stations were equal to or higher than values at marginal stations.
Average values that were higher at good stations than at marginal stations were
most often reflected in metrics that were based on the percent abundance of fish.
However, metric values that were based on percent abundances were not significantly
different between marginal and good stations (Wilcoxon test, Dunn-Sidak test, k=19,
p<0.0027). Metrics based on the number of taxa and density of fish showed greater
differences between good and marginal stations (Wilcoxon test, Dunn-Sidak test, k=19,
p<0.0027). Therefore, trends observed for the current study were generalized based on
the density and number of taxa of fish (Table 2).
Most fish collected at good and marginal stations for the current study utilized the
estuary (97% of fish) and tidal creeks (88% of fish) for nursery grounds and/or were
estuarine dependent (81% of fish; Appendix E.1). Many of the fish were also transient
(59% of fish) and spawned offshore or nearshore (50% of fish; Appendix E.1). The
majority of the fish identified were benthic (76% of fish), benthic feeders (83% of fish),
detritivores (81% of fish), and/or carnivores that fed on invertebrates (69% of fish;
Appendix E.2).
Several metrics did not have heavy representation among the fish collected at
good and marginal stations. Only 31% of the fish community were top predators
(piscivores), with relatively few omnivores (14%) or herbivores (<1%) collected
(Appendix E.2). Small percentages of the various taxonomic metrics were found at good
- 40 -
and marginal stations, such as bay anchovy (15%), shad (<1%), flounder (<1%), and
flatfish (8%; Appendix E.3).
The resilient and salinity independent metrics described only 43% and 47%,
respectively, of the fish community at good and marginal stations (Appendix E.3).
Although the resilient and salinity independent metrics are not ideal reflections of the fish
community due to their inability to definitively categorize many fish, these studies were
considered to gain insight on possible differences in the fish community that may vary
with environmental quality.
Development of the estuarine biotic integrity (EBI) index
One-way analyses
For stations sampled in 1999-2001, nine of the 73 candidate metrics were
significantly different between good and marginal stations (Wilcoxon test, Dunn-Sidak
test, k=73, α=0.10, p<0.0014; Figure 4). The nine metrics described fish life history
(estuarine nursery taxa, tidal creek nursery taxa, tidal creek resident taxa), trophic level
(carnivorous taxa, top predator taxa), tolerance (salinity independent taxa, highly resilient
taxa), and community structure (number of taxa, species richness). All of these nine
metrics were used to develop EBI index A1 (Table 6 and 7). After adjusting to a stricter
critical value (α=0.05; p<0.0007), a subset of the nine metrics were significantly different
between marginal and good stations. This subset included six metrics (carnivorous taxa,
estuarine nursery taxa, number of taxa, salinity independent taxa, tidal creek nursery taxa,
and top predator taxa) that were used to develop EBI index A2 (Tables 6 and 7).
- 41 -
For stations sampled in 1999-2002, the top predator taxa metric was the only
metric significantly different between good and marginal stations based on a conservative
(α=0.10) or strict (α=0.05) criteria (Wilcoxon test, Dunn Sidak test, χ2=11.3900,
p=0.0002). Although it is a single metric, the number of top predator taxa was designated
as EBI index A3 for consistency (Table 6).
Stepwise discriminant analyses
For stations sampled in 1999-2001, five of the 50 candidate metrics were selected
(forward stepwise discriminant analysis, p<0.15) describing fish trophic level (top
predator taxa), life history (tidal creek nursery taxa), tolerance (flatfish density), and
community structure (number of taxa that composed 90% of the total abundance,
dominance of the most abundant taxon). All five of the metrics that were selected
accounted for 46% of the total variation and were used to develop EBI index B1 (Tables 6
and 8). After adjusting to a stricter critical value (p<0.10), a subset of three of the five
metrics were significant discriminators, including flatfish density, number of taxa that
composed 90% of the total abundance, and dominance of the most abundant taxon. This
subset of three metrics accounted for 40% of the total variation and was used to develop
EBI index B2 (Tables 6 and 8).
For stations sampled in 1999-2002, seven of the 50 metrics were selected
(forward stepwise discriminant analysis, p<0.15) describing fish trophic level (top
predator taxa, detritivore density), life history (tidal creek nursery density, estuarine
dependent density), tolerance (flatfish density, salinity independent taxa), and community
structure (dominance of the most abundant taxon). All of the seven metrics that were
- 42 -
selected accounted for 29% of the total variation and were used to develop EBI index B3
(Tables 6 and 9). After adjusting to a stricter critical value (p<0.10), a subset of four of
the seven metrics were significant discriminators, including estuarine dependent density,
salinity independent taxa, tidal creek nursery density, and top predator taxa. This subset
of four metrics accounted for 22% of the total variation and was used to develop EBI
index B4 (Tables 6 and 9). After a final adjustment of the critical value (p<0.05), a subset
of three of the four metrics remained as significant discriminators, excluding tidal creek
nursery density. This subset of three metrics accounted for 19% of the total variation and
was used to develop EBI index B5 (Tables 6 and 9).
Previous studies
A total of nine fish metrics that were used in previous estuarine biotic integrity
indices (Deegan et al. 1993, 1997; Meng et al. 2002) were transferable to the current
study (Table 10). These metrics were used to develop three EBI indices applicable to the
South Carolina tidal creek fish found in the current study.
Deegan et al. (1993, 1997) successfully developed an estuarine biotic integrity
index (EBI) for estuaries near Massachusetts using metrics describing fish ecology
(proportion of benthic fishes), life history (number of estuarine nursery species, number
of estuarine spawning species, number of resident species), tolerance (proportion of
abnormal or diseased fishes), and community structure (number of species, dominance,
abundance) Since the current study did not find any abnormal or diseased fishes, this
metric was not examined. The seven remaining metrics selected by Deegan et al. (1993,
1997) were used to develop EBI index C1 (Tables 6 and 10).
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Meng et al. (2002) developed an estuarine index of biotic integrity for the
Narragansett Bay using metrics describing fish ecology (proportion of benthic species),
life history (number of estuarine spawning species), tolerance (proportion of killifish,
proportion of flounder), and community structure (abundance, species diversity [H']).
Since the current study did not find any killifish, this metric was not examined. The five
remaining metrics selected by Meng et al. (2002) were used to develop EBI index C2
(Tables 6 and 10).
Finally, all nine metrics that have been selected and used successfully in other
indices for estuarine fish communities (Deegan et al. 1993, 1997; Meng et al. 2002) were
considered together. The nine metrics selected by either Deegan et al. (1993, 1997) or
Meng et al. (2002) were used to develop EBI index C3 (Tables 6 and 10).
Composite and single metric analyses
Eight composite indices were developed using a combination of results from the
one-way and stepwise discriminant analyses, previous studies, and the knowledge and
opinions of local fish scientists. For EBI index D1-5, metrics were included after
considering the number of times a metric was selected by one of the three analyses used
in the current study, the units of the metric (i.e., density of individuals, number of taxa, or
percent of individuals), and the aspect of the fish community the metric was describing.
Eight metrics that were selected more than twice for EBI indices A1-3, B1-5, and C1, 2 were
analyzed for five composite indices (Table 6). EBI indices D1-5 included the number of
top predator taxa, the number of tidal creek nursery taxa, and salinity independent taxa
because they were the three metrics that were selected most frequently by both the one-
- 44 -
way and stepwise discriminant analyses. Both the number of taxa and flatfish density
were metrics that were also included in EBI index D1-5 because the metrics were easy to
identify and calculate, had units that can be clearly interpreted, and have historically been
used to indicate differences in environmental quality. The number of estuarine nursery
taxa was not included in EBI indices D1-5 because it was redundant with the metric
already selected to describe the number of tidal creek nursery taxa. As a result of
eliminating redundant metrics and retaining metrics that had broad groupings (which
would simplify identification procedures for future studies), five “core” metrics were
included for EBI indices D1-5 that described fish life history, trophic composition,
tolerance, and community structure.
In addition to these five core metrics, one additional metric was added to each of
indices D2-4 in an effort to discern the relative contribution of the three additional metrics
that were also selected frequently by the one-way analyses, stepwise discriminant
analyses, or previous studies. Metrics describing the dominance of the most abundant
taxon, density of individuals, and estuarine dependent taxa were added to EBI indices D2-
4, respectively (Table 6).
All metrics included in EBI index D1 were included in EBI index D5, with the
exception of the metric describing the number of salinity independent taxa. The metric
describing salinity independent taxa, as discussed previously, was derived from a study
on North Carolina fish communities (Weinstein 1979), but not all fish taxa found in this
study were definitively profiled as independent or dependent of salinity. Therefore, this
metric was not included in EBI index D5 as a conservative measure to avoid
misrepresentation of the fish community.
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EBI index C3, produced by using metrics selected by Deegan et al. (1993, 1997)
or Meng et al. (2002), was modified slightly with closely related metrics for EBI indices
D6 and D7. EBI index D6 used the same metrics included in EBI index C3 with the
substitution of the density of flatfish for the density of flounder (Tables 6 and 12).
Another example of two closely related metrics was the number of taxa that composed
90% of the total abundance and the dominance of the most abundant taxon. EBI index
D7 included the metrics selected for EBI index C3 with the substitution of the number of
taxa that composed 90% of the total abundance for the dominance of the most abundant
taxon (Table 6).
EBI index D8 was the result of determining key metrics that were predicted to be
useful, based on ecological principles and previous studies using estuarine fish as
indicators of environmental condition (see Thompson and Fitzhugh 1986; Deegan et al.
1993, 1997; Guillen 2000; Meng et al. 2002). EBI index D8 included metrics that
described fish life history (tidal creek nursery taxa), trophic composition (top predator
taxa), tolerance (flatfish density), and community structure (density of individuals,
number of taxa that composed 90% of the total abundance; Table 6).
Three community structure metrics historically used as individual indicators of
environmental quality (the density of individuals, number of taxa, and species diversity)
were designated as EBI indices E1-3, respectively, for consistency (Table 6).
- 46 -
Application of the EBI index – Median analyses
EBI index Ax
Although EBI indices A1 and A2 were developed with different metrics (Table 6),
they had the same error rates when used to classify stations with the median analysis
(Figures 5-7). EBI index A1 had a maximum EBI score of 45, using the critical values
(Table 7) to score nine metrics as good (5) or marginal (0). For EBI index A1, stations
that scored above or equal to 22.5 were classified as good, and stations that scored below
22.5 were classified as marginal. EBI index A2 had a maximum EBI score of 30, using
the critical values (Table 7) to score six metrics as good (5) or marginal (0). For EBI
index A2, stations that scored above or equal to 15 were classified as good, and stations
that scored 15 or below were classified as marginal. For both EBI indices A1 and A2, 24
of the 69 (34.78%) stations sampled in 1999-2001 were incorrectly classified (Figure 5).
Twenty-four of the 61 (39.34%) good stations and none of the eight marginal stations
were misclassified (Figure 5). When applied to stations sampled in 2002, EBI indices A1
and A2 incorrectly classified 18 of the 27 (66.67%) stations (Figure 5). Seventeen of the
26 (65.38%) good stations and the only marginal station were misclassified. For stations
sampled in 1999-2002, EBI indices A1 and A2 incorrectly classified 42 of the 96
(43.75%) stations (Figure 6). Forty-one of the 87 (47.13%) good stations and one
marginal station were misclassified (Figure 7).
EBI index A3 scored stations sampled in 1999-2002 as good (5) or marginal (0) by
using the critical value for the number of top predator taxa (Table 7). EBI index A3
incorrectly classified 40 of the 96 (41.67%) stations (Figure 6). Forty of the 87 (45.98%)
good stations and none of the marginal stations were misclassified (Figure 7).
- 47 -
EBI index Bx
EBI index B1 had a maximum EBI score of 25, using the critical values (Table 8)
to score five metrics as good (5) or marginal (0). Stations that scored above or equal to
12.5 were classified as good, and stations that scored below 12.5 were classified as
marginal. EBI index B1 incorrectly classified 23 of the 69 (33.33%) stations sampled in
1999-2001 (Figure 5). Twenty-three of the 61 (37.70%) good stations and no marginal
stations were misclassified for stations sampled in 1999-2001. When applied to stations
sampled in 2002, EBI index B1 incorrectly classified 20 of the 27 (74.07%) stations
(Figure 5). Nineteen of the 26 (73.08%) good stations and the only marginal station were
misclassified. For stations sampled in 1999-2002, EBI index B1 incorrectly classified 43
of the 96 (44.79%) stations (Figure 6). Forty-two of the 87 (48.28%) good stations and
one of the nine (11.11%) marginal stations were misclassified (Figure 7).
EBI index B2 had a maximum EBI score of 15, using the critical values (Table 8)
to score three metrics as good (5) or marginal (0). Stations that scored above or equal to
7.5 were classified as good, and stations that scored below 7.5 were classified as
marginal. EBI index B2 incorrectly classified 24 of the 69 (34.78%) stations sampled in
1999-2001 (Figure 5). Twenty-four of the 61 (39.34%) good stations and no marginal
stations were misclassified. When applied to stations sampled in 2002, EBI index B2
incorrectly classified 19 of the 27 (70.37%) stations (Figure 5). Eighteen of the 26
(69.23%) good stations and the only marginal station were misclassified. For stations
sampled in 1999-2002, EBI index B2 incorrectly classified 43 of the 96 (44.79%) stations
- 48 -
(Figure 6). Forty-two of the 87 (48.28%) good stations and one of the nine (11.11%)
marginal stations were misclassified (Figure 7).
EBI index B3 had a maximum EBI score of 35, using the critical values (Table 9)
to score seven metrics as good (5) or marginal (0). Stations sampled in 1999-2002 that
scored above or equal to 17.5 were classified as good, and stations that scored below 17.5
were classified as marginal. EBI index B3 incorrectly classified 39 of the 96 (40.63%)
stations (Figure 6). Thirty-eight of the 87 (43.68%) good stations and one of the nine
(11.11%) marginal stations were misclassified (Figure 7).
EBI index B4 had a maximum EBI score of 20, using the critical values (Table 9)
to score four metrics as good (5) or marginal (0). Stations sampled in 1999-2002 that
scored above or equal to 10 were classified as good, and stations that scored below 10
were classified as marginal. EBI index B4 incorrectly classified 33 of the 96 (34.38%)
stations (Figure 6). Thirty-two of the 87 (36.78%) good stations and one of the nine
(11.11%) marginal stations were misclassified (Figure 7).
EBI index B5 had a maximum EBI score of 15, using the critical values (Table 9)
to score three metrics as good (5) or marginal (0). Stations sampled in 1999-2002 that
scored above or equal to 7.5 were classified as good, and stations that scored below 7.5
were classified as marginal. EBI index B5 incorrectly classified 34 of the 96 (35.42%)
stations (Figure 6). Thirty-four of the 87 (39.08%) good stations and one of the nine
(11.11%) marginal stations were misclassified (Figure 7).
- 49 -
EBI index Cx
EBI index C1 had a maximum EBI score of 35, using the critical values (Table 10)
to score seven metrics as good (5) or marginal (0). Stations sampled in 1999-2002 that
scored above or equal to 17.5 were classified as good, and stations that scored below 17.5
were classified as marginal. EBI index C1 incorrectly classified 39 of the 96 (40.63%)
stations (Figure 6). Thirty-eight of the 87 (43.68%) good stations and one of the nine
(11.11%) marginal stations were misclassified (Figure 7).
EBI index C2 had a maximum EBI score of 25, using the critical values (Table 10)
to score five metrics as good (5) or marginal (0). Stations sampled in 1999-2002 that
scored above or equal to 12.5 were classified as good, and stations that scored below 12.5
were classified as marginal. EBI index C2 incorrectly classified 32 of the 96 (33.33%)
stations (Figure 6). Thirty-one of the 87 (35.63%) good stations and one of the nine
(11.11%) marginal stations were misclassified (Figure 7).
EBI index C3 had a maximum EBI score of 45, using the critical values (Table 10)
to score nine metrics as good (5) or marginal (0). Stations that scored above or equal to
22.5 were classified as good, and stations that scored below 22.5 were classified as
marginal. EBI index C3 incorrectly classified 38 of the 96 (39.58%) stations (Figure 6).
Thirty-seven of the 87 (42.53%) good stations and one of the nine (11.11%) marginal
stations were misclassified (Figure 7).
EBI index Dx
Although EBI indices D1 and D6 included different metrics, they had the same
error rates when used to classify stations sampled in 1999-2002 with the median analysis.
- 50 -
EBI index D1 had a maximum EBI score of 25, using the critical values (Table 11) to
score 5 metrics as good (5) or marginal (0). For EBI index D1, stations that scored above
or equal to 12.5 were classified as good, and stations that scored below 12.5 were
classified as marginal. EBI index D6 had a maximum EBI score of 45, using the critical
values (Table 12) to score nine metrics as good (5) or marginal (0). For EBI index D6,
stations that scored above or equal to 22.5 were classified as good, and stations that
scored a 22.5 or below were classified as marginal. Both EBI indices D1 and D6
incorrectly classified 40 of the 96 (41.67%) stations (Figure 6). Thirty-nine of the 87
(44.83%) good stations and one of the nine (11.11%) marginal stations were misclassified
(Figure 7).
EBI index D2 had a maximum EBI score of 30, using the critical values (Table 11)
to score six metrics as good (5) or marginal (0). Stations sampled in 1999-2002 that
scored above or equal to 15 were classified as good, and stations that scored a 15 or
below were classified as marginal. EBI index D2 incorrectly classified 32 of the 96
(33.33%) stations (Figure 6). Thirty-one of the 87 (35.63%) good stations and one of the
nine (11.11%) marginal stations were misclassified (Figure 7).
EBI index D3 had a maximum EBI score of 30, using the critical values (Table
11) to score six metrics as good (5) or marginal (0). Stations sampled in 1999-2002 that
scored above or equal to 15 were classified as good, and stations that scored a 15 or
below were classified as marginal. EBI index D3 incorrectly classified 34 of the 96
(35.42%) stations (Figure 6). Thirty-three of the 87 (37.93%) good stations and one of
the nine (11.11%) marginal stations were misclassified (Figure 7).
- 51 -
EBI index D4 had a maximum EBI score of 30, using the critical values (Table
11) to score six metrics as good (5) or marginal (0). Stations sampled in 1999-2002 that
scored above or equal to 15 were classified as good, and stations that scored a 15 or
below were classified as marginal. EBI index D4 incorrectly classified 33 of the 96
(34.38%) stations (Figure 6). Thirty-two of the 87 (36.78%) good stations and one of the
nine (11.11%) marginal stations were misclassified (Figure 7).
EBI index D5 had a maximum EBI score of 20, using the critical values (Table 11)
to score four metrics as good (5) or marginal (0). For EBI index D5, stations that scored
above or equal to 10 were classified as good, and stations that scored a 10 or below were
classified as marginal. EBI index D5 incorrectly classified 36 of the 96 (37.50%) stations
(Figure 6). Thirty-five of the 87 (40.23%) good stations and one of the nine (11.11%)
marginal stations were misclassified (Figure 7).
EBI index D7 had a maximum EBI score of 45, using the critical values (Table
11) to score nine metrics as good (5) or marginal (0). Stations sampled in 1999-2002 that
scored above or equal to 22.5 were classified as good, and stations that scored a 22.5 or
below were classified as marginal. EBI index D7 incorrectly classified 42 of the 96
(43.75%) stations (Figure 6). Forty-one of the 87 (47.13%) good stations and one of the
nine (11.11%) marginal stations were misclassified (Figure 7).
EBI index D8 had a maximum EBI score of 25, using the critical values (Table 11)
to score five metrics as good (5) or marginal (0). Stations sampled in 1999-2002 that
scored above or equal to 12.5 were classified as good, and stations that scored a 12.5 or
below were classified as marginal. EBI index D8 incorrectly classified 44 of the 96
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(45.83%) stations (Figure 6). Forty-three of the 87 (49.43%) good stations and one of the
nine (11.11%) marginal stations were misclassified (Figure 7).
EBI index Ex
EBI index E1 scored stations sampled in 1999-2002 as good (5) or marginal (0) by
using the critical value for the density of individuals (Table 11). EBI index E1 incorrectly
classified 44 of the 96 (45.83%) stations (Figure 6). Forty-three of the 87 (49.43%) good
stations and one of the nine (11.11%) marginal stations were misclassified (Figure 7).
EBI index E2 scored stations sampled in 1999-2002 as good (5) or marginal (0) by
using the critical value for the number of taxa (Table 11). EBI index E2 incorrectly
classified 43 of the 96 (44.79%) stations sampled in 1999-2002 (Figure 6). Forty-two of
the 87 (48.28%) good stations and one of the nine (11.11%) marginal stations were
misclassified (Figure 7).
EBI index E3 scored stations sampled in 1999-2002 as good (5) or marginal (0) by
using the critical value for the number of top predator taxa (Table 11). EBI index E3
incorrectly classified 45 of the 96 (46.88%) stations (Figure 6). Forty-three of the 87
(49.43%) good stations and two of the nine (22.22%) marginal stations were
misclassified (Figure 7).
Application of the EBI index – Discriminant analyses
EBI index Ax
For EBI index A1, the number of estuarine nursery taxa and species richness (D)
were eliminated from the discriminant analysis because they were highly correlated
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(Spearman’s rank correlation, r>0.95, p<0.0001) with the number of taxa. EBI index A1
incorrectly classified four of the 69 (5.80%) stations sampled in 1999-2001 (Figure 5)
using a nonparametric, quadratic discriminant analysis (multivariate analysis of variance
[MANOVA], p=0.0004; Bartlett’s test, p=0.0001). None of the good stations and four of
the eight (50%) marginal stations were misclassified. When applied to stations sampled
in 1999-2002, EBI index A1 incorrectly classified eight of the 96 (8.33%) stations (Figure
5) using a nonparametric, quadratic discriminant analysis (MANOVA, p=0.0057;
Bartlett’s test, p=0.0518). One of the 87 (1.15%) good stations and seven of the nine
(77.78%) marginal stations were misclassified (Figure 8).
For EBI index A2, the number of estuarine nursery taxa was eliminated from the
discriminant analysis because it was highly correlated (Spearman’s rank correlation,
r>0.95, p<0.0001) with the number of taxa. EBI index A2 incorrectly classified eight of
the 69 (11.59%) stations sampled in 1999-2001 (Figure 5) using a nonparametric, linear
discriminant analysis (MANOVA, p<0.0001; Bartlett’s test, p=0.1030). One of the 61
(1.64%) good stations and seven of the eight (87.50%) marginal stations were
misclassified. When applied to stations sampled in 1999-2002, EBI index A2 incorrectly
classified nine of the 96 (9.38%) stations (Figure 5) using a nonparametric, quadratic
discriminant analysis (MANOVA, p=0.0038; Bartlett’s test, p=0.0080). One of the 87
(1.15%) good stations and eight of the nine (88.89%) marginal stations were
misclassified (Figure 8).
EBI index A3 incorrectly classified nine of the 96 (9.38%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
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(MANOVA, p=0.0009; Bartlett’s test, p=0.0539). None of the 87 good stations and all of
the nine marginal stations were misclassified (Figure 8).
EBI index Bx
EBI index B1 incorrectly classified five of the 69 (7.25%) stations sampled in
1999-2001 (Figure 5) using a nonparametric, quadratic discriminant analysis
(MANOVA, p<0.0001; Bartlett’s test, p=0.0506). For stations sampled in 1999-2001,
one of the 61 (1.64%) good stations and four of the eight (50%) marginal stations were
misclassified. When applied to stations sampled in 1999-2002, EBI index B1 incorrectly
classified nine of the 96 (9.38%) stations (Figure 5) using a nonparametric, quadratic
discriminant analysis (MANOVA, p<0.0001; Bartlett’s test, p=0.0006). Three of the 87
good stations (3.45%) and six of the nine (66.67%) marginal stations were misclassified
(Figure 8).
EBI index B2 incorrectly classified six of the 69 (8.7%) stations sampled in 1999-
2001 (Figure 5) using a nonparametric, linear discriminant analysis (MANOVA,
p<0.0001; Bartlett’s test, p=0.1406). None of the good stations and six of the eight
(75%) marginal stations were misclassified. When applied to stations sampled in 1999-
2002, EBI index B2 incorrectly classified eight of the 96 (8.33%) stations (Figure 5) using
a nonparametric, quadratic discriminant analysis (MANOVA, p<0.0001; Bartlett’s test,
p=0.0010). None of the good stations and eight of the nine (88.89%) marginal stations
were misclassified (Figure 8).
EBI index B3 incorrectly classified six of the 96 (6.25%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
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(MANOVA, p<0.0001; Bartlett’s test, p=0.0002). None of the good stations and six of
the nine (66.67%) marginal stations were misclassified (Figure 8).
EBI index B4 incorrectly classified eight of the 96 (8.33%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
(MANOVA, p=0.0012; Bartlett’s test, p=0.0184). None of the 87 good stations and eight
of the nine (88.89%) marginal stations were misclassified (Figure 8).
EBI index B5 incorrectly classified seven of the 96 (8.33%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
(MANOVA, p=0.0004; Bartlett’s test, p=0.0016). None of the good stations and seven
of the nine (77.78%) marginal stations were misclassified (Figure 8).
EBI index Cx
For EBI index C1, the number of estuarine nursery taxa was eliminated from the
discriminant analysis because it was highly correlated (Spearman’s rank correlation,
r>0.95, p<0.0001) with the number of taxa. EBI index C1 incorrectly classified 14 of the
96 (14.58%) stations sampled in 1999-2002 (Figure 6) using a nonparametric, quadratic
discriminant analysis (MANOVA, p=0.0189; Bartlett’s test, p=0.0562). Five of the 87
(5.75%) good stations and all nine marginal stations were misclassified (Figure 8).
EBI index C2 incorrectly classified 19 of the 96 (19.79%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
(MANOVA, p=0.0191; Bartlett’s test, p=0.0052). Thirteen of the 87 (14.94%) good
stations and six of the nine (66.67%) marginal stations were misclassified (Figure 8).
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For EBI index C3, the number of estuarine nursery taxa was eliminated from the
discriminant analysis because it was highly correlated (Spearman’s rank correlation,
r>0.95, p<0.0001) with the number of taxa. EBI index C3 incorrectly classified one of
the 96 (1.04%) stations sampled in 1999-2002 (Figure 6) using a nonparametric,
quadratic discriminant analysis (MANOVA, p=0.0484; Bartlett’s test, p<0.0001). One of
the 87 (1.15%) good stations and none of the marginal stations were misclassified (Figure
8).
EBI index Dx
EBI index D1 incorrectly classified six of the 96 (6.25%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
(MANOVA, p=0.0008; Bartlett’s test, p=0.0023). Two of the 87 good stations (2.30%)
and four of the nine (44.44%) marginal stations were misclassified (Figure 8).
EBI index D2 incorrectly classified five of the 96 (5.21%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
(MANOVA, p=0.0017; Bartlett’s test, p=0.0155). None of the good stations and five of
the nine (55.56%) marginal stations were misclassified (Figure 8).
EBI index D3 incorrectly classified seven of the 96 (7.29%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
(MANOVA, p=0.0002; Bartlett’s test, p=0.0002). One of the 87 (1.15%) good stations
and six of the nine (66.67%) marginal stations were misclassified (Figure 8).
EBI index D4 incorrectly classified seven of the 96 (7.29%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
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(MANOVA, p=0.0003; Bartlett’s test, p=0.0006). One of the 87 (1.15%) good stations
and six of the nine (66.67%) marginal stations were misclassified (Figure 8).
EBI index D5 incorrectly classified four of the 96 (4.17%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
(MANOVA, p=0.0003; Bartlett’s test, p=0.0004). None of the good stations and four of
the nine (44.44%) marginal stations were misclassified (Figure 8).
EBI index D6 correctly classified all 96 stations sampled in 1999-2002 (Figures 6
and 8) using a nonparametric, quadratic discriminant analysis (Appendix H; MANOVA,
p=0.0033; Bartlett’s test, p<0.0001).
EBI index D7 incorrectly classified six of the 96 (6.25%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
(MANOVA, p=0.0062; Bartlett’s test, p<0.0001). Four of the 87 (4.60%) good stations
and 2 of the nine (22.22%) marginal stations were misclassified (Figure 8).
EBI index D8 incorrectly classified six of the 96 (6.25%) stations sampled in
1999-2002 (Figure 6) using a nonparametric, quadratic discriminant analysis
(MANOVA, p=0.0001; Bartlett’s test, p=0.0003). One of the 87 (1.15%) good stations
and five of the nine (55.56%) marginal stations were misclassified (Figure 8).
EBI index Ex
Although EBI indices E1-3 used different metrics, they all had the same error rates
when used to classify stations sampled in 1999-2002 with the discriminant analysis. EBI
index E1 used a nonparametric quadratic discriminant analysis (MANOVA, p=0.007;
Bartlett’s test, p=0.114) while EBI indices E2 and E3 used a nonparametric linear
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discriminant analysis (MANOVA, p<0.02; Bartlett’s test, p>0.30). EBI indices E1-3
incorrectly classified nine of the 96 (9.38%) stations (Figure 6). None of 87 good
stations and all nine marginal stations were misclassified by EBI indices E1-3 (Figure 8).
Evaluation and selection of the final EBI index
Metrics selected by the one-way analyses, stepwise discriminant analyses, and
previous studies differed greatly and not one metric was chosen by all three selection
methods (Table 6). The indices that included metrics selected by the one-way analyses
(EBI indices Ax) and stepwise discriminant analyses (EBI indices Bx) were most closely
related by having three metrics in common that described fish life history (tidal creek
nursery taxa), trophic composition (top predator taxa), and tolerance (salinity independent
taxa; Table 6). The one-way analyses and previous studies shared two metrics (estuarine
nursery taxa and number of taxa), while the stepwise discriminant analyses and previous
studies shared only one metric (dominance of the most abundant taxon). All three
selection methods chose metrics that described fish life history, tolerance, and
community structure (Table 6).
For both the median and discriminant analyses, EBI indices A1,2 and B1,2 had
lower misclassification rates when applied back to the original data from which they were
developed (Figure 5). For the median analysis, EBI indices A1,2 and B1,2 were not
effective in predicting the environmental quality of stations sampled in 2002 because of
extremely high error rates (>65%, Figure 5). Discriminant analysis was impossible for
stations sampled in 2002 because stations showed little to no difference in water,
sediment, or upland quality (degree of freedom less than one for marginal stations). Error
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rates were also higher for the combined 1999-2002 data than when compared to error
rates as a result of application to stations sampled in 1999-2001 (Figure 5).
High error rates obtained by the median analysis for good, marginal, and the total
number of stations did not necessarily correlate with high error rates obtained by the
discriminant analysis (Figure 6). The median analysis was more conservative in that this
technique misclassified good stations more often than marginal stations (Figure 7), while
the discriminant analysis had extremely high rates of error for marginal stations (Figure
8). Overall, the discriminant analysis had lower error rates using the cross-validation
method than when compared to the median analysis (Figure 6).
Five EBI indices with relatively low error rates were selected for further
consideration as the final EBI index. Results of the median analysis indicated that EBI
index A3 had the lowest misclassification rate for marginal stations (Figure 7) and EBI
indices C2 and D2 had the lowest misclassification rates for good and total number of
stations (Figures 6 and 7). Based on the discriminant analysis, EBI index D6 was the only
index that correctly classified all stations (Figures 6 and 8). Since EBI index C3 included
similar metrics to EBI index D6, it was also considered.
The fish metrics that were incorporated, the number of metrics, and the maximum
score differed greatly among EBI indices A3, C2, C3, D2, and D6 (Table 10; Figure 9).
When the scores of these five EBI indices were plotted for stations classified a priori as
good or marginal, each of the five EBI indices had a large overlap in EBI scores for good
and marginal stations (Figure 9). Stations that were scored within the overlap were
labeled as “unknown” because the range of scores could not determine environmental
quality without error. For example, 70 good and marginal stations scored by EBI index
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D2 overlapped at scores that fell below 25, while 26 stations classified as good scored 25
or higher (Figure 9d). For EBI index D2, a solid vertical line representing the new
threshold value was drawn at 22.5 to distinguish the cutoff EBI score between good and
unknown stations.
EBI index A3 had the lowest number of stations labeled as unknown (n=49), when
the original criterion (2.5) was used to score stations, and EBI index A3 had the highest
number of stations correctly labeled as good (n=47; Figure 9a). On the other hand, EBI
indices C2 and D2 were composed of more than one metric, and threshold values were
increased from 12.5 and 15, respectively, to 22.5 for both indices. For EBI index C3, the
threshold value was increased from 22.5 to 37.5. These threshold values were established
because stations that scored above the new values were all classified a priori as good and
stations that scored below the new values were labeled as unknown. As a result of the
establishment of these new thresholds, which allowed no overlap of marginal and good
stations, all of the marginal stations and most of the good stations were labeled as
unknown. EBI indices C2, D2, and C3 had a total of 85, 70, and 73 of the 96 stations,
respectively, labeled as unknown. Unlike EBI indices A3, C2, and D2, the criterion for
EBI index D6 was adjusted by using two new thresholds. Stations labeled as unknown
(n=81) were bounded by upper and lower limit threshold values (37.5 and 2.5,
respectively). The upper threshold value separated 14 good stations from unknown
stations while the lower threshold value separated one marginal station from unknown
stations.
EBI index D6 was the only index that had scores that could classify stations as
good and marginal without error (Figure 9). Therefore, EBI index D6 was selected and
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named as the final EBI index for this study. However, EBI index D6 correctly classified a
limited number of good and marginal stations. Since most of the stations (84.38%) were
labeled as unknown, another review was necessary to assess the threshold values for
marginal and good stations used for the final EBI index. The original threshold was
modified with four threshold value adjustments (1, 2, 3, and 4; Figure 9). Adjustment 1
changed the marginal threshold value from 2.5 to 7.5 and correctly classified five
unknown stations as marginal, while misclassifying five good stations that were labeled
as unknown. Although this adjustment of the marginal threshold value decreased the
percent of stations labeled as unknown from 84.38% to 73.96%, it increased the error rate
from zero to 5.21%. Likewise, adjustment 2 changed the good threshold value from 37.5
to 32.5 and correctly classified 10 unknown stations as good, while misclassifying one
marginal station that was labeled as unknown. Although this adjustment of the good
threshold value decreased the percent of stations labeled as unknown from 84.38% to
72.92%, it also increased the error rate from zero to 10.42%. Adjustment 3 used both of
the previously discussed adjustments of the marginal and good threshold values, and
misclassified 15 of the 96 (15.63%) stations, while 61 of the 96 (63.54%) were labeled as
unknown. Finally, adjustment 4 established a threshold value (17.5) that would result in
the lowest error rate, while classifying all 96 stations as either marginal or good. With
this threshold value, 34 of the 96 (35.42%) stations sampled in 1999-2002 were
misclassified. Thirty-three of the 87 (37.93%) good stations and one of the nine
(11.11%) marginal stations were misclassified with a threshold value at 17.5.
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Stations with excellent environmental quality
A subset of 16 good stations sampled in 1999-2002 were classified as excellent as
a result of scoring good (5) for all parameters describing water, sediment, and upland
quality (Appendix G). Fish metric critical values for excellent stations overlapped with
critical values for good stations (Table 11). No consistent relationship existed between
environmental quality and the average values of all 21 fish metrics selected by one-way
analyses, stepwise discriminant analyses, and previous studies (Table 5). The final EBI
index predicted only three of the 16 (18.75%) excellent stations to have good
environmental quality, using the original threshold values (Appendix G). Using
threshold values established by adjustment 1, three of the 16 (18.75%) excellent stations
were classified as good, while one of the 16 (6.25%) excellent stations was classified as
marginal. Threshold values that were established by adjustment 2 classified five of the
16 (31.25%) excellent stations as good, while none was classified as marginal. Threshold
values that were established by adjustment 3, which were the combined threshold values
of adjustments 1 and 2, classified five of the 16 (31.25%) excellent stations as good,
while one was classified as marginal. Finally, threshold values established by adjustment
4 classified nine of the 16 (56.25%) excellent stations as good, while seven of the 16
(43.75%) excellent stations were classified as marginal.
DISCUSSION
Environmental quality and physical features
Based on the criteria developed for this study, South Carolina tidal creeks in
1999-2002 had good overall environmental quality and were similar in water, sediment,
and upland quality. These results are comparable to a study done by Van Dolah et al.
(2002), which also used South Carolina Estuarine and Coastal Assessment Program
(SCECAP) data to determine the quality of South Carolina tidal creeks. Van Dolah et al.
(2002) included different parameters to define tidal creek quality, using integrated
measures of water quality, sediment quality, and a benthic index of biotic integrity (B-
IBI). The overall estimate of the condition of creek quality was calculated by Van Dolah
et al. (2002) with a cumulative distribution function (CDF). Although Van Dolah et al.
(2002) used different methods to determine tidal creek quality, and analyzed data from
only 1999-2000, it was reported that 88% of South Carolina tidal creeks were in good
condition in 1999-2000, which is very similar to the value of 91% found in the current
study.
In contrast, studies in other areas of the United States (US) have often found
lower overall environmental quality and have developed indices of biotic integrity
without available reference sites (sites of good environmental quality) because most areas
had high levels of anthropogenic degradation (Karr 1981; Hughes et al. 1986; Deegan et
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al. 1993, 1997; Meng et al. 2002). Dame et al. (2000) compared south Atlantic US
estuaries to find that the coastal human population of South Carolina was one of the
smallest in the country, suggesting relatively low levels of detrimental anthropogenic
environmental impact. However, Kennish (2002) estimated that by 2020, 75% of the
world’s population will live within 60 km of the coast and predicted that the growing
human population will contribute significantly to habitat loss in estuaries. Although there
are currently low levels of environmental degradation in South Carolina, an estuarine
biotic integrity (EBI) index for South Carolina tidal creeks will become an increasingly
important tool as coastal populations continue to increase.
Estuarine environmental quality was defined in the current study using many of
the same parameters (dissolved oxygen, total nitrogen, sediment contaminants, and
human disturbance) that have been used in previous studies to develop an index of
estuarine biotic integrity based on invertebrates or fishes (e.g., Deegan et al. 1993, 1997;
Weisberg et al. 1997; Engle and Summers 1999; Van Dolah et al. 1999; Meng et al.
2002). Additional parameters, such as pH, biological oxygen demand, total phosphorus,
and fecal coliform bacteria concentration, were incorporated in the current study because
they are also indicators of anthropogenic pollution (e.g., Mallin et al. 1999a, 1999b;
Vernberg et al. 1992; Lebo and Sharp 1993; Ringwood and Keppler 2002; Ansari et al.
2003; Scott et al. 1996, 1998). The final combination of water, sediment, and upland
quality parameters used in the current study were selected because of their ability to
influence estuarine biological community structure.
Unlike previously developed fish indices of estuarine biotic integrity (see Deegan
et al. 1993, 1997; Meng et al. 2002), the current study did not use the abundances of
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other biota, such as eelgrass and chlorophyll a, to define environmental quality. While
these biotic indicators have been proven to be useful in the development of some indices,
provided that they are capable of identifying differences in environmental conditions,
biotic indicators were not transferable to the current study for several reasons. In
northeastern estuaries, the decline of eelgrass is a response partly due to increased
anthropogenic development, organic loading, and eutrophication (Costa 1988; Short and
Burdick 1996; Short and Wyllie-Echeverria 1996; McClelland et al. 1997; Deegan et al.
2002; Meng et al. 2002; Hughes et al. 2002; Hauxwell et al. 2003). Therefore, eelgrass
abundance is a useful indicator of environmental quality in northeastern estuaries.
However, eelgrass and other sea grasses are very rare in South Carolina estuaries due to
naturally occurring high turbidity and tidal amplitude (Ernst and Stephan 1997; Thayer et
al. 1997). Therefore, abundance of sea grass is not a useful metric in South Carolina
estuarine systems. Likewise, high levels of chlorophyll a are not common in South
Carolina, with elevated levels found in only 13% of South Carolina tidal creeks in 1999-
2000 (Bricker et al. 1999; Van Dolah et al. 2002). Furthermore, Vernberg et al. 1992
found that chlorophyll a levels were not significantly different between a developed
estuary in South Carolina and a relatively pristine estuary in South Carolina, which
suggests that chlorophyll a is not a critical biotic indicator for the current study.
In the current study, the percent of physically altered land may have been
underestimated since outdated levels of physically altered land (Anderson et al. 1976; US
Fish and Wildlife 1989, 1994) were used to quantify upland quality. The presence of
industrial, urban, residential, and agricultural land within 500 m of a station was rare in
1989 and 1994. However, the amount of developed land (urban, built up, or
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transportation areas) in South Carolina rose by 21% between 1992-1997, mainly from
urbanization (USDA 2000; USDA 2003). South Carolina was ranked 10th, out of the 48
contiguous US, for having the most acres of land developed between 1992 and 1997
(USDA 2000). In 2001, 6% of the land within the 48 contiguous US was developed, a
23% increase from 1992 (USDA 2003). Although the use of 1989 or 1994 land use and
land cover data were out of date for the time period covered in the current study (1999-
2002), the inclusion of 1989 or 1994 data was better than leaving the effects of upland
quality on tidal creek environmental quality unexplored. Data from 1989 or 1994 showed
that the percent of physically altered land was significantly higher in areas surrounding
marginal stations sampled in 1999-2002 than when compared to good stations (Table 4).
The ability to detect environmental quality of tidal creeks, with low levels of
development found in 1984 or 1994, emphasized the need to continue to monitor South
Carolina tidal creeks as levels of land development increase.
Physical features for all tidal creeks were similar except for depth and location of
the station (Table 4). Marginal stations were significantly more shallow than good
stations, although the average depth of marginal and good stations differed by only 1 m
(Table 4). Shallow areas are more vulnerable to anthropogenic influences because fine
sediments that are associated with shallow areas may concentrate contaminants, such as
trace metals and pesticides (Liu et al. 2003). Shallow areas are also usually found in
upper reaches of the estuary and are in close proximity to pollutants, such as high levels
of nitrogen and phosphorus that cause eutrophication (Staver et al. 1996; Mallin et al.
1999a). Stations classified as having marginal environmental quality had significantly
higher levels of physically altered land, which could increase the amount of surface water
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run-off and serve as a source of harmful contaminants. In addition, two shallow stations
with marginal environmental quality were located upstream relative to two deeper
stations with good environmental quality. However, the sampling protocol did not allow
for strong statistical analyses to examine the relationship between tidal creek depth,
relative location of the station within the tidal creek, and upland quality because of the
low availability of marginal stations.
Fish community
The profiles of fish species that were completed for this study provide an
overview of life history, trophic and ecological composition, and tolerance of South
Carolina tidal creek fishes. High numbers of juvenile transient fish were found since
sampling occurred during the summer, when most juvenile fish move into the estuary
after being spawned offshore (Shealy et al. 1974; Cain and Dean 1976; Wenner et al.
1981, 1984, 1991; Allen and Barker 1990). The trawl sampled at the bottom of the water
column and collected many benthic organisms that fed mostly on detritus or benthic and
demersal crustaceans (Shealy et al. 1974; Wenner et al. 1981, 1984, 1991). Gear
selectivity resulted in high numbers of benthic fish and benthic invertivores. South
Carolina tidal creeks had low numbers of tolerant fish, as predicted for relatively pristine
areas (see Karr 1981; Karr et al. 1986). Average community values were comparable to
other tidal creek fish communities (Appendix E.4; see Wenner et al. 1981, 1984, 1991;
Van Dolah et al. 2002).
Many of the candidate fish metrics showed a statistically significant response to
each of the environmental parameters evaluated for this study, but many of the metrics
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still had overlapping values between marginal and good stations (Figure 5). The overlap
in fish metric values for marginal and good stations may be explained by the fish
community’s inability to detect environmental quality for the areas sampled. The small
differences in environmental parameters found in the current study may have not been
large enough to affect the fish community. For example, although some fish have been
shown to respond quickly to degraded environments (i.e., fleeing areas of low dissolved
oxygen concentrations; Klauda and Bender 1987; Giattina and Garton 1983), other fish
are more tolerant and can remain in areas of poor condition because they have higher
thresholds (Klauda and Bender 1987). The South Carolina tidal creek fish may not
demand the same criteria, or threshold values, that were used in the current study to
classify good and marginal stations.
Another factor that may explain the similarity in fish metric values for marginal
and good stations is that although the fish can detect differences in environmental quality,
they are opportunistically utilizing marginal habitats (i.e., feeding or avoiding predators)
because the benefits outweigh the costs of being in an area that is less pristine, as
suggested by Meng et al. (2002). These benefits may be strong enough to influence fish
to continue to seek out areas of lower environmental quality. Since fish have the
advantage of mobility, it is also possible that fish spend only limited amounts of time in
marginal habitats, while the majority of the time is spent in areas that are in good
condition. The behavior and residence times of fish in response to environmental quality
could not be examined in the current study because sampling provided only an isolated
point-in-time observation.
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Fish that were sensitive to poor conditions were predicted to be present in higher
numbers in areas that had relatively high dissolved oxygen and low anthropogenic
influence (Carmichael et al. 1992; Deegan et al. 1993, 1997). In contrast, the current
study showed that higher numbers of fish that were sensitive to environmental
degradation were generally found at marginal stations when compared to good stations
(Table 2). This interesting trend may be explained by the previously mentioned factors
that affect the overlap in fish metric values for marginal and good stations. However, the
current study was not able to determine the causes that directly influenced sensitive fish
to be in higher abundances at lower quality stations.
Meng et al. (2002) also observed higher numbers and densities of fish sensitive to
environmental degradation in low quality sites in Narragansett Bay. These unexpected
results were attributed to the location of the station within the estuary, since the low
quality sites that had higher numbers and densities of fish were generally located in the
upper estuary (Meng et al. 2002). Depth may have also contributed to structuring the
unexpected trends in fish density with environmental quality found in the study done by
Meng et al. (2002), since higher numbers of fish were located in more shallow areas.
Stations located in more shallow and protected areas can provide fish with more adequate
habitats for food and shelter (Boesch and Turner 1984; McIvor and Odum 1988; Ruiz et
al. 1993; Meng and Powell 1999; Meng et al. 2002) when compared to deeper tidal creek
areas. Additionally, depth is closely associated with sediment type, and the interaction
between the and sediment type is one of the major parameters that influence estuarine
fish distribution (Araujo et al. 2002; Prista et al. 2003).
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Although targeting to sample stations at different locations within the tidal creek
and at different depths was not within the scope of this study, a preliminary analysis was
conducted to address this issue. For the 96 stations sampled in 1999-2002, there were
nine creeks that allowed for comparisons between stations located upstream and
downstream of each other. Two of the nine creeks (Kiawah River and May River)
contained one marginal station that was located in the upper estuary while one good
station was located downstream (Figure 3). While the general trend in these two station
pairs follows results from the study done by Meng et al. (2002), the fish community was
not significantly different between marginal and good stations. Furthermore, seven other
creeks that contained two stations did not differ in environmental quality or any of the 73
candidate fish metrics. For the environmental criteria developed for this study, South
Carolina tidal creeks were very similar in water, sediment, and upland quality.
Therefore, stations located less than 2.5 km apart, and within the same creek, were not
expected to differ greatly in environmental quality or fish community.
Development and evaluation of the final EBI index
The use of one-way analyses in the development of an EBI index had several
advantages, including the basic interpretation and display of metrics that were
significantly different between good and marginal stations (Figure 5). One-way analyses
are also relatively common procedures that can be learned without the prerequisite of
advanced statistical knowledge, which is appealing when presenting developmental
procedures for future studies. On the other hand, with each additional metric that is
evaluated, the statistical power of the one-way analyses decreases and the amount of time
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needed to run analyses increases. The one-way analyses were used in the current study as
a preliminary tool to evaluate fish metrics, and therefore, statistical power was not a
primary concern.
The use of the stepwise discriminant analyses in the development of an index had
the ability to combine a large number of redundant metrics without discounting the
relationships between metrics. Another advantage of stepwise discriminant analyses was
the ability to produce the cumulative percent of the total variation that the metrics
explained, by calculating the average squared canonical correlation (Tables 8 and 9). The
cumulative percent of the total variation can then be used to guide the selection of metric
combinations for further analyses. A disadvantage of the discriminant analyses was that
the results varied depending on how many metrics were entered into the initial analyses.
Another disadvantage was that proportions and densities of metrics could not be entered
simultaneously into analyses because of problems associated with collinearity. In
addition, stepwise discriminant analyses are less popular, and therefore, results from
stepwise discriminant analyses can be easily misinterpreted as the best combination of
metrics when, in fact, further analyses are required. Like the one-way analyses, the
current study used results from stepwise discriminant analyses as a preliminary
assessment of candidate metrics.
After compiling a list of 73 candidate fish metrics based on ecological principles
and the results from previous studies, statistical tests helped to indicate preliminary fish
metrics that may be strong discriminators of environmental quality. One-way and
stepwise discriminant analyses proved to be easy to employ and produced straightforward
results. A drawback to the use of statistical analyses for describing ecological systems is
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the common tendency to focus on the results without investigating if the results agree
with established ecological principles (Yoccoz 1991; Hughes and Noss 1992; Fore et al.
1996). Therefore, comparisons between metrics that were selected by statistical tests in
the current study and metrics that were selected or suggested by previous studies
provided insight for the application of an EBI index in South Carolina tidal creeks.
Many of the metrics selected in the current study, as a result of the one-way and
stepwise discriminant analyses, were similar to those chosen for other estuarine indices
(see Thompson and Fitzhugh 1986; Guillen 2000; Deegan et al. 1993, 1997; Meng et al.
2002). However, previous estuarine studies differed in fish species, sampling technique,
environmental quality definition, and the method used to select fish metrics. Deegan et
al. (1993, 1997) and Meng et al. (2002) developed estuarine indices of biotic integrity for
northeastern US estuaries by modifying metrics of the freshwater index of biotic integrity
(IBI) developed by Karr et al. (1986). Deegan et al. (1993, 1997) developed and
validated an estuarine biotic integrity index (EBI) for estuaries in the Massachusetts area,
where habitat quality of stations were found to be marginal or poor based on parameters
such as oxygen, physical alteration, dissolved inorganic nitrogen, disturbance, eelgrass
abundance, chlorophyll a, and macroalgal abundance. Fish were sampled using a semi-
balloon otter trawl and the metrics included in the final EBI were selected by using
analysis of variance (ANOVA), Chi-square contingency tables, and Bonferroni test
(Deegan et al. 1997). Meng et al. (2002) developed an estuarine index of biotic integrity
for estuaries in the Rhode Island area, where the habitat quality of stations was found to
be high or low based on dissolved oxygen, total nitrogen concentration, human
disturbance, abundance of macroalgae, and eelgrass presence. Fish were sampled using a
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beach seine deployed from a boat, and metrics included in the final estuarine index were
selected using a stepwise discriminant analysis. Deegan et al. (1993) also used a
stepwise discriminant analysis, but found that metrics selected with this technique were
not useful in classifying stations, in contrast to Meng et al. (2002).
Metrics that were not directly transferable from previously developed estuarine
indices included the proportion of abnormal or diseased fishes and the proportion of
killifish. Deegan et al. (1993, 1997) did not find a high proportion of abnormal or
diseased fishes, but the metric was included into their final index for future application.
Fishes that were abnormal or diseased have been associated with estuarine habitats of
high anthropogenic stress (Mulcahy et al. 1987; Sindermann 1995; Moore et al. 1996).
