impacts of multiple stressors on fish in saginaw bay...impacts of multiple stressors on fish...
TRANSCRIPT
Impacts of Multiple Stressors on Fish Production in Saginaw Bay
Adaptive Integrated Framework (AIF): a new methodology for
managing impacts of multiple stressors in coastal ecosystems
Tomas Hook, Steve Pothoven, Lori Ivan, Charles Roswell, Hank Vanderploeg, Tom Nalepa, and Tammy Newcomb
Yellow perch
Walleye
Percids in Saginaw Bay
Historically second largest commercial
fishery in Great Lakes.
Walleye collapse ~1950 due to
eutrophication, over‐fishing, invasive
species, etc.
Recent collapse of L. Huron alewives has
led to improved reproductive success,
but poor growth and long‐term
survival.
Fielder and Thomas 2006 MI‐DNR; Fielder et al. 2007 JGLR
Percid Production Requires a Balance Within the Ecosystem
Yellow perch
ZooplanktonBenthic invertebrates
Invasive Species
Moderate temperatures
Mesotrophic conditions
Balance between sufficient
pelagic and benthic prey
Adaptive Integrative Framework (AIF)
Modeling synthesis
Ecosystemdrivers
Ecosystem characterization (data)
Scientific evaluation
&Stakeholderassessment
B) Guidance for future management actions
A) Guidance for future empirical efforts
Manager Workshop (Winter 2008) 5 Research Priorities
1a‐b) Walleye and yellow perch recruitment dynamics (early life factors affecting survival to later age…incl. habitat effects)
2a) Ecological connections between Saginaw Bay and Lake Huron
2b) Suitability of SB for lake herring
2c) Fish community dynamics
Saginaw Bay AIF
Coupled bio-physical 3D
models
Empirically based
(Bayesian)
Simple statistical (e.g.
regression)
Artificial Neural
network
EcosystemStressors
Ecos
yste
m
Mod
els
Ecosystem Characterization
Fish community dynamics
Water quality &
Human health
Ecos
yste
m
endp
oint
s
• Land & Resource use
• Climate Change• Invasive Species
• Watershed model• Hydrodynamic model• Biophysical data and
processes
Recommendations for ecosystem characterization•Experimental•Monitoring•Synthesis
Socio-economic integration to guide management•Economic models•Public preference •Workshops
Dynamic Factor Analysis
• Dimension reduction technique– Models N observed time series with M common
trends• For Q1
– N = Species in Sag Bay– M = Selected by user
• For Q2– N = Space– M = Selected by user
– Select between models with AIC & validation
Gill Net Data Sets
MI‐DNR Gillnet data
Preliminary Dynamic Factor Analysis of MI‐DNR Gillnet Data (1994‐20008):
Carp
Channel_Catf ish
Freshw ater_drum
Gizzard_shad
Longnose_gar
Northern_PikeNorthern_redhorse
Quillback
Walleye
White_bassWhite_perch
White_sucker
Yellow _perch
factor loadings axis 1-0.2 0 0.2
fact
or lo
adin
gs a
xis
2
-0.2
0
0.2
Time1995 2000 2005
Y
-4
-2
0
2
Time1995 2000 2005
Y
-1
0
1
Time1995 2000 2005
Y
-1
0
1
Time1995 2000 2005
Y
-2
-1
0
1
Time1995 2000 2005
Y
-1
0
1
2
Walleye
Yellow perch
Carp
Freshwater drum
Preliminary Dynamic Factor Analysis of MI‐DNR Trawl Data (1970‐2008):
Time1970 1980 1990 2000
Y
-1
0
1
2
Time1970 1980 1990 2000
Y
-1
0
1
2
Yellow perch
Walleye
Coupled 3‐D process –based models
• Saginaw Bay Ecosystem Model (SAGEM)– Deterministic, process‐based model
– Phytoplankton model first developed in 1970’s
– Updated to include:• Multi‐class phytoplankton
• Zebra mussel bioenergetics
• PCB fate, transport and lower food web bioaccumulation
• Benthic algae productivity
– Latest version: Bierman et al. 2005 JGLR 2005
• Will be coupled to fish individual‐based model
Next Individual
Add new individuals
Forageƒ(fish size, temperature, prey densities,
water clarity)
Respire (bioenergetics)ƒ(fish size, temperature, food consumed)
Predation Mortalityƒ(fish size, current location)
Starvation Mortalityƒ(fish size, % storage tissue)
Move?ƒ(fish size, current location)
Next Day
Loop through individuals
Saginaw Bay AIF
Coupled bio-physical 3D
models
Empirically based
(Bayesian)
Simple statistical (e.g.
regression)
Artificial Neural
network
EcosystemStressors
Ecos
yste
m
Mod
els
Ecosystem Characterization
Fish community dynamics
Water quality &
Human health
Ecos
yste
m
endp
oint
s
• Land & Resource use
• Climate Change• Invasive Species
• Watershed model• Hydrodynamic model• Biophysical data and
processes
Recommendations for ecosystem characterization•Experimental•Monitoring•Synthesis
Socio-economic integration to guide management•Economic models•Public preference •Workshops
2008 Field Season
Pilot field season
Benthic invertebrate and zooplankton sampling
Black dot:Ponar samples for total benthos(1987 and 1988)
Circled black dot:Ponar samples for total benthos(1987‐1996)
X:diver samples for zebra mussels(1991‐1996)
Location of sites sampled for benthos in 1987‐1996.
Source: Tom Nalepa
Ponar samples for total benthos(2007 and 2008)
diver samples for dreissenids(Fall 2008)
Location of sites sampled for benthos in 2007‐2008.
Source: Tom Nalepa
triplicate Ponar samples in spring,
summer, and fall
Dreissenid densities
(Means ± SE)
(Inner Bay Stations 11, 13 ,14,16)
Tom Nalepa
Manager Workshop (Winter 2008) 5 Research Priorities
1a‐b) Walleye and yellow perch recruitment dynamics (early life factors affecting survival to later age…incl. habitat effects)
2a) Ecological connections between Saginaw Bay and Lake Huron
2b) Suitability of SB for lake herring
2c) Fish community dynamics
Primary 2009 Plans1a‐b) Walleye and yellow perch recruitment dynamics (early life
factors affecting survival to later age…incl. habitat effects)
Track young walleye and perch from hatch through the next spring in both nearshore
and offshore habitats.
Characterize habitats, prey base, and predator fields.
Goal to identify bottlenecks to growth and survival (predation, overwinter mortality).
Provide data for model development and application.
Fish Analyses
Empirical analyses should also contribute towards other objectives.
2a) Ecological connections between Saginaw Bay and Lake Huron
2b) Suitability of SB for lake herring
2c) Fish community dynamics
These objectives are also being addressed through model analyses and coordination with other
researchers.