Genetic relationships among populations of Florida bass

Genetic Relationships among Populations of Florida Bass

BRANDON L. BARTHEL*Illinois Natural History Survey, Institute of Natural Resource Sustainability; and Program in Ecology and

Evolutionary Biology, University of Illinois Urbana–Champaign, Urbana, Illinois 61802, USA

DIJAR J. LUTZ-CARRILLO AND KRISTEN E. NORBERG

Texas Parks and Wildlife Department, A. E. Wood Laboratory, San Marcos, Texas 78666, USA

WESLEY F. PORAK

Florida Fish and Wildlife Conservation Commission, Eustis Fisheries Research Laboratory,Eustis, Florida 32726, USA

MICHAEL D. TRINGALI

Florida Fish and Wildlife Conservation Commission, Fish and Wildlife Research Institute,St. Petersburg, Florida 33701, USA

TODD W. KASSLER1

Illinois Natural History Survey, Institute of Natural Resource Sustainability,University of Illinois Urbana–Champaign, Urbana, Illinois 61802, USA

WILLIAM E. JOHNSON

Florida Fish and Wildlife Conservation Commission, Eustis Fisheries Research Laboratory,Eustis, Florida 32726, USA

ANNE M. READEL

Program in Ecology and Evolutionary Biology, University of Illinois Urbana–Champaign,Urbana, Illinois 61802, USA

RICHARD A. KRAUSE

Florida Fish and Wildlife Conservation Commission, Fish and Wildlife Research Institute,Holt, Florida 32564, USA

DAVID P. PHILIPP

Illinois Natural History Survey, Institute of Natural Resource Sustainability,University of Illinois Urbana–Champaign, Urbana, Illinois 61802, USA

Abstract.—Florida bass Micropterus floridanus are endemic to peninsular Florida and co-occur with

largemouth bass M. salmoides in a natural intergrade zone in the northern portions of the state. In this study,

we resolved the genetic population structure among populations of largemouth bass, Florida bass, and their

interspecific hybrids from 48 lakes and streams across Florida, and we updated and refined the southernmost

boundary of introgression. Nuclear (allozyme and microsatellite) and mitochondrial (restriction fragment

length polymorphism) markers produced somewhat different results. Microsatellite genotypes alone and the

combination of all nuclear genotypes resolved genetic structure among four regional groups within Florida:

(1) northwest, (2) north-central, (3) central-west, and (4) south, central-east, and northeast. Allozyme

genotypes alone did not resolve well-defined groups. The distribution of mitochondrial haplotypes suggested

that populations from the St. Johns River drainage should be considered their own distinct group (rather than

be included in the south–central-east–northeast Florida group). Although mitochondrial markers failed to

* Corresponding author: [email protected]

1 Present address: Washington Department of Fish and Wildlife, Olympia, Washington 98501, USA.

Received October 4, 2009; accepted March 8, 2010Published online October 11, 2010

1615

Transactions of the American Fisheries Society 139:1615–1641, 2010� Copyright by the American Fisheries Society 2010DOI: 10.1577/T09-185.1

[Article]

detect introgression throughout much of the intergrade zone, nuclear markers revealed an expected decline in

introgression from west to east as well as from north to south. Largemouth bass alleles, however, were

detected at low frequencies in 12 populations below the southern boundary of the accepted intergrade zone,

some of which are the result of stocking. There was no evidence of nonrandom mating or selection against

hybrids in the distribution of nuclear genotypes; however, the rarity of largemouth bass mitochondrial

haplotypes suggests either assortative mating or reduced fitness in the progeny of female largemouth bass 3

male Florida bass crosses.

Animal populations are commonly influenced by

hybridization (Allendorf et al. 2001), and fishes

hybridize more frequently than do any other verte-

brates, in part due to recreational species being

translocated outside of their native ranges and into

contact with closely related species (Campton 1987;

Rhymer and Simberloff 1996). In some cases,

hybridization and introgression can be a driving force

in range expansion and speciation by introducing novel

genotypes that are fit enough to occupy new adaptive

peaks (Dobzhansky 1970; Choler et al. 2004; Grant et

al. 2005). However, when anthropogenic influences

affect the rate and magnitude of this natural phenom-

enon, introgressive hybridization can obscure the

genetic identity of endemic species (Mallet 2005) and

alter endemic biodiversity (Tanaka 2007). This is

particularly true when anthropogenic influences result

in the hybridization of spatially isolated species that

have not fully developed isolating mechanisms due to a

lack of previous reinforcement (Rubidge and Taylor

2004). Hybridization is known to have played a

substantial role in the extinction of a number of fish

species listed under the U.S. Endangered Species Act

(Rhymer and Simberloff 1996), and outbreeding

negatively affects populations that do not go extinct

(Edmands 2007). In addition to the adverse effects on

the populations themselves, decisions concerning

conservation and management become more compli-

cated when significant proportions of individuals are

hybrids (Allendorf et al. 2001).

The black basses Micropterus spp. are among the

most popular freshwater sport fishes in North America

and have been translocated widely for many decades.

Numerous studies have documented hybridization

between endemic and nonindigenous species after

introductions (Edwards 1979; Philipp et al. 1983;

Whitmore 1983; Maciena et al. 1988; Morizot et al.

1991; Dunham et al. 1992; Gilliland 1994; Koppelman

1994; Forshage and Fries 1995; Gelwick et al. 1995;

Pierce and Van Den Avyle 1997; Pipas and Bulow

1998; Barwick et al. 2006), including endemic taxa

designated as ‘‘species of special concern’’ due to

limited ranges or small population sizes (Koppelman

and Garrett 2002). In one example, the persistence of

Guadalupe bass M. treculii in central Texas is currently

threatened not only by habitat degradation but also by

competition and introgression with introduced small-

mouth bass M. dolomieu and spotted bass M.punctulatus (Morizot et al. 1991). Florida bass M.floridanus and largemouth bass M. salmoides coexist in

introgressed populations throughout a hybrid zone that

includes all of the southeastern United States, a number

of the mid-Atlantic coast states, some southwestern

states, and California (Philipp et al. 1983).2 Although

some of the introgressed populations are the result of

natural hybridization that occurred when the two taxa

came into secondary contact, stocking activities have

greatly expanded the hybrid zone (Philipp et al. 1983)

and created a patchwork of introgressed and nonintro-

gressed populations. Florida bass, which are endemic

to peninsular Florida, tend to grow to larger ultimate

sizes than do largemouth bass (Chew 1975) and have

been stocked outside of their native range to enhance

trophy bass production. As a result, nonintrogressed

populations of largemouth bass are primarily restricted

to the midwestern and northeastern United States and

southern parts of Canada, while nonintrogressed

populations of Florida bass are only found in

peninsular Florida (Philipp et al. 1983).

Although many states have been importing Florida

bass for stocking purposes for decades, the Florida Fish

and Wildlife Conservation Commission (FWC) is

presently committed to preserving the genetic integrity

of Florida bass populations within the state. Manage-

ment actions designed to limit hybridization depend on

the FWC having accurate information on the distribu-

tions of the Florida bass, largemouth bass, and hybrid

populations within the state. Using meristic and

morphometric techniques, Bailey and Hubbs (1949)

concluded that largemouth bass populations existed

north and west of the Choctawhatchee and Apalachi-

cola River drainages in northwest Florida, whereas

populations south and east of the Suwannee River

drainage in peninsular Florida (including the St. Johns

River) were exclusively composed of Florida bass; the

region between these areas was bisected by an

2 Editor’s note: Although some authorities (e.g., Kassler etal. 2002; Near et al. 2003) recognize the Florida bass as aseparate species, pending further investigation the AmericanFisheries Society’s Committee on Names of Fishes continuesto recognize it as a subspecies of the largemouth bass with thescientific name M. salmoides floridanus.

1616 BARTHEL ET AL.

intergrade zone (Bailey and Hubbs 1949). Philipp et al.

(1981, 1983) re-evaluated the range of the species and

the intergrade zone using taxon-specific allelic differ-

ences at a number of allozyme loci and found the

southern delineation to be similar to that described by

Bailey and Hubbs (1949). Philipp et al. (1981, 1983),

however, also found that all populations in northwest

Florida were introgressed, suggesting either that

molecular genetic techniques offered greater resolution

than meristics and morphometrics or that there had

been an expansion of the intergrade zone in that

direction during the period since the Bailey and Hubbs

(1949) study. This delineation (Philipp et al. 1983) has

been accepted by fisheries biologists and managers as

the boundary between Florida bass and intergrade

populations in Florida for more than two decades.

The FWC has obtained most of the broodstock for

their main hatchery from the putative range of pure

Florida bass since the early 1980s, but broodfish were

not genetically tested on a routine basis until 1999. In

the first year of genetic testing, the analysis of

broodfish collected from Lake Parker, located 150

km south of the recognized intergrade zone, docu-

mented nonnative largemouth bass alleles in 10% of

the fish tested (W. F. Porak, unpublished data). This

finding was particularly disconcerting because Lake

Parker had been used as a source for hatchery

broodstock over several years before genetic testing;

indeed, hatchery reports indicated that the lake had

been stocked with fish from a hatchery in northern

Florida—one that used intergrade broodstock—during

the 1970s. The Lake Parker example proved that

collecting broodfish south of the recognized intergrade

zone was not sufficient to prevent unintentional

hybridization within nonintrogressed Florida bass

populations and that a new approach was needed to

avoid additional hybridization events in the future.

A number of studies have recently found that both

inter- and intraspecific outbreeding can result in

reduced fitness for largemouth bass and Florida bass.

Philipp and Claussen (1995) and Philipp et al. (2002)

showed that local populations of black bass (both

Florida bass and largemouth bass) had greater growth,

survival, and reproductive success than nonlocal and

introgressed fish when they were raised in pond

environments. Others found that interstock F1

gener-

ations of largemouth bass displayed reduced cardio-

vascular, swimming, and respiratory performance

relative to parental stocks in the Midwest, which was

interpreted as a loss of local adaptation (Cooke et al.

2001; Cooke and Philipp 2005). Goldberg et al. (2005)

proposed that the disruption of coadapted genes

involved in immune function were responsible for F2

juvenile largemouth bass being significantly more

susceptible to largemouth bass virus than the parental

or F1

generation.

This study was designed to collect the information

needed by the FWC to develop a comprehensive plan

for protecting the genetic integrity of endemic

populations of Florida bass. The primary objectives

were to (1) define the current extent of hybridization

between Florida bass and largemouth bass in Florida

and (2) resolve the genetic structure among populations

of these two basses within Florida. Given the lack of

congruence in rates and directions of gene flow

between nuclear and mitochondrial genomes in other

hybrid zones (Avise 2001), three types of molecular

markers (allozymes, microsatellite DNA, and mito-

chondrial DNA [mtDNA] restriction fragment length

polymorphisms [RFLPs]) incorporating both lineages

were used.

Methods

Study area and sampling.—The U.S. Geological

Survey has designated eight major hydrologic units

(formally defined as subregions; represented by bold

lines in Figure 1) and 50 distinct watersheds (fine lines

in Figure 1) within the state of Florida. Between 1999

and 2003, FWC biologists sampled 48 public lakes and

streams located in 25 watersheds and 7 major

hydrologic units (Tables 1, A.1). Sampling was

greatest in central Florida due to the large number of

lakes and streams in the region and its location at the

southern boundary of the hybrid zone (Figure 1).

Samples were taken by means of electrofishing gear

in all water bodies except Nine Mile Pond, where bass

were collected by angling. Sixty individuals were

collected from all but four collection sites, with as few

as 31 and 36 fish being collected from the Peace River

and Lake Trafford, respectively (Table 1). White

skeletal muscle and liver tissues were dissected from

all individuals, immediately frozen on dry ice, and then

stored at�708C until they were shipped to the Illinois

Natural History Survey (INHS), Champaign, and the

A. E. Wood Laboratory, Texas Parks and Wildlife

Department (TPWD), San Marcos, for genetic analysis.