There were no externally abnormal or diseased fish reported for the current study, but
other studies on South Carolina tidal creeks should reconsider abnormal or diseased
fishes as an indicator of environmental quality, when present. Based on fish sampled
using a beach seine with a mesh size of 0.95 cm (Meng 2004), Meng et al. (2002) found
the proportion of striped killifish (Fundulus majalis) to be a significant discriminator of
fish habitat quality. High numbers of killifish were expected in degraded environmental
conditions because they are relatively tolerant fish (Meng et al. 2002). In the current
study, gear selectivity largely explains the absence of killifish (Fundulus spp.), since a
bottom trawl with a larger mesh size (2 cm) was used to sample fish. In South Carolina,
killifish are present in tidal creeks and coastal inlets (Ogburn-Matthews and Allen 1993),
but killifish were rare in trawl surveys (Shealy et al. 1974; Wenner et al. 1981, 1984,
1991). The metric assessing killifish abundance was not directly transferable to this
study, but other tolerant taxa that may be regarded as equivalent to the killifish metric
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were evaluated as candidate metrics. Bay anchovy (Anchoa mitchilli) and shad (Alosa
sapidissima and Dorosoma sp.) are tolerant taxa commonly found in bottom trawls, and
high abundances are expected in areas of degraded environmental conditions (Bechtel
and Copeland 1970; Thompson and Fitzhugh 1986; Guillen 2000).
EBI indices developed in the current study were composed of metrics that were
selected through one-way analyses, stepwise discriminant analyses, and results from
previous studies. When the EBI indices were used to predict environmental quality with
the median and discriminant analyses, high error rates often resulted (Figures 6-8). These
high error rates emphasized further evaluation of the selected metrics by incorporating
established ecological principles that were specific to South Carolina tidal creek fish
communities. Therefore, the development of composite indices (EBI indices D1-8) was a
more subjective approach that applied statistical analyses from the current study, results
from previous studies, and scientific knowledge.
When compared to indices developed using the one-way analyses, stepwise
discriminant analyses, or previous studies, most of the misclassification rates of
composite indices were lower (Figures 6-8). For example, EBI index B1 was developed
using six metrics selected by discriminant analysis, and four of the six metrics
(dominance of the most abundant taxon, flatfish density, tidal creek nursery taxa, and top
predator taxa) were shared with EBI index D2 (Table 6). One metric that was included in
EBI index B1 and excluded in EBI index D2 was the metric describing 90% of the total
abundance, which may be redundant to the metric already incorporated into EBI index B1
that described the dominance of the most abundant taxon. EBI index D2 included two
metrics (number of taxa and salinity independent taxa) that were among the metrics that
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were most frequently selected. Based on results from the median and discriminant
analyses, overall misclassification rates were lower for EBI index D2 when compared to
EBI index B1 (Figure 6).
Individual fish community metrics that were traditionally used as indicators of
habitat quality (EBI indices E1-3) had relatively high error rates when compared to other
indices that were composed of more than one metric (Figures 6-8). High error rates
confirmed that community metrics, such as density of individuals, number of taxa,
species diversity, were not effective as individual indicators of environmental quality
because they often missed many of the ecological and trophic interactions that are
affected by environmental quality (Livingston 1976; Karr 1981; Angermeier and
Schlosser 1987; Ohio EPA 1987; Fausch et al. 1990; Hughes and Noss 1992; Van Dolah
et al. 1999). In most cases, error rates decreased when individual community metrics
used in EBI indices E1-3 were used in conjunction with other metrics as a multimetric
index (Figures 6-8). For example, results from the discriminant analyses showed that
EBI index E3, which uses only the species diversity metric, incorrectly classified all
marginal stations (Figure 8). In comparison, EBI index C3, which uses the species
diversity metric in addition to eight other metrics, correctly classified all marginal
stations (Figure 8). Results from the current study clearly demonstrated the limited value
of individual metrics and that the multimetric approach was a better methodology to
determine environmental quality.
Median and discriminant analyses were useful tools in categorizing good and
marginal stations because they had relatively simple application procedures that were
rapid and repeatable. Ultimately, the evaluation of the range of EBI scores from potential
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EBI indices as selected by either discriminant or median analyses was needed before
choosing the final EBI index. When evaluating indices in the current study, discriminant
analyses proved to be more helpful than the median analyses; in fact, results from the
discriminant analyses were used to select EBI index D6 as a potential final EBI index.
Results from the discriminant analyses indicated that EBI index D6 was the only index to
correctly classify all stations (Figures 6 and 8), while results from the median analyses
indicated that no index was able to correctly classify all stations. Consequently, EBI
index D6 was the only index to have threshold values that could clearly distinguish
between good and marginal stations without error, and was determined as the final EBI
index in the current study.
The final EBI index was developed by applying knowledge of South Carolina
tidal creek habitats to modify EBI index C3, after finding that EBI index C3 had relatively
low error rates when used to predict environmental quality (Table 12). The EBI index C3
included metrics used by Deegan et al. (1993, 1997) and Meng et al. (2002), and was
modified into the final EBI index by substituting one metric (percent abundance of
flatfish) for another metric (percent abundance of flounder). Meng et al. (2002)
developed a fish index using flounder in the northeastern US, where winter flounder
(Pseudopleuronectes americanus) was the dominant flounder present. Winter flounder
have been shown in a number of studies to be relatively sensitive to anthropogenic stress
(Sindermann 1996). However, summer flounder (Paralichthys dentatus) was one of the
dominant recreationally important flounders in southeastern US estuaries (Nelson et al.
1991a; this study) and is relatively tolerant of sediment contaminants and pollution (Hoss
et al. 1974; Schaaf et al. 1987). Therefore, the flounder metric used for northeastern US
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estuaries was not appropriate in the southeast. Results from the current study indicated
that flounders (Paralichthys dentatus and P. lethostigma) were extremely rare (<1%) in
the fish community, while the broader grouping of flatfish composed a slightly larger
proportion (8%) of the overall abundance of fishes. The metric describing flatfish
included flounder taxa, in addition to other flatfish taxa collected in South Carolina tidal
creeks, such as whiffs (Citharichthys sp.), fringed flounder (Etropus crossotus),
blackcheek tounguefish (Symphurus plagiusa) and hogchoker (Trinectes maculatus). The
flatfish metric made the final EBI index more sensitive in detecting environmental
conditions than the original flounder metric that was used in EBI index C3.
Although EBI index C3 and the final EBI index shared all but one metric,
misclassification rates differed greatly. Based on the discriminant analyses, EBI index C3
had higher error rates than the final EBI index for good, marginal, and across all stations,
while the median analyses showed slightly lower error rates (Figures 6-8). After the
distribution of EBI scores was plotted and new thresholds were considered, EBI index C3
was not able to distinguish between good and marginal stations without error and was not
as adequate as the final EBI index for determining environmental quality (Figure 9).
Future directions and recommendations
Based on the results from the current study, metrics describing fish life history
(estuarine nursery taxa, estuarine resident taxa, and estuarine spawner taxa), ecological
composition (percent abundance of benthic individuals), tolerance (density of flatfish),
and community structure (density of individuals, dominance of the most abundant taxon,
number of taxa, and species diversity) should be the primary metrics considered in future
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indices. Low values for estuarine nursery taxa, estuarine resident taxa, estuarine spawner
taxa, density of flatfish, density of individuals, number of taxa, and species diversity
indicated areas of good estuarine biotic integrity. High values for percent abundance of
benthic individuals, dominance of the most abundant taxon, and density of flatfish
indicated areas of marginal estuarine biotic integrity. Since the trends found in the
current study were unexpected and could not be explained (Tables 2 and 12), the EBI
index needs to be validated as more datasets become available. Sampling for the South
Carolina Estuarine and Assessment Program (SCECAP) was continued in 2003-2004
(Van Dolah et al. 2004a) and is planned to continue through 2009. SCECAP data will
provide a good validation data set for the final EBI index, and/or could be used for future
development and evaluation of a new index based on the methods that were used in the
current study.
Validation data sets are also needed for the criteria used in the current study to
describe the South Carolina the tidal creek fish communities present in habitats with
excellent environmental quality. Although the final EBI index was not successful in
predicting excellent stations with the EBI score, as only three of the 16 excellent stations
were classified as good (Appendix G), these fish metric criteria were the first step to
establish important thresholds to be considered in future studies on estuarine biotic
integrity. At this time, fish metric criteria for marginal, good, and excellent
environmental quality can be used as a guide for resource managers as efforts continue to
identify and protect critical habitats.
Resource managers should consider final classification of stations based on the
median analyses as preferable to the discriminant analyses due to the more conservative
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approach. The median analyses was more conservative in that marginal stations were
generally misclassified at a lower rate than when compared to the discriminant analysis
approach (Figures 7 and 8). All but one index (EBI index E3) correctly identified eight
out of nine (88.88%) marginal stations using the median analysis, while average error
rate for marginal stations was 67.17% after using the discriminant analysis approach.
Resource managers would have the ability to detect marginal stations at a higher rate
using the median approach, which would be beneficial in targeting areas to maintain,
conserve, and protect.
For the current study, the ability to distinguish between marginal and good
stations without error was the principal factor in selecting the final EBI index, which was
the result of establishing EBI score threshold values at 2.5 and 37.5 (Figure 9). However,
adjustments in the original threshold values that were established for the final EBI index
resulted in lower numbers of unknown stations and increased error rates. These adjusted
values are useful for future applications of the EBI index when the potential for
classifying the environmental quality of stations is more essential than accuracy. The
acceptable amount of error should be the guide that is considered when choosing the
appropriate threshold values.
In addition, the levels for each parameter incorporated in the current study to
define water and sediment quality should be reevaluated in regards to fish communities.
The critical values used in the current study may not have been biologically relevant, that
is not strict enough for fish to detect degraded environments. Therefore, supplemental
experiments to determine the critical threshold values of environmental parameters (i.e.,
pH, dissolved oxygen, and upland development) and observations on the behavior of
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local fish species could be beneficial in discerning the dynamics that structure fish
communities.
It is important to continue monitoring tidal creeks for changes in the fish
community, water, sediment, and upland quality, especially in areas that were classified
as marginal or poor in the current study. Using the original threshold values, only one
station (RT99017) that was classified a priori as marginal was predicted by the EBI score
(0) to have marginal estuarine biotic integrity. Replicate samples should focus on areas
near RT99017 and other stations that had low EBI scores, such as the 10 stations had an
EBI score of 5. Additionally, two stations (NT02301 and NT01518) sampled for the
current study were specifically placed in Shem Creek, a highly developed tidal creek
area. NT02301 was classified as having poor environmental quality, but was ultimately
eliminated from analyses because other stations classified as poor were unavailable for
comparison. For future studies, Shem Creek and other areas of known anthropogenic
stress should be targeted to increase the likelihood of detecting a fish community
response to degraded conditions, if and when present. In the current study, large
differences in the fish community between good and marginal stations were not present
because of low numbers of marginal stations (n=9). However, monitoring water,
sediment, and upland quality of tidal creeks will help to determine if a greater amount of
variability among stations is reflected in the fish community.
As the development of land in South Carolina continues, upland quality criteria
should be reevaluated as land cover and land use change in South Carolina. Wang et al.
(1996, 2000, 2001) studied the effects of upland development within a 100 m buffer of
freshwater stream sites and found that there was a threshold percent of development
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(between 8-12%) that significantly affected biotic integrity (Wang et al. 1996, 2000,
2001). The use of a threshold suggested that fish species richness, biotic integrity, and
habitat may still be high within areas that had levels of upland development below the
threshold. In the current study, due to low levels of physical alteration from residential or
agricultural development (average=2%), a presence/absence criteria for upland quality
was used. As levels of physical alteration increase, a criteria based on the percent of
upland development may be more practical than a presence/absence criteria. Although
South Carolina presently has a small coastal population compared to other states in the
eastern US (Dame et al. 2000), the human population and the rate of land development
continues to grow at a rapid pace. South Carolina’s human population growth rate was
15% in 1990-2000, 2% higher than the national growth rate (Perry and Mackun 2001).
Residential, urban, and agricultural developments were the major contributors to losses of
wetlands and tidal creeks in South Carolina (Dardeau et al. 1992, Fulton et al. 1993).
The relationship between upland development and biological communities should be
further investigated in South Carolina tidal creeks to determine if there is a threshold
percent of development similar to that found in freshwater stream sites by Wang et al.
(1996, 2000, 2001).
Results from the current study suggested that future development and evaluation
of EBI indices should not rely strictly on statistical analyses, but needs to incorporate
scientific knowledge and local expertise. While statistical analyses were extremely
useful in directing further investigation in this study, the statistically significant results
must not be interpreted as the final solution to managing finfish and their habitats.
Knowledge of the local fish community and habitat is always of critical importance and
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should be expanded through monitoring and assessment programs to determine the types
of fish that are sensitive to environmental degradation.
Results from the current study also found that metrics based on the number of
taxa were the most common discriminators for environmental quality when compared to
metrics based on percent abundances or density. This suggested that fish are more
valuable as indicators of environmental quality when identified to the lowest practical
taxonomic level. Although broad categories such as fish life history, ecological and
trophic composition, and tolerance metrics are useful in understanding the fish
community composition, it is critical for future sampling efforts to accurately identify
fish at the lowest practical taxonomic level.
The examination of the relationship of each of the metrics used in the final EBI
index will also help with detecting subtle differences in the environmental quality of
future studies. For example, in the current study, estuarine nursery taxa and the number
of taxa were highly correlated because 97% of the fish utilized the estuary as a nursery
ground. Although the estuarine nursery taxa and the number of taxa may be redundant,
both metrics were retained in the final EBI index. If future studies found that the number
of taxa and estuarine nursery taxa differed greatly, this may indicate environmental
change that has limited the fish community’s use of the estuary.
In addition, the physical condition of the fish should be considered as a metric of
estuarine biotic integrity in future studies. In this study, there were very low occurrences
of fish deviating from normal conditions, but if fish were found to have visible lesions,
abnormalities, and/or disease, this would undoubtedly indicate that high stress was
present in the environment (Sindermann 1994, 1995). Another interesting direction may
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be to test fish for possible sublethal effects from contaminants, since many stressors of
the environment may not manifest in obvious characteristics (Sindermann 1994, 1995).
SCECAP has analyzed fish tissue contaminant loads of select fish species sampled from
South Carolina tidal creeks (Van Dolah et al. 2002, 2004a) and these data may be useful
when incorporated into future indices. As more information and data become available,
the final EBI index for South Carolina tidal creeks may include additional fish metric(s)
that describe the physical condition of fish.
Currently, there are still many gaps in the body of information available for South
Carolina tidal creek fish species, especially with respect to fish that are less commonly
sampled and studied. For example, resilient and salinity independent metrics were
limited in describing fish tolerance because information was available for only a subset of
fish species found in the current study. It is possible that the number of highly resilient
and salinity independent fish were underestimated at marginal stations because the lack
of information caused fish to be conservatively categorized as not resilient or not salinity
independent. In addition, an increased amount of information available for future studies
may conclude that additional fish metrics that were not evaluated in the current study,
such as contaminant loads in fish tissue, biomass, and fish physical condition are
significant discriminators of environmental quality. As more studies on tidal creek fish
life history, trophic and ecological composition, relative tolerance, and habitat
preferences become available, candidate fish metrics incorporated into a future index may
differ from those included in the final EBI index developed in the current study.
Supplemental studies on the effects of environmental parameters would be useful
for biological communities other than fish. Although some fish metrics evaluated for the
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current study were able to detect differences in environmental quality, other biological
communities may be more reliable indicators of tidal creek quality, such as
macroinvertebrates (e.g., Van Dolah et al. 1999). Detailed information on
macroinvertebrate tolerance to low dissolved oxygen levels, sensitivity to sediment
contaminants, and behavior in areas of high anthropogenic influence may allow for the
development of a more accurate index. Future evaluations and comparisons are needed
to determine if fish communities are an effective indicator of tidal creek environmental
quality.
The purpose of the final EBI index developed in the current study was to
distinguish differences in environmental quality, but future fish indices may be directed
to detect differences in fish habitat preferences. Due to the random selection process
used to establish sampling sites, there were not enough replicates of paired stations to
explore the relationship between environmental quality and fish community response
with regards to physical features such as the location of the station (upstream or
downstream) and depth. However, preliminary analyses based on the two-paired stations
showed that stations determined to have marginal quality had higher abundances of fish,
were shallower, and were located relatively upstream in the tidal creek. An interesting
approach for future studies would be to sample within single tidal creeks to examine the
differences between shallow, upper reaches and deeper, lower reaches in relation to fish
and environmental quality.
To date, indices developed in freshwater and estuarine habitats have usually been
limited to specific regions because of regional differences in habitats and fish community
composition (Hughes et al. 1986, Miller et al. 1988, Weisberg et al. 1997). The current
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study was the first to develop and evaluate an EBI index based on the tidal creek fish
community in the southeastern US. General methods used in this study have benefited
greatly from the results of previous studies and are most adaptable to other estuarine
areas similar in habitat and fish community. The South Carolina tidal creek fish
community sampled for the current study was similar to other southeastern US and Gulf
of Mexico estuarine fish communities (e.g., Subrahmanyam and Drake 1975; Hackney et
al. 1976; Weinstein 1979; Bozeman and Dean 1980; Thompson and Fitzhugh 1986,
Miglarese and Sandifer 1982; Rogers and Herke 1985; Williams et al. 1990; Nelson et al.
1991b; Dardeau et al. 1992). Southeastern US and Gulf of Mexico estuarine fish
communities have also been used successfully as indicators of environmental changes
(Thompson and Fitzhugh 1986, Guillen 2000), but have not yet been used in a fully
developed multimetric index. Future research should also include testing the final EBI
index in other regions for applicability. For example, this study’s development and
evaluation methods can be applied to data, such as Georgia’s National Coastal
Assessment (NCA) Program, to determine if an EBI index is feasible for a larger
southeastern US region.
SUMMARY AND CONCLUSIONS
Fish are valuable environmental indicators because they are sensitive to physical,
chemical, and biological stress, and are relatively easy to sample and identify. In
addition, fish communities are likely to be assessed in future studies because they
continue to be widely recognized as recreationally and economically important by
resource managers and the general public. A multimetric estuarine biotic integrity (EBI)
index was developed in the current study with the goal of creating a simple tool to
quickly assess the South Carolina tidal creek environmental quality using fish
communities as indicators.
Methods in this study provided the groundwork for development and evaluation
of future EBI indices in this and other regions (see Figure 2). Statistical analyses,
previous studies, and ecological concepts directed the selection of fish metrics that were
the best discriminators of environmental quality. Potential multimetric estuarine biotic
integrity (EBI) indices used combinations of fish metrics to calculate a single score to
predict environmental quality. Station classification results from the median analyses
were more conservative in having low error rates for classifying marginal stations, while
results from the discriminant analyses were most useful in determining the final EBI
index that could discriminate between marginal and good stations without error. The
final EBI index used nine fish metrics that described fish life history, ecological
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composition, tolerance, and community structure (Table 12). These metrics were
sensitive in determining environmental quality as described by water, sediment, and
upland quality parameters, and should be among the primary metrics considered for the
development of future indices.
The fish metrics incorporated into the final EBI index were useful indicators of
environmental quality. However, fish metric values that were predicted to be low in
response to degraded conditions, such as estuarine nursery fish, benthic fish, and species
diversity, were found to be high at stations that were classified as having marginal
environmental quality, relative to stations of good environmental quality. The
unexpected response of these and other fish metrics revealed that more information on
fish habitat preferences and research on the criteria fish require for specific water,
sediment, and upland parameters are necessary.
The multivariate discriminant analysis showed that the nine metrics used in the
final EBI index (Table 12) correctly classified the environmental quality of all stations
(Figure 8). However, the multimetric approach of scoring metrics based on the criteria
established by the median of 87 good stations and the original thresholds, showed that
metrics used in the final EBI index did not adequately reflect estuarine biotic integrity for
all stations (Figure 9). Using the original thresholds, the EBI index correctly classified
14 of the 87 (16.09%) good stations and one of the nine (11.11%) marginal stations.
However, values of the EBI scores overlapped for the majority of stations, which made
the environmental quality of 81 of the 96 (84.38%) stations unknown. The inability of
the EBI index to consistently distinguish between good and marginal stations using a
multimetric approach was due to the lack of variation in environmental quality among
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South Carolina tidal creek stations sampled in 1999-2002. Preliminary analyses indicated
that tidal creeks that were shallow, near headwaters, and in close proximity to upland that
is highly developed are areas that warrant future monitoring and assessment.
As US coastal regions become more developed in the future, South Carolina tidal
creek habitats will become more susceptible to degradation. Future projections for South
Carolina in the next 20 years include increases in residential, urban, and agricultural
development of land and high rates of human population growth. The final EBI index
presented in the current study should be considered as an index in the developmental
stage, due to the low number of marginal stations available and the lack of a true
validation dataset. While the final EBI index did not prove to be a perfect tool for
assessing environmental quality in South Carolina’s tidal creeks, it can serve as a point of
departure for continuing development of future indices. It is highly recommended that
future efforts of monitoring and assessment work towards understanding and protecting
estuarine biotic integrity. The EBI index developed and evaluated for South Carolina
tidal creeks has the potential to be an effective tool for resource managers to determine
critical areas to rehabilitate, monitor, and protect. This study was the first effort to
develop and evaluate an estuarine index of biotic integrity using the fish community and
was an important first step in understanding the relationships between fish metrics and
environmental quality in South Carolina tidal creeks.
LITERATURE CITED
Able, K. W., M. P. Fahay, and G. R. Shepherd. 1995. Early life history of black sea bass,
Centropristis striata, in the mid-Atlantic Bight and a New Jersey estuary. Fishery
Bulletin 93:429-445.
Able, K. W. and S. C. Kaiser. 1994. Synthesis of summer flounder habitat parameters.
National Oceanic and Atmospheric Administration Coastal Ocean Program
Decision Analysis Series No. 1, National Oceanic and Atmospheric
Administration Coastal Ocean Office, Silver Spring, Maryland.
Able, K. W., R. E. Matheson, W. W. Morse, M. P. Fahay, and G. Shepherd. 1990.
Patterns of summer flounder Paralichthys dentatus early life history in the Mid-
Atlantic Bight and New Jersey estuaries. Fishery Bulletin 88(1):1-12.
Adams, S. M. 1976. The ecology of eelgrass, Zostera marina (L.), fish communities. I.
Structural analysis. Journal Experimental Marine Biology and Ecology 22:269-
91.
- 90 -
Aguirre-Leon, A. and A. Yanez-Arancibia. 1986. The mojarras from Terminos Lagoon:
taxonomy, biology, ecology and trophic dynamic. (Pisces: Gerreidae). Anales del
Instituto Ciencias del Mar y Limnologia, Universidad Nacional Autonoma de
Mexico 13(1):369-444.
Ahrenholz, D. W. 1991. Population biology and life history of the North American
menhadens, Brevoortia spp. Marine Fisheries Review 53(4):3-19.
Alexander, C. E. and M. E. Monaco. 1994. NOAA’s national estuarine inventory:a tool
for comparative assessments, p. 814-827. In P. G. Wells and P. J. Ricketts (eds.),
Coastal Zone Canada ’94, Cooperation in the Coastal Zone: Conference
Proceedings, Volume 2. Coastal Zone Canada Association, Halifax, Nova Scotia.
Allen, D. M. and D. L. Barker. 1990. Interannual variations in larval fish recruitment to
estuarine epibenthic habitats. Marine Ecology Progress Series 63:113-125.
Allen, D. M., W. S. Johnson, and V. Ogburn-Matthews. 1995. Trophic relationships and
seasonal utilization of salt-marsh creeks by zooplanktivorous fishes.
Environmental Biology of Fishes 42:37-50.
Allen, G. R. (ed.) 1985. Snappers of the world: an annotated and illustrated catalogue of
lutjanid species known to date. Food and Agriculture Organization species
- 91 -
catalogue, Volume 6, United Nations Food and Agriculture Organization
Fisheries Synopsis, Rome, Italy.
Allen, R. L. and D. M. Baltz. 1997. Distribution and microhabitat use by flatfishes in a
Louisiana estuary. Environmental Biology of Fishes 50:85-103.
Alshuth, S. and R. G. Gilmore, Jr. 1993. Egg identification, early larval development and
ecology of the spotted seatrout, Cynoscion nebulosus C. (Pisces: Sciaenidae).
International Council for the Exploration of the Sea Council Meeting Papers,
Copenhagen, Denmark.
Alvarez-Lanjonchere, L. 1976. Contribution to the study of the life cycle of Mugil
curema Valenciennes in Cuvier et Valenciennes, 1836 (Pisces: Mugilidae).
Ciencias 8 Investigaciones Marinas 28:1-130.
Anderson, J. R., E. E. Hardy, J. T. Roach, and R. E. Witmer. 1976. A land use and land
cover classification system for use with remote sensor data. Geological Survey
Professional Paper, Washington, DC.
Anderson, T. W. 1984. An introduction to multivariate statistical analysis, 2nd ed. John
Wiley and Sons, Inc., New York.
- 92 -
Anderson, W. W. 1958. Larval development, growth, and spawning of the striped mullet
(Mugil cephalus) along the South Atlantic coast of the U.S. United States Fish
and Wildlife Service Fishery Bulletin 58:501-519.
Anderson, W. W., J. W. Gehringer, and F.H. Berry. 1966. Order Iniomi, Family
Synodontidae, Lizardfishes, p. 30-102. In G.W. Mead, H.B. Bigelow, C.M.
Breder, D.M. Cohen, D. Merriman, Y.H. Olsen, W.C. Schroeder, L.P. Schultz,
and J. Tee-Van (eds.), Fishes of the Western North Atlantic, No. 1, Part 5.
Memoirs of the Sears Foundation for Marine Research, Yale University, New
Haven, Connecticut.
Angermeier, P. L. and J. R. Karr. 1986. Applying an index of biotic integrity based on
stream-fish communities: considerations in sampling and interpretation. North
American Journal of Fisheries Management 6:418-429.
Angermeier, P. L. and I. J. Schlosser. 1987. Assessing biotic integrity of the fish
community in a small Illinois stream. North American Journal of Fisheries
Management 7:331-338.
Ansari Z. A., R. A. Sreepada, S. G. Dalal, B. S. Ingole, and A. Chatterji. 2003.
Environmental influences on the trawl catches in a bay-estuarine system of Goa,
west coast of India. Estuarine Coastal and Shelf Science 56(3-4):503-515.
- 93 -
Araujo, F. G., M. C. C. de Azevedo, M. D. Silva, A. L. M. Pessanha, I. D. Gomes, and A.
G. da Cruz. 2002. Environmental influences on the demersal fish assemblages in
the Sepetiba Bay, Brazil. Estuaries 25(3):441-450.
Araujo, F. G., W. P. Williams, and R. G. Bailey. 2000. Fish assemblages as indicators of
water quality in the Middle Thames Estuary, England (1980-1989). Estuaries
23(3):305- 317.
Arnold, E. L. and J. R. Thompson. 1958. Offshore spawning of the striped mullet, Mugil
cephalus, in the Gulf of Mexico. Copeia 1958(2):130-132.
Baltz, D. M., J. W. Fleeger, C. F. Rakocinski, and J. N. McCall. 1998. Food, density, and
microhabitat: factors affecting growth and recruitment potential of juvenile
saltmarsh fishes. Environmental Biology of Fishes 53(1):89-103.
Barbour, M. T., J. B. Stribling, and J. R. Karr. 1995. Multimetric approach for
establishing biocriteria and measuring biological condition, p. 63-77. In W. S.
Davis, and T. P. Simon (eds.), Biological Assessment and Criteria: Tools for
Water Resources Planning and Decision Making. Lewis Publishers, Boca Raton,
Louisiana.
- 94 -
Bearden, C. M. 1963. A contribution to the biology of the king whitings, genus
Menticirrhus, of South Carolina. Bears Bluff Lab Contribution No. 38. Bears
Bluff Laboratory, Wadmalaw Island, South Carolina.
Bechtel, T. J. and B. J. Copeland. 1970. Fish species diversity indices as indicators of
pollution in Galveston Bay, Texas. Contributions in Marine Science 15:103-132.
Berger, W. H. and F. L. Parker. 1970. Diversity of planktonic Foraminifera in deep sea
sediments. Science 168:1345-1347.
Berkman, H. E., C. F. Rabeni, and T. P. Boyle. 1986. Biomonitors of stream quality in
agricultural areas: fish versus invertebrates. Environmental Management
10(3):413-419.
Bigelow, H. B. and W.C. Schroeder. 1948. Sharks, p. 59-546. In J. Tee-Van, C.M.
Breder, S.F. Hildebrand, A.E. Parr, and W.C. Schroeder (eds), Fishes of the
Western North Atlantic, No. 1, Part 1. Memoirs of the Sears Foundation for
Marine Research, Yale University, New Haven, Connecticut.
Bigelow, H. B. and W. C. Schroeder. 1953. Fishes of the Gulf of Maine. Fishery Bulletin
53:1-577.
- 95 -
Blaber, S. J. M. 1999. Assessment of biodiversity, threats, trends and emerging issues:
estuarine ecosystems. International workshop on status of the
freshwater/coastal/marine living resources with particular emphasis on threats and
options in coastal areas. Institute of Research for Development, United Nations
Environment Program, Biodiversity Workshop, Montpellier, France.
Blaber, S. J. M. and T. G. Blaber. 1980. Factors affecting the distribution of juvenile
estuarine and inshore fish. Journal of Fish Biology 17:143–162.
Blaber, S. J. M., D. T. Brewer, and J. P. Salini. 1989. Species composition and biomasses
of fishes in different habitats of a tropical northern Australian estuary: their
occurrence in the adjoining sea and estuarine dependence. Estuarine and Coastal
Shelf Science 29:509–531.
Bodola, A. 1966. Life history of the gizzard shad, Dorosoma cepedianum (Le Seur), in
western Lake Erie. Fishery Bulletin 65:391-425.
Boesch, D. F. and R. E. Turner. 1984. Dependence of fishery species on salt marshes: the
role of food and refuges. Estuaries 7:460-468.
Böhlke, J. E. and C. C. G. Chaplin. 1968. Fishes of the Bahamas and adjacent tropical
waters. Livingston Publications, Wynnewood, Pennsylvania.
- 96 -
Böhlke, J. E. and C. C. G. Chaplin. 1993. Fishes of the Bahamas and adjacent tropical
waters, 2nd ed. University of Texas Press, Austin, Texas.
Bonham, K. 1941. Food of gars in Texas. Transactions of the American Fisheries Society
70:356-362.
Boulton, A. J. 1999. An overview of river health assessment: philosophies, practice,
problems and prognosis. Freshwater Biology 41(2):469-479.
Bowman, R. E., C. E. Stillwell, W. L. Michaels, and M. D. Grosslein. 2000. Food of
northwest Atlantic fishes and two common species of squid. Technical
Memorandum National Marine Fisheries Service-NE 155, National Oceanic and
Atmospheric Administration, Woods Hole, Massachusetts.
Bozeman, Jr. E. L. and J. M. Dean. 1980. The abundance of larval and juvenile fish in a
South Carolina intertidal creek. Estuaries 3(3):89-97.
Bramblett, R. and K. Fausch. 1991. Variable fish communities and the index of biotic
integrity in the Western Great Plains River. Transactions of the American
Fisheries Society 120:752-769.
Branstetter, S. 1981. Biological notes on the sharks of the North Central Gulf of Mexico.
Contributions to Marine Science 24:13-34.
- 97 -
Bricker, S. B., C. G. Clement, D. E. Pirhalla, S. P. Orlando, and D. R. G. Farrow. 1999.
National estuarine eutrophication assessment: effects of nutrient enrichment in the
nation’s estuaries. National Oceanic and Atmospheric Administration, National
Ocean Service, Special Projects Office and the National Centers for Coastal
Ocean Science. Silver Spring, Maryland.
Buckel, J. A., M. J. Fogarty, and D. O. Conover. 1999. Foraging habits of bluefish,
Pomatomus saltatrix, on the U.S. east coast continental shelf. Fishery Bulletin
97(4):758-775.
Burke, J. S. 1995. Role of feeding and prey distribution of summer and southern flounder
in selection of estuarine nursery habitats. Journal of Fish Biology 47(3):355-366.
Burke, J. S., J. M. Miller, and D. E. Hoss. 1991. Immigration and settlement pattern of
Paralichthys dentatus and P. lethostigma in an estuarine nursery ground, North
Carolina, USA. Netherlands Journal of Sea Research 27(3-4):393-405.
Cain, R. L. and J. M. Dean. 1976. Annual occurrence, abundance and diversity of fish in
a South Carolina intertidal creek. Marine Biology 36:369-379.
Cairns, J. J., P. V. McCormick, and B. R. Niederlehner. 1993. A proposed framework for
developing indicators of ecosystem health. Hydrobiologia 263:1-44.
- 98 -
Carmichael, J. T., B. M. Richardson, M. Roberts, and S. J. Jordan. 1992. Fish
assemblages and dissolved oxygen trends in eight Chesapeake Bay tributaries
during the summers of 1989-1991: a data report. Maryland Department of Natural
Resources, Tidewater Administration, Chesapeake Bay Research and Monitoring
Division, Annapolis, Maryland.
Carr, W. E. S. and C. A. Adams. 1973. Food habitats of juvenile marine fishes occupying
seagrass beds in the estuarine zone near Crystal River, Florida. Transactions of
the American Fisheries Society 102:511-540.
Castillo-Rivera, M., A. Kobelkowsky, and A. M. Chavez. 2000. Feeding biology of the
flatfish Citharichthys spilopterus (Bothidae) in a tropical estuary of Mexico.
Journal of Applied Ichthyology 16(2):73-78.
Castro, J. I. 1993. The shark nursery of Bulls Bay, South Carolina, with a review of the
shark nurseries of the southeastern coast of the United States. Environmental
Biology of Fishes 38:37-48.
Cervigón, F., R. Cipriani, W. Fischer, L. Garibaldi, M. Hendrickx, A. J. Lemus, R.
Márquez, J. M. Poutiers, G. Robaina, and B. Rodriguez. 1992. FAO records for
the identification of species for the fishing industry: field guide to commercial
- 99 -
marine and salt water species of the northern coast of South America. United
Nations Food and Agricultural Organization, Rome, Italy.
Chandler, J. R. 1970. A biological approach to water quality management. Water
Pollution Control 4:415-422.
Chang, C-W., W. N. Tzeng, and Y-C. Lee. 2000. Recruitment and hatching dates of grey
mullet (Mugil cephalus l.) juveniles in the Tanshui estuary of Northwest Taiwan.
Zoological Studies 39(2):99-106.
Chao, L. M. and J. A. Musick. 1977. Life history, feeding habits, and functional
morphology of juvenile sciaenid fishes in the York River estuary, Virginia.
Fishery Bulletin 75:657-702.
Chapman, R. W. 1978. Observations of spawning behavior in Atlantic spade fish,
Chaetodipterus faber. Copeia 1978(2):336.
Chavance, P., D. F. Hernández, A. Yañez-Arancibia, and F. A. Linares. 1984. Ecología,
biología y dinámica de las poblaciones de Bairdiella chrysoura en la Laguna de
Terminos, sur del Golfo de Mexico (Pisces: Sciaenidae). Anales del Centro de
Ciencias del Mar y Limnologia Universidad Nacional Autónoma de México
11(1):123-162.
- 100 -
Chaves, P. T. C. and A. Serenato. 1998. Diets diversity of flatfish abundants (Teleostei,
Pleuronectiformes) in the mangrove of Guaratuba Bay, Parana, Brazil. Brazilian
Journal of Oceanography 46(1):61-68.
Chernick, M. R. 1999. Bootstrap methods: a practitioner’s guide. John Wiley and Sons,
Inc., New York.
Chessman, B. C. 1995. Rapid assessment of rivers using macroinvertebrates: a procedure
based on habitat specific sampling, family level identification and a biotic index.
Australian Journal of Ecology 20:122-129.
Chittenden, Jr. M. E. 1969. Life history and ecology of the American shad, Alosa
sapidissima, in the Delaware River. Doctoral Dissertation, Rutgers University,
New Brunswick, New Jersey.
Chittenden, Jr. M. E., L. R. Barbieri, and C. M. Jones. 1993. Fluctuations in abundance of
Spanish mackerel in Chesapeake Bay and the mid-Atlantic region. North
American Journal of Fisheries Management 13:450-458.
Chun, K., W. J. Weaver, and L. A. Deegan. 1996. Assessment of fish communities in
New England embayments: application of the Estuarine Biotic Integrity Index.
Biological Bulletin 191:320-321.
- 101 -
Clarke, K. R. 1993. Non-parametric multivariate analyses of changes in community
structure. Australian Journal of Ecology 18:117-143.
Clements, W. H. and R. J. Livingston. 1983. Overlap and pollution-induced variability in
feeding habitats of filefish (Pisces: Monacanthidae) from Apalachee Bay, Florida.
Copeia 1983(2):331-338.
Collette, B. B. and C. E. Nauen. 1983. Scombrids of the world, an annotated and
illustrated catalogue of tunas, mackerels, bonitos and related species known to
date. Food and Agriculture Organization species catalogue, Volume 2, No. 125,
United Nations Food and Agriculture Organization Fisheries Synopsis, Rome,
Italy.
Compagno, L. J. V. 1984. Sharks of the world: an annotated and illustrated catalogue of
shark species known to date. Carcharhiniformes. Food and Agriculture
Organization species catalogue, Volume. 4, Part 2, No. 125, United Nations Food
and Agriculture Organization Fisheries Synopsis, Rome, Italy.
Cortés, E. 1999. Standardized diet compositions and trophic levels of sharks.
International Council for the Exploration of the Sea Journal of Marine Science
56:707-717.
- 102 -
Costa, J. E. 1988. Distribution, production, and historical changes in abundance of
eelgrass (Zostera marina) in southeastern Massachusetts. Doctoral Dissertation,
Boston University, Boston, Massachusetts.
Costa, M. J. and H. N. Cabral. 1999. Changes in the Tagus nursery function for
commercial fish species: some perspectives for management. Aquatic Ecology
33(3): 287-292.
Cowan, Jr. J.H. and R.F. Shaw. 1988. The distribution, abundance and transport of larval
sciaenids collected during winter and early spring from the continental shelf
waters off west Louisiana. Fishery Bulletin 86(1):129-142.
Cowan, Jr. J. H. and R. S. Birdsong. 1985. Seasonal occurrence of larval and juvenile
fishes in a Virginia Atlantic coast estuary with emphasis on drum (Family
Sciaenidae). Estuaries 8:48-59.
Crabtree, R. E. and D. P. Middaugh. 1982. Oyster shell size and the selection of
spawning sites by Chasmodes bosquianus, Hypleurochilus geminatus,
Hypsoblennius ionthas (Pisces, Blenniidae) and Gobiosoma bosci (Pisces,
Gobiidae) in two South Carolina estuaries. Estuaries 5(2):150-155.
Cranston, P. S., P. Fairweather and G. Clarke. 1996. Biological indicators of water
quality, p. 143-154. In J. Walker, and D. J. Reuter (eds.), Indicators of Catchment
- 103 -
Health: a Technical Perspective, Commonwealth Scientific and Industrial
Research Organization, Melbourne, Australia.
Crawford, D. W., N. L. Bonnevie, C. A. Gillis, and R. J. Wenning. 1994. Historical
changes in the ecological health of the Newark Bay estuary, New Jersey.
Ecotoxicology and Environmental Safety 29(3):276-303.
Crumpton, J. 1970. Food habits of longnose gar (Lepisosteus osseus) and Florida gar
(Lepisosteus platyrhincus) collected from five central Florida lakes, p. 419-424.
In J.W. Webb (ed.), Proceedings of the Twenty-fourth Annual Conference,
Southeastern Association of Game and Fish Commissioners, Atlanta, Georgia.
Cuellar, N., G. R. Sedberry, D. J. Machowski, and M. R. Collins. 1996. Species
composition, distribution, and trends in abundance of snappers of the southeastern
USA, based on fishery-independent sampling, pp. 60-74 In F. Arreguín-Sánchez,
J. L. Munro, M. C. Balgos, and D. Pauly (eds.), Biology, fisheries and culture of
tropical groupers and snappers. International Center for Living Aquatic Resources
Management Conference Proceedings 48:59-73.
Dahlberg, M. D. 1972. An ecological study of coastal Georgia fishes. Fishery Bulletin
70:323-353.
- 104 -
Dahlberg, M. D. 1980. Guide to coastal fishes of Georgia and nearby states. University of
Georgia Press, Athens, Georgia.
Dame, R., M. Alber, D. Allen, M. Mallin, C. Montague, A. Lewitus, A. Chalmers, R.
Gardner, C. Gilman, B. Kjerfve, J. Pinckney, and N. Smith. 2000. Estuaries of the
south Atlantic coast of North America: their geographic signatures. Estuaries
23:793-819.
Daniel, III L. B. and J. E. Graves. 1994. Morphometric and genetic identification of eggs
of spring-spawning sciaenids in lower Chesapeake Bay. Fishery Bulletin
92(2):254-261.
Darcy, G. H. 1985. Synopsis of biological data on the pinfish, Lagodon rhomboides
(Pisces: Sparidae). United States Department of Commerce, National Oceanic and
Atmospheric Administration, National Marine Fisheries Service, National
Oceanic and Atmospheric Administration Technical Report No. 23.
Dardeau, M. R., R. F. Madlin, W. W. Schroeder, and J. P. Stout. 1992. Estuaries, p. 615-
744. In C. T. Hackney, S. M. Adams, and W. H. Martin (eds), Biodiversity of the
southeastern United States, John Wiley and Sons, New York.
- 105 -
Darnell, R. M. 1958. Food habits of fishes and larger macroinvertebrates of Lake
Pontchartrain, Louisiana, an estuarine community. Publications of the Institute of
Marine Science, University of Texas 5:353-416.
Darnell, R. M. 1961. Trophic spectrum of an estuarine community, based on studies of
Lake Pontchartrain, Louisiana. Ecology 42:553-568.
Darovec, Jr. J. E.1983. Sciaenid fishes (Osteichthyes: Perciformes) of western peninsular
Florida. Memoirs of the Hourglass Cruises 6(3):1-74.
Davis, B. M. and J. W. Foltz. 1991. Food of blueback herring and threadfin shad in
Jocassee Reservoir, South Carolina. Transactions of the American Fisheries
Society 120(5):605-613.
Dawson, C. E. 1958. A study of the biology and life history of spot, Leiostomus
xanthurus Lacepede, with special reference to South Carolina. Contributions to
Bears Bluff Laboratory 28:1-44.
Deegan L. A., A. Wright, S. G. Ayvazian, J. T. Finn, H. Golden, R. R. Merson, and J.
Harrison. 2002. Nitrogen loading alters seagrass ecosystem structure and support
of higher trophic levels. Aquatic Conservation – Marine and Freshwater
Ecosystems 12(2):193-212.
- 106 -
Deegan, L. A., J. T. Finn, S. G. Ayvazian, and C. Ryder. 1993. Feasibility and application
of the Index of Biotic Integrity to Massachusetts Estuaries (EBI). Final report to
Massachusetts Executive Office of Environmental Affairs, Department of
Environmental Protection, North Grafton, Massachusetts.
Deegan, L. A., J. T. Finn, S. G. Ayvazian, C. A. Ryder-Kieffer, and J. Buonaccorsi. 1997.
Development and validation of an estuarine biotic integrity index. Estuaries
20(3):601-617.
DeLancey, L. B. 1989. Trophic relationship in the surf zone during the summer at Folly
Beach, South Carolina. Journal of Coastal Research 5(3):477-488.
Derrick, P. A. and V. S. Kennedy. 1997. Prey selection by the hogchoker, Trinectes
maculatus (Pisces: Soleidae), along summer salinity gradients in Chesapeake Bay,
USA. Marine Biology 129(4):699-711.
Dettmers, J. M. and R. A. Stein. 1992. Food consumption by larval gizzard shad:
zooplankton effects and its implications for reservoir communities. Transactions
of the American Fisheries Society 121:494-507.
Dettmers, J. M. and R. A. Stein. 1996. Quantifying linkages among gizzard shad,
zooplankton, and phytoplankton in reservoirs. Transactions of the American
Fisheries Society 125:27-41.
- 107 -
Devries, D. R. and R. A. Stein. 1992. Complex interactions between fish and
zooplankton: quantifying the role of an open-water planktivore. Canadian Journal
of Fisheries and Aquatic Sciences 49:1216-1227.
Diener, R. A., A. Inglish, and G. B. Adams. 1974. Stomach contents of fishes from Clear
Lake and tributary waters, a Texas estuarine area. Contributions to Marine
Science 18:7-17.
Diouf, P. S. 1996. Les peuplements de poissons des milieux estuariens de l'Afrique de
l'Ouest: L'exemple de l'estuaire hyperhalin du Sine-Saloum. Doctoral
Dissertation, L'Université de Montpellier II., Paris, France.
DiPinto, L. M. and B. C. Coull. 1997. Trophic-transfer of sediment-associated
polychlorinated biphenyl from meiobenthos to bottom-feeding fish.
Environmental Toxicology and Chemistry 16:2568-2575.
Dooley, J. K. 1972. Fishes associated with the pelagic sargassum complex with a
discussion of the sargassum community. Contributions to Marine Science 16:1-
32.
- 108 -
Drenner, R. W., F. DeNoyelles, Jr., and D. Kettle. 1982a. Selective impact of filter-
feeding gizzard shad on zooplankton community structure. Limnology and
Oceanography 27:965-968.
Drenner, R. W., W. J. O’Brien, and J. R. Mummert. 1982b. Filter-feeding rates of gizzard
shad. Transactions of the American Fisheries Society 111:210-215.
Duarte Lopes, P. R. and J. Tavares de Oliveira Silva. 1999. Occurrence of Astroscopus
sp. (Actinopterygii: Uranoscopidae) in the Todos os Santos Bay (Bahia State).
Acta Biology Leopold 21(1):153-160.
Durbin, A. G. and E. G. Durbin. 1998. Effects of menhaden predation on plankton
populations in Narragansett Bay, Rhode Island. Estuaries 21(3):449-465.
Earll, R. E. 1882. The Spanish mackerel, Cybium maculatum (Mitchill) Agassiz; its
natural history and artificial propagation, with an account of the origin and
development of the fishery. United States Commerce Fisheries Report 1880:395-
426.
Ellis, M. M., B. A. Westfall, D. K. Meyer, and W. S. Platner. 1947. Water quality studies
of the Delaware River with reference to shad migration. United States Fish and
Wildlife Service Special Scientific Report 38.
- 109 -
Elvidge, C. D., C. M. Milesi, J. B. Dietz, B. T. Tuttle, P. C. Sutton, R. Nemani, and J. E.
Vogelman. 2004. US constructed area approaches the size of Ohio. Earth
Observing System 85(24):233-240.
Engle, V. D., J. K. Summers, and G. R. Gaston. 1994. A benthic index of environmental
condition of Gulf of Mexico estuaries. Estuaries 17:372-384.
Engle, V. D. and J. K. Summers. 1999. Refinement, validation, and application of a
benthic condition index for Northern Gulf of Mexico estuaries. Estuaries 22:624-
635.
Environmental Systems Research Institute (ESRI). 1998. ArcView GIS Version 3.1.
Redlands, California.
Ernst, L. M. and C. D. Stephan. 1997. State regulation and management of submerged
aquatic vegetation along the Atlantic coast of the United States. In C. D. Stephan,
and T. E. Bigford (eds.), Atlantic Coastal Submerged Aquatic Vegetation: a
Review of its Ecological Role, Anthropogenic Impacts, State Regulation and
Value to Atlantic Coastal Fisheries. Atlantic States Marine Fisheries Commission
Habitat Management Series No. 1., Washington, DC.
Fausch, K. D., J. Lyons, J. R. Karr, and P. L. Angermeir. 1990. Fish communities as
indicators of environmental degradation, p. 123-144. In S. Marshall Adams (ed.),
- 110 -
Biological Indicators of Stress in Fish, American Fisheries Society Symposium 8,
American Fisheries Society, Bethesda, Maryland.
Fausch, K. D., J. R. Karr, and P. R. Yant. 1984. Regional application of an index of biotic
integrity based on stream fish communities. Transactions of the American
Fisheries Society 113(1):39-55.
Ferraro, S. P. 1980. Daily time of spawning of 12 fishes in the Peconic Bays, New York.
Fishery Bulletin 78(2):455-464.
Finucane, J. H., C. B. Grimes, and S. P. Naughton. 1990. Diets of young king and
Spanish mackerel off the southeast United States. Northeast Gulf Science
11(2):145-153.
Flores-Coto, C., A. Sanchez-Iturbe, F. Zavala-Garcia, and S. M. Warlen. 1998. Age,
growth, mortality and Food habits of larval Stellifer lanceolatus, Cynoscion
arenarius and Cynoscion nothus (Pisces: Sciaenidae), from the Southern Gulf of
Mexico. Estuarine Coastal and Shelf Science 47(5):593-602.
Fore, L. S., J. R. Karr, and L. L. Conquest. 1994. Statistical properties of an index of
biological integrity used to evaluate water resources. Canadian Journal of
Fisheries and Aquatic Sciences 51:1077-1087.
- 111 -
Fore, L. S., J. R. Karr, and R. W. Wisseman. 1996. Assessing invertebrate responses to
human activities: evaluating alternative approaches. Journal of North American
Benthological Society 15(2):212-231.
Forward, Jr. R. B., K. A. Reinsel, D. S. Peters, R. A. Tankersley, J. H. Churchill, L. B.
Crowder, W. F. Hettler, S. M. Warlen, and M. D. Green. 1999. Transport of fish
larvae through a tidal inlet. Fisheries Oceanography 8(Suppl. 2):153-172.
Franks, J. S. 1970. An investigation of the fish population within the inland waters of
Horn Island, Mississippi, a barrier island in the northern Gulf of Mexico. Gulf
Research Report 3(1):3-104.
Franks, J. S. and K. E. Vanderkooy. 2000. Feeding habits of juvenile lane snapper
Lutjanus synagris from Mississippi coastal waters, with comments on the diet of
gray snapper Lutjanus griseus. Gulf and Caribbean Research 12:11-17.
Friedland, K. D., D. W. Ahrenholz, and J. F. Guthrie. 1989. Influence of plankton on
distribution patterns of the filter-feeder Brevoortia tyrannus (Pisces: Clupeidae).
Marine Ecology Progress Series 54(1-2):1-11.
Friedland, K. D., D. W. Ahrenholz, and J. F. Guthrie. 1996. Formation and seasonal
evolution of Atlantic menhaden juvenile nurseries in coastal estuaries. Estuaries
19(1):105-114.
- 112 -
Froese, R. and D. Pauly. 2000. FishBase 2000: concepts, design and data sources.
International Center for Living Aquatic Resources Management, Los Bańos,
Laguna, Philippines.
Fulton, M. H., G. I. Scott, A. Fortner, T. F. Bidleman, and B. Ngabe. 1993. The effects of
urbanization on small high salinity estuaries of the southeastern United States.
Archives of Environmental Contamination and Toxicology 25(4):476-484.
Funicelli, N. A. 1975. Taxonomy, feeding, limiting factors and sex ratios of Dasyatis
sabina, Dasyatis americana, Daysatis sayi, and Narcine barsiliensis. Doctoral
dissertation, University of Southern Mississippi, Hattiesburg, Mississippi.
Gammon, J. F. 1976. The fish population of the middle 340 km of the Wabash River.
Purdue University Water Resources Research Center Technical Report 86.
LaFayette, Indiana.
Ganasan, V. and R. M. Hughes. 1998. Application of an index of biological integrity
(IBI) to fish assemblages of the rivers Khan and Kshipra (Madhya Pradesh),
India. Freshwater Biology 40(2):367-383.
Garcia-Abad, M. C., A. Yanez-Arancibia, P. Sanchez-Gil, and M. Tapia-Garcia. 1999.
Distribution, abundance and reproduction of Synodus foetens (Linnaeus, 1766)
- 113 -
(Pisces: Synodontidae) at the continental shelf of Southern Mexico Gulf).
Thalassas 15:9-18.
Geary, B. W., J. R. Rooker, and J. W. Webb. 2001. Utilization of saltmarsh shorelines by
newly settled sciaenids in a Texas estuary. Gulf and Caribbean Research 13:37-
49.
