Draft Data - Do not cite or quote Spatial and temporal patterns in food web accumulation of Hg EEPS Five Year Workplan Presentation to Exposure and Effects

Draft Data - Do not cite or quoteDraft Data - Do not cite or quote

Spatial and temporal Spatial and temporal patterns in food web patterns in food web accumulation of Hg accumulation of Hg

EEPS Five Year Workplan EEPS Five Year Workplan

Presentation to Exposure and Effects Work GroupPresentation to Exposure and Effects Work Group


Talk outlineTalk outline

Review workplan Results update Questions for EEWG and Science

Advisory Panel– Questions on small fish work– Other potential studies


Five Year Workplan: Five Year Workplan: Specific questions to Specific questions to addressaddress1. 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?


Approach: Hg in small Approach: Hg in small fishfish Annual monitoring at 10 stations

to determine trends Spatial survey of about 40

stations Comparison of biosentinel tools

(pending first year results)– Fish vs. bivalves vs. sediment vs.

diffusive gradient thinfilm devices


Annual monitoring of Annual monitoring of trend stationstrend stations


Trend Sampling Trend Sampling LocationsLocations

Alviso Slough

Newark Slough

Bird Island/Steinberger Slough

Eden Landing

China Camp

Benicia Park

Control

Impact (Restoration)Point Isabel

CandlestickPoint

Hamilton

Oakland Middle Harbor


Trend analysis – a Trend analysis – a multiple station BACI multiple station BACI designdesign

0

0.05

0.1

0.15

0.2

0.25

0.3

1 2 3 4 5 6 7 8 9

Year

Mer

cury

Con

cent

ratio

ns Control 1

Impact 1

Control 2

Impact 2

Control 3

Impact 3

Control 4

Impact 4


Spatial surveySpatial survey

Targeting 40 locationsTargeting 40 locations Multiple interrelated factorsMultiple interrelated factors

A.A. Land use, land cover, and Hg Land use, land cover, and Hg sourcessources

B.B. Spatial location in BaySpatial location in Bay

C.C. Subtidal hydrology and bathymetrySubtidal hydrology and bathymetry

D.D. Sediment physical and chemical Sediment physical and chemical parametersparameters


Results updateResults updatePreliminary results from 2005 and Preliminary results from 2005 and 20062006

Spatial patternsSpatial patterns Interannual trendsInterannual trends Focusing on topsmelt and Focusing on topsmelt and

Mississippi silverside (most Mississippi silverside (most complete spatial coverage)complete spatial coverage)


0 20Miles

Mississippi silverside 2005

Hg

(ug/

g w

et)

0.05

0.1

0.15

0.2

Hg

wet

weig

ht

(g

/g)

Mississippi Silverside 2006

0 20Miles

Hg

(ug/

g w

et)

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

2005 elevated in 2005 elevated in southern stations southern stations (significant)(significant)

2006 elevated in Pt. 2006 elevated in Pt. Isabel (significant)Isabel (significant)

Spatial patternsSpatial patterns


0 20Miles

Topsmelt 2005

Hg

(ug/

g w

et)

0.028

0.03

0.032

0.034

0.036

0.038

0.04

0.042

0.044

0.046

0.048

Topsmelt 2006

0 20Miles

Hg

(ug/

g w

et)

0.025

0.03

0.035

0.04

0.045

0.05

0.055

2005 elevated in 2005 elevated in southern stations southern stations (not significant)(not significant)

2006 elevated in 2006 elevated in southern stations, southern stations, Pt. Isabel, and Pt. Isabel, and Tiburon Tiburon (significant)(significant)


Potential Potential explanations for explanations for spatial patterns:spatial patterns:– High sediment High sediment

MeHg in MeHg in southern southern stations, stations, TiburonTiburon

– Suggests Suggests linkage: fish vs. linkage: fish vs. sediment MeHgsediment MeHg

– Suggests spatial Suggests spatial gradientgradient

Source: RMP


ALVSL

BENPK

CHINA

EDENL

NEWSL

STATION

0.0

0.1

0.2

0.3H

GW

W

20062005

YEAR

•Station effect•Year effect•Interaction term

Interannual trendsInterannual trendsMississippi silversideMississippi silverside


Least Squares Means

ALVSL

BENPKCHIN

A

EDENL

NEWSL

STATION

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

LOG

HG

DW

Station effectStation effect


Least Squares Means

ALVSL

2005 2006YEAR

-1.0

-0.5

0.0

0.5

1.0

LO

GH

GD

W

BENPK

2005 2006YEAR

-1.0

-0.5

0.0

0.5

1.0

LO

GH

GD

W

CHINA

2005 2006YEAR

-1.0

-0.5

0.0

0.5

1.0

LO

GH

GD

W

EDENL

2005 2006YEAR

-1.0

-0.5

0.0

0.5

1.0

LO

GH

GD

W

NEWSL

2005 2006YEAR

-1.0

-0.5

0.0

0.5

1.0

LO

GH

GD

W

Year effect and Year effect and interactioninteraction

2006 generally lower than 2005


ALVSL

BIRDI

EDENL

NEWSL

OMHEA

STATION

0.02

0.03

0.04

0.05

0.06

0.07

0.08H

GW

W

20062005

YEAR

•Station effect•Year effect2006 higher than 2005!

