34 th Annual Meeting New England Association of Environmental Biologists 31st Annual Meeting Hotel...
Preview:
Citation preview
- Slide 1
- 34 th Annual Meeting New England Association of Environmental
Biologists 31st Annual Meeting Hotel Viking Newport, RI March 19,
2010 1
- Slide 2
- Application of the Index of Biotic Similarity (B) to the
Analysis of the Data Generated Carlos F. A. Pinkham Declan J.
McCabe Biology Department Biology Department Norwich University St
Michaels College Northfield, VT Colchester, VT Farley Brown
Johnathon L. Miller Sterling College Formerly of Craftsbury
Commons, VT Geology Department Norwich University 2 by the
- Slide 3
- Outline Vermont Streams Project Index of Biotic Similarity,
BioSim2, & the statistical test Results Conclusions 3
- Slide 4
- Outline Vermont Streams Project Concept Participants Drainage
Basins in the Project Macroinvertebrate Techniques 4
- Slide 5
- The Streams Project is a collaborative effort involving
Universities, Colleges, VT DEC, and high schools, managed by VT
EPSCoR (Experimental Programs to Stimulate Competitive Research).
It is dedicated to collecting high-quality data on streams in the
Champlain basin while training the next generation of scientists.
Ultimately this database will be instrumental in understanding
watershed dynamics around the state. Vermont Streams Project
Concept 5
- Slide 6
- Vermont Streams Project Participants 6
- Slide 7
- Vermont Streams Project 2008, College Baseline Study: 33 sites
6 drainage basins 7
- Slide 8
- Collected in summer-early fall (June & July up to October)
Collected from representative locations in a riffle in the stream
Substrate in an area about 1 square meter upstream of a 500 micron
mesh D-net is thoroughly disturbed by hand Four replicates
collected each replicate lasting about 30 seconds Replicates
preserved individually in 75% alcohol Vermont Streams Project
Macroinvertebrate Techniques Sampling 8
- Slide 9
- 1)Sample is washed and spread evenly over a white, gridded tray
with 16 squares. 2)Starting with random grid, it and the next 3
consecutive squares are picked clean of macroinvertebrates using a
3 diopter magnifying headset and separate light. 3)Process is
continued if necessary until 300 organisms are picked. 4)Total
number of squares picked is recorded. 5)Picked macroinvertebrates
are preserved in 75% alcohol. 6)Macroinvertebrates are identified
to genus, except Oligochaetes and Chironomids (Family). Vermont
Streams Project Macroinvertebrate Techniques Processing 9
- Slide 10
- Outline Index of Biotic Similarity, BioSim2, & the
Statistical Test Brief Review What is a Sector? Statistically Valid
Sectors 10
- Slide 11
- Index of Biotic Similarity, BioSim2, & the Statistical Test
(Pinkham-Pearson Index) Brief Review Barbour et al. (1992) in a
systematic comparison of the metrics proposed in EPA's rapid
bioassessment protocol (Pfalkin et al., 1989), concluded that B
"may be the most appropriate metric to serve as a measure of
community similarity." 11
- Slide 12
- Index of Biotic Similarity, BioSim2, & the Statistical Test
Brief Review 12
- Slide 13
- Brief Review Matrix of Bs Between 11 Parameters Index of Biotic
Similarity, BioSim2, & the Statistical Test 13
- Slide 14
- Site Dendrogram Index of Biotic Similarity, BioSim2, & the
Statistical Test Brief Review 14
- Slide 15
- Taxa Dendrogram Index of Biotic Similarity, BioSim2, & the
Statistical Test Brief Review 15
- Slide 16
- What is a Sector? Index of Biotic Similarity, BioSim2, &
the Statistical Test 16
- Slide 17
- Assumptions The measurements in each site are independent The %
composition of taxa follow a normal distribution Independent Index
of Biotic Similarity, BioSim2, & the Statistical Test
Statistically Valid Sectors 17
- Slide 18
- Calculations Index of Biotic Similarity, BioSim2, & the
Statistical Test Statistically Valid Sectors 18
- Slide 19
- Calculations H o : There is a not a significant difference
between the percent compositions of taxa in the sites making up
Sector 1 & Sector 2. H a : There is a significant difference
between the percent compositions of taxa in the sites making up
Sector 1 & Sector 2. Given H o is true then The p-value is
calculated using the chi-square distribution. Index of Biotic
Similarity, BioSim2, & the Statistical Test Statistically Valid
Sectors 19
- Slide 20
- Outline Results Original Macroinvertebrate Data Matrix
Macroinvertebrate % Composition Data Statistically Valid Sector
Analysis Abundance Values for Each Sector 20
- Slide 21
- 208 taxa collected at 33 sites comprising 24, 677 organisms
compressed to 83 taxa at 33 sites comprising 23,987 organisms
(
- These 83 taxa at 33 sites comprising 23,987 organisms further
compressed to 65 taxa at 33 sites by eliminating those taxa with a
sum of their % compositions over all sites that did not exceed 4%.