Sample processing.—White skeletal muscle and

liver tissues were homogenized in 100-mM tris-HCl

(pH 7.0), centrifuged at 22,000 3 gravity for 10 min at

48C, and then subjected to vertical starch gel

electrophoresis coupled with histochemical staining as

described by Philipp et al. (1979), with modifications

from Koppelman and Philipp (1986). In this study, we

examined products from three loci expressed in white

muscle tissue (aspartate aminotransferase A, enzyme

number 2.6.1.1, IUBMB 1992; malate dehydrogenase

A and B, 1.1.1.37) and three loci expressed in liver

tissue (aspartate aminotransferase B [AAT-B*], 2.6.1.1;

FLORIDA BASS GENETIC RELATIONSHIPS 1617

isocitrate dehydrogenase B [IDH-B*], 1.1.1.42; super-

oxide dismutase A [SOD-A*], 1.15.1.1). Both AAT-B*

and IDH-B* have fixed allelic differences between

Florida bass and largemouth bass (Philipp et al. 1981).

We isolated genomic DNA from either (1) a small

amount of muscle tissue (;2–3 mm3) by modifying the

methodology of Miller et al. (1988) and using

ammonium acetate in place of sodium chloride for

salting out cellular proteins or (2) 200 mg of white

skeletal muscle using a technique described by Saghai-

Maroof et al. (1984) and modified by Fields et al.

(1989). Recovered DNA was quantified by spectro-

photometry and adjusted to a concentration of 50 ng/

lL with a low tris–EDTA buffer.

The panel of nuclear markers also included 12

microsatellite loci. Three multiplex polymerase chain

reactions (PCRs) were used to amplify the following

loci: (1) Msa21, Mdo7, Lma12, and Msa29 (designed

from GenBank accession number DQ211538); (2)

Msa13, Mdo6, and Mdo3; and (3) MiSaTPW111,

MiSaTPW112, and MiSaTPW169 (Colbourne et al.

1996; DeWoody et al. 2000; Malloy et al. 2000; Lutz-

Carrillo et al. 2008). Single-locus PCRs were used to

amplify alleles at the loci MiSaTPW60 and MiS-

aTPW70 (Lutz-Carrillo et al. 2008). All PCRs were

carried out in 10-lL volumes on a Mastercycler ep

gradient S thermal cycler (Eppendorf). Reactions

consisted of 50 ng of template DNA, 13 buffer (20-

mM tris-HCl [pH 8.4], 50-mM KCl; Invitrogen), 1.5–

2.5-mM MgCl2

(Invitrogen), 0.2 mM of each deoxy-

nucleotide triphosphate (dNTP), 0.05–0.08 lM of an

unlabeled 5 0-tailed primer, 0.07–0.20 lM of an

unlabeled nontailed primer, 0.2 lM of a 25% labeled

(700 or 800 IRDye; LI-COR) fluorescent tail (M13–29

or CAG sequence), and 0.5 unit of Platinum Taq DNA

polymerase (2.7.7.7; Invitrogen). Cycling conditions

were (1) 948C for 90 s; (2) 29–33 cycles of

denaturation at 948C for 30 s, annealing for 30 s at

FIGURE 1.—Locations of the 48 lakes and streams in Florida sampled for this study; pie charts depict the frequency of

largemouth bass and Florida bass alleles at eight diagnostic loci (6 microsatellites, 2 allozymes) within populations. The thick

lines delineate the major hydrologic units designated by the U.S. Geological Survey, and the thin lines represent watershed

boundaries. Population codes are given in parentheses.

1618 BARTHEL ET AL.

primer-specific temperature, and extension at 728C for

30–60 s; and (3) a final extension at 728C for 10 min.

Amplicons with alternate fluorescent labels were

combined, and 10 lL of stop solution were added for

a final volume of 30 lL before being loaded in 0.25-lL

volumes and resolved on a NEN 4300 DNA sequencer

(LI-COR) alongside LI-COR 50–350 or 50–700 size

standards. Allele sizes were determined with BioNu-

merics version 4.6 (Applied Maths).

Digestions for RFLP analyses were performed on

PCR-amplified segments of the mitochondrial genome

that included two genes (NADH subunits 3 and 4).

Approximately 2,200 base pairs (bp) were amplified

with a light-strand primer (L9386) located in the

transfer RNAGly (tRNAGly) gene (50-GTACACGT-

CACTTCCAATCA-30; Park et al. 1993) and a heavy-

strand primer (H11540) located in the tRNAHis gene

(5 0-AGAATCACAATCTAATGTTT-3 0; Park et al.

1993). All PCRs were carried out in 50-lL volumes

on an MJ Research PTC-100–60 thermocycler. Reac-

tions consisted of approximately 25 ng of template

DNA, 103 buffer, 2.5-mM MgCl2, 100 lM of each

dNTP, 0.08-pmol/lL concentrations of the light- and

heavy-strand primers, and 15 units of Taq polymerase

(Applied Biosystems). Cycling conditions were (1)

958C for 2 min; (2) 29 cycles at 948C for 45 s and 458C

for 1 min; (3) a final extension step at 708C for 4 min;

and (4) a final holding step at 48C. Subsamples (8 lL)

of each amplicon were digested with one of six

restriction endonucleases (Dde I, Dpn II, Hae III, HhaI, Msp I, and Rsa I; New England Biolabs) following

the manufacturer’s recommendations. Digests were

separated electrophoretically on 2.0% agarose and

1.0% Synergel (Diversified Biotech) gels in tris–

acetate–EDTA buffer (0.04-M tris-HCl, 5.7% glacial

acetic acid, and 1-mM EDTA [pH 8.0]) with a 0.5-lg/

mL concentration of ethidium bromide to visualize

banding patterns under ultraviolet light. A 100-bp

DNA ladder (0.5 lg/lane) was used as a standard for

fragment size determination.

Genetic variation.—For the nuclear markers, allele

frequencies, mean number of alleles observed per

locus, and observed and expected heterozygosities

based on allozyme and microsatellite genotypes were

calculated with GENETIX version 4.0 (Belkhir et al.

2000). Tests of conformation to Hardy–Weinberg

equilibrium (HWE), linkage equilibrium, and differen-

tiation for each population pair were performed with

exact tests in ARLEQUIN version 3.1 (10,000

Markov-chain permutations; Excoffier et al. 2005),

and significance was evaluated with sequential Bon-

ferroni corrections for multiple tests (Rice 1989). For

mitochondrial markers, comparisons of haplotype

distributions for each population pair were conducted

with Fisher’s exact tests (Raymond and Rousset 1995)

in ARLEQUIN (10,000 Markov-chain permutations;

Excoffier et al. 2005).

Introgression.—Values of the hybrid index, defined

as the proportion of Florida bass alleles detected at

diagnostic loci for each individual, were calculated

with the allozyme loci AAT-B* and IDH-B* and the

microsatellite loci Mdo6, Msa21, Msa29, MiS-aTPW112, MiSaTPW111, and MiSaTPW169. Mean

hybrid index values were calculated for each popula-

tion and represent the probability that a randomly

selected allele was derived from a Florida bass

ancestor.

Genetic structure.—Estimates of nuclear genetic

structure were performed with the Bayesian model

implemented in STRUCTURE version 2.2 (Pritchard et

al. 2000; Falush et al. 2003). This model attempts to

partition multilocus genotypes into an optimal number

of groups whose composition minimizes Hardy–

Weinberg and linkage disequilibrium. Simultaneously,

genotypes are assigned to each resolved group with an

associated membership coefficient (q). An admixture

model with independent allele frequencies and non-

informative priors was used as suggested by Pritchard

et al. (2007) to minimize the chances of overestimating

the number of groups. The ad hoc statistic DK was used

in conjunction with the distribution of likelihood and avalues (i.e., admixture among resolved groups) to

evaluate each solution as suggested by Evanno et al.

(2005). After preliminary experimental runs were

conducted, 10 independent replicates of the number

of genetic clusters (K) from 1 to 10 were performed

with 104 burn-in steps and 105 Markov-chain Monte

Carlo iterations. Runs were performed with multilocus

microsatellite genotypes (9 loci) from 47 populations

(Lake Jackson was not included in analyses because

there were insufficient tissue samples to conduct

microsatellite genotyping; N ¼ 1,410), multilocus

allozyme genotypes (6 loci) from 48 populations (N¼ 2,856), and a combination of the two (15 loci) for 47

populations (N ¼ 1,410). Genotypes composing each

resolved cluster at the optimal K were then re-evaluated

under independent STRUCTURE runs as suggested for

data sets containing genotypes from contact zones

(Evanno et al. 2005). Values of q were averaged over

all 10 runs for individual fish and then over populations

to allow the assignment of populations to groups.

Genetic relationships were further explored as

genetic distances between populations. A consensus

neighbor-joining dendrogram based on 1,000 bootstrap

data sets and Cavalli-Sforza and Edwards (1967)

genetic distances based on the combined nuclear data

set were produced with PHYLIP version 3.6 (Felsen-

stein 1989) and visualized with TreeView version 1.6


(Page 1996). A similar approach was used to create a

consensus tree from the mtDNA RFLP data set; the

primary differences were that (1) pairwise genetic

differentiation index (FST

) values (ARLEQUIN; Ex-

coffier et al. 2005) were used in the place of Cavalli-

Sforza and Edwards (1967) chord distances and (2) 300

rather than 1,000 bootstraps were employed. A

haplotype network constructed by median-joining

methods (Fluxus Network version 4.5; Bandelt et al.

1999) was used to explore genetic structure based on

the mitochondrial data alone.

Analyses of molecular variance and isolation by

TABLE 1.—Sample sizes and genetic diversity parameters of the Florida bass, largemouth bass, and intergrade populations

sampled in Florida. Sample size (N), average number of alleles per locus (Na), observed heterozygosity (H

O), expected

heterozygosity (HE), inbreeding coefficient (F

IS), the proportion of individuals with hybrid genotypes (Prop. hybrid), and the

mean hybrid index (Hyb. index) for the allozyme and microsatellite loci are shown for each population. Sample size (N), number

of different haplotypes observed (Hapl.), total number of polymorphic sites (Poly. sites), and gene diversity (6SD) for

mitochondrial DNA (mtDNA) restriction fragment length polymorphism (RFLP) analyses are also presented.

