Spatial and temporal patterns in food web accumulation of Hg Project Update RMP Contaminant Fate Work Group Jan. 15, 2008

RMP Organizational Structure Mike Stenstrom Barbara Mahler Eric Stein Joel Baker Frank Gobas Keith Stolzenbach Rob Mason Steve Weisberg Don Weston Harry Ohlendorf Michael Fry Dan Schlenk David Sedlak Derek Muir Jen Fields Program Review Panel

Talk outline Results update Review workplan

Results update Preliminary results from 2005 and 2006 Spatial patterns Interannual trends Focusing on topsmelt and Mississippi silverside (most complete spatial coverage)

Hg wet weight ( g/g) 2005 elevated in southern stations (significant) 2006 elevated in Pt. Isabel (significant) 2006 elevated in Pt. Isabel (significant) Spatial patterns

Spatial patterns including salt pond data Includes data provided by C. Eagles-Smith and J. Ackerman

2005 elevated in southern stations (not significant) 2006 elevated in southern stations, Pt. Isabel, and Tiburon (significant) 2006 elevated in southern stations, Pt. Isabel, and Tiburon (significant)

Potential explanations for spatial patterns: –High sediment MeHg in southern stations, Tiburon –Suggests linkage: fish vs. sediment MeHg –Suggests spatial gradient Source: RMP

Sediment MeHg may be correlated with topsmelt Hg Topsmelt 2006 data RMP and Calfed sediment data within 1.5 km disk of fish R 2 = 0.61

Station effect Year effect Interaction term not significant Interannual trends Mississippi silverside

Station effect

Year effect 2006 higher than 2005! Interannual trends Topsmelt

Relative importance of station vs. year effect

Results update summary Ability to detect significant spatial variation –South Bay, Tiburon, Pt. Isabel appear elevated –Salt pond stations higher than Bay stations (silverside) Substantial interannual variation –Topsmelt and silverside seeing different MeHg signals –Subtle treatment effects likely missed Biosentinels sensitive to changes

Workplan: Specific questions to address 1.Where is mercury entering the Bay food web? 2.What habitats, conditions, or factors help to identify hotspots of food web accumulation in Bay margins? 3.Are there interannual trends in MeHg bioaccumulation resulting from wetland and margin restoration activities? 4.What are the best biomonitoring tools for characterizing hotspots of MeHg bioaccumulation?

Recent survey decisions Regional Board Requests: –Hypothesis testing approach –Coordinate sampling with South Bay Mercury Project –Focus more on spatial analysis than long- term trend detection –Add a seasonal variation component

Approach: Hg in small fish Spatial survey of about 40 stations –75% of effort Annual monitoring at 8 stations to determine trends –10% of effort Monthly monitoring at 2 stations to determine seasonal variation –10% of effort Comparison of biosentinel tools (pending first year results) –Fish vs. bivalves vs. sediment vs. diffusive gradient thin film devices –5% of effort

Spatial survey Targeting 40 locations Multiple interrelated factors A.Land use, land cover, and Hg sources B.Spatial location in Bay C.Subtidal hydrology and bathymetry D.Sediment physical and chemical parameters

Spatial survey potential design Focus on four types of location – test hypothesis of effect Include spatial gradient from North to South Bay Also consider subtidal bathymetery/hydrology Focus on topsmelt and Mississippi silverside Land Use/Land CoverN BayS Bay Wetlands5 sites Urban outfall5 sites POTW into slough/marsh5 sites Control (upland, residential, no discharges) 5 sites

Potential sampling locations – E.g., POTW outfalls: –Fairfield-Suisun –Palo Alto –Sunnyvale –San Jose

Coordinate with SBMP sites: Improve understanding of wetland – Bay linkages Marsh fish Brine flies Song sparrows Topsmelt Silversides

Trend analysis – a multiple station BACI design

Trend Sampling Locations Alviso Slough Newark Slough Bird Island/ Steinberger Slough Eden Landing China Camp Benicia Park Control Impact (Restoration) Point Isabel Candlestick Point Hamilton Oakland Middle Harbor

Trend Sampling Locations Alviso Slough Newark Slough Bird Island/ Steinberger Slough Eden Landing China Camp Benicia Park Control Impact (Restoration) Point Isabel Candlestick Point Hamilton Oakland Middle Harbor

Monthly sampling locations Martin Luther King Shoreline Additional North Bay Station Sampled by USFWS

MLK Shoreline Location

Collection of additional parameters Aimed at better understanding mechanisms for spatial variation in bioavailable Hg GIS spatial parameters Sediment parameters

GIS spatial parameters Parameter TypeHypothesized mechanism of influence Water residence timeWater dilution and replacement and sediment advective transport may cause net loss of Hg or MeHg, and redox conditions Distance to nearest POTW and nearest storm drain discharge Loading of Hg and MeHg, as well as nutrients, fine particulates, influencing methylation potential Number of storm drains feeding into inlet (for urban stormwater outfall sites) As above. Distance to creeks and tributariesAs above. Also, movement of fish upstream to conditions favoring methylation. LatitudeLonger residence time in South Bay favoring reduced conditions and consequent methylation. Average depth near siteHigh biotic activity and repeated wetting and drying at shallow sites favoring bacterial methylation activity. Abundance of intertidal mudflat near site As above. Nearby Land Cover/Land UsesMultiple potential mechanisms

Sediment parameters Sediment parameters: redox, TON, grain size, total and methyl Hg Duplicate sediment samples at subset of 20 stations

Sediment MeHg: < 1 ng/g 1 – 2 ng/g > 2 ng/g

Sediment MeHg may be correlated with topsmelt Hg Topsmelt 2006 data RMP and Calfed sediment data within 1.5 km disk of fish R 2 = 0.61

Questions for the Workgroup Is the general approach appropriate? –Indicators selected –Allocation of effort to spatial vs. interannual vs. monthly vs. tool comparison Spatial survey design –Hypothesis testing approach –Sampling sites (wetlands, POTWs) Trend sampling –Annual sampling sites –Monthly sampling sites Additional parameters –Sediment parameters

Annual monitoring of trend stations