34th Annual Meeting

New England Association of Environmental Biologists

31st Annual MeetingHotel Viking Newport, RI

March 19, 2010

1

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 Michael’s College Northfield, VT Colchester, VT

Farley Brown Johnathon L. Miller Sterling College Formerly of Craftsbury Commons, VT Geology Department Norwich University

2

by the

Outline

• Vermont Streams Project

• Index of Biotic Similarity, BioSim2, & the statistical test

• Results

• Conclusions

3

Outline

• Vermont Streams Project– Concept

– Participants

– Drainage Basins in the Project

– Macroinvertebrate Techniques

4

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 ProjectConcept

5

Vermont Streams Project

Participants

6

Vermont Streams Project

2008, College Baseline Study:

33 sites 6 drainage

basins

7

• 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 ProjectMacroinvertebrate Techniques

Sampling

8

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 ProjectMacroinvertebrate Techniques

Processing

9

Outline

• Index of Biotic Similarity, BioSim2, & the Statistical Test– Brief Review

– What is a Sector?

– Statistically Valid Sectors

10

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

Index of Biotic Similarity, BioSim2, & the Statistical TestBrief Review

12

Brief Review

Matrix of B’s Between 11 Parameters

Index of Biotic Similarity, BioSim2, & the Statistical Test

13

Site Dendrogram

Index of Biotic Similarity, BioSim2, & the Statistical TestBrief Review

14

Taxa Dendrogram

Index of Biotic Similarity, BioSim2, & the Statistical TestBrief Review

15

What is a Sector?

Index of Biotic Similarity, BioSim2, & the Statistical Test

16

• 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

• Calculations

Group 1ta

xon

1

taxo

n 2

taxo

n k

Creek 1Creek 2

Creek n

Group 2

taxo

n 1

taxo

n 2

taxo

n k

Creek 1Creek 2

Creek m

1,1

1,1

x

s1,2

1,2

x

s1,

1,

k

k

x

s

2,1

2,1

x

s2,2

2,2

x

s2,

2,

k

k

x

s

1, 2,

2 21, 2,

i ii

i i

x xd

s sn m

Index of Biotic Similarity, BioSim2, & the Statistical Test

Statistically Valid Sectors

18

• CalculationsHo: There is a not a significant difference between the percent

compositions of taxa in the sites making up Sector 1 & Sector 2. Ha: There is a significant difference between the percent

compositions of taxa in the sites making up Sector 1 & Sector 2.

Given Ho 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

Outline

• Results– Original Macroinvertebrate Data Matrix

– Macroinvertebrate % Composition Data

– Statistically Valid Sector Analysis

– Abundance Values for Each Sector

20

• 208 taxa collected at 33 sites comprising 24, 677 organisms…

• compressed to 83 taxa at 33 sites comprising 23,987 organisms (<97% of original) by eliminating– taxa which appeared in only one site with 30 or fewer

organisms (82 taxa).– taxa which appeared in only two sites with total of 30

or fewer organisms (25 taxa).– taxa which appeared in only three sites with a total of

30 or fewer organisms (18 taxa).

ResultsOriginal Macroinvertebrate Data Matrix

21

• 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)

ResultsMacroinvertebrate % Composition Data

22

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 0.4 1 0.5 12.8 0.9 3 0.4 20.2 2.5 3 35.9 15.6

MB_ER_47_081 1 0.8 0.2 0.2 0.2 0.6 0.5 40.2 0.7 2.9 0.4 47.1 0.6

MB_PD_48_081-A 0.2 7 0.2 0.3 0.6 2.3 7.6 0.5 0.2 20.3 0.7 2.9 3.8 9.3 36.7

MB_R7_46_081 0.9 0.9 0.5 0.7 2 0.2 0.5 3.7 0.7 0.2 0.5 2 7.4 0.5 9.6 60.9 2.6

MB_BrR_114_081 0.2 0.2 0.5 0.2 0.5 0.7 2.3 0.9 3.7 0.9 0.9 3.2 3.4 0.4 12.3 2.5 4.8 3.9 0.5 37 7.1