Collection (code) Total (N)

Allozyme analysis

N Na

HO

HE

FIS

Prop.hybrid Hyb. index

1. Nine Mile Pond (Nine) 60 60 1.50 0.181 0.185 0.031 0.000 1.0002. Tamiami Canal (Tami) 59 59 1.40 0.210 0.196 �0.065 0.000 1.0003. Conservation Area 3 (Con3) 60 60 1.50 0.208 0.203 �0.019 0.000 1.0004. Lake Trafford (Traf) 36 36 1.67 0.259 0.203 �0.263 0.028 0.9935. Lake Okeechobee (Okee) 60 60 1.50 0.192 0.177 �0.071 0.000 1.0006. Lake Istokpoga (Isto) 60 60 1.50 0.114 0.136 0.173 0.000 1.0007. Lake Weohyakapka (Weoh) 60 60 1.67 0.194 0.178 �0.084 0.000 1.0008. East Lake Tohopekaliga (Toho) 60 60 1.67 0.208 0.188 �0.102 0.000 1.0009. Lake Down (Down) 60 60 1.50 0.147 0.156 0.065 0.000 1.000

10. Conway Chain (Conw) 60 60 1.50 0.167 0.155 �0.066 0.000 1.00011. Peace River (Peac) 31 31 1.50 0.214 0.185 �0.150 0.000 1.00012. Medard Reservoir (Meda) 59 59 1.50 0.113 0.141 0.207 0.000 1.00013. Hillsborough River (Hill) 60 60 1.50 0.206 0.207 0.017 0.000 1.00014. Lake Tarpon (Tarp) 60 60 1.50 0.169 0.173 0.027 0.000 1.00015. Lake Parker (Park) 60 60 1.83 0.161 0.171 0.068 0.033 0.98316. Lake Shipp (Ship) 60 60 1.50 0.133 0.142 0.068 0.000 1.00017. Homosassa River (Homo) 60 60 2.00 0.236 0.250 0.062 0.067 0.96318. Lake Tsala Apopka (Tsal) 60 60 1.67 0.231 0.211 �0.085 0.000 1.00019. Lake Panasoffkee (Pana) 60 60 1.83 0.211 0.215 0.026 0.067 0.99220. Lake Weir (Weir) 60 60 1.50 0.222 0.191 �0.158 0.000 1.00021. Lake Minneola (Minn) 60 60 1.50 0.242 0.222 �0.083 0.000 1.00022. Lake Harris (Harr) 60 60 1.83 0.097 0.097 0.008 0.033 0.99223. Lake Dora (Dora) 60 60 1.50 0.094 0.112 0.166 0.000 1.00024. Lake Lawne (Lawn) 60 60 1.67 0.219 0.192 �0.132 0.050 0.98825. Farm 13 Reservoir (Farm) 60 60 1.67 0.183 0.176 �0.035 0.017 0.99626. Lake Washington (Wash) 60 60 1.50 0.189 0.183 �0.022 0.000 1.00027. Lake Monroe (Monr) 60 60 1.67 0.175 0.183 0.051 0.000 1.00028. Lake Norris (Norr) 60 60 1.33 0.125 0.114 �0.084 0.000 1.00029. Lake George (Geor) 60 60 1.67 0.200 0.178 �0.116 0.017 0.99630. Lake Kerr (Kerr) 60 60 1.67 0.156 0.146 �0.055 0.283 0.92131. Lochloosa Lake (Loch) 60 60 1.67 0.119 0.121 0.020 0.050 0.98832. Rodman Reservoir (Rodm) 60 60 1.67 0.189 0.182 �0.028 0.000 1.00033. Kingsley Lake (King) 60 60 1.50 0.150 0.157 0.050 0.000 1.00034. St. Johns River (StJo) 60 60 1.67 0.269 0.259 �0.032 0.017 0.89235. Ocean Pond (Ocea) 60 60 1.67 0.172 0.172 0.009 0.517 0.99636. Lake Santa Fe (Sant) 60 60 2.00 0.231 0.220 �0.039 0.367 0.85037. Lake Sampson (Samp) 60 60 1.83 0.192 0.195 0.023 0.250 0.93238. Waccasassa River (Wacc) 60 60 2.00 0.183 0.177 �0.029 0.050 0.98839. Suwannee River (Suwa) 60 60 1.67 0.183 0.168 �0.081 0.100 0.97540. Steinhatchee River (Stei) 60 60 1.67 0.169 0.173 0.027 0.083 0.97941. Cherry Lake (Cher) 60 60 1.67 0.150 0.154 0.032 0.017 0.99242. Aucilla River (Auci) 60 60 1.83 0.134 0.186 0.292 0.194 0.92743. Lake Jackson (Jack) 60 60 2.00 0.197 0.172 �0.140 0.383 0.89444. Lake Talquin (Talq) 60 60 2.00 0.257 0.252 �0.010 0.883 0.64245. Lake Seminole (Semi) 60 60 2.00 0.286 0.289 0.019 0.867 0.58846. Lower Apalachicola River (Apal) 60 60 2.00 0.292 0.277 �0.044 0.933 0.51347. Choctawhatchee River (Choc) 60 60 2.33 0.217 0.228 0.056 0.900 0.39648. Escambia River (Esca) 60 60 2.00 0.144 0.120 �0.197 0.600 0.179

a Samples from Lake Jackson were not included in the microsatellite analysis.

1620 BARTHEL ET AL.

distance.—The significance of genetic structure ob-

served among the regional groups resolved by the

STRUCTURE analyses was determined by analyses of

molecular variance (AMOVAs). Analyses of the

allozyme, microsatellite, and mtDNA data sets with

ARLEQUIN (10,000 Markov-chain permutations; Ex-

coffier et al. 2005) were performed independently.

Mantel tests were used to evaluate the strength and

significance of correlations between pairwise FST

values and the geographic distances between collection

sites (10,000 Markov-chain permutations) at two

scales: (1) among populations sampled across the state

and (2) among populations within the resolved regional

groups.

TABLE 1.—Extended.

Collection (code)

Microsatellite analysis mtDNA RFLP analysis

N Na

HO

HE

FIS

Prop.hybrid

Hyb.index N Hapl.

Poly.sites Gene diversity

1. Nine Mile Pond (Nine) 29 7.22 0.471 0.496 0.070 0.000 1.000 20 3 8 0.195 6 0.11452. Tamiami Canal (Tami) 30 7.22 0.506 0.530 0.064 0.000 1.000 22 3 9 0.325 6 0.11733. Conservation Area 3 (Con3) 30 6.67 0.489 0.506 0.051 0.000 1.000 21 3 6 0.186 6 0.11024. Lake Trafford (Traf) 30 7.00 0.489 0.487 0.013 0.000 1.000 21 3 6 0.657 6 0.05725. Lake Okeechobee (Okee) 30 6.78 0.493 0.510 0.051 0.000 1.000 20 4 9 0.284 6 0.12846. Lake Istokpoga (Isto) 30 6.78 0.521 0.510 0.129 0.000 1.000 20 3 9 0.279 6 0.12357. Lake Weohyakapka (Weoh) 30 5.89 0.456 0.475 0.062 0.000 1.000 21 3 4 0.186 6 0.11028. East Lake Tohopekaliga (Toho) 30 6.33 0.495 0.489 0.006 0.000 1.000 20 2 5 0.100 6 0.08809. Lake Down (Down) 30 4.44 0.417 0.453 0.098 0.000 1.000 20 4 7 0.616 6 0.0671

10. Conway Chain (Conw) 30 5.00 0.386 0.425 0.112 0.000 1.000 20 2 5 0.395 6 0.100611. Peace River (Peac) 30 6.44 0.430 0.467 0.097 0.000 1.000 20 2 1 0.395 6 0.100612. Medard Reservoir (Meda) 30 5.67 0.485 0.530 0.105 0.000 1.000 21 3 2 0.667 6 0.049813. Hillsborough River (Hill) 30 4.78 0.360 0.398 0.116 0.000 1.000 20 3 3 0.626 6 0.078714. Lake Tarpon (Tarp) 30 7.78 0.485 0.500 0.049 0.000 1.000 22 5 8 0.649 6 0.064515. Lake Parker (Park) 30 8.00 0.505 0.535 0.073 0.000 1.000 21 6 9 0.752 6 0.061016. Lake Shipp (Ship) 30 7.33 0.502 0.520 0.053 0.000 1.000 20 3 2 0.542 6 0.104617. Homosassa River (Homo) 30 5.89 0.399 0.437 0.110 0.000 1.000 20 4 5 0.626 6 0.083918. Lake Tsala Apopka (Tsal) 30 7.44 0.495 0.515 0.057 0.000 1.000 20 3 2 0.532 6 0.100419. Lake Panasoffkee (Pana) 30 8.33 0.475 0.499 0.064 0.000 1.000 20 4 4 0.742 6 0.050620. Lake Weir (Weir) 30 6.00 0.490 0.509 0.055 0.000 1.000 20 3 6 0.353 6 0.122721. Lake Minneola (Minn) 30 5.56 0.493 0.466 �0.041 0.000 1.000 20 4 4 0.600 6 0.077122. Lake Harris (Harr) 30 7.00 0.551 0.557 0.029 0.000 1.000 20 2 4 0.190 6 0.108123. Lake Dora (Dora) 30 6.78 0.505 0.492 �0.006 0.000 1.000 20 3 2 0.484 6 0.112924. Lake Lawne (Lawn) 30 6.44 0.473 0.532 0.129 0.033 0.995 20 3 2 0.484 6 0.112925. Farm 13 Reservoir (Farm) 30 7.11 0.471 0.510 0.094 0.000 1.000 20 4 6 0.595 6 0.097726. Lake Washington (Wash) 30 7.22 0.483 0.536 0.116 0.000 1.000 20 4 7 0.721 6 0.065327. Lake Monroe (Monr) 30 6.89 0.485 0.503 0.057 0.033 0.996 20 4 7 0.684 6 0.063628. Lake Norris (Norr) 30 6.00 0.420 0.452 0.091 0.000 1.000 20 3 6 0.616 6 0.077029. Lake George (Geor) 30 8.67 0.516 0.537 0.056 0.067 0.993 24 6 7 0.703 6 0.062330. Lake Kerr (Kerr) 30 6.33 0.536 0.527 0.000 0.067 0.993 20 3 2 0.416 6 0.115731. Lochloosa Lake (Loch) 30 6.67 0.479 0.522 0.100 0.233 0.973 20 3 6 0.195 6 0.114532. Rodman Reservoir (Rodm) 30 8.00 0.498 0.536 0.089 0.033 0.997 20 9 7 0.895 6 0.039633. Kingsley Lake (King) 30 5.11 0.503 0.467 �0.058 0.000 1.000 20 4 5 0.705 6 0.061234. St. Johns River (StJo) 30 7.44 0.514 0.517 0.022 0.100 0.996 20 4 6 0.690 6 0.066435. Ocean Pond (Ocea) 30 7.67 0.526 0.520 0.007 0.467 0.988 20 2 1 0.190 6 0.108136. Lake Santa Fe (Sant) 30 4.89 0.426 0.442 0.054 0.033 0.943 24 5 6 0.638 6 0.060637. Lake Sampson (Samp) 30 7.11 0.462 0.494 0.081 0.133 0.982 20 4 6 0.700 6 0.061938. Waccasassa River (Wacc) 30 6.67 0.361 0.438 0.196 0.200 0.967 21 4 5 0.271 6 0.124239. Suwannee River (Suwa) 30 7.56 0.394 0.460 0.162 0.400 0.950 20 5 5 0.811 6 0.036540. Steinhatchee River (Stei) 30 4.56 0.428 0.512 0.183 0.600 0.900 20 4 13 0.600 6 0.077141. Cherry Lake (Cher) 30 5.11 0.444 0.458 0.048 0.233 0.976 20 2 3 0.100 6 0.088042. Aucilla River (Auci) 30 6.78 0.530 0.554 0.062 0.500 0.927 22 4 6 0.671 6 0.060543. Lake Jackson (Jack) 0 a 22 4 4 0.463 6 0.119944. Lake Talquin (Talq) 29 7.78 0.527 0.521 0.006 0.500 0.932 6 3 2 0.733 6 0.155245. Lake Seminole (Semi) 30 7.89 0.626 0.634 0.031 0.964 0.736 20 3 12 0.195 6 0.114546. Lower Apalachicola River (Apal) 30 6.56 0.590 0.599 0.035 0.967 0.713 20 2 1 0.100 6 0.088047. Choctawhatchee River (Choc) 30 8.89 0.655 0.689 0.066 1.000 0.581 23 1 0 0.000 6 0.000048. Escambia River (Esca) 30 7.33 0.476 0.531 0.122 0.633 0.109 20 3 11 0.353 6 0.1227


ResultsGenetic Variation

The number of alleles observed at allozyme loci

ranged from 2 to 4 alleles/locus over all samples and

from 1.33 to 2.33 alleles/locus within populations

(mean ¼ 1.69 alleles/locus; SD ¼ 0.21; Table 1). A

single population deviated from HWE at a single locus

after sequential Bonferroni correction (Lake Istokpoga,

SOD-A*: P ¼ 0.0001; Table A.2), and linkage

disequilibrium was not detected in any population.

Allele frequencies were significantly different in 72%of comparisons between pairs of populations.

