Benthic Community Assessment Tool Development

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Benthic Community Assessment Tool Development
Sediment Quality Objectives for California Bays
and Estuaries

• Ananda Ranasinghe (Ana)
• Southern California Coastal Water Research
  Project (SCCWRP)
• anar_at_sccwrp.org

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Outline

• Background Why Benthic Communities?
• Approach
• Refine and Validate Benthic Indicators
• Evaluate Field and Laboratory Methods
• Task Details and Schedule

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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 1990s
• 301(h) waivers granted to dischargers
• Toxic hotspot cleanup decisions in San Diego Bay

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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

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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. EPAs guidance for
  biocriteria development

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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

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Refine And ValidateBenthic 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

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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

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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

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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

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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

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Task 4 Evaluate Field MethodsWhy?

• Sampling gear affects benthic assessments
• Larger gear collect more species and organisms
• Smaller sieves catch
• More and smaller species
• More organisms that cant be identified to
  species
• Three gears and two sieves are used in California
• Gears
• 0.1m2 Van Veen grab
• 0.05 m2 Van Veen grab
• 0.00785 m2 corer
• Sieves
• 1.0 mm or 0.5 mm apertures

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Task 4 Evaluate Field MethodsApproach 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

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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, Bight98, Bight03 and SCAMIT
• Procedures will address three areas
• Sorting (organism recovery)
• Accuracy of counts
• Accuracy of identifications

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Schedule
Task Activity or Deliverable Completion 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 Program June 2005