MB_ByR_42_081 0.6 4.9 2.9 0.3 0.6 2.8 0.6 12.2 3.6 0.6 5.2 50.9 4.2

MB_PD_48_081-B 2 0.4 2.7 0.2 10.8 6.9 0.4 2.4 3.1 0.4 0.8 9 3.3 0.8 8 2 36.1 4.3

MB_HR_58_081 0.5 2.6 0.5 0.4 0.4 0.4 5.9 0.1 2.6 0.1 0.4 0.1 2.2 2.2 5.2 0.7 20.6 2.6 7.1 0.5 23 0.1

MB_SS_87_081 7.1 2.8 0.3 5.4 0.9 2.3 2 0.9 0.1 0.6 0.1 0.9 4.6 2.8 0.7 0.6 50.4 3.4

LR_MB_142_081 0.3 12.5 0.5 0.7 2.2 0.5 0.9 2 0.3 0.3 0.3 24.7 0.7 7.6 0.9 0.5 10.4 8.4 20.6

LR_MB_103_081 14.3 0.9 0.2 0.1 0.5 0.3 2.7 2.6 0.9 0.6 0.2 46.5 13.1 3.7 0.3 10.1 0.4 0.606MB_LD_48_081 3.5 0.6 0.1 1 0.2 0.1 0.4 0.4 20.7 27.9 0.2 0.2 19.8 5.2 0.2 0.2 0.1 0.4 0.4 0.3 5.7 7

MB_SS_87_083 0.2 0.1 0.8 0.2 0.7 0.2 24.2 10.7 0.4 0.3 19.3 13.3 0.6 0.3 0.5 0.4 0.9 13.3 7.2

MB_SS_87_084 0.3 0.5 0.3 0.2 0.4 0.1 0.3 27.4 2.5 0.2 0.8 2 12 10.4 0.1 0.6 0.5 10.3 4.7 0.5 10.5 7

MB_ByR_42_082 1 0.2 0.8 0.3 0.2 2.7 0.2 34.8 18.5 0.1 3 2.6 7.9 0.8 0.3 0.3 0.3 4.5 10.3 4.9

MB_SS_87_082 0.5 0.7 5 0.2 0.8 0.2 0.8 0.8 0.2 3.2 5.5 0.2 15.1 0.3 3 10.7 0.2 0.2 0.8 0.5 0.8 3.3 30.3 5.9

PB_CC_63_081 2.2 0.2 0.1 2.1 0.1 0.6 0.8 0.1 10.3 0.5 0.5 0.2 3.9 4 0.5 6 0.6 12.9 10.1 6.2 0.5 20.3 9.8 0.55LR_BR_318_081 15.6 2.2 0.5 19.3 0.5 4.4 0.5 2.2 0.7 0.7 8.9 3 3.7 0.5 5.2 3 0.7 3 3 5.9 0.7

LR_FHB_321_081 0.6 3.5 15.5 15.5 0.1 6.7 0.8 0.5 0.8 0.1 0.6 0.3 2.1 6.7 3.5 0.8 2.9 3.5 0.9 0.8 10.5 0.9

OC_CR_XXX_081 0.3 0.8 0.2 0.1 0.1 0.7 0.7 0.5 0.4 0.2 0.8 0.4 0.4 0.5 0.5 12.1 0.3 33.2 0.9 0.5 0.4 0.1 0.3 0.3 12.2 24.7 0.3

OC_NHR-XXX-081 0.2 0.3 0.1 2.4 0.1 3.5 0.4 0.5 0.2 0.8 0.7 2.1 0.2 0.2 3.1 10.3 4.4 0.4 0.3 32 2 0.3 0.3 0.3 3.9 4.8 20.3 0.3

LC_R7_51_081 0.5 0.3 0.3 0.8 0.3 25.1 0.8 0.3 3.1 0.3 0.3 3.3 15 0.3 5.1 0.9 1 0.3 0.4 0.8 0.3 33.6 0.8

LB_MR_229_081 3.9 0.3 2 1 0.9 2.1 0.6 2.8 0.9 2.3 0.4 3.4 18.6 0.4 0.2 0.1 0.4 2.3 0.5 0.4 8.6 0.1 2 16.7 0.3 5.8 9.8 5.7

LB_MR_288_081 0.6 8.6 0.9 6.9 0.2 18.2 0.5 4.2 0.5 5 10.7 3.1 0.9 0.4 0.6 0.3 0.1 0.6 1 22.6 4.1 0.2

OC_BC_172_081 2.4 0.7 0.2 0.7 3.7 0.4 0.4 0.7 0.4 0.2 0.4 10.1 5.9 0.4 0.4 0.2 0.3 4.8 39.1 0.4 0.5 0.5 0.5 9 9.2 0.483LR_RB_197_081 0.2 0.2 0.6 0.3 0.2 0.2 0.8 0.2 0.8 0.2 0.6 0.6 2.3 0.2 2.9 0.6 1 6.2 7.8 0.2 0.2 0.2 1 16.2 0.4 0.8 3 16.8 0.2 22.1 7.4

