Karen Blocksom and Joseph Flotemersch EPA/ORD/NERL NWQM Conference, San Jose, CA May 11, 2006

1. Karen Blocksom and Joseph Flotemersch EPA/ORD/NERL NWQM Conference, San Jose, CA May 11, 2006 Effect of Taxonomic Resolution on Performance Characteristics of a Method for Sampling Large Rivers *Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.

2. Background • A new bioassessment method developed for collecting macroinvertebrates in non-wadeable rivers (In press: River Research and Applications, vol. 22, July 2006) • Study conducted to estimate performance characteristics using metrics: precision and sensitivity • Evaluated at the lowest possible taxon (species) level • Many states stop at genus or family, so relevant to evaluate performance characteristics at these levels as well

3. Transect A 1 B C 100 m A 2 B C A 3 B C 500 m Flow Flow A 4 B C A 5 B C A 6 B C Sample Collection and Processing • 19 sites across 5 rivers • Deep and shallow sites across disturbance gradient • 3 replicate samples per site in field • Also habitat, basic water chemistry collected • Up to three 300-organism sorts per sample in the laboratory

4. Expectations (Family/Genus relative to Species level) • Richness metrics will have lower values in general and hence, lower variability (higher precision) at the genus and family levels (Total and EPT taxa richness) • Tolerance and functional feeding group metrics will have lower variability because designations will apply to broader groups and should be more consistent at this level (% Tolerant individuals and % Collector-filterers) • Laboratory variability will be lower because less chance for error than at species level • Sensitivity will be poorer because of broader groups at the family level – fewer correlations with abiotic variables

5. Precision - Methods • Perform ANOVA with: • Site ID as factor • Multiple samples (A,B,C) as field replicates • Multiple 300-organism sorts as lab replicates • Use RMSE from this analysis to calculate: • Detectable difference (DD) – minimum difference detectable based on sample size of 3 • Relative DD (as percentage of metric range)

6. 8 7 6 5 Family 4 Genus DD Species 3 2 1 0 % Tolerant EPT richness Taxa richness % Coll-filterer Precision - Field

7. 12 10 8 Family Genus 6 Relative DD Species 4 2 0 % Tolerant EPT richness % Coll-filterer Taxa richness Precision - Field

8. 7 6 5 Family Genus 4 Species 3 DD 2 1 0 % Tolerant EPT richness Taxa richness % Coll-filterer Precision - Laboratory

9. 15 Family 10 Genus Species Relative DD 5 0 % Tolerant EPT richness Taxa richness % Coll-filterer Precision - Laboratory

10. Results - Precision • Taxa and EPT richness • DD (variability) increased from family to species as expected • BUT relative DD similar or slight decrease from family to species • % Tolerant individuals • For lab, DD (variability) increased family to species • No strong pattern for field DD • % Collector-filterers • Genus and species identical - same designations • All measures similar among taxonomic levels

11. Sensitivity - Methods • Spearman rank correlations • Family, genus, and species levels • Between mean metric values and potential gradients: • Taxa richness, EPT richness, % Tolerant individuals, % Collector-filterers • Conductivity, pH, DO, temperature, EMAP habitat and human influence variables, NWHI metrics

12. Family Genus Species 80 r = -0.49 r = -0.62 r = -0.66 70 60 Taxa richness 50 40 30 20 10 0 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Human influence - Roads Sensitivity

13. Family Genus Species 25 r = 0.61 r = 0.59 r = 0.59 20 EPT richness 15 10 5 0 200 400 600 800 200 400 600 800 200 400 600 800 Conductivity (uS/cm) Sensitivity

14. Family Genus Species 90 r = -0.50 r = -0.45 r = -0.41 80 70 60 % Tolerant individuals 50 40 30 20 10 0 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Bottom Deposition score (NWHI) Sensitivity

15. Family Genus Species 40 r = 0.66 r = 0.67 r = 0.67 30 % Collector-filterers 20 10 0 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Bottom Deposition score (NWHI) Sensitivity

16. Results – Sensitivity • As expected, generally more significant correlations at species level • Strength of common correlations similar among taxonomic levels • Variability around trend lines tends to be greater for genus and species level data

17. Conclusions • In the context of relative DD, taxonomic level had little to no effect • Sensitivity only slightly stronger at genus/species level than at the family level • Overall, taxonomic resolution did not strongly affect performance characteristics of the method