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Mercury and Methylmercury Processes in North SF Bay Tidal Wetland EcosystemsSan Francisco Estuary InstituteUSGS BRD WERC Vallejo, CA USGS WRD Menlo Park, CAUSGS WRD Middleton, WIAvocet Research Associates
Background: The Good?Tidal wetland restoration plans
Adding 12,000+ acres North Bay
Tidal wetlandsHabitat for threatened & other wildlife
Wetland restoration = good
but…
The Bad?Mercury (Hg) already in Bay-Delta biota @ levels of concern
human & wildlife health
Hg in biota correlates to watershed % wetlands
Mostly freshwater systemsSimilar in tidal marshes?
Attractive nuisance?Wildlife check in, but …? x
Species
Cal
iforn
ia H
alib
ut
Jack
smel
t
Leop
ard
Sha
rk
Shi
ner
Sur
fper
ch
Str
iped
Bas
s
Whi
te C
roak
er
Whi
te S
turg
eon
Hg
(ug/
g w
et
wei
ght)
0.0
0.5
1.0
1.5
2.0
2.5
The Ugly?Not just a matter of reducing Hg…
0.0
0.5
1.0
1.5
2.0
2.5
0.00 0.20 0.40 0.60 0.80 1.00
Hg mg/kg dw
MeH
g µ
g/k
g d
w
2002
2003
2004 y = 1.06x + 0.23
R2 = 0.067
What (Me)Hg Worry? Not just Hg, need to worry about reducing methylmercury (MeHg)
Most bioaccumulative formFormed by sulfate reducing bacteria under reducing conditions
But is subject to degradation- MicrobialAbiotic (photolytic)
Ask Questions First(Me)Hg in wetlands: where, when, how much?What influences (Me)Hg distribution & production?How does (Me)Hg accumulate in tidal wetland food webs?How does (Me)Hg get there: wetlands to bay (or vice versa)?
Approach: GeneralSpatial distribution of (Me)Hg (water, sediments, biota)
Differences in (Me)Hg concentrationsDifferences in (de)methylation processes
Temporal distributionSeasonal differences in methylation rates and concentrations
Spatial Distribution3 wetlands along Petaluma River
Gambinini Ranch(Mid-)Petaluma MarshBlack John Slough
Salinity gradient along Petaluma main stem
Petaluma Marsh North
Black John Slough
Gambonini Ranch
Petaluma Marsh North
Black John Slough
Gambonini Ranch
Spatial DistributionWithin wetlands: habitat elements
Medium channels (2nd-3rd order)High marsh plain
Transect composites (some grabs)Replicates of habitat elements
Food WebCharismatic Critter: California Black Rail (USGS-BRD CA) - capture, tag, track
Identify distribution, habitat use, range, diet
BioaccumulationExamine (Me)Hg in biota:
High marsh food web:Hg in California Black Rails (blood, feathers)(Me)Hg in probable/potential diet items
Channel biota food webChannel fish and invertebrates to compare
MeHg Processes Sediment processes (USGS-Menlo Park CA)
(De)Methylation rates in channel and high marsh
Lab incubations of sediment composites
Microbially available (reactive) HgSediment quality (sulfur, carbon)
Water processes (USGS-Middleton WI)
Demethylation ratesPhoto-incubation experiments
Results: Hg DistributionSediment Hg similar @ all sites
>>ancient Hg levelscomparable to Bay sediments
High marsh < channel
0
50
100
150
200
250
300
350
400
BJS MP GAM
Hg
(ng/
g)
High Marsh
Slough
Sediment MeHg DistributionHigh marsh
Highest at mid-Petaluma
Channel MeHgOpposite of salinity gradient< high marsh
0
1
2
3
4
5
6
7
8
9
BJS MP GAM
MeH
g (n
g/g)
High Marsh
Slough
Vertical MeHg DistributionMeHg highest in high marsh surface layers
0
2
4
6
8
10
12
14
16
18
20
0-2
5-1
0
0-2
5-1
0
15
-20
2-5
10
-15
2-5
10
-15
2-5
10
-15
0-2
5-1
0
15
-20
Depth (cm)
Co
nc
(n
g/g
dry
) BJS-HM1
BJS-HM2
GAM-HM1
GAM-HM2
MP-HM1
MP-HM2
Black John
Gambinini
MidPetaluma
MeHg in SedimentsNet = methylation - demethylationSediment MeHg parallels sulfate reductiony = 0.0009x + 1.1511
R2 = 0.67
0
2
4
6
8
10
0 1 2 3 4 5 6 7 8 9
SRR (mol/g dry sed/d)
Me
Hg
(ng
/g d
ryse
d)
MPGAMBJS
Figure 2. The positive relationship between microbial sulfate reduction rate (SRR) and methylmercury (MeHg) concentration during April 2005 for the three wetland regions studied. SRR data from August 2005 is pending. The best fit linear regression equation and associated r2 value is given.