LR_EB_213_081 2.8 0.4 2.3 0.6 0.6 0.4 0.6 0.6 0.7 2.3 0.7 0.6 2.3 0.7 0.9 0.6 0.3 0.3 2 6.3 0.3 10.3 30.1 0.6 0.6 0.9 18.5 2.3

LR_WB_215_081 5.9 6.1 4 0.2 8.5 0.4 3.3 5 0.2 0.2 0.2 0.7 4 0.7 0.2 2.6 20.5 4 3.1 0.2 0.7 0.5 0.2 14.2

LR_WB_244_081 4.5 5 15.1 6.8 2.6 5.4 0.3 0.2 0.9 2.6 2.9 2.6 0.9 8.3 4.2 3.3 5.5 3.3 0.3 0.5 2.9 2.1 0.2 0.3 2.6 0.6

LR_WB_386_081 0.8 0.8 0.1 14.8 0.8 6.8 15.2 0.1 3.4 0.4 0.8 3 0.4 4.2 0.4 0.1 6.5 0.4 12.5 0.4

LR_BR_141_081 12.7 0.4 0.4 0.4 0.4 0.9 0.4 0.9 10.1 3.1 0.4 0.9 6.6 4.4 4.8 0.8 0.4 0.4 5.7 0.3 10.5 2.2 0.9 0.4 0.4 0.3 2.2 0.9 0.9 16.7 0.8

LR_SR_139_081 0.4 0.7 0.4 0.4 0.4 0.7 0.7 0.7 0.7 0.4 3.2 8.6 0.7 3.6 0.4 2.9 0.8 4.3 0.1 0.4 0.4 0.7 2.2 0.8 0.4 0.1 2.5 0.1 0.4 0.4 6.1 9 0.7 13.3 16.5

LR_BR_165_081 0.5 2.5 0.8 0.4 2.7 0.2 0.2 0.2 2.3 0.8 0.4 0.4 0.2 0.4 0.5 4.2 0.5 2.7 2.3 6 0.8 0.2 1 0.5 0.2 0.4 0.5 5.2 8.5 7.9 2.3 3.8 4.8 0.4 0.8 7.9 0.5

0.684 0.645 0.457

ResultsStatistically Valid Sectors

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-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 0.4 1 0.5 12.8 0.9 3 0.4 20.2 2.5 3 35.9 15.6

MB_ER_47_081 1 0.8 0.2 0.2 0.2 0.6 0.5 40.2 0.7 2.9 0.4 47.1 0.6

MB_PD_48_081-A 0.2 7 0.2 0.3 0.6 2.3 7.6 0.5 0.2 20.3 0.7 2.9 3.8 9.3 36.7

MB_R7_46_081 0.9 0.9 0.5 0.7 2 0.2 0.5 3.7 0.7 0.2 0.5 2 7.4 0.5 9.6 60.9 2.6

MB_BrR_114_081 0.2 0.2 0.5 0.2 0.5 0.7 2.3 0.9 3.7 0.9 0.9 3.2 3.4 0.4 12.3 2.5 4.8 3.9 0.5 37 7.1

MB_ByR_42_081 0.6 4.9 2.9 0.3 0.6 2.8 0.6 12.2 3.6 0.6 5.2 50.9 4.2

MB_PD_48_081-B 2 0.4 2.7 0.2 10.8 6.9 0.4 2.4 3.1 0.4 0.8 9 3.3 0.8 8 2 36.1 4.3

MB_HR_58_081 0.5 2.6 0.5 0.4 0.4 0.4 5.9 0.1 2.6 0.1 0.4 0.1 2.2 2.2 5.2 0.7 20.6 2.6 7.1 0.5 23 0.1

MB_SS_87_081 7.1 2.8 0.3 5.4 0.9 2.3 2 0.9 0.1 0.6 0.1 0.9 4.6 2.8 0.7 0.6 50.4 3.4

LR_MB_142_081 0.3 12.5 0.5 0.7 2.2 0.5 0.9 2 0.3 0.3 0.3 24.7 0.7 7.6 0.9 0.5 10.4 8.4 20.6

LR_MB_103_081 14.3 0.9 0.2 0.1 0.5 0.3 2.7 2.6 0.9 0.6 0.2 46.5 13.1 3.7 0.3 10.1 0.4 0.606MB_LD_48_081 3.5 0.6 0.1 1 0.2 0.1 0.4 0.4 20.7 27.9 0.2 0.2 19.8 5.2 0.2 0.2 0.1 0.4 0.4 0.3 5.7 7

