The Influence of Natural and Anthropogenic Perturbations on
Lake Riparian Forest and Coarse Woody Debris
Modeling Linkages Between Aquatic and Terrestrial Ecosystems
September 26, 2002
Greg Sass
This is a collaborative effort!
• NSF-Biocomplexity Project• Dr. Monica Turner• Dr. Stephen Carpenter• Isaac Kaplan, Anna Sugden-Newbery, Anthony
Yannarell, Theodore Willis, Greg Sass• Scott van Egeren, Michelle Parara
Biocomplexity
Riparian forest, land, people, and lakes
http://limnology.wisc.edu
Click on research link, follow to biocomplexity
web page
Relationship between CWD density and shoreline development in N. Wisconsin
lakes
CWDDensity(no./km)
Shoreline DevelopmentFrom Christensen et al. 1996
-Also truefor MNmacrophytes!
Relationship between fish growth and coarse woody debris (CWD) in N. Wisconsin
lakes
logGrowthRate(mm/yr)
CWD Density (no./km)
High Development
Low Development
Undeveloped
High Development
Low Development
Undeveloped
From Schindler et al. 2000
How are changes on land and land/water interface reflected in the
adjacent lake ecosystem?
• Does the riparian forest influence fish populations?
– The riparian forest is linked to fish through Coarse Woody Debris (CWD)
CWD abundance influenced by:
• Forest structure (Harmon et al. 1986, Hely et al. 2000)
– Successional state
• Natural and anthropogenic disturbance (Christensen et al. 1996, Guyette and Cole 1999 , Hely et al 2000)
– Windthrows– Logging– Lakeshore development
Photo courtesy of Michelle Parara
Why model CWD dynamics?
• These are big systems with slow (and fast) dynamics!! Photo courtesy of Michelle Parara
923 year-old white pine in
Swan Lake, Ontario
Guyette and Cole 1999
Three Aspects Compose the Linked Terrestrial-Aquatic
Model
Terrestrial Terrestrial-AquaticInterface
Aquatic
Riparian Model Fish Model
Main Goals of the Wood Model
1. Create CWD via riparian forest that can be affected by both natural and anthropogenic processes
2. Simulate realistic CWD densities that can be used to test hypotheses/ask questions about effect of CWD on fish communities
Conceptual Structure of the Wood Model
Saplings
Adults
Snags CWD
Graduation
Trees that die and stay upright
Trees that die and fall immediately
Falling
Recruitment
Loss to decay and deep water
Falling away from water
Falling away from water
Two Pools of Trees:
• “Softwoods”– Representative of early
succession canopy– Paper birch (Betula
papyrifera), aspens (Populus spp)
• “Hardwoods”– Representative of mid-late
succession canopy– White pine (Pinus strobus),
sugar maple (Acer saccharum)
Big tooth aspen (Populus grandidentata)
Paper birch(Betula papyrifera)
White pine (Pinus strobus)
Sugar maple (Acer saccharum)
Riparian Model Formulas• SAPLINGS
Si(t+1) = Si(t) + {Ai(t)ri * (1-αjiAj(t) – αjiAi(t))} - Si(t)gi
• ADULT TREES
Ai(t+1) = Ai(t) + Si(t)gi - mi Ai(t);
• STANDING SNAGS
SSi(t+1) = SSi(t) + (1-Li) mi Ai(t) - fi SSi(t);
• COARSE WOODY DEBRIS
Di(t+1) = Di(t) + (γ fi SSi(t)) + {γ fi SSi(t) Li mi Ai(t)} - (a11 + a21) Di(t) ;
“Shading” terms
Conceptual Structure of the Wood Model
Hardwood Saplings
Adult Hardwoods
Graduation
Recruitment
Softwood Saplings
Adult Softwoods
Graduation
Recruitment
“Shading”(+) (+)
(-)(-)
Model Scenarios• Baseline Scenario
– Riparian forest density from Turner 2001 and Christensen et al. 1996
– CWD values from undeveloped Little Rock Lake in Vilas County, WI
• Windthrow Scenario– 65% instantaneous death of
hardwood and softwood adults and snags
• Clearcut Scenario– 95% instantaneous death of
hardwood and softwood adults and snags