Gelsleichter, J., J. A. Musick, and S. Nichols. 1999. Food habits of the smooth dogfish,
Mustelus canis, dusky shark, Carcharhinus obscurus, Atlantic sharpnose shark,
Rhizoprionodon terraenovae, and the sand tiger, Carcharias taurus, from the
northwest Atlantic Ocean. Environmental Biology of Fishes 54(2):205-217.
Gelwick, F. P., S. Akin, D. A. Arrington, and K. O. Winemiller. 2001. Fish assemblage
structure in relation to environmental variation in a Texas Gulf coastal wetland.
Estuaries 24(2):285-296.
Gerritsen, J. 1995. Additive biological indices for resource management. Journal of the
North American Benthological Society 14:451-457.
Giattina, J. D. and R. R. Garton. 1983. A review of the preference-avoidance responses of
fishes to aquatic contaminants. Residue Reviews 87:44-90.
- 114 -
Ginsburg, I. 1951. Western Atlantic tonguefishes with descriptions of six new species.
Zoologica 36(3):185-201.
Gomez Gaspar, A. 1981. Taxonomic and ecological observations of Elops saurus and
Albula vulpes larvae and juveniles from the Restringa Lagoon and adjacent areas
(Margarita Island, Venezuela). Boletin Museo del Mar 10:3-23.
Goshorn, D. M. and C. E. Epifanio. 1991. Diet of larval weakfish and prey abundance in
Delaware Bay. Transactions of the American Fisheries Society 120(6):684-692.
Grabe, S. A. 1996. Feeding chronology and habits of Alosa spp. (Clupeidae) juveniles
from the lower Hudson River estuary, New York. Environmental Biology of
Fishes 47(3):321-326.
Gray, J. S. 1976. The fauna of the polluted River Tees estuary. Estuarine and Coastal
Marine Science 4:653-676.
Gray, J. S. 1989. Effects of environmental stress on species rich assemblages. Biological
Journal of the Linnean Society 37:19-32.
Gray, J. S. 2000. The measurement of marine species diversity, with an application to the
benthic fauna of the Norwegian continental shelf. Journal of Experimental
Marine Biology and Ecology 250:23-49.
- 115 -
Grecco, V. A. and M. M. Blake. 1983. Feeding ecology of coexisting larvae of American
shad and blueback herring in the Connecticut River. Transactions of the American
Fisheries Society 112(4):498-507.
Grover, J. J. 1998. Feeding habits of pelagic summer flounder, Paralichthys dentatus,
larvae in oceanic and estuarine habitats. Fishery Bulletin 96(2):248-257.
Gudger, E. W. 1916. The gaff-topsail, Felichthys felis, a sea catfish that carries its eggs in
its mouth. Zoologica 2(5):123-158.
Guillen, G. 2000. Galveston Bay – development of a rapid bioassessment method and
index of biotic integrity for coastal environments: northwestern Gulf of Mexico
pilot studies, p. 13-9-13-19. In United States Environmental Protection Agency,
EPA-822-13-00-024, Estuarine and Coast Marine Waters: Bioassessment and
Biocriteria Technical Guidance, Washington, DC.
Gunter, G. 1945. Studies on the marine fishes of Texas. Publications of the Institute of
Marine Science, University of Texas 1:1-190.
Gusey, W. F. 1981. The fish and wildlife resources of the South Atlantic Coast. Shell Oil
Co., Houston, Texas.
- 116 -
Hackney, C. T., W. D. Burbanck and O. P. Hackney. 1976. Biological and physical
dynamics of a Georgia tidal creek. Chesapeake Science 17:271-280.
Hammann, M. G. 1981. Utilization of the Columbia River Estuary by American shad,
Alosa sapidissima (Wilson). Estuaries 4(3):287.
Hansen, D. J. 1969. Food, growth, migration, and abundance of pinfish, Lagodon
rhomboides, and Atlantic croaker, Micropogon undulatus, near Pensacola,
Florida, 1963-1965. Fishery Bulletin 68:135-46.
Harding, J. M. 1999. Selective feeding behaviour of larval naked gobies Gobiosoma bosc
and blennies Chasmodes bosquianus and Hypsoblennius hentzi: preferences for
bivalve veligers. Marine Ecology Progress Series 179:145-153.
Harding, J. M. and R. Mann. 2000. Estimates of naked goby (Gobiosoma bosc), striped
blenny (Chasmodes bosquianus) and eastern oyster (Crassostrea virginica) larval
production around a restored Chesapeake Bay oyster reef. Bulletin of Marine
Science 66:29-45.
Harmelin-Vivien, M. L. and J. C. Quéro. 1990. Monacanthidae, p. 1061-1066. In J.C.
Quero, J.C. Hureau, C. Karrer, A. Post, and L. Saldanha (eds.), Check-list of the
Fishes of the Eastern Tropical Atlantic (CLOFETA), Volume 2. United Nations
Educational, Scientific and Cultural Organization, Paris, France.
- 117 -
Harrel, R. C. and M. A. Hall, III. 1991. Macrobenthic community structure before and
after pollution abatement in the Neches River estuary (Texas). Hydrobiologia
211(3):241-252.
Harris, A. H. and C. P. Rose. 1968. Shrimp predation by the sea catfish, Galeichthys felis.
Transactions of the American Fisheries Society 97:503-504.
Harris, G. P. 1994. Pattern, process and prediction in aquatic ecology; a limnological
view of some general ecological problems. Freshwater Biology 32:143-160.
Harris, J. H. 1995. The use of fish in ecological assessments. Australian Journal of
Ecology 20:65-80.
Hartman, K. J. and S. B. Brandt. 1995. Trophic resource partitioning, diets, and growth of
sympatric estuarine predators. Transactions of the American Fisheries Society
124(4):520-537.
Hartwell, S. I., C. E. Dawson, E. Q. Durell, R. W. Alden, P. C. Adolphson, D. A. Wright,
G. M. Coelho, J. A. Magee, S. Ailstock and M. Norman. 1997. Correlation of
measures of ambient toxicity and fish community diversity in Chesapeake Bay,
USA, tributaries – urbanizing watersheds. Environmental Toxicology and
Chemistry 16(12):2556-2567.
- 118 -
Hauxwell J, J. Cebrian, and I. Valiela. 2003. Eelgrass Zostera marina loss in temperate
estuaries: relationship to land-derived nitrogen loads and effect of light limitation
imposed by algae. Marine Ecology Progress Series 247:59-73.
Haven, D. S. 1959. Migration of the croaker, Micropogonias undulatus. Copeia 1959:25-
30.
Hawkins, D. M. (ed.) 1982. Topics in applied multivariate analysis. Cambridge
University Press, Cambridge, England.
Hay, G. L. 2001. Using a GIS to assess the relationships between tidal creek habitat
characteristics and finfish and crustacean assemblages. Master’s Thesis, College
of Charleston, Charleston, South Carolina.
Hayse, J. W. 1987. Feeding habits, age, growth and reproduction of Atlantic spadefish,
Chaetodipterus faber (Pisces: Ephippidae), in South Carolina. Master’s Thesis,
College of Charleston, Charleston, South Carolina.
Hensley, D. A. 1995. Paralichthyidae. Lenguados, p. 1349-1380. In W. Fischer, F. Krupp,
W. Schneider, C. Sommer, K.E. Carpenter, and V. Niem (eds.), Guia Food and
Agriculture Organization para Identification de Especies para lo Fines de la Pesca.
- 119 -
Pacifico Centro-Oriental, Volume 3, Vertebrados Part 2, United Nations Food and
Agriculture Organization, Rome, Italy.
Hester, Jr. J. M. and B. J. Copeland (eds.) 1975. Nekton population dynamics in the
Albemarle Sound and Neuse River estuaries. Sea Grant Publication No. 75-02,
University of North Carolina, Chapel Hill, North Carolina.
Hildebrand, S. F. 1963a. Family Clupeidae, Genus Alosa Link 1790, Shads, p. 293-308.
In H. B. Bigelow, C. M. Breder, D. M. Cohen, G. W. Mead, D. Merriman, Y. H.
Olsen, W. C. Schroeder, L. P. Schultz, and J. Tee-Van (eds.), Fishes of the
Western North Atlantic, No. 1, Part 3. Memoirs of the Sears Foundation for
Marine Research, Yale University, New Haven, Connecticut.
Hildebrand, S. F. 1963b. Family Clupeidae, Genus Brevoortia Gill 1861, Menhaden, p.
342-380. In H. B. Bigelow, C. M. Breder, D. M. Cohen, G. W. Mead, D.
Merriman, Y. H. Olsen, W. C. Schroeder, L. P. Schultz, and J. Tee-Van (eds.),
Fishes of the Western North Atlantic, No. 1, Part 3. Memoirs of the Sears
Foundation for Marine Research, Yale University, New Haven, Connecticut.
Hildebrand, S. F. 1963c. Family Elopidae, p. 111-131. In H. B. Bigelow, C. M. Breder,
D. M. Cohen, G. W. Mead, D. Merriman, Y. H. Olsen, W. C. Schroeder, L. P.
Schultz, and J. Tee-Van (eds.), Fishes of the Western North Atlantic, No. 1, Part
- 120 -
3. Memoirs of the Sears Foundation for Marine Research, Yale University, New
Haven, Connecticut.
Hildebrand, S. F. 1963d. Family Engraulidae, p. 152-253. In H. B. Bigelow, C. M.
Breder, D. M. Cohen, G. W. Mead, D. Merriman, Y. H. Olsen, W. C. Schroeder,
L. P. Schultz, and J. Tee-Van (eds.), Fishes of the Western North Atlantic, No. 1,
Part 3. Memoirs of the Sears Foundation for Marine Research, Yale University,
New Haven, Connecticut.
Hildebrand, S. F. and L. F. Cable. 1930. Development and life history of fourteen
teleostean fishes at Beaufort, N. C. United States Bureau Fishery Bulletin 46:383-
488.
Hildebrand, S. F. and L. F. Cable. 1934. Reproduction and development of whitings or
kingfishes, drums, spot, croaker, and weakfishes of seatrouts family Sciaenidae,
of the Atlantic coast of the United States. United States Bureau Fishery Bulletin
48(16):41-117.
Hildebrand, S. F. and L. F. Cable. 1938. Further notes on the development and life
history of some teleosts at Beaufort, N. C. United States Bureau Fishery Bulletin
24:505-642.
- 121 -
Hildebrand, S. F. and W. C. Schroeder. 1927. Fishes of the Chesapeake Bay. United
States Bureau Fishery Bulletin 43:109-111.
Hildebrand, S. F. and W. C. Schroeder. 1928. Fishes of the Chesapeake Bay. United
States Bureau Fishery Bulletin 53(pt.1):1-388.
Hines, A. H., A. M. Haddon, and L. A. Wiechert. 1990. Guild structure and foraging
impact of blue crabs and epibenthic fish in a subestuary of Chesapeake Bay.
Marine Ecology Progress Series 67(2):105-126.
Hocutt, C. H. 1981. Fish as indicators of biological integrity. Fisheries 6(6):28-31.
Hoese, H. D. 1966. Ecroparasitism by juvenile sea catfish, Galeichthyes felis. Copeia
1966:880-881.
Hoese, H. D. 1973. A trawl study of nearshore fishes and invertebrates of the Georgia
coast. Publications of the Institute of Marine Science, University of Texas 1:1-
190.
Hoese, H. D. and R. H. Moore. 1977. Fishes of the Gulf of Mexico: Texas, Louisiana and
adjacent waters. Texas A&M University Press, College Station, Texas.
- 122 -
Holland, A. F., D. M. Sanger, C. P. Gawle, S. B. Lerberg, M. S. Santiago, G. H. M.
Riekerk, L. E. Zimmerman, and G. I. Scott. 2004. Linkages between tidal creek
ecosystems and the landscape and demographic attributes of their watersheds.
Journal of Experimental Marine Biology and Ecology 298:151-178.
Holland, A. F., G. H. M. Riekerk, S. B. Lerberg, L. E. Zimmerman, and D. M. Sanger.
1997. Assessment of the impact of watershed development on the nursery
functions of tidal creek habitats, p. 110-115. In C. D. Stephan, and K. Beidler
(eds.), Management of Atlantic Coastal Marine Fish Habitat: Proceedings of a
Workshop for Habitat Managers, Atlantic States Marine Fisheries Commission
Habitat Management Series No. 2, Atlantic States Marine Fisheries Commission,
Washington DC.
Holloway, A. D. 1954. Notes on the life history and management of the shortnose and
longnose gars in Florida waters. Journal of Wildlife Management 18(14):438-449.
Holt, G. J. and S. A. Holt. 2000. Vertical distribution and the role of physical processes in
the feeding dynamics of two larval sciaenids Sciaenops ocellatus and Cynoscion
nebulosus. Marine Ecology Progress Series 193:181-190.
Hoss, D. E., L. C. Coston, and W. E. Schaaf. 1974. Effects of seawater extracts of
sediments from Charleston Harbor, S. C., on larval estuarine fishes. Estuarine and
Coastal Marine Science 2:323-328.
- 123 -
Houde, E. D. and J. A. Lovdal. 1984. Seasonality of occurrence, foods and food
preferences of ichthyoplankton in Biscayne Bay, Florida. Estuarine, Coastal and
Shelf Science 18(4):403-419.
Howe, J. C. 2001. Diet Composition of juvenile pigfish, Orthopristis chrysoptera
(Perciformes: Haemulidae), from the Northern Gulf of Mexico. Gulf of Mexico
Science 19(1):55-60.
Hughes J. E., L. A. Deegan, J. C. Wyda, M. J. Weaver, and A. Wright. 2002. The effects
of eelgrass habitat loss on estuarine fish communities of southern New England.
Estuaries 25(2):235-249.
Hughes, R. M. 1989. The IBI: a quantitative, easily communicated assessment of the
health and complexity of entire fish communities. In Proceedings of the Southeast
Stream Ecology Workshop, United States Fish and Wildlife Service Biological
Report 90(5):26-28.
Hughes, R. M., P. R. Kaufmann, A. T. Herlihy, T. M. Kincaid, L. Reynolds, and D. P.
Larsen. 1998. A process for developing and evaluating indices of fish assemblage
integrity. Canadian Journal of Fisheries and Aquatic Science 55:1618-1631.
- 124 -
Hughes, R. M., D. P. Larsen and J. M. Omernik. 1986. Regional reference sites: a method
for assessing stream pollution. Environmental Management 10:629-635.
Hughes, R. M. and R. F. Noss. 1992. Biological diversity and biological integrity:current
concerns for lakes and streams. Fisheries 17(3):11-19.
Hughes, R. M. and T. Oberdorff. 1999. Applications of IBI concepts and metrics to
waters outside the United States and Canada, p. 79-93. In T. P. Simon (ed.),
Assessing the Sustainability and Biological Integrity of Water Resources Using
Fish Communities. CRC Press, New York.
Hyland, J. L., L. Balthis, C. T. Hackney, G. McRae, A. H. Ringwood, T. R. Snoots, R. F.
Van Dolah, and T. L. Wade. 1998. Environmental quality of estuaries of the
Carolinian Province: 1995. Annual statistical summary for the 1995 EMAP-
Estuaries Demonstration Project in the Carolinian Province. National Oceanic and
Atmospheric Administration Technical Memorandum, NOS ORCA 123, National
Ocean Service, Office of Ocean Resources Conservation and Assessment, Silver
Spring, Maryland.
Hyland, J. L., R. F. Van Dolah, and T. R. Snoots. 1999. Predicting stress in benthic
communities of southeastern U. S. estuaries in relation to chemical contamination
of sediments. Environmental Toxicology and Chemistry. 18(11):2557-2564.
- 125 -
Irlandi, E. A. and M. E. Mehlich. 1996. The effect of tissue cropping and disturbance by
browsing fishes on growth of two species of suspension-feeding bivalves. Journal
of Experimental Marine Biology and Ecology 197:279-293.
Irwin, R. J. 1970. Geographic varation, systematics, and general biology of shore fishes
of the genus Menticirrhus, family Sciaenidae. Doctoral Dissertation, Tulane
University, New Orleans, Louisiana.
Jackson, C. D. 1990. Recruitment of fish larvae to shallow estuarine habitats along a
salinity gradient. Master’s Thesis, College of Charleston, Charleston, South
Carolina.
Jannke, T. E. 1971. Abundance of young Sciaenid fishes in Everglades National Park,
Florida in relation to season and other variables. University of Miami Sea Grant
Technical Bulletin 11:1-128.
Javonillo, R. 2004. A systematic study of the Blenniid genus Chasmodes (Teleostei:
Perciformes). Master’s Thesis, College of Charleston, Charleston, South Carolina.
Johnson, B. L. and D. B. Noltie. 1997. Demography, growth, and reproductive allocation
in stream-spawning longnose gar. Transactions of the American Fisheries Society
126(3):438-466.
- 126 -
Johnson, G. D. 1978. Development of fishes of the mid-Atlantic Bight: an atlas of egg,
larval and juvenile stages. Volume 4: Carrangidae through Ephippidae. United
States Fish and Wildlife Service Office of Biological Services FWS/OBS-78/12,
Fort Collins, Colorado.
Johnson, L. L., J. T. Landahl, L. A. Kubin, B. H. Horness, M. S. Myers, T. K. Collier,
and J. E. Stein. 1998. Assessing the effects of anthropogenic stressors in Puget
Sound flatfish populations. Journal of Sea Research 39:125-137.
Johnson, W. S., D. M. Allen, M. V. Ogburn, and S. E. Stancyk. 1990. Short-term
predation responses of adult bay anchovies Anchoa mitchilli to estuarine
zooplankton availability. Marine Ecology Progress Series 64(1-2):55-68.
Jones, P. W., F. D. Martin, and J. D. Hardy, Jr. 1978. Development of fishes of the Mid-
Atlantic Bight: an atlas of eggs, larval and juvenile stages. Volume 1:
Acipenseridae through Ictaluridae. United States Fish and Wildlife Service Office
of Biological Services FWS/OBS-78/12, Fort Collins, Colorado.
Jørgensen, S.E. (ed.). 1979. Handbook of environmental data and ecological parameters.
International Society of Ecological Modelling, Copenhagen, Denmark.
- 127 -
Joyeux, J. -C. 1998. Spatial and temporal entry patterns of fish larvae into North Carolina
estuaries: comparisons among one pelagic and two demersal species. Estuarine,
Coastal and Shelf Science 47(6):731-752.
Joyeux, J. -C. 1999. The abundance of fish larvae in estuaries: within-tide variability at
inlet and immigration. Estuaries 22(4):889-904.
June, F. C. and F. T. Carlson. 1971. Food of young Atlantic menhaden, Brevoortia
tyrannus, in relation to metamorphosis. Fishery Bulletin 68:493-512.
Jutte, P. C., G. H. M. Riekerk, R. F. Van Dolah, S. E. Crowe, and M. V. Levison. 2004.
An assessment of the habitat quality of tidal creeks used by recreationally
important finfish species. Final report submitted to the United States Fish and
Wildlife Service. South Carolina Department of Natural Resources, Charleston,
South Carolina.
Karr, J. R. 1981. Assessment of biotic integrity using fish communities. Fisheries
6(6):21-27.
Karr, J. R. 1991. Biological integrity: a long-neglected aspect of water resource
management. Ecological Applications 1(1):66-84.
Karr, J. R. 1999. Defining and measuring river health. Freshwater Biology 41:221-234.
- 128 -
Karr, J. R. and E. W. Chu. 1997. Biological monitoring and assessment: using
multimetric indexes effectively. EPA 235-R97-001. University of Washington,
Seattle, Washington.
Karr, J. R. and D. R. Dudley. 1981. Ecological perspective on water quality goals.
Environmental Management 5:55-68.
Karr, J. R., K. D. Fausch, P. L. Angermeier, P. R. Yant, and I. J. Schlosser. 1986.
Assessing biological integrity in running waters: a method and its rationale.
Illinois Natural History Survey Special Publication 5, Champaign, Illinois.
Karr, J. R., P. R. Yant, and K. D. Fausch. 1987. Spatial and temporal variability of the
index of biotic integrity in three Midwestern streams. Transactions of the
American Fisheries Society 116(1):1-11.
Keefe, M. L. and K. W. Able. 1994. Contributions of abiotic and biotic factors to
settlement in summer flounder, Paralichthys dentatus. Copeia 2:458-465.
Keith, P., O. -Y. Le Bail, and P. Planquett. 2000. Atlas des poissons d'eau douce de
Guyane, Tome 2, Fascicule I. Publications scientifiques du Museum National
D’histoire Naturelle, Paris, France.
- 129 -
Kendall, Jr. A. W. 1972. Description of black sea bass, Centropristis striata (Linnaeus),
larvae and their occurrences north of Cape Lookout, North Carolina, in 1966.
Fishery Bulletin 70:1243-1260.
Kendall, Jr. A. W. 1977. Biological and fisheries data on black sea bass, Centropristis
striata (Linnaeus). National Oceanic and Atmospheric Administration, National
Marine Fisheries Service, Northeast Fisheries Center Technical Series Report 7,
National Oceanic and Atmospheric Administration, National Marine Fisheries
Service, Highlands, New Jersey.
Kennish, M. J. 2002. Environmental threats and environmental future of estuaries.
Environmental Conservation 29(1):78-107.
Khattree, R. and D. N. Naik. 2000. Multivariate data reduction and discrimination with
SAS software. SAS Institute Inc., Cary, North Carolina.
Kime, D. E. 1995. The effects of pollution on reproduction in fish. Reviews in Fish
Biology and Fisheries 5:52-96.
Kimura, R., D. H. Secor, E. D. Houde, and P. M. Piccoli. 2000. Up-estuary dispersal of
young-of-the-year bay anchovy Anchoa mitchilli in the Chesapeake Bay:
inferences from microprobe analysis of strontium in otoliths. Marine Ecology
Progress Series 208:217-227.
- 130 -
Kjelson, M. A. and G. N. Johnson. 1976. Further observations of the feeding ecology of
postlarval pinfish, Lagodon rhomboides, and the spot, Leiostomus xanthurus.
Fishery Bulletin 74(2):423-432.
Kjelson, M. A., D. S. Peters, G. W. Thayer, and G. N. Johnson. 1975. The general
feeding ecology of postlarval fishes in the Newport River estuary. Fishery
Bulletin 73(1):137-144.
Klauda, R. J. and M. E. Bender. 1987. Contaminant effects on Chesapeake Bay finfishes,
p. 321-371. In S. K. Majumdar, L. W. Hall, and H. M. Austin (eds.), Contaminant
Problems and Management of Living Chesapeake Bay Resources Pennsylvania
Academy of Science, Easton, Pennsylvania.
Klecka, W. R. 1980. Discriminant analysis. Sage Publications, Beverly Hills, California.
Kleynhans, C. J. 1999. The development of a fish index to assess the biological integrity
of South African rivers. Water South Africa 25(3):265-278.
Klima, E. F. 1959. Aspects of the biology and the fishery for Spanish mackerel
Scomberomorus maculatus (Mitchill) of southern Florida. Florida Board of
Conservation Marine Resources Laboratory, Technical Series 27.
- 131 -
Kobelkowsky, D. A. and M. Castillo Rivera. 1995. Digestive system and feeding of the
catfish (Pisces: Ariidae) of the Gulf of Mexico. Hidrobiologica (Iztapalapa) 5(1-
2):95-103.
Kobylinski, G. J. and P. F. Sheridan. 1979. Distribution, abundance, feeding and long-
term fluctuations of spot, Leiostomus xanthurus, and croaker, Micropogonias
undulatus, in Apalachicola Bay, Florida, 1972-1977. Contributions to Marine
Science 22:149-161.
Koli, A. K., W. R. Williams, E. B. McClary, E. L. Wright, and T. M. Burrell. 1977.
Mercury levels in freshwater fish of the state of South Carolina. Bulletin of
Environmental Contamination and Toxicology 17(1):82-89.
Krebs, C. J. 1972. Ecology: the experimental analysis of distribution and abundance.
Harper and Row Publishers, New York.
Lachenbruch, P. A. 1967. An almost unbiased method of obtaining confidence intervals
for the probability of misclassification in discriminant analysis. Biometrics
23:639-645.
Lachenbruch, P. A. and M. R. Mickey. 1968. Estimation of error rates in discriminant
analysis. Technometrics 10:1-11.
- 132 -
Lankford, Jr. T. E. and T. E. Targett. 1994. Suitability of estuarine nursery zones for
juvenile weakfish (Cynoscion regalis): effects of temperature and salinity on
feeding, growth and survival. Marine Biology 119(4):611-620.
Larson, E. T. and A. L. Shanks. 1996. Consumption of marine snow by two species of
juvenile mullet and its contribution to their growth. Marine Ecology Progress
Series 130(1-3):19-28.
Layman, C. A. 2000. Fish assemblage structure of the shallow ocean surf-zone on the
eastern shore of Virginia barrier islands. Estuarine, Coastal and Shelf Science
51:201-213.
Lebo, M. E. and J. H. Sharp. 1993. Distribution of phosphorus along the Delaware, an
urbanized coastal plain estuary. Estuaries 16(2):290-301.
Lee, D. S., C. R. Gilbert, C. H. Hocutt, R. E. Jenkins, D. E. McAllister, and J. R. Stauffer,
Jr. (eds.). 1981. Atlas of North American freshwater fishes. North Carolina State
Museum of Natural History, Raleigh, North Carolina.
Lenanton, R. C. J. 1982. Alternative non-estuarine nursery habitats for some
commercially and recreationally important fish species of South-western
Australia. Australia Journal of Marine and Freshwater Research 33:881-900.
- 133 -
Lenanton, R. C. J. and I. C. Potter. 1987. Contributions of estuaries to commercial
fisheries in temperate western Australia and the concept of estuarine dependence.
Estuaries 10(1):28-35.
Leonard, J. 1997. The energetics of swimming and upstream migration in adult American
shad (Alosa sapidissima) in the Connecticut River. Doctoral dissertation,
University of Massachusetts, Amherst, Massachusetts.
Leonard, P. M. and D. J. Orth. 1986. Application and testing of an index of biotic
integrity in small, coolwater streams. Transactions of the American Fisheries
Society 115:401-414.
Leppakoski, E. 1977. Monitoring the benthic environment of organically polluted river
mouths, 125-132. In J. S. Alabaster (ed.), Biological Monitoring of Inland
Fisheries, Applied Science Publishers, Barking, Essex, United Kingdom.
Lerberg, S. B., A. F. Holland, and D. M. Sanger. 2000. Responses of tidal creek
macrobenthic communities to the effects of watershed development. Estuaries
23(6):838-853.
Lewis, R. M. 1966. Effects of salinity and temperature on survival and development of
larval Atlantic menhaden, Brevoortia tyrannus. Transactions of the American
Fisheries Society 95:423-426.
- 134 -
Lewis, R. M. and W. C. Mann. 1971. Occurrence and abundance of larval Atlantic
menhaden, Brevoortia tyrannus, at two North Carolina inlets with notes on
associated species. Transactions of the American Fisheries Society 100:296-301.
Limburg, K. E. 1996a. Growth and migration of 0-year American shad (Alosa
sapidissima) in the Hudson River estuary: otolith microstructural analysis.
Canadian Journal of Fisheries and Aquatic Science 53(1):220-238.
Limburg, K. E. 1996b. Modelling the ecological constraints on growth and movement of
juvenile American shad (Alosa sapidissima) in the Hudson River estuary.
Estuaries 19(4):794-813.
Lindquist, D. G. and R. M. Dillaman. 1986. Trophic morphology of four western Atlantic
blennies (Pisces: Blenniidae). Copeia 1986:207-213.
Link, Jr. G. W. 1980. Age, growth, reproduction, feeding, and ecological observations on
the three species of Centropristis (Pisces, Serranidae) in North Carolina waters.
Doctoral Dissertation, University of North Carolina at Chapel Hill, Chapel Hill,
North Carolina.
Linton, E. 1901. Parasites of the fishes of the Woods Hole region. Bulletin of the United
States Fisheries Commerce 19(1899):405-492.
- 135 -
Linton, E. 1904. Parasites of fishes of Beaufort, North Carolina. United States Bureau
Fishery Bulletin 24:321-428.
Liu, W. X., X. D. Li, Z. G. Shen, D. C. Wang, O. W. H. Wai, and Y. S. Li. 2003.
Multivariate statistical study of heavy metal enrichment in sediments of the Pearl
River Estuary. Environmental Pollution 121(3):377-388.
Livingston, R. J. 1976. Diurnal and seasonal fluctuations of organisms in a north Florida
estuary. Estuarine and Coastal Marine Science 4:373-400.
Llanso, R. J., S. S. Bell, and F. E. Vose. 1998. Food habits of red drum and spotted
seatrout in a restored mangrove impoundment. Estuaries 21(2):294-306.
Long, E. R., G. I. Scott, J. Kucklick, M. Fulton, B. Thompson, R. S. Carr, K. J. Scott, G.
B. Thursby, G. T. Chandler, J. W. Anderson, and G. M. Sloane. 1995. Final
report: magnitude and extent of sediment toxicity in selected estuaries of South
Carolina and Georgia. National Oceanic and Atmospheric Administration
Technical Memorandum 128, National Oceanic and Atmospheric Administration,
National Ocean Service, Ocean Resources Conservation and Assessment, Silver
Spring, Maryland.
- 136 -
Luczkovich, J. J., M. W. Sprague, S. E. Johnson, and R. C. Pullinger. 1999. Delimiting
spawning areas of weakfish Cynoscion regalis (family Sciaenidae) in Pamlico
Sound, North Carolina using passive hydroacoustic surveys. Bioacoustics 10(2-
3):143-160.
Lyons, J., L. Wang, and T. D. Simonson. 1996. Development and validation of an index
of biotic integrity for coldwater streams in Wisconsin. North American Journal of
Fishery Management 16:241-256.
Mallin, M. A., E. C. Esham, K. E. Williams, and J. E. Nearhoof. 1999a. Tidal stage
variability of fecal coliform and chlorophyll a concentrations in coastal creeks.
Marine Pollution Bulletin 38(5):414-422.
Mallin, M. A., M. H. Posey, G. C. Shank, M. R. McIver, S. H. Ensign, and T. D. Alphin.
1999b. Hurricane effects on water quality and benthos in the Cape Fear
watershed: natural and anthropogenic impacts. Ecological Applications 9(1)350-
362.
Manderson, J. P., B. A. Phelan, A. W. Stoner, and J. Hilbert. 2000. Predator-prey
relations between age-1+ summer flounder (Paralichthys dentatus, Linnaeus) and
age-0 winter flounder (Pseudopleuronectes americanus, Walbaum): predator
diets, prey selection, and effects of sediments and macrophytes. Journal of
Experimental Marine Biology and Ecology 251(1):17-39.
- 137 -
Margalef, D. R. 1958. Information theory in ecology. General Systems 3:36-71.
Martin, F. H. and G. E. Drewry. 1978. Development of fishes of the Mid-Atlantic Bight.
In Atlas of eggs, larval and juvenile stages, Volume 4, Carangidae through
Ephippidae. United States Fish and Wildlife Service Biological Service Program
FWS/OBS-78/12.
Martore, R. M. 1986. Feeding habits and trophic relationships of fishes in wetland
impoundments. Master’s Thesis, College of Charleston, Charleston, South
Carolina.
Massmann, W. H. 1952. Characteristics of spawning areas of shad, Alosa sapidissima
(Wilson), in some Virginia streams. Transactions of the American Fisheries
Society 81:78-93.
Massmann, W. H. 1954. Marine fishes in fresh and brackish waters of Virginia rivers.
Ecology 35(1):75-78.
Massmann, W. H., E. C. Ladd, and H. N. McCutcheon. 1954. Postlarvae and young of
the menhaden (Brevoortia tyrannus) in brackish and fresh waters of Virginia.
Copeia 1954:19-23.
- 138 -
Massmann, W. H., J. P. Whitcomb, and A. L. Pacheco. 1958. Distribution and abundance
of gray weakfish in the York River system, Virginia. Transactions of North
American Wildlife and Natural Resources Conference 23:361-369.
Matheson, Jr. R. E. and J. D. McEachran. 1984. Taxonomic studies of the Eucinostomus
argenteus complex (Pisces: Gerreidae): preliminary studies of external
morphology. Copeia 1984(4):893-902.
Matheson, Jr. R. E. and R. G. Gilmore, Jr. 1995. Mojarras (Pisces: Gerreidae) of the
Indian River Lagoon. Bulletin of Marine Science 57(1):281-285.
McBride, R. S., T. C. MacDonald, R. E. Matheson, Jr., D. A. Rydene, and P. B. Hood.
2001. Nursery habitats for ladyfish, Elops saurus, along salinity gradients in two
Florida estuaries. Fishery Bulletin 99(3):443-458.
McCain, B. B., D. W. Brown, T. Hom, M. S. Myers, S. M. Pierce, T. K. Collier, J. E.
Stein, S. L. Chan, and U. Varanasi. 1996. Chemical contaminant exposure and
effects in four fish species from Tampa Bay, Florida. Estuaries 19(1):86-104.
McClelland J. W., I. Valiela, and R. H. Michener. 1997. Nitrogen-stable isotope
signatures in estuarine food webs: a record of increasing urbanization in coastal
watersheds. Limnology and Oceanography 42 (5):930-937.
- 139 -
McDowall, R. M. 1988. Diadromy in fishes: migrations between freshwater and marine
environments. Timber Press, Portland, Oregon.
McEachran, J. D. and B. Seret. 1990. Gymnuridae, p. 64-66. In J. C. Quero, J. C. Hureau,
C. Karrer, A. Post, and L. Saldanha (eds.), Check-list of the Fishes of the Eastern
Tropical Atlantic (CLOFETA), Volume 1. United Nations Educational, Scientific
and Cultural Organization, Paris, France.
McEachran, J. D., J. H. Finucane, and L. S. Hall. 1980. Distribution, seasonality and
abundance of king and Spanish mackerel larvae in the northwestern Gulf of
Mexico (Pisces: Scombridae). Northeast Gulf Science 4(1):1-16.
McGovern, J. C. 1986. Seasonal recruitment of larval and juvenile fishes into impounded
and non-impounded marshes. Master’s Thesis, College of Charleston, Charleston,
South Carolina.
McHugh, J. L. 1966. Management of estuarine fishes. A Symposium on Estuarine
Fisheries, American Fisheries Society Special Publication 3:133-154.
McHugh, J. L. 1967. Estuarine nekton, p. 581-620. In G.H. Lauff (ed.), Estuaries.
American Association of Advanced Science Publication No. 83, Washington, DC.
- 140 -
McIvor, C. C. and W. E. Odum. 1988. Food, predation risk, and microhabitat selection in
a marsh fish assemblage. Ecology 69(5):1341-1351.
McMichael, Jr. R. H. and S. T. Ross. 1987. The relative abundance and feeding habits of
juvenile kingfish (Sciaenidae: Menticirrhus) in a Gulf of Mexico surf zone.
Northeast Gulf Science 9(2):109-123.
Mebane, C. A. 2001. Testing bioassessment metrics: macroinvertebrate, sculpin, and
salmonid responses to stream habitat, sediment, and metals. Environmental
Monitoring and Assessment 67(3):293-322.
Menezes, M. F. 1970. Feeding habits of Spanish mackerel, Scomberomorus maculatus
Mitchill, in coastal waters of the state of Ceara. Arquivos de Ciencias do Mar
10(2):171-176.
Meng, L. March 17, 2004. Personal communication. United States Environmental
Protection Agency (USEPA), Narragansett, Rhode Island.
Meng, L., C. D. Orphanides, and J. C. Powell. 2002. Use of a fish index to assess habitat
quality in Narragansett Bay, Rhode Island. Transactions of the American
Fisheries Society 131:731-742.
- 141 -
Meng, L. and J. C. Powell. 1999. Linking juvenile fish and their habitats:An example
from Narragansett Bay, Rhode Island. Estuaries 22:905.
Meng L., J. C. Powell, and B. Taplin. 2001. Using winter flounder growth rates to assess
habitat quality across an anthropogenic gradient in Narragansett Bay, Rhode
Island. Estuaries 24 (4):576-584.
Merriner, J. V. 1975. Food habits of the weakfish, Cynoscion regalis, in North Carolina
waters. Chesapeake Science 16:74-76.
Merriner, J. V. 1976. Aspects of the reproductive biology of the weakfish, Cynoscion
regalis (Sciaenidae), in North Carolina. Fishery Bulletin 74(1):18-26.
Mertler, C. A. and R. A. Vannatta, 2002. Advanced and multivariate statistical methods:
practical application and interpretation, 2nd ed. Pryczak Publishing, Los Angeles,
California.
Migdalski, E. C. 1958. Angler's guide to the salt water game fishes, Atlantic and Pacific.
Ronald Press, New York.
Miglarese, J. V. and P. A. Sandifer. 1982. An ecological characterization of South
Carolina wetland impoundments. South Carolina Department of Natural
- 142 -
Resources, Marine Resources Research Institute, South Carolina Wildlife and
Marine Resources Department, Charleston, South Carolina.
Miller, D. L., P. M. Leonard, R. M. Hughes, J. R. Karr, P. B. Moyle, L. H. Schrader, B.
A. Thompson, R. A. Daniels, K. D. Fausch, G. A. Fitzhugh, J. R. Gammon, D. B.
Haliwell, P. L. Angermeir, and D. J. Orth. 1988. Regional applications of an
index of biotic integrity for use in water resource management. Fisheries 13:12-
20.
Miller, J. M., J. S. Burke, and G. R. Fitzhugh. 1991. Early life history patterns of Atlantic
North American flatfish: likely (and unlikely) factors controlling recruitment.
Netherlands Journal of Sea Research 27:261-275.
Miller, M. J. and K. W. Able. 2002. Movements and growth of tagged young-of-the-year
Atlantic croaker (Micropogonias undulatus L.) in restored and reference marsh
creeks in Delaware Bay, USA. Journal of Experimental Marine Biology and
Ecology 267(1):15-33.
Miller, M. J., P. M. Rowe, and K. W. Able. 2002. Occurrence and growth rates of young-
of-year Northern kingfish, Menticirrhus saxatilis, on ocean and estuarine beaches
in southern New Jersey. Copeia 2002(3):815-823.
- 143 -
Miller, R. R. 1960. Sytematics and biology of the gizzard shad (Dorosoma cepedianum)
and related species. Fishery Bulletin 60:371-392.
Miller, R. R. 1963. Genus Dorosoma Rafinesque 1820, gizzard shads, threadfin shad, p.
443-451. In H. B. Bigelow, C. M. Breder, D. M. Cohen, G. W. Mead, D.
Merriman, Y. H. Olsen, W. C. Schroeder, L. P. Schultz, and J. Tee-Van (eds.),
Fishes of the Western North Atlantic No. 1, Part 3. Memoirs of the Sears
Foundation for Marine Research, Yale University, New Haven, Connecticut.
Miltner, R. J., S. W. Ross, and M. H. Posey. 1995. Influence of food and predation on the
depth distribution of juvenile spot (Leiostomus xanthurus) in tidal nurseries.
Canadian Journal of Fisheries and Aquatic Sciences 52(5):971-982.
Minello, T. J., R. J. Zimmerman, and T. E. Czapla. 1989. Habitat-related differences in
diets of small fishes in Lavaca Bay, Texas, 1985-1986. National Oceanic and
Atmospheric Administration Technical Memorandum SEFC-NMFS-236,
National Oceanic and Atmospheric Administration, National Marine Fisheries
Service.
Modde, T. 1980. Growth and residency of juvenile fishes within a surf zone habitat in the
Gulf of Mexico. Gulf Research Reports 6(4):377-385.
- 144 -
Modde, T. and S. T. Ross. 1983. Trophic relationships of fishes occurring within a surf
zone habitat in the northern Gulf of Mexico. Northeast Gulf Science 6(2):109-
120.
Mol, J. H., J. S. Ramlal, C. Lietar, and M. Verloo. 2001. Mercury contamination in
freshwater, estuarine, and marine fishes in relation to small-scale gold mining in
Suriname, South America. Environmental Research 86(2):183-197.
Moore M. J., D. Shea, R. E. Hillman, and J. J. Stegeman. 1996. Trends in hepatic
tumours and hydropic vacuolation, fin erosion, organic chemicals and stable
isotope ratios in winter flounder from Massachusetts, USA. Marine Pollution
Bulletin 32(6):458-470.
Moore, R. H. 1974. General ecology, distribution and relative abundance of Mugil
cephalus and Mugil curema on the South Texas coast. Contributions to Marine
Science 18:241-255.
Morrison, D. F. 1976. Multivariate Statistical Methods. 2nd ed. McGraw-Hill Book
Company, New York.
Morrow, J. E. 1980. The freshwater fishes of Alaska. Alaska Northwest Publishing
Company, Anchorage, Alaska.
- 145 -
Motta, P. J., K. B. Clifton, P. Hernandez, and B. T. Eggold. 1995. Ecomorphological
correlates in ten species of subtropical seagrass fishes: diet and microhabitat
utilization. Environmental Biology of Fishes 44(1-3):37-60.
Motta, P. J., K. B. Clifton, P. Hernandez, B. T. Eggold, S. D. Giordano, and R. Wilcox.
1993. Feeding relationships among nine species of seagrass fishes of Tampa Bay,
Florida. Bulletin of Marine Science 56(1):185-200.
Mulcahy, M. F., E. Twomey, A. Petersen, and C. T. Maye. 1987. Pathobiology of
estuarine fish and shellfish in relation to pollution, p. 201-210. In D. H. S.
Richardson (ed.), Proceedings of the Biological Indicators of Pollution Seminar,
Royal Irish Academy, Dublin, Ireland.
Murchelano, R. A. and R. E. Wolke. 1985. Epizootic carcinoma in the winter flounder,
Pseudopleuronectes americanus. Science 228:587-589.
Murdy, E. O., R. S. Birdsong, and J. A. Musick. 1997. Fishes of Chesapeake Bay.
Smithsonian Institution Press, Washington, DC.
Music, J. L. and J. M. Pafford. 1984. Population dynamics and life history aspects of
major marine sportfishes in Georgia’s coastal waters. Georgia Department of
Natural Resources Contribution Series 38, Georgia Department of Natural
Resources, Coastal Research Division, Brunswick, Georgia.
- 146 -
Musick, J. A. 1999. Criteria to define extinction risk in marine fishes. Fisheries 24(12):6-
14
Musick, J. A. and L.P. Mercer. 1977. Seasonal distribution of black sea bass,
Centropristis striata, in the Mid-Atlantic Bight with comments on the ecology
and fisheries of the species. Transactions of the American Fisheries Society
106:12-25.
Perry, M. and P. Mackun. 2001. Population change and distribution: 1990-2000. US
Census Bureau 2000 Brief C2KBR/01-2. US Department of Commerce, US
Census Bureau, Washington, DC.
National Ocean Service/National Oceanic and Atmospheric Administration Office of
Response and Restoration (NOAA/NOS). 2002. Complete ESI species list.
http://www.response.restoration.noaa.gov/esi/species.pdf. 2 July 2002.
Naughton, S. P. and C. H. Saloman. 1981. Stomach contents of juveniles of king
mackerel (Scomberomorus cavalla) and Spanish mackerel (S. maculatus).
Northeast Gulf Science 5(1):71-74.
Nelson, D. A., J. E. Miller, D. Rusanowsky, R. A. Sennefelder, G. R. Mercaldo-Allen, C.
Kuropat, E. Gould, F. P. Thurberg, and A. Calabrese. 1991a. Comparative
- 147 -
reproductive success of winter flounder in Long Island Sound: a 3-year study
(biology, biochemistry, and chemistry). Estuaries 14:318-331.
Nelson, D. M., M. E. Monaco, E. A. Irlandi, L. R. Settle, and L. Coston-Clements.
1991b. Distribution and abundance of fishes and invertebrates in southeast
estuaries. Estuarine Living Marine Resources Report 9, National Oceanic and
Atmospheric Administration/National Ocean Service Strategic Environmental
Assessment Division, Silver Spring, Maryland.
Nelson, J. S. 1994. Fishes of the world, 3rd ed. John Wiley and Sons, New York.
Netsch, N. F. and A. Witt, Jr. 1962. Contributions to the life history of the longnose gar
(Lepisosteus osseus) in Missouri. Transactions of the American Fisheries Society
91:251-262.
Ocana-Luna, A. and M. Sanchez-Ramirez. 1999. Feeding of sciaenid (Pisces: Sciaenidae)
larvae in two coastal lagoons of the Gulf of Mexico. Gulf Research Report 10:1-9.
Odum, W. E. 1970. Utilization of the direct grazing and plant detritus food chains by the
striped mullet Mugil cephalus, pp. 222-240. In J. Steele (ed.), Marine Food
Chains Symposium, University of Califrnia Press, Berkeley, California.
- 148 -
Odum, W. E. and E. J. Heald. 1972. Trophic analysis of an estuarine mangrove
community. Bulletin of Marine Science 22:671-738.
Ogburn, M. V., D. M. Allen, and W. K. Michener (eds.). 1988. Fishes, shrimps, and crabs
of the North Inlet Estuary, SC: a four-year seine and trawl survey. Baruch
Institute Technical Report Series 88-1, University of South Carolina, Columbia,
South Carolina.
Ogburn-Matthews, M. and D. M. Allen. 1993. Interactions among some dominant
estuarine nekton species. Estuaries 16(4):840-850.
Ohio Environmental Protection Agency (EPA). 1988. Biological criteria for the
protection of aquatic life: Volumes I-III. Division of Water Quality Monitoring
and Assessment, Surface Water Section, Columbus, Ohio.
Olla, B. L., C. E. Samet, and A. L. Studholme. 1972. Activity and feeding behavior of the
summer flounder (Paralichthys dentatus) under controlled laboratory conditions.
Fishery Bulletin 70(4):1127-1136.
Olney, J. E. and G. C. Grant. 1976. Early planktonic larvae of the blackcheek tonguefish,
Symphurus plagiusa (Pisces: Cynoglossidae), in the Lower Chesapeake Bay.
Chesapeake Science 17(4):229-237.
- 149 -
Owen, R. D., R. L. Bedenbaugh, and R. S. Birdsong. 1984. Seasonality and abundance of
demersal fishes in an industrialized estuary. Virginia Journal of Science
35(2):117.
Pacheco, A. L. 1962. Age and growth of spot in lower Chesapeake Bay, with notes on
distribution and abundance of juveniles in the York River system. Chesapeake
Science 3:18-28.
Paller, M. H. 1994. Relationships between fish assemblage structure and stream order in
South Carolina coastal plain streams. Transactions of the American Fisheries
Society 123:150-161.
Paller, M. H., M. J. M. Reichert, and J. M. Dean. 1996. Use of fish communities to assess
environmental impacts in South Carolina Coastal Plain streams. Transactions of
the American Fisheries Society 125(5):633-644.
Parsons, G. R. 1981. Growth and reproduction of the Atlantic sharpnose shark
Rhizoprionodon terraenovae (Richardson). Master’s Thesis, University of South
Alabama, Mobile, Alabama.
Parsons, G. R. 1983. The reproductive biology of the Atlantic sharpnose shark,
Rhizoprionodon terraenovae (Richardson). Fishery Bulletin 81(1):61-74.
- 150 -
Pattillo, M. E., T. E. Czapla, D. M. Nelson, and M. E. Monaco. 1997. Distribution and
abundance of fishes and invertebrates in Gulf of Mexico estuaries, Volume 2,
species life history summaries. Estuarine Living Marine Resources Report 9
Report No. 11, National Oceanic and Atmospheric Administration/National
Ocean Service Strategic Environmental Assessments Division, Rockville,
Maryland.
Pearcy, W. G. and S. W. Richards. 1962. Distribution and ecology of fishes of the Mystic
River estuary, Connecticut. Ecology 43:248-259.
Pearson, J. C. 1928. Natural history and conservation of the redfish and other commercial
sciaenids of the Texas Gulf. Bulletin of the United States Bureau of Fisheries
44:129-214.
Pearson T. H. and R. Rosenberg. 1978. Macrobenthic succession in relation to organic
enrichment and pollution of the marine environment. Oceanography and Marine
Biology Annual Review 16:229-311.
Peebles, E. B. and S. G. Tolley. 1988. Distribution, growth, and mortality of larval
spotted seatrout, Cynoscion nebulosus: a comparison between two estuarine areas
of southwest Florida. Bulletin of Marine Science 42(3):397-410.
- 151 -
Perry, J. A., R. C. Ward, and J. C. Loftis. 1984. Survey of state water quality monitoring
programs. Environmental Management 8:21-26.
Peters, D. W. and W. E. Schaaf. 1981. Food requirements and sources for juvenile
Atlantic menhaden. Transactions of the American Fisheries Society 110:317-324.
Peterson, T. L. 1996. Seasonal migration in the southern hogchoker, Trinectes maculatus
fasciatus (Achiridae). Gulf Research Report 9(3):169-176.
Pew, P. (ed.) 1971. Food and game fishes of Texas coast. Texas Parks and Wildlife
Department Bulletin 33, Series 4, Marine Laboratory, Austin, Texas.
Phillips, R. R. 1977. The relationship between social behaviour and the use of space in
the benthic fish Chasmodes bosquianus Lacepede (Teleostei, Blenniidae). 4.
Effects of topography on habitat selection and shelter choice. Behaviour 60(1-
2):1-27.
Pielou, E. C. 1966. The measurement of diversity in different types of biological
collections. Journal of Theoretical Biology 13:131-144.
Pierce, D. J. and B. Mahmoudi. 2001. Nearshore fish assemblages along the central west
coast of Florida. Bulletin of Marine Science 68(2):243-270.
- 152 -
Pihl, L., S. P. Baden, and R. J. Diaz. 1991. Effects of periodic hypoxia on distribution of
demersal fish and crustaceans. Marine Biology 108(3):349-360.
Plafkin, J. L., M. T. Barbour, K. D. Porter, S. K. Gross, and R. M. Hughes. 1989. Rapid
bioassessment protocols for use in streams and rivers: benthic macroinvertebrates
and fish. EPA 440-4-89-001. Office of Water Regulations and Standards. US
Environmental Protection Agency, Washington, DC.
Potter, I. C., N. R. Loneragan, R. C. J. Lenanton, P. J. Chrystal, and C. J. Grant. 1983.
Abundance, distribution and age structure of fish populations in a Western
Australian estuary. Journal of Zoology 200(1):21-50.
Powell, A. B. and R. E. Robbins. 1998. Ichthyoplankton adjacent to live-bottom habitats
in Onslow Bay, North Carolina. United States Department of Commerce,
National Oceanic and Atmospheric Administration Technical Report National
Marine Fisheries Service 133.
Powell, A. B. and F. J. Schwartz. 1979. Food of Paralichthys dentatus and P. lethostigma
(Pisces:Bothidae) in North Carolina estuaries. Estuaries 2(4):276-279.
Powell, D. 1975. Age, growth, and reproduction in Florida stocks of Spanish mackerel,
Scomberomorus maculatus. Florida Marine Research Publication 5, Florida
- 153 -
Marine Research Institute, Florida Fish and Wildlife Conservation Commission,
St. Petersburg, Florida.
Powles, H. 1980. Descriptions of larval silver perch, Bairdiella chrysoura , banded drum,
Larimus fasciatus, and star drum, Stellifer lanceolatus (Sciaenidae). Fishery
Bulletin 78(1):119-136.
Powles, H. 1981. Distribution and movements of neustonic young of estuarine dependent
(Mugil spp., Pomatomus saltatrix) and estuarine independent (Coryphaena spp.)
fishes off the southeastern United States. Rapport et Proces-Verbaux des
Reunions du Conseil International pour l'Exploration de la Mer (CIEM) 178:207-
209.
Powles, H. and B. W. Stender. 1978. Taxonomic data on the early life history stages of
Sciaenidae of the South Atlantic Bight of the United States. South Carolina
Marine Resources Center Technical Report No. 31, South Carolina Wildlife and
Marine Resources Department, Charleston, South Carolina.