23,454 organisms remained (>95% of the original) Results
Macroinvertebrate % Composition Data 22
- Slide 23
- AI-Ple-Pero-Isop AI-Eph-Hep-Rhi AI-Eph-Bae-Acen AI-Tri-Hyds-Che
AI-Eph-Ephi-Eph AI-Tri-Hyds-Pot-f AI-Ple-Pero AI-Cole-Elm-Ord-n
AI-Tri-Phi-Dol AI-Cole-Elm AI-Eph-Ephe-Ser AI-Eph-Ephe
AI-Tri-Hel-Hel AI-Ple-Peri AI-Eph-Lepp-Par AI-Eph-Bae-Pse
AI-Eph-Bae-Fal AI-Dip-Tab AC-Iso-Ase-Lir-l AI-Ple-Pte-Pte
AI-Tri-Glo-Aga AI-Ple-Chl-All AI-Tri-Rhy-Rhy AI-Ple-Leu-Leu
AI-Eph-Ephe-Eph AI-Eph-Bae-Acer AI-Ple-Cap-Cap AI-Eph-Sip-Par
AI-Ple-Cap-Nem-c AI-Ple AI-Eph-Hep-Hep AI-Tri-Glo-Glo
AI-Eph-Lepp-Lep AI-Meg-Cor-Nig AI-Tri-Bra-Bra AI-Eph-Hep
AI-Dip-Tip-Ped AI-Cole-Pse-Pse AI-Eph-Hep-Epe AI-Eph-Ephe-Dru
AI-Ple-Peri-Neo AI-Dip-Tip MG-Pul-Lym AC-Amp-Cra-Cra
AI-Cole-Dyt-Dyts AI-Tri-Hyds-Hyd AI-Tri-Hyds AI-Tri AI-Tri-Hyds-Cer
AI-Tri-Hyds-Arc AI-Tri-Uen-Neo AI-Dip-Tip-Ant AI-Eph-Bae
AI-Tri-Phi-Chi AI-Eph-Bae-Bae AI-Dip-Cer A AI-Eph AI-Dip-Nym-Nym
AI-Dip AI-Cole-Elm-Opt AC-Oli AI-Dip-Sim AI-Dip-Chi AI-Cole-Elm-Ste
MB_BiR_76_081 0.41 0.5 12.8 0.930.420.2 2.5 335.915.6 MB_ER_47_081
10.80.2 0.60.5 40.2 0.72.90.447.10.6 MB_PD_48_081-A 0.2 7
0.30.62.37.6 0.50.2 20.30.72.93.89.336.7 MB_R7_46_081 0.9 0.50.72
0.2 0.5 3.70.70.20.527.40.59.660.92.6 MB_BrR_114_081 0.2 0.5 0.2
0.5 0.72.30.93.70.9 3.23.40.412.32.54.83.90.5377.1 MB_ByR_42_081
0.6 4.9 2.90.30.62.8 0.6 12.23.60.65.250.94.2 MB_PD_48_081-B 2 0.4
2.7 0.2 10.86.9 0.4 2.43.1 0.40.893.30.88 236.14.3 MB_HR_58_081
0.52.60.5 0.4 5.90.12.60.1 0.4 0.12.2 5.20.720.62.67.10.5 230.1
MB_SS_87_081 7.1 2.8 0.3 5.40.9 2.32 0.90.10.6 0.10.94.6 2.80.70.6
50.43.4 LR_MB_142_081 0.3 12.5 0.5 0.7 2.2 0.5 0.920.3 24.7
0.77.60.9 0.510.4 8.420.6 LR_MB_103_081 14.3 0.9 0.2 0.1 0.5 0.32.7
2.60.90.6 0.2 46.5 13.1 3.70.3 10.10.4 0.606 MB_LD_48_081 3.50.6
0.1 1 0.2 0.1 0.4 20.727.90.2 19.85.20.2 0.10.4 0.35.77
MB_SS_87_083 0.2 0.1 0.8 0.2 0.7 0.2 24.210.70.40.3 19.313.3
0.60.30.50.40.913.37.2 MB_SS_87_084 0.3 0.5 0.3 0.20.4 0.1 0.3
27.42.50.20.821210.40.1 0.60.510.34.70.510.57 MB_ByR_42_082 10.20.8