• Development Scenario– 1% annual loss of adult
hardwoods and softwoods– 5% annual loss of Snags and
CWD
Little Rock Lake
Adult Tree and CWD Dynamics During Baseline Scenario
0
200
400
600
0 50 100 150 200 250 300 350 400 450 500Years
# L
og
s/km
sh
ore
line
0
500
1000
1500
2000
# T
ree
s/k
m S
ho
relin
e
HardwoodsSoftwoods
Adult Trees
CWD
Adult Tree and CWD Dynamics During Windthrow Scenario
0
500
1000
1500
2000
# T
ree
s/k
m S
ho
relin
e
0
200
400
600
0 50 100 150 200 250 300 350 400 450 500Years
# L
og
s/k
m s
ho
relin
e
HardwoodsSoftwoods
Adult Trees
CWD
CWD Dynamics During Windthrow Scenario
0
200
400
600
800
0 100 200 300 400 500Years
Har
dw
oo
d +
So
ftw
oo
d
CW
D/k
m S
ho
relin
e
CWD Abundance (all Trees) Following FireDisturbance
Hely et al. 2000
0
500
1000
1500
2000
# T
rees
/km
Sh
ore
lin
e
0
200
400
600
0 100 200 300 400 500
Time (years)
# L
og
s/k
m S
ho
relin
eAdult Tree and CWD Dynamics
During Clearcut ScenarioHardwoodsSoftwoods
Adult Trees
CWD
CWD Dynamics During Clearcut Scenario
0
500
1000
1500
2000
2500
0 100 200 300 400 500
Time (years)
Ha
rdw
oo
d +
So
ftw
oo
d
CW
D/k
m S
ho
relin
e
Adult Tree and CWD Dynamics During Development Scenario
0
200
400
600
0 50 100 150 200 250 300 350 400 450 500Years
# L
og
s/k
m s
ho
relin
e
0
500
1000
1500
2000
# T
ree
s/k
m S
ho
relin
e
HardwoodsSoftwoods
Adult Trees
CWD
CWD Dynamics during Development Scenario
0
200
400
600
800
0 50 100 150 200 250 300 350 400 450 500
Years
Har
dw
oo
d +
So
ftw
oo
d
CW
D/k
m S
ho
relin
e
Can the model mimic ‘real’ history?
Skidding Logs, Upper Chippewa Basin, Circa 1890
Lakeshore DevelopmentLast ~50 years
Taming the Northwoods
0
200
400
600
0 100 200 300 400 500
Time (years)
# L
og
s/k
m S
ho
relin
e
0
500
1000
1500
2000
# T
rees
/km
Sh
ore
lin
e
HardwoodsSoftwoods
Adult Trees
CWD
Clear cut Development
CWD Dynamics in Clearcut + Development Scenario
0
200
400
600
0 100 200 300 400 500
Time (years)
# L
og
s/k
m S
ho
relin
e
Summary of Wood Model
• Model is simple, but fairly realistic
• Windthrows and clearcuts have long-term effects on CWD pool
• Development a powerful force
Conclusions
• This ecosystem-level model is a useful tool for creating questions about CWD inputs/removals.– Can we devise ways to observe long-term changes in
riparian forest and CWD structure?– Does indiscriminate thinning actually occur?– How long does it take for the CWD pool to recover?– How do changes in CWD abundance affect fish
communities?
• How can we obtain answers to these questions?
Biocomplexity Cross-lakes Crew
• Led by Michelle Parara and Scott van Egeren
• Riparian forest/CWD analysis: Anna Sugden-Newbery
Modeling linkages between terrestrial
and aquatic ecosystems part II:
The influence of riparian forest dynamics on aquatic
food webs
Isaac Kaplan, Tanya Havlicek, Pieter Johnson, Brian Roth,Greg Sass, Anna Sugden-Newbery, Theodore Willis, Anthony Yannarell, Monica Turner, and Steve Carpenter
Biocomplexity
Riparian forest, land, people, and lakes
Relationship between fish growth and coarse woody debris in N. Wisconsin lakes
logGrowthRate(mm/yr)
Coarse Woody Debris Density (no./km)
High Development
Low Development
Undeveloped
High Development
Low Development
Undeveloped
From Schindler et al. 2000
Conceptual Model
Forestcoarsewoody debris
Growth
Humans
Senescence
Windthrow
Development
Decay/Physical Transport
AquaticFood Web
Fishing
Terrestrial Terrestrial-Aquaticinterface
Aquatic
Questions• How does the aquatic food web respond to
stable levels of coarse woody debris?