MB_SS_87_083 0.2 0.1 0.8 0.2 0.7 0.2 24.2 10.7 0.4 0.3 19.3 13.3 0.6 0.3 0.5 0.4 0.9 13.3 7.2

MB_SS_87_084 0.3 0.5 0.3 0.2 0.4 0.1 0.3 27.4 2.5 0.2 0.8 2 12 10.4 0.1 0.6 0.5 10.3 4.7 0.5 10.5 7

MB_ByR_42_082 1 0.2 0.8 0.3 0.2 2.7 0.2 34.8 18.5 0.1 3 2.6 7.9 0.8 0.3 0.3 0.3 4.5 10.3 4.9

MB_SS_87_082 0.5 0.7 5 0.2 0.8 0.2 0.8 0.8 0.2 3.2 5.5 0.2 15.1 0.3 3 10.7 0.2 0.2 0.8 0.5 0.8 3.3 30.3 5.9

PB_CC_63_081 2.2 0.2 0.1 2.1 0.1 0.6 0.8 0.1 10.3 0.5 0.5 0.2 3.9 4 0.5 6 0.6 12.9 10.1 6.2 0.5 20.3 9.8 0.55LR_BR_318_081 15.6 2.2 0.5 19.3 0.5 4.4 0.5 2.2 0.7 0.7 8.9 3 3.7 0.5 5.2 3 0.7 3 3 5.9 0.7

LR_FHB_321_081 0.6 3.5 15.5 15.5 0.1 6.7 0.8 0.5 0.8 0.1 0.6 0.3 2.1 6.7 3.5 0.8 2.9 3.5 0.9 0.8 10.5 0.9

OC_CR_XXX_081 0.3 0.8 0.2 0.1 0.1 0.7 0.7 0.5 0.4 0.2 0.8 0.4 0.4 0.5 0.5 12.1 0.3 33.2 0.9 0.5 0.4 0.1 0.3 0.3 12.2 24.7 0.3

OC_NHR-XXX-081 0.2 0.3 0.1 2.4 0.1 3.5 0.4 0.5 0.2 0.8 0.7 2.1 0.2 0.2 3.1 10.3 4.4 0.4 0.3 32 2 0.3 0.3 0.3 3.9 4.8 20.3 0.3

LC_R7_51_081 0.5 0.3 0.3 0.8 0.3 25.1 0.8 0.3 3.1 0.3 0.3 3.3 15 0.3 5.1 0.9 1 0.3 0.4 0.8 0.3 33.6 0.8

LB_MR_229_081 3.9 0.3 2 1 0.9 2.1 0.6 2.8 0.9 2.3 0.4 3.4 18.6 0.4 0.2 0.1 0.4 2.3 0.5 0.4 8.6 0.1 2 16.7 0.3 5.8 9.8 5.7

LB_MR_288_081 0.6 8.6 0.9 6.9 0.2 18.2 0.5 4.2 0.5 5 10.7 3.1 0.9 0.4 0.6 0.3 0.1 0.6 1 22.6 4.1 0.2

OC_BC_172_081 2.4 0.7 0.2 0.7 3.7 0.4 0.4 0.7 0.4 0.2 0.4 10.1 5.9 0.4 0.4 0.2 0.3 4.8 39.1 0.4 0.5 0.5 0.5 9 9.2 0.483LR_RB_197_081 0.2 0.2 0.6 0.3 0.2 0.2 0.8 0.2 0.8 0.2 0.6 0.6 2.3 0.2 2.9 0.6 1 6.2 7.8 0.2 0.2 0.2 1 16.2 0.4 0.8 3 16.8 0.2 22.1 7.4

LR_EB_213_081 2.8 0.4 2.3 0.6 0.6 0.4 0.6 0.6 0.7 2.3 0.7 0.6 2.3 0.7 0.9 0.6 0.3 0.3 2 6.3 0.3 10.3 30.1 0.6 0.6 0.9 18.5 2.3