The number of alleles observed at microsatellite loci

ranged from 6 to 108 alleles/locus over all samples and

from 4.44 to 8.89 alleles/locus within populations

(mean ¼ 6.70 alleles/locus; SD ¼ 1.07; Table 1). Four

populations significantly deviated from HWE at a

single locus after sequential Bonferroni correction

(Waccasassa River, Msa21: P , 0.001; Steinhatchee

River, MiSaTPW60: P , 0.001; Lake Tsala Apopka,

MiSaTPW70: P , 0.001; Choctawhatchee River,

MiSaTPW70: P , 0.001; Table A.2); no linkage

disequilibrium was detected. Allele frequencies among

populations were significantly different in 92% of

pairwise comparisons.

Analyses of mtDNA RFLPs identified 21 polymor-

phic sites distributed among 25 haplotypes. The

number of haplotypes per population ranged from 1

to 9 (mean ¼ 3.5 haplotypes/population; SD ¼ 1.3;

Table 1), which corresponded to 0–13 polymorphic

sites/collection (mean ¼ 5.3 polymorphic sites/collec-

tion; SD ¼ 2.9; Table 1). Haplotype frequencies

FIGURE 2.—Hybrid index frequency histogram for Florida bass 3 largemouth bass intergrade populations with three or more

hybrid index levels. Estimates of introgression are based on eight diagnostic loci (6 microsatellites, 2 allozymes). The values

range from 0.0 (individuals with all largemouth bass alleles) to 1.0 (individuals with all Florida bass alleles) via one-allele

increments.

1622 BARTHEL ET AL.

differed between populations in 45% of the pairwise

comparisons.

Introgression

The proportion of individuals with hybrid genotypes

in single populations ranged from 0.0 (all Florida bass)

to 1.0 (Table 1). At the six diagnostic microsatellite

loci, the proportion of largemouth bass alleles ranged

from 0.003 to 0.856 (mean¼ 0.12; SD¼ 0.210) in the

introgressed populations, and the number of overall

alleles per locus was significantly greater in intro-

gressed populations (mean ¼ 7.02 alleles/locus; SD ¼1.08) than in populations of Florida bass (mean¼ 6.31

alleles/locus; SD¼0.95; t-test: t¼�2.381, df¼45, P¼0.0215). At the two diagnostic allozyme loci, the

proportion of largemouth bass alleles ranged from

0.004 to 0.820 (mean ¼ 0.14; SD ¼ 0.220) in

introgressed populations, and the number of overall

alleles per locus was significantly greater in intro-

gressed populations (mean ¼ 1.82 alleles/locus; SD ¼0.180) than in populations of Florida bass (mean¼1.51

alleles/locus; SD¼ 0.08; t-test: t¼�7.482, df¼ 46, P, 0.0001). Mean hybrid index values ranged from

0.109 (indicating a substantial contribution of large-

mouth bass alleles) to 1.000 (indicating that all alleles

were of Florida bass descent; Table 1) for the six

diagnostic microsatellite loci and from 0.179 to 1.000

for the allozyme loci (Table 1). The frequency of

largemouth bass alleles decreased in populations from

west to east and from north to south in both the

microsatellite and allozyme data sets (Figure 1). Six

populations below the southern boundary of the

recognized intergrade zone had largemouth bass alleles

in low frequency at the microsatellite loci (Lake

Lawne, Lake Monroe, Lake George, Lake Kerr,

Rodman Reservoir, and St. Johns River; Table 1),

and 10 populations south of the intergrade zone had

largemouth bass alleles at low frequencies at the two

diagnostic allozyme loci (Lake Trafford, Lake Parker,

Homosassa River, Lake Panasoffkee, Lake Harris,

Lake Lawne, Farm 13 Reservoir, Lake George, Lake

Kerr, and St. Johns River; Table 1). The hybrid index

plots (based on the two diagnostic allozyme loci and

six diagnostic microsatellite loci) were unimodal

(Figure 2). Largemouth bass mtDNA RFLP haplotypes

were resolved for only five fish, most of which were

from the westernmost collection (Escambia River) and

none of which were from populations south of the

intergrade zone (Figure 1). Introgressed and pure

Florida bass collections (defined by nuclear markers)

did not differ in either the number of mtDNA

haplotypes (introgressed mean ¼ 3.74, SD ¼ 1.58;

Florida bass mean¼3.19, SD¼0.75; t-test: t¼�1.467,

df ¼ 46, P ¼ 0.1491) or the number of polymorphic

sites (introgressed mean ¼ 5.41, SD ¼ 3.23; Florida

bass mean ¼ 5.24, SD ¼ 2.59; t-test: t ¼�0.196, df ¼46, P¼ 0.8453).

Genetic Structure

Bayesian analyses using STRUCTURE indicated the

presence of genetic structure based on all three marker

data sets (microsatellites, allozymes, and combined).

Results from the combined data set are presented here.

Likelihood values increased substantially from a K-

value of 1 (mean ¼�41,789.9; SD ¼ 0.765) to a K-

value of 4 (mean ¼ �38,017.7; SD ¼ 24.825) and

plateaued or declined thereafter (Figure 3a). Values of

a (admixture) were minimized at a K of 3 (Figure 3a),

and the profile of DK produced a strong peak at a K-

value of 2 followed by a weaker peak at a K-value of 4

(Figure 3d). Given the presence of a contact zone in

this data set and the possible hierarchical structure, we

evaluated each of the groups defined at a K-value of 2

(individuals assigned by majority q-value to each

group) with independent STRUCTURE runs. Group 1

(consisting of genotypes from southern and eastern

Florida) produced likelihood values that plateaued after

a K-value of 3 and showed a weak optimal peak of DKat a K of 2 (Figure 3b, e). Group 2 (consisting of

genotypes from northern and northwestern Florida)

produced likelihood values that plateaued after a K of 4

and showed a strong optimal DK peak at a K of 2

(Figure 3c, f). Overall, the four resolved groups

produced clusters in (1) south, central-east, and

northeast; (2) central-west; (3) north-central; and (4)

northwest Florida (Figure 4); groups 1 and 2 and

groups 3 and 4 were initially resolved together at a

K of 2.

Individuals were assigned to each of the four

resolved groups in two ways. First, all genotypes were

partitioned at a K-value of 2 (based on majority q-

values) and then partitioned again based on subsequent

runs at a K of 2 within each group. Second, all

genotypes were partitioned at a K of 4 (based on

plurality q-values). Under each scenario, to ease

visualization of the data in a geographic context, qwas averaged within populations and the populations

(rather than individuals) were assigned to groups with

an associated probability (Figure 4). Results were

highly similar using both methods, and we present the

results from the latter method here. The strength of

each group (i.e., mean q-value among all constituents

within a group) ranged from 0.67 (SD ¼ 0.117) in

group 1 to 0.87 (SD ¼ 0.104) in group 4 (group 2:

mean q ¼ 0.68, SD ¼ 0.190; group 3: mean q ¼ 0.77,

SD ¼ 0.170).

Relationships observed in the dendrogram created

from the pairwise genetic distances observed in the


nuclear data set were highly concordant with the

STRUCTURE results (Figure 5a). The populations that

STRUCTURE assigned to the northwest group formed

a distinct cluster in the dendrogram, with the exception

that Lake Talquin, a reservoir that is known to have

been stocked in the past, was included in the grouping

rather than occurring with the collections from the

north-central group. Six of the seven populations from

FIGURE 3.—Likelihood (logeP[D]; mean 6 SD), admixture coefficient (a; mean 6 SD), and number of clusters (K) for

STRUCTURE runs using (a) all Florida bass and largemouth bass genotypes; (b) genotypes from group 1 (southern and eastern

Florida); and (c) genotypes from group 2 (northern and northwestern Florida). P(D) is the probability of the data under each

clustering solution (K). The K-values plotted in relation to DK are shown for (d) all genotypes, (e) group 1 genotypes, and (f)group 2 genotypes. All genotypes were composed of 15 nuclear markers (9 microsatellites, 6 allozymes), and all runs were

performed for K-values of 1–10, with 10 independent replicates.

1624 BARTHEL ET AL.

the St. Johns River drainage (Lake George, Lake Kerr,

Lake Monroe, Rodman Reservoir, St. Johns River, and

Lake Washington; all of which were assigned to the

south–central-east–northeast group by STRUCTURE)

are connected hydrologically and were located near

each other in the dendrogram but did not form a single

cluster. The largest cluster consisted of 15 collections

that were all assigned to the south–central-east–

northeast Florida group based on STRUCTURE

analyses. The last cluster consisted of 13 populations,

12 of which were assigned to the central-west Florida

group and Lake Lawne, another waterbody that is

known to have been stocked in the past, which had

very similar STRUCTURE assignment values for the

central-west group and the south–central-east–north-

east group. The central-west group included a number

of populations from waters that drained to the Gulf of

Mexico, while others drained to the Atlantic Ocean via

the St. Johns River system.

The relationships in the mtDNA RFLP dendrogram

did not correspond to hydrology as strongly as those

identified with the nuclear markers. However, the

majority of populations from north, central, and south

Florida occurred in a separate cluster in the dendro-

gram (Figure 5b), although each cluster also included

populations from the other latitudinal zones. For

example, one cluster consisted of 7 (of 10) populations

from the Kissimmee River and Everglades system

(southern-latitude collections) and two populations

each from the northwest, north-central, central-east,

and central-west regions. One important difference

between the relationships identified by the nuclear and

mtDNA markers is that the populations from the

Kissimmee River and Everglades systems grouped

separately from those of the St. Johns River system in

the mtDNA dendrogram, whereas both had been

assigned to a single group in the STRUCTURE

analysis.

FIGURE 4.—Population genetic structure in four groups resolved by STRUCTURE (K ¼ 4 clusters) based on 15 nuclear

markers (9 microsatellites, 6 allozymes) in Florida bass, largemouth bass, and intergrade populations. Membership coefficients

(q) to each resolved group are averaged within populations (defined in Figure 1) and depicted by pie graphs.


The relationships among haplotypes (based on

shared restriction sites) were depicted in a network

diagram (Figure 6). The six most abundant haplotypes

were found in 91% of individuals; 10 haplotypes were

only observed in one individual each. The most

frequent haplotype (haplotype 1 in Figure 6; present

in 447 of 971 samples) was ubiquitously distributed

throughout the region, although it was lowest in

frequency throughout central Florida and highest in

frequency in southern and northwestern Florida (Figure

6). The second most frequent haplotype (haplotype 2;

present in 219 of 971 samples) differed from haplotype

1 at a single character; haplotype 2 was absent or low

in frequency in southern and northwestern Florida but

FIGURE 5.—Genetic relationships of Florida bass, largemouth bass, and hybrid collections (population codes are defined in

Figure 1) based on (a) Cavalli-Sforza and Edwards (1967) chord distances calculated from the nuclear data set and (b) pairwise

genetic differentiation index (FST

) values calculated from the mitochondrial DNA (mtDNA) restriction fragment length

polymorphism data set. The percentages of bootstrap support are presented for nodes with greater than 50% support (nuclear and

mtDNA dendrograms were based on 1,000 and 300 bootstraps, respectively). The assigned cluster (i.e., groups 1–4) for each

collection based on the optimal solution to the STRUCTURE analysis of the combined nuclear data set is given in parentheses.

1626 BARTHEL ET AL.

was abundant in central Florida along an east–west

transect. Additional haplotypes were found to be

present or abundant over relatively small geographic

regions. For instance, haplotype 3 was concentrated in

north-central Florida, haplotype 7 occurred only

between the Suwannee and Homosassa rivers on the

west coast, and haplotype 13 occurred only near or

within the Everglades system (Table A.3). Haplotype

12, the sole largemouth bass haplotype resolved,

occurred in five samples from collections in northwest

Florida. It was also the most divergent haplotype in the

network, differing by a minimum of eight characters

from the remaining haplotypes.