0.30.22.7 0.234.818.50.13 2.67.9 0.80.3 4.510.34.9 MB_SS_87_082
0.50.7 5 0.20.8 0.20.8 0.23.25.50.215.10.3 310.70.2 0.8 0.50.8
3.330.35.9 PB_CC_63_081 2.2 0.2 0.1 2.1 0.1 0.6 0.80.1 10.3 0.5 0.2
3.940.560.612.9 10.16.20.520.39.8 0.55 LR_BR_318_081 15.6 2.2 0.5
19.30.54.40.5 2.20.7 8.9 3 3.70.55.230.7 3 35.90.7 LR_FHB_321_081
0.63.5 15.5 0.16.7 0.8 0.5 0.80.10.6 0.3 2.16.73.50.82.93.50.9
0.810.50.9 OC_CR_XXX_081 0.3 0.80.20.1 0.7 0.5 0.40.20.8 0.4 0.5
12.10.333.20.90.50.40.10.3 12.224.70.3 OC_NHR-XXX-081 0.20.3 0.1
2.40.13.5 0.40.5 0.2 0.80.72.1 0.2 3.110.34.40.4 0.332 20.3 3.9
4.820.30.3 LC_R7_51_081 0.50.3 0.8 0.3 25.1 0.80.33.10.3
3.3150.35.1 0.91 0.3 0.40.8 0.333.60.8 LB_MR_229_081 3.9 0.3
210.92.1 0.62.8 0.9 2.3 0.4 3.418.60.4 0.2 0.10.42.3 0.5 0.48.6 0.1
216.70.35.89.85.7 LB_MR_288_081 0.6 8.6 0.96.90.218.2 0.5 4.2 0.5
510.73.1 0.90.4 0.6 0.30.10.6122.64.10.2 OC_BC_172_081 2.4
0.70.20.73.70.4 0.7 0.4 0.20.410.15.90.4 0.2 0.3 4.839.1 0.40.5
99.2 0.483 LR_RB_197_081 0.2 0.60.3 0.2 0.80.2 0.80.20.6 2.30.2
2.90.616.27.80.2 116.20.4 0.8316.8 0.222.17.4 LR_EB_213_081 2.80.4
2.3 0.6 0.4 0.6 0.72.30.7 0.6 2.3 0.70.90.6 0.3 26.3 0.310.330.1
0.6 0.9 18.52.3 LR_WB_215_0815.96.140.28.5 0.4 3.35 0.2 0.7 4
0.22.6 20.54 3.1 0.2 0.7 0.50.214.2 LR_WB_244_0814.5515.16.82.65.4
0.30.2 0.9 2.6 2.92.6 0.9 8.34.2 3.35.5 3.30.3 0.5 2.9
2.10.20.32.60.6 LR_WB_386_0810.8 0.1 14.8 0.8 6.815.20.1 3.4 0.4
0.8 3 0.44.2 0.40.1 6.5 0.4 12.50.4 LR_BR_141_081 12.7 0.4
0.90.40.9 10.13.1 0.40.96.64.44.80.8 0.4 5.7 0.310.52.20.90.4
0.32.20.9 16.70.8 LR_SR_139_081 0.40.7 0.4 0.7 0.4 3.2
8.60.73.60.42.9 0.84.30.10.4 0.72.20.80.40.12.50.10.4
6.190.713.316.5 LR_BR_165_081 0.5 2.5 0.80.42.7 0.2 2.3 0.80.4
0.20.4 0.5 4.20.52.72.360.80.2 1 0.50.20.40.55.28.5 7.92.3 3.84.8
0.4 0.87.90.5 0.6840.6450.457 Results Statistically Valid Sectors
23
- Slide 24
- AI-Ple-Pero-Isop AI-Eph-Hep-Rhi AI-Eph-Bae-Acen AI-Tri-Hyds-Che
AI-Eph-Ephi-Eph AI-Tri-Hyds-Pot-f AI-Ple-Pero AI-Cole-Elm-Ord-n
AI-Tri-Phi-Dol AI-Cole-Elm AI-Eph-Ephe-Ser AI-Eph-Ephe
AI-Tri-Hel-Hel AI-Ple-Peri AI-Eph-Lepp-Par AI-Eph-Bae-Pse