LR_WB_215_081 5.9 6.1 4 0.2 8.5 0.4 3.3 5 0.2 0.2 0.2 0.7 4 0.7 0.2 2.6 20.5 4 3.1 0.2 0.7 0.5 0.2 14.2

LR_WB_244_081 4.5 5 15.1 6.8 2.6 5.4 0.3 0.2 0.9 2.6 2.9 2.6 0.9 8.3 4.2 3.3 5.5 3.3 0.3 0.5 2.9 2.1 0.2 0.3 2.6 0.6

LR_WB_386_081 0.8 0.8 0.1 14.8 0.8 6.8 15.2 0.1 3.4 0.4 0.8 3 0.4 4.2 0.4 0.1 6.5 0.4 12.5 0.4

LR_BR_141_081 12.7 0.4 0.4 0.4 0.4 0.9 0.4 0.9 10.1 3.1 0.4 0.9 6.6 4.4 4.8 0.8 0.4 0.4 5.7 0.3 10.5 2.2 0.9 0.4 0.4 0.3 2.2 0.9 0.9 16.7 0.8

LR_SR_139_081 0.4 0.7 0.4 0.4 0.4 0.7 0.7 0.7 0.7 0.4 3.2 8.6 0.7 3.6 0.4 2.9 0.8 4.3 0.1 0.4 0.4 0.7 2.2 0.8 0.4 0.1 2.5 0.1 0.4 0.4 6.1 9 0.7 13.3 16.5

LR_BR_165_081 0.5 2.5 0.8 0.4 2.7 0.2 0.2 0.2 2.3 0.8 0.4 0.4 0.2 0.4 0.5 4.2 0.5 2.7 2.3 6 0.8 0.2 1 0.5 0.2 0.4 0.5 5.2 8.5 7.9 2.3 3.8 4.8 0.4 0.8 7.9 0.5

0.684 0.645 0.457

ResultsStatistically Valid Sectors

(Cont’d)

24

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 Absent to Mostly Mostly

MB_R7_46_081 Absent   Mostly Absent Mostly Rare Absent Rare to Abs-Rare Mostly Rare Lower Upper

MB_BrR_114_081       Common

MB_ByR_42_081      

MB_PD_48_081-B

MB_HR_58_081

MB_SS_87_081Absent

Absent to Mostly Absent to Mostly

LR_MB_142_081 Mostly Absent Mostly Rare Absent Absent Abs-Uncom Common Abs-Uncom Upper

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 Common Abs-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 to Absent Mostly Absent to Absent to Mostly

OC_CR_XXX_081     Abs-Uncom Mostly Rare to Absent Mostly Rare Common Abs-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 Absent Abs-Rare Common Abs-Rare Common

OC_BC_172_081  

LR_RB_197_081 Absent Abs-Rare Abs-Uncom Rare to Abs-Rare Mostly Mostly Abs-Rare Mostly

LR_EB_213_081   Uncommon Lower Lower Upper

LR_WB_215_081 Rare to   Absent Absent to Absent to Mostly

LR_WB_244_081 Common   Mostly Absent Abs-Uncom to Absent Common Mostly Rare Mostly Absent Lower

LR_WB_386_081     Rare

LR_BR_141_081   Absent to Rare to Mostly Absent to Rare to Rare to

LR_SR_139_081 Mostly Absent Mostly Rare Abs-Uncom Common Absent Abs-Uncom Common Uncommon Common

LR_BR_165_081

ResultsAbundance Values for Each Sector

25

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 elevhigh 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 elevmod impact

LR_MB_142_081 Common Upper

LR_MB_103_081

MB_LD_48_081

Low elevsome

impact

MB_SS_87_083 Absent to Rare to

MB_SS_87_084 Common Common

MB_ByR_42_082

MB_SS_87_082

PB_CC_63_081

LR_BR_318_081

Hi elevmod 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 toHi elev

some impLB_MR_288_081 Common Common Common

OC_BC_172_081

LR_RB_197_081 MostlyHi elev

hi impactLR_EB_213_081 Upper

LR_WB_215_081 Rare to   Absent to

Hi elevlo impact

LR_WB_244_081 Common   Common

LR_WB_386_081    

LR_BR_141_081 Rare to Absent to Rare to

Hi elevsome imp

LR_SR_139_081 Common Common Common

LR_BR_165_081

ResultsAbundance Values for Each Sector

Low elevHigh imp

Low elevmod imp

Low elevsome imp

High elevmod imp

High elevsome imp

High elevHigh imp

High elevlo imp

High elevsome imp

26

• 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.

ResultsMajor Conclusions

27

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

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