• How does the food web respond to perturbations?- windthrow, development, fishing
• How can we learn about effects of coarse woody debris on fish predation and growth rates in experimental lakes?
Fish biomass dynamics model
juv. piscivore
adult piscivore
benthivore
insects
Hypothesized Effects of Coarse Woody Debris on Fish Community
Insect Abundance
0
0.2
0.4
0.6
0.8
1
015
030
045
060
075
090
0
logs /km shoreline
kg
of
tric
ho
pte
ran
s +
o
do
na
tes
/ha
Response of Vulnerability and Hiding
0
0.5
1
1.5
2
0 200 400 600 800logs/km of shoreline
par
amet
er v
alu
e
vulnerability ofbenthivore
hiding ofbenthivore
vulnerability ofjuv. piscivore
hiding of juv.piscivore
Fish Model: Benthivore Biomass Equation
dB/dt=G-mB2-P2 –P3
G=fishC*g1 +BugC*g2
Bt+1=Bt-harvest
---------------------------------------------------Functional Response:
Piscivory
B1-V1 V1
B2
hiding vulnerable
v1
h1 predators
c12
Hypothesis 1:
Similar piscivore and benthivore behavioral response to logs
Response of Vulnerability and Hiding
0
0.5
1
1.5
2
0 200 400 600 800logs/km of shoreline
par
amet
er v
alu
e
vulnerability ofbenthivore
hiding ofbenthivore
vulnerability ofjuv. piscivore
hiding of juv.piscivore
Fish Biomass at Steady State
0
5
10
15
20
25
30
35
50 500 1000 500 andfishing
kg/ h
ecta
re benthivore
juv. piscivore
adult piscivore
logs / km of shoreline
Hypothesis 2:
Benthivore is less dependent on refuge than piscivore
Response of Vulnerability and Hiding
0
0.5
1
1.5
2
0 100 200 300 400logs/km of shoreline
par
amet
er v
alu
e
vulnerability ofbenthivore
hiding ofbenthivore
vulnerability ofjuv. piscivore
hiding of juv.piscivore
Fish Biomass at Steady State
0
10
20
30
40
50
50 500 1000 500 andfishing
kg/ h
ecta
re benthivore
juv. piscivore
adult piscivore
logs / km of shoreline
BenthivoreJuvenile PiscivoreAdult PiscivoreCoarse Woody Debris
Windthrow
Fish Biomass Response to Windthrow
years
100 200 300 400 500
kg o
f fi
sh /
hec
tare
0
10
20
30
Lo
gs /km
of sh
orelin
e
0
100
200
300
400
500
600
700
Fish Biomass Response to Windthrowand Fishing
years
100 200 300 400 500
kg o
f fi
sh /
hec
tare
0
10
20
30L
og
s /km o
f sho
reline
0
100
200
300
400
500
600
700
fishing starts
BenthivoreJuvenile PiscivoreAdult PiscivoreCoarse Woody Debris
Development
Fish Biomass Response to Development
years
100 200 300 400 500
kg o
f fi
sh /
hec
tare
0
10
20
30
Lo
gs /km
of sh
orelin
e
0
100
200
300
400
500
600
Fish Biomass Response to Development and Fishing
years
100 200 300 400 500
kg o
f fi
sh /
hec
tare
0
10
20
30L
og
s /km o
f sho
reline
0
100
200
300
400
500
600
fishing starts
Conclusions
• Coarse woody debris could be a major driver of fish community dynamics (and we will test this)
• Effect of development is much greater than effect of windthrow
• For benthivore, moderate reductions in coarse woody debris may be balanced by fishing on piscivore
• Help Greg chop down trees this winter
Work in ProgressField experiments in N. Wisconsin: • Removal of coarse woody debris from Little Rock Lake• Addition of coarse woody debris to Camp Lake• Observations of growth and abundance• Estimation of predation and vulnerability parameters and
hypothesis testing
Acknowledgements
Michele Parara, Scott VanEgeren, and the Biocomplexity Field Crew
This work is funded by the National Science Foundation under Cooperative Agreement #DEB-0083545
Increasing vulnerability
of benthivore
Increasing vulnerability
of benthivore
050
100150
200250
0
500
10000
10
20
30
40
inflection pt. for benthivore
Benthivore Response to CWD
logs / km
kg
of
fis
h /h
a
0100
200300
0
500
10000
20
40
60
inflection pt. for benthivore
Piscivore Response to CWD
logs / km
kg
of
fis
h /h
a