1. 1 Sediment Quality Objectives for California Enclosed Bays and Estuaries Benthic Indicator Development Scientific Steering Committee 26 th July 2005

2. 2 Overview Why Benthos and Benthic Indices? The Index Development Process –Define Habitat Strata –Calibrate Candidate Benthic Indices –Validate and Evaluate Candidate Indices Proposed Next Steps

3. 3 Why Benthos? Benthic organisms are living resources –Direct measure of what legislation intends to protect They are good indicators –Sensitive, limited mobility, high exposure, integrate impacts, integrate over time Already being used to make regulatory and sediment management decisions –Santa Monica Bay removed from 303(d) list Listed for metals in the early 1990’s –301(h) waivers granted to dischargers –Toxic hotspot designations for the Bay Protection and Toxic Cleanup Program

4. 4 Benthic Assessments Pose Several Challenges Interpreting species abundances is difficult –Samples may have tens of species and hundreds of organisms Benthic species and abundances vary naturally with habitat –Different assemblages occur in different habitats –Comparisons to determine altered states should vary accordingly Sampling methods vary –Gear, sampling area and sieve size affect species and individuals captured

5. 5 Benthic Indices Meet These Challenges Benthic Indices –Remove much of the subjectivity associated with data interpretation –Account for habitat differences –Are single values –Provide simple means of Communicating complex information to managers Tracking trends over time Correlating benthic responses with stressor data –Are included in the U.S. EPA’s guidance for biocriteria development

6. 6 Overview Why Benthos and Benthic Indices? The Index Development Process –Define Habitat Strata –Calibrate Candidate Benthic Indices –Validate and Evaluate Candidate Indices Proposed Next Steps

7. 7 Define Habitat Strata Rationale –Species and abundances vary naturally from habitat to habitat Benthic indicators and definitions of reference condition should vary accordingly Objectives –Identify naturally occurring benthic assemblages, and –The habitat factors that structure them

8. 8 Approach Identify assemblages by cluster analysis –Standard choices Species in ≥ 2 samples ³ √ transform, species mean standardization Bray Curtis dissimilarity with step-across adjustment Flexible sorting ß=-0.25 Evaluate habitat differences between assemblages –Salinity, % fines, depth, latitude, longitude, TOC –Using Mann-Whitney tests

9. 9 Data EMAP data enhanced by regional data sets –Comparable methods Sampling, measurements, taxonomy –OR and WA data included Potential to increase amount of data for index development –1164 samples in database Eliminated potentially contaminated sites –≥ 1 chemical > ERM or ≥ 4 chemicals > ERL –Toxic to amphipods –Located close to point sources –DO < 2 ppm 714 samples analyzed

10. 10 Identified Eight Assemblages APuget Sound Fine Sediments BPuget Sound Coarse Sediments CSouthern California Euhaline Bays DPolyhaline San Francisco Bay EEstuaries and Wetlands FVery Coarse Sediments GMesohaline San Francisco Bay HLimnetic or Freshwater

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13. 13 Overview Why Benthos and Benthic Indices? The Index Development Process –Define Habitat Strata –Calibrate Candidate Benthic Indices –Validate and Evaluate Candidate Indices Proposed Next Steps

14. 14 Six Candidate Indices AcronymName IBIIndex of Biotic Integrity RBIRelative Benthic Index BRI*Benthic Response Index RIVPACS River Invertebrate Prediction and Classification System BQIBenthic Quality Index *: Two variations

15. 15 Candidate Indices Components Candidate IndexData IBICommunity measures RBICommunity measures BRI-TCSpecies abundances BRI-MNDFSpecies abundances RIVPACSPresence/absence of multiple species BQI Species abundances & community measures

16. 16 Index Development Teams Candidate Index Index LeaderReference IBIBruce Thompson Thompson and Lowe (2004) RBIJim Oakden Hunt et al. (2001) BRI*Bob Smith Smith et al. (2001, 2003) RIVPACSDavid Huff Wright et al. 1993 BQIBob Smith Rosenberg et al. (2004) *: Two variations

17. 17 Common Definitions A common set of definitions were established –For “Good” and “Bad” sites Used in two ways –Identify data to be withheld from index development Subsequently used to validate index Goal: A set of clearly affected or reference sites to evaluate index performance –“A Gold Standard” –Identify reference and degraded condition for index calibration

