Spatial and temporal patterns in food web accumulation of Hg
Project UpdateRMP Contaminant Fate Work Group Jan. 15, 2008
S o u rce s,P a th w a ys,
a n d L o a d in gsW o rkg ro up
C o n ta m in a n tF a te
W o rkg ro up
E xp o su rea n d E ffe c tsW o rkg ro up
E m e rg ingC o n ta m in a n ts
W o rkg ro up
M e rcu ryG ro up
T e ch n ica l R e v ie wC o m m ittee
S te e ring C o m m ittee
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 updatePreliminary results from 2005 and 2006
• Spatial patterns
• Interannual trends
• Focusing on topsmelt and Mississippi silverside (most 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 southern stations (significant)
2006 elevated in Pt. 2006 elevated in Pt. Isabel (significant)Isabel (significant)
Spatial patterns
Spatial patterns including salt pond data
Includes data provided by C. Eagles-Smith and J. Ackerman
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 southern stations (not significant)
2006 elevated in 2006 elevated in southern stations, southern stations, Pt. Isabel, and Pt. Isabel, and Tiburon Tiburon (significant)(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
0.5 1.0 1.5 2.0 2.53.03.5
MeHg in sediment (ng/g)
0.02
0.03
0.04
0.05
0.06
0.070.08
Hg
in f
ish
(u
g/g
)
•Topsmelt 2006 data
•RMP and Calfed sediment data within 1.5 km disk of fish
•R2 = 0.61
ALVSL
BENPK
CHINA
EDENL
NEWSL
STATION
0.0
0.1
0.2
0.3H
GW
W
20062005
YEAR
•Station effect•Year effect•Interaction term not significant
Interannual trendsMississippi 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 effect
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 trendsTopsmelt
Relative importance of station vs. year effect
Species Station R2 Year R2Station/Year
Topsmelt 0.30 0.43 0.7Mississippi Silverside 0.58 0.05 11.6
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 factorsA. 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 Cover N Bay S Bay
Wetlands 5 sites 5 sites
Urban outfall 5 sites 5 sites
POTW into slough/marsh 5 sites 5 sites
Control (upland, residential, no discharges)
5 sites 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 fishBrine fliesSong sparrows
TopsmeltSilversides
Trend analysis – a multiple station BACI design
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
Trend Sampling Locations
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 Sampling Locations
Alviso Slough
Newark Slough
Bird Island/Steinberger Slough
Eden Landing
China Camp
Benicia Park
Control
Impact (Restoration)Point Isabel
CandlestickPoint
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 parametersParameter Type Hypothesized mechanism of influence
Water residence time Water 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 tributaries As above. Also, movement of fish upstream to conditions favoring methylation.
Latitude Longer residence time in South Bay favoring reduced conditions and consequent methylation.
Average depth near site High 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 Uses Multiple potential mechanisms
Sediment parameters
• Sediment parameters: redox, TON, grain size, total and methyl Hg
• Duplicate sediment samples at subset of 20 stations
-122.6 -122.3 -122.0 -121.7Longitude
37.4
37.5
37.6
37.7
37.8
37.9
38.0
38.1
38.2La
titud
e
-3-2-1012
LOGMEHG
0.00.51.01.52.02.5
MEHG_HIGH1
Sediment MeHg: < 1 ng/g 1 – 2 ng/g > 2 ng/g
Sediment MeHg may be correlated with topsmelt Hg
0.5 1.0 1.5 2.0 2.53.03.5
MeHg in sediment (ng/g)
0.02
0.03
0.04
0.05
0.06
0.070.08
Hg
in f
ish
(u
g/g
)
•Topsmelt 2006 data
•RMP and Calfed sediment data within 1.5 km disk of fish
•R2 = 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
0.5 1.0 1.5 2.0 2.53.03.5
SEDIMENT
0.02
0.03
0.04
0.05
0.06
0.070.08
FIS
H
SQ
Pt Isabel
Tiburon
Alviso
Newark
Oakland Harb
Treasure Isl
China Camp
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