Analyses of Molecular Variance and Isolation by

Distance

The AMOVAs were used to partition genetic

variation under the geographic group delineation

identified by the STRUCTURE analyses. Separate

AMOVAs were conducted for each of the three data

FIGURE 5.—Continued.


sets (microsatellites, allozymes, and mtDNA RFLPs).

The group delineation partitioned significant portions

of the total genetic variation among groups for all three

data sets (allozyme AMOVA: FCT

[the genetic

variance among groups relative to the total variance]

¼ 0.11, P , 0.001; microsatellite AMOVA: FCT¼

0.07, P , 0.001; mtDNA AMOVA: FCT¼ 0.10, P ,

0.001; Table 2).

Mantel tests identified significant correlations be-

tween genetic and geographic distances across the state

in the allozyme and microsatellite data sets (allozymes:

r¼ 0.3589, P¼ 0.0009; microsatellites: r¼ 0.5832, P

, 0.0001; Table 3) but not in the mtDNA data set (r¼�0.0219, P ¼ 0.5670; Table 3). The microsatellite

markers identified isolation by distance (IBD) within

the central-west group (r¼ 0.6559, P¼0.0299) and the

south–central-east group (r ¼ 0.3542, P ¼ 0.0039).

Significant IBD was not detected within any of the

groups in analyses conducted on the allozyme data set

(Table 3). Analyses of the mtDNA data set identified

IBD within the north-central group (r ¼ 0.3128, P ¼0.0487) and central-west group (r ¼ 0.8876, P ¼0.0082).

Discussion

This study represents the most extensive evaluation

of the genetic relationships among populations of

Florida bass and Florida bass 3 largemouth bass

hybrids within Florida. The detection of largemouth

bass alleles in 12 populations south of the intergrade

zone described by Philipp et al. (1983) could be due to

improved resolution (i.e., more populations sampled,

greater sample sizes per population, and more

diagnostic loci) or to additional hybridization that

might have occurred since the Philipp et al. (1983)

evaluation. Of the 12 hybrid collections located south

FIGURE 6.—Median-joining haplotype network based on mitochondrial DNA restriction fragment length polymorphisms in

971 samples collected from Florida bass, largemouth bass, and intergrade populations. Open nodes are observed haplotypes (H)

sized according to frequency. Closed nodes are inferred haplotypes. Linked nodes represent a single character change, with hatch

marks for each additional change. Selected nodes are labeled with diagrams illustrating their geographic distribution and

intrapopulation frequency (frequency shading: black ¼ 1.0, white¼ 0.0). The only largemouth bass haplotype is H12.

1628 BARTHEL ET AL.

of the intergrade zone, 10 had mean hybrid index

values greater than 0.980, indicating a low frequency of

largemouth bass alleles, which would have had a lower

probability of being detected under the sampling design

of Philipp et al. (1983). Four of the 12 populations (i.e.,

Farm 13 Reservoir, Lake Lawne, Lake Parker, and

Lake Trafford) were located more than 100 km south of

the intergrade zone boundary, which suggests that

stocking is more likely than natural gene flow to be

responsible for the presence of largemouth bass genes.

All four of these populations were in previously

stocked waters, and hatchery reports indicate that

largemouth bass alleles were translocated into Lake

Parker in the 1970s. The other eight hybrid populations

were located closer to the recognized boundary of the

intergrade zone, making natural gene flow a more

plausible explanation. Five of seven collections from

the St. Johns River drainage (i.e., Lake Monroe, Lake

George, Lake Kerr, Rodman Reservoir, and St. Johns

River) were found to be intergrades in this study,

whereas previous studies had not detected largemouth

bass alleles in the St. Johns River system. Largemouth

bass alleles were also detected at low frequencies in

bass sampled from Lake Harris (in the Ocklawaha

River system, central Florida) but not in those sampled

from Lake Dora, which is physically connected to Lake

Harris through a series of canals in the Harris Chain of

Lakes, or among fish sampled in Lake Minneola or

Lake Weir, which are also part of the Ocklawaha River

drainage. The collection from Lake Panasoffkee

contained largemouth bass alleles, whereas those from

nearby Lake Tsala Apopka did not, even though both

lakes are part of the Withlacoochee River system.

Ultimately, the generally low levels of introgression

and the lack of detailed stocking records mean it is not

possible to determine whether the detection of

largemouth bass alleles is the result of stocking or the

improved genetic resolution of the current study,

except for rare cases, such as Lake Parker. Even so,

this study represents a significant update of the hybrid

zone description: from this point forward, (1) the St.

Johns River drainage should be considered an

TABLE 2.—Genetic variation captured by four groups identified in the STRUCTURE analysis of genetic relationships among

Florida bass, largemouth bass, and intergrade populations. The percentage of the genetic variation that was partitioned among

defined groups, among bass populations (pops) within defined groups, and within bass populations by an analysis of molecular

variance conducted with each of three marker data sets is presented. Fixation indices and the percentage of genetically

differentiated and nondifferentiated pairs of populations that occurred in the same group or different groups are also presented for

each data set (number of tests is given in parentheses). The fixation index FST

represents the genetic variance among populations

relative to the total variance, FSC

represents the variance among populations within groups, and FCT

represents the variance

among groups relative to the total variance. Ideally, all nondifferentiated pairs of populations would occur in the same groups,

while all differentiated populations would be in different groups.

Data set

Percentage of variation

Fixation indices

Pairwise genic differentiation tests

Significantly differentiatedpopulations

Not significantlydifferentiated populations

Amonggroups

Among popswithin groups

Withinpops F

STF

SCF

CTSame group Different groups Same group Different groups

Allozymes 11.40 7.37 81.23 0.1877 0.0832 0.1140 15.2 (171) 56.0 (632) 14.9 (168) 13.9 (157)Microsatellites 6.53 5.13 88.35 0.1165 0.0549 0.0653 23.5 (254) 68.5 (741) 7.6 (82) 0.4 (4)Mitochondrial DNA 10.30 24.13 65.56 0.2691 0.3444 0.1030 5.8 (65) 39.6 (447) 25.1 (283) 29.5 (333)

TABLE 3.—Correlation coefficients (r) and P-values from Mantel tests of isolation by distance for each of three genetic marker

data sets describing the genetic relationships among Florida bass, largemouth bass, and intergrade populations. The statewide

analyses included all 48 collections in a single test for each marker data set. The intragroup analyses evaluated the strength of the

correlation among the collections assigned to each group by the STRUCTURE analysis for each marker data set. Asterisks

indicate statistical significance (P , 0.05).

Analysis

Allozymes Microsatellites Mitochondrial DNA

r P r P r P

Statewide 0.3589 0.0009* 0.5832 0.0000* �0.0219 0.5560Groups assigned by STRUCTURE

1. Northwest 0.3463 0.2489 0.5913 0.1220 �0.4017 0.74632. North-central �0.4316 0.9844 0.0045 0.4827 0.3128 0.0487*3. Central-west �0.1310 0.7421 0.6559 0.0299* 0.8876 0.0082*4. South and central-east �0.0105 0.5191 0.3542 0.0039* 0.0171 0.3994


intergrade system, (2) the Ocklawaha River and other

central Florida systems should not be assumed to

contain pure Florida bass populations, and (3) more

generally, geographic distance alone cannot be consid-

ered a reliable indicator of taxonomic status due to the

fact that low-level intergrade populations were detected

in south Florida.

Stocking has been a part of black bass management

in Florida for more than 80 years. Therefore,

evaluations of the current genetic relationships of

Florida bass and largemouth bass in Florida must

consider the potential effect of past stocking practices.

Establishment of a statewide fish hatchery system

consisting of one federal and two state hatcheries began

in 1926. Although stocking of freshwater fishes

occurred before the 1920s, the release of hatchery-

reared fish has been more widespread throughout

Florida since that time. Hatchery records (FWC,

unpublished data) indicate that from 1966 to 2005,

more than 8 million Florida bass cultured at Richloam

State Fish Hatchery (the primary facility) were stocked

into Florida waters. Before the early 1980s, bass were

translocated throughout Florida without consideration

of broodfish origins; this practice could have instigated

an expansion of the intergrade zone. Although there is

no way to definitively determine how these historical

stocking activities altered the natural distribution of

Florida bass and largemouth bass within Florida, there

are at least a few cases (i.e., introgression in south

Florida) that illustrate the effect of stocking, with Lake

Parker providing an example of unintentional genetic

contamination that has occurred in recent decades.

This study found little evidence of nonrandom

mating in the distribution of nuclear alleles in

introgressed populations. None of the collections

showed significant linkage disequilibrium. Only two

of six loci that deviated from HWE in any population

were diagnostic markers, and hybrid index distributions

were unimodal in central regions of the intergrade

zone. Four of the collections from the panhandle region

of Florida (Lake Seminole, Lower Apalachicola River,

Choctawhatchee River, and Escambia River) had

introgressed to the point that none of the sampled

individuals were fixed for Florida bass or largemouth

bass alleles at the diagnostic loci; these populations

exist as hybrid swarms because all or nearly all

individuals in each population are of hybrid origin

(Allendorf et al. 2001). These results are consistent

with a hypothesis of random mating within sampled

populations, a lack of isolating mechanisms in parental

taxa, and very weak (if present at all) disruptive

selection against hybrid genotypes. The apparent

disagreement between these results and previous

experiments reporting that intergrade and nonlocal

individuals had lower survival rates and fitness than did

local fish might be due to biogeographic effects and the

time scales involved. Whereas fish used in the previous

experiments were collected from populations that had

been genetically isolated for millions of years and

originated in environments with reasonably different

climatic conditions, hybridization has been occurring in

the systems of north Florida ever since Florida bass and

largemouth bass came into secondary contact during

the Pleistocene epoch (Near et al. 2003). The hybrid

index distributions indicate that these populations have

passed beyond the early stages of hybridization and

now consist of later-generation hybrids and, in some

systems, individuals from one of the two parental

species and their backcrosses. None of the intergrade

populations included both pure Florida bass and pure

largemouth bass, and some only included hybrids.

Although our results indicate that populations in the

natural hybrid zone may not currently face adverse

consequences from interspecific introgression, these

findings offer little insight into how populations were

affected by hybridization during earlier stages of

introgression. It is entirely possible that there was

selection against hybrids after secondary contact;

however, hybrid swarms could still have developed

as long as hybrid offspring were fertile and could mate

both with each other and with the parental taxa

(Allendorf et al. 2001). Bolnick and Near (2005) found

that hybrid viability declined more slowly in Cen-

trarchidae than in most other taxonomic groups

evaluated to date; those authors concluded that most

speciation events must have resulted from prezygotic

rather than postzygotic isolation. Weak postzygotic

isolating mechanisms would have contributed—and

continue to contribute—to the production of hybrid

progeny when Florida bass and largemouth bass, two

morphologically similar species with nearly identical

reproductive ecology, inhabit the same systems. The

reduced fitness of experimentally introgressed popula-

tions relative to parental taxa (i.e., Philipp and Claussen

1995; Cooke et al. 2001; Philipp et al. 2002; Cooke and

Philipp 2005; Goldberg et al. 2005), which provides

ample evidence of the potential for negative conse-

quences from introgression, should prompt managers

to take steps to avoid additional hybridization events in

the future.