18. 18 Common Criteria “Good” (Reference) Sites Meet all the following criteria: –Far from known point sources –Data available for sediment chemistry and at least one amphipod toxicity test –No ERM* exceedences –No more than 3 ERL* exceedences –No toxicity Amphipod survival > 83% –Species abundance list does not indicate bad biology (In progress) *: As, Cd, Cu, Pb, Hg, Ag, Zn, Hmw(8) & Lmw(11) PAH, Total PCB

19. 19 Common Criteria “Bad” (Degraded) Sites Meet both of the following criteria –1 or more ERM exceedences, or 3 or more ERL exceedences, and –>50% mortality in an acute amphipod test

20. 20 National vs. CA data SouthNorth

21. 21 Data For Benthic Index Development Habitat # Samples GoodBad CEuhaline California Bays8517 DPolyhaline San Francisco Bay1812 EEstuaries and Wetlands1023 FVery Coarse Sediments560 GMesohaline San Francisco Bay204 HTidal Freshwater650

22. 22 Data For Benthic Index Development Numbers of samples Habitat CalibrationValidation GBGB CEuhaline California Bays759108 DPolyhaline San Francisco Bay96116

23. 23 The Calibration Process Identify habitats with sufficient data –“Good” and “Bad” sites –For index calibration and validation Distribute calibration data –Teams calibrate candidate indices Distribute independent data for validation –Teams apply candidates to data Results compiled for evaluation

24. 24 Overview Why Benthos and Benthic Indices? The Index Development Process –Define Habitat Strata –Calibrate Candidate Benthic Indices –Validate and Evaluate Candidate Indices Proposed Next Steps

25. 25 Index Validation Approaches Classification accuracy –Chemistry and toxicity –Biologist best professional judgment Repeatability –Same day –Same site on different days Independence from natural gradients Correlations with other information –Species richness –Other indices

26. 26 Overall Classification Accuracy Validation Data (%) Index Overall (n=35) RIVPACS83 BRI-TC77 IBI70 BRI-MNDF63 BQI63 RBI51

27. 27 Habitat Classification Accuracy Validation Data (%) Index Southern California (n=18) San Francisco Bay (n=17) RIVPACS7294 BRI-TC7282 IBI6773 BRI-MNDF5671 BQI5076 RBI2282

28. 28 Status Classification Accuracy Validation Data (%) Index “Good” Sites (n=21) “Bad” Sites (n=14) RIVPACS8679 BRI-TC8171 IBI10029 BRI-MNDF6757 BQI8136 RBI5250

29. 29 Potential Reasons for Low Classification Accuracy Do threshold and scaling problems exist? –Does an index correlate well with condition, but an incorrect threshold lead to the wrong interpretation? Are chemistry-toxicity “bad” definitions inadequate? –Chemistry criteria were less stringent than many other benthic index efforts

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33. 33 Are Validation Sites Misclassified? Is our “Gold Standard” correct? –Are multiple indices disagreeing? –How do index disagreements relate to biology? Samples with multiple disagreements evaluated –Using biologist best professional judgment

34. 34 Disagreements with Status Designations Number of Candidates Disagreeing N (Σ=35) 08 19 25 36 44 52 61

35. 35 Biology Comparison For six of seven samples –Biologists agreed that the chemistry-toxicity status was incorrect All four biologists agreed for four samples 75% agreement for other two “Gold Standard” is tarnished

36. 36 Effect of Status Change on Overall Classification Accuracy IndexOriginalAfter Change RIVPACS83 BRI-TC7789 IBI7076 BRI-MNDF6374 BQI6380 RBI5163

37. 37 Overview Why Benthos and Benthic Indices? The Index Development Process –Define Habitat Strata –Calibrate Candidate Benthic Indices –Validate and Evaluate Candidate Indices Proposed Next Steps

38. 38 Complete the Index Validation Process Classification accuracy –Chemistry and toxicity –Biologist best professional judgment Repeatability –Same day –Same site on different days Independence from natural gradients Correlations with other information –Species richness –Other indices

39. 39 Biology Classification Panel of six external experts –Evaluate 20-25 samples –Samples where 5 of 6 experts agree will establish a new “Gold Standard” To be used in the same way as the chemistry- toxicity classification

40. 40 Repeatability Identify sites where –Multiple samples were collected on the same visit –Multiple visits to the same site Evaluate candidate index stability

41. 41 Summary We will be able to develop benthic indices for two habitats –Some indices validating well Validation rates with sediment toxicity and chemistry data are low –Need to re-visit our scaling methods for some indices –Need to establishing biology-based good and bad criteria Best professional judgment of an independent panel of experts Have more validation steps to complete before making final selections