Prista N., R. P. Vasconcelos, M. J. Costa, and H. Cabral. 2003. The demersal fish
assemblage of the coastal area adjacent to the Tagus estuary (Portugal):
relationships with environmental conditions. Oceanologica Acta 26(5-6):525-536.
- 154 -
Pritchard, D. W. 1955. Estuarine circulation patterns. Proceedings of the American
Society of Civil Engineers 81(717):1-11.
Pulsford, A. L., M. Crampe, A. Langston, and P. J. Glynn, 1995. Modulatory effects of
disease, stress, copper, TBT and vitamin E on the immune system of flatfish, Fish
and Shellfish Immunology 5:631-643.
Ramm, A. E. 1988. The community degradation index: a new method for assessing the
deterioration of aquatic habitats. Water Research 22:293-301.
Randall, J. E. 1967. Food habits of reef fishes of the West Indies. Studies in Tropical
Oceanography, Miami 5:665-847.
Randall, J. E. and W. D. Hartman. 1968. Sponge-feeding fishes of the West Indies.
Marine Biology 1:216-225.
Rasmussen, E. and R. W. Heard. 1995. Observations on extant populations of the
softshell clam, Mya arenaria Linne, 1758 (Bivalvia: Myidae), from Georgia
(USA) estuarine habitats. Gulf Research Report 9(2):85-96.
Reichert, M. J. M. 2002. On the life history the fringed flounder (Etropus crossotus,
Pleuronectiformes), a small tropical flatfish in the South Atlantic Bight. Doctoral
Dissertation, University of Groningen, Netherlands.
- 155 -
Reichert, M. J. M. and H. W. Van der Veer. 1991. Settlement, abundance, growth and
mortality of juvenile flatfish in a subtropical tidal estuary (Georgia, USA).
Netherlands Journal of Sea Research 27(3-4): 375-391.
Reid, Jr. G. K. 1954. An ecological study of the Gulf of Mexico fishes in the vicinity of
Cedar Key, Florida. Bulletin of Gulf and Caribbean Marine Science 4:1-94.
Reid, Jr. G. K. 1955. A summer study of the biology and ecology of East Bay, Texas. II.
The fish fauna of East Bay, the Gulf beach, and summary. Texas Journal of
Science 7:430-453.
Reid, Jr. G. K., A. Inglis, and H. D. Hoese. 1956. Summer foods of some fish species in
East Bay, Texas. The Southwestern Naturalist 1:100-104.
Reynoldson, T. B., R. H. Norris, V. H. Resh, K. E. Day, and D. M. Rosenberg. 1997. The
reference condition: a comparison of multimetric and multivariate approaches to
assess water-quality impairment using benthic macroinvertebrates. Journal of
North American Benthological Society 16(4):833-852.
Ringwood A. H. and C. J. Keppler. 2002. Water quality variation and clam growth: is pH
really a non-issue in estuaries? Estuaries 25(5):901-907.
- 156 -
Rivas, A., E. E. Mendez De, L. J. Ruiz, J. A. Torres De, and L. Martinez. 1999. The
feeding habits of Eucinostomus gula and E. argenteus (Pisces: Gerreidae) in the
Mochima Bay, Sucre State, Venezuela. Boletim del Instituto Oceanografico de
Venezuela 38(2):91-97.
Riviera-Arriaga, E., F. Arreguin-Sanchez, A. L. Lara-Dominguez, P. Sanchez-Gil, and A.
Yanez-Arancibia. 1994. Niche overlap in two tropical fishes Lutjanus synagris
and Polydactylus octonemus of the southern Gulf of Mexico. Fish Biology 45.
Robinette, H. R. 1983. Species profiles: life histories and environmental requirements of
coastal fishes and invertebrates (Gulf of Mexico), bay anchovy and striped
anchovy. United States Fish and Wildlife Service Office of Biological Services
FWS/OBS-82/11.14, Washington, DC.
Robins, C. R. and G. C. Ray. 1986. A field guide to Atlantic coast fishes of North
America, the Peterson field guide series. Houghton Mifflin, Boston,
Massachusetts.
Roelofs, E. W. 1954. Food studies of young sciaenid fishes, Micropogon and Leiostomus,
from North Carolina. Copeia 1954:151-53.
Rogers, B. D. and W. H. Herke. 1985. Estuarine-dependent fish and crustacean
movements and weir management, p. 201-219. In C. F. Bryan, P. J. Zwank, and
- 157 -
H. R. Chabreck (eds.), Proceedings of the Fourth Coastal Marsh and Estuary
Management Symposium, Louisiana State University Agricultural Center,
Louisiana Cooperative Fish and Wildlife Research Unit, Baton Rouge, Louisiana.
Rogers, I. H., J. S. Macdonald, and M. Sadar. 1992. Uptake of selected organochlorine
contaminants in fishes resident in the Fraser River Estuary, Vancouver, British
Columbia. Water Pollution Research Journal of Canada 27(4):733-749.
Rogers, J. S., J. A. Hare, and D. G. Lindquist. 2001. Otolith record of age, growth, and
ontogeny in larval and pelagic juvenile Stephanolepis hispidus (Pisces:
Monacanthidae). Marine Biology 138:945-953.
Rogers, S. G., T. E. Targett, and S. B. Van Sant. 1984. Fish-nursery use in Georgia salt-
marsh estuaries: The influence of springtime freshwater conditions. Transactions
of the American Fisheries Society 113(5):595-606.
Rooker, J. R., S. A. Holt, M. A. Soto, and G. J. Holt. 1998. Postsettlement patterns of
habitat use by sciaenid fishes in subtropical seagrass meadows. Estuaries
21(2):318-327.
Rosen, B. H. 1995. Use of periphyton in the development of biocriteria, p. 209-215. In
W. S. Davis and T. P. Simon (eds.), Biological assessment and criteria:tools for
- 158 -
water resources planning and decision making, Lewis Publishers, Boca Raton,
Louisiana.
Rosenberg, D. M. and V. H. Resh (eds.). 1993. Freshwater biomonitoring and benthic
macroinvertebrates. Chapman and Hall, New York.
Ross, J. L., J. S. Pavela, and M. E. Chittenden, Jr. 1989. Food habits of the rock sea bass,
Centropristis philadelphica, in the western Gulf of Mexico. Northeast Gulf
Science 10(2):139-152.
Ross, R. M., R. M. Bennett, and J. H. Johnson. 1997. Habitat use and feeding ecology of
riverine juvenile American shad. North American Journal of Fisheries
Management 17(4):964-974.
Ross, S. T. 1977. Patterns of resource partitioning in searobins (Pisces:Triglidae). Copeia
1977(3):561-571.
Ross, S. T. 1978. Trophic ontogeny of the leopard searobin, Prionotus scitulus (Pisces:
Triglidae). Fishery Bulletin 76:225-234.
Ross, S. T. 1983. Searobins (Pisces: Triglidae). Memoirs of the Hourglass Cruises 6(4).
- 159 -
Ross, S. W. and J. E. Lancaster. 2002. Movements and site fidelity of two juvenile fish
species using surf zone nursery habitats along the southeastern North Carolina
coast. Environmental Biology of Fishes 63:161-172.
Roth, N., M. Southerland, J. Chaillou, R. Klauda, P. Kazyak, S. Stranko, S. Weisberg, L.
Hall, Jr., and R. Morgan, II. 1998. Maryland biological stream survey:
development of a fish index of biotic integrity. Environmental Monitoring and
Assessment 51(1-2):89-106.
Roumillat, W. A. December 3, 2002a. Personal communication. South Carolina
Department of Natural Resources, Charleston, South Carolina.
Roumillat, W. A. December 17, 2002b. Personal communication. South Carolina
Department of Natural Resources, Charleston, South Carolina.
Roumillat, W. A. February 29, 2003. Personal communication. South Carolina
Department of Natural Resources, Charleston, South Carolina.
Rountree, R. A. 1990. Community structure of fishes attracted to shallow water fish
aggregation devices off South Carolina, USA. Environmental Biology of Fishes
29:241-262.
- 160 -
Rountree, R. A. and K. W. Able. 1992. Foraging habits, growth, and temporal patterns of
salt-marsh creek habitat use by young-of-year summer flounder in New Jersey.
Transactions of the American Fisheries Society 121(6):765-776.
Roux, C. 1986. Gerreidae, p. 325-326. In J. Daget, J. -P. Gosse, and D. F. E. Thys van
den Audenaerde (eds.), Check-list of the Freshwater Fishes of Africa (CLOFFA),
Volume 2. Office Recherche Scientifique and Technologique Outre Mer, Paris,
France.
Roux, C. 1990. Gerreidae, p. 781-782. In J. C. Quero, J. C. Hureau, C. Karrer, A. Post,
and L. Saldanha (eds.), Check-list of the Fishes of the Eastern Tropical Atlantic
(CLOFETA), Volume 2. United Nations Educational, Scientific and Cultural
Organization, Paris, France.
Rozas, L. P. and C. T. Hackney. 1984. Use of oligohaline marshes by fishes and
macrofaunal crustaceans in North Carolina. Estuaries 7:213-224.
Rozas, L. P. and T. J. Minello. 1998. Nekton use of salt marsh, seagrass, and
nonvegetated habitats in a south Texas (USA) estuary. Bulletin of Marine Science
63(3):481-501.
- 161 -
Ruiz, G. M., A. H. Hines, and M. H. Posey, 1993. Shallow water as a refuge habitat for
fish and crustaceans in non-vegetated estuaries: an examples from Chesapeake
Bay. Marine Ecology Progress Series 99:1-16.
Ruple, D. L. 1984. Occurrence of larval fishes in the surf zone of a northern Gulf of
Mexico barrier island. Estuarine Coastal and Shelf Science 18(2):191-208.
Ryder, C. 1993. Application of the estuarine Index of Biotic Integrity to Buttermilk Bay,
MA. Master’s Thesis, University of Massachusetts, Amherst, Massachusetts.
Sandifer, P., J. V. Miglarese, D.R. Calder, J.J. Manzi, and L.A. Barclay. (eds.). 1980.
Ecological characterization of the sea island coastal region of South Carolina and
Georgia, Volume 3, biological features of the characterization area. United States
Fish and Wildlife Service Office of Biological Service FWS/OBS-79/42,
Washington, DC.
Sanger, D. M., A. F. Holland, and G. I. Scott. 1999a. Tidal creek and salt marsh
sediments in South Carolina coastal estuaries. I. Distribution of trace metals.
Archives Environmental Contaminants and Toxicology 37:445-457.
Sanger, D. M., A. F. Holland, and G. I. Scott. 1999b. Tidal creek and salt marsh
sediments in South Carolina coastal estuaries. II. Distribution of organic
contaminants. Archives Environmental Contaminants and Toxicology 37:458-471.
- 162 -
SAS Institute. 2002a. JMP statistics and graphics guide, Version 5.0. SAS Institute
Incorporation, Cary, North Carolina.
SAS Institute. 2002b. SAS/STAT® user's guide, Version 8.01. SAS Institute
Incorporation, Cary, North Carolina.
Saylor, C. and E. M. Scott. 1987. Application of the index of biotic integrity to existing
TVA data. Tennessee Valley Authority Report TVA/ONRED/AWR-87/32,
Norris, Tennessee.
Sazima, I. 1986. Similarities in feeding behaviour between some marine and freshwater
fishes in two tropical communities. Journal of Fish Biology 29:53-65.
Schaaf, W. E., D. S. Peters, D. S., Vaughan, L. Coston-Clements, and C. W. Krouse.
1987. Fish population responses to chronic and acute pollution: the influence of
life history strategies. Estuaries 10:267-275.
Schaefer, R. H. 1965. Age and growth of the northern kingfish in New York waters. New
York Fish and Game Journal 12:191-216.
- 163 -
Schaus, M. H., M. J. Vanni, and T. E. Wissing. 2002. Biomass-dependent diet shifts in
omnivorous gizzard shad: implications for growth, food web, and ecosystem
effects. Transactions of the American Fisheries Society 131(1): 40-54.
Schimmel, S. C., S. J. Benyi, and C. J. Strobel. 1999. An assessment of the ecological
condition of Long Island Sound, 1990-1993. Environmental Monitoring and
Assessment 56(1):27-49.
Schleiger, S. L. 2000. Use of an Index of Biotic Integrity to detect effects of land uses on
stream fish communities in west-central Georgia. Transactions of the American
Fisheries Society. 129(5):1118-1133.
Schubauer-Berigan M. K., M. Smith, J. Hopkins, and S. M. Cormier. 2000. Using
historical biological data to evaluate status and trends in the Big Darby Creek
watershed (Ohio, USA). Environmental Toxicology and Chemistry 19(4):1097-
1105.
Schwartz, F. J. and M. D. Dahlberg. 1978. Biology and ecology of the Atlantic stingray,
Dasyatis sabina (Pisces: Dasyatidae), in North Carolina and Georgia. Northeast
Gulf Science 2:1-23.
- 164 -
Scott, M. C. and L. W. Hall, Jr. 1997. Fish assemblages as indicators of environmental
degradation in Maryland coastal plain streams. Transactions of the American
Fisheries Society 126, 349–360.
Scott, G. I., M. H. Fulton, E. D. Strozier, P. B. Key, J. W. Daugomah, D. Porter, and S.
Strozier. 1996. The effects of urbanization on the American oyster, Crassostrea
virginica (Gmelin). Journal of Shellfish Research 15(2):523-524.
Scott, G. I., L. Webster, B. Thompson, W. Ellenberg, P. Comar, and G. P. Richards.
1998. The impacts of urbanization on shellfish harvesting waters: development of
techniques to identify coliform pollution sources. Presented at the International
Conference on Shellfish Restoration (ICSR) meeting, Hilton Head, South
Carolina.
Sedberry, G. R. 1987. Feeding habits of sheepshead, Archosargus probatocephalus, in
offshore reef habitats of the southeastern continental shelf. Northeast Gulf Science
9(1):29-37.
Sekavec, G. B. 1974. Summer foods, length-weight relationships, and condition factor of
juvenile ladyfish, Elops saurus Linnaeus, from Louisiana coastal streams.
Transactions of the American Fisheries Society 103(3):472-476.
- 165 -
Setzler, E. M., J. A. Mihursky, K. V. Wood, W. R. Boynton, T. T. Polgar, and G.E.
Drewry. 1981. Major features of ichthyoplankton populations in the upper
Potomac estuary: 1974-76. Rapport et Proces-Verbaux des Reunions du Conseil
International pour l'Exploration de la Mer (CIEM) 178: 204-206.
Setzler-Hamilton, E. M. 1987. Utilization of Chesapeake Bay by early life history stages
of fishes, p. 63-93. In S. K. Majumdar, L. W. Hall, Jr., and H. M. Austin (eds.),
Contaminant Problems and Management of Living Chesapeake Bay Resources,
American Association for the Advancement of Science National Meeting:
Chesapeake Bay Fisheries and Contaminant Problems, Philadelphia,
Pennsylvania.
Shannon, C. E. 1948. A mathematical theory of communication. Bell System Technical
Journal 27:379-423.
Shealy, M. H., J. V. Miglarese, and E. B. Joseph. 1974. Bottom fishes of South Carolina
estuaries – relative abundance, seasonal distribution and length-frequency
relationships. South Carolina Marine Resources Center Technical Report No. 6,
South Carolina Wildlife and Marine Resources Department, Charleston, South
Carolina.
- 166 -
Shenker, J. M. and J. M. Dean, 1979. The utilization of an intertidal salt marsh creek by
larval and juvenile fishes: abundance, diversity and temporal variation. Estuaries
2:154-163.
Sheridan, P. F., D. L. Trimm, and B. M. Baker. 1984. Sex ratios, length-weight
relationships, maturation, fecundity, and food habits were determined from 7,400
individuals of seven species of inner continental shelf fishes. Contributions to
Marine Science, University of Texas 27:175-204.
Short, F. T. and D. M. Burdick. 1996. Quantifying eelgrass habitat loss in relation to
housing development and nitrogen loading in Waquoit Bay, Massachusetts.
Estuaries 19(3):730-739.
Short, F. T. and S. Wyllie-Echeverria. 1996. Natural and human-induced disturbance of
seagrasses. Environmental Conservation 23 (1):17-27.
Sierra, L. M., R. Claro, and O. A. Popova. 1994. Alimentacion y relaciones tróficas, p.
263-284. In R. Claro (ed.), Ecología de los Peces Marinos de Cuba. Instituto de
Oceanología Academia de Ciencias de Cuba and Centro de Investigaciones, de
Quintana Roo, Mexico.
- 167 -
Simon, T. P. and J. Lyons. 1995. Application of the index of biotic integrity to evaluate
water resource integrity in freshwater ecosystems, p. 245-262. In W. S. Davis and
T. P. Simon (eds.), Biological assessment and criteria: tools for water resources
planning and decision making. Lewis Publishers, Boca Raton, Louisiana.
Simonoff, J. S. 1996. Smoothing methods in statistics. Springer-Verlag, New York.
Sindermann, C. J. 1994. Quantitative effect of pollution on marine and anadromous fish
populations. National Oceanic and Atmospheric Administration Technical
Memorandum NMFS-F/NEC-104, National Marine Fisheries Service, National
Oceanic Atmospheric Administration, Woods Hole, Massachusetts.
Sindermann, C. J. 1995. Ocean pollution: effects on living resources and humans. CRC
Press, New York.
Sindermann, C. J. 1996. Sustainable development in the southeastern coastal zone: a
summary, p. 509-516. In F. J. Vernberg, W. B. Vernberg, and T. Siewicki (eds.),
Sustainable Development in the Southeastern Coastal Zone. University South
Carolina Press, Columbia, South Carolina.
Smith, H. M. 1907. The fishes of North Carolina. North Carolina Geological and
Economic Survey, Volume 2. Raleigh, North Carolina.
- 168 -
Smith, J. W. and C. A. Wenner. 1985. Biology of the southern kingfish in the South
Atlantic Bight. Transactions of the American Fisheries Society 114(3):356-366.
Snelson, Jr. F. F. and S. E. Williams. 1981. Notes on the occurrence, distribution, and
biology of elasmobranch fishes in the Indian River lagoon system, Florida.
Estuaries 4(2):110-120.
Snelson, Jr. F. F., S. E. Williams-Hooper, and T. H. Schmid. 1988. Reproduction and
ecology of the Atlantic stingray, Dasyatis sabina, in Florida coastal lagoons.
Copeia 1988:729-739.
Snyder, B. D., J. B. Stribling, M. T. Barbour, and C. L. Missimer. 1999. Integrating
assessments of fish and macroinvertebrate assemblages and physical habitat
condition in Pennsylvania, p. 639-652. In T. P. Simon (ed.), Assessing the
sustainability and biological integrity of water resources using fish communities.
CRC Press, Washington, DC.
Soares, L. S. H., M. A. Gasalla, M. A. T. Rios, M. V. Arrasa, and C. L. B. Rossi-
Wongtschowski. 1993. Trophic groups of eleven dominant demersal fish species
from the inner continental shelf of Ubatuba, Brazil. Publicacao Especial do
Instituto Oceanografico 10:189-198.
- 169 -
Sokal, R. R. and F. J. Rohlf. 1995. Biometry:the principles and practice of statistics in
biological research, 3rd ed. W. H. Freeman, New York.
South Carolina Department of Health and Environmental Control (SCDHEC). 1997.
Procedures and quality control manual for chemistry laboratories. Bureau of
Environmental Services, Columbia, South Carolina.
South Carolina Department of Health and Environmental Control (SCDHEC). 1998a.
Laboratory procedures manual for environmental microbiology. Bureau of
Environmental Services, Columbia, South Carolina.
South Carolina Department of Health and Environmental Control (SCDHEC). 1998b.
Summary of selected water quality parameter concentrations in South Carolina
waters and sediments, January 1, 1993 – December 31, 1997. Technical Report
004-98. Bureau of Water, Columbia, South Carolina.
South Carolina Department of Health and Environmental Control (SCDHEC). 2001.
Environmental investigations standard operating procedures and quality assurance
manual. Office of Environmental Quality Control, Columbia, South Carolina.
Southerland, M. T. and J. B. Stribling. 1995. Status of the biological criteria development
and implementation, p. 81-96. In S. Davis, and T. P. Simon (eds.), Biological
assessment and criteria: tools for water resources planning and decision making,
Lewis Publishers, Boca Raton, Louisiana.
- 170 -
Springer, S. 1967. Social organization of shark populations, p. 149-174. In P.W. Gilbert,
R. F. Mathewson, and D. P. Rall (eds.), Sharks, Skates and Rays, Johns Hopkins
Press, Baltimore, Maryland.
Springer, V. G. and K. D. Woodburn. 1960. An ecological study of the fishes of the
Tampa Bay area. Florida State Board of Conservation Marine Laboratory
Professional Paper, No. 1. St. Petersburg, Florida.
Staver, L. W., K. W. Staver, and J. C. Stevenson. 1996. Nutrient inputs to the Choptank
River estuary: implications for watershed management. Estuaries 19:342–358.
Steedman, R. J. 1988. Modification and assessment of an index of biotic integrity to
quantify stream quality in southern Ontario. Canadian Journal of Fishery and
Aquatic Science 45:492-501.
Stevens, Jr. D. L. 1997. Variable density grid-based sampling designs for continuous
spatial populations. Environmetrics 8:167-195.
Stevens, Jr. D. L. and A. R. Olsen. 1999. Spatially restricted surveys over time for
aquatic resources. Journal of Agricultural, Biological, and Environmental
Statistics 4:415-428.
- 171 -
Stickney, R. R. 1976. Food habits of Georgia estuarine fishes. II. Symphurus plagiusa
(Pleuronectiformes: Cynoglossidae). Transactions of the American Fisheries
Society 105:202-207.
Stickney, R. R. 1984. Estuarine ecology of the southeastern United States and Gulf of
Mexico. Texas A&M University Press, College Station, Texas.
Stickney, R. R. and R. B. McGeachin. 1978. Food habits of fishes associated with
marshland developed on dredged material. Proceedings of the Annual Conference
of the Southeastern Association for Fish and Wildlife Agencies 32:547-560.
Stickney, R. R. and S. E. Shumway. 1974. Occurrence of cellulase activity in the
stomachs of fishes. Journal of Fishery Biology 6:779-790.
Stickney, R. R., G. L. Taylor, and R. W. Heard, III. 1974. Food habits of Georgia
estuarine fishes. I. Four species of flounders (Pleuronectiformes: Bothidae).
Fishery Bulletin 72:515-525.
Stickney, R. R., G. L. Taylor, and D. B. White. 1975. Food habits of five species of
young southeastern United States Sciaenidae. Chesapeake Science 16:104-114.
Stoner, A. W. 1980. Feeding ecology of Lagodon rhomboides (Pisces: Sparidae):
variation and functional responses. Fishery Bulletin 78(2):337-352.
- 172 -
Stoner, A. W. 1986. Community structure of the demersal fish species of Laguna Joyoda,
Puero Rico. Estuaries 9:142-152.
Subrahmanyan, C. B. and S. H. Drake. 1975. Studies on the animal communities in two
north Florida salt marshes, Part 1: Fish communities. Bulletin of Marine Science
25:445-465.
Sutter, F. C., and T. D. McIlwain. 1987. Species profiles: life histories and environmental
requirements of coastal fishes and invertebrates (Gulf of Mexico): pigfish. US
Fish and Wildlife Service Biological Report 82 (11.71).
Suttkus, R. D. 1963. Order Lepisostei, p. 61-88. In H.B. Bigelow, M.G. Bradbury, J.R.
Drymond, J.R. Greeley, S.F. Hildebrand, G.W. Mead, R.R. Miller, L.R. Rivas,
W.C. Schroeder, R.D. Suttkus, and V.D. Vladykov (eds.), Fishes of the Western
North Atlantic, Soft-rayed Bony Fishes Part 3, Yale University, New Haven,
Connecticut.
Swan, C. M. and M. A. Palmer. 2000. What drives small-scale spatial patterns in lotic
meiofauna communities? Freshwater Biology 44:1109-121.
- 173 -
Szedlmayer, S. T. and K. W. Able. 1993. Ultrasonic telemetry of age-0 summer flounder,
Paralichthys dentatus, movements in a southern New Jersey estuary. Copeia
3:728-736.
Talbot, G. B. and J. E. Sykes. 1958. Atlantic coast migrations of American shad. Fishery
Bulletin 58:473-490.
Teixeira, R. L. and G. I. Almeida. 1998. Composition of the ichthyofauna occupying the
inner surf-zone of sandy beaches of Maceio-AL, northeastern Brazil. Boletim do
Museu de Biologia Mello Leitao 8:21-38.
Teixeira, R. L. and J. L. Helmer. 1997. Biology of young mojarras (Pisces: Gerreidae)
occupying the shallow waters of a tropical estuary. Revista Brasileira de Biologia
57(4):637-646.
Teixeira, R. L., G. A. F. Falcao, and S. C. Melo. 1992. Occurrence and feeding of
juvenile Sciaenidae (Pisces: Perciformes) in the surf zones of the beaches of
Maceio, Brazil. Atlantica 14:29-42.
Thayer, G. W., M. S. Fonseca, and J. W. Kenworthy. 1997. Ecological value of
seagrasses: A brief summary for the ASMFC Habitat Committee’s SAV
Subcommittee. In C. D. Stephan and T. E. Bigford (eds.), Atlantic Coastal
Submerged Aquatic Vegetation: a review of its ecological role, anthropogenic
- 174 -
impacts, state regulation and value to Atlantic coastal fisheries. Atlantic States
Marine Fisheries Commission Habitat Management Series No. 1, Washington,
DC.
Thayer, G. W., A. B. Powell, and D. E. Hoss. 1999. Composition of larval, juvenile, and
small adult fishes relative to changes in environmental conditions in Florida Bay.
Estuaries 22(2B):518-533.
Thomas, D. L. 1971. The early life history and ecology of drum (Sciaenidae) in the lower
Delaware River, a brackish tidal estuary. Ichthyology Association Bulletin 3:1-
247.
Thompson, B. A. and G. R. Fitzhugh. 1986. A use attainability study: an evaluation of
fish and macroinvertebrate assemblages of the lower Calcasieu River. LSU-CFI-
29. Louisiana Center for Wetlands Resources, Coastal Fisheries Institute,
Louisiana State University, Baton Rouge.
Thorrold, S. R., C. M. Jones, P. K. Swart, and T. E. Targett. 1998. Accurate classification
of juvenile weakfish Cynoscion regalis to estuarine nursery areas based on
chemical signatures in otoliths. Marine Ecology Progress Series 173:253-265.
- 175 -
Toepfer, C. S. and J. W. Fleeger. 1995. Diet of juvenile fishes Citharichthys spilopterus,
Symphurus plagiusa and Gobionellus boleosoma. Bulletin of Marine Science
56(1):238-249.
Tucker, Jr. J. W. 1982. Larval development of Citharichthys cornutus, C. Gymnorhinus,
C. spilopterus, and Etropus crossotus (Bothidae), with notes on larval occurence.
Fishery Bulletin 80:35-73.
Tyler, J. C. 1978. Monacanthidae. In W. Fischer (ed.), Food and Agriculture
Organization Species Identification Sheets for Fishery Purposes. Western Central
Atlantic (Fishing Area 31), Volume 3. United Nations Food and Agriculture
Organization, Rome, Italy.
Tzeng, W-N. and Y-T. Wang. 1992. Structure, composition and seasonal dynamics of the
larval and juvenile fish community in the mangrove estuary of Tanshui River,
Taiwan. Marine Biology 113(3):481-490.
United States Department of Agriculture (USDA). 2000. Summary Report:1997 National
Resources Inventory (revised December 2000). Natural Resources Conservation
Service, Washington, DC, and Statistical Laboratory, Iowa State University,
Ames, Iowa.
- 176 -
United States Department of Agriculture (USDA). 2003. 2001 Annual National
Resources Inventory. Natural Resources Conservation Service, Washington, DC.,
and Statistical Laboratory, Iowa State University, Ames, Iowa.
United States Environmental Protection Agency (USEPA). 1988. Report of the national
workshop on instream biological monitoring and criteria. United States
Environmental Protection Agency, Office of Water Regulations and Standards,
Washington, DC.
United States Environmental Protection Agency (USEPA). 2001. National coastal
condition report. EPA620-R-01-005. United States Environmental Protection
Agency, Office of Research and Development and Office of Water, Washington,
DC.
United States Environmental Protection Agency (USEPA). 2004. National coastal
condition report II. EPA842-F-02-001. United States Environmental Protection
Agency, Office of Research and Development and Office of Water, Washington,
DC.
United States Fish and Wildlife. 1989. United States Geological Survey, National
Wetlands Inventory. 1:24,000 7. 5 Minute Quadrangle Topographic Map Series.
St. Petersburg, Florida.
- 177 -
United States Fish and Wildlife. 1994. United States Geological Survey, National
Wetlands Inventory. 1:24,000 7. 5 Minute Quadrangle Topographic Map Series.
St. Petersburg, Florida.
United States Geological Survey (USGS). 1994. United States Geological Survey
National Mapping Program. Earth Science Information Center, Menlo Park,
California.
United States Geological Survey (USGS). 1999. United States Geological Survey
National Mapping Program. Earth Science Information Center, Menlo Park,
California.
Van Dolah, R. F., D. E. Chestnut, and G. I. Scott. 2000. A baseline assessment of
environmental and biological conditions in Broad Creek and the Okatee River,
Beaufort County, South Carolina: final report to the Beaufort County Council,
Beaufort County, South Carolina. South Carolina Department of Health and
Environmental Control, Charleston, South Carolina.
Van Dolah, R. F., J. L. Hyland, A. F. Holland, J. S. Rosen, and T. R. Snoots. 1999. A
benthic index of biological integrity for assessing habitat quality in estuaries of
the southeastern United States. Marine Environmental Research 48:269-283.
- 178 -
Van Dolah, R. F., P. C. Jutte, G. H. M. Riekerk, M. V. Levisen, L. E. Zimmerman, J D.
Jones, A. Lewitus, D. E. Chestnut, W. McDermott, D. Bearden, G. T. Scott, and
M. H. Fulton. 2002. The condition of South Carolina’s estuarine and coastal
habitats during 1999-2000: technical report. South Carolina Marine Resources
Division, Charleston, South Carolina.
Van Dolah, R. F., P. C. Jutte, G. H. M. Riekerk, M. V. Levisen, S. E. Crowe, A. Lewitus,
D. E. Chestnut, W. McDermott, D. Bearden, and M.H. Fulton. 2004a. The
condition of South Carolina's estuarine and coastal habitats during 2001-2002:
technical report. Technical Report 100. South Carolina Marine Resources
Division, Charleston, South Carolina.
Van Dolah, R. F., D. M. Sanger, and A. B. Filipowicz (eds.). 2004b. A baseline
assessment of environmental and biological conditions in the May River, Beaufort
County, South Carolina. Final report submitted to the Town of Bluffton. South
Carolina Marine Resources Division, Charleston, South Carolina.
Vega-Cendejas, M. E., V. Castillo, and M. Hernandez. 1994. Diet of mojarra,
Eucinostomus argenteus, in relation to the abundance of its prey. Journal of Fish
Biology 45: Supplement A.
Vernberg, F. J., W. B. Vernberg, E. Blood, A. Fortner, M. Fulton, H. McKellar, W.
Michener, G. Scott, T. Siewicki, and K. El-Figi. 1992. Impact of urbanization on
- 179 -
high-salinity estuaries in the southeastern United States. Netherlands Journal of
Sea Research 30:239-248.
Vetter, R. D. 1982. Seasonal metabolic compensation in sympatric seatrout: adaptation to
the estuary. Transactions of the American Fisheries Society 111(2):193-198.
Vieira, J. P. and J. A. Musick. 1994. Fish faunal composition in warm-temperate and
tropical estuaries of western Atlantic. Atlantica Rio Grande 16:31-53.
Walburg, C. H. and P. R. Nichols. 1967. Biology and management of the American shad
and status of the fisheries, Atlantic coast of the United States, 1960. United States
Fish and Wildlife Service Special Scientific Report, Fisheries No. 550,
Washington, DC.
Walsh, H. J., D. S. Peters, and D. P. Cyrus. 1999. Habitat utilization by small flatfishes in
a North Carolina estuary. Estuaries 22(3B): 803-813.
Wang, L., J. Lyons, P. Kanehl, and R. Bannerman. 2001. Impacts of urbanization on
stream habitat and fish across multiple spatial scales. Environmental Management
28(2):255-266.
- 180 -
Wang, L., J. Lyons, P. Kanehl, R. Bannerman, and E. Emmons. 2000. Watershed
urbanization and changes in fish communities in southeastern Wisconsin streams.
Journal of the American Water Resources Association 36(5):1173-1175.
Wang, L., J. Lyons, P. Kanehl, and R. Gatti. 1996. Influences of watershed land use on
habitat quality and biotic integrity in Wisconsin streams. Fisheries 22(6):6-12.
Wannamaker, C. M. and J. A. Rice. 2000. Effects of hypoxia on movements and behavior
of selected estuarine organisms from the southeastern United States. Journal of
Experimental Marine Biology and Ecology 249(2):145-163.
Warlen, S. M. and J. S. Burke. 1990. Immigration of larvae of fall/winter spawning
marine fishes into a North Carolina estuary. Estuaries 13(4):453-461.
Wedemeyer, G. A., D. J. McLeay, and C. P. Goodyear. 1984. Assessing the tolerance of
fish and fish populations to environmental stress: the problems and methods of
monitoring, p. 163-195. In V. W. Cairns, P. V. Hodson, and J. O. Nriagu (eds.),
Contaminant effects on fisheries, Volume 16. John Wiley and Sons, New York.
Weinstein, M. P. 1979. Shallow marsh habitats as primary nursery areas for fish and
shellfish, Cape Fear River, North Carolina. Fishery Bulletin 77:339-357.
- 181 -
Weinstein, M. P., L. Scott, S. P. O’Neil, R. C. Siegfried, and S. T. Szedlmayer. 1984.
Population dynamics of spot, Leiostomus xanthurus, in polyhaline tidal creeks of
the York River estuary, Virginia. Estuaries 7(4A):444-450.
Weinstein, M. P., S. L. Weiss, R. G. Hodson, and L. R. Gerry. 1980. Multiple
determinants of community structure in shallow marsh habitats, Cape Gear
estuary, North Carolina, USA. Marine Biology 58:227-243.
Weisberg, S. B., J. A. Ranasinghe, D. M. Dauer, L. C. Schaffner, R. J. Diaz, and J. B.
Frithsen. 1997. An estuarine benthic index of biotic integrity (B-IBI) for
Chesapeake Bay. Estuaries 20(1):149-158.
Welsh, W. W. and C. M. Breder, Jr. 1923. Contributions to the life histories of
Sciaenidae of the eastern United States coast. Fishery Bulletin 39:141-201.
Wenner, E. L., W. P. Coon, III, M. H. Shealy, Jr., and P. A. Sandifer. 1981. Species
assemblages, distribution, and abundance of fishes and decapod crustaceans from
the Winyah Bay estuarine system S.C. South Carolina Technical Report No. 3,
South Carolina Sea Grant Consortium, South Carolina Sea Grant, Charleston,
South Carolina.
Wenner, E. L., W. P. Coon, III, M. H. Shealy, Jr., and P. A. Sandifer. 1984. Five-year
study of seasonal distribution and abundance of fishes and decapod crustaceans in
- 182 -
the Cooper River and Charleston Harbor, South Carolina, prior to diversion.
National Oceanic and Atmospheric Administration Technical Report NMFS
SSRF-782, National Marine Fisheries Service, National Oceanic and Atmospheric
Administration, Washington, DC.
Wenner, E. L., W. P. Coon, III, P. A. Sandifer, and M. H. Shealy, Jr. 1991. A comparison
of species composition and abundance of decapod crustaceans and fishes from the
north and south Edisto Rivers in South Carolina. South Carolina Marine
Resources Center Technical Report No. 78, South Carolina Wildlife and Marine
Resources Department, Charleston, South Carolina.
Werner, F. E., B. O. Blanton, J. A. Quinlan, and R. A. Luettich, Jr. 1999. Physical
oceanography of the North Carolina continental shelf during the fall and winter
seasons: implications for the transport of larval menhaden. Fisheries
Oceanography 8(Supplement 2):7-21.
White, M. G. 1970. Anadromous fish survey III: job complete report for period July 1,
1969 through December 31, 1970. South Carolina Wildlife Resources Division,
Charleston, South Carolina.
Whitehead, P. J. P. 1985. Clupeoid fishes of the world: an annotated and illustrated
catalogue of the herrings, sardines, pilchards, sprats, shads, anchovies and wolf-
herrings. Part 1 - Chirocentridae, Clupeidae and Pristigasteridae. Food and
- 183 -
Agriculture Organization species catalogue. United Nations Food and Agriculture
Organization Fisheries Synopsis, Rome, Italy.
Whitehead, P. J. P., G. J. Nelson, and T. Wongratana. 1988. Clupeoid fishes of the world
(Suborder Clupeoidei): an annotated and illustrated catalogue of the herrings,
sardines, pilchards, sprats, shads, anchovies and wolf-herrings. Part 2 -
Engraulididae. Food and Agriculture Organization species catalogue. United
Nations Food and Agriculture Organization Fisheries Synopsis, Rome, Italy.
Wilcox, D. A., J. E. Meeker, P. L. Hudson, B. J. Armitage, M. G. Black, and D. G.
Uzarski. 2002. Hydrologic variability and the application of index of biotic
integrity metrics to wetlands: a Great Lakes evaluation. Wetlands 22(3):588-615.
Wilk, S. J. 1979. Biological and fisheries data on weakfish, Cynoscion regalis (Bloch and
Schneider). Technical Series 21, Sandy Hook Laboratory, National Oceanic and
Atmospheric Administration/National Marine Fisheries Service, Highlands, New
Jersey.
Wilkens, E. P. H. and R. H. Lewis. 1971. Abundance and distribution of young, Atlantic
menhaden, Brevoortia tyrannus, in the White Oak River estuary, North Carolina.
Fishery Bulletin 69(4):783-789.
- 184 -
Williams, C. D., D. M. Nelson, L. C. Clements, M. E. Monaco, S. L. Stone, L. R. Settle,
C. Iancu, and E. A. Irlandi. 1990. Distribution and abundance of fishes and
invertebrates in Eastern Gulf of Mexico Estuaries. Estuarine Living Marine
Resources Report No. 6. National Oceanic and Atmospheric Administration,
Strategic Assessment Branch, National Ocean Service, Rockville, Maryland.
Williams, R. O. and G. E. Brager (eds.). 1972. Investigations on American shad in the St.
Johns River. Florida Department of Natural Resources Technical Series Volume
66.
Wilson, J. G. and Jeffrey, D. W. 1987. Europe-wide indices for monitoring estuarine
quality, p. 225-242. In D. H. S. Richardson (ed.), Biological Indicators of
Pollution, Royal Irish Academy, Dublin, Ireland.
Winner, R. W., M. W. Boesel, and M. P. Farrell. 1980. Insect community structure as an
index of heavy-metal pollution in lotic ecosystems. Canadian Journal of Fishery
and Aquatic Science 37:641-658.
Witherell, D. B. and B. Kynard. 1990. Vertical distribution of adult American shad in the
Connecticut River. Transactions of the American Fisheries Society 119(1):151-
155.
- 185 -
Wollam, M. B. 1970. Description and distribution of larvae and early juveniles of king
mackerel Scomberomorus cavalla (Cuvier), and Spanish mackerel,
Scomberomorus maculatus (Mitchill); (Pisces: Scombridae); in the western North
Atlantic. Florida Department of Natural Resources Marine Research Laboratory,
Technical Series 61.
Yako, L. A., J. M. Dettmers, and R. A. Stein. 1996. Feeding preferences of omnivorous
gizzard shad as influenced by fish size and zooplankton density. Transactions of
the American Fisheries Society 125:753-759.
Yanez-Arancibia, A. and A. L. Lara-Dominguez. 1988. Ecology of three sea catfishes
(Ariidae) in a tropical coastal ecosystem - southern Gulf of Mexico. Marine
Ecology Progress Series 49(3):215-230.
Yannai, S. and K. Sachs. 1978. Mercury compounds in some eastern Mediterranean
fishes, invertebrates, and their habitats. Environmental Research 16(1-3):408-418
Yoccoz, N. G. 1991. Use, overuse, and misuse of significance tests in evolutionary
biology and ecology. Bulletin of the Ecological Society of America 72:106-111.
Yoder, C. O. and E. T. Rankin. 1995. Biological response signatures and the area of
degradation value: new tools for interpreting multimetric data, p. 263-286. In W.
S. Davis and T. P. Simon (eds.), Biological Assessment and Criteria: Tools for
- 186 -
Water Resources Planning and Decision Making, Lewis Publishers, Boca Raton,
Louisiana.
Yoder, C. O. and E. T. Rankin. 1998. The role of biological indicators in a state water
quality management process. Journal of Environmental Monitoring and
Assessment 51:61-88.
Yoder, C. O. and M. A. Smith. 1999. Using fish assemblages in a state biological
assessment and criteria program: essential concepts and considerations, p. 17-56.
In T. P. Simon (ed.), Assessing the Sustainability and Biological Integrity of
Water Resources Using Fish Communities. CRC Press, New York.
Zahorcsak, P., R. A. M. Silvano, and I. Sazima. 2000. Feeding biology of a guild of
benthivorous fishes in a sandy shore on south-eastern Brazilian coast. Revista
Brasileira de Biology 60(3):511-518.
Zar, J. H. 1984. Biostatistical analysis. Prentice-Hall, New York.
- 187 -
Figure 1. Array of 97 tidal creek stations sampled in 1999-2002 used in the
current study, chosen from the larger South Carolina Estuarine Coastal
Assessment Program (SCECAP) sampling array. Tidal creeks were defined as
tidally influenced water bodies that were less than 100 m wide from marsh bank
to marsh bank. Stations that had salinities greater than 18 ppt were selected for
the current study. Environmental quality of each station was determined by using
water, sediment, and upland quality parameters. Estuarine biotic integrity (EBI)
score was calculated using the final EBI index (EBI index D6).
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$T
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N
EW
S
%U 0%U 5%U 10%U 15%U 20%U 25%U 30%U 35%U 40%U 45
T Poor
Environmental Quality
â Marginal
EBI Score
GoodS
0 20 40 60 80 100 Kilometers
%U N/A
LEGEND
- 189 -
Figure 2. Flowchart of methods for developing and evaluating an estuarine biotic
integrity (EBI) index for South Carolina tidal creeks. General steps are boxed or
italicized; details of each step taken in the current study are adjacent; steps that
led to the selection of the final EBI index (EBI index D6) are in bold font. See text
for details.
Seventy-three Candidate Metrics - Life history - Trophic and ecological composition - Tolerance - Community structure
Compile Candidate
Fish Metrics
Develop Candidate
Indices with Subset of Fish
Metrics
Apply Candidate
Indices
Evaluate Subset of Candidate
Indices
Five Approaches to Select Subset of Fish Metrics Used to Develop 22 Candidate Indices
1) One-way analyses (EBI Index Ax) 2) Stepwise discriminant analyses (EBI
Index Bx) 3) Previous studies (EBI Index Cx) 4) Composite analyses (EBI Index Dx)5) Individual metrics (EBI Index Ex)
Two Application Approaches 1) Median Analyses 2) Discriminant Analyses
Plot EBI Scores for a Subset of Five Candidate Indices
1) EBI Index A3 2) EBI Index C2 3) EBI Index C3 4) EBI Index D2 5) EBI Index D6
Select Final EBI
Index
One Final EBI Index of Nine Metrics - EBI Index D6
Choose index that can determine environmental quality, without error
Choose indices with lowest misclassification rates
- 191 -
Figure 3. The two creeks that contained one marginal station located upstream
relative to one good station located downstream: a) Kiawah River and b) May
River. Land use and land cover data surrounding each station were obtained
from National Wetland Inventory (NWI) 1989 and 1994 databases, categorized
by using the Anderson classification system (Anderson et al. 1976; US Fish and
Wildlife 1989, 1994; ESRI 1998). A 100 m buffer for each station was used to
determine upland quality. Environmental quality of each station was determined
by using water, sediment, and upland quality parameters. Estuarine biotic
integrity (EBI) score was calculated using the final EBI index (EBI index D6). For
environmental and physical parameters at each station, see Table 4.
#S
#S
ÊÚ
#S#S
ÊÚ
ResidentialCropland/PastureTransportation/UtilityMixed ForestForested WetlandEvergreen ForestPlanted PineNon-forested WetlandSand
Tidal CreekOpen Water
EBI score%U 5%U 10
S Goodâ Marginal
Environmental Quality
Land Use/Land CoverLEGEND
0 1 2 3 4 Kilom eters
N
EW
S
a)
b)
2535
%U%U
Buffer (100 m)Herbaceous Rangeland
- 193 -
Figure 4. Box-plots of nine of the 73 candidate fish metrics that were significantly
different between good and marginal stations sampled in 1999-2001 (one-way
analyses, Wilcoxon test, Dunn-Sidak test, k=73, α=0.10, p<0.0014).
Car
nivo
re (#
of t
axa)
-10123456789
1011
Good Marginal
Environmental Quality
Est
uarin
e N
urse
ry (#
of t
axa)
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ilient
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f tax
a)
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4
Good Marginal
Environmental Quality
Spe
cies
Ric
hnes
s (M
arga
lef's
D)
0
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Good Marginal
Environmental Quality
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ber o
f Tax
a
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Good Marginal
Environmental Quality
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Pre
dato
r (#
of ta
xa)
0
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2
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4
Good Marginal
Environmental Quality
Sal
inity
Inde
pend
ent (
# of
taxa
)
0
1
2
3
4
Good Marginal
Environmental Quality
Tida
l Cre
ek N
urse
ry (#
of t
axa)
-10123456789
10
Good Marginal
Environmental Quality
Tida
l Cre
ek R
esid
ent (
# of
taxa
)
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
Good Marginal
Environmental Quality
- 195 -
Figure 5. Total misclassification rates of EBI indices A1,2 and B1,2, based on the
median or discriminant analyses. EBI indices A1,2 incorporated metrics selected
by the one-way analyses, while EBI indices B1,2 incorporated metrics selected by
the stepwise discriminant analyses. All indices were developed using 1999-2001
data. For the median analyses, indices were applied to three data sets: 1) 1999-
2001 stations, 2) 1999-2002 stations, and 3) 2002 stations. For the discriminant
analyses, indices were applied to two data sets: 1) 1999-2001 stations, and 2)
1999-2002 stations. The discriminant analyses were not applicable for the data
set limited to 2002 stations because there was only one marginal station found
(degree of freedom was less than one) in 2002.
0
10
20
30
40
50
60
70
80
A1 A2 B1 B2
One-Way Analysis Stepwise Discriminant Analysis
Estuarine Biotic Integrity Index
Tota
l Mis
clas
sifie
d (%
)Median Analysis (99-01)
Median Analysis (99-02)
Discriminant Analysis (99-01)
Discriminant Analysis (99-02)
Median Analysis (2002)
- 197 -
Figure 6. Total misclassification rates for all EBI indices developed in the current
study, based on the median or discriminant analyses. EBI indices Ax
incorporated metrics selected by one-way analyses; EBI indices Bx incorporated
metrics selected by stepwise discriminant analyses; EBI indices Cx incorporated
metrics selected by previous studies; EBI indices Dx incorporated metrics
selected by a combination of methods; EBI indices Ex included single community
structure metrics. All indices were developed with and applied to stations
sampled in 1999-2002.
0
5
10
15
20
25
30
35
40
45
50
A1 A2 A3 B1 B2 B3 B4 B5 C1 C2 C3 D1 D2 D3 D4 D5 D6 D7 D8 E1 E2 E3
One-WayAnalysis
Stepwise DiscriminantAnalysis
Previous Studies Composite Analysis SingleCommunity
Metrics
Estuarine Biotic Integrity Index
Tota
l Mis
clas
sifie
d (%
)
Discriminant Analysis Median Analysis
- 199 -
Figure 7. Good and marginal station misclassification rates for all EBI indices
developed in the current study, based on the median analyses. EBI indices Ax
incorporated metrics selected by one-way analyses; EBI indices Bx incorporated
metrics selected by stepwise discriminant analyses; EBI indices Cx incorporated
metrics selected by previous studies; EBI indices Dx incorporated metrics
selected by a combination of methods; EBI indices Ex included single community
structure metrics. All indices were developed with and applied to stations
sampled in 1999-2002.
0
10
20
30
40
50
60
70
80
90
100
A1 A2 A3 B1 B2 B3 B4 B5 C1 C2 C3 D1 D2 D3 D4 D5 D6 D7 D8 E1 E2 E3
One-Way Analysis Stepwise Discriminant Analysis Previous Studies Composite Analysis Single CommunityMetrics
Estuarine Biotic Integrity Index
Tota
l Mis
clas
sifie
d (%
)GoodMarginal
- 201 -
Figure 8. Good and marginal station misclassification rates for all EBI indices
developed in the current study, based on discriminant analyses. EBI indices Ax
incorporated metrics selected by one-way analyses; EBI indices Bx incorporated
metrics selected by stepwise discriminant analyses; EBI indices Cx incorporated
metrics selected by previous studies; EBI indices Dx incorporated metrics
selected by a combination of methods; EBI indices Ex included single community
structure metrics. All indices were developed with and applied to stations
sampled in 1999-2002.
0
10
20
30
40
50
60
70
80
90
100
A1 A2 A3 B1 B2 B3 B4 B5 C1 C2 C3 D1 D2 D3 D4 D5 D6 D7 D8 E1 E2 E3
One-Way Analysis Stepwise Discriminant Analysis Previous Studies Composite Analysis Single CommunityMetrics
Estuarine Biotic Integity Index
Tota
l Mis
clas
sifie
d (%
)
Good
Marginal
- 203 -
Figure 9. Estuarine biotic integrity (EBI) scores of marginal and good stations,
calculated by a) EBI index A3, b) EBI index C2, c) EBI index C3, d) EBI index D2,
and e) EBI index D6 (final EBI index). The EBI score range that contained good
and marginal stations was labeled as “unknown” because the range of scores
could not determine environmental quality without error. A solid vertical line
represented the new threshold value that distinguished the cutoff EBI score
between unknown stations and good or marginal stations. A dashed vertical line
represented threshold values that were adjusted from original values (1=lower
boundary adjustment from 2.5 to 7.5; 2=upper boundary adjustment from 37.5 to
32.5; 3=combined upper and lower boundary adjustments of 1 and 2, and
4=adjustment to one threshold value at 17.5).
-5 0 5 10 15 20 25 30 35 40 45 50Estuarine Biotic Integrity Score (D6)
Stat
ion
Marginal Goode)
Unknown
-5 0 5 10 15 20 25 30 35Estuarine Biotic Integrity Score (D2)
Stat
ion
d)
-5 0 5 10Estuarine Biotic Integrity Score (A3)
Stat
ion
a)Unknown Good
GoodUnknown
0 5 10 15 20 25 30 35 40 45 50Estuarine Biotic Integrity Score (C3)
Sta
tion
Unknown Goodc)
0 5 10 15 20 25 30Estuarine Biotic Integrity Score (C2)
Sta
tion
b)Unknown Good
Marginal (n=9)Good (n=87)
1, 3 2, 34
Threshold valueAdjusted threshold value
- 205 -
Table 1. Critical values of water, sediment, and upland quality parameters that
were used to classify 97 stations sampled in 1999-2002 for the South Carolina
Estuarine and Coastal Assessment Program (SCECAP) as good, marginal, or
poor. Each water and sediment quality parameter was scored: 5=good,
3=marginal, or 1=poor. The upland parameter was scored: 5=good, or
2=marginal/poor. Overall environmental quality was determined by averaging the
scores of the parameters within each of the three quality categories (water,
sediment, and upland) and then adjusting the average score.