AI-Eph-Bae-Fal AI-Dip-Tab AC-Iso-Ase-Lir-l AI-Ple-Pte-Pte
AI-Tri-Glo-Aga AI-Ple-Chl-All AI-Tri-Rhy-Rhy AI-Ple-Leu-Leu
AI-Eph-Ephe-Eph AI-Eph-Bae-Acer AI-Ple-Cap-Cap AI-Eph-Sip-Par
AI-Ple-Cap-Nem-c AI-Ple AI-Eph-Hep-Hep AI-Tri-Glo-Glo
AI-Eph-Lepp-Lep AI-Meg-Cor-Nig AI-Tri-Bra-Bra AI-Eph-Hep
AI-Dip-Tip-Ped AI-Cole-Pse-Pse AI-Eph-Hep-Epe AI-Eph-Ephe-Dru
AI-Ple-Peri-Neoe AI-Dip-Tip MG-Pul-Lym AC-Amp-Cra-Cra
AI-Cole-Dyt-Dyts AI-Tri-Hyds-Hyd AI-Tri-Hyds AI-Tri AI-Tri-Hyds-Cer
AI-Tri-Hyds-Arc AI-Tri-Uen-Neo AI-Dip-Tip-Ant AI-Eph-Bae
AI-Tri-Phi-Chi AI-Eph-Bae-Bae AI-Dip-Cer A AI-Eph AI-Dip-Nym-Nym
AI-Dip AI-Cole-Elm-Opt AC-Oli AI-Dip-Sim AI-Dip-Chi AI-Cole-Elm-Ste
MB_BiR_76_081 0.41 0.5 12.8 0.930.420.2 2.5 335.915.6 MB_ER_47_081
10.80.2 0.60.5 40.2 0.72.90.447.10.6 MB_PD_48_081-A 0.2 7
0.30.62.37.6 0.50.2 20.30.72.93.89.336.7 MB_R7_46_081 0.9 0.50.72
0.2 0.5 3.70.70.20.527.40.59.660.92.6 MB_BrR_114_081 0.2 0.5 0.2
0.5 0.72.30.93.70.9 3.23.40.412.32.54.83.90.5377.1 MB_ByR_42_081
0.6 4.9 2.90.30.62.8 0.6 12.23.60.65.250.94.2 MB_PD_48_081-B 2 0.4
2.7 0.2 10.86.9 0.4 2.43.1 0.40.893.30.88 236.14.3 MB_HR_58_081
0.52.60.5 0.4 5.90.12.60.1 0.4 0.12.2 5.20.720.62.67.10.5 230.1
MB_SS_87_081 7.1 2.8 0.3 5.40.9 2.32 0.90.10.6 0.10.94.6 2.80.70.6
50.43.4 LR_MB_142_081 0.3 12.5 0.5 0.7 2.2 0.5 0.920.3 24.7
0.77.60.9 0.510.4 8.420.6 LR_MB_103_081 14.3 0.9 0.2 0.1 0.5 0.32.7
2.60.90.6 0.2 46.5 13.1 3.70.3 10.10.4 0.606 MB_LD_48_081 3.50.6
0.1 1 0.2 0.1 0.4 20.727.90.2 19.85.20.2 0.10.4 0.35.77
MB_SS_87_083 0.2 0.1 0.8 0.2 0.7 0.2 24.210.70.40.3 19.313.3
0.60.30.50.40.913.37.2 MB_SS_87_084 0.3 0.5 0.3 0.20.4 0.1 0.3
27.42.50.20.821210.40.1 0.60.510.34.70.510.57 MB_ByR_42_082 10.20.8
0.30.22.7 0.234.818.50.13 2.67.9 0.80.3 4.510.34.9 MB_SS_87_082
0.50.7 5 0.20.8 0.20.8 0.23.25.50.215.10.3 310.70.2 0.8 0.50.8
3.330.35.9 PB_CC_63_081 2.2 0.2 0.1 2.1 0.1 0.6 0.80.1 10.3 0.5 0.2
3.940.560.612.9 10.16.20.520.39.8 0.55 LR_BR_318_081 15.6 2.2 0.5
19.30.54.40.5 2.20.7 8.9 3 3.70.55.230.7 3 35.90.7 LR_FHB_321_081