y = 0.0009x + 1.1511
R2 = 0.67
0
2
4
6
8
10
0 1 2 3 4 5 6 7 8 9
SRR (mol/g dry sed/d)
Me
Hg
(ng
/g d
ryse
d)
MPGAMBJS
y = 0.0009x + 1.1511
R2 = 0.67
0
2
4
6
8
10
0 1 2 3 4 5 6 7 8 9
SRR (mol/g dry sed/d)
Me
Hg
(ng
/g d
ryse
d)
MPGAMBJS
Figure 2. The positive relationship between microbial sulfate reduction rate (SRR) and methylmercury (MeHg) concentration during April 2005 for the three wetland regions studied. SRR data from August 2005 is pending. The best fit linear regression equation and associated r2 value is given.
What Drives Sediment MeHg?Sulfate reducing bacteria need food!
% LOI versus % Total as MethylmercuryTop 2 cm of Sediment
R2 = 0.7452
0
5
10
15
20
25
30
0 1 2 3 4 5 6 7 8
% Total as Methyl
% L
OI
(Me)Hg in WaterWater MeHg similar to channel sediments
MeHg lowest near Bay end of PetalumaMeHg & Hg mostly (80%+) in particulate phase
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
BJS MP GM
Filt
ere
d H
g n
g/L
2005-Apr
2005-Aug
0
0.05
0.1
0.15
0.2
0.25
BJS MP GM
Pa
rtic
ula
te M
eH
g (
ng
/L)
0
5
10
15
20
25
30
Pa
rticula
te H
g (n
g/L
)
MeHg
HgT
Where do Biota Fit?Are black rails in areas w/ high MeHg?
Small ranges (avg .24ha) in spring
Black John Slough Mid Petaluma
Habitat UsagePrimarily in high marsh pickleweed
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Salicornia Scirpus Distichlis Grindelia Other Bare
Pe
rcen
t co
ver
Black John Slough
Petaluma Marsh
Gambonini Marsh
Does It Add Up?
0
1
2
3
4
5
6
7
8
9
BJS MP GAM
MeH
g (n
g/g)
High MarshSlough
High Marsh sediment MeHg ~2x higher Mid-PetalumaMeHg is bioaccumulative form of Hg
Black Rail (Feather) HgBlack rails reside and feed in high marsh,
therefore…Rail Hg differs among wetlands (Mid-Petaluma
~2x)
0
2
4
6
8
10
12
Black John Slough Petaluma Marsh Gambinini Marsh
[TH
g]
(mg
/kg
)
Implications for ManagementMP feather Hg up to 10ng/g, is it bad?
Other birds “background” in feather ~1-5ng/g
Can we do anything about it?Less (or more) reducing conditions?Less organic matter?
Other goals and priorities?(Me)Hg not the only factorNewer marsh Hg < ancient marsh (problem in 2000 years?)
Closing CreditsFunding: CBDA Ecosystem Restoration Program grant
ERP-02D-P62Site Access: CDFG, the PhelansProject Partners:
SFEI: (Don Yee), Josh Collins, Letitia Grenier, S. PearceUSGS WRD-CA: Mark Marvin-DiPasquale, Jennifer Agee, Le Kieu, Nick Ladizinski, Lisa WindhamUSGS WRD-WI: Dave Krabbenhoft, Shane Olund, Tom SabinUSGS BRD- John Takekawa, Isa Woo, Danika Tsao-MelcerAvocet Associates: Jules Evens