Good (5) Marginal (3) Poor (1)
pH ≥7.4 7.1 - <7.4 <7.1Dissolved oxygen (mg/L) ≥4 3 - 4 <3Biological oxygen demand (mg/L) ≤1.8 1.8 - 2.6 >2.6Total nitrogen (mg/L) ≤0.95 >0.95 - 1.29 >1.29Total phosphorus (mg/L) ≤0.09 >0.09 - 0.17 >0.17Fecal coliform bacteria (col/100mL) ≤43 >43 - 400 >400
Effects range median-quotient (score) <0.020 0.020 - 0.058 >0.058
Physically altered (within 100 m buffer) No Yes YesOverall environmental quality
Average quality ≥3.667 2.334 - <3.667 <2.334
Upland quality parameter
Environmental Quality
Water quality parameters
Sediment quality parameter
- 207 -
Table 2. Fish metrics that described life history, ecological and trophic
composition, tolerance, and community structure (italicized metrics were not
included as candidate fish metrics in statistical analyses). The expected fish
metric responses to degraded environmental quality were based on a review of
literature and ecological principals. The actual fish response was based on
observations from the current study.
Expected Actual
Estuarine dependent Spawns offshore and larva actively or passively immigrates to estuaries to settle out as a juvenile (pre-adult, immature non-spawning recruits) or spawns in estuary and remains as a juvenile; juvenile is not found nearshore, offshore, near the coast, or at the surf zone (McHugh, J.L. 1966; Blaber and Blaber 1980; Lenanton 1982; Lenanton and Potter 1987; Blaber et al . 1989; Forward et al . 1999)
Decrease Increase
Estuarine nursery Juvenile (pre-adult, immature non-spawning recruit) uses estuary as a nursery ground (develop, forage, reside); larva may have spawned offshore and recruit into estuary or juvenile may move out of the estuary after being spawned and developed in estuary and continue as juveniles offshore; do not include development of juvenile at sea or offshore
Decrease Increase
Estuarine resident Lives in estuary year round and are not diadromous or marine; uses estuary for all life stages and does not move offshore, nearshore, near the coast, or in the surf zone at any time
Increase Increase
Estuarine spawner Uses estuary (including most bays and sounds) as spawning ground; larva found in estuaries along with gravid adults; gravid adult does not spawn offshore, near shore, along the coast, or in the surf zone
Decrease Increase
Tidal creek nursery* Same as estuarine nursery, but specifically utilizes the tidal creek habitat, when information was available
Decrease Increase
Tidal creek resident* Same as estuarine resident, but specifically utilizes the tidal creek habitat Increase IncreaseTidal creek spawner* Same as estuarine spawner, but specifically utilizes the tidal creek habitat Decrease Increase
Benthic Typically found near, dwells on, or is associated with the bottom; demersal Decrease IncreaseBenthic feeder Diet includes benthic infauna and/or demersal epifauna; diet typically includes
invertebrates not found in the water column (i.e. crabs, mollusks, penaeid shrimp)Decrease Increase
Carnivore Depends on "animal" material for the majority (>60%) of diet; cannot mechanically or chemically digest incidental plant material (Stickney and Shumway 1974)
Decrease Increase
Detritivore Diet includes detritus (may be significant proportion or incidental) Decrease IncreaseHerbivore Depends on "plant" material for the majority (>60%) of diet; can mechanically or
chemically digest plant material (Stickney and Shumway 1974)Increase Decrease
Omnivore Depends on "animal" and "plant" material for diet; usually about 50/50 animal/plant but up to 40/60 or 60/40 animal/plant; have been found to sometimes have all animal or all plant diets in an individual; usually generalistic opportunistic feeders dependent on environmental conditions
Increase Decrease
Pelagic Typically found in/related to/associated with the water column; Living in open waters away from the bottom; bathy/epi/mesopelagic; was not used in statistical analyses
Increase Increase
Top predator Top predator; subset of carnivores that includes fish in their diet Decrease Increase
Definition
Response to degraded environmental quality
Life history metricsMetric
Ecological and trophic composition metrics
Expected ActualDefinition
Response to degraded environmental quality
Metric
Bay anchovy Anchoa mitchilli (bay anchovy) Increase IncreaseBay anchovy and shad Alosa sapidissima (American shad) and Anchoa mitchilli (bay anchovy) Increase IncreaseFlatfish Belongs to the Bothidae, Cynoglossidae, or Soleidae family Decrease DecreaseFlounder Recreationally important flatfish Decrease DecreaseResilient* Resilience to fishing pressure/productivity (Musick 1999); in this study, high and medium
resilience are termed as "resilient" and low and very low resilience are termed "not Increase Increase
Salinity independent* Independent of salinity within the range 1-32 ppt (Weinstein 1979) Increase IncreaseSciaenid Belongs in the Sciaenidae family Decrease IncreaseShad Alosa sapidissima (American shad) Increase Decrease
Density of fish Number of individuals per hectare Decrease IncreaseDominance Described with three submetrics (Berger and Parker 1970): 1) the percent of the fish
population that is made up of the most abundant taxon 2) the percent of the fish population that is made up of the two most abundant taxa, and 3) the percent of the fish population that is made up of the three most abundant taxa
Increase Decrease
Percent abundance Described with two submetrics: 1) the number of taxa that it takes to make up a cumulative abundance 90% of the total fish abundance, and 2) the number of taxa that it takes to make up a cumulative abundance of 95% of the total fish abundance
Decrease Increase
Species diversity H' (Shannon-Wiener species diversity Index; Shannon 1948) Decrease IncreaseSpecies evenness J' (Pielou's species evenness Index; Pielou 1966) Decrease DecreaseNumber of Taxa Average number of fish species/taxa per sample Decrease IncreaseSpecies richness D (Margalef's species richness index; Margalef 1958) Decrease Increase
Tolerance metrics
Community structure metrics
*Incomplete profile of community; available information was compiled for certain taxa while other taxa were conservatively left as blank
- 210 -
Table 3. Average values (±1 standard deviation) of water, sediment, upland, and
physical parameters for marginal, good, and excellent stations sampled in 1999-
2002. Excellent stations were a subset of good stations. *Depth and the percent
of physically altered land within a 100 m buffer were the only parameters
significantly different between good and marginal stations (Wilcoxon test, Dunn-
Sidak test, α=0.05, k=19, p<0.0027). All other parameters shown and not shown
(latitude, longitude, month, and year) were not significantly different between
good and marginal stations (Wilcoxon test, Dunn-Sidak test, α=0.05, k=19,
p>0.0027). For a complete list of water, sediment, upland, and physical
parameter values for each stations, refer to Appendices A and B.
Water quality parameterspH 7.41 ±0.11 7.55 ±0.20 7.70 ±0.069Dissolved oxygen (mg/L) 3.56 ±0.93 4.39 ±0.73 4.97 ±0.55Biological oxygen demand (mg/L) 2.58 ±2.02 1.15 ±1.56 0.06 ±0.24Total nitrogen (mg/L) 0.78 ±0.25 0.59 ±0.29 0.42 ±0.17Total phosphorus (mg/L) 0.11 ±0.02 0.09 ±0.05 0.06 ±0.02Fecal coliform bacteria (col/100 mL) 172.44 ±289.00 17.73 ±45.62 4.13 ±5.66
Sediment quality parameterEffects range median-quotient (score) 0.02 ±0.01 0.01 ±0.01 0.01 ±0.00
Upland quality parameterPhysically altered (%) *9.47 ±9.88 *1.38 ±3.86 0.00 ±0.00
Physical parametersTemperature (degrees C) 30.11 ±1.16 29.67 ±1.35 29.82 ±1.40Salinity (ppt) 29.58 ±4.63 32.55 ±4.06 34.42 ±1.73Width (m) 77.88 ±34.53 71.06 ±28.51 72.32 ±38.19Depth (m) *1.74 ±0.54 *2.60 ±0.97 3.00 ±1.02Width/depth ratio (m) 50.38 ±38.84 30.96 ±17.06 25.01 ±10.60Sinuousity (m) 821.75 ±79.32 791.20 ±181.45 793.90 ±154.69Rivulets 15.50 ±8.45 21.19 ±9.78 24.06 ±7.11
Excellent (n=16)Environmental Quality
Good (n = 87)Marginal (n = 9)
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Table 4. Environmental and physical parameters of two creeks (May and Kiawah
Rivers) that each contained one good and one marginal station. Numbers in
parenthesis were scored parameters; italicized parameters showed a significant
difference between good and marginal stations (analysis of variance [ANOVA],
p>0.05). The small sample size (n=2) does not allow statistical tests to detect
differences because of a lack of power.
Water quality parameters pH 7.63 (5) 7.37 (3) 7.61 (5) 7.47 (5)Dissolved oxygen (mg/L) 4.59 (5) 3.79 (3) 3.70 (3) 3.68 (3)Biological oxygen demand (mg/L) 0 (5) 1.20 (5) 1.80 (5) 3.20 (1)Total nitrogen (mg/L) N/A 1.20 (3) 1.12 (3) 0.83 (5)Total phosphorus (mg/L) 0.073 (5) 0.082 (5) 0.11 (3) 0.11 (3)Fecal coliform (col/100mL) 22 (5) 15 (5) 8 (5) 110 (3)
Sediment quality parameterEffects range median-quotient (score) 0.0017 (5) 0.0013 (5) 0.0071 (5) 0.0056 (5)
Upland quality parameterPhysically altered (%) 0 (5) 8.10 (2) 0 (5) 3.51 (2)
Physical parametersTemperature (degrees C)Salinity (ppt)Width (m)Depth (m)Width/depth ratio (m)Sinuousity (m)Rivulets (#)Latitude (decimal degrees)Longitude (decimal degrees)Relative location
10 5
31.8130.74
25 35Downstream
32.2166-80.9158
31.99
July (7)2001
808.9033
192.703.653.53 80.13 59.60
29.69 29.23 29.7928.91 34.35 33.6677.58 89.75 35.762.4 1.1 0.60
830.50 656.98 903.4231 18 12
July (7) August (8) July (7)2002 1999 2000
Upstream Downstream Upstream
32.2237 32.6439 32.6465-80.9256 -80.0437 -80.0576
May River May River Kiawah River Kiawah RiverGood Marginal Good Marginal
RT00542MR1-01-TRT01602May River Kiawah River
RT99004Station code
EBI score
Overall environmental qualityCreekMonth of samplingYear of sampling
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Table 5. Average value (±1 standard deviation) of the 21 fish metrics selected by
the one-way analyses, stepwise discriminant analyses, or previous studies for
marginal, good, and excellent stations. Excellent stations were a subset of good
stations. For a complete list of fish metric averages and values for each station,
refer to Appendix E.
Estuarine dependent (density of individuals) 485.37 ±352.30 214.81 ±191.36 169.97 ±154.29Estuarine nursery (# of taxa) 6.44 ±2.23 4.07 ±2.16 4.28 ±1.38Estuarine resident (# of taxa) 2.11 ±0.70 1.34 ±0.88 1.41 ±1.00Estuarine spawner (# of taxa) 3.06 ±1.10 2.00 ±1.29 2.00 ±1.11Tidal creek nursery (# of taxa) 5.56 ±2.30 3.34 ±1.70 3.72 ±1.30Tidal creek nursery (# of individuals/hectare) 513.63 ±388.02 226.20 ±206.35 195.22 ±182.90Tidal creek resident (# of taxa) 1.78 ±0.83 1.04 ±0.73 1.09 ±0.74
Benthic (% of individuals) 77.86 ±14.16 75.13 ±27.06 80.94 ±22.37Carnivore (# of taxa) 5.78 ±1.86 3.57 ±1.97 3.63 ±1.22Detritivore (# of individuals/hectare) 488.05 ±386.67 219.54 ±200.06 190.73 ±182.07Top predator (# of taxa) 2.39 ±0.49 1.35 ±0.89 1.34 ±0.77
Flatfish (# of individuals/hectare) 14.49 ±19.17 17.90 ±43.39 17.19 ±31.19Flounder (% of individuals) 0.17 ±0.50 0.85 ±3.08 1.36 ±3.22Resilient (# of taxa) 2.50 ±0.83 1.51 ±0.95 1.31 ±0.51Salinity independent (# of taxa) 2.28 ±1.09 1.34 ±0.72 1.44 ±0.60
Density of individuals (# of individuals/hectare) 536.72 ±385.60 246.77 ±216.90 207.45 ±183.95Dominance of most abundant taxon (%) 48.45 ±11.97 56.26 ±17.01 53.52 ±16.20Number of taxa 6.44 ±2.23 4.07 ±2.16 4.28 ±1.38Species diversity (H') 1.91 ±0.50 1.38 ±0.64 1.57 ±0.52Species richness (D) 0.90 ±0.33 0.57 ±0.33 0.63 ±0.2390% abundance (# of taxa) 7.22 ±2.86 5.45 ±2.68 6.13 ±1.93
Excellent (n = 16)Marginal (n = 9) Good (n = 87)Environmental Quality
Ecological and trophic metrics
Life history metrics
Tolerance metrics
Community structure
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Table 6. Summary of the 21 fish metrics included for each EBI index evaluated
(boxed X=not used in discriminant analyses). EBI indices Ax incorporated
metrics selected by one-way analyses; EBI indices Bx incorporated metrics
selected by stepwise discriminant analyses; EBI indices Cx incorporated metrics
selected by previous studies; EBI indices Dx incorporated metrics selected by a
combination of methods; EBI indices Ex included single community structure
metrics. All metric scores were summed for an EBI score for each station and
the maximum EBI score for each index was 5i, where i=the number of metrics
used for the index. Selection frequency was based on the number of times a
metric was selected for EBI indices A1-3, B1-3, and C1, 2.
A1 A2 A3 B1 B2 B3 B4 B5 C1 C2 C3 D1 D2 D3 D4 D5 D6 D7 D8 E1 E2 E3
Estuarine dependent (# of individuals/hectare) X X X X 3Estuarine nursery (# of taxa) X X X X X X 3Estuarine resident (# of taxa) X X X X 1Estuarine spawner (# of taxa) X X X X X 2Tidal creek nursery (# of taxa) X X X X X X X X X X 4Tidal creek nursery (# of individuals/hectare) X X 2Tidal creek resident (# of taxa) X 1
Benthic (% of individuals) X X X X X 2Carnivore (# of taxa) X X 2Detritivore (# of individuals/hectare) X 1Top predator (# of taxa) X X X X X X X X X X X X X 7
Flatfish (# of individuals/hectare) X X X X X X X X X X X 3Flounder (% of individuals) X X 1Resilient (# of taxa) X 1Salinity independent (# of taxa) X X X X X X X X X 5
Density of individuals (# of individuals/hectare) X X X X X X X X 2Dominance of most abundant taxon (%) X X X X X X 3Number of taxa X X X X X X X X X X X X 3Species diversity (H') X X X X X 1Species richness (D) X 190% abundance (# of taxa) X X X X 2Total number of metrics selected 9 6 1 5 3 7 4 3 7 5 9 5 6 6 6 4 9 9 5 1 1 1Maximum EBI score 45 30 5 25 15 35 20 15 35 25 45 25 30 30 30 20 45 45 25 5 5 5
Life history metrics
Ecological and trophic composition metrics
Tolerance metrics
Community stucture metrics
EBI Index
Selection frequency
One-way Stepwise discriminant Previous Composite Individual
- 218 -
Table 7. Fish metrics that were significantly different between good and marginal
stations sampled in 1999-2001 (Wilcoxon test, Dunn-Sidak test, 61
stations=good, 8 stations=marginal, α=0.10, k=73, p<0.0014). Critical value for
good quality was the 50th percentile of 61 good stations sampled in 1999-2001.
All metrics used in estuarine biotic integrity (EBI) index A1; metrics that were
significant at α<0.05 (p<0.0007) were used in EBI index A2; one metric (top
predator taxa) was significantly different for stations sampled in 1999-2002 and
used in EBI index A3 (Wilcoxon test, Dunn-Sidak test, 87 stations=good, 9
stations=marginal, α=0.10, k=73, χ2=11.3900, p=0.0002). For box-plots of fish
metrics, see Figure 2.
Metric χ2 pCritical value for good environmental quality
Tidal creek nursery (# of taxa) 14.1900 0.0002 ≤3.0Top predator (# of taxa) 13.9363 0.0002 ≤1.0Salinity independent (# of taxa) 12.8602 0.0003 ≤1.5Carnivore (# of taxa) 12.2417 0.0005 ≤3.0Estuarine nursery (# of taxa) 11.8483 0.0006 ≤3.5Number of taxa 11.8483 0.0006 ≤3.5Tidal creek resident (# of taxa) 10.9643 0.0009 ≤1.0Resilient (# of taxa) 10.3191 0.0013 ≤1.5Species richness (D) 10.1565 0.0014 ≤0.46
- 220 -
Table 8. Significant fish metrics selected by stepwise discriminant analyses,
using a subset of 50 candidate metrics and stations sampled in 1999-2001 (61
stations=good; 8 stations=marginal; p<0.15). Critical values were determined by
using the 50th percentile of 61 good stations sampled in 1999-2001. All fish
metrics were used in EBI index B1; three of the five metrics that were significant
at p<0.10 were used in EBI index B2.
Step Metric Partial r 2 χ2 pAverage squared
canonical correlationCritical value for good environmental quality
1 Tidal creek nursery (# of taxa) 0.2600 23.71 <0.0001 0.2614 ≤3.002 Flatfish (# of individuals/hectare) 0.1015 7346.00 0.0081 0.3364 ≥7.253 90% abundance (# of taxa) 0.0993 7317.00 0.0094 0.4023 ≤5.004 Top predator (# of taxa) 0.0526 3.55 0.0640 0.4337 ≤1.005 Dominance of most abundant taxon (%) 0.0467 3.09 0.0837 0.4602 ≥61.95
- 222 -
Table 9. Significant fish metrics selected by stepwise discriminant analyses,
using a subset of 50 candidate metrics and stations sampled in 1999-2002 (87
stations=good; 9 stations=marginal, p<0.15). Critical values were determined by
using the 50th percentile of 87 good sites. All metrics were used in EBI index B3;
four of the metrics that were significant at p<0.10 were used in EBI index B4;
three of the metrics that were significant at p<0.05 were used in EBI index B5.
Step Metric Partial r 2 χ2 pAverage squared
canonical correlationCritical value for good environmental quality
1 Estuarine dependent (# of individuals/hectare) 0.1260 13.55 0.0004 0.1260 ≤152.172 Salinity independent (# of taxa) 0.0455 4.44 0.0379 0.1658 ≤1.505 Top predator (# of taxa) 0.0458 4.32 0.0405 0.2510 ≤1.004 Tidal creek nursery (# of individuals/hectare) 0.0353 3.33 0.0712 0.2150 ≤166.666 Detritivore (# of individuals/hectare) 0.0262 2.40 0.1250 0.2706 ≤159.423 Flatfish (# of individuals/hectare) 0.0246 2.32 0.1312 0.1863 ≥7.257 Dominance of most abundant taxon (%) 0.0236 2.13 0.1479 0.2879 ≥55.95
- 228 -
Table 12. Nine fish metrics that were used in the final EBI index (EBI index D6).
Metrics were selected by applying expert knowledge of the local habitat to modify
metrics selected by previous studies (i.e., Deegan et al. 1997; Meng et al. 2002).
Good estuarine biotic integrity (EBI) was determined by using the critical values
for good quality, which were calculated using the 50th percentile for 87 good
stations sampled in 1999-2002. The expected fish metric responses to good EBI
were based on a review of literature and ecological principals. The actual fish
response was based on observations from the current study. See Table 2 or text
for more details.
Metric ReferenceCritical value for good environmental quality
Benthic (% of individuals) Deegan et al . 1997; Meng et al . 2002 ≥85.83Density of individuals (# of individuals/hectare) Deegan et al . 1997; Meng et al . 2002 ≤181.15Dominance of most abundant taxon (%) Deegan et al . 1997 ≥55.95Estuarine nursery (# of taxa) Deegan et al . 1997 ≤3.5Estuarine resident (# of taxa) Deegan et al . 1997 ≤1.5Estuarine spawner (# of taxa) Deegan et al . 1997; Meng et al . 2002 ≤1.5Flounder (% of individuals) Meng et al . 2002 ≥0Number of taxa Deegan et al . 1997 ≤3.5Species diversity (H') Meng et al . 2002 ≤1.41
- 224 -
Table 10. Subset of fish metrics that were used in previously developed estuarine
biotic integrity indices (Deegan et al. 1997; Meng et al. 2002). Critical values
were determined by using the 50th percentile of 87 good sites sampled in 1999-
2002 for the current study. Metrics selected by Deegan et al. (1997) were used
in EBI index C1; metrics selected by Meng et al. (2002) were used in EBI index
C2; metrics selected by either Deegan et al. (1997) or Meng et al. (2002) were
used in EBI index C3.
Good Excellent
Estuarine dependent (# of individuals/hectare) ≤152.17 ≤110.51X Estuarine nursery (# of taxa) ≤3.5 ≤4X Estuarine resident (# of taxa) ≤1.5 ≤1.5X Estuarine spawner (# of taxa) ≤1.5 ≤1.5
Tidal creek nursery (# of individuals/hectare) ≤166.66 ≤124.86Tidal creek nursery (# of taxa) ≤3 ≤3.75Tidal creek resident (# of taxa) ≤1 ≤1
X Benthic (% of individuals) ≥85.83 ≥89.23Carnivore (# of taxa) ≤3.5 ≤3.5Detritivore (# of individuals/hectare) ≤159.42 ≤119.56Top predator (# of taxa) ≤1 ≤1.5
Tolerance metricsX Flatfish (# of individuals/hectare) ≥7.25 ≥7.25
Flounder (% of individuals) ≥0 ≥0Resilient (# of taxa) ≤1.5 ≤1.25Salinity independent (# of taxa) ≤1.5 ≤1.5
Community metricsX Density of individuals (# of individuals/hectare) ≤181.15 ≤130.43X Dominance of most abundant taxon (%) ≥55.95 ≥49.11X Number of taxa ≤3.5 ≤4X Species diversity (H') ≤1.41 ≤1.66
Species richness (D) ≤0.56 ≤0.6490% abundance (# of taxa) ≤5 ≤6.5
Life history metrics
Ecological and trophic metrics
Critical ValueUsed in final EBI index Metric
- 226 -
Table 11. Twenty-one candidate fish metrics that were selected by statistical
analyses or by previous studies. Subsets of metrics and critical values were
used for EBI indices D1-8 and E1-3 (see Table 6 for details). Critical values for
good quality were calculated using the 50th percentile for 87 good stations
sampled in 1999-2002. Critical values for excellent quality were calculated using
the 50th percentile for 16 stations sampled in 1999-2002. Excellent stations were
a subset of good stations. Critical values for good quality were used in the
current study for the final EBI index, while critical values for excellent quality are
suggested for future resource managers.
Good EBI Expected?
Estuarine nursery (# of taxa) ≤3.5Estuarine resident (# of taxa) ≤1.5Estuarine spawner (# of taxa) ≤1.5
Benthic (% of individuals) ≥85.83Tolerance metric
Flatfish (# of individuals/hectare) ≥7.25Community metrics
Density of individuals (# of individuals/hectare) ≤181.15Dominance of most abundant taxon (%) ≥55.95Number of taxa ≤3.5Species diversity (H') ≤1.41
Ecological metric
Life history metrics
APPENDICES
Appendix A. Water, sediment, and upland quality parameters and overall
environmental quality of 97 stations sampled in 1999-2002. Missing data (n=38)
were regarded as blank values for analyses. Minimum, maximum, range, and
average values were calculated using 96 good and marginal stations. *Poor
station (NT02301) was not included in calculating minimum, maximum, range,
and average values and was eliminated in final analysis. See text for details.
Dissolved Oxygen
Biological Oxygen Demand
Total Nitrogen
Total Phosphorus
Fecal Coliform
Effects Range-Median Quotient
Physically Altered
(mg/L) (mg/L) (mg/L) (mg/L) (col/100mL) (score) (%)MR1-01-T Marginal 7.3669 3.7906 1.2 1.200 0.082 15 0.0013 8.10MR3-03-T Good 7.6632 4.9143 1.2 1.200 0.077 3 0.0023 0.00MR3-04-T Good 7.6425 4.2332 1.2 0.520 0.112 1 0.0067 0.00NT01598 Good 7.5505 4.7216 2.2 0.360 0.083 280 0.0168 17.75NT02301* Poor 7.6081 3.9555 2.4 0.829 0.060 1601 0.1113 2.38RT00501 Good 7.4535 4.0121 0.0 0.540 0.100 0 0.0088 0.00RT00502 Good 7.0268 3.2466 0.0 0.610 0.200 23 0.0023 0.00RT00503 Good 7.7132 3.8296 0.0 0.500 0.060 22 0.0140 17.08RT00504 Good 7.3150 3.8462 1.2 17 0.0048 0.00RT00505 Good 7.4572 3.9476 0.0 0.530 0.060 0 0.0153 0.00RT00517 Good 7.6952 4.1598 1.0 0.610 0.040 2 0.0053 0.00RT00518 Marginal 7.2270 2.9052 2.5 0.970 0.110 80 0.0279 0.00RT00519 Good 7.2430 4.4668 0.0 0.800 0.100 2 0.0126 0.00RT00520 Good 7.6969 4.8099 0.0 0.350 0.080 0 0.0113 0.00RT00521 Good 7.5387 4.5978 0.0 0.470 0.060 2 0.0355 0.00RT00523 Marginal 7.3878 3.5726 0.0 0.800 0.140 900 0.0199 7.18RT00525 Good 7.4158 3.4996 0.0 0.590 0.070 0 0.0087 0.00RT00528 Good 7.1719 4.1348 2.5 1.110 0.200 50 0.0168 0.00RT00531 Good 7.3754 5.0289 2.6 0.660 0.060 23 0.0040 0.00RT00541 Good 7.6668 4.6337 0.0 0.420 0.060 0 0.0171 0.00RT00542 Marginal 7.4687 3.6751 3.2 0.830 0.110 110 0.0056 3.51RT00543 Good 7.4436 4.2582 1.7 90 0.0049 0.00RT00544 Good 7.7588 4.2980 3.4 0.550 0.080 2 0.0028 0.00RT00545 Good 7.9086 5.4874 3.3 0.180 0.060 0 0.0003 12.11RT00546 Good 7.4891 3.9120 2.1 0.580 0.100 0 0.0043 0.00RT00547 Good 7.5463 3.8778 0.0 0.660 0.070 14 0.0121 0.00RT00550 Good 7.7530 5.1940 4.3 0.380 0.050 20 0.0031 8.25RT00554 Good 7.0884 3.7856 0.0 0.670 0.090 22 0.0078 0.00RT00557 Good 7.4283 4.9142 0.0 0.740 0.160 30 0.0087 4.90RT00558 Good 7.3350 4.4964 0.0 0.490 0 0.0307 0.00RT01602 Good 7.6346 4.5880 0.0 0.073 22 0.0017 0.00RT01603 Good 7.0639 3.0640 0.0 1.395 0.250 70 0.0029 0.00
pHStation Quality
Dissolved Oxygen
Biological Oxygen Demand
Total Nitrogen
Total Phosphorus
Fecal Coliform
Effects Range-Median Quotient
Physically Altered
(mg/L) (mg/L) (mg/L) (mg/L) (col/100mL) (score) (%)pHStation QualityRT01604 Good 7.4688 3.8864 0.0 0.097 23 0.0102 9.95RT01606 Good 7.7957 5.3392 0.0 2 0.0328 0.00RT01619 Good 7.7201 4.5603 0.0 0.110 0 0.0080 0.00RT01624 Good 7.7640 4.9898 0.0 0.074 0 0.0040 0.00RT01642 Good 7.7933 6.0240 0.0 7 0.0096 0.00RT01643 Good 7.3705 3.7358 0.0 1.088 0.230 2 0.0101 0.00RT01645 Good 7.7141 4.5024 2.9 3 0.0035 0.00RT01646 Good 7.6314 5.3986 0.0 2 0.0292 0.00RT01647 Marginal 7.5638 2.4214 2.0 0.531 0.060 4 0.0104 0.55RT01648 Good 7.4470 4.3489 0.0 0.584 0.160 0 0.0354 0.00RT01649 Good 7.8086 5.0826 0.0 7 0.0066 0.00RT01650 Good 7.8539 5.4825 0.0 0.061 11 0.0072 1.04RT01652 Good 7.5958 4.7481 0.0 11 0.0138 0.00RT01653 Good 7.4197 4.1756 2.3 0.089 4 0.0131 0.00RT01655 Good 7.9497 4.0821 2.4 4 0.0052 0.65RT01664 Good 7.7059 5.2513 0.0 0.272 0.065 4 0.0094 2.42RT01668 Good 7.7292 5.2503 2.0 0.0333 0.00RT02002 Good 7.6872 4.0957 0.0 0.450 0.054 0 0.0079 0.00RT02006 Good 7.9439 5.6993 0.0 0.140 0.041 21 0.0070 7.79RT02007 Good 7.7068 5.2119 0.0 0.528 0.063 2 0.0373 0.00RT02008 Good 7.8480 5.3193 0.0 0.170 0.052 7 0.0062 0.00RT02009 Good 7.6617 5.3801 0.0 0.554 0.084 2 0.0114 0.00RT02013 Good 7.7070 5.1120 0.0 0.677 0.058 8 0.0011 3.42RT02015 Good 7.5836 2.7070 0.0 0.360 0.066 22 0.0080 0.00RT02016 Good 7.5319 4.5088 0.0 0.450 0.053 0 0.0247 0.00RT02019 Good 7.6338 4.8002 0.0 0 0.0114 0.00RT02021 Good 7.2127 3.9020 0.0 300 0.0201 0.00RT02027 Good 7.4668 4.6233 4.3 0.980 0.089 11 0.0144 0.00RT02030 Good 7.2179 4.4529 0.0 0.390 0.028 9 0.0071 0.00RT02152 Good 7.2159 2.8955 0.0 0.616 0.056 7 0.0434 0.00RT02153 Good 7.4225 3.9418 0.0 0.600 0.059 50 0.0229 0.00RT02154 Good 7.6501 5.4139 0.0 0.703 0.081 2 0.0098 0.00RT02155 Good 7.6283 3.9590 0.0 0.440 0.110 4 0.0109 0.00RT02156 Good 7.7102 4.3539 0.0 0.360 0.042 2 0.0058 0.00RT02157 Good 7.5057 4.3446 2.3 0.193 0.062 4 0.0054 0.00
Dissolved Oxygen
Biological Oxygen Demand
Total Nitrogen
Total Phosphorus
Fecal Coliform
Effects Range-Median Quotient
Physically Altered
(mg/L) (mg/L) (mg/L) (mg/L) (col/100mL) (score) (%)pHStation QualityRT02160 Good 7.6408 5.9813 0.0 0.190 0.048 0 0.0044 0.00RT02162 Good 7.3798 4.3490 2.2 0.220 0.030 0 0.0099 0.00RT02164 Good 7.6971 4.7694 2.7 0.230 0.047 2 0.0200 0.00RT02165 Good 7.4775 5.2735 0.0 0.676 0.099 13 0.0203 0.00RT02167 Good 7.3698 3.5423 0.0 0.518 0.061 7 0.0230 0.00RT02171 Good 7.6727 5.1096 0.0 4 0.0033 0.00RT99001 Good 7.5530 3.9111 1.9 1.270 0.120 13 0.0365 0.00RT99003 Good 7.4610 3.6832 1.0 0.670 0.000 22 0.0171 0.00RT99004 Good 7.6089 3.6987 1.8 1.120 0.110 8 0.0071 0.00RT99005 Marginal 7.5094 3.9554 7.2 0.630 0.120 0 0.0230 7.33RT99006 Good 7.7774 4.8492 2.3 0.860 0.160 70 0.0075 0.00RT99008 Good 7.5014 1.4 0.800 0.100 2 0.0137 0.00RT99009 Marginal 7.2840 2.5346 1.6 0.800 0.100 130 0.0293 7.29RT99010 Good 7.3692 4.4555 5.5 0.570 0.110 8 0.0186 0.00RT99012 Good 7.5025 3.8820 3.8 0.440 0.100 0 0.0080 0.00RT99013 Good 7.5877 3.7479 1.3 0.790 0.000 4 0.0328 0.00RT99017 Marginal 7.3801 5.5448 3.4 0.890 0.110 300 0.0148 29.98RT99019 Good 7.4491 4.0051 2.3 0.700 0.070 4 0.0036 15.51RT99022 Good 7.6338 3.5227 1.3 0.530 0.100 30 0.0139 10.08RT99024 Good 7.3986 3.4727 1.3 0.350 0.080 11 0.0062 0.00RT99026 Good 7.3060 2.6517 2.2 0.860 0.000 0 0.0082 0.00RT99027 Good 7.3031 4.7376 2.2 0.050 13 0.0066 8.85RT99028 Good 7.7196 4.4916 1.2 0.210 0.100 0 0.0135 0.00RT99029 Good 7.6012 4.5 0.840 0.080 8 0.0060 0.00RT99030 Marginal 7.4935 3.6781 2.1 0.350 0.120 13 0.0142 21.25RT99036 Good 7.4770 4.0399 1.4 1.210 0.130 8 0.0367 0.00RT99037 Good 7.1212 3.0551 3.6 0.440 0.100 60 0.0053 0.00RT99038 Good 7.8472 4.7741 4.1 0.190 0.230 0 0.0157 0.00RT99039 Good 7.6538 3.6321 1.1 0.540 0.120 4 0.0063 0.00RT99040 Good 7.4809 4.3865 7.7 1.050 0.110 8 0.0075 0.00
7.0268 2.4214 0.0 0.1400 0.000 0 0.0003 0.007.9497 6.0240 7.7 1.3950 0.250 900 0.0434 29.980.9229 3.6026 7.7 1.2550 0.250 900 0.0431 29.987.5359 4.3153 1.3 0.6151 0.089 32 0.0130 2.14
RangeOverall Average
MinimumMaximum
Appendix B. Physical features and overall environmental quality of 97 stations
sampled in 1999-2002. Data that were not available or applicable were left
blank. Minimum, maximum, range, and average values were calculated using 96
good and marginal stations. *Poor station (NT02301) was not included in
calculating minimum, maximum, range, and average values and was eliminated
in final analysis. See text for details.
Temperature Salinity Width Depth W/D Ratio Sinuosity Rivulets Latitude Longitude(degrees C) (ppt) (m) (m) (m) (m) (number) (decimal decrees (decimal decrees
MR1-01-T Marginal 2002 July 29.69 28.91 77.58 2.43 31.99 830.50 31 32.2237 -80.9256 UpstreamMR3-03-T Good 2002 August 28.97 33.51 73.55 3.88 18.98 900.89 19 32.2112 -80.8152MR3-04-T Good 2002 July 29.52 33.20 72.87 2.20 33.12 922.68 22 32.2223 -80.8078NT01598 Good 2001 July 30.13 29.57 44.10 3.80 11.61 754.70 19 32.7995 -79.8708NT02301* Poor 2002 August 28.38 27.00 90.11 4.25 21.18 735.63 12 32.7913 -79.8830RT00501 Good 2000 August 30.50 30.00 69.65 3.10 22.47 989.55 17 32.0896 -80.9150RT00502 Good 2000 July 28.67 25.64 126.36 1.80 70.20 918.63 25 32.6066 -80.5369 UpstreamRT00503 Good 2000 July 29.46 34.71 88.17 1.90 46.40 875.83 14 32.5996 -80.2028RT00504 Good 2000 June 29.36 33.21 124.07 1.50 82.70 929.45 26 32.4153 -80.5978RT00505 Good 2000 July 30.81 36.23 76.86 3.40 22.60 734.54 13 33.0360 -79.3952 UpstreamRT00517 Good 2000 June 29.51 35.90 43.03 1.70 25.30 548.02 15 32.3015 -80.5842RT00518 Marginal 2000 July 28.66 28.56 56.45 1.90 29.70 860.13 24 32.6068 -80.2737RT00519 Good 2000 July 30.46 33.80 38.53 2.10 18.30 748.15 12 32.5506 -80.8343RT00520 Good 2000 July 30.57 35.27 85.49 2.90 29.50 963.36 27 32.8143 -79.7547RT00521 Good 2000 July 30.56 36.49 63.16 2.00 31.60 915.41 15 33.0378 -79.4919RT00523 Marginal 2000 July 28.92 33.11 40.93 1.50 27.30 900.86 8 32.5042 -80.3058RT00525 Good 2000 July 30.47 37.11 36.42 2.40 15.20 738.71 28 32.9037 -79.6263RT00528 Good 2000 June 29.38 26.62 45.20 1.00 45.20 910.68 31 32.5884 -80.4494RT00531 Good 2000 July 29.63 23.63 100.75 2.40 42.00 829.34 19 32.8994 -79.9011 DownstreamRT00541 Good 2000 August 30.13 34.47 92.89 3.60 25.80 780.74 26 32.1581 -80.8428RT00542 Marginal 2000 July 29.79 33.66 35.76 0.60 59.60 903.42 12 32.6465 -80.0576 UpstreamRT00543 Good 2000 June 29.59 31.78 85.86 2.40 35.80 885.59 24 32.4717 -80.5082RT00544 Good 2000 July 29.36 34.68 62.62 3.00 20.90 732.16 15 32.6466 -79.9880RT00545 Good 2000 August 28.39 36.55 84.24 1.90 44.34 986.02 8 33.8437 -78.6066RT00546 Good 2000 August 30.03 34.82 60.95 3.00 20.30 947.04 14 32.1808 -80.8215RT00547 Good 2000 July 29.42 34.73 54.21 1.60 33.90 495.71 9 32.5833 -80.1873 UpstreamRT00550 Good 2000 August 29.37 36.16 71.75 2.10 34.20 854.88 16 33.5658 -79.0210RT00554 Good 2000 August 29.70 23.89 113.73 2.50 45.50 919.59 44 32.1558 -80.9517RT00557 Good 2000 July 30.80 33.86 58.61 0.85 69.00 781.34 23 32.5057 -80.7580RT00558 Good 2000 July 30.59 35.44 43.49 2.50 17.40 379.82 6 33.0466 -79.5350
Relative Location
Month of Samping
Year of SamplingStation Quality
Temperature Salinity Width Depth W/D Ratio Sinuosity Rivulets Latitude Longitude(degrees C) (ppt) (m) (m) (m) (m) (number) (decimal decrees (decimal decrees
Relative Location
Month of Samping
Year of SamplingStation Quality
RT01602 Good 2001 July 31.81 30.74 192.70 3.60 53.53 808.90 33 32.2166 -80.9158 DownstreamRT01603 Good 2001 August 29.91 26.10 94.40 4.40 21.45 743.80 17 32.5920 -80.5387 DownstreamRT01604 Good 2001 August 30.35 34.41 103.60 1.80 57.56 919.10 10 32.4341 -80.8618RT01606 Good 2001 July 28.83 34.97 105.10 3.30 31.85 598.20 16 33.0399 -79.3781 DownstreamRT01619 Good 2001 August 27.97 35.68 43.40 2.30 18.87 243.30 32 32.3134 -80.5794RT01624 Good 2001 August 27.85 35.91 86.30 4.00 21.58 933.30 21 32.3173 -80.5195RT01642 Good 2001 August 30.36 33.70 32.30 2.00 16.15 971.10 18 32.6211 -80.0011RT01643 Good 2001 August 30.08 30.06 73.50 5.30 13.87 729.62 35 32.5209 -80.5778RT01645 Good 2001 July 28.70 35.90 96.40 3.50 27.54 790.90 26 33.3494 -79.1760RT01646 Good 2001 July 30.88 31.19 104.00 2.30 45.22 997.30 11 32.1621 -80.8672RT01647 Marginal 2001 August 31.60 31.74 78.44 1.30 60.34 761.47 24 32.6327 -80.0854RT01648 Good 2001 August 29.97 24.24 58.80 3.80 15.47 772.80 29 32.4892 -80.5288RT01649 Good 2001 August 30.52 33.80 58.20 3.90 14.92 719.10 18 32.6601 -79.9765RT01650 Good 2001 July 28.38 29.16 84.30 1.40 60.21 947.60 13 33.8571 -78.5748 DownstreamRT01652 Good 2001 August 30.54 33.29 48.50 3.30 14.70 598.10 23 32.5649 -80.2251RT01653 Good 2001 July 29.29 32.57 102.90 2.10 49.00 866.30 19 32.4197 -80.5719RT01655 Good 2001 July 29.04 36.59 50.20 1.20 41.83 857.40 38 33.5318 -79.0531RT01664 Good 2001 August 27.61 34.70 124.70 4.10 30.41 979.50 9 32.3247 -80.4873RT01668 Good 2001 July 29.31 34.93 56.40 2.40 23.50 942.30 22 32.9605 -79.6152RT02002 Good 2002 August 29.61 36.37 72.69 4.40 16.52 977.12 28 32.3065 -80.5479 UpstreamRT02006 Good 2002 July 30.32 33.40 87.01 2.55 34.12 914.12 10 32.7750 -79.8241RT02007 Good 2002 July 30.18 35.92 77.16 1.87 41.15 915.79 40 32.4872 -80.8039RT02008 Good 2002 July 30.82 35.45 69.05 1.97 34.96 934.56 16 32.7010 -79.9145RT02009 Good 2002 July 30.59 36.04 94.46 2.54 37.23 818.81 41 32.5032 -80.8458RT02013 Good 2002 July 29.99 34.42 77.11 1.40 55.08 862.14 30 32.4624 -80.6649RT02015 Good 2002 June 27.24 36.28 50.66 2.40 21.11 591.79 45 32.5186 -80.5855RT02016 Good 2002 July 31.77 33.13 41.07 2.88 14.29 505.15 13 33.0418 -79.3933RT02019 Good 2002 June 27.84 31.97 49.35 3.58 13.77 819.24 25 32.5045 -80.3774RT02021 Good 2002 June 26.16 24.93 26.51 2.52 10.53 637.48 45 32.6179 -80.3324RT02027 Good 2002 June 28.02 36.86 51.56 2.94 17.55 375.19 18 32.4444 -80.5971RT02030 Good 2002 August 28.63 24.09 35.67 1.68 21.29 444.01 18 32.9419 -79.7884RT02152 Good 2002 August 29.36 27.53 97.80 4.14 23.64 950.06 30 32.1260 -81.0041
Temperature Salinity Width Depth W/D Ratio Sinuosity Rivulets Latitude Longitude(degrees C) (ppt) (m) (m) (m) (m) (number) (decimal decrees (decimal decrees
Relative Location
Month of Samping
Year of SamplingStation Quality
RT02153 Good 2002 July 29.69 33.51 99.33 1.29 77.15 637.14 32 32.3056 -80.9284RT02154 Good 2002 July 31.80 33.46 60.06 1.95 30.80 926.28 28 32.7874 -80.0808RT02155 Good 2002 July 31.33 33.73 54.33 3.35 16.22 652.04 15 32.6252 -80.0253RT02156 Good 2002 August 29.52 37.15 84.56 4.37 19.33 762.91 25 32.3061 -80.5571 DownstreamRT02157 Good 2002 June 28.05 37.19 118.31 4.33 27.35 998.86 31 32.4228 -80.6026RT02160 Good 2002 August 28.88 34.22 58.05 3.05 19.01 598.91 32.2616 -80.7959RT02162 Good 2002 August 28.30 25.61 72.69 2.65 27.43 934.18 18 32.8598 -79.8510RT02164 Good 2002 August 28.36 37.37 38.36 1.92 19.93 865.61 15 32.9084 -79.6400RT02165 Good 2002 July 30.58 34.28 44.08 1.95 22.60 788.27 57 32.5284 -80.7937RT02167 Good 2002 June 27.22 33.85 95.03 2.64 36.03 989.47 29 32.5778 -80.5137RT02171 Good 2002 June 26.80 32.94 29.51 1.09 27.13 542.00 17 32.5774 -80.2209 DownstreamRT99001 Good 1999 July 27.50 33.76 49.55 2.81 17.63 908.67 14 33.0261 -79.4613RT99003 Good 1999 July 28.76 32.35 76.92 3.89 19.77 980.55 20 32.3310 -80.4985RT99004 Good 1999 August 29.23 34.35 89.75 1.12 80.13 656.98 18 32.6439 -80.0437 DownstreamRT99005 Marginal 1999 July 31.11 28.71 132.13 0.88 150.14 946.88 6 32.4404 -80.6522RT99006 Good 1999 August 28.91 32.34 61.53 1.00 61.53 837.15 12 33.8526 -78.5840 UpstreamRT99008 Good 1999 July 29.11 32.09 67.05 2.75 24.38 770.62 23 32.3626 -80.4768RT99009 Marginal 1999 August 31.66 32.61 92.51 1.60 57.82 722.31 14 32.5579 -80.3618RT99010 Good 1999 August 32.53 24.64 40.31 2.78 14.50 794.72 14 32.5063 -80.8020RT99012 Good 1999 August 31.17 35.28 82.78 2.32 35.68 910.03 19 32.2953 -80.6201RT99013 Good 1999 July 29.48 33.61 94.13 2.94 32.02 972.05 20 32.3358 -80.5599RT99017 Marginal 1999 July 29.91 18.78 51.29 1.34 38.28 735.17 13 32.8247 -79.8667RT99019 Good 1999 July 32.10 31.48 38.37 1.99 19.28 780.64 21 32.5622 -80.2441RT99022 Good 1999 July 32.43 30.08 28.54 1.56 18.29 368.74 17 32.1578 -80.7882RT99024 Good 1999 August 32.57 25.69 93.14 4.50 20.70 883.12 9 32.4523 -80.8365RT99026 Good 1999 July 27.51 32.95 66.96 2.17 30.86 974.20 14 33.0843 -79.4201RT99027 Good 1999 July 29.87 20.13 73.05 2.66 27.46 823.65 24 32.8934 -79.9069 UpstreamRT99028 Good 1999 August 30.90 35.89 88.85 3.00 29.62 703.45 16 32.3462 -80.5566RT99029 Good 1999 July 31.66 32.33 28.49 1.29 30.90 523.85 20 32.5762 -80.2242 UpstreamRT99030 Marginal 1999 August 31.40 32.75 123.61 1.63 27.46 821.16 11 32.3885 -80.6334RT99036 Good 1999 July 27.41 32.38 42.13 2.16 75.83 997.55 9 33.0894 -79.3643RT99037 Good 1999 August 29.26 20.35 102.93 1.63 16.72 932.79 14 32.9418 -79.7725RT99038 Good 1999 August 30.83 35.95 47.73 2.00 23.87 920.07 17 32.3436 -80.5464RT99039 Good 1999 August 31.09 34.25 54.84 3.24 16.93 479.45 10 32.5822 -80.1862 DownstreamRT99040 Good 1999 August 31.29 33.43 38.10 2.90 13.10 313.42 8 32.3929 -80.6413
1999 July 26.16 18.78 26.51 0.60 10.53 243.30 6 32.0896 -81.00412002 August 32.57 37.37 192.70 5.30 150.14 998.86 57 33.8571 -78.5748
3 3 6.41 18.59 166.19 4.70 139.61 755.56 51 1.7675 2.42942001 July 29.73 32.30 71.57 2.50 33.08 794.96 21 32.6229 -80.2379
Maximum
Overall AverageRange
Minimum
Appendix C. Fish density (# of individuals/hectare) for two trawls and average
fish density (# of individuals/hectare) at 97 stations sampled in 1999-2002. Zero
values were left blank. *Poor station (NT02301) was eliminated in final analysis.
See text for details.