Once foreign genes have been introduced into a

population, it can be extremely difficult and costly to

remove them. One approach that was applied to

introgressed populations of cutthroat trout Oncorhyn-chus clarkii was to poison the fish inhabiting a

waterbody and then to restore the population with

hatchery-produced pure cutthroat trout (Rinne and

Hanson 1981; Allendorf and Leary 1988). The

1630 BARTHEL ET AL.

undesirable aspects of this approach include limited

feasibility for large-scale systems, the high likelihood

that some hybrid individuals will survive, and the

destruction of large numbers of fish, including any

individuals with native genotypes that remained in the

population. A less-invasive approach is to try to reduce

the proportion of foreign genes by aggressively

stocking the native species into the population. This

approach has been used in watersheds inhabited by

Guadalupe bass, which are threatened by introgressive

swamping via breeding with introduced smallmouth

bass. In one case, 2 years of extensive stocking failed

to prevent the loss of pure Guadalupe bass from the

Blanco River (Littrell et al. 2007); however, annual

stocking over a 10-year period appears to have reduced

the proportion of hybrid genotypes in Johnson Creek,

another system where the persistence of Guadalupe

bass has been a conservation concern (Koppelman and

Garrett 2002). The different results in these two cases

are probably due to differences in the magnitude of

introgression at the time the stocking programs began.

The case of the Blanco River provides evidence that

extensive stocking activities will not be able to rescue

an endemic species once introgression has surpassed a

threshold level. It also highlights the fact that stocking

activities can lead to long-term, irreversible genetic

changes in native populations.

In the present study, most introgressed Florida bass

populations south of the natural intergrade zone had

very low frequencies of largemouth bass alleles, and it

is possible that random genetic drift may lead to the

loss of these alleles from some of the populations.

However, the potential for irreversible consequences

should be an important consideration as the new state-

of-the-art fish hatchery at the Florida Bass Conserva-

tion Center in Webster, Florida, heralds a dramatic

increase in the scope and magnitude of bass stocking

practices in the state. Protection of pure Florida bass

populations should be a high priority for black bass

management in Florida. Preventing further introduc-

tions of largemouth bass into populations south of the

natural intergrade zone and avoiding intraspecific

hybridization between genetically divergent popula-

tions of Florida bass will be critical aspects of the long-

term protection of Florida bass.

An interesting finding was that the estimates of

introgression varied widely between the nuclear and

mitochondrial markers. Although some populations

had nearly 90% of their nuclear alleles derived from

largemouth bass, only 5 of 971 fish carried a known

largemouth bass mitochondrial haplotype. Haplotype

12 differed from all other haplotypes at a minimum of

eight nucleotide positions and stood apart from all

other haplotypes in a minimum spanning network.

Kassler et al. (2002) found this haplotype to be fixed

for largemouth bass (using the same region of the

genome and four of the restriction endonucleases

included in this study), and it was the sole haplotype

observed in largemouth bass collected from the Mobile

Delta, Alabama (B. L. Barthel, unpublished data). The

discrepancy between the frequency of haplotype 12

and the frequency of largemouth bass microsatellite

and allozyme alleles (4.9% and 7.2%, respectively)

strongly suggests the possibility of cytonuclear dis-

equilibrium. Due to the low abundance of haplotype

12, a statistical evaluation of suspected cytonuclear

disequilibrium was not possible because of insufficient

statistical power. However, cytonuclear disequilibrium

can result from a number of potential causes (Excoffier

1990; Scribner et al. 2001) and is a common

phenomenon in hybrid zones (Arnold 1993). In this

case, potential causes for the discordance between

largemouth bass nuclear and mitochondrial marker

frequencies include random genetic drift, mating

asymmetry, greatly skewed sex ratios of offspring, or

selection against largemouth bass mitochondrial ge-

nomes. Drift is the least likely explanation because

each population would need to have drifted in the same

direction. Prezygotic isolating mechanisms capable of

producing mating asymmetry include (1) gametic

incompatibility between largemouth bass females and

Florida bass males, (2) assortative mating, and (3)

behavioral, temporal, or spatial differences in repro-

ductive ecology that have resulted in infrequent mating

by female largemouth bass. However, Florida bass

sperm have been documented to fertilize largemouth

bass ova when researchers have physically combined

gametes in the laboratory (Philipp et al. 1985). The two

species have also been documented to hybridize under

natural conditions, producing hybrid progeny in both

experimental ponds and public waterbodies, indicating

that there was spatial and temporal overlap in the

reproductive activity of the species (Isely et al. 1987;

Philipp et al. 2002); however, directionality of these

crosses were not determined. Bolnick and Near (2005)

found that hybrid viability was asymmetrical in nearly

all centrarchid fishes for which reciprocal crosses had

been performed; they proposed cytonuclear interaction

as the most probable explanation, but they were unable

to rule out the direct effects of sex chromosomes or

mitochondria. Experimental studies with fruit flies

Drosophila spp. have documented purifying selection

against maladaptive mtDNA genomes and have shown

that individual fitness may be reduced when nuclear

and cytoplasmic genomes are discordant (reviewed in

Rand 2001). Hybrid inviability, however, appears to

accumulate more slowly in centrarchids than in other

studied taxa, including Drosophila, birds, and anurans


(Bolnick and Near 2005). Further study is required to

identify which of a number of plausible explanations

are responsible for the observed cytonuclear disequi-

librium of introgressed bass populations in Florida

systems. Until then, the genetic composition of

intergrade populations should be considered the natural

condition in the systems of northern Florida, a

geographic region where numerous hybrid zones have

resulted from secondary contact after many of the

southeastern drainages had been isolated by interglacial

periods during the Pliocene (Bermingham and Avise

1986; Swenson and Howard 2005).

The nuclear and mitochondrial markers resolved

somewhat different genetic structure among the black

bass populations sampled in Florida. Nuclear markers

suggest four groups that are located mostly in

accordance with the major hydrologic units of Florida

except that the populations from the St. Johns River

system clustered with those from the Kissimmee River

and Everglades systems. However, although a K of 2

was the optimal solution for the south–central-east–

northeast group, the DK peak was weak; under a K-

value of 3 (the second-highest DK), the collections

from the southern drainages (Kissimmee River and

Everglades systems) and from the northern drainages

were separated into two distinct groups. Relationships

in the mtDNA data set indicated that collections from

the St. Johns River system were differentiated from

those in the southern drainages. This was particularly

evident for haplotype 2, which was abundant in the St.

Johns River system but was absent or found at very low

frequency in the Kissimmee River and Everglades

systems. Although these are discrete drainages, the

nuclear data suggest some gene flow from north to

south, possibly due to intermittent high-water events.

Under this scenario, however, we would expect to see

haplotype 2 at higher frequencies in populations from

the southern drainages. One explanation for the

different patterns resolved with the nuclear and

mitochondrial markers may be differences in the

selective pressures on these sequences. Microsatellites

are considered to be selectively neutral, whereas recent

data suggest that the mitochondrial genome, particu-

larly when in cytonuclear disequilibrium, may be under

strong selective pressures that could alter patterns of

observed gene flow (Datta et al. 1996; Dowling et al.

2008). As a result, selective pressures in the more

tropical Kissimmee River and Everglades region of

Florida may account for the low abundance of

haplotype 2 in the region.

Collections from water bodies that drain into the

Gulf of Mexico and the Atlantic Ocean were

differentiated by nuclear markers, with a few excep-

tions (e.g., Lakes Weir, Minneola, Harris, Dora, and

Norris). This pattern was previously suggested for

Micropterus spp. (Lutz-Carrillo et al. 2006) and has

been documented in other fishes (Wirgin et al. 2002),

turtles (Walker and Avise 1998), and the American

alligator Alligator mississippiensis (Davis et al. 2002);

it is commonly referred to as the Gulf versus Atlantic

division (Avise 1992, 2000). A subset of this pattern, in

which collections from the Lower Apalachicola River

and west formed distinct groups from those collections

to the east, was also resolved. This result is consistent

with genetic discontinuities noted for a number of other

taxa, including the eastern tiger salamander Ambystomatigrinum tigrinum (Church et al. 2003) and some other

centrarchids (Bermingham and Avise 1986). In our

study, the Gulf versus Atlantic division was not

supported in that the four collections from the

Ocklawaha River system (Lakes Weir, Minneola,

Harris, and Dora), which is a tributary of the St. Johns

River, grouped with collections from Gulf coast

drainages. Presently, the Ocklawaha River is the only

one of four rivers with headwaters in the Green

Swamp, central Florida, that drains to the Atlantic

Ocean (the Hillsborough, Peace, and Withlacoochee

rivers all drain to the Gulf of Mexico); an electropho-

retic study found that sheepshead minnow Cyprinodonvariegatus collected from lakes in the Ocklawaha River

system shared genetic similarities to populations from

both the Gulf of Mexico and Atlantic drainages

(Duggins et al. 1983). In the present study, there was

no Gulf versus Atlantic division apparent in the

relationships for the mtDNA data set, even though

mitochondrial markers were used in most of the work

that previously suggested the existence of such a

division (Avise 1992; Soltis et al. 2006). The nuclear

and mtDNA results indicate that there has been gene

flow between populations inhabiting Gulf of Mexico

and Atlantic drainages and that the Ocklawaha River

system, central Florida, is one place where the Gulf

versus Atlantic division has broken down at least once

in the past.

Recently, the FWC has instituted a number of

policies and procedures to protect the genetic integrity

of Florida bass populations in Florida. First, they have

developed and adopted a comprehensive genetics

policy that sets forth guidelines and policy standards

designed to protect populations of freshwater and

marine finfishes from adverse consequences resulting

from the release of cultured fishes, including the

promotion of fish hatchery protocols that minimize the

potential for inbreeding and domestication (Tringali et

al. 2007). Second, the FWC has designated five regions

as black bass genetic management units (MUs); the

regions are based on the results of the present study and

include the northwest, north-central, central-west,

1632 BARTHEL ET AL.

south, and central-east–northeast groups (the south–

central-east–northeast group from the STRUCTURE

analyses has been split due to the mtDNA differences

between collections from the St. Johns River system

and Everglades drainage). State and federal stocking

programs are prohibited from translocating bass

between MUs; this ensures that hatchery-reared fish

are released into waterbodies in the same MU from

which their parents were collected (with the exception

of a long-term research project conducted on Lake

Talquin). Prohibiting intergroup transfers is expected to

prevent the most severe outcrossing; however, it is

possible that outbreeding depression could result from

crosses between individuals from populations that

occur within the same group. Each group consists of

populations that tend to be more genetically similar to

each other than to populations in another group.

However, depending on the data set, between 6% and

24% of genetically differentiated population pairs

occurred within the same group. To that end, the

FWC considers special measures for more divergent

populations. For example, the isolated location and

unique characteristics of the St. Mary’s River have led

managers to release only the progeny of broodstock

collected from the St. Mary’s River during a recent

stock enhancement project. More general safeguards

include routine genetic testing to ensure that every

hatchery-reared fish stocked into peninsular water

bodies are pure Florida bass. The FWC is currently

implementing a number of approaches to prevent

private fish dealers from transporting largemouth bass

and largemouth bass hybrids into the Florida peninsula.

These recent steps to incorporate genetic conservation

principles into black bass management in Florida

represent a comprehensive approach to the long-term

conservation of black bass populations throughout the

state, with special concern for the endemic Florida

bass.

Acknowledgments

This project was partially funded by the Wildlife

Foundation of Florida, the Texas Parks and Wildlife

Foundation, and Federal Aid in Sport Fish Restoration

Program Grant F101 to the TPWD. The authors are

grateful for the expert field and laboratory assistance of

Andy Strickland, Gina Delpizzo, Holly Alred, Rich

Cailteux, and Steve Crawford of FWC and Olivia

Dorothy of INHS. Llyn French (FWC) provided

assistance with the production of figures. We also

thank Jim Estes and Jason Dotson from the Florida

Fish and Wildlife Research Institute and Loraine Fries

from the TPWD for providing helpful comments that

improved the quality of the manuscript. A.M.R. was

supported by a Jonathan Baldwin Turner Undergrad-

uate Research Grant and the Environmental and

Special Undergraduate Research on the Environment

Grant.

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1636 BARTHEL ET AL.

Appendix. Location and Genetic Data for Bass Collections in Florida

TABLE A.1.—Locations of the 48 populations of Florida bass, largemouth bass, and hybrids included in this study.