0.63.5 15.5 0.16.7 0.8 0.5 0.80.10.6 0.3 2.16.73.50.82.93.50.9
0.810.50.9 OC_CR_XXX_081 0.3 0.80.20.1 0.7 0.5 0.40.20.8 0.4 0.5
12.10.333.20.90.50.40.10.3 12.224.70.3 OC_NHR-XXX-081 0.20.3 0.1
2.40.13.5 0.40.5 0.2 0.80.72.1 0.2 3.110.34.40.4 0.332 20.3 3.9
4.820.30.3 LC_R7_51_081 0.50.3 0.8 0.3 25.1 0.80.33.10.3
3.3150.35.1 0.91 0.3 0.40.8 0.333.60.8 LB_MR_229_081 3.9 0.3
210.92.1 0.62.8 0.9 2.3 0.4 3.418.60.4 0.2 0.10.42.3 0.5 0.48.6 0.1
216.70.35.89.85.7 LB_MR_288_081 0.6 8.6 0.96.90.218.2 0.5 4.2 0.5
510.73.1 0.90.4 0.6 0.30.10.6122.64.10.2 OC_BC_172_081 2.4
0.70.20.73.70.4 0.7 0.4 0.20.410.15.90.4 0.2 0.3 4.839.1 0.40.5
99.2 0.483 LR_RB_197_081 0.2 0.60.3 0.2 0.80.2 0.80.20.6 2.30.2
2.90.616.27.80.2 116.20.4 0.8316.8 0.222.17.4 LR_EB_213_081 2.80.4
2.3 0.6 0.4 0.6 0.72.30.7 0.6 2.3 0.70.90.6 0.3 26.3 0.310.330.1
0.6 0.9 18.52.3 LR_WB_215_0815.96.140.28.5 0.4 3.35 0.2 0.7 4
0.22.6 20.54 3.1 0.2 0.7 0.50.214.2 LR_WB_244_0814.5515.16.82.65.4
0.30.2 0.9 2.6 2.92.6 0.9 8.34.2 3.35.5 3.30.3 0.5 2.9
2.10.20.32.60.6 LR_WB_386_0810.8 0.1 14.8 0.8 6.815.20.1 3.4 0.4
0.8 3 0.44.2 0.40.1 6.5 0.4 12.50.4 LR_BR_141_081 12.7 0.4
0.90.40.9 10.13.1 0.40.96.64.44.80.8 0.4 5.7 0.310.52.20.90.4
0.32.20.9 16.70.8 LR_SR_139_081 0.40.7 0.4 0.7 0.4 3.2
8.60.73.60.42.9 0.84.30.10.4 0.72.20.80.40.12.50.10.4
6.190.713.316.5 LR_BR_165_081 0.5 2.5 0.80.42.7 0.2 2.3 0.80.4
0.20.4 0.5 4.20.52.72.360.80.2 1 0.50.20.40.55.28.5 7.92.3 3.84.8
0.4 0.87.90.5 0.6840.6450.457 Results Statistically Valid Sectors
(Contd) 24
- Slide 25
- AI-Ple-Pero-Isop AI-Eph-Hep-Rhi AI-Eph-Bae-Acen AI-Tri-Hyds-Che
AI-Eph-Ephi-Eph AI-Tri-Glo-Aga AI-Ple-Chl-All AI-Tri-Rhy-Rhy
AI-Ple-Leu-Leu AI-Eph-Ephe-Eph AI-Eph-Bae-Acer AI-Ple-Cap-Cap
AI-Eph-Sip-Par AI-Tri-Glo-Glo AI-Eph-Lepp-Lep AI-Meg-Cor-Nig
AI-Tri-Bra-Bra AI-Eph-Hep AI-Dip-Tip-Ped AI-Cole-Pse-Pse
AI-Eph-Hep-Epe AI-Eph-Ephe-Dru AI-Ple-Peri-Neoe AI-Dip-Tip
MG-Pul-Lym AC-Amp-Cra-Cra AI-Cole-Dyt-Dyts AI-Tri-Hyds-Hyd
AI-Tri-Hyds AI-Tri AI-Tri-Hyds-Cer AI-Tri-Hyds-Arc AI-Tri-Uen-Neo
AI-Dip-Tip-Ant AI-Eph-Bae AI-Tri-Phi-Chi AI-Eph-Bae-Bae AI-Dip-Cer