Taxon Common NamePercent
AbundanceTotal
Abundance MR
1-01
-T
MR
3-03
-T
MR
3-04
-T
NT0
1598
Alosa sapidissima American Shad 0.03 14.49Aluterus schoepfi Orange Filefish 0.03 14.49Anchoa hepsetus Striped Anchovy 0.69 362.32Anchoa mitchilli Bay Anchovy 14.29 7519.07 28.99Archosargus probatocephalus Sheepshead 0.03 14.49 14.49Arius felis Sea Catfish 0.08 43.48Astroscopus y-graecum Stargazer 0.03 14.49Bagre marinus Gafftopsail Catfish 0.14 72.46Bairdiella chrysoura Silver Perch 21.91 11523.54 86.96 115.94Blenniidae Combtooth Blennies 0.03 14.49Brevoortia tyrannus Atlantic Menhaden 0.69 362.32Centropristis philadelphica Rock Sea Bass 0.27 143.37Centropristis striata Black Sea Bass 0.03 14.49Chaetodipterus faber Atlantic Spadefish 1.67 880.95Chilomycterus schoepfi Striped Burrfish 0.46 243.27Chloroscombrus chrysurus Atlantic Bumper 0.28 144.93 14.49Citharichthys macrops Spotted Whiff 0.08 43.48Citharichthys sp. Whiff 0.08 43.48Citharichthys spilopterus Bay Whiff 0.72 376.81 14.49Cynoscion nebulosus Spotted Sea Trout 0.17 86.96Cynoscion regalis Weakfish 3.39 1782.61 14.49 14.49Dasyatis sabina Atlantic Stingray 0.11 57.97Dorosoma cepedianum Gizzard Shad 0.03 14.49Dorosoma petenense Threadfin Shad 0.03 14.49Elops saurus Ladyfish 0.14 72.46Etropus crossotus Fringed Flounder 0.58 304.35 43.48Eucinostomus gula Silver Jenny 0.74 391.30Eucinostomus sp. Mojarra 0.33 173.91 14.49
Common NameAmerican ShadOrange FilefishStriped AnchovyBay AnchovySheepsheadSea CatfishStargazerGafftopsail Catfish Silver PerchCombtooth BlenniesAtlantic MenhadenRock Sea BassBlack Sea BassAtlantic SpadefishStriped BurrfishAtlantic BumperSpotted WhiffWhiffBay WhiffSpotted Sea TroutWeakfishAtlantic StingrayGizzard ShadThreadfin ShadLadyfishFringed FlounderSilver JennyMojarra
NT0
2301
*
RT0
0501
RT0
0502
RT0
0503
RT0
0504
RT0
0505
RT0
0517
RT0
0518
RT0
0519
RT0
0520
RT0
0521
RT0
0523
57.97 333.33 492.75 86.96 173.91 318.84 14.49 231.88 28.99
28.99 28.99 391.30 57.97 536.23 28.99 158.39 202.90 231.8814.49
14.4914.49
14.49 43.48 25.88 28.9928.99 14.49
28.99
14.4928.99
57.97 14.49 14.4914.49
43.4814.49
14.49 14.49
Common NameAmerican ShadOrange FilefishStriped AnchovyBay AnchovySheepsheadSea CatfishStargazerGafftopsail Catfish Silver PerchCombtooth BlenniesAtlantic MenhadenRock Sea BassBlack Sea BassAtlantic SpadefishStriped BurrfishAtlantic BumperSpotted WhiffWhiffBay WhiffSpotted Sea TroutWeakfishAtlantic StingrayGizzard ShadThreadfin ShadLadyfishFringed FlounderSilver JennyMojarra
RT0
0525
RT0
0528
RT0
0531
RT0
0541
RT0
0542
RT0
0543
RT0
0544
RT0
0545
RT0
0546
RT0
0547
RT0
0550
RT0
0554
14.49
72.46 27.43 536.23 115.94 72.46 72.46
14.49
57.97 27.43 376.81 14.49 101.45
260.87 14.4912.94 28.99 14.49
14.4914.49 25.88 14.49 14.49
14.49
57.97 14.4914.49
14.49 72.46 144.93
14.4914.49 14.49 14.49 28.99
28.99 43.48 202.90 14.49
Common NameAmerican ShadOrange FilefishStriped AnchovyBay AnchovySheepsheadSea CatfishStargazerGafftopsail Catfish Silver PerchCombtooth BlenniesAtlantic MenhadenRock Sea BassBlack Sea BassAtlantic SpadefishStriped BurrfishAtlantic BumperSpotted WhiffWhiffBay WhiffSpotted Sea TroutWeakfishAtlantic StingrayGizzard ShadThreadfin ShadLadyfishFringed FlounderSilver JennyMojarra
RT0
0557
RT0
0558
RT0
1602
RT0
1603
RT0
1604
RT0
1606
RT0
1619
RT0
1624
RT0
1642
RT0
1643
RT0
1645
RT0
1646
101.45 72.46 188.41 57.97 14.49 14.49 14.49
144.93 478.26 67.93 14.49 14.49 14.49 57.97
14.49 14.49
43.48 43.4814.49
28.99
14.49 28.99
43.48 14.49 43.48 72.46
43.48 14.4914.49
Common NameAmerican ShadOrange FilefishStriped AnchovyBay AnchovySheepsheadSea CatfishStargazerGafftopsail Catfish Silver PerchCombtooth BlenniesAtlantic MenhadenRock Sea BassBlack Sea BassAtlantic SpadefishStriped BurrfishAtlantic BumperSpotted WhiffWhiffBay WhiffSpotted Sea TroutWeakfishAtlantic StingrayGizzard ShadThreadfin ShadLadyfishFringed FlounderSilver JennyMojarra
RT0
1647
RT0
1648
RT0
1649
RT0
1650
RT0
1652
RT0
1653
RT0
1655
RT0
1664
RT0
1668
RT0
2002
RT0
2006
14.49 14.49 14.49 42.36 57.97
14.49 14.49173.91 724.64 188.41 217.39 43.48 14.49 139.35 28.99
14.49
86.96 14.49 14.4914.49 14.49
14.49 28.99
14.49 14.49
Common NameAmerican ShadOrange FilefishStriped AnchovyBay AnchovySheepsheadSea CatfishStargazerGafftopsail Catfish Silver PerchCombtooth BlenniesAtlantic MenhadenRock Sea BassBlack Sea BassAtlantic SpadefishStriped BurrfishAtlantic BumperSpotted WhiffWhiffBay WhiffSpotted Sea TroutWeakfishAtlantic StingrayGizzard ShadThreadfin ShadLadyfishFringed FlounderSilver JennyMojarra
RT0
2007
RT0
2008
RT0
2009
RT0
2013
RT0
2015
RT0
2016
RT0
2019
RT0
2021
RT0
2027
RT0
2030
RT0
2152
RT0
2153
57.97 86.96 28.99 57.97 159.42 304.35
159.42 130.43 14.49 246.38 72.46 14.49
14.49 14.49 14.49
14.49 14.49 28.99 14.49
14.49 14.49
14.4914.49 14.49 14.49
14.49173.91 14.49 130.43 14.49 14.49
14.49
Common NameAmerican ShadOrange FilefishStriped AnchovyBay AnchovySheepsheadSea CatfishStargazerGafftopsail Catfish Silver PerchCombtooth BlenniesAtlantic MenhadenRock Sea BassBlack Sea BassAtlantic SpadefishStriped BurrfishAtlantic BumperSpotted WhiffWhiffBay WhiffSpotted Sea TroutWeakfishAtlantic StingrayGizzard ShadThreadfin ShadLadyfishFringed FlounderSilver JennyMojarra
RT0
2154
RT0
2155
RT0
2156
RT0
2157
RT0
2160
RT0
2162
RT0
2164
RT0
2165
RT0
2167
RT0
2171
RT9
9001
28.99 57.97 86.96 130.43
14.49
14.49 101.45 28.99 1028.99 144.93 72.46 14.49
14.4914.49 14.49 14.49
14.49 57.97 43.48 144.93 14.49
14.49144.93
28.9914.49 28.99 72.46 14.49 43.48
14.49 14.49
101.45 14.49
14.49 115.94
Common NameAmerican ShadOrange FilefishStriped AnchovyBay AnchovySheepsheadSea CatfishStargazerGafftopsail Catfish Silver PerchCombtooth BlenniesAtlantic MenhadenRock Sea BassBlack Sea BassAtlantic SpadefishStriped BurrfishAtlantic BumperSpotted WhiffWhiffBay WhiffSpotted Sea TroutWeakfishAtlantic StingrayGizzard ShadThreadfin ShadLadyfishFringed FlounderSilver JennyMojarra
RT9
9003
RT9
9004
RT9
9005
RT9
9006
RT9
9008
RT9
9009
RT9
9010
RT9
9012
RT9
9013
RT9
9017
RT9
9019
86.96 101.45 14.49 28.99 14.4928.99 318.84 188.41 217.39 28.99 14.49 101.45 130.43
14.49 28.9928.99 57.97 550.72 1101.45 14.49 72.46 28.99 318.84 86.96 57.97
14.49
14.49 14.4957.97 28.99
14.4914.49
86.96 28.99 14.49 173.91 144.93
14.49
28.99 14.49
Common NameAmerican ShadOrange FilefishStriped AnchovyBay AnchovySheepsheadSea CatfishStargazerGafftopsail Catfish Silver PerchCombtooth BlenniesAtlantic MenhadenRock Sea BassBlack Sea BassAtlantic SpadefishStriped BurrfishAtlantic BumperSpotted WhiffWhiffBay WhiffSpotted Sea TroutWeakfishAtlantic StingrayGizzard ShadThreadfin ShadLadyfishFringed FlounderSilver JennyMojarra
RT9
9022
RT9
9024
RT9
9026
RT9
9027
RT9
9028
RT9
9029
RT9
9030
RT9
9036
RT9
9037
RT9
9038
RT9
9039
RT9
9040
14.49
14.49 72.46 28.99115.94 579.71 43.48 202.90 289.86 623.19 28.99 391.30
14.4914.49
57.97 507.25 28.99 231.88 57.97 840.58 463.77 115.94 14.49 101.45
14.49 57.97 28.99 57.97 14.49
28.99
246.38 28.99 14.49
14.4914.49
43.48
Taxon Common NamePercent
AbundanceTotal
Abundance MR
1-01
-T
MR
3-03
-T
MR
3-04
-T
NT0
1598
Gobiidae Goby 0.00 0.00Gymnura micrura Smooth Butterfly Ray 0.39 202.90 43.48Hypsoblennius hentzi Feather Blenny 0.06 28.99 14.49Lagodon rhomboides Pinfish 14.44 7595.63 637.68Leiostomus xanthurus Spot 23.79 12513.33 188.41 159.42Lepisosteus osseus Longnose Gar 0.17 86.96Lutjanus synagris Lane Snapper 0.03 14.49Menticirrhus americanus Southern Kingfish 0.03 14.49Menticirrhus sp. Kingfish 0.14 72.46Micropogonias undulatus Atlantic Croaker 3.88 2043.48 14.49Mugil cephalus Striped Mullet 0.13 70.91Opsanus tau Oyster Toadfish 0.91 478.26 14.49Orthopristis chrysoptera Pigfish 1.63 855.07 14.49 14.49Paralichthys dentatus Summer Flounder 0.25 130.43Paralichthys lethostigma Southern Flounder 0.30 158.86Peprilus alepidotus Harvestfish 0.06 28.99Prionotus scitulus Leopard Searobin 0.03 14.49Prionotus tribulus Bighead Searobin 0.03 14.49Rhizoprionodon terraenovae Atlantic Sharpnose Shark 0.06 28.99Scomberomorus maculatus Spanish Mackerel 0.08 43.48 14.49Selene vomer Lookdown 1.12 590.54 14.49 28.99Stellifer lanceolatus Star Drum 0.52 275.36Stephanolepis hispidus Planehead Filefish 0.17 86.96Symphurus plagiusa Blackcheek Tounguefish 0.22 115.94Synodus foetens Inshore Lizardfish 0.36 188.41 14.49 14.49Trinectes maculatus Hogchoker 4.19 2202.90 14.49
Overall Total 100.00 52601.80 86.96 449.28 333.33 695.65Average Density (n=2) 26300.90 43.48 224.64 166.67 347.83
*Excluded from analysis
Common NameGobySmooth Butterfly RayFeather BlennyPinfishSpotLongnose GarLane SnapperSouthern KingfishKingfishAtlantic CroakerStriped MulletOyster ToadfishPigfishSummer FlounderSouthern FlounderHarvestfishLeopard SearobinBighead SearobinAtlantic Sharpnose SharkSpanish MackerelLookdownStar DrumPlanehead FilefishBlackcheek TounguefishInshore LizardfishHogchoker
Overall TotalAverage Density (n=2)
*Excluded from analysis
NT0
2301
*
RT0
0501
RT0
0502
RT0
0503
RT0
0504
RT0
0505
RT0
0517
RT0
0518
RT0
0519
RT0
0520
RT0
0521
RT0
0523
14.49
14.49 12.94 14.49 43.4857.97 14.49 347.83 43.48 14.49 57.97 347.83 43.48 173.91
14.49
14.49
14.49 28.99 86.96 28.99
14.49 14.49 43.4814.49
14.4914.49
14.49
28.99
14.49 86.96 28.99173.91 405.80 0 898.55 565.22 202.90 260.87 1536.23 86.96 197.20 521.74 695.6586.96 202.90 0 449.28 282.61 101.45 130.43 768.12 43.48 98.60 260.87 347.83
Common NameGobySmooth Butterfly RayFeather BlennyPinfishSpotLongnose GarLane SnapperSouthern KingfishKingfishAtlantic CroakerStriped MulletOyster ToadfishPigfishSummer FlounderSouthern FlounderHarvestfishLeopard SearobinBighead SearobinAtlantic Sharpnose SharkSpanish MackerelLookdownStar DrumPlanehead FilefishBlackcheek TounguefishInshore LizardfishHogchoker
Overall TotalAverage Density (n=2)
*Excluded from analysis
RT0
0525
RT0
0528
RT0
0531
RT0
0541
RT0
0542
RT0
0543
RT0
0544
RT0
0545
RT0
0546
RT0
0547
RT0
0550
RT0
0554
14.49 28.9914.49
28.99 14.49 157.87 231.88 14.49 217.39391.30 57.97 14.49 269.67 188.41 101.45 43.48 362.32
14.49
14.49 86.96 43.48 14.49 28.9970.91
14.49 14.4928.99 14.49
43.48 14.49 14.4914.49
14.4914.49 14.49
25.8886.96
57.9714.49 14.49
14.49 28.99 14.4914.49 14.49 86.96 14.49144.93 768.12 72.46 144.93 661.49 913.04 1086.96 43.48 86.96 1086.96 333.33 304.3572.46 384.06 36.23 72.46 330.75 456.52 543.48 21.74 43.48 543.48 166.67 152.17
Common NameGobySmooth Butterfly RayFeather BlennyPinfishSpotLongnose GarLane SnapperSouthern KingfishKingfishAtlantic CroakerStriped MulletOyster ToadfishPigfishSummer FlounderSouthern FlounderHarvestfishLeopard SearobinBighead SearobinAtlantic Sharpnose SharkSpanish MackerelLookdownStar DrumPlanehead FilefishBlackcheek TounguefishInshore LizardfishHogchoker
Overall TotalAverage Density (n=2)
*Excluded from analysis
RT0
0557
RT0
0558
RT0
1602
RT0
1603
RT0
1604
RT0
1606
RT0
1619
RT0
1624
RT0
1642
RT0
1643
RT0
1645
RT0
1646
14.49
57.97 376.81 308.88 86.96 289.86 28.99 72.46 14.49101.45 43.48 376.81 113.22 246.38 43.48 28.99 28.99 14.49 101.45
43.48 43.48
14.49 14.4943.48 86.96 14.49 14.49
14.4914.49
14.49 14.49 14.49 14.49
14.4928.99 101.45 14.49 14.49 14.49
492.75 666.67 898.55 43.48 504.53 913.04 405.80 144.93 101.45 173.91 101.45 159.42246.38 333.33 449.28 21.74 252.26 456.52 202.90 72.46 50.72 86.96 50.72 79.71
Common NameGobySmooth Butterfly RayFeather BlennyPinfishSpotLongnose GarLane SnapperSouthern KingfishKingfishAtlantic CroakerStriped MulletOyster ToadfishPigfishSummer FlounderSouthern FlounderHarvestfishLeopard SearobinBighead SearobinAtlantic Sharpnose SharkSpanish MackerelLookdownStar DrumPlanehead FilefishBlackcheek TounguefishInshore LizardfishHogchoker
Overall TotalAverage Density (n=2)
*Excluded from analysis
RT0
1647
RT0
1648
RT0
1649
RT0
1650
RT0
1652
RT0
1653
RT0
1655
RT0
1664
RT0
1668
RT0
2002
RT0
2006
28.99 14.49
1362.32 188.41 144.93 188.41 1115.94 43.48797.10 57.97 43.48 565.22 14.49 14.49 463.77 942.03 14.49 14.49
14.49101.45 246.38 14.49 86.96
14.49 14.49 14.4957.97 28.99 14.49 14.49
14.4914.49 13.94
14.49 28.99 14.49 28.43
14.49
57.97 14.4943.48 260.87 28.99 14.49 28.99 289.86
2652.17 927.54 463.77 173.91 1536.23 101.45 1188.41 637.68 1376.81 253.07 144.931326.09 463.77 231.88 86.96 768.12 50.72 594.20 318.84 688.41 126.53 72.46
Common NameGobySmooth Butterfly RayFeather BlennyPinfishSpotLongnose GarLane SnapperSouthern KingfishKingfishAtlantic CroakerStriped MulletOyster ToadfishPigfishSummer FlounderSouthern FlounderHarvestfishLeopard SearobinBighead SearobinAtlantic Sharpnose SharkSpanish MackerelLookdownStar DrumPlanehead FilefishBlackcheek TounguefishInshore LizardfishHogchoker
Overall TotalAverage Density (n=2)
*Excluded from analysis
RT0
2007
RT0
2008
RT0
2009
RT0
2013
RT0
2015
RT0
2016
RT0
2019
RT0
2021
RT0
2027
RT0
2030
RT0
2152
RT0
2153
14.49 14.49
275.36 318.84 101.45 43.48 28.99 28.9928.99 115.94 391.30 115.94 57.97 753.62 86.96 28.99
14.49
14.49 14.49202.90 57.97 173.91 14.49
14.49 28.99 14.49 14.49 14.4928.99 43.48 43.48 28.99 57.97
14.49 43.48
14.4943.48 14.49
159.42
14.49 14.49 14.49
28.99 14.49 43.4886.96 666.67 362.32 28.99 826.09 637.68 347.83 1463.77 391.30 28.99 231.88 449.2843.48 333.33 181.16 14.49 413.04 318.84 173.91 731.88 195.65 14.49 115.94 224.64
Common NameGobySmooth Butterfly RayFeather BlennyPinfishSpotLongnose GarLane SnapperSouthern KingfishKingfishAtlantic CroakerStriped MulletOyster ToadfishPigfishSummer FlounderSouthern FlounderHarvestfishLeopard SearobinBighead SearobinAtlantic Sharpnose SharkSpanish MackerelLookdownStar DrumPlanehead FilefishBlackcheek TounguefishInshore LizardfishHogchoker
Overall TotalAverage Density (n=2)
*Excluded from analysis
RT0
2154
RT0
2155
RT0
2156
RT0
2157
RT0
2160
RT0
2162
RT0
2164
RT0
2165
RT0
2167
RT0
2171
RT9
9001
14.49
130.43 86.96 14.49 217.39 72.46 14.49 28.9914.49 14.49 28.99 159.42 14.49 14.49 72.46 144.93 14.49
43.48 14.49
14.49 14.4914.49 28.99 217.39 72.46
28.99 14.49 14.49 57.97 14.4928.99 14.49 14.49 86.96 43.48
14.4914.49 14.49
28.99 14.49
14.4914.49
14.4928.99 14.49 405.80 28.99 86.96260.87 333.33 231.88 130.43 565.22 217.39 2130.43 449.28 463.77 202.90 202.90130.43 166.67 115.94 65.22 282.61 108.70 1065.22 224.64 231.88 101.45 101.45
Common NameGobySmooth Butterfly RayFeather BlennyPinfishSpotLongnose GarLane SnapperSouthern KingfishKingfishAtlantic CroakerStriped MulletOyster ToadfishPigfishSummer FlounderSouthern FlounderHarvestfishLeopard SearobinBighead SearobinAtlantic Sharpnose SharkSpanish MackerelLookdownStar DrumPlanehead FilefishBlackcheek TounguefishInshore LizardfishHogchoker
Overall TotalAverage Density (n=2)
*Excluded from analysis
RT9
9003
RT9
9004
RT9
9005
RT9
9006
RT9
9008
RT9
9009
RT9
9010
RT9
9012
RT9
9013
RT9
9017
RT9
9019
57.97 28.99 57.97 115.94 14.49710.14 130.43 28.99 28.99 202.90 637.68 57.97 376.81 57.97 115.94
115.94 14.49 72.46 86.96
14.49 14.4943.48
101.45 14.49 43.48
130.43 72.46 173.911173.91 478.26 782.61 420.29 1623.19 1159.42 159.42 144.93 1101.45 463.77 318.84586.96 239.13 391.30 210.14 811.59 579.71 79.71 72.46 550.72 231.88 159.42
Common NameGobySmooth Butterfly RayFeather BlennyPinfishSpotLongnose GarLane SnapperSouthern KingfishKingfishAtlantic CroakerStriped MulletOyster ToadfishPigfishSummer FlounderSouthern FlounderHarvestfishLeopard SearobinBighead SearobinAtlantic Sharpnose SharkSpanish MackerelLookdownStar DrumPlanehead FilefishBlackcheek TounguefishInshore LizardfishHogchoker
Overall TotalAverage Density (n=2)
*Excluded from analysis
RT9
9022
RT9
9024
RT9
9026
RT9
9027
RT9
9028
RT9
9029
RT9
9030
RT9
9036
RT9
9037
RT9
9038
RT9
9039
RT9
9040
14.49
115.94 130.43 28.99 14.4957.97 884.06 159.42 72.46 14.49 43.48 28.99
14.49 57.97 14.49
14.49 14.49 14.4914.49 28.99 14.49
28.99
14.4914.49 43.48 57.97
28.99
57.97318.84 1101.45 1347.83 739.13 405.80 115.94 1623.19 594.20 14.49 797.10 144.93 217.39159.42 550.72 673.91 369.57 202.90 57.97 811.59 297.10 7.25 398.55 72.46 108.70
Appendix D.1. Life history classification compiled for fish taxa caught and
identified in trawls at tidal creek stations sampled in 1999-2002 and species that
comprise taxonomic categories that were higher than species level, but were not
identified in trawls (1=Yes; 0=No; blank=no information available, treated as a 0
in the final analysis). For fish metric definitions, refer to Table 2.
Taxon Common NameEstuarine
DependentEstuarine Nursery
Tidal Creek Nursery
Estuarine Resident
Tidal Creek Resident
Estuarine Spawner
Tidal Creek Spawner
Alosa sapidissima American Shad 1 1 0 0 1 1Aluterus schoepfi Orange Filefish 0 1 1 0 0 1Anchoa hepsetus Striped Anchovy 1 1 1 0 0 1 0Anchoa mitchilli Bay Anchovy 1 1 1 1 1 1 0Archosargus probatocephalus Sheepshead 1 1 1 0 0 0 0Arius felis Sea Catfish 1 1 0 0 1 0Astroscopus y-graecum Stargazer 1 0 0 0 0Bagre marinus Gafftopsail Catfish 1 0 0 0 0Bairdiella chrysoura Silver Perch 1 1 1 1 1 1 1Blenniidae Combtooth Blennies 1 1 1 1 1Brevoortia tyrannus Atlantic Menhaden 1 1 1 0 0 0 0Centropristis philadelphica Rock Sea Bass 1 1 0 0 0 0Centropristis striata Black Sea Bass 0 1 0 0 0 0 0Chaetodipterus faber Atlantic Spadefish 1 1 0 0 0 0Chasmodes bosquianus 1 * Striped Blenny 1 1 1 1 1 1Chilomycterus schoepfi Striped Burrfish 1 1 0 0 0 0Chloroscombrus chrysurus Atlantic Bumper 1 0 0 0 0Citharichthys macrops 2 Spotted Whiff 1 0 0 0 0Citharichthys sp. Whiff 1 0 0 0Citharichthys spilopterus 2 Bay Whiff 1 1 1 0 0 1 0Cynoscion nebulosus Spotted Sea Trout 1 1 0 0 1 0Cynoscion regalis Weakfish 1 1 0 0 1 0Dasyatis sabina Atlantic Stingray 1 1 0 0 1 1Dorosoma cepedianum Gizzard Shad 1 1 0 0 0 0Dorosoma petenense Threadfin Shad 1 0 0 0 0Elops saurus Ladyfish 1 1 1 0 0 0 0Etropus crossotus Fringed Flounder 1 1 1 0 0 0 0Eucinostomus argenteus 3 * Spotfin Mojarra 0 1 1 0 0 0 0Eucinostomus gula 3 Silver Jenny 0 1 0 0 0 0Eucinostomus melanopterus 3 * Flagfin Mojarra 1 1 0 0 0 0Eucinostomus sp. Mojarra 0 1 0 0 0 0Gymnura micrura Smooth Butterfly Ray 1 1 1 1 1
Life History Metrics
Taxon Common NameEstuarine
DependentEstuarine Nursery
Tidal Creek Nursery
Estuarine Resident
Tidal Creek Resident
Estuarine Spawner
Tidal Creek Spawner
Life History Metrics
Hypleurochilus geminatus 1 * Crested Blenny 1 1 1 1 1 1Hypsoblennius hentzi1 Feather Blenny 1 1 1 1 1 1Hypsoblennius ionthas 1 * Freckled Blenny 1 1 1 1 1 1Lagodon rhomboides Pinfish 1 1 1 0 0 0 0Leiostomus xanthurus Spot 1 1 1 0 0 0 0Lepisosteus osseus Longnose Gar 1 1 1 1 1 1Lutjanus synagris Lane Snapper 1 0 0 0 0Menticirrhus americanus 4 Southern Kingfish 1 1 1 0 0 0 0Menticirrhus littoralis 4 * Gulf Kingfish 0 0 0 0 0Menticirrhus saxatalis 4 * Northern Kingfish 1 1 0 0 0 0Menticirrhus sp. Kingfish 1 1 0 0 0 0Micropogonias undulatus Atlantic Croaker 1 1 1 0 0 0 0Mugil cephalus Striped Mullet 1 1 1 0 0 0 0Opsanus tau Oyster Toadfish 1 1 1 1 1 0Orthopristis chrysoptera Pigfish 0 1 1 0 0 1 0Paralichthys dentatus Summer Flounder 1 1 1 0 0 0 0Paralichthys lethostigma Southern Flounder 1 1 1 0 0 0 0Peprilus alepidotus Harvestfish 0 1 0 0 0 0Prionotus scitulus Leopard Searobin 1 0 0 0 0Prionotus tribulus Bighead Searobin 1 1 0 0 0 0Rhizoprionodon terraenovae Atlantic Sharpnose Shark 1 1 0 0 1Scomberomorus maculatus Spanish Mackerel 1 1 0 0 0 0Selene vomer Lookdown 1 1 0 0 0 0Stellifer lanceolatus Star Drum 1 1 0 0 1 0Stephanolepis hispidus Planehead Filefish 0 1 0 0 0 0Symphurus plagiusa Blackcheek Tounguefish 1 1 1 0 0 1 0Synodus foetens Inshore Lizardfish 1 1 0 0 0 0Trinectes maculatus Hogchoker 1 1 1 1*species within higher taxonomic categories found in trawl, but were not reported as catch in 1999-20021species that comprise Blenniidae2species that comprise Citharichthys sp.3species that comprise Eucinostomus sp.4species that comprise Menticirrhus sp.
Appendix D.2. Ecological and trophic classification compiled for fish taxa caught
and identified in trawls at tidal creek stations sampled in 1999-2002 and species
that comprise taxonomic categories that were higher than species level, but were
not identified in trawls (1=Yes; 0=No; blank=no information available, treated as a
0 in the final analysis). For definitions of fish metrics, refer to Table 2.
Taxon Common Name Pelagic BenthicBenthic Feeder Carnivore
Top Predator Detritivore Herbivore Omnivore
Alosa sapidissima American Shad 1 0 0 1 1 0 0Aluterus schoepfi Orange Filefish 0 1 0 0 0 1 0Anchoa hepsetus Striped Anchovy 1 0 0 1 0 0 0Anchoa mitchilli Bay Anchovy 1 0 0 1 0 1 0 0Archosargus probatocephalus Sheepshead 0 1 1 1 0 0 0Arius felis Sea Catfish 0 1 1 1 0 1 0 0Astroscopus y-graecum Stargazer 0 1 1 1 1 0 0Bagre marinus Gafftopsail Catfish 0 1 1 1 1 1 0 0Bairdiella chrysoura Silver Perch 0 1 1 1 1 1 0 0Blenniidae Combtooth Blennies 0 1 1 0 0 0 1Brevoortia tyrannus Atlantic Menhaden 1 0 0 0 0 1 0 1Centropristis philadelphica Rock Sea Bass 0 1 1 1 0 0 0Centropristis striata Black Sea Bass 0 1 1 1 1 1 0 0Chaetodipterus faber Atlantic Spadefish 1 0 1 1 0 1 0 0Chasmodes bosquianus 1 * Striped Blenny 0 1 1 0 0 0 1Chilomycterus schoepfi Striped Burrfish 0 1 1 1 0 0 0Chloroscombrus chrysurus Atlantic Bumper 1 0 0 1 0 1 0 0Citharichthys macrops 2 Spotted Whiff 0 1 1 1 1 0 0Citharichthys sp. Whiff 0 1 1 1 1 0 0Citharichthys spilopterus 2 Bay Whiff 0 1 1 1 1 0 0Cynoscion nebulosus Spotted Sea Trout 0 1 1 1 1 1 0 0Cynoscion regalis Weakfish 0 1 1 1 1 0 0Dasyatis sabina Atlantic Stingray 0 1 1 1 0 1 0 0Dorosoma cepedianum Gizzard Shad 1 0 0 0 0 1 0 1Dorosoma petenense Threadfin Shad 1 0 0 0 0 1 0 1Elops saurus Ladyfish 1 0 1 1 1 1 0 0Etropus crossotus Fringed Flounder 0 1 1 1 0 0 0 0Eucinostomus argenteus 3 * Spotfin Mojarra 0 1 1 1 0 1 0 0Eucinostomus gula 3 Silver Jenny 0 1 1 1 0 1 0 0Eucinostomus melanopterus 3 * Flagfin Mojarra 0 1 1 1 0 1 0 0Eucinostomus sp. Mojarra 0 1 1 1 0 1 0 0Gymnura micrura Smooth Butterfly Ray 0 1 1 1 1 0 0
Ecological and Trophic Metrics
Taxon Common Name Pelagic BenthicBenthic Feeder Carnivore
Top Predator Detritivore Herbivore Omnivore
Ecological and Trophic Metrics
Hypleurochilus geminatus 1 * Crested Blenny 0 1 1 0 0 0 1Hypsoblennius hentzi1 Feather Blenny 0 1 1 0 0 0 1Hypsoblennius ionthas 1 * Freckled Blenny 0 1 1 0 0 0 1Lagodon rhomboides Pinfish 0 1 1 0 0 1 0 1Leiostomus xanthurus Spot 0 1 1 1 0 1 0 0Lepisosteus osseus Longnose Gar 1 0 1 1 1 0 0Lutjanus synagris Lane Snapper 0 1 1 1 0 0 0Menticirrhus americanus 4 Southern Kingfish 0 1 1 1 0 1 0 0Menticirrhus littoralis 4 * Gulf Kingfish 0 1 1 1 0 0 0Menticirrhus saxatalis 4 * Northern Kingfish 0 1 1 1 0 1 0 0Menticirrhus sp. Kingfish 0 1 1 1 0 1 0 0Micropogonias undulatus Atlantic Croaker 0 1 1 1 0 1 0 0Mugil cephalus Striped Mullet 1 0 1 0 0 1 0 1Opsanus tau Oyster Toadfish 0 1 1 1 1 0 0Orthopristis chrysoptera Pigfish 0 1 1 1 0 1 0 0Paralichthys dentatus Summer Flounder 0 1 1 1 1 0 0Paralichthys lethostigma Southern Flounder 0 1 1 1 1 0 0Peprilus alepidotus Harvestfish 1 0 0 1 0 1 0 0Prionotus scitulus Leopard Searobin 0 1 1 1 0 0 0Prionotus tribulus Bighead Searobin 0 1 1 1 0 1 0 0Rhizoprionodon terraenovae Atlantic Sharpnose Shark 0 1 1 1 1 0 0Scomberomorus maculatus Spanish Mackerel 1 0 0 1 1 0 0Selene vomer Lookdown 1 0 1 1 1 0 0Stellifer lanceolatus Star Drum 0 1 1 1 0 0 0Stephanolepis hispidus Planehead Filefish 1 0 1 1 0 1 0 0Symphurus plagiusa Blackcheek Tounguefish 0 1 1 0 0 1 0 1Synodus foetens Inshore Lizardfish 0 1 0 1 1 0 0Trinectes maculatus Hogchoker 0 1 1 1 0 1 0 0*species within higher taxonomic categories found in trawl, but were not reported as catch in 1999-20021species that comprise Blenniidae2species that comprise Citharichthys sp.
4species that comprise for Menticirrhus sp.
3species that comprise Eucinostomus sp.
Appendix D.3. Relative tolerance classification compiled for fish taxa caught and
identified in trawls at tidal creek stations sampled in 1999-2002 and species that
comprise taxonomic categories that were higher than species level, but were not
identified in trawls (1=Yes; 0=No; blank=no information available, treated as a 0
in the final analysis). For definitions of fish metrics, refer to Table 2.
Taxon Common NameBay
Anchovy Shad Flatfish Flounder ResilientSalinity
Independent Sciaenid
Tolerance Metrics
Hypleurochilus geminatus 1 * Crested Blenny 0 0 0 0 0Hypsoblennius hentzi1 Feather Blenny 0 0 0 0 0Hypsoblennius ionthas 1 * Freckled Blenny 0 0 0 0 0Lagodon rhomboides Pinfish 0 0 0 0 1 0Leiostomus xanthurus Spot 0 0 0 0 1 1Lepisosteus osseus Longnose Gar 0 0 0 0 0 0Lutjanus synagris Lane Snapper 0 0 0 0 1 0Menticirrhus americanus 4 Southern Kingfish 0 0 0 0 1Menticirrhus littoralis 4 * Gulf Kingfish 0 0 0 0 1 1Menticirrhus saxatalis 4 * Northern Kingfish 0 0 0 0 1 1Menticirrhus sp. Kingfish 0 0 0 0 1Micropogonias undulatus Atlantic Croaker 0 0 0 0 0 1Mugil cephalus Striped Mullet 0 0 0 0 1 0Opsanus tau Oyster Toadfish 0 0 0 0 0Orthopristis chrysoptera Pigfish 0 0 0 0 0Paralichthys dentatus Summer Flounder 0 0 1 1 0Paralichthys lethostigma Southern Flounder 0 0 1 1 0Peprilus alepidotus Harvestfish 0 0 0 0 1 0Prionotus scitulus Leopard Searobin 0 0 0 0 0Prionotus tribulus Bighead Searobin 0 0 0 0 0Rhizoprionodon terraenovae Atlantic Sharpnose Shark 0 0 0 0 1 0Scomberomorus maculatus Spanish Mackerel 0 0 0 0 1 0Selene vomer Lookdown 0 0 0 0 0Stellifer lanceolatus Star Drum 0 0 0 0 1Stephanolepis hispidus Planehead Filefish 0 0 0 0 0Symphurus plagiusa Blackcheek Tounguefish 0 0 1 0 1 0Synodus foetens Inshore Lizardfish 0 0 0 0 0Trinectes maculatus Hogchoker 0 0 1 0 0*species within higher taxonomic categories found in trawl, but were not reported as catch in 1999-20021species that comprise Blenniidae
3species that comprise Eucinostomus sp.
2species that comprise Citharichthys sp.
4species that comprise for Menticirrhus sp.
Taxon Common NameBay
Anchovy Shad Flatfish Flounder ResilientSalinity
Independent SciaenidAlosa sapidissima American Shad 0 1 0 0 0 0Aluterus schoepfi Orange Filefish 0 0 0 0 1 0Anchoa hepsetus Striped Anchovy 0 0 0 0 1 1 0Anchoa mitchilli Bay Anchovy 1 0 0 0 1 0Archosargus probatocephalus Sheepshead 0 0 0 0 0Arius felis Sea Catfish 0 0 0 0 0Astroscopus y-graecum Stargazer 0 0 0 0 0Bagre marinus Gafftopsail Catfish 0 0 0 0 0Bairdiella chrysoura Silver Perch 0 0 0 0 1 1 1Blenniidae Combtooth Blennies 0 0 0 0 0Brevoortia tyrannus Atlantic Menhaden 0 0 0 0 1 0Centropristis philadelphica Rock Sea Bass 0 0 0 0 0Centropristis striata Black Sea Bass 0 0 0 0 1 0Chaetodipterus faber Atlantic Spadefish 0 0 0 0 0Chasmodes bosquianus 1 * Striped Blenny 0 0 0 0 0Chilomycterus schoepfi Striped Burrfish 0 0 0 0 0Chloroscombrus chrysurus Atlantic Bumper 0 0 0 0 1 0Citharichthys macrops 2 Spotted Whiff 0 0 1 0 0Citharichthys sp. Whiff 0 0 1 0 0Citharichthys spilopterus 2 Bay Whiff 0 0 1 0 0Cynoscion nebulosus Spotted Sea Trout 0 0 0 0 1 1Cynoscion regalis Weakfish 0 0 0 0 1 1Dasyatis sabina Atlantic Stingray 0 0 0 0 1 0Dorosoma cepedianum Gizzard Shad 0 1 0 0 1 0Dorosoma petenense Threadfin Shad 0 1 0 0 1 0Elops saurus Ladyfish 0 0 0 0 1 0Etropus crossotus Fringed Flounder 0 0 1 0 0Eucinostomus argenteus 3 * Spotfin Mojarra 0 0 0 0 0Eucinostomus gula 3 Silver Jenny 0 0 0 0 0Eucinostomus melanopterus 3 * Flagfin Mojarra 0 0 0 0 0Eucinostomus sp. Mojarra 0 0 0 0 0Gymnura micrura Smooth Butterfly Ray 0 0 0 0 0
Tolerance Metrics
Appendix D.4. Fish metric references, by number. For full list of references, refer
to Appendix D.5.
Taxon Common Name Reference NumberAlosa sapidissima American Shad 19, 24, 50, 51, 88, 89, 95, 106, 114, 152, 153, 163, 170, 174, 195, 197, 199, 239, 245, 268, 293, 306, 315,
315, 316, 317, 320, 321Aluterus schoepfi Orange Filefish 60, 99, 125, 157, 190, 195, 205, 213, 228, 302Anchoa hepsetus Striped Anchovy 8, 24, 31, 50, 51, 60, 109, 110, 121, 170, 188, 191, 192, 197, 205, 238, 251, 252, 270, 284, 288, 289, 317
Anchoa mitchilli Bay Anchovy 8, 31, 50, 51, 55, 65, 73, 105, 109, 110, 114, 121, 125, 130, 131, 140, 174, 188, 197, 199, 204, 239, 251, 270, 282, 284, 289, 317
Archosargus probatocephalus Sheepshead 50, 112, 125, 157, 197, 204, 239, 252, 253, 266, 280Arius felis Sea Catfish 50, 54, 60, 65, 100, 116, 144, 192, 204, 205, 212, 239, 251, 252, 272, 303, 324Astroscopus y-graecum Stargazer 24, 34, 50, 65, 70, 145, 187, 239, 252Bagre marinus Gafftopsail Catfish 50, 51, 65, 91, 93, 144, 197, 204, 218, 235, 239, 260, 273, 324Bairdiella chrysoura Silver Perch 7, 24, 30, 36, 38, 50, 51, 52, 55, 110, 126, 157, 173, 174, 185, 195, 197, 202, 205, 225, 235, 242, 243, 251,
260, 261, 269, 270, 282, 284, 286, 303, 309Blenniidae Combtooth Blennies 200, 239, 250Brevoortia tyrannus Atlantic Menhaden 6, 19, 24, 25, 50, 63, 71, 76, 79, 94, 107, 114, 125, 133, 134, 135, 142, 148, 150, 164, 165, 174, 195, 197,
199, 205, 216, 251, 260, 268, 269, 276, 282, 284, 308, 309, 314, 316, 319Centropristis philadelphica Rock Sea Bass 155, 205, 244, 251, 252, 261, 284Centropristis striata Black Sea Bass 2, 19, 24, 51, 138, 139, 157, 174, 195, 196, 197, 205, 251, 253, 284Chaetodipterus faber Atlantic Spadefish 27, 50, 65, 103, 114, 125, 157, 174, 205, 229, 235, 253, 274, 282, 288Chasmodes bosquianus 1 * Striped Blenny 47, 50, 98, 125, 127, 219, 239, 250Chilomycterus schoepfi Striped Burrfish 114, 157, 191, 192, 205, 213, 253, 269, 274Chloroscombrus chrysurus Atlantic Bumper 7, 24, 50, 51, 66, 195, 197, 220, 239, 284Citharichthys macrops 2 Spotted Whiff 8, 222, 252, 261Citharichthys spilopterus 2 Bay Whiff 7, 32, 39, 93, 197, 232, 251, 252, 261, 285, 300, 301Cynoscion nebulosus Spotted Sea Trout 7, 11, 16, 31, 36, 50, 51, 55, 65, 83, 92, 94, 114, 120, 157, 158, 173, 186, 194, 195, 197, 202, 205, 214,
215, 227, 243, 251, 258, 269, 282, 284, 304Cynoscion regalis Weakfish 19, 24, 36, 50, 52, 73, 87, 92, 101, 115, 146, 157, 159, 166, 166, 173, 174, 177, 178, 194, 195, 197, 205,
227, 261, 269, 270, 282, 284, 286, 299, 312, 318Dasyatis sabina Atlantic Stingray 19, 50, 81, 93, 117, 195, 205, 230, 239, 251, 252, 265, 276, 277, 284Dorosoma cepedianum Gizzard Shad 20, 51, 55, 62, 63, 64, 68, 69, 86, 118, 174, 183, 184, 193, 195, 197, 205, 239, 251, 264, 268, 316, 323
Dorosoma petenense Threadfin Shad 55, 57, 86, 118, 132, 170, 184, 193, 195, 205, 251, 315, 316Elops saurus Ladyfish 22, 34, 39, 50, 51, 55, 65, 86, 92, 94, 107, 108, 114, 157, 162, 169, 179, 195, 197, 199, 204, 252, 267, 273,
282Etropus crossotus Fringed Flounder 39, 104, 125, 157, 174, 197, 205, 231, 232, 236, 251, 252, 261, 282, 285Eucinostomus argenteus 3 * Spotfin Mojarra 5, 50, 51, 77, 167, 168, 204, 205, 228, 249, 262, 278, 280, 282, 288, 289, 295, 303Eucinostomus gula 3 Silver Jenny 22, 31, 157, 168, 191, 192, 197, 204, 205, 228, 233, 236, 239, 249, 280, 282, 295, 303, 325Eucinostomus melanopterus 3 * Flagfin Mojarra 5, 66, 249, 255, 256, 295Eucinostomus sp. Mojarra 21, 220, 261, 289, 295, 305Gymnura micrura Smooth Butterfly Ray 50, 51, 66, 172, 193, 205, 218, 239, 251, 252, 284
Taxon Common Name Reference NumberHypleurochilus geminatus 1 * Crested Blenny 154, 239Hypsoblennius hentzi 1 Feather Blenny 47, 50, 97, 114, 125, 154, 157, 205, 218, 239, 250Hypsoblennius ionthas 1 * Freckled Blenny 125, 154, 239, 250Lagodon rhomboides Pinfish 4, 7, 25, 31, 55, 65, 76, 93, 94, 96, 112, 125, 134, 141, 157, 191, 192, 197, 199, 204, 205, 220, 233, 258,
271, 274, 282, 287, 289, 290, 297, 303, 308Leiostomus xanthurus Spot 7, 24, 25, 36, 46, 50, 55, 58, 65, 76, 94, 96, 105, 110, 114, 115, 125, 126, 133, 134, 145, 148, 151, 157,
174, 185, 195, 197, 199, 202, 205, 208, 209, 213, 214, 234, 242, 243, 261, 269, 270, 272, 282, 283, 284, 286, 289, 308, 309, 310
Lepisosteus osseus Longnose Gar 23, 48, 51, 65, 92, 117, 119, 128, 149, 174, 193, 195, 201, 205, 257, 291Lutjanus synagris Lane Snapper 4, 9, 22, 49, 78, 195, 197, 199, 205, 237, 284Menticirrhus americanus 4 Southern Kingfish 17, 24, 36, 46, 50, 76, 94, 114, 124, 129, 157, 174, 194, 239, 269, 270, 275, 284Menticirrhus littoralis 4 * Gulf Kingfish 60, 111, 148, 175, 182, 187, 188, 194, 195, 239, 249, 259, 275, 294, 296, 324, 325Menticirrhus saxatalis 4 * Northern Kingfish 24, 50, 56, 111, 126, 148, 174, 182, 195, 197, 213, 239, 263, 269, 284, 298, 312Micropogonias undulatus Atlantic Croaker 7, 25, 36, 45, 46, 50, 55, 65, 76, 83, 94, 96, 102, 105, 110, 114, 115, 125, 133, 134, 145, 157, 173, 174,
181, 197, 201, 202, 205, 214, 227, 234, 235, 240, 242, 243, 269, 270, 271, 272, 282, 283, 284, 286, 308, 309, 311
Mugil cephalus Striped Mullet 12, 13, 15, 25, 35, 50, 55, 93, 94, 114, 147, 162, 170, 174, 189, 197, 199, 203, 205, 213, 221, 226, 239, 269, 282, 284, 289, 309
Opsanus tau Oyster Toadfish 4, 7, 19, 50, 51, 156, 157, 174, 197, 205, 213, 251, 253, 260, 270, 282, 284Orthopristis chrysoptera Pigfish 4, 24, 31, 53, 110, 114, 122, 157, 197, 205, 251, 252, 290, 303Paralichthys dentatus Summer Flounder 1, 3, 7, 19, 24, 25, 28, 29, 50, 76, 90, 92, 94, 110, 114, 136, 148, 160, 180, 185, 197, 205, 206, 213, 223,
232, 254, 261, 269, 271, 292Paralichthys lethostigma Southern Flounder 7, 25, 28, 29, 50, 65, 76, 92, 94, 162, 174, 180, 197, 205, 232, 235, 242, 261, 269, 271, 289Peprilus alepidotus Harvestfish 24, 27, 118, 174, 195, 197, 205, 269, 284Prionotus scitulus Leopard Searobin 7, 50, 118, 157, 205, 233, 239, 246, 247, 248, 280Prionotus tribulus Bighead Searobin 7, 50, 118, 125, 157, 174, 205, 233, 239, 246, 248, 256, 280, 289Rhizoprionodon terraenovae Atlantic Sharpnose Shark 18, 24, 26, 33, 43, 44, 84, 195, 205, 210, 211, 239, 252, 279Scomberomorus maculatus Spanish Mackerel 24, 40, 42, 72, 74, 112, 125, 143, 171, 174, 176, 195, 198, 199, 205, 224, 284, 322Selene vomer Lookdown 51, 59, 114, 125, 137, 157, 174, 197, 205, 251, 273Stellifer lanceolatus Star Drum 7, 50, 65, 75, 111, 197, 205, 225, 227, 239, 251, 261, 270, 282, 284, 286, 313Stephanolepis hispidus Planehead Filefish 4, 24, 41, 67, 117, 123, 205, 222, 241, 253, 278Symphurus plagiusa Blackcheek Tounguefish 10, 50, 65, 85, 110, 114, 157, 161, 174, 180, 197, 205, 207, 232, 261, 269, 270, 273, 281, 282, 284, 289,
300, 307, 309Synodus foetens Inshore Lizardfish 14, 24, 31, 51, 82, 92, 114, 125, 157, 174, 174, 185, 197, 205, 213, 228, 281, 282, 284, 289Trinectes maculatus Hogchoker 7, 31, 50, 54, 55, 61, 65, 73, 105, 114, 115, 180, 204, 205, 217, 232, 242, 270, 284, 313
4species considered for Menticirrhus sp.
*possible species within higher taxonomic categories considered, but were not reported as catch in 1999-20021species considered for Blennidae2species considered for Citharichthys sp.3species considered for Eucinostomus sp.
Appendix D.5. List of fish metric references. For full citations, refer to literature
cited section.
Reference Number Reference NumberAble and Kaiser 1994 1 Darovec 1983 56Able et al . 1995 2 Davis and Foltz 1991 57Able et al . 1990 3 Dawson 1958 58Adams 1976 4 Deegan et al . 1993 59Aguirre-Leon and Yanez Arancibia 1986 5 Delancey 1989 60Ahrenholz 1991 6 Derrick and Kennedy 1997 61Allen and Barker 1990 7 Dettmers and Stein 1992 62Allen et al . 1995 8 Dettmers and Stein 1996 63Allen 1985 9 Devries and Stein 1992 64Allen and Baltz 1997 10 Diener 1974 65Alshuth and Gilmore 1993 11 Diouf 1996 66Alvarez-Lanjonchere 1976 12 Dooley 1972 67Anderson 1958 13 Drenner et al . 1982a 68Anderson et al . 1966 14 Drenner et al . 1982b 69Arnold and Thompson 1958 15 Duarte Lopes and Tavares de Oliveira Silva 1999 70Baltz et al . 1998 16 Durbin and Durbin 1988 71Bearden 1963 17 Earll 1882 72Bigelow and Schroeder 1948 18 Ferraro 1980 73Bigelow and Schroeder 1953 19 Finucane et al . 1990 74Bodola 1966 20 Flores-Coto et al . 1998 75Bohlke and Chaplin 1968 21 Forward et al . 1999 76Bohlke and Chaplin 1993 22 Franks 1970 77Bonham 1941 23 Franks and Vanderkooy 2000 78Bowman et al . 2000 24 Friedland et al . 1989 79Bozeman and Dean 1980 25 Friedland et al . 1996 80Branstetter 1981 26 Funicelli 1975 81Buckel et al . 1999 27 Garcia-Abad et al . 1999 82Burke 1995 28 Geary et al . 2001. 83Burke et al . 1991 29 Gelsleichter et al . 1999 84Cain and Dean 1976 30 Ginsburg 1951 85Carr and Adams 1973 31 Gomez Gasper 1981 86Castillo-Rivera et al . 2000 32 Goshorn and Epifanio 1991 87Castro 1993 33 Grabe 1996 88Cervigon et al . 1992 34 Grecco and Blake 1983 89Chang et al . 2000 35 Grover 1998 90Chao and Musick 1977 36 Gudger 1916 91Chapman 1978 37 Guillen 2000 92Chavance et al . 1984 38 Gunter 1945 93Chaves and Serenato 1998 39 Gusey 1981 94Chittenden et al . 1993 40 Hammann 1981 95Clements and Livingston 1983 41 Hansen 1969 96Collette and Nauen 1983 42 Harding 1999 97Compagno 1984 43 Harding and Mann 2000 98Cortes 1999 44 Harmelin-Vivien and Quero 1990 99Cowan and Birdsong 1988 45 Harris and Rose 1968 100Cowan and Shaw 1988 46 Hartman and Brandt 1995 101Crabtree and Middaugh 1982 47 Haven 1959 102Crumpton 1970 48 Hayse 1987 103Cueller et al . 1996 49 Hensley 1995 104Dahlberg 1972 50 Hester and Copeland 1975 105Dahlberg 1980 51 Hildebrand 1963a 106Daniel and Graves 1994 52 Hildebrand 1963b 107Darcy 1985 53 Hildebrand 1963c 108Darnell 1958 54 Hildebrand 1963d 109Darnell 1961 55 Hildebrand and Cable 1930 110
Reference Number Reference NumberHildebrand and Cable 1934 111 Massmann et al . 1958 166Hildebrand and Cable 1938 112 Matheson and Gilmore 1995 167Hildebrand and Schroeder 1927 113 Matheson and McEachran 1984 168Hildebrand and Schroeder 1928 114 McBride et al . 2001 169Hines et al . 1990 115 McDowall 1988 170Hoese 1966 116 McEachran et al . 1980 171Hoese 1973 117 McEachran and Seret 1990 172Hoese and Moore 1977 118 McGovern 1986 173Holloway 1954 119 McHugh 1967 174Holt and Holt 2000 120 McMichael and Ross 1987 175Houde and Lovdal 1984 121 Menezes 1970 176Howe 2001 122 Merriner 1975 177Irlandi and Mehlich 1996 123 Merriner 1976 178Irwin 1970 124 Migdalski 1958 179Jackson 1990 125 Miller et al . 1991 180Jannke 1971 126 Miller and Able 2002 181Javonillo, R. in review 127 Miller et al . 2002 182Johnson and Noltie 1997 128 Miller 1960 183Johnson 1978 129 Miller 1963 184Johnson et al . 1990 130 Miltner et al . 1995 185Jones et al . 1978 131 Minello et al . 1989 186Jorgensen 1979 132 Modde 1980 187Joyeux 1998 133 Modde and Ross 1983 188Joyeux 1999 134 Moore 1974 189June and Carlson 1971 135 Morrow 1980 190Keefe and Able 1994 136 Motta et al . 1995 191Keith et al . 2000 137 Motta et al . 1993 192Kendall 1972 138 Murdy et al . 1997 193Kendall 1977 139 Music and Pafford 1984 194Kimura et al . 2000 140 Musick 1999 195Kjelson and Johnson 1976 141 Musick and Mercer 1977 196Kjelson et al . 1975 142 NOAA/NOS 2002 197Klima 1959 143 Naughton and Saloman 1981 198Kobelkowsky D. and Castillo Rivera 1995 144 Nelson et al . 1991a 199Kobylinski and Sheridan 1979 145 Nelson 1994 200Lankford and Targett 1994 146 Netsch and Witt 1962 201Larson and Shanks 1996 147 Ocana-Luna and Sanchez-Ramirez 1999 202Layman 2000 148 Odum 1970 203Lee et al . 1981 149 Odum and Heald 1972 204Lewis 1966 150 Ogburn et al . 1988 205Lewis and Mann 1971 151 Olla et al . 1972 206Limburg 1996a 152 Olney and Grant 1976 207Limburg 1996b 153 Owen et al . 1984 208Lindquist and Dillaman 1986 154 Pacheco 1962 209Link 1980 155 Parsons 1981 210Linton 1901 156 Parsons 1983 211Linton 1904 157 Pattillo et al . 1997 212Llanso et al . 1998 158 Pearcy and Richards 1962 213Luczkovich et al . 1999 159 Pearson 1928 214Manderson et al . 2000 160 Peebles and Tolley 1988 215Martin and Drewery 1978 161 Peters and Schaaf 1981 216Martore 1986 162 Peterson 1996 217Massmann 1952 163 Pew 1971 218Massmann 1954 164 Phillips 1977 219Massmann et al . 1954 165 Pierce and Mahmoudi 2001 220
Reference Number Reference NumberPotter et al . 1983 221 Snelson and Williams 1981 276Powell and Robbins 1998 222 Snelson et al . 1988 277Powell and Schwartz 1979 223 Soares et al . 1993 278Powell 1975 224 Springer 1967 279Powles 1980 225 Springer and Woodburn 1960 280Powles 1981 226 Stickney 1976 281Powles and Stender 1978 227 Stickney 1984 282Randall 1967 228 Stickney and McGeachin 1978 283Randall and Hartman 1968 229 Stickney and Shumway 1974 284Rasmussen and Heard 1995 230 Stickney et al . 1974 285Reichert 2002 231 Stickney et al . 1975 286Reichert and Van der Veer 1991 232 Stoner 1980 287Reid 1954 233 Stoner 1986 288Reid 1955 234 Subrahmanyan and Drake 1975 289Reid et al . 1956 235 Sutter and McIlwain 1987 290Rivas et al . 1999 236 Suttkus 1963 291Riviera-Arriaga et al . 1994 237 Szedlmayer and Able 1993 292Robinette 1983 238 Talbot and Sykes 1958 293Robins and Ray 1986 239 Teixeira and Almeida 1998 294Roelofs 1954 240 Teixeira and Helmer 1997 295Rogers et al . 2001 241 Teixeira et al . 1992 296Rogers et al . 1984 242 Thayer et al . 1999 297Rooker et al . 1998 243 Thomas 1971 298Ross et al . 1989 244 Thorrold et al . 1998 299Ross et al . 1997 245 Toepfer and Fleeger 1995 300Ross 1977 246 Tucker 1982 301Ross 1978 247 Tyler 1978 302Ross 1983 248 Vega-Cendejas et al . 1994 303Ross and Lancaster 2002 249 Vetter 1982 304Roumillat 2002a 250 Vieira and Musick 1994 305Roumillat 2002b 251 Walburg and Nichols 1967 306Roumillat 2003 252 Walsh et al . 1999 307Rountree 1990 253 Warlen and Burke 1990 308Rountree and Able 1992 254 Weinstein 1979 309Roux 1986 255 Weinstein et al . 1984 310Roux 1990 256 Weinstein et al . 1980 311Rozas and Hackney 1984 257 Welsh and Breder 1923 312Rozas and Minello 1998 258 Wenner et al . 1981 313Ruple 1984 259 Werner et al . 1999 314Ryder 1993 260 White 1970 315Sandifer et al . 1980 261 Whitehead 1985 316Sazima 1986 262 Whitehead et al . 1988 317Schaefer 1965 263 Wilk 1979 318Schaus et al . 2002 264 Wilkens and Lewis 1971 319Schwartz and Dahlberg 1978 265 Williams and Brager 1972 320Sedberry 1987 266 Witherall and Kynard 1990 321Sekavec 1974 267 Wollam 1970 322Setzler et al . 1981 268 Yako et al . 1996 323Setzler-Hamilton 1987 269 Yanez-Arancibia and Lara-Dominguez 1988 324Shealy et al . 1974 270 Zahorcsak et al . 2000 325Shenker and Dean 1979 271Sheridan et al . 1984 272Sierra et al . 1994 273Smith 1907 274Smith and Wenner 1985 275
Appendix E.1. Life history fish metrics calculated for 96 good and marginal
stations sampled in 1999-2002 (metrics in normal and bold font = used in one-
way analyses; metrics in bold font = used in discriminant analyses; italicized
metrics = not used in statistical analyses). *Average/median value at good
stations equal to or lower than average/median value at marginal stations. For
fish metric definitions, refer to Table 2.