Collection (code) County Latitude Longitude

1. Nine Mile Pond (Nine) Monroe 25815015 00 �80847053 00

2. Tamiami Canal (Tami) Dade 25845046 00 �80840052 00

3. Conservation Area 3 (Con3) Broward 2688056 00 �8084308 00

4. Lake Trafford (Traf) Collier 26825058 00 �81828059 00

5. Lake Okeechobee (Okee) Multiple 26841055 00 �80845038 00

6. Lake Istokpoga (Isto) Highlands 27822026 00 �8181506 00

7. Lake Weohyakapka (Weoh) Polk 27848048 00 �81824049 00

8. East Lake Tohopekaliga (Toho) Osceola 28816026 00 �8181704 00

9. Lake Down (Down) Orange 28830024 00 �81831052 00

10. Conway Chain (Conw) Orange 28828055 00 �81821010 00

11. Peace River (Peac) Multiple 2783307 00 �81847039 00

12. Medard Reservoir (Meda) Hillsborough 2785502 00 �8289039 00

13. Hillsborough River (Hill) Hillsborough 2883018 00 �82821053 00

14. Lake Tarpon (Tarp) Pinellas 2885011 00 �8284304 00

15. Lake Parker (Park) Polk 288400 00 �81855052 00

16. Lake Shipp (Ship) Polk 2880012 00 �81844036 00

17. Homosassa River (Homo) Citrus 28847059 00 �82835022 00

18. Lake Tsala Apopka (Tsal) Citrus 2885001 00 �8281904 00

19. Lake Panasoffkee (Pana) Sumter 28847024 00 �8286039 00

20. Lake Weir (Weir) Marion 2981024 00 �81855033 00

21. Lake Minneola (Minn) Lake 28833030 00 �81846021 00

22. Lake Harris (Harr) Lake 28843018 00 �81845025 00

23. Lake Dora (Dora) Lake 28851010 00 �81841027 00

24. Lake Lawne (Lawn) Orange 28833056 00 �81826027 00

25. Farm 13 Reservoir (Farm) Brevard 27847057 00 �80842033 00

26. Lake Washington (Wash) Brevard 2888051 00 �8084404 00

27. Lake Monroe (Monr) Volusia/Seminole 2885050 00 �8181905 00

28. Lake Norris (Norr) Lake 28855041 00 �81832051 00

29. Lake George (Geor) Lake/Volusia 2981205 00 �81834040 00

30. Lake Kerr (Kerr) Marion 29821020 00 �81848046 00

31. Lochloosa Lake (Loch) Alachua 29830030 00 �8286043 00

32. Rodman Reservoir (Rodm) Marion/Putnam 29830058 00 �81848043 00

33. Kingsley Lake (King) Clay 29857054 00 �81859040 00

34. St. Johns River (Green Cove) (StJo) Duval 2985408 00 �81837039 00

35. Ocean Pond (Ocea) Baker 30813030 00 �8282601 00

36. Lake Santa Fe (Sant) Alachua 29844033 00 �8284037 00

37. Lake Sampson (Samp) Bradford 29855030 00 �8281200 00

38. Waccasassa River (Wacc) Levy 29812047 00 �82845048 00

39. Suwannee River (Suwa) Multiple 29823045 00 �8381033 00

40. Steinhatchee River (Stei) Taylor/ Dixie 29842028 00 �8382104 00

41. Cherry Lake (Cher) Madison 30836056 00 �83824053 00

42. Aucilla River (Auci) Multiple 3088047 00 �83858021 00

43. Lake Jackson (Jack) Leon 30831056 00 �84819044 00

44. Lake Talquin (Talq) Gadsen/Leon 30827030 00 �84829039 00

45. Lake Seminole (Semi) Jackson 30843060 00 �8485500 00

46. Lower Apalachicola River (Apal) Gulf/Franklin 29845036 00 �8581024 00

47. Choctawhatchee River (Choc) Multiple 3082704 00 �85853055 00

48. Escambia River (Esca) Escambia/Santa Rosa 3083309 00 �8787030 00


TABLE A.2.—Number of alleles per locus (NA), observed heterozygosity (H

O), and adherence to Hardy–Weinberg equilibrium

(PHWE

) for 48 Florida bass, largemouth bass, and intergrade populations from Florida. Location codes are provided in Table 1.

Asterisks next to PHWE

values indicate statistically significant deviation from Hardy–Weinberg expectations after Bonferroni

correction (na ¼ not applicable).

Locus Nine Tami Con3 Traf Okee Isto Weoh Toho Down Conw Peac Meda Hill Tarp Park Ship

AAT-A* NA

2 na 2 2 2 2 2 2 2 2 2 2 2 2 2 2H

O0.167 0.350 0.250 0.150 0.067 0.083 0.183 0.017 0.083 0.217 0.034 0.333 0.067 0.150 0.083

PHWE

1.000 0.184 1.000 1.000 1.000 1.000 1.000 na 0.169 1.000 1.000 0.717 1.000 1.000 1.000AAT-B* N

A2 2 2 3 2 2 2 2 2 2 2 2 2 2 3 2

HO

0.550 0.509 0.450 0.583 0.483 0.517 0.483 0.467 0.517 0.633 0.633 0.390 0.383 0.500 0.367 0.450P

HWE0.423 0.791 1.000 0.591 0.380 1.000 1.000 1.000 0.797 0.037 0.041 0.115 0.258 0.788 0.209 0.754

IDH-B* NA

1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1H

O0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.033 0.000

PHWE

na na na na na na na na na na na na na na 1.000 naMDH-A* N

A1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1

HO

0.000 0.000 0.000 0.000 0.000 0.000 0.067 0.017 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000P

HWEna na na na na na 1.000 1.000 na na na na na na na na

MDH-B* NA

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1H

O0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

PHWE

na na na na na na na na na na na na na na na naSOD-A* N

A2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

HO

0.367 0.542 0.450 0.722 0.517 0.100 0.533 0.583 0.350 0.283 0.433 0.254 0.517 0.450 0.417 0.267P

HWE0.100 0.602 0.598 0.017 1.000 0.000* 0.256 0.300 0.220 0.256 1.000 0.201 0.139 0.443 1.000 0.065

Lma12 NA

4 4 4 4 3 5 3 4 4 4 3 3 3 3 5 4H

O0.607 0.577 0.567 0.500 0.467 0.567 0.593 0.571 0.333 0.467 0.464 0.267 0.133 0.200 0.552 0.345

PHWE

0.939 0.859 0.949 0.892 0.517 0.823 0.511 0.500 0.303 0.656 0.615 0.023 0.006 0.154 0.154 0.516Mdo3 N

A4 4 3 4 3 4 3 4 3 5 4 4 4 7 3 4

HO

0.276 0.467 0.300 0.567 0.433 0.571 0.533 0.667 0.633 0.600 0.517 0.600 0.517 0.733 0.633 0.630P

HWE0.006 0.701 0.155 0.123 0.338 0.786 0.797 0.506 0.229 0.060 0.400 0.523 0.378 0.203 0.585 0.441

Mdo6 NA

3 3 4 2 3 3 2 1 1 2 2 1 1 4 2 3H

O0.179 0.300 0.267 0.200 0.200 0.103 0.069 0.000 0.000 0.033 0.035 0.000 0.000 0.333 0.100 0.148

PHWE

0.045 1.000 1.000 1.000 1.000 0.014 1.000 na na na na na na 1.000 1.000 0.077Mdo7 N

A3 3 2 2 3 2 3 2 2 2 2 2 2 2 3 2

HO

0.111 0.138 0.033 0.067 0.200 0.100 0.077 0.074 0.036 0.067 0.333 0.379 0.182 0.111 0.345 0.250P

HWE1.000 0.032 0.051 0.101 0.133 0.165 0.116 1.000 1.000 1.000 0.633 0.419 1.000 0.183 1.000 1.000

Msa13 NA

4 3 4 4 4 4 6 4 4 4 5 5 2 4 4 5H

O0.483 0.433 0.500 0.633 0.533 0.435 0.370 0.400 0.393 0.267 0.379 0.348 0.037 0.233 0.167 0.539

PHWE

1.000 0.079 0.727 0.475 0.927 0.141 0.726 1.000 0.133 0.591 0.295 0.357 1.000 0.022 0.071 1.000Msa21 N

A3 4 5 4 4 4 3 4 2 2 3 3 4 4 4 4

HO

0.593 0.483 0.500 0.533 0.567 0.379 0.375 0.586 0.536 0.500 0.200 0.667 0.480 0.467 0.690 0.517P

HWE0.849 0.280 0.024 0.204 0.115 0.045 0.177 0.731 0.708 1.000 1.000 0.540 0.239 0.569 0.475 0.767

Msa29 NA

2 2 2 2 2 3 2 2 2 2 2 2 3 3 3 2H

O0.292 0.423 0.567 0.233 0.267 0.400 0.423 0.536 0.375 0.103 0.370 0.313 0.421 0.522 0.346 0.400

PHWE

1.000 1.000 0.200 1.000 1.000 1.000 1.000 0.690 0.390 0.032 0.406 0.530 0.325 1.000 0.051 0.663MiSaTPW60 N

A22 22 20 19 20 24 16 19 12 11 20 13 11 22 22 19

HO

0.846 1.000 0.933 0.808 0.933 0.926 0.783 0.833 0.810 0.611 0.815 0.958 0.818 0.926 0.893 0.857P

HWE0.333 0.693 0.633 0.102 0.876 0.980 0.010 0.206 0.694 0.056 0.168 0.979 0.261 0.728 0.157 0.829

MiSaTPW70 NA

20 20 16 22 19 12 16 17 10 13 17 18 14 21 26 23H

O0.852 0.731 0.733 0.862 0.833 0.611 0.882 0.786 0.640 0.828 0.759 0.833 0.654 0.840 0.828 0.833

PHWE

0.060 0.023 0.145 0.103 0.311 0.031 0.853 0.001 0.005 0.611 0.360 0.824 0.131 0.268 0.035 0.185

1638 BARTHEL ET AL.

TABLE A.2.—Extended.

