ecosystem jello… kerim aydin bob francis pat livingston
TRANSCRIPT
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ECOSYSTEM JELLO…
Kerim Aydin Bob Francis Pat Livingston
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Ecosystem properties
• “Stability” Many Many terms– Resilience– Resistance
• Food web structure?– Diversity– High biomass or other adaptations in
susceptible groups
• MEASURE VARIANCE
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Need to understand control
• TOP DOWN?• BOTTOM UP?• MIDDLE OUT?
– Which (if any) is dominant in marine systems??
– Explanations may be easy to find and hard to confirm!
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“Kitchellization”
• The process of losing beer money by making poor guesses about ecosystem responses
Phytoplankton
Zooplankton
Forage Fish
Large Fish
Marine Mammals Sharks
???
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“Revenge??”
Phytoplankton
Zooplankton
Forage Fish
Large Fish
Marine Mammals Sharks
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Top-down-bottom-up-ENSO-PDO-fishing?
Figure the Frequency!!!
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Where can you go from a marine food web?
Food Webs Process models•Investigate specific environmental linkages•Address species concerns (endangered spp.)
Multi-species harvest models•Predict returns from harvest strategies
Biomass dynamics models•Measure broad ecosystem properties•Assess risks of regime shifts• Determine the need for mechanisms
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Why use the most general models?
Regimes Happen!
• There needs to be a way to abstract ecosystems, and look for risks.
• This is one example of using “whole ecosystem properties” to examine this risk.
Biomass dynamics models•Measure broad ecosystem properties•Assess risks of regime shifts• Determine the need for mechanisms
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Food web forcing?
Phytoplankton
Zooplankton
Forage Fish
Large Fish
Marine Mammals Sharks
????
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Correlation requires Variation
Phytoplankton
Zoopla
nkto
n
PiscivoresPla
nkti
vore
s
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Variation comes with history
• This is maybe not so important in labs and lakes (“white” systems).
• But in large marine systems….
0.5
0 50 100Year
-EN
SO
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History vs. the correlation method - equilib. Vs. time...
• TOP DOWN OR BOTTOM UP???• TOP DOWN OR BOTTOM UP???
Phytoplankton
Zoop
lank
ton
PiscivoresPlan
ktiv
ores
00.2
0.40.60.8
11.21.4
1.61.8
1 140 279 418 557 696 835 974 1113
Phytoplankton
Large Flatfish
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How can variability vary?
0.5
0 50 100Year
-EN
SO
• Amplitude• Frequency• Cadence
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What are the characteristics of a food web component?
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What are the characteristics of a food web component?
• Biomass (“tons”)• Production (“tons/year”)• P/B (1/year)-
– inverse of replacement time– related to generation time
B
P/B
P
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What are the characteristics of a food web component?
• Biomass (“tons”)• Production (“tons/year”)• P/B (1/year)• Trophic level
B
P/B
P
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What are the characteristics of a food web component?
• Biomass (“tons”)• Production (“tons/year”)• P/B (1/year)• Trophic level
• Network characteristics• Dissipative characteristics
B
P/B
P
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B vs. P/B
• R vs. K selected...
P P
P/B
B B
P/B
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This experiment
• Start with two “Actual” Food Webs
The East. Bering Sea Shelf system with pollock as the dominant fished species
The East. Tropical Pacific Tuna are dominant fished species
Both have shown interannual variation in primary productionwhich may be linked to climate signals.
The East. Bering Sea Shelf system with pollock as the dominant fished species
The East. Tropical Pacific Tuna are dominant fished species
Both have shown interannual variation in primary productionwhich may be linked to climate signals.
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Need rules for species interactions
• One possibility of many:– P/B then B of predator respond to increases of
prey biomass– “overly stable” - only looking for chances of
regimes – Ratio-dependent predator/prey model with
satiation (ECOSIM based)– Mimics surplus production (Pella-Tomlinson)
model when predator, prey fixed.– Next step is to add better age-structure
(single biggest weakness of the model).
????
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Dynamics of overlap
Bi - Vij Vij
Bj
vijVij
vij (Bi-Vij)aijVijBj
dVij /dt = vij(Bi-Vij) - vijVij - aijVijBj
Assume fast equilibrium for Vij
V
B-V
“It’s cold down there!”
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The appearance of Density Dependence
• dVij /dt = vij(Bi-Vij) - vijVij - aijVijBj = 0
• Vij = vijBi/(2* vij + aijBj)
• Cij (Bi,Bj) = aijvijBiBj
(2* vij + aijBj)Predator Biomass
Cij (or Minstant)
Prey biomass
Cij /Bj
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P/B vs. Trophic Level - EBS
• (note missing microzooplankton)• B vs. Trophic Level? No firm
relationship…
0
1
2
3
4
5
-6 -4 -2 0 2 4 6log [P/B]
Tro
ph
ic L
evel
Phytoplankton
ZooplanktonForage fish
Large Flatfish
Pollock
Marine Mammals
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P/B vs. Trophic Level - ETP
0
1
2
3
4
5
6
-5 0 5 10log [P/B]
Tro
ph
ic L
evel
Phytoplankton
Zooplankton
Small Tuna
Large Tuna
Marine Mammals
Sharks
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Insert bottom up variation
• Use “natural” signal (e.g. ENSO)
0.1
1
10
0 10 20 30 40 50 60 70 80 90Year
Pri
ma
ry P
rod
uc
tio
n ~6 Year Period
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Insert bottom up variation
• Use “natural” signal (e.g. ENSO)
• Vary amplitude, frequency, cadence
0.1
1
10
0 10 20 30 40 50 60 70 80 90Year
Pri
mar
y P
rod
uct
ion ~12 Year Period
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Insert bottom up variation
• Use “natural” signal (e.g. ENSO)
• Vary amplitude, frequency, cadence
0.1
1
10
0 10 20 30 40 50 60 70 80 90Year
Pri
ma
ry P
rod
uc
tio
n ~24 Year Period
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Insert bottom up variation
• Use “natural” signal (e.g. ENSO)
• Vary amplitude, frequency, cadence
0.1
1
10
0 10 20 30 40 50 60 70 80 90Year
Pri
mar
y P
rod
uct
ion ~48 Year Period
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Results• Here’s a couple 100-year time
tracks...
• We care about:• Amount of variability transmitted (CV
over 100 years)
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Amplitude and cadence
– Increasing the amplitude of forcing increases the amplitude of response.
– Cadence is complex, and depends too heavily on (unknown) parameters.
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Frequency and Variation
0 1 2 3 4 5
Trophic Level
CV Phytoplankton
Sm. Zooplankton
Pollock
Marine Mammals
Lg. Zooplankton
~6 year cycle
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Frequency and Variation
-6 -4 -2 0 2 4 6
log [P/B]
CV Phytoplankton
Sm. Zooplankton
PollockMarine Mammals
Lg. Zooplankton
~6 year cycle
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Frequency and Variation
-5 0 5log [P/B]
CV
~6 year cycle
-5 0 5log [P/B]
CV
~24 year cycle
-5 0 5log [P/B]
CV
~12 year cycle
-5 0 5log [P/B]
CV
~48 year cycle
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Frequency II - CV (tuna)
-5 0 5 10log [P/B]
CV
~6 year cycle
-5 0 5 10log [P/B]
CV
~12 year cycle
-5 0 5 10log [P/B]
CV
~24 year cycle
-5 0 5 10log [P/B]
CV
~48 year cycle
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What about correlations