Estuarine
DependentEstuarine
DependentEstuarine
DependentEstuarine Nursery
Estuarine Nursery*
Estuarine Nursery
Tidal Creek Nursery
Tidal Creek Nursery
Tidal Creek Nursery
Estuarine Resident
Estuarine Resident
Estuarine Resident
Station Quality (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)MR-101-T Marginal 36.23 83.33 2 43.47 100 2.5 14.49 33.33 1 28.98 66.67 1.5MR-303-T Good 173.9 78.46 3 224.61 100 6.5 202.88 78.08 5 57.96 39.61 2MR-304-T Good 152.17 80.83 1.5 166.66 100 2.5 166.66 100 2.5 72.46 53.33 1NT01598 Good 326.08 93.3 1.5 347.82 100 3 347.82 100 3 0 0 0RT00501 Good 202.89 100 2.5 202.89 100 2.5 202.89 100 2.5 181.15 88.46 1.5RT00502 Good 0 0 0 0 0 0 0 0 0 0 0 0RT00503 Good 427.52 96.43 4.5 449.25 100 6 398.54 90.36 4 217.39 56.67 2.5RT00504 Good 268.11 94.84 2 282.6 100 3 275.35 97.62 2.5 253.62 90.08 1.5RT00505 Good 101.44 100 3.5 101.44 100 3.5 86.95 91.67 2.5 72.46 83.34 1.5RT00517 Good 115.94 88.89 1.5 130.43 100 2.5 123.19 94.45 2 86.96 66.67 1RT00518 Marginal 688.38 93.89 6.5 768.08 100 8.5 731.85 92.08 6.5 478.25 62.36 3RT00519 Good 43.47 100 2 43.47 100 2 43.47 100 2 21.74 70 1.5RT00520 Good 85.65 92.31 1.5 98.59 100 2 98.59 100 2 79.19 88.47 1RT00521 Good 224.63 87.5 2.5 260.85 100 4.5 239.12 91.67 3 231.87 87.5 2.5RT00523 Marginal 297.08 87.58 6 347.79 100 8 340.55 98.49 7.5 152.17 44.55 2RT00525 Good 50.72 78.57 2 72.45 100 3 57.96 85.71 2.5 36.23 45.24 1.5RT00528 Good 384.04 100 3.5 384.04 100 3.5 376.8 96.15 3 0 0 0RT00531 Good 36.23 100 1.5 36.23 100 1.5 36.23 100 1.5 0 0 0RT00541 Good 65.21 94.44 2.5 72.46 100 3 57.97 88.89 2 36.23 27.78 0.5RT00542 Marginal 310.51 93.53 7 330.69 100 8 311.29 93.18 7 27.42 8.39 2RT00543 Good 449.26 99 4 456.51 100 4.5 413.03 88.31 3 275.36 38 1RT00544 Good 456.49 88.89 6.5 543.44 100 10 442 84.13 6 268.1 56.09 3.5RT00545 Good 7.25 25 0.5 21.74 100 1.5 21.74 100 1.5 0 0 0RT00546 Good 43.47 100 2 43.47 100 2 43.47 100 2 7.25 16.67 0.5RT00547 Good 376.78 78.41 8.5 543.44 100 11 420.26 83.25 9 137.67 21.4 2.5RT00550 Good 130.43 72.32 2.5 166.65 100 5 144.92 82.59 3.5 21.74 17.41 1.5RT00554 Good 152.17 100 2.5 152.17 100 2.5 36.23 26.39 1 36.23 26.39 1RT00557 Good 195.63 80.4 3.5 246.35 100 6 231.86 95.24 5.5 123.18 50.73 2RT00558 Good 333.32 100 3.5 333.32 100 3.5 333.32 100 3.5 275.36 81.34 2RT01602 Good 427.53 95.12 3.5 449.26 100 4.5 427.53 92.5 4 0 0 0RT01603 Good 7.25 16.67 0.5 21.74 50 1 14.49 33.33 0.5 14.49 33.33 0.5RT01604 Good 245.01 75 2 252.26 100 2.5 252.26 100 2.5 33.97 7.14 0.5
Life History Metrics
Estuarine
DependentEstuarine
DependentEstuarine
DependentEstuarine Nursery
Estuarine Nursery*
Estuarine Nursery
Tidal Creek Nursery
Tidal Creek Nursery
Tidal Creek Nursery
Estuarine Resident
Estuarine Resident
Estuarine Resident
Station Quality (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Life History Metrics
RT01606 Good 326.06 70.53 5.5 456.48 100 9 427.5 94.02 8 159.41 35.45 3RT01619 Good 181.15 87.12 2.5 202.88 100 4 188.39 89.39 3 14.49 16.67 1RT01624 Good 43.47 60 2 72.45 100 4 72.45 100 4 50.72 70 2.5RT01642 Good 43.47 90 3 50.72 100 3.5 50.72 100 3.5 21.74 30 1.5RT01643 Good 86.95 100 3.5 86.95 100 3.5 50.72 62.5 2.5 28.98 31.25 1RT01645 Good 50.72 100 2 50.72 100 2 50.72 100 2 7.25 12.5 0.5RT01646 Good 72.46 91.67 2.5 79.7 100 3 72.46 90 2.5 7.25 10 0.5RT01647 Marginal 1181.14 89.63 4 1326.05 100 9 1318.81 99.61 8.5 123.18 11.18 3RT01648 Good 449.26 96.61 3.5 463.75 100 4.5 449.26 96.61 3.5 362.31 78.16 1RT01649 Good 224.63 98.39 2.5 231.87 100 3 224.63 98.39 2.5 101.45 22.58 1RT01650 Good 72.46 81.25 1 86.95 100 2 86.95 100 2 0 0 0RT01652 Good 608.67 80.32 3.5 768.08 100 6 768.08 100 6 246.37 32.18 2.5RT01653 Good 28.98 33.33 1 50.72 100 2.5 50.72 100 2.5 36.23 83.33 1.5RT01655 Good 579.71 96.3 2 594.2 100 3 579.71 96.3 2.5 28.98 7.41 1.5RT01664 Good 282.59 81.66 4 318.82 100 6.5 289.84 88.8 4.5 21.74 9.85 1.5RT01668 Good 536.22 77.5 3 688.39 100 4.5 681.14 99.09 4 152.17 22.84 1.5RT02002 Good 105.07 71.43 2.5 126.52 100 4 126.52 100 4 90.86 55.36 1.5RT02006 Good 65.21 92.86 3 72.45 100 3.5 57.96 76.19 2.5 50.72 69.05 2RT02007 Good 43.47 100 1.5 43.47 100 1.5 43.47 100 1.5 28.98 75 1RT02008 Good 268.1 80.44 3.5 333.31 100 7 326.06 97.83 6.5 144.92 43.48 3RT02009 Good 166.66 90.08 4.5 181.15 100 5.5 166.66 90.08 4.5 101.44 47.62 3RT02013 Good 0 0 0 14.49 50 0.5 14.49 50 0.5 14.49 50 0.5RT02015 Good 405.78 98.49 4.5 413.02 100 5 318.83 76.89 3.5 21.74 5.68 1.5RT02016 Good 268.1 84.16 4 318.82 100 6.5 311.57 97.62 6 50.72 16.46 1.5RT02019 Good 123.18 72.22 3 173.9 100 5.5 159.41 93.33 4.5 0 0 0RT02021 Good 695.63 94.54 6.5 731.85 100 8.5 652.15 87.32 6.5 130.43 15.47 1.5RT02027 Good 152.17 76.99 3.5 195.64 100 5.5 188.39 95.45 5 86.96 38.92 1RT02030 Good 14.49 50 0.5 14.49 50 0.5 14.49 50 0.5 0 0 0RT02152 Good 115.93 100 2 115.93 100 2 36.23 35 1 36.23 35 1RT02153 Good 217.38 90 4.5 224.62 100 5 210.13 96.15 4 159.42 50.39 1.5RT02154 Good 94.2 73.22 3 130.42 100 5 115.93 83.93 4 36.23 26.78 2
Estuarine
DependentEstuarine
DependentEstuarine
DependentEstuarine Nursery
Estuarine Nursery*
Estuarine Nursery
Tidal Creek Nursery
Tidal Creek Nursery
Tidal Creek Nursery
Estuarine Resident
Estuarine Resident
Estuarine Resident
Station Quality (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Life History Metrics
RT02155 Good 79.7 47.22 3 166.65 100 6.5 137.67 81.75 4.5 21.74 14.68 1RT02156 Good 86.95 84.62 3 115.93 100 4 94.19 88.46 3 57.97 56.41 1.5RT02157 Good 50.72 67.86 1.5 65.21 100 2.5 28.98 64.28 2 7.25 7.14 0.5RT02160 Good 202.89 70.32 3 282.59 100 5.5 210.13 72.59 3.5 0 0 0RT02162 Good 86.95 70 2.5 108.68 100 3 108.68 100 3 65.21 60 1.5RT02164 Good 717.37 69.08 5.5 1065.18 100 9 1050.69 98.51 8 797.09 70.52 3.5RT02165 Good 217.38 95 5.5 224.62 100 6 202.89 90.24 4.5 144.92 58.1 2.5RT02167 Good 224.62 96.88 4 231.86 100 4.5 202.88 87.5 3.5 0 0 0RT02171 Good 57.97 55 2 101.44 100 3.5 101.44 100 3.5 57.97 55 1.5RT99001 Good 57.97 48.48 2 101.44 100 3 94.2 95.46 2.5 50.72 56.06 1.5RT99003 Good 514.47 88.33 6 586.93 100 7.5 514.47 88.06 5.5 101.44 16.67 3.5RT99004 Good 195.64 77.27 4.5 239.11 100 7 202.89 81.82 4.5 28.99 9.09 0.5RT99005 Marginal 340.57 87.64 3 391.29 100 4 391.29 100 4 275.36 68.61 1RT99006 Good 202.89 95.83 3.5 210.13 100 4 210.13 100 4 159.42 76.96 1RT99008 Good 811.57 100 6 811.57 100 6 789.83 97.35 4.5 644.92 79.47 2RT99009 Marginal 565.2 97.46 5 579.69 100 6 478.25 82.22 4 115.94 21.59 1.5RT99010 Good 79.71 50 1.5 79.71 50 1.5 79.71 50 1.5 50.72 31.82 1RT99012 Good 21.74 18.75 1 72.46 100 3 57.97 68.75 2 57.97 68.75 2RT99013 Good 463.75 83.15 4 550.7 100 5 478.24 87.89 4 246.37 42.29 2RT99017 Marginal 181.14 78.02 4 231.86 100 7 224.61 97.83 6.5 101.44 40.58 2.5RT99019 Good 159.42 100 2.5 159.42 100 2.5 159.42 100 2.5 94.2 57.14 1RT99022 Good 123.18 71.18 3 159.4 100 5 130.42 81.18 3.5 86.95 49.41 1.5RT99024 Good 543.47 98.49 2 550.72 100 2.5 550.72 100 2.5 550.72 100 2.5RT99026 Good 666.65 99.07 5 673.89 100 5.5 550.71 81.41 4.5 36.23 6.05 1.5RT99027 Good 362.31 97.22 3.5 369.55 100 4 369.55 100 4 217.39 60.61 1.5RT99028 Good 152.17 63.75 1.5 202.88 100 3.5 202.88 100 3.5 144.92 61.25 1RT99029 Good 57.96 100 2 57.96 100 2 57.96 100 2 28.98 46.67 1RT99030 Marginal 768.1 94.31 3 811.57 100 5 811.57 100 5 739.12 90.84 2.5RT99036 Good 297.09 100 3.5 297.09 100 3.5 268.11 92.31 2.5 246.37 83.72 1.5RT99037 Good 7.25 50 0.5 7.25 50 0.5 7.25 50 0.5 0 0 0RT99038 Good 318.83 80.37 4 398.53 100 6.5 369.55 92.53 5 253.62 65.7 1.5RT99039 Good 28.98 41.67 1.5 72.45 100 3.5 72.45 100 3.5 43.47 62.5 2RT99040 Good 94.19 85 3 108.68 100 4 94.19 80 3 57.97 55 1.5Average Good 214.81 79.77 2.91 246.77 95.98 4.07 226.20 87.07 3.34 103.29 40.09 1.34Average Marginal 485.37 89.49 4.50 536.72 100.00 6.44 513.63 88.53 5.56 226.87 46.09 2.11Average All 240.18 80.68 3.06 273.95 96.35 4.29 253.15 87.21 3.55 114.88 40.65 1.41Median Good 152.17 87.12 3.00 181.15 100* 3.50 166.66 93.33 3.00 50.72 39.61 1.50Median Marginal 340.57 89.63 4.00 391.29 100.00 7.00 391.29 97.83 6.50 123.18 44.55 2.00Median All 177.52 87.61 3.00 202.89 100.00 4.00 202.88 93.68 3.50 57.97 41.44 1.50
*Average/median value at good stations equal to or lower than average/median value at marginal stations
Station Quality
MR-101-T MarginalMR-303-T GoodMR-304-T GoodNT01598 GoodRT00501 GoodRT00502 GoodRT00503 GoodRT00504 GoodRT00505 GoodRT00517 GoodRT00518 MarginalRT00519 GoodRT00520 GoodRT00521 GoodRT00523 MarginalRT00525 GoodRT00528 GoodRT00531 GoodRT00541 GoodRT00542 MarginalRT00543 GoodRT00544 GoodRT00545 GoodRT00546 GoodRT00547 GoodRT00550 GoodRT00554 GoodRT00557 GoodRT00558 GoodRT01602 GoodRT01603 GoodRT01604 Good
Tidal Creek Resident
Tidal Creek Resident
Tidal Creek Resident
Estuarine Spawner
Estuarine Spawner*
Estuarine Spawner
Tidal Creek Spawner
Tidal Creek Spawner
Tidal Creek Spawner
(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)0 0 0 36.23 83.33 2 21.74 50 1
57.96 39.61 2 79.7 53.46 3.5 50.72 37.69 1.572.46 53.33 1 79.71 55.83 1.5 57.97 20 0.5
0 0 0 0 0 0 0 0 0181.15 88.46 1.5 181.15 88.46 1.5 14.49 6.67 0.5
0 0 0 0 0 0 0 0 0202.9 54.29 1.5 246.37 62.74 3.5 202.9 54.29 1.5
253.62 90.08 1.5 253.62 90.08 1.5 0 0 072.46 83.34 1.5 79.71 87.5 2 28.99 16.67 0.586.96 66.67 1 86.96 66.67 1 0 0 0
434.77 59.03 2.5 514.47 70.28 5 282.6 42.22 221.74 70 1.5 21.74 70 1.5 14.49 60 179.19 88.47 1 79.19 88.47 1 79.19 88.47 1
217.38 83.34 2 231.87 87.5 2.5 101.45 31.25 1152.17 44.55 2 173.9 52.73 3.5 115.94 33.34 128.98 38.1 1 36.23 45.24 1.5 28.98 38.1 1
0 0 0 7.25 3.85 0.5 0 0 00 0 0 0 0 0 0 0 0
36.23 27.78 0.5 43.48 33.33 1 0 0 027.42 8.39 2 27.42 8.39 2 13.71 4.19 1
268.12 37 0.5 318.84 49.69 2.5 0 0 0260.86 55.16 3 282.59 59.39 4.5 202.89 37.57 2
0 0 0 0 0 0 0 0 07.25 16.67 0.5 14.49 33.33 1 7.25 16.67 0.594.2 16.56 2 195.63 33.93 5.5 50.72 11.72 1
0 0 0 36.23 27.68 2.5 14.49 10.27 136.23 26.39 1 152.17 100 2.5 0 0 0
123.18 50.73 2 123.18 50.73 2 72.46 28.2 1275.36 81.34 2 282.6 84.28 2.5 239.13 70.29 1
0 0 0 43.47 12.38 1.5 0 0 00 0 0 21.74 50 1 0 0 0
33.97 7.14 0.5 33.97 7.14 0.5 33.97 7.14 0.5
Life History Metrics
Station Quality
RT01606 GoodRT01619 GoodRT01624 GoodRT01642 GoodRT01643 GoodRT01645 GoodRT01646 GoodRT01647 MarginalRT01648 GoodRT01649 GoodRT01650 GoodRT01652 GoodRT01653 GoodRT01655 GoodRT01664 GoodRT01668 GoodRT02002 GoodRT02006 GoodRT02007 GoodRT02008 GoodRT02009 GoodRT02013 GoodRT02015 GoodRT02016 GoodRT02019 GoodRT02021 GoodRT02027 GoodRT02030 GoodRT02152 GoodRT02153 GoodRT02154 Good
Tidal Creek Resident
Tidal Creek Resident
Tidal Creek Resident
Estuarine Spawner
Estuarine Spawner*
Estuarine Spawner
Tidal Creek Spawner
Tidal Creek Spawner
Tidal Creek Spawner
(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Life History Metrics
108.69 24.84 2 239.11 53.74 5.5 7.25 1.92 0.50 0 0 21.74 18.94 1.5 7.25 8.33 0.5
43.47 60 2 57.96 80 3 7.25 10 0.514.49 20 1 21.74 30 1.5 7.25 10 0.528.98 31.25 1 65.21 68.75 2 28.98 31.25 17.25 12.5 0.5 7.25 12.5 0.5 0 0 07.25 10 0.5 7.25 10 0.5 0 0 0
101.44 9.01 2 159.4 14.15 4.5 86.95 7.72 1362.31 78.16 1 362.31 78.16 1 362.31 78.16 1101.45 22.58 1 108.69 72.58 1.5 94.2 20.97 0.5
0 0 0 0 0 0 0 0 0115.94 16.49 1.5 260.86 34.27 3 108.69 15.45 121.74 25 0.5 43.47 91.67 2 21.74 25 0.57.25 1.85 0.5 28.98 7.41 1.5 14.49 3.7 0.57.25 1.35 0.5 21.74 9.85 1.5 0 0 07.25 1.25 0.5 152.17 22.84 1.5 7.25 1.25 0.5
90.86 55.36 1.5 90.86 55.36 1.5 69.68 35.72 0.543.47 52.38 1.5 57.96 76.19 2.5 21.74 30.95 128.98 75 1 28.98 75 1 0 0 0
130.43 39.13 2.5 166.65 50 4.5 79.71 23.91 186.95 42.06 2 115.93 57.54 4 86.95 42.06 214.49 50 0.5 14.49 50 0.5 0 0 014.49 3.6 1 115.93 28.22 3 14.49 4.17 128.99 9.52 0.5 86.95 27.74 3.5 0 0 0
0 0 0 28.98 15.55 1 0 0 0130.43 15.47 1.5 217.38 29.42 3.5 123.19 14.66 186.96 38.92 1 130.43 61.93 3 0 0 0
0 0 0 0 0 0 0 0 036.23 35 1 115.93 100 2 36.23 35 1
159.42 50.39 1.5 166.66 52.31 2 7.25 1.92 0.521.74 10.71 1 43.47 39.28 2.5 14.49 16.07 1
Station Quality
RT02155 GoodRT02156 GoodRT02157 GoodRT02160 GoodRT02162 GoodRT02164 GoodRT02165 GoodRT02167 GoodRT02171 GoodRT99001 GoodRT99003 GoodRT99004 GoodRT99005 MarginalRT99006 GoodRT99008 GoodRT99009 MarginalRT99010 GoodRT99012 GoodRT99013 GoodRT99017 MarginalRT99019 GoodRT99022 GoodRT99024 GoodRT99026 GoodRT99027 GoodRT99028 GoodRT99029 GoodRT99030 MarginalRT99036 GoodRT99037 GoodRT99038 GoodRT99039 GoodRT99040 GoodAverage GoodAverage MarginalAverage AllMedian GoodMedian MarginalMedian All
Tidal Creek Resident
Tidal Creek Resident
Tidal Creek Resident
Estuarine Spawner
Estuarine Spawner*
Estuarine Spawner
Tidal Creek Spawner
Tidal Creek Spawner
Tidal Creek Spawner
(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Life History Metrics
14.49 11.11 0.5 50.72 28.97 2.5 0 0 057.97 56.41 1.5 72.46 64.1 2 50.72 52.57 17.25 7.14 0.5 50.72 67.86 1.5 0 0 0
0 0 0 14.49 5.21 1 7.25 2.94 0.565.21 60 1.5 65.21 60 1.5 36.23 40 1
586.95 52.64 2 913.02 81.98 5.5 521.73 45.29 1.5144.92 58.1 2.5 166.66 67.86 4 79.71 34.05 1.5
0 0 0 28.98 12.5 1 0 0 043.48 30 1 79.7 70 2 36.23 25 0.57.25 4.54 0.5 50.72 56.06 1.5 7.25 4.54 0.5
36.23 6.11 2.5 144.91 23.89 4.5 14.49 2.5 128.99 9.09 0.5 115.93 45.45 3.5 28.99 9.09 0.5
275.36 68.61 1 326.08 83.81 2 275.36 68.61 1159.42 76.96 1 166.66 79.9 1.5 0 0 0644.92 79.47 2 666.66 82.06 3 550.72 67.95 1115.94 21.59 1.5 210.14 38.25 3 7.25 1.43 0.550.72 31.82 1 50.72 31.82 1 36.23 22.73 0.521.74 18.75 1 57.97 68.75 2 14.49 12.5 0.5
159.42 25.45 1 318.83 54.41 3 159.42 25.45 1101.44 40.58 2.5 101.44 40.58 2.5 43.48 19.81 1
94.2 57.14 1 94.2 57.14 1 28.99 25 0.586.95 49.41 1.5 86.95 49.41 1.5 28.98 25.88 1
550.72 100 2.5 550.72 100 2.5 253.62 46.34 136.23 6.05 1.5 166.66 25.57 3 14.49 2.21 1
217.39 60.61 1.5 217.39 60.61 1.5 115.94 24.24 0.5144.92 61.25 1 152.17 63.75 1.5 0 0 028.98 46.67 1 28.98 46.67 1 28.98 46.67 1
739.12 90.84 2.5 753.61 92.08 3 420.29 45.76 1246.37 83.72 1.5 275.35 91.41 2.5 231.88 79.87 1
0 0 0 0 0 0 0 0 0253.62 65.7 1.5 297.09 75.68 3 57.97 12.5 0.514.49 25 1 50.72 70.83 2.5 7.25 12.5 0.550.72 45 1 86.95 80 3 65.21 60 290.47 34.32 1.04 123.36 49.11 1.99 53.99 18.68 0.59
216.41 38.07 1.78 255.85 53.73 3.06 140.81 30.34 1.06102.27 34.67 1.11 135.78 49.55 2.09 62.13 19.77 0.6436.23 30.00 1.00 79.70 53.46* 1.50 14.49 10.27 0.50
115.94 40.58 2.00 173.90 52.73 3.00 86.95 33.34 1.0043.48 30.63 1.00 83.33 53.10 2.00 14.49 12.11 0.50
*Average/median value at good stations equal to or lower than average/median value at marginal stations
Appendix E.2. Ecological and trophic composition fish metrics calculated for 96
good and marginal stations sampled in 1999-2002 (metrics in normal and bold
font = used in one-way analyses; metrics in bold font = used in discriminant
analyses; italicized metrics = not used in statistical analyses). *Average/median
value at good stations equal to or lower than average/median value at marginal
stations. For fish metric definitions, refer to Table 2.
Station Quality
MR-101-T MarginalMR-303-T GoodMR-304-T GoodNT01598 GoodRT00501 GoodRT00502 GoodRT00503 GoodRT00504 GoodRT00505 GoodRT00517 GoodRT00518 MarginalRT00519 GoodRT00520 GoodRT00521 GoodRT00523 MarginalRT00525 GoodRT00528 GoodRT00531 GoodRT00541 GoodRT00542 MarginalRT00543 GoodRT00544 GoodRT00545 GoodRT00546 GoodRT00547 GoodRT00550 GoodRT00554 GoodRT00557 GoodRT00558 GoodRT01602 GoodRT01603 GoodRT01604 Good
Pelagic Pelagic Pelagic Benthic Benthic* BenthicBenthic Feeder
Benthic Feeder*
Benthic Feeder Carnivore Carnivore Carnivore
Top Predator
Top Predator
Top Predator
(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)0.00 0.00 0.00 43.47 100 2.5 43.47 100 2.5 43.47 100 2.5 28.98 66.67 1.5
21.74 5.77 1.50 202.88 94.23 5 210.12 96.15 5.5 217.37 98.08 6 79.7 53.46 3.514.49 33.33 0.50 152.17 66.67 2 144.93 50 1.5 166.66 100 2.5 65.22 36.67 114.49 5.27 1.00 333.33 94.73 2 340.57 98.57 2.5 28.98 8.13 2 21.74 6.7 1.5
166.66 81.80 1.00 36.23 18.2 1.5 36.23 18.2 1.5 202.89 100 2.5 14.49 6.67 0.50.00 0.00 0.00 0 0 0 0 0 0 0 0 0 0 0 00.00 0.00 0.00 449.25 100 6 449.25 100 6 442.01 98.81 5.5 231.88 60.36 2.5
246.37 87.30 1.00 36.23 12.7 2 36.23 12.7 2 282.6 100 3 14.49 5.16 143.48 66.67 1.00 57.97 33.33 2.5 57.97 33.33 2.5 94.2 95.83 3 36.23 20.83 194.20 72.22 1.50 36.23 27.78 1 43.48 33.33 1.5 130.43 100 2.5 0 0 0
188.40 22.15 2.00 579.68 77.85 6.5 608.66 80.07 7.5 768.08 100 8.5 304.34 43.89 37.25 10.00 0.50 36.23 90 1.5 36.23 90 1.5 43.47 100 2 14.49 60 1
12.94 7.69 0.50 85.65 92.31 1.5 98.59 100 2 92.12 96.16 1.5 79.19 88.47 1137.67 60.42 2.50 123.18 39.58 2 123.18 39.58 2 253.61 95.83 4 101.45 31.25 150.72 19.70 1.50 297.08 80.3 6.5 333.3 93.33 7.5 311.57 90.61 6.5 166.66 49.4 2.50.00 0.00 0.00 72.45 100 3 72.45 100 3 57.96 66.67 2.5 28.98 38.1 1
130.43 32.89 1.00 253.61 67.11 2.5 253.61 67.11 2.5 246.37 63.27 2 7.25 3.85 0.50.00 0.00 0.00 36.23 100 1.5 36.23 100 1.5 36.23 100 1.5 0 0 0
36.23 27.78 0.50 36.23 72.22 2.5 36.23 72.22 2.5 72.46 100 3 7.25 5.56 0.569.34 20.63 3.00 261.35 79.37 5 309.74 93.88 6.5 216.32 68.53 6 41.14 12.59 2.5
268.12 37.00 0.50 188.39 63 4 188.39 63 4 456.51 100 4.5 65.21 14.69 286.95 21.30 1.50 456.49 78.7 8.5 478.23 81.48 8.5 413.01 78.97 8 217.38 39.42 30.00 0.00 0.00 21.74 100 1.5 7.25 25 0.5 14.49 75 1 14.49 75 10.00 0.00 0.00 43.47 100 2 43.47 100 2 36.23 83.33 1.5 7.25 16.67 0.5
43.48 4.84 1.00 499.96 95.16 10 499.96 95.16 10 528.95 98.39 10 108.68 24.25 47.25 3.12 0.50 159.41 96.88 4.5 159.41 96.88 4.5 57.96 41.07 4 28.98 16.52 2
36.23 26.39 1.00 115.94 73.61 1.5 115.94 73.61 1.5 152.17 100 2.5 72.46 48.61 179.70 34.98 2.50 166.65 65.02 3.5 188.38 75.09 4.5 246.35 100 6 101.44 39.19 2.536.23 11.05 1.00 297.1 88.95 2.5 297.1 88.95 2.5 304.34 93.1 3 246.38 73.23 1.57.25 1.19 0.50 442.02 98.81 4 442.02 98.81 4 253.61 67.86 3.5 21.74 7.5 0.50.00 0.00 0.00 21.74 50 1 21.74 50 1 21.74 50 1 7.25 16.67 0.57.25 25.00 0.50 245.01 75 2 252.26 100 2.5 97.82 44.05 1.5 41.21 32.14 1
Ecological and Trophic Metrics
Station Quality
RT01606 GoodRT01619 GoodRT01624 GoodRT01642 GoodRT01643 GoodRT01645 GoodRT01646 GoodRT01647 MarginalRT01648 GoodRT01649 GoodRT01650 GoodRT01652 GoodRT01653 GoodRT01655 GoodRT01664 GoodRT01668 GoodRT02002 GoodRT02006 GoodRT02007 GoodRT02008 GoodRT02009 GoodRT02013 GoodRT02015 GoodRT02016 GoodRT02019 GoodRT02021 GoodRT02027 GoodRT02030 GoodRT02152 GoodRT02153 GoodRT02154 Good
Pelagic Pelagic Pelagic Benthic Benthic* BenthicBenthic Feeder
Benthic Feeder*
Benthic Feeder Carnivore Carnivore Carnivore
Top Predator
Top Predator
Top Predator
(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Ecological and Trophic Metrics
123.18 26.97 2.00 333.31 73.03 7 355.04 77.08 7.5 413.01 89.6 8 50.72 11.17 2.50.00 0.00 0.00 202.88 100 4 202.88 100 4 57.96 36.36 3 7.25 8.33 0.5
43.47 60.00 2.00 28.98 40 2 36.23 50 2.5 65.21 90 3.5 21.74 30 1.57.25 10.00 0.50 43.47 90 3 43.47 90 3 36.23 65 2.5 7.25 10 0.50.00 0.00 0.00 86.95 100 3.5 86.95 100 3.5 86.95 100 3.5 72.46 81.25 2.57.25 12.50 0.50 43.47 87.5 1.5 43.47 87.5 1.5 14.49 29.17 1 0 0 0
14.49 18.33 1.00 65.21 81.67 2 72.46 90 2.5 72.46 91.67 2.5 7.25 8.33 0.565.21 5.04 2.50 1260.84 94.96 6.5 1282.58 97.14 7.5 644.9 55 8 137.67 11.47 37.25 1.22 0.50 456.5 98.78 4 463.75 100 4.5 463.75 100 4.5 369.56 80.33 1.5
14.49 3.23 1.00 217.38 96.77 2 224.63 98.39 2.5 137.67 79.03 2.5 101.45 70.97 114.49 18.75 1.00 72.46 81.25 1 86.95 100 2 14.49 18.75 1 14.49 18.75 10.00 0.00 0.00 768.08 100 6 760.84 99.14 5.5 673.88 86.46 5.5 123.18 17.35 20.00 0.00 0.00 50.72 100 2.5 50.72 100 2.5 50.72 100 2.5 21.74 25 0.50.00 0.00 0.00 594.2 100 3 594.2 100 3 36.23 9.26 2 21.74 5.55 1
28.98 11.20 2.00 289.84 88.8 4.5 297.08 90.15 5 297.08 84.36 5.5 7.25 1.35 0.50.00 0.00 0.00 688.39 100 4.5 688.39 100 4.5 688.39 100 4.5 28.98 4.66 2
42.64 48.21 2.50 83.89 51.79 1.5 105.34 80.36 3 126.52 100 4 90.85 55.36 228.98 38.10 1.00 43.47 61.9 2.5 43.47 61.9 2.5 72.45 100 3.5 21.74 30.95 128.98 75.00 1.00 14.49 25 0.5 14.49 25 0.5 43.47 100 1.5 0 0 072.46 21.74 2.50 260.85 78.26 4.5 282.59 84.78 5.5 195.63 58.69 6 115.93 34.78 321.74 17.06 1.50 159.41 82.94 4 166.66 90.08 4.5 173.9 97.22 5 86.95 37.7 20.00 0.00 0.00 14.49 50 0.5 14.49 50 0.5 14.49 50 0.5 14.49 50 0.50.00 0.00 0.00 413.02 100 5 413.02 100 5 405.78 98.49 4.5 108.69 26.7 2.5
43.48 13.87 1.50 275.34 86.13 5 282.59 88.3 5.5 144.91 46.38 4.5 7.25 2.38 0.528.98 17.78 2.00 144.92 82.22 3.5 159.41 93.33 4.5 115.93 68.89 4 21.74 14.44 1.521.74 2.89 1.50 710.12 97.11 7 724.61 99.19 8 702.87 96.3 7 202.89 26.86 386.96 38.92 1.00 108.68 61.08 4.5 108.68 61.08 4.5 181.15 92.33 4.5 28.98 18.18 20.00 0.00 0.00 14.49 50 0.5 14.49 50 0.5 0 0 0 0 0 00.00 0.00 0.00 115.93 100 2 115.93 100 2 115.93 100 2 36.23 35 1
159.42 58.46 1.50 65.21 41.54 3.5 72.45 51.54 4 224.62 100 5 36.23 25.77 27.25 3.57 0.50 123.18 96.43 4.5 130.42 100 5 65.21 58.93 4 21.74 10.71 1
Station Quality
RT02155 GoodRT02156 GoodRT02157 GoodRT02160 GoodRT02162 GoodRT02164 GoodRT02165 GoodRT02167 GoodRT02171 GoodRT99001 GoodRT99003 GoodRT99004 GoodRT99005 MarginalRT99006 GoodRT99008 GoodRT99009 MarginalRT99010 GoodRT99012 GoodRT99013 GoodRT99017 MarginalRT99019 GoodRT99022 GoodRT99024 GoodRT99026 GoodRT99027 GoodRT99028 GoodRT99029 GoodRT99030 MarginalRT99036 GoodRT99037 GoodRT99038 GoodRT99039 GoodRT99040 GoodAverage GoodAverage MarginalAverage AllMedian GoodMedian MarginalMedian All
Pelagic Pelagic Pelagic Benthic Benthic* BenthicBenthic Feeder
Benthic Feeder*
Benthic Feeder Carnivore Carnivore Carnivore
Top Predator
Top Predator
Top Predator
(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Ecological and Trophic Metrics
65.21 42.06 2.00 101.44 57.94 4.5 144.91 83.33 5.5 123.17 74.6 5.5 28.98 20.24 1.521.74 11.54 0.50 94.19 88.46 3.5 115.93 100 4 108.68 96.15 3.5 72.46 64.1 20.00 0.00 0.00 65.21 100 2.5 65.21 100 2.5 65.21 100 2.5 43.48 42.86 17.25 2.94 0.50 275.34 97.06 5 282.59 100 5.5 173.9 64.57 4.5 21.74 8.82 1.5
50.72 50.00 1.00 57.96 50 2 79.7 80 2.5 72.46 65 2 36.23 40 1123.18 14.17 2.00 942 85.83 7 1014.46 93.27 8 1050.69 98.08 8 623.18 54.84 372.46 29.05 1.50 152.16 70.95 4.5 159.41 75.95 5 224.62 100 6 101.44 43.81 37.25 3.12 0.50 224.62 96.88 4 231.86 100 4.5 224.62 96.88 4 28.98 12.5 10.00 0.00 0.00 101.44 100 3.5 101.44 100 3.5 86.95 82.5 2.5 50.72 42.5 1.50.00 0.00 0.00 101.44 100 3 101.44 100 3 101.44 100 3 7.25 4.54 0.5
14.49 2.50 1.00 572.44 97.5 6.5 572.44 97.5 6.5 586.93 100 7.5 65.21 10.83 2.550.72 18.18 1.00 188.39 81.82 6 195.64 86.36 6.5 210.13 90.91 6.5 50.72 20.45 2
101.44 27.56 2.00 289.85 72.44 2 340.57 84.8 3 391.29 100 4 326.08 80.97 2173.91 84.07 2.00 36.23 15.93 2 43.47 20.1 2.5 195.64 94.12 3.5 7.25 4.17 0.5108.69 13.25 1.50 702.88 86.75 4.5 702.88 86.75 4.5 782.59 96.36 5 557.97 68.81 1.5115.94 21.59 1.50 463.75 78.41 4.5 463.75 78.41 4.5 579.69 100 6 108.69 19.21 2.514.49 9.09 0.50 65.22 40.91 1 65.22 40.91 1 79.71 50 1.5 36.23 22.73 0.57.25 6.25 0.50 65.21 93.75 2.5 65.21 93.75 2.5 72.46 100 3 28.98 43.75 1.50.00 0.00 0.00 550.7 100 5 550.7 100 5 550.7 100 5 231.88 37.56 2
86.95 36.23 3.00 144.91 63.77 4 173.89 79.23 5.5 166.65 77.05 5.5 72.46 35.27 2.565.22 32.14 0.50 94.2 67.86 2 94.2 67.86 2 152.17 96.43 2 28.99 25 0.572.46 36.47 1.50 86.94 63.53 3.5 101.43 76.47 4.5 159.4 100 5 43.47 31.76 2
289.85 52.15 1.00 260.87 47.85 1.5 260.87 47.85 1.5 550.72 100 2.5 260.87 47.85 1.521.74 3.85 0.50 652.16 96.15 5 652.16 96.15 5 615.93 90.81 4.5 137.68 20.8 2
108.69 39.14 1.50 260.86 60.86 2.5 268.11 63.64 3 304.34 85.1 3 123.19 27.02 1202.88 100.00 3.50 0 0 0 50.72 36.25 2 202.88 100 3.5 21.74 15 1
0.00 0.00 0.00 57.96 100 2 57.96 100 2 57.96 100 2 28.98 46.67 1333.33 46.32 2.00 478.25 53.68 3 492.74 54.92 3.5 811.57 100 5 434.78 48.98 214.49 3.85 0.50 282.6 96.15 3 282.6 96.15 3 282.6 93.33 3 246.37 83.72 1.50.00 0.00 0.00 7.25 50 0.5 7.25 50 0.5 0 0 0 0 0 0
311.58 81.25 4.50 86.95 18.75 2 144.92 32.47 3.5 391.28 98.44 6 101.44 23.1 20.00 0.00 0.00 72.45 100 3.5 72.45 100 3.5 72.45 100 3.5 14.49 25 1
28.98 25.00 1.50 79.7 75 2.5 86.95 85 3 108.68 100 4 72.46 70 2.547.53 20.85 0.90 199.24 75.13 3.17 205.72 78.01 3.44 209.77 81.32 3.57 73.06 28.98 1.35
112.37 22.14 1.94 424.35 77.86 4.50 449.86 84.64 5.33 437.06 87.91 5.78 180.09 40.94 2.3953.61 20.97 0.99 220.34 75.38 3.30 228.60 78.63 3.61 231.08 81.94 3.78 83.09 30.10 1.4514.49 11.05 0.50 108.68 85.83* 2.50 115.94 90.00* 3.00 137.67 96.15 3.50 28.99 25.00 1.0086.95 21.59 2.00 297.08 78.41 4.50 340.57 84.80 5.50 391.29 100.00 6.00 137.67 43.89 2.5021.74 12.02 1.00 123.18 82.02 3.00 144.92 89.48 3.00 155.79 96.16 3.50 36.23 25.00 1.50
*Average/median value at good stations equal to or lower than average/median value at marginal stations
Station Quality
MR-101-T MarginalMR-303-T GoodMR-304-T GoodNT01598 GoodRT00501 GoodRT00502 GoodRT00503 GoodRT00504 GoodRT00505 GoodRT00517 GoodRT00518 MarginalRT00519 GoodRT00520 GoodRT00521 GoodRT00523 MarginalRT00525 GoodRT00528 GoodRT00531 GoodRT00541 GoodRT00542 MarginalRT00543 GoodRT00544 GoodRT00545 GoodRT00546 GoodRT00547 GoodRT00550 GoodRT00554 GoodRT00557 GoodRT00558 GoodRT01602 GoodRT01603 GoodRT01604 Good
Detritivore Detritivore* Detritivore Herbivore* Herbivore* Herbivore* Omnivore* Omnivore* Omnivore*(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
14.49 33.33 1 0 0 0 0.00 0.00 0.00159.41 74.62 3 0 0 0 7.25 1.92 0.50159.42 83.33 2 0 0 0 0.00 0.00 0.00318.84 91.87 1 0 0 0 318.84 91.87 1.00202.89 100 2.5 0 0 0 0.00 0.00 0.00
0 0 0 0 0 0 0.00 0.00 0.00384.05 87.98 3 0 0 0 7.25 1.19 0.50275.35 97.22 2.5 0 0 0 0.00 0.00 0.0086.95 91.67 2.5 0 0 0 7.25 4.17 0.50
130.43 100 2.5 0 0 0 0.00 0.00 0.00739.1 95.21 6.5 0 0 0 0.00 0.00 0.0043.47 100 2 0 0 0 0.00 0.00 0.0098.59 100 2 0 0 0 6.47 3.84 0.50
260.85 100 4.5 0 0 0 7.25 4.17 0.50311.57 92.43 6.5 0 0 0 36.23 9.39 1.5072.45 100 3 0 0 0 14.49 33.33 0.50376.8 96.15 3 0 0 0 137.68 36.73 1.5028.98 83.33 1 0 0 0 0.00 0.00 0.0050.72 38.89 1.5 0 0 0 0.00 0.00 0.00
283.87 84.79 5.5 0 0 0 114.38 31.47 2.00391.3 85.31 2.5 0 0 0 0.00 0.00 0.00
470.99 89.29 5.5 7.25 0.93 0.5 123.18 20.11 1.507.25 25 0.5 0 0 0 7.25 25.00 0.50
43.47 100 2 0 0 0 7.25 16.67 0.50463.74 82.01 7 0 0 0 14.49 1.61 1.00137.67 83.48 3 0 0 0 108.69 58.93 1.0036.23 26.39 1 0 0 0 0.00 0.00 0.00
195.63 81.87 4 0 0 0 0.00 0.00 0.00326.08 97.06 3 0 0 0 28.99 6.90 0.50427.53 92.5 4 0 0 0 195.65 32.14 1.0014.49 33.33 0.5 0 0 0 0.00 0.00 0.00
245.01 75 2 0 0 0 154.44 55.95 1.00
Ecological and Trophic Metrics
Station Quality
RT01606 GoodRT01619 GoodRT01624 GoodRT01642 GoodRT01643 GoodRT01645 GoodRT01646 GoodRT01647 MarginalRT01648 GoodRT01649 GoodRT01650 GoodRT01652 GoodRT01653 GoodRT01655 GoodRT01664 GoodRT01668 GoodRT02002 GoodRT02006 GoodRT02007 GoodRT02008 GoodRT02009 GoodRT02013 GoodRT02015 GoodRT02016 GoodRT02019 GoodRT02021 GoodRT02027 GoodRT02030 GoodRT02152 GoodRT02153 GoodRT02154 Good
Detritivore Detritivore* Detritivore Herbivore* Herbivore* Herbivore* Omnivore* Omnivore* Omnivore*(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Ecological and Trophic Metrics
413.01 90.75 7 0 0 0 43.48 10.40 1.00188.39 83.33 3 0 0 0 144.92 63.64 1.0057.96 80 3 0 0 0 7.25 10.00 0.5050.72 100 3.5 0 0 0 14.49 35.00 1.0043.47 50 2 0 0 0 0.00 0.00 0.0050.72 100 2 0 0 0 36.23 70.83 1.0065.21 81.67 2 0 0 0 7.25 8.33 0.50
1275.33 96.25 7 0 0 0 681.16 45.00 1.00463.75 100 4.5 0 0 0 0.00 0.00 0.00224.63 50 2.5 0 0 0 94.20 20.97 0.5072.46 81.25 1 0 0 0 72.46 81.25 1.00
753.59 98.1 5 0 0 0 94.20 13.54 0.5050.72 100 2.5 0 0 0 0.00 0.00 0.00
572.46 94.45 2 0 0 0 557.97 90.74 1.00297.08 95.95 5 0 0 0 21.74 15.64 1.00673.9 97.5 3.5 0 0 0 0.00 0.00 0.00
105.35 80.36 2.5 0 0 0 0.00 0.00 0.0057.96 76.19 2.5 0 0 0 0.00 0.00 0.0043.47 100 1.5 0 0 0 0.00 0.00 0.00
297.08 89.13 5 0 0 0 137.68 41.31 1.00159.41 87.3 4 0 0 0 7.25 2.78 0.50
0 0 0 0 0 0 0.00 0.00 0.00311.58 75.38 3 0 0 0 7.25 1.51 0.50311.57 97.62 6 0 0 0 173.91 53.62 2.00152.16 85.56 4 0 0 0 57.97 31.11 1.50659.4 88.61 7 0 0 0 28.98 3.70 1.50
166.66 81.82 3.5 0 0 0 14.49 7.67 1.0014.49 50 0.5 0 0 0 14.49 50.00 0.5036.23 35 1 0 0 0 0.00 0.00 0.00
195.64 76.15 3.5 0 0 0 0.00 0.00 0.00108.69 89.29 4 0 0 0 65.22 41.07 1.00
Station Quality
RT02155 GoodRT02156 GoodRT02157 GoodRT02160 GoodRT02162 GoodRT02164 GoodRT02165 GoodRT02167 GoodRT02171 GoodRT99001 GoodRT99003 GoodRT99004 GoodRT99005 MarginalRT99006 GoodRT99008 GoodRT99009 MarginalRT99010 GoodRT99012 GoodRT99013 GoodRT99017 MarginalRT99019 GoodRT99022 GoodRT99024 GoodRT99026 GoodRT99027 GoodRT99028 GoodRT99029 GoodRT99030 MarginalRT99036 GoodRT99037 GoodRT99038 GoodRT99039 GoodRT99040 GoodAverage GoodAverage MarginalAverage AllMedian GoodMedian MarginalMedian All
Detritivore Detritivore* Detritivore Herbivore* Herbivore* Herbivore* Omnivore* Omnivore* Omnivore*(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Ecological and Trophic Metrics
137.67 79.76 5 0 0 0 43.48 25.40 1.0086.95 84.62 2.5 0 0 0 7.25 3.85 0.5021.74 57.14 1.5 0 0 0 0.00 0.00 0.00
260.85 91.18 4 0 0 0 108.69 35.43 1.0086.95 70 2.5 0 0 0 36.23 35.00 1.00
898.53 82.24 6 0 0 0 14.49 1.92 1.00202.89 87.62 4.5 0 0 0 0.00 0.00 0.00202.88 87.5 3.5 0 0 0 7.25 3.12 0.5086.95 82.5 2.5 0 0 0 14.49 17.50 1.00
101.44 100 3 0 0 0 0.00 0.00 0.00507.23 86.95 5 0 0 0 0.00 0.00 0.00166.66 70.46 4.5 0 0 0 28.99 9.09 0.50289.85 72.44 2 0 0 0 0.00 0.00 0.00195.64 92.89 3 0 0 0 14.49 5.88 0.50775.34 95.63 4 0 0 0 28.98 3.64 1.00478.25 82.22 4 0 0 0 0.00 0.00 0.0079.71 50 1.5 0 0 0 0.00 0.00 0.0072.46 100 3 0 0 0 0.00 0.00 0.00
478.24 87.89 4 0 0 0 0.00 0.00 0.00202.88 84.54 5.5 0 0 0 65.21 22.95 1.50159.42 100 2.5 0 0 0 7.25 3.57 0.50152.16 97.06 4.5 0 0 0 0.00 0.00 0.00543.47 98.49 2 0 0 0 0.00 0.00 0.00550.71 81.41 4.5 0 0 0 57.97 9.19 1.00362.31 97.22 3.5 0 0 0 65.22 14.90 1.00173.9 82.5 2 0 0 0 0.00 0.00 0.0057.96 100 2 0 0 0 0.00 0.00 0.00
797.08 96.77 4 0 0 0 0.00 0.00 0.00268.11 92.31 2.5 0 0 0 14.49 6.67 0.50
7.25 50 0.5 0 0 0 7.25 50.00 0.50318.83 80.98 4 0 0 0 7.25 1.56 0.5065.21 87.5 3 0 0 0 0.00 0.00 0.0072.46 65 2 0 0 0 0.00 0.00 0.00
219.54 81.27 2.99 0.08* 0.01* 0.01* 36.92 14.65* 0.49488.05 82.00 4.67 0.00 0.00 0.00 99.66 12.09 0.67244.72 81.34 3.15 0.08 0.01 0.01 42.80 14.41 0.51159.42 87.50* 3.00 0.00* 0.00* 0.00* 7.25* 3.57* 0.50*311.57 84.79 5.50 0.00 0.00 0.00 0.00 0.00 0.00170.28 87.40 3.00 0.00 0.00 0.00 7.25 3.35 0.50
*Average/median value at good stations equal to or lower than average/median value at marginal stations
Appendix E.3. Tolerance fish metrics calculated for 96 good and marginal
stations sampled in 1999-2002 (metrics in normal and bold font = used in one-
way analyses; metrics in bold font = used in discriminant analyses; italicized
metrics = not used in statistical analyses). *Average/median value at good
stations equal to or lower than average/median value at marginal stations. For
fish metric definitions, refer to Table 2.
