1. Benthic Community Assessment Tool Development Ananda Ranasinghe (Ana) Southern California Coastal Water Research Project (SCCWRP) anar@sccwrp.org Sediment Quality Objectives for California Bays and Estuaries

2. Outline Background: Why Benthic Communities? Approach –Refine and Validate Benthic Indicators –Evaluate Field and Laboratory Methods Task Details and Schedule

3. Why Benthos? Benthos are living resources –Direct measure of what legislation intends to protect Benthic organisms are good indicators of conditions at a site because of –Limited mobility, high exposure to anthropogenic impacts, integrate different types of impacts, and over time Already being used to make Regulatory and Sediment Management decisions –Santa Monica Bay removed from 303(d) list Was listed for metals in early 1990’s –301(h) waivers granted to dischargers –Toxic hotspot cleanup decisions in San Diego Bay

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 –Comparisons to determine altered states should vary accordingly Sampling methods vary –Gear, sampling area and sieve size affect species and individuals captured

5. Benthic Indices Meet These Challenges Benthic Indices Are Single values Account for habitat differences Remove much of the subjectivity associated with data interpretation 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. California Benthic Indices Three benthic indices have been developed for California bays –BRI (Benthic Response Index) for Southern California Smith et al. (2001, 2003) –IBI (Index of Biotic Integrity) for San Francisco Bay Thompson and Lowe (In press) –RBI (Relative Benthic Index) for several bays Hunt et al. 2001 They can all benefit by refinement –Data limitations constrained development How assessment results relate is not known –Except for some preliminary work completed recently

7. Refine And Validate Benthic Indicators (3 Tasks) Task 1: Refine existing benthic indices Task 2: Compare and evaluate benthic tools Task 3: Identify natural assemblages and the habitat factors that structure them

8. Task 1: Refine Benthic Tools Initial development of the three indices was constrained by data limitations –Lack of independent data for validation –Insufficient data from highly disturbed sites to define the entire range of the impact gradient –Uncertainty in the effect of environmental variables regardless of pollution impacts Subsequent data collection has removed this constraint for two regions –Southern California bays & San Francisco Bay Refine all three indices for the two regions –Same approaches as before, but more data

9. Task 2: Evaluate Benthic Tools For the three indices, it is not known –How assessment results relate –How robust they are to Taxonomy (level and accuracy) Seasonality, Grain size distribution, TOC and other habitat factors Evaluate based on: –Agreement with sediment chemistry and sediment toxicity –Conformity with known spatial and temporal gradients –Repeatability –Agreement with each other

10. Task 3: Identify Natural Assemblages (Biogeography) Identify naturally occurring assemblages and the habitat factors that structure them –To define habitats for determination of altered states –Evaluate annual and seasonal stability of habitat definitions Approach –Eliminate potentially contaminated sites from data collected throughout California using consistent methods –Use cluster analysis to identify assemblages and test habitat variables across dendrogram splits –Follows Bergen et al. (2001) Leverages the EMAP West Coast benthic index effort –Potentially increase data availability for index development in northern CA bays –Preliminary analysis indicates OR & WA coastal bays are similar to northern CA bays

11. Support Methods Guidance (2 Tasks) Task 4: Evaluate field sampling methods –Three gear sizes and two sieve mesh sizes are used in California –What is the nature and magnitude of these effects on assessment results? Task 5: Develop sample processing QA procedures –Assessment results vary depending on Sorting efficiency, and Identification and counting accuracy –Develop procedures to ensure consistent assessments regardless of which laboratory processes samples

12. Task 4: Evaluate Field Methods Why? Sampling gear affects benthic assessments –Larger gear collect more species and organisms –Smaller sieves catch More and smaller species More organisms that can’t be identified to species Three gears and two sieves are used in California –Gears: 0.1m 2 Van Veen grab 0.05 m 2 Van Veen grab 0.00785 m 2 corer –Sieves: 1.0 mm or 0.5 mm apertures

13. Task 4: Evaluate Field Methods Approach & Data Approach: Evaluate assessment differences –For samples processed with different gear and sieves –Apply indices and measures from Tasks 1 & 2 –Identify the nature and magnitude of gear and sieve effects Data –For gear questions: 89 sites sampled in summer 2004 –For sieve questions: 89 sites sampled in summer 2004 64 EMAP 1999 sites (Process 0.5 mm fractions) 103+ sites have existing data for San Francisco Bay and Marina Del Rey

14. Task 5: Develop QA Procedures Sample processing and taxonomy affect assessment results – Recovery of organisms from samples – Accuracy of taxonomy and enumeration QA approach will build on successful models – EMAP, SCBPP, Bight’98, Bight’03 and SCAMIT Procedures will address three areas – Sorting (organism recovery) – Accuracy of counts – Accuracy of identifications

15. Schedule TaskActivity or DeliverableCompletion Date 1: Refine Benthic Tools 1.1 Data available 1.2 Data analysis October 2004 January 2005 2: Evaluate Benthic Tools 2.1 Data analysis 2.2 Develop application strategy May 2005 June 2005 3: Identify Natural Assemblages 3.1 Data available 3.2 Data analysis 3.3 Results summary September 2004 December 2004 January 2005 4: Evaluate Field Methods 4.1 Data available 4.2 Data analysis February 2005 May 2005 5: Develop QA protocols 5.1 Develop QA ProgramJune 2005