Locus Hom Tsal Pana Weir Minn Harr Dora Lawn Farm Wash Monr Norr Geor Kerr Loch Rodm

AAT-A* 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 20.067 0.533 0.383 0.267 0.383 0.050 0.083 0.167 0.150 0.200 0.233 0.000 0.150 0.100 0.133 0.2001.000 0.157 0.258 0.579 1.000 1.000 0.169 1.000 1.000 1.000 1.000 Na 1.000 1.000 1.000 0.577

AAT-B* 2 2 2 2 2 2 2 2 2 2 2 2 3 3 2 20.300 0.333 0.250 0.683 0.500 0.117 0.217 0.567 0.467 0.500 0.483 0.317 0.567 0.683 0.150 0.5000.443 0.670 0.626 0.009 1.000 1.000 0.319 0.436 1.000 1.000 1.000 0.330 0.510 0.001 1.000 0.398

IDH-B* 3 2 2 1 1 2 1 2 2 1 1 1 1 1 2 10.450 0.033 0.067 0.000 0.000 0.033 0.000 0.050 0.017 0.000 0.000 0.000 0.000 0.000 0.050 0.0000.019 1.000 1.000 na na 1.000 na 1.000 1.000 na na na na na 1.000 na

MDH-A* 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 20.000 0.000 0.000 0.000 0.000 0.017 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.017

na na na na na 1.000 na na na na na na na na na 1.000MDH-B* 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1

0.133 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.033 0.000 0.000 0.000 0.000 0.0001.000 na na na na na na na na na 1.000 na na na na na

SOD-A* 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 20.467 0.483 0.567 0.383 0.567 0.367 0.267 0.533 0.467 0.433 0.300 0.433 0.483 0.150 0.383 0.4171.000 1.000 0.435 0.543 0.163 1.000 0.221 0.259 1.000 1.000 0.162 1.000 0.380 0.396 0.544 1.000

Lma12 3 6 4 5 4 5 4 4 4 4 5 4 3 3 4 40.100 0.500 0.379 0.567 0.300 0.586 0.539 0.567 0.500 0.433 0.448 0.250 0.367 0.600 0.400 0.4140.165 0.415 0.758 0.005 0.253 0.197 0.737 0.912 1.000 0.381 0.623 0.025 1.000 1.000 0.810 0.233

Mdo3 4 3 4 3 3 3 3 3 4 4 4 4 7 4 6 50.467 0.600 0.724 0.700 0.533 0.767 0.828 0.767 0.633 0.600 0.567 0.600 0.700 0.633 0.533 0.7670.238 1.000 0.616 0.081 0.405 0.564 0.038 0.488 0.338 0.556 0.482 0.464 0.100 0.458 0.116 0.084

Mdo6 2 1 1 1 1 2 1 3 2 2 2 1 3 3 3 30.033 0.000 0.000 0.000 0.000 0.067 0.000 0.138 0.067 0.133 0.100 0.000 0.200 0.133 0.033 0.100

na na na na na 1.000 na 0.072 1.000 1.000 1.000 na 1.000 1.000 0.015 1.000Mdo7 2 2 3 2 2 2 2 2 3 3 3 2 3 2 2 2

0.400 0.367 0.286 0.233 0.533 0.250 0.044 0.100 0.133 0.233 0.310 0.039 0.133 0.148 0.100 0.1381.000 0.418 0.064 0.102 0.218 1.000 1.000 1.000 1.000 0.226 1.000 1.000 0.031 1.000 1.000 1.000

Msa13 3 4 5 4 3 3 3 3 5 3 3 4 3 3 5 40.138 0.100 0.172 0.267 0.100 0.233 0.333 0.393 0.400 0.500 0.300 0.423 0.367 0.621 0.567 0.4331.000 1.000 0.330 0.509 1.000 0.136 1.000 0.020 0.271 0.253 0.019 0.846 0.075 0.917 0.620 0.025

Msa21 5 4 4 3 4 4 4 5 3 4 5 5 6 4 5 40.600 0.633 0.483 0.500 0.733 0.667 0.792 0.500 0.500 0.500 0.600 0.680 0.567 0.500 0.633 0.5000.901 0.419 0.016 0.430 0.557 0.356 0.121 0.689 0.140 0.535 0.952 0.903 0.940 0.032 0.382 0.051

Msa29 3 4 4 2 2 3 3 4 3 3 2 5 5 2 2 30.222 0.533 0.448 0.433 0.435 0.536 0.455 0.348 0.400 0.467 0.467 0.370 0.552 0.464 0.400 0.4000.340 0.215 0.061 1.000 1.000 0.508 0.152 0.008 0.431 0.848 0.637 0.404 0.002 1.000 1.000 0.670

MiSaTPW60 13 19 26 18 14 22 26 20 19 24 21 16 22 18 22 260.767 0.923 0.897 0.846 0.900 0.917 0.889 0.808 0.846 0.926 0.905 0.690 0.828 0.920 0.852 0.9670.219 0.876 0.386 0.276 0.972 0.247 0.152 0.306 0.194 0.423 0.306 0.059 0.303 0.916 0.150 0.518

MiSaTPW70 18 24 24 16 17 19 15 14 21 18 17 13 26 18 11 210.862 0.800 0.889 0.862 0.900 0.933 0.667 0.640 0.759 0.556 0.667 0.727 0.933 0.808 0.793 0.7600.773 0.000* 0.849 0.729 0.859 0.941 0.116 0.094 0.161 0.000 0.004 0.094 0.631 0.264 0.359 0.019


TABLE A.2.—Extended.

Locus King StJo Ocea Sant Samp Wacc Suwa Stei Cher Auci Jack Talq Semi Apal Choc Esca

AAT-A* 2 2 2 2 2 2 1 1 1 2 2 2 1 2 3 20.083 0.067 0.050 0.300 0.017 0.050 0.000 0.000 0.000 0.065 0.117 0.017 0.000 0.117 0.217 0.0331.000 1.000 1.000 0.332 1.000 1.000 Na na na 1.000 1.000 1.000 na 1.000 1.000 1.000

AAT-B* 2 3 3 2 3 3 3 2 4 3 3 3 4 3 4 40.417 0.550 0.517 0.533 0.533 0.467 0.583 0.383 0.533 0.226 0.600 0.733 0.617 0.367 0.400 0.5331.000 0.277 0.007 0.796 0.888 0.772 0.524 0.543 0.010 0.010 0.281 0.784 0.935 0.891 0.772 0.018

IDH-B* 1 1 2 2 2 2 2 2 1 2 2 2 2 2 2 20.000 0.000 0.433 0.300 0.217 0.033 0.050 0.083 0.000 0.129 0.153 0.417 0.483 0.367 0.433 0.200

na na 0.756 0.442 1.000 1.000 1.000 1.000 na 0.055 1.000 0.412 0.561 0.4280 0.429 1.000MDH-A* 1 1 2 1 1 1 1 1 1 1 2 2 2 2 2 1

0.000 0.000 0.067 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.117 0.117 0.283 0.483 0.050 0.000na na 1.000 na na na na na na na 1.000 1.000 0.429 0.014 1.000 na

MDH-B* 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 10.000 0.000 0.000 0.000 0.000 0.017 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

na na na na na 1.000 na na na na na na na na na naSOD-A* 2 2 2 2 2 2 2 2 2 2 na na 2 2 2 2

0.400 0.417 0.317 0.483 0.383 0.533 0.467 0.517 0.367 0.387 0.333 0.417 0.200 0.1000.558 0.414 0.703 0.784 0.543 0.402 1.000 1.000 0.241 0.679 1.000 0.208 0.110 1.000

Lma12 3 4 3 4 3 3 3 2 4 3 na 3 4 3 4 30.600 0.467 0.533 0.690 0.400 0.567 0.357 0.567 0.600 0.296 0.250 0.414 0.241 0.600 0.4140.373 0.454 1.000 1.000 0.479 0.133 1.000 0.711 0.816 0.234 1.000 0.090 0.037 0.281 0.348

Mdo3 3 6 4 6 4 5 3 2 3 5 na 5 5 7 7 60.633 0.567 0.467 0.700 0.700 0.567 0.172 0.367 0.367 0.724 0.833 0.759 0.833 0.633 0.2000.181 0.577 0.060 0.242 0.431 0.434 0.165 1.000 0.352 0.966 0.232 0.432 0.796 0.136 0.037

Mdo6 1 2 2 4 3 3 3 3 4 5 na 3 4 5 5 40.000 0.100 0.267 0.233 0.172 0.133 0.286 0.333 0.233 0.333 0.133 0.750 0.633 0.600 0.400

na 1.000 0.306 0.010 0.101 1.000 0.157 0.103 0.027 0.006 0.032 0.769 0.038 0.901 0.619Mdo7 2 3 3 1 1 4 2 1 1 1 na 3 2 1 4 4

0.179 0.333 0.200 0.000 0.000 0.143 0.042 0.000 0.000 0.000 0.179 0.035 0.000 0.467 0.5191.000 1.000 1.000 Na Na 1.000 1.000 na na na 1.000 1.000 Na 0.565 0.408

Msa13 3 6 4 6 5 4 7 4 3 4 na 4 8 4 8 60.400 0.393 0.433 0.733 0.483 0.250 0.360 0.172 0.267 0.464 0.567 0.759 0.679 0.667 0.3930.368 0.176 0.411 0.589 0.327 0.532 0.163 0.002 1.000 0.379 0.194 0.571 0.509 0.778 0.017

Msa21 2 4 4 5 5 5 5 5 3 6 na 5 6 5 6 40.633 0.483 0.533 0.393 0.414 0.192 0.480 0.464 0.667 0.586 0.621 0.571 0.593 0.733 0.1380.271 0.828 1.000 0.484 0.014 0.001* 0.004 0.002 0.498 0.019 0.488 0.167 0.193 0.854 1.000

Msa29 2 3 2 2 2 3 2 2 3 3 na 4 5 5 6 40.267 0.647 0.100 0.185 0.207 0.077 0.231 0.440 0.300 0.519 0.448 0.462 0.526 0.536 0.5420.306 0.325 0.164 1.000 0.427 0.058 1.000 0.687 1.000 0.761 0.473 0.008 0.874 0.281 0.241

MiSaTPW60 16 23 14 23 19 18 25 13 12 20 na 26 20 15 19 181.000 0.897 0.833 0.933 0.963 0.800 0.833 0.652 0.862 0.880 0.933 0.958 0.938 0.900 0.7920.832 0.074 0.180 0.273 0.697 0.178 0.059 0.000* 0.205 0.217 0.773 0.173 0.557 0.227 0.050

MiSaTPW70 14 18 9 16 22 15 18 9 14 16 na 17 17 14 21 170.815 0.852 0.467 0.759 0.821 0.522 0.786 0.857 0.700 0.964 0.778 0.929 0.870 0.759 0.8890.058 0.156 0.027 0.142 0.013 0.007 0.091 0.904 0.067 0.530 0.237 0.073 0.653 0.000* 0.698

1640 BARTHEL ET AL.

TABLE A.3.—Number of individuals with each of the 25 mitochondrial DNA restriction fragment length polymorphism

haplotypes and the sample size (N) for each of 48 Florida bass, largemouth bass, and intergrade populations from Florida. The

letters in the haplotype descriptions represent different banding patterns observed when the amplified DNA segment was

digested with different endonucleases. For example, seven distinct banding patterns were observed for Dde I (B, G, R, S, T, U,

and V). Location codes are defined in Table 1.

Restrictionendonucleaseor collection

Haplotype

N1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Haplotype description

Dde I B B S B U S B V B V S G T R U V S V B S B B B R VDpn II G G G G L L G G G G G A L G G G L L G G G L M G GHae III C C S C C S R T C R C R S R C C C C C S R C C C CHha I A A A A A A A A J A A A A A A A A A B A A A A A AMsp I C B C C C C C C B C C A C B C C C C C C C C C B CRsa I A A A I A A A A A A A A A A A A A A A I I A A A I

Number of individuals with haplotype

Nine 18 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 20Tami 18 3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 22Con3 19 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21Traf 10 7 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21Okee 17 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 20Isto 17 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 20Weoh 19 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21Toho 19 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Down 8 1 0 1 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Conw 15 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Peac 15 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Meda 9 8 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21Hill 11 4 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Tarp 9 10 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22Park 7 8 0 3 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 21Ship 13 4 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Homo 2 6 0 0 1 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Tsala 5 13 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Pana 4 7 0 0 0 0 2 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Weir 1 16 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Minn 7 11 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 20Harr 0 18 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Dora 2 14 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Lawn 14 4 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Farm 12 5 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Wash 9 5 0 4 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Monr 9 7 0 0 0 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Norr 6 11 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Geor 10 9 0 1 0 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 24Kerr 4 15 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Loch 0 1 18 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Rodm 3 5 3 3 0 2 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 1 20King 9 5 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 20StJo 7 9 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Ocea 18 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Sant 10 0 1 1 11 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 24Samp 4 0 6 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 20Wacc 1 0 18 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21Suwa 5 0 0 0 4 0 5 0 0 5 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 20Stei 0 0 1 0 11 0 0 7 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 20Cher 0 0 19 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Auci 0 1 0 8 10 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22Jack 3 0 0 16 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 1 0 0 0 0 22Talq 2 1 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6Semi 18 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 20Apal 19 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20Choc 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23Esca 16 0 0 1 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 20Total N 447 219 68 59 51 43 20 14 13 7 5 5 4 3 3 1 1 1 1 1 1 1 1 1 1 971


Documents

Genetic relationships among populations of Florida bass