Station Quality
MR-101-T MarginalMR-303-T GoodMR-304-T GoodNT01598 GoodRT00501 GoodRT00502 GoodRT00503 GoodRT00504 GoodRT00505 GoodRT00517 GoodRT00518 MarginalRT00519 GoodRT00520 GoodRT00521 GoodRT00523 MarginalRT00525 GoodRT00528 GoodRT00531 GoodRT00541 GoodRT00542 MarginalRT00543 GoodRT00544 GoodRT00545 GoodRT00546 GoodRT00547 GoodRT00550 GoodRT00554 GoodRT00557 GoodRT00558 GoodRT01602 GoodRT01603 GoodRT01604 Good
Bay Anchovy
Bay Anchovy*
Bay Anchovy Shad* Shad* Shad*
Bay Anchovy / Shad
Bay Anchovy / Shad*
Bay Anchovy / Shad Flatfish* Flatfish* Flatfish*
(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)0 0 0 0 0 0 0 0 0 7.25 16.67 0.50 0 0 0 0 0 0 0 0 28.98 7.69 1
14.49 33.33 0.5 0 0 0 14.49 33.33 0.5 0 0 00 0 0 0 0 0 0 0 0 0 0 0
166.66 81.8 1 0 0 0 166.66 81.8 1 0 0 00 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 7.25 1.19 0.5
246.37 87.3 1 0 0 0 246.37 87.3 1 0 0 043.48 66.67 1 0 0 0 43.48 66.67 1 0 0 086.96 66.67 1 0 0 0 86.96 66.67 1 0 0 0
159.42 19.93 1 0 0 0 159.42 19.93 1 57.97 4.44 1.57.25 10 0.5 0 0 0 7.25 10 0.5 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0115.94 52.08 1 0 0 0 115.94 52.08 1 14.49 4.17 0.514.49 6.67 0.5 0 0 0 14.49 6.67 0.5 21.74 6.36 1.5
0 0 0 0 0 0 0 0 0 7.25 7.14 0.50 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 7.25 16.67 0.5
36.23 27.78 0.5 0 0 0 36.23 27.78 0.5 7.25 50 0.513.71 4.19 1 0 0 0 13.71 4.19 1 7.25 1.92 0.5
268.12 37 0.5 0 0 0 268.12 37 0.5 28.98 4 157.97 17.59 1 0 0 0 57.97 17.59 1 14.49 1.85 1
0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 7.25 16.67 0.5
36.23 4.03 0.5 0 0 0 36.23 4.03 0.5 108.68 18.18 3.50 0 0 0 0 0 0 0 0 14.49 10.27 1
36.23 26.39 1 0 0 0 36.23 26.39 1 0 0 050.72 22.53 1 0 0 0 50.72 22.53 1 36.23 11.9 136.23 11.05 1 0 0 0 36.23 11.05 1 7.25 2.94 0.5
0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 14.49 33.33 0.50 0 0 0 0 0 0 0 0 0 0 0
Tolerance Metrics
Station Quality
RT01606 GoodRT01619 GoodRT01624 GoodRT01642 GoodRT01643 GoodRT01645 GoodRT01646 GoodRT01647 MarginalRT01648 GoodRT01649 GoodRT01650 GoodRT01652 GoodRT01653 GoodRT01655 GoodRT01664 GoodRT01668 GoodRT02002 GoodRT02006 GoodRT02007 GoodRT02008 GoodRT02009 GoodRT02013 GoodRT02015 GoodRT02016 GoodRT02019 GoodRT02021 GoodRT02027 GoodRT02030 GoodRT02152 GoodRT02153 GoodRT02154 Good
Bay Anchovy
Bay Anchovy*
Bay Anchovy Shad* Shad* Shad*
Bay Anchovy / Shad
Bay Anchovy / Shad*
Bay Anchovy / Shad Flatfish* Flatfish* Flatfish*
(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Tolerance Metrics
94.2 21 1 0 0 0 94.2 21 1 65.21 13.88 20 0 0 0 0 0 0 0 0 14.49 16.67 1
28.98 40 1 0 0 0 28.98 40 1 7.25 10 0.57.25 10 0.5 0 0 0 7.25 10 0.5 7.25 10 0.5
0 0 0 0 0 0 0 0 0 7.25 12.5 0.57.25 12.5 0.5 0 0 0 7.25 12.5 0.5 0 0 07.25 10 0.5 0 0 0 7.25 10 0.5 0 0 07.25 0.89 0.5 0 0 0 7.25 0.89 0.5 28.98 3.07 1.5
0 0 0 0 0 0 0 0 0 0 0 07.25 1.61 0.5 0 0 0 7.25 1.61 0.5 7.25 50 0.5
0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 130.43 15.7 10 0 0 0 0 0 0 0 0 14.49 58.33 10 0 0 0 0 0 0 0 0 7.25 1.85 0.5
7.25 1.35 0.5 0 0 0 7.25 1.35 0.5 14.49 8.49 10 0 0 0 0 0 0 0 0 159.41 24.09 2
21.18 19.64 1 0 0 0 21.18 19.64 1 6.97 3.57 0.528.98 38.1 1 0 0 0 28.98 38.1 1 0 0 028.98 75 1 0 0 0 28.98 75 1 0 0 043.48 13.04 1 0 0 0 43.48 13.04 1 21.74 6.52 114.49 9.92 1 0 0 0 14.49 9.92 1 21.74 8.33 1.5
0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 7.25 1.51 0.5
28.99 9.52 0.5 0 0 0 28.99 9.52 0.5 28.98 9.11 1.50 0 0 0 0 0 0 0 0 14.49 8.89 10 0 0 0 0 0 0 0 0 0 0 0
79.71 34.38 0.5 0 0 0 79.71 34.38 0.5 7.25 4.55 0.50 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0
152.17 48.46 1 0 0 0 152.17 48.46 1 21.74 21.92 10 0 0 0 0 0 0 0 0 14.49 16.07 1
Station Quality
RT02155 GoodRT02156 GoodRT02157 GoodRT02160 GoodRT02162 GoodRT02164 GoodRT02165 GoodRT02167 GoodRT02171 GoodRT99001 GoodRT99003 GoodRT99004 GoodRT99005 MarginalRT99006 GoodRT99008 GoodRT99009 MarginalRT99010 GoodRT99012 GoodRT99013 GoodRT99017 MarginalRT99019 GoodRT99022 GoodRT99024 GoodRT99026 GoodRT99027 GoodRT99028 GoodRT99029 GoodRT99030 MarginalRT99036 GoodRT99037 GoodRT99038 GoodRT99039 GoodRT99040 GoodAverage GoodAverage MarginalAverage AllMedian GoodMedian MarginalMedian All
Bay Anchovy
Bay Anchovy*
Bay Anchovy Shad* Shad* Shad*
Bay Anchovy / Shad
Bay Anchovy / Shad*
Bay Anchovy / Shad Flatfish* Flatfish* Flatfish*
(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Tolerance Metrics
14.49 11.11 0.5 0 0 0 14.49 11.11 0.5 7.25 3.57 0.50 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 14.49 5.88 1
28.99 20 0.5 0 0 0 28.99 20 0.5 0 0 043.48 5.77 0.5 0 0 0 43.48 5.77 0.5 326.08 31.52 2.565.22 24.05 1 0 0 0 65.22 24.05 1 7.25 5 0.5
0 0 0 0 0 0 0 0 0 14.49 6.25 10 0 0 0 0 0 0 0 0 21.74 37.5 10 0 0 0 0 0 0 0 0 43.48 51.52 1
14.49 2.5 1 0 0 0 14.49 2.5 1 65.21 10.55 10 0 0 0 0 0 0 0 0 7.25 4.55 0.50 0 0 0 0 0 0 0 0 0 0 0
159.42 76.96 1 0 0 0 159.42 76.96 1 0 0 094.2 11.53 1 0 0 0 94.2 11.53 1 0 0 0
108.7 20.16 1 0 0 0 108.7 20.16 1 7.25 1.11 0.514.49 9.09 0.5 0 0 0 14.49 9.09 0.5 0 0 07.25 6.25 0.5 0 0 0 7.25 6.25 0.5 36.23 50 1
0 0 0 0 0 0 0 0 0 86.95 16.85 150.72 18.6 1 7.25 2.17 0.5 57.97 20.77 1.5 0 0 065.22 32.14 0.5 0 0 0 65.22 32.14 0.5 0 0 057.97 23.53 0.5 0 0 0 57.97 23.53 0.5 0 0 0
289.85 52.15 1 0 0 0 289.85 52.15 1 0 0 021.74 3.85 0.5 0 0 0 21.74 3.85 0.5 0 0 0
101.45 36.36 1 0 0 0 101.45 36.36 1 0 0 0144.92 61.25 1 0 0 0 144.92 61.25 1 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0311.59 43.47 1 0 0 0 311.59 43.47 1 0 0 014.49 3.85 0.5 0 0 0 14.49 3.85 0.5 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0195.65 53.19 1 7.25 1.56 0.5 202.9 54.75 1.5 14.49 3.12 0.5
0 0 0 0 0 0 0 0 0 28.98 37.5 10 0 0 7.25 5 0.5 7.25 5 0.5 0 0 0
35.56 15.20* 0.41 0.17 0.08 0.01 35.73 15.27* 0.42 17.90* 8.64* 0.5173.99 12.66 0.67 0.81 0.24 0.06 74.79 12.90 0.72 14.49 3.73 0.6739.16 14.96 0.43 0.23 0.09 0.02 39.39 15.05 0.45 17.58 8.18 0.527.25 2.50 0.50 0.00* 0.00* 0.00* 7.25 3.85 0.50 7.25* 1.85 0.50*
14.49 6.67 1.00 0.00 0.00 0.00 14.49 6.67 1.00 7.25 1.92 0.507.25 3.85 0.50 0.00 0.00 0.00 7.25 3.94 0.50 7.25 1.89 0.50
*Average/median value at good stations equal to or lower than average/median value at marginal stations
Station Quality
MR-101-T MarginalMR-303-T GoodMR-304-T GoodNT01598 GoodRT00501 GoodRT00502 GoodRT00503 GoodRT00504 GoodRT00505 GoodRT00517 GoodRT00518 MarginalRT00519 GoodRT00520 GoodRT00521 GoodRT00523 MarginalRT00525 GoodRT00528 GoodRT00531 GoodRT00541 GoodRT00542 MarginalRT00543 GoodRT00544 GoodRT00545 GoodRT00546 GoodRT00547 GoodRT00550 GoodRT00554 GoodRT00557 GoodRT00558 GoodRT01602 GoodRT01603 GoodRT01604 Good
Flounder* Flounder* Flounder* Resilient Resilient ResilientSalinity
IndependentSalinity
IndependentSalinity
Independent Sciaenid Sciaenid Sciaenid(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)0 0 0 7.25 16.67 0.5 0 0 0 14.49 33.33 10 0 0 159.41 74.62 3 43.47 35.77 1 144.92 70.77 20 0 0 137.68 47.5 1 72.46 53.33 1 137.68 47.5 10 0 0 0 0 0 318.84 91.87 1 0 0 00 0 0 21.74 10.51 1 181.15 88.46 1.5 36.23 18.2 1.50 0 0 0 0 0 0 0 0 0 0 00 0 0 398.54 91.67 3 195.65 53.1 1 405.78 92.86 3.50 0 0 28.98 9.92 1.5 246.37 87.3 1 21.74 7.54 10 0 0 43.48 25 1.5 79.71 87.5 2 43.48 25 1.50 0 0 28.99 22.22 0.5 86.96 66.67 1 28.99 22.22 0.50 0 0 471 61.81 3.5 427.53 58.47 2 507.23 69.72 40 0 0 36.23 90 1.5 21.74 70 1.5 36.23 90 1.50 0 0 79.19 88.47 1 85.65 92.31 1.5 79.19 88.47 10 0 0 123.18 39.58 2.5 224.63 87.5 2.5 101.45 31.25 1
7.25 1.51 0.5 224.63 65.15 2.5 166.66 49.4 3 217.38 60 30 0 0 28.98 38.1 1 43.47 71.43 1.5 36.23 45.24 1.50 0 0 333.32 88.65 2.5 7.25 3.85 0.5 246.37 63.27 20 0 0 28.98 83.33 1 0 0 0 28.98 83.33 10 0 0 14.49 11.11 1 36.23 27.78 0.5 7.25 5.56 0.50 0 0 155.78 49.13 2.5 141.8 39.86 4 148.54 47.21 2
21.74 3 0.5 137.68 47.46 2.5 268.12 37 0.5 152.17 55.15 2.57.25 0.93 0.5 253.61 45.5 3 362.3 72.49 3 239.12 43.65 2
0 0 0 0 0 0 7.25 25 0.5 0 0 00 0 0 28.98 66.67 1 14.49 33.33 1 36.23 83.33 1.5
14.49 4.65 1 246.37 51.74 3 94.2 16.56 2 253.61 55.58 3.50 0 0 0 0 0 108.69 58.93 1 0 0 00 0 0 72.46 48.61 1 36.23 26.39 1 115.94 73.61 1.50 0 0 123.18 50.73 2 123.18 50.73 2 123.18 50.73 20 0 0 260.87 79.11 1.5 304.34 88.24 2.5 260.87 79.11 1.50 0 0 217.39 59.29 2 188.41 30.95 0.5 231.88 62.98 2.50 0 0 7.25 16.67 0.5 0 0 0 7.25 16.67 0.50 0 0 90.58 19.05 1 188.4 63.1 1.5 90.58 19.05 1
Tolerance Metrics
Station Quality
RT01606 GoodRT01619 GoodRT01624 GoodRT01642 GoodRT01643 GoodRT01645 GoodRT01646 GoodRT01647 MarginalRT01648 GoodRT01649 GoodRT01650 GoodRT01652 GoodRT01653 GoodRT01655 GoodRT01664 GoodRT01668 GoodRT02002 GoodRT02006 GoodRT02007 GoodRT02008 GoodRT02009 GoodRT02013 GoodRT02015 GoodRT02016 GoodRT02019 GoodRT02021 GoodRT02027 GoodRT02030 GoodRT02152 GoodRT02153 GoodRT02154 Good
Flounder* Flounder* Flounder* Resilient Resilient ResilientSalinity
IndependentSalinity
IndependentSalinity
Independent Sciaenid Sciaenid Sciaenid(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Tolerance Metrics
0 0 0 159.41 33.73 2.5 144.92 33.32 2.5 173.9 35.86 2.50 0 0 21.74 6.82 0.5 144.92 63.64 1 21.74 6.82 0.50 0 0 14.49 20 1 36.23 50 1.5 7.25 10 0.50 0 0 21.74 45 1.5 28.98 55 2 21.74 45 1.5
7.25 12.5 0.5 79.7 87.5 3 28.98 31.25 1 79.7 87.5 30 0 0 7.25 16.67 0.5 43.47 83.33 1.5 7.25 16.67 0.50 0 0 50.72 63.34 1 14.49 18.33 1 50.72 63.34 10 0 0 492.74 43.24 2.5 775.35 53.61 2.5 485.5 42.85 20 0 0 391.29 83.99 2 362.31 78.16 1 449.26 96.61 3.50 0 0 115.94 25.81 1 195.65 43.55 1.5 115.94 25.81 10 0 0 0 0 0 72.46 81.25 1 0 0 00 0 0 391.29 51.58 2 202.89 28.99 1.5 514.47 66.77 30 0 0 28.98 33.33 1 21.74 25 0.5 28.98 33.33 10 0 0 7.25 1.85 0.5 557.97 90.74 1 7.25 1.85 0.50 0 0 246.37 69.11 2 28.98 16.99 1.5 239.12 61.97 1.5
14.49 2.5 1 478.26 67.5 1.5 7.25 1.25 0.5 521.73 75 26.97 3.57 0.5 76.92 48.22 1 90.86 55.36 1.5 76.92 48.22 1
0 0 0 21.74 30.95 1 43.47 52.38 1.5 21.74 30.95 10 0 0 14.49 25 0.5 28.98 75 1 14.49 25 0.50 0 0 86.95 26.09 1.5 260.86 78.26 3 79.71 23.91 1
7.25 2.78 0.5 130.43 71.83 2 86.95 37.7 2 123.19 64.69 1.50 0 0 0 0 0 0 0 0 0 0 00 0 0 289.84 71.97 2.5 14.49 3.6 1 391.29 94.89 3.50 0 0 72.46 23.19 2 195.65 60.98 2 65.21 21.01 1.50 0 0 43.48 28.89 1.5 50.72 27.78 1 57.97 35.56 10 0 0 579.7 77.83 4 144.92 17.56 2 666.65 90.84 50 0 0 57.97 34.94 2 94.2 42.05 1.5 50.72 30.4 1.50 0 0 0 0 0 14.49 50 0.5 0 0 00 0 0 36.23 35 1 36.23 35 1 115.93 100 2
21.74 21.92 1 28.98 7.69 1.5 159.42 50.39 1.5 43.47 19.61 2.50 0 0 14.49 16.07 1 72.46 44.64 1.5 14.49 16.07 1
Station Quality
RT02155 GoodRT02156 GoodRT02157 GoodRT02160 GoodRT02162 GoodRT02164 GoodRT02165 GoodRT02167 GoodRT02171 GoodRT99001 GoodRT99003 GoodRT99004 GoodRT99005 MarginalRT99006 GoodRT99008 GoodRT99009 MarginalRT99010 GoodRT99012 GoodRT99013 GoodRT99017 MarginalRT99019 GoodRT99022 GoodRT99024 GoodRT99026 GoodRT99027 GoodRT99028 GoodRT99029 GoodRT99030 MarginalRT99036 GoodRT99037 GoodRT99038 GoodRT99039 GoodRT99040 GoodAverage GoodAverage MarginalAverage AllMedian GoodMedian MarginalMedian All
Flounder* Flounder* Flounder* Resilient Resilient ResilientSalinity
IndependentSalinity
IndependentSalinity
Independent Sciaenid Sciaenid Sciaenid(#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa) (#) (%) (taxa)
Tolerance Metrics
0 0 0 14.49 7.14 1 57.97 36.51 1.5 14.49 7.14 10 0 0 72.46 76.92 2 57.97 56.41 1.5 72.46 76.92 20 0 0 50.72 67.86 1.5 0 0 0 50.72 67.86 1.5
7.25 2.94 0.5 86.95 31.95 1.5 108.69 35.43 1 79.71 29.01 10 0 0 21.74 15 1 79.7 65 2 21.74 15 10 0 0 528.98 46.69 2 565.21 51.5 2 521.73 45.73 1.50 0 0 130.43 61.19 3.5 137.68 53.1 2 144.92 65.95 4
7.25 3.12 0.5 94.19 40.62 1.5 7.25 3.12 0.5 210.13 90.63 37.25 12.5 0.5 36.23 25 0.5 50.72 42.5 1.5 36.23 25 0.5
0 0 0 14.49 21.21 1 7.25 4.54 0.5 57.97 48.48 20 0 0 413.04 71.67 3 28.98 5 2 471 81.11 40 0 0 152.17 59.09 3 101.45 31.82 1.5 108.69 45.46 2.50 0 0 340.57 87.64 3 326.08 83.81 2 289.85 72.44 20 0 0 21.74 10.05 1.5 181.15 85.79 2 21.74 10.05 1.50 0 0 673.9 83.05 3 688.39 84.84 3.5 659.41 81.32 2.50 0 0 420.28 71.11 3 123.19 23.02 2 449.26 75.87 3.50 0 0 65.22 40.91 1 50.72 31.82 1 65.22 40.91 10 0 0 14.49 12.5 0.5 21.74 18.75 1 14.49 12.5 0.50 0 0 420.28 75.48 3 159.42 25.45 1 463.75 83.15 40 0 0 79.7 40.82 2.5 152.16 59.18 3 72.46 38.65 20 0 0 86.96 64.29 1.5 101.45 60.71 1.5 86.96 64.29 1.50 0 0 65.21 47.65 2.5 86.95 49.41 1.5 57.96 44.7 20 0 0 253.62 46.34 1 543.47 98.49 2 253.62 46.34 10 0 0 579.7 85.12 3 94.19 15.24 2.5 586.95 86.04 3.50 0 0 195.65 45.96 1.5 282.6 75.51 2.5 195.65 45.96 1.50 0 0 7.25 2.5 0.5 152.17 63.75 1.5 0 0 00 0 0 28.98 46.67 1 28.98 46.67 1 57.96 100 20 0 0 463.76 52.45 2.5 731.88 89.23 2 456.51 50.84 20 0 0 246.37 83.72 1.5 260.86 90.39 2 268.11 89.49 2.50 0 0 0 0 0 7.25 50 0.5 0 0 0
14.49 3.12 0.5 123.18 28.4 3 289.85 74.12 2.5 65.22 14.06 10 0 0 28.98 41.67 1.5 7.25 12.5 0.5 28.98 41.67 1.50 0 0 86.95 75 2.5 65.21 55 1.5 72.46 65 2
1.58* 0.85* 0.09* 125.10 41.64 1.51 123.55 46.83 1.34 132.35 44.63 1.550.81 0.17 0.06 295.08 54.22 2.50 316.07 50.73 2.28 293.47 54.55 2.391.51 0.78 0.08 141.04 42.82 1.60 141.60 47.20 1.43 147.45 45.56 1.630.00* 0.00* 0.00* 65.22 40.91 1.50 79.71 50.00 1.50 65.22 45.00 1.500.00 0.00 0.00 340.57 52.45 2.50 166.66 53.61 2.00 289.85 50.84 2.000.00 0.00 0.00 74.69 44.12 1.50 86.96 50.00 1.50 72.46 45.35 1.50
*Average/median value at good stations equal to or lower than average/median value at marginal stations
Appendix E.4. Fish community structure metrics calculated for 96 good and
marginal stations sampled in 1999-2002 (metrics in normal and bold font = used
in one-way analyses; metrics in bold font = used in discriminant analyses;
italicized metrics = not used in statistical analyses). *Average/median value at
good stations equal to or lower than average/median value at marginal stations.
For fish metric definitions, refer to Table 2.
Station Quality
MR-101-T MarginalMR-303-T GoodMR-304-T GoodNT01598 GoodRT00501 GoodRT00502 GoodRT00503 GoodRT00504 GoodRT00505 GoodRT00517 GoodRT00518 MarginalRT00519 GoodRT00520 GoodRT00521 GoodRT00523 MarginalRT00525 GoodRT00528 GoodRT00531 GoodRT00541 GoodRT00542 MarginalRT00543 GoodRT00544 GoodRT00545 GoodRT00546 GoodRT00547 GoodRT00550 GoodRT00554 GoodRT00557 GoodRT00558 GoodRT01602 GoodRT01603 GoodRT01604 Good
90% Abundance
95% Abundance Density Dominance* Dominance* Dominance*
Species Diversity
Species Evenness*
Species Richness Taxa
(taxa) (taxa) (#) (top taxon) (top 2 taxa) (top 3 taxa) (H') (J') (D) (#)5 5 43.47 50 83.33 100 1.25 0.96 0.4 2.5
10 11 224.61 55 70.77 86.54 1.93 0.81 0.99 6.53 4 166.66 60.83 97.5 100 1.07 0.84 0.31 2.52 3 347.82 91.87 97.14 98.57 0.47 0.34 0.34 34 4 202.89 81.8 96.15 100 0.78 0.6 0.28 2.50 0 0 0 0 0 0 0 0 06 9 449.25 65 85.6 91.67 1.51 0.61 0.8 63 5 282.6 87.3 94.84 100 0.67 0.42 0.35 36 7 101.44 66.67 83.34 87.5 1.13 0.44 0.48 3.54 5 130.43 66.67 94.45 100 0.95 0.69 0.31 2.58 11 768.08 38.54 60.7 80.63 2.34 0.78 1.16 8.53 3 43.47 80 90 100 0.69 0.43 0.23 23 4 98.59 88.47 96.16 100 0.5 0.31 0.2 25 7 260.85 64.59 83.34 91.67 1.44 0.66 0.63 4.5
10 12 347.79 33.34 58.49 69.7 2.54 0.85 1.21 85 6 72.45 54.76 85.71 92.86 1.38 0.92 0.46 35 5 384.04 51.92 84.81 96.15 1.51 0.85 0.44 3.52 2 36.23 83.33 100 100 0.46 0.46 0.13 1.55 6 72.46 77.78 83.33 88.89 0.94 0.4 0.41 3
11 14 330.69 48.78 66.79 79.03 2.22 0.74 1.21 85 6 456.51 67.77 84.31 92.15 1.39 0.65 0.59 4.5
13 17 543.44 35.72 64.42 77.12 2.5 0.79 1.41 102 2 21.74 75 100 100 0.5 0.5 0.15 1.54 4 43.47 66.67 83.33 100 0.79 0.5 0.27 2
13 17 543.44 38.4 57.38 66.07 2.71 0.81 1.6 117 8 166.65 58.93 69.2 79.47 1.72 0.74 0.8 53 4 152.17 52.78 95.83 100 1.16 0.91 0.3 2.59 11 246.35 32.05 54.58 73.26 2.35 0.91 0.91 65 6 333.32 70.29 86.01 97.06 1.24 0.69 0.44 3.55 6 449.26 68.45 89.05 93.93 1.32 0.61 0.58 4.52 2 21.74 33.33 50 50 0.46 0.46 0.13 13 4 252.26 55.95 92.86 100 1.16 0.92 0.31 2.5
Community Structure Metrics
Station Quality
RT01606 GoodRT01619 GoodRT01624 GoodRT01642 GoodRT01643 GoodRT01645 GoodRT01646 GoodRT01647 MarginalRT01648 GoodRT01649 GoodRT01650 GoodRT01652 GoodRT01653 GoodRT01655 GoodRT01664 GoodRT01668 GoodRT02002 GoodRT02006 GoodRT02007 GoodRT02008 GoodRT02009 GoodRT02013 GoodRT02015 GoodRT02016 GoodRT02019 GoodRT02021 GoodRT02027 GoodRT02030 GoodRT02152 GoodRT02153 GoodRT02154 Good
90% Abundance
95% Abundance Density Dominance* Dominance* Dominance*
Species Diversity
Species Evenness*
Species Richness Taxa
(taxa) (taxa) (#) (top taxon) (top 2 taxa) (top 3 taxa) (H') (J') (D) (#)
Community Structure Metrics
12 14 456.48 27.76 46.83 63.2 2.79 0.88 1.31 96 7 202.88 63.64 78.79 89.39 1.44 0.72 0.6 47 8 72.45 40 60 80 1.85 0.93 0.7 45 5 50.72 35 70 80 1.66 1 0.62 3.55 6 86.95 37.5 68.75 87.5 1.7 0.94 0.58 3.54 4 50.72 70.83 100 100 0.86 0.86 0.26 25 6 79.7 63.34 81.67 100 1.31 0.83 0.46 36 9 1326.05 54.82 80.13 87.85 1.91 0.6 1.13 95 6 463.75 78.16 89.56 95.39 1.1 0.51 0.57 4.53 5 231.87 70.97 91.94 96.77 0.85 0.37 0.33 32 3 86.95 81.25 100 100 0.68 0.68 0.23 26 8 768.08 36.14 65.37 90.99 1.98 0.77 0.76 64 4 50.72 75 83.33 91.67 0.9 0.45 0.34 2.52 3 594.2 90.74 94.45 96.3 0.52 0.23 0.34 37 9 318.82 60.62 76.26 84.75 1.62 0.68 0.96 6.54 4 688.39 66.25 87.84 96.25 1.3 0.6 0.54 4.57 8 126.52 48.22 67.86 83.93 1.65 0.82 0.65 46 7 72.45 38.1 69.05 92.86 1.71 0.96 0.59 3.52 2 43.47 75 100 100 0.5 0.5 0.12 1.59 11 333.31 41.31 67.39 80.44 2.24 0.8 1.03 77 8 181.15 53.57 71.83 81.75 1.9 0.8 0.86 5.5
0.5 0.5 14.49 50 50 50 0 0 0 0.56 8 413.02 48.86 75.95 92.8 1.76 0.76 0.67 59 11 318.82 49.28 67.91 81.78 2.02 0.75 0.95 6.59 10 173.9 38.89 63.34 78.89 2.17 0.88 0.88 5.58 11 731.85 50.97 72.05 84.58 2.11 0.69 1.14 8.58 9 195.64 57.11 71.02 78.69 1.86 0.76 0.87 5.51 1 14.49 50 50 50 0 0 0 0.54 4 115.93 65 100 100 0.86 0.86 0.21 27 9 224.62 58.46 72.31 84.23 1.61 0.73 0.77 58 9 130.42 41.07 60.72 76.79 1.98 0.88 0.84 5
Station Quality
RT02155 GoodRT02156 GoodRT02157 GoodRT02160 GoodRT02162 GoodRT02164 GoodRT02165 GoodRT02167 GoodRT02171 GoodRT99001 GoodRT99003 GoodRT99004 GoodRT99005 MarginalRT99006 GoodRT99008 GoodRT99009 MarginalRT99010 GoodRT99012 GoodRT99013 GoodRT99017 MarginalRT99019 GoodRT99022 GoodRT99024 GoodRT99026 GoodRT99027 GoodRT99028 GoodRT99029 GoodRT99030 MarginalRT99036 GoodRT99037 GoodRT99038 GoodRT99039 GoodRT99040 GoodAverage GoodAverage MarginalAverage AllMedian GoodMedian MarginalMedian All
90% Abundance
95% Abundance Density Dominance* Dominance* Dominance*
Species Diversity
Species Evenness*
Species Richness Taxa
(taxa) (taxa) (#) (top taxon) (top 2 taxa) (top 3 taxa) (H') (J') (D) (#)
Community Structure Metrics
11 12 166.65 25.4 50.8 69.05 2.51 0.93 1.08 6.57 8 115.93 52.57 80.77 88.46 1.6 0.9 0.61 44 4 65.21 60.72 92.86 100 1.07 0.86 0.36 2.58 10 282.59 47.19 73.26 85.96 1.95 0.81 0.8 5.55 6 108.68 50 85 95 1.41 0.95 0.42 39 11 1065.18 44.77 63.08 71.48 2.38 0.75 1.17 98 10 224.62 39.05 68.1 77.86 2.17 0.84 0.94 66 8 231.86 46.88 78.13 90.63 1.72 0.8 0.64 4.55 6 101.44 50 77.5 95 1.59 0.89 0.55 3.55 6 101.44 56.06 90.91 95.46 1.3 0.88 0.43 38 10 586.93 61.95 72.5 81.95 1.84 0.63 1.02 7.59 11 239.11 31.82 52.27 65.91 2.52 0.9 1.11 74 5 391.29 68.61 90.06 96.17 1.24 0.62 0.5 45 6 210.13 76.96 87.01 94.12 1.13 0.57 0.56 45 6 811.57 67.95 81.32 91.99 1.51 0.59 0.75 66 8 579.69 53.02 75.4 88.41 1.81 0.7 0.79 63 3 79.71 22.73 40.91 50 0.75 0.47 0.2 1.55 5 72.46 50 87.5 93.75 1.37 0.94 0.46 37 9 550.7 51.26 71.43 83.55 1.89 0.81 0.64 5
11 13 231.86 31.88 56.04 75.85 2.42 0.89 1.1 73 4 159.42 57.14 96.43 100 1.1 0.88 0.29 2.57 8 159.4 43.53 62.35 78.24 2.04 0.9 0.8 54 4 550.72 52.15 98.49 100 1.08 0.86 0.24 2.55 7 673.89 64.32 82.91 92.1 1.53 0.63 0.69 5.55 6 369.55 57.58 80.81 94.19 1.53 0.76 0.51 45 6 202.88 61.25 82.5 97.5 1.2 0.7 0.47 3.53 3 57.96 63.33 100 100 0.94 0.94 0.25 24 7 811.57 57.05 89.23 94.31 1.49 0.64 0.61 55 6 297.09 79.87 90.39 94.23 0.97 0.58 0.43 3.51 1 7.25 50 50 50 0 0 0 0.58 10 398.53 53.19 70.04 80.64 1.91 0.7 0.91 6.56 7 72.45 37.5 66.67 87.5 1.73 0.96 0.59 3.57 8 108.68 45 65 85 1.84 0.92 0.65 4
5.45 6.55 246.77 56.26* 77.28* 86.45* 1.38 0.69 0.57 4.077.22 9.33 536.72 48.45 73.35 85.77 1.91 0.75 0.90 6.445.62 6.81 273.95 55.53 76.91 86.39 1.43 0.70 0.60 4.295.00 6.00 181.15 55.95* 80.81* 91.67* 1.41 0.76* 0.56 3.506.00 9.00 391.29 50.00 75.40 87.85 1.91 0.74 1.10 7.005.00 6.00 202.89 54.79 80.45 91.33 1.47 0.76 0.58 4.00
*Average/median value at good stations equal to or lower than average/median value at marginal stations
Appendix F. Individual water quality parameter scores, overall average water
quality, and adjusted average water quality for 97 stations sampled in 1999-2002.
*Poor station (NT02301) was eliminated from final analysis. See text for details.
Station pHDissolved
Oxygen (mg/L)Biological Oxygen Demand (mg/L)
Total Nitrogen (mg/L)
Total Phosphorus (mg/L)
Fecal Coliform (col/100mL)
Water Quality (Average)
Water Quality (Adjusted Average)
MR1-01-T 3 3 5 3 5 5 4.000 5MR3-03-T 5 5 5 3 5 5 4.667 5MR3-04-T 5 5 5 5 3 5 4.667 5NT01598 5 5 3 5 5 3 4.333 5NT02301* 5 3 3 5 5 1 3.667 3RT00501 5 5 5 5 3 5 4.667 5RT00502 1 3 5 5 1 5 3.333 3RT00503 5 3 5 5 5 5 4.667 5RT00504 3 3 5 5 4.000 5RT00505 5 3 5 5 5 5 4.667 5RT00517 5 5 5 5 5 5 5.000 5RT00518 3 1 3 3 3 3 2.667 3RT00519 3 5 5 5 3 5 4.333 5RT00520 5 5 5 5 5 5 5.000 5RT00521 5 5 5 5 5 5 5.000 5RT00523 3 3 5 5 3 1 3.333 3RT00525 5 3 5 5 5 5 4.667 5RT00528 3 5 3 3 1 3 3.000 3RT00531 3 5 3 5 5 5 4.333 5RT00541 5 5 5 5 5 5 5.000 5RT00542 5 3 1 5 3 3 3.333 3RT00543 5 5 5 3 4.500 5RT00544 5 5 1 5 5 5 4.333 5RT00545 5 5 1 5 5 5 4.333 5RT00546 5 3 3 5 3 5 4.000 5RT00547 5 3 5 5 5 5 4.667 5RT00550 5 5 1 5 5 5 4.333 5RT00554 1 3 5 5 5 5 4.000 5RT00557 5 5 5 5 3 5 4.667 5RT00558 3 5 5 5 5 4.600 5RT01602 5 5 5 5 5 5.000 5RT01603 1 3 5 1 1 3 2.333 3RT01604 5 3 5 3 5 4.200 5RT01606 5 5 5 5 5.000 5RT01619 5 5 5 3 5 4.600 5
Station pHDissolved
Oxygen (mg/L)Biological Oxygen Demand (mg/L)
Total Nitrogen (mg/L)
Total Phosphorus (mg/L)
Fecal Coliform (col/100mL)
Water Quality (Average)
Water Quality (Adjusted Average)
RT01624 5 5 5 5 5 5.000 5RT01642 5 5 5 5 5.000 5RT01643 3 3 5 3 1 5 3.333 3RT01645 5 5 1 5 4.000 5RT01646 5 5 5 5 5.000 5RT01647 5 1 3 5 5 5 4.000 5RT01648 5 5 5 5 3 5 4.667 5RT01649 5 5 5 5 5.000 5RT01650 5 5 5 5 5 5.000 5RT01652 5 5 5 5 5.000 5RT01653 5 5 3 5 5 4.600 5RT01655 5 5 3 5 4.500 5RT01664 5 5 5 5 5 5 5.000 5RT01668 5 5 3 4.333 5RT02002 5 5 5 5 5 5 5.000 5RT02006 5 5 5 5 5 5 5.000 5RT02007 5 5 5 5 5 5 5.000 5RT02008 5 5 5 5 5 5 5.000 5RT02009 5 5 5 5 5 5 5.000 5RT02013 5 5 5 5 5 5 5.000 5RT02015 5 1 5 5 5 5 4.333 5RT02016 5 5 5 5 5 5 5.000 5RT02019 5 5 5 5 5.000 5RT02021 3 3 5 3 3.500 3RT02027 5 5 1 3 5 5 4.000 5RT02030 3 5 5 5 5 5 4.667 5RT02152 3 1 5 5 5 5 4.000 5RT02153 5 3 5 5 5 3 4.333 5RT02154 5 5 5 5 5 5 5.000 5RT02155 5 3 5 5 3 5 4.333 5RT02156 5 5 5 5 5 5 5.000 5RT02157 5 5 3 5 5 5 4.667 5RT02160 5 5 5 5 5 5 5.000 5RT02162 3 5 3 5 5 5 4.333 5RT02164 5 5 1 5 5 5 4.333 5
Station pHDissolved
Oxygen (mg/L)Biological Oxygen Demand (mg/L)
Total Nitrogen (mg/L)
Total Phosphorus (mg/L)
Fecal Coliform (col/100mL)
Water Quality (Average)
Water Quality (Adjusted Average)
RT02165 5 5 5 5 3 5 4.667 5RT02167 3 3 5 5 5 5 4.333 5RT02171 5 5 5 5 5.000 5RT99001 5 3 3 3 3 5 3.667 3RT99003 5 3 5 5 5 5 4.667 5RT99004 5 3 5 3 3 5 4.000 5RT99005 5 3 1 5 3 3.400 3RT99006 5 5 3 5 3 3 4.000 5RT99008 5 5 5 3 5 4.600 5RT99009 3 1 5 5 3 3 3.333 3RT99010 3 5 1 5 3 5 3.667 3RT99012 5 3 1 5 3 5 3.667 3RT99013 5 3 5 5 5 5 4.667 5RT99017 3 5 1 5 3 3 3.333 3RT99019 5 5 3 5 5 5 4.667 5RT99022 5 3 5 5 3 5 4.333 5RT99024 3 3 5 5 5 5 4.333 5RT99026 3 1 3 5 5 5 3.667 3RT99027 3 5 3 5 5 4.200 5RT99028 5 5 5 5 3 5 4.667 5RT99029 5 1 5 5 5 4.200 5RT99030 5 3 3 5 3 5 4.000 5RT99036 5 5 5 3 3 5 4.333 5RT99037 3 3 1 5 3 3 3.000 3RT99038 5 5 1 5 1 5 3.667 3RT99039 5 3 5 5 3 5 4.333 5RT99040 5 5 1 3 3 5 3.667 3
Appendix G. Water, sediment, upland, and overall quality and final estuarine
biotic integrity (EBI) scores for 97 stations sampled in 1999-2002 (5=good;
3=marginal; 1=poor; e=excellent). Excellent stations were a subset of good
stations. EBI scores were determined using the final EBI index (EBI index D6). A
station that classified as good was correctly predicted if it had an EBI score
≥37.5; a station that classified as marginal was correctly predicted if it had an EBI
score ≤2.5.
Station Year Water Sediment Upland EBI score PredictedMR1-01-T 2002 4.000 5 2 3 35MR3-03-T 2002 4.667 5 5 5 10MR3-04-T 2002 4.667 5 5 5 35NT01598 2001 4.333 5 2 5 35NT02301* 2002 3.667 1 2 1 N/ART00501 2000 4.667 5 5 5 30RT00502 2000 3.333 5 5 5 30RT00503 2000 4.667 5 2 5 15RT00504 2000 4.000 5 5 5 30RT00505 2000 4.667 5 5 5 30RT00517 2000 5.000 5 5 5 e 35RT00518 2000 2.667 3 5 3 5RT00519 2000 4.333 5 5 5 40 YesRT00520 2000 5.000 5 5 5 e 40 YesRT00521 2000 5.000 3 5 5 10RT00523 2000 3.333 5 2 3 5RT00525 2000 4.667 5 5 5 40 YesRT00528 2000 3.000 5 5 5 20RT00531 2000 4.333 5 5 5 45 YesRT00541 2000 5.000 5 5 5 e 40 YesRT00542 2000 3.333 5 2 3 5RT00543 2000 4.500 5 5 5 20RT00544 2000 4.333 5 5 5 5RT00545 2000 4.333 5 2 5 40 YesRT00546 2000 4.000 5 5 5 45 YesRT00547 2000 4.667 5 5 5 10RT00550 2000 4.333 5 2 5 25RT00554 2000 4.000 5 5 5 25RT00557 2000 4.667 5 2 5 5RT00558 2000 4.600 3 5 5 30RT01602 2001 5.000 5 5 5 e 25RT01603 2001 2.333 5 5 5 35RT01604 2001 4.200 5 2 5 30RT01606 2001 5.000 3 5 5 5RT01619 2001 4.600 5 5 5 25RT01624 2001 5.000 5 5 5 e 10RT01642 2001 5.000 5 5 5 e 35RT01643 2001 3.333 5 5 5 30RT01645 2001 4.000 5 5 5 40 YesRT01646 2001 5.000 3 5 5 35RT01647 2001 4.000 5 2 3 10RT01648 2001 4.667 3 5 5 25RT01649 2001 5.000 5 5 5 e 40 YesRT01650 2001 5.000 5 2 5 35RT01652 2001 5.000 5 5 5 e 10RT01653 2001 4.600 5 5 5 40 YesRT01655 2001 4.500 5 2 5 40 YesRT01664 2001 5.000 5 2 5 25RT01668 2001 4.333 3 5 5 30
OverallEnvironmental Quality
Station Year Water Sediment Upland EBI score PredictedOverallEnvironmental Quality
RT02002 2002 5.000 5 5 5 e 15RT02006 2002 5.000 5 2 5 15RT02007 2002 5.000 3 5 5 35RT02008 2002 5.000 5 5 5 e 5RT02009 2002 5.000 5 5 5 e 10RT02013 2002 5.000 5 2 5 30RT02015 2002 4.333 5 5 5 15RT02016 2002 5.000 3 5 5 15RT02019 2002 5.000 5 5 5 e 20RT02021 2002 3.500 3 5 5 10RT02027 2002 4.000 5 5 5 15RT02030 2002 4.667 5 5 5 30RT02152 2002 4.000 3 5 5 35RT02153 2002 4.333 3 5 5 15RT02154 2002 5.000 5 5 5 e 15RT02155 2002 4.333 5 5 5 15RT02156 2002 5.000 5 5 5 e 15RT02157 2002 4.667 5 5 5 40 YesRT02160 2002 5.000 5 5 5 e 20RT02162 2002 4.333 5 5 5 30RT02164 2002 4.333 5 5 5 10RT02165 2002 4.667 3 5 5 5RT02167 2002 4.333 3 5 5 20RT02171 2002 5.000 5 5 5 e 30RT99001 1999 3.667 3 5 5 45 YesRT99003 1999 4.667 5 5 5 15RT99004 1999 4.000 5 5 5 10RT99005 1999 3.400 3 2 3 15RT99006 1999 4.000 5 5 5 20RT99008 1999 4.600 5 5 5 10RT99009 1999 3.333 3 2 3 10RT99010 1999 3.667 5 5 5 30RT99012 1999 3.667 5 5 5 30RT99013 1999 4.667 3 5 5 10RT99017 1999 3.333 5 2 3 0 YesRT99019 1999 4.667 5 2 5 35RT99022 1999 4.333 5 2 5 15RT99024 1999 4.333 5 5 5 15RT99026 1999 3.667 5 5 5 15RT99027 1999 4.200 5 2 5 15RT99028 1999 4.667 5 5 5 30RT99029 1999 4.200 5 5 5 40 YesRT99030 1999 4.000 5 2 3 5RT99036 1999 4.333 3 5 5 30RT99037 1999 3.000 5 5 5 30RT99038 1999 3.667 5 5 5 10RT99039 1999 4.333 5 5 5 25RT99040 1999 3.667 5 5 5 10
*Eliminated from analyses
Appendix H. The SAS procedure for applying the metrics selected for EBI index
D6 in a non-parametric, quadratic discriminant analysis, with cross-validation
(SAS Institute 2000b). Preliminary tests included a multivariate analysis of
variance (MANOVA) and a Bartlett's modification of the likelihood ratio test
(Morrison 1976; Anderson 1984; SAS Institute 2000b). The standard kernel was
normal and the smoothing parameter was 1. Metrics for EBI index D6 correctly
classified all 96 stations sampled in 1999-2002 (MANOVA, p=0.0033; Bartlett’s
test, p<0.0001). See text for more details.
data indxall2;input Station$ Category ABUN_M BENTH_PM DOM1_M ERES_NM ESPAW_NM FLAT_AM H_PRI_M NSPP_M;cards;
MR1-01-T 3 43.47 100 50 1.5 2 7.25 1.25 2.5MR3-03-T 5 224.61 94.23 55 2 3.5 28.98 1.93 6.5MR3-04-T 5 166.66 66.67 60.83 1 1.5 0 1.07 2.5NT01598 5 347.82 94.73 91.87 0 0 0 0.47 3RT00501 5 202.89 18.2 81.8 1.5 1.5 0 0.78 2.5RT00502 5 0 0 0 0 0 0 0 0RT00503 5 449.25 100 65 2.5 3.5 7.25 1.51 6RT00504 5 282.6 12.7 87.3 1.5 1.5 0 0.67 3RT00505 5 101.44 33.33 66.67 1.5 2 0 1.13 3.5RT00517 5 130.43 27.78 66.67 1 1 0 0.95 2.5RT00518 3 768.08 77.85 38.54 3 5 57.97 2.34 8.5RT00519 5 43.47 90 80 1.5 1.5 0 0.69 2RT00520 5 98.59 92.31 88.47 1 1 0 0.5 2RT00521 5 260.85 39.58 64.59 2.5 2.5 14.49 1.44 4.5RT00523 3 347.79 80.3 33.34 2 3.5 21.74 2.54 8RT00525 5 72.45 100 54.76 1.5 1.5 7.25 1.38 3RT00528 5 384.04 67.11 51.92 0 0.5 0 1.51 3.5RT00531 5 36.23 100 83.33 0 0 7.25 0.46 1.5RT00541 5 72.46 72.22 77.78 0.5 1 7.25 0.94 3RT00542 3 330.69 79.37 48.78 2 2 7.25 2.22 8RT00543 5 456.51 63 67.77 1 2.5 28.98 1.39 4.5RT00544 5 543.44 78.7 35.72 3.5 4.5 14.49 2.5 10RT00545 5 21.74 100 75 0 0 0 0.5 1.5RT00546 5 43.47 100 66.67 0.5 1 7.25 0.79 2RT00547 5 543.44 95.16 38.4 2.5 5.5 108.68 2.71 11RT00550 5 166.65 96.88 58.93 1.5 2.5 14.49 1.72 5RT00554 5 152.17 73.61 52.78 1 2.5 0 1.16 2.5RT00557 5 246.35 65.02 32.05 2 2 36.23 2.35 6RT00558 5 333.32 88.95 70.29 2 2.5 7.25 1.24 3.5RT01602 5 449.26 98.81 68.45 0 1.5 0 1.32 4.5RT01603 5 21.74 50 33.33 0.5 1 14.49 0.46 1RT01604 5 252.26 75 55.95 0.5 0.5 0 1.16 2.5RT01606 5 456.48 73.03 27.76 3 5.5 65.21 2.79 9RT01619 5 202.88 100 63.64 1 1.5 14.49 1.44 4RT01624 5 72.45 40 40 2.5 3 7.25 1.85 4RT01642 5 50.72 90 35 1.5 1.5 7.25 1.66 3.5
RT01643 5 86.95 100 37.5 1 2 7.25 1.7 3.5RT01645 5 50.72 87.5 70.83 0.5 0.5 0 0.86 2RT01646 5 79.7 81.67 63.34 0.5 0.5 0 1.31 3RT01647 3 1326.05 94.96 54.82 3 4.5 28.98 1.91 9RT01648 5 463.75 98.78 78.16 1 1 0 1.1 4.5RT01649 5 231.87 96.77 70.97 1 1.5 7.25 0.85 3RT01650 5 86.95 81.25 81.25 0 0 0 0.68 2RT01652 5 768.08 100 36.14 2.5 3 130.43 1.98 6RT01653 5 50.72 100 75 1.5 2 14.49 0.9 2.5RT01655 5 594.2 100 90.74 1.5 1.5 7.25 0.52 3RT01664 5 318.82 88.8 60.62 1.5 1.5 14.49 1.62 6.5RT01668 5 688.39 100 66.25 1.5 1.5 159.41 1.3 4.5RT02002 5 126.52 51.79 48.22 1.5 1.5 6.97 1.65 4RT02006 5 72.45 61.9 38.1 2 2.5 0 1.71 3.5RT02007 5 43.47 25 75 1 1 0 0.5 1.5RT02008 5 333.31 78.26 41.31 3 4.5 21.74 2.24 7RT02009 5 181.15 82.94 53.57 3 4 21.74 1.9 5.5RT02013 5 28.98 100 100 1 1 0 0 1RT02015 5 413.02 100 48.86 1.5 3 7.25 1.76 5RT02016 5 318.82 86.13 49.28 1.5 3.5 28.98 2.02 6.5RT02019 5 173.9 82.22 38.89 0 1 14.49 2.17 5.5RT02021 5 731.85 97.11 50.97 1.5 3.5 0 2.11 8.5RT02027 5 195.64 61.08 57.11 1 3 7.25 1.86 5.5RT02030 5 14.49 50 50 0 0 0 0 0.5RT02152 5 115.93 100 65 1 2 0 0.86 2RT02153 5 224.62 41.54 58.46 1.5 2 21.74 1.61 5RT02154 5 130.42 96.43 41.07 2 2.5 14.49 1.98 5RT02155 5 166.65 57.94 25.4 1 2.5 7.25 2.51 6.5RT02156 5 115.93 88.46 52.57 1.5 2 0 1.6 4RT02157 5 65.21 100 60.72 0.5 1.5 0 1.07 2.5RT02160 5 282.59 97.06 47.19 0 1 14.49 1.95 5.5RT02162 5 108.68 50 50 1.5 1.5 0 1.41 3RT02164 5 1065.18 85.83 44.77 3.5 5.5 326.08 2.38 9RT02165 5 224.62 70.95 39.05 2.5 4 7.25 2.17 6RT02167 5 231.86 96.88 46.88 0 1 14.49 1.72 4.5RT02171 5 101.44 100 50 1.5 2 21.74 1.59 3.5RT99001 5 101.44 100 56.06 1.5 1.5 43.48 1.3 3RT99003 5 586.93 97.5 61.95 3.5 4.5 65.21 1.84 7.5RT99004 5 239.11 81.82 31.82 0.5 3.5 7.25 2.52 7
RT99005 3 391.29 72.44 68.61 1 2 0 1.24 4RT99006 5 210.13 15.93 76.96 1 1.5 0 1.13 4RT99008 5 811.57 86.75 67.95 2 3 0 1.51 6RT99009 3 579.69 78.41 53.02 1.5 3 7.25 1.81 6RT99010 5 79.71 40.91 22.73 1 1 0 0.75 1.5RT99012 5 72.46 93.75 50 2 2 36.23 1.37 3RT99013 5 550.7 100 51.26 2 3 86.95 1.89 5RT99017 3 231.86 63.77 31.88 2.5 2.5 0 2.42 7RT99019 5 159.42 67.86 57.14 1 1 0 1.1 2.5RT99022 5 159.4 63.53 43.53 1.5 1.5 0 2.04 5RT99024 5 550.72 47.85 52.15 2.5 2.5 0 1.08 2.5RT99026 5 673.89 96.15 64.32 1.5 3 0 1.53 5.5RT99027 5 369.55 60.86 57.58 1.5 1.5 0 1.53 4RT99028 5 202.88 0 61.25 1 1.5 0 1.2 3.5RT99029 5 57.96 100 63.33 1 1 0 0.94 2RT99030 3 811.57 53.68 57.05 2.5 3 0 1.49 5RT99036 5 297.09 96.15 79.87 1.5 2.5 0 0.97 3.5RT99037 5 7.25 50 50 0 0 0 0 0.5RT99038 5 398.53 18.75 53.19 1.5 3 14.49 1.91 6.5RT99039 5 72.45 100 37.5 2 2.5 28.98 1.73 3.5RT99040 5 108.68 75 45 1.5 3 0 1.84 4
run;Proc print;run;
Proc DISCRIM POOL=NO METHOD=NPAR KERNEL=NORMAL R=1 WCOV PCOV BCOV MANOVA crosslist;Class CATEGORY;Priors proportional;
Var ABUN_M BENTH_PM DOM1_M ERES_NM ESPAW_NM FLAT_AM NSPP_M H_PRI_M;
run;