A AI-Eph AI-Dip-Nym-Nym AI-Dip-Sim AI-Dip-Chi AI-Cole-Elm-Ste
MB_BiR_76_081 MB_ER_47_081 MB_PD_48_081-A Absent to Mostly
MB_R7_46_081 Absent Mostly Absent Mostly Rare Absent Rare to
Abs-Rare Mostly Rare LowerUpper MB_BrR_114_081 Common MB_ByR_42_081
MB_PD_48_081-B MB_HR_58_081 MB_SS_87_081 Absent Absent to Mostly
Absent to Mostly LR_MB_142_081 Mostly Absent Mostly Rare Absent
Abs-UncomCommon Abs-UncomUpper LR_MB_103_081 MB_LD_48_081
MB_SS_87_083 Mostly Absent to Rare to MB_SS_87_084 Absent Absent to
Abs-Rare Mostly Abs-Rare Lower CommonAbs-Rare Common MB_ByR_42_082
Mostly Rare Absent MB_SS_87_082 PB_CC_63_081 LR_BR_318_081
LR_FHB_321_081 Absent Absent toAbsent MostlyAbsent to Mostly
OC_CR_XXX_081 Abs-Uncom Mostly Rareto AbsentMostly
RareCommonAbs-Uncom Upper OC_NHR-XXX-081 Uncommon LC_R7_51_081
LB_MR_229_081 Rare to Mostly Absent to Rare to LB_MR_288_081 Absent
Abs-Uncom Abs-Rare Common AbsentAbs-RareCommonAbs-Rare Common
OC_BC_172_081 LR_RB_197_081 Absent Abs-Rare Abs-Uncom Rare
toAbs-Rare Mostly Abs-Rare Mostly LR_EB_213_081 Uncommon Lower
Upper LR_WB_215_081 Rare to Absent Absent to Mostly LR_WB_244_081
Common Mostly Absent Abs-Uncom toAbsentCommon Mostly Rare Mostly
Absent Lower LR_WB_386_081 Rare LR_BR_141_081 Absent to Rare to
Mostly Absent to Rare to LR_SR_139_081 Mostly AbsentMostly Rare
Abs-Uncom Common AbsentAbs-UncomCommon UncommonCommon LR_BR_165_081
Results Abundance Values for Each Sector 25
- Slide 26
- AI-Ple-Pero-Isop AI-Eph-Hep-Rhi AI-Eph-Bae-Acen AI-Tri-Hyds-Che
AI-Eph-Ephe-Eph AI-Tri-Glo-Aga AI-Ple-Chl-All AI-Tri-Rhy-Rhy
AI-Ple-Leu-Leu AI-Eph-Ephe-Eph AI-Eph-Bae-Acer AI-Ple-Cap-Cap
AI-Eph-Sip-Par AI-Tri-Glo-Glo AI-Eph-Lepp-Lep AI-Meg-Cor-Nig
AI-Tri-Bra-Bra AI-Eph-Hep AI-Dip-Tip-Ped AI-Cole-Pse-Pse
AI-Eph-Hep-Epe AI-Eph-Ephe-Dru AI-Ple-Peri-Neoe AI-Dip-Tip
MG-Pul-Lym AC-Amp-Cra-Cra AI-Cole-Dyt-Dyts AI-Tri-Hyds-Hyd
AI-Tri-Hyds AI-Tri AI-Tri-Hyds-Cer AI-Tri-Hyds-Arc AI-Tri-Uen-Neo
AI-Dip-Tip-Ant AI-Eph-Bae AI-Tri-Phi-Chi AI-Eph-Bae-Bae AI-Dip-Cer
A AI-Eph AI-Dip-Nym-Nym AI-Dip-Sim AI-Dip-Chi AI-Cole-Elm-Ste
MB_BiR_76_081 low elev high impact MB_ER_47_081 MB_PD_48_081-A
Mostly MB_R7_46_081 Rare to Upper MB_BrR_114_081 Common
MB_ByR_42_081 MB_PD_48_081-B MB_HR_58_081 MB_SS_87_081 Absent to
Mostly Low elev mod impact LR_MB_142_081 Common Upper LR_MB_103_081
MB_LD_48_081 Low elev some impact MB_SS_87_083 Absent to Rare to
MB_SS_87_084 Common MB_ByR_42_082 MB_SS_87_082 PB_CC_63_081
LR_BR_318_081 Hi elev mod impact LR_FHB_321_081 Absent to Mostly
OC_CR_624_081 Common Upper OC_NHR-187-081 LC_R7_51_081
LB_MR_229_081 Rare to Absent to Rare to Hi elev some imp
LB_MR_288_081 Common OC_BC_172_081 LR_RB_197_081 Mostly Hi elev hi
impact LR_EB_213_081 Upper LR_WB_215_081 Rare to Absent to Hi elev
lo impact LR_WB_244_081 Common LR_WB_386_081 LR_BR_141_081 Rare to
Absent to Rare to Hi elev some imp LR_SR_139_081 Common
LR_BR_165_081 Results Abundance Values for Each Sector Low elev
High imp Low elev mod imp Low elev some imp High elev mod imp High
elev some imp High elev High imp High elev lo imp High elev some
imp 26
- Slide 27
- Four major site sets (clusters of sites) were identified. These
four site sets could be distinguished on the basis of as few as 25
taxa. These 25 taxa included taxa sets (clusters of taxa) of
pollution intolerant, intermediate and tolerant organisms, thus
These four site sets could be assessed for impact on the basis of
as few as 25 taxa. It is not at all unreasonable to have HS
students master the consistent identification of these 25 taxa and
thus be in a position to assist the professional effort by state
DECs/DEMs to assess stream quality on an ongoing basis. Results
Major Conclusions 27
- Slide 28
- Acknowledgements The authors wish to thank: The EPSCoR 2008
& 2009 Baccalaureate College Development (BCD) Faculty Support
Streams Project Grants under NSF Grant Number, EPS-0236976 28
- Slide 29
- Questions For more information, go to:
http://www2.norwich.edu/pinkhamc/
http://thestartingfive.wordpress.com/2008/01/29/five-questions-to-take-advantage-of-a-black-sense-of-urgency/
29