Interannual trendsInterannual trendsTopsmeltTopsmelt


Results update Results update summarysummary Ability to detect significant spatial Ability to detect significant spatial

variationvariation– South Bay, Tiburon, Pt. Isabel appear South Bay, Tiburon, Pt. Isabel appear

elevatedelevated Substantial interannual variationSubstantial interannual variation

– Topsmelt and silverside “seeing” Topsmelt and silverside “seeing” different MeHg signalsdifferent MeHg signals

– Subtle treatment effects likely missedSubtle treatment effects likely missed Biosentinels sensitive to changesBiosentinels sensitive to changes



Questions to Advisory Questions to Advisory Panel Design Panel Design considerationsconsiderations

1.1. Habitat types: Bay margins vs. Habitat types: Bay margins vs. wetlands and salt pondswetlands and salt ponds

2.2. Design – probabilistic vs. gradients Design – probabilistic vs. gradients and factorsand factors

3.3. Collection of additional parametersCollection of additional parameters


1. Collection of additional 1. Collection of additional habitatshabitats

Small fish sampling has focused on Small fish sampling has focused on Bay margins (foreshore)Bay margins (foreshore)

Limited sampling on wetlands and salt Limited sampling on wetlands and salt pondsponds– Area of avian wildlife riskArea of avian wildlife risk– Greater variability in MeHgGreater variability in MeHg– May provide clues as to sourcesMay provide clues as to sources

Question to Science Advisory Panel: Question to Science Advisory Panel: What percent of budget allocation to What percent of budget allocation to margins vs. wetlands and salt ponds?margins vs. wetlands and salt ponds?




2. Design – probabilistic vs. 2. Design – probabilistic vs. gradients and factorsgradients and factors

Gradient and factor designGradient and factor design– Select specific attributes expected to be Select specific attributes expected to be

important for Hg exposureimportant for Hg exposure– Allows for explicit hypothesis testingAllows for explicit hypothesis testing


Probabilistic designProbabilistic design– Following EPA Generalized Random Tessellation Stratified Following EPA Generalized Random Tessellation Stratified

(GRTS) or some other Spatially-Balanced Survey Design(GRTS) or some other Spatially-Balanced Survey Design– Bay margin samples chosen along a line tracking bay shorelineBay margin samples chosen along a line tracking bay shoreline– Ensure selection of representative conditionsEnsure selection of representative conditions– Determine gradient of relevant parameters for selected sitesDetermine gradient of relevant parameters for selected sites


Question to Advisory PanelQuestion to Advisory Panel– Which design (factor vs. probabilistic) more Which design (factor vs. probabilistic) more

appropriate for this project?appropriate for this project?


3. Collection of additional 3. Collection of additional parametersparameters

Aimed at better understanding mechanisms Aimed at better understanding mechanisms for spatial variation in bioavailable Hgfor spatial variation in bioavailable Hg

Trade off is reduced number of stationsTrade off is reduced number of stations Potential parameters:Potential parameters:

– Sediment parameters: redox, TOC, grain size, Sediment parameters: redox, TOC, grain size, MeHgMeHg

– Water parameters: TSS, nutrients, chlorophyll Water parameters: TSS, nutrients, chlorophyll – Bathymetry and hydrology: more detailed Bathymetry and hydrology: more detailed

bathymetric profile and water retention time databathymetric profile and water retention time data– MeHg via Diffusive Gradient Thinfilm devicesMeHg via Diffusive Gradient Thinfilm devices

Recommendation for Advisory Panel to Recommendation for Advisory Panel to consider – collect ancillary parameters for consider – collect ancillary parameters for subset of 20 - 30 stationssubset of 20 - 30 stations


Questions – shifts in Questions – shifts in emphasisemphasis

1.1. Including other contaminants in Including other contaminants in small fish surveyssmall fish surveys

2.2. Studies of food web contaminant Studies of food web contaminant uptakeuptake


Inclusion of other contaminants Inclusion of other contaminants in small fish surveysin small fish surveys

Current workplan focuses on MeHgCurrent workplan focuses on MeHg– Top management priorityTop management priority– Uncertainty of food-web uptake hotspotsUncertainty of food-web uptake hotspots– Not well characterized by other RMP Not well characterized by other RMP

analysesanalyses– Cost leverage (analytical costs ~10x less)Cost leverage (analytical costs ~10x less)

Recommendation for Advisory Panel to Recommendation for Advisory Panel to consider – not include other consider – not include other contaminants in surveyscontaminants in surveys


Studies on mechanisms of Studies on mechanisms of contaminant uptake into food webcontaminant uptake into food web

Topics that could be evaluated:Topics that could be evaluated:– Food-web structureFood-web structure– Relative role of sediments vs. the Relative role of sediments vs. the

water column as transport pathways water column as transport pathways of contaminants to biotaof contaminants to biota

– Spatial areas that biosentinel Spatial areas that biosentinel species integratespecies integrate

– Spatial variation in food-webs Spatial variation in food-webs diet diet

Contaminant uptake

Currently, not in work plan or anywhere in RMP


Source: Bridges et al. 2006



Available ApproachesAvailable Approaches

Review literature and local data from other Review literature and local data from other agenciesagencies

Dietary analysis of predators (current Dietary analysis of predators (current studies)studies)

Stable isotope analysisStable isotope analysis Food web and contaminant modelingFood web and contaminant modeling

– Linkage to contaminant fate and transport modelsLinkage to contaminant fate and transport models– Models of spatial movement of contaminants in Models of spatial movement of contaminants in

fishes and other biotafishes and other biota


Examples of results:Examples of results:1. PCBs in shiner perch as a function 1. PCBs in shiner perch as a function of spatial variation in dietof spatial variation in diet

Source: Gobas, F. A. P. C., and J. Wilcockson. 2002. San Francisco PCB food-web model. RMP Technical Report SFEI Contribution #90

Draft Data - Do not cite or quoteDraft Data - Do not cite or quoteSource: Greenfield, B. K., A. R. Melwani, J. J. Oram, and S. M. Bay. 2007. Indicator development and framework for assessing indirect effects of sediment contaminants. SFEI Contribution #524

Examples of results:Examples of results:2. Water vs. sediment contribution of 2. Water vs. sediment contribution of PCBsPCBs

Draft Data - Do not cite or quoteDraft Data - Do not cite or quoteSource: Greenfield, B. K., J. A. Davis, C. Roberts, R. Fairey, M. A. Sigala, and J. Negrey. 2002. The relationship between trophic position, spatial location, and contaminant concentration for San Francisco Bay sport fish: a stable isotope study. Unpublished manuscript

15 N

2 4 6 8 10 12

Mer

cury

( g

/g w

et)

0.0

0.2

0.4

0.6

0.8

= Jacksmelt= Shiner Surfperch= White Croaker= Striped Bass= Halibut= White Sturgeon

Examples of results:Examples of results:3. Stable isotope (trophic position) vs. 3. Stable isotope (trophic position) vs. Hg in sport fishHg in sport fish


Question to Advisory Question to Advisory Panel Panel

Should we incorporate studies on Should we incorporate studies on mechanisms of food web mechanisms of food web contaminant uptake?contaminant uptake?– Currently no effortCurrently no effort– Could allocate 10 – 20% of effort to Could allocate 10 – 20% of effort to

process studies (isotopes/diet process studies (isotopes/diet analyses) and modelinganalyses) and modeling


Summary of questions to Work Summary of questions to Work Group and Advisory Panel Group and Advisory Panel (spatial and temporal patterns in food web (spatial and temporal patterns in food web accumulation)accumulation)

What percent of budget allocation to margins vs. What percent of budget allocation to margins vs. wetlands and salt ponds?wetlands and salt ponds?

Which design (factor vs. probabilistic) more Which design (factor vs. probabilistic) more appropriate for this project?appropriate for this project?

Do you agree with recommendation to collect Do you agree with recommendation to collect ancillary parameters on subset of stations?ancillary parameters on subset of stations?

Do you agree with recommendation not to include Do you agree with recommendation not to include other contaminants in small fish sampling?other contaminants in small fish sampling?

Should some effort (e.g., 10-20% of budget) be Should some effort (e.g., 10-20% of budget) be allocated towards studying processes of food web allocated towards studying processes of food web uptake?uptake?

Documents

Draft Data - Do not cite or quote Spatial and temporal patterns in food web accumulation of Hg EEPS Five Year Workplan Presentation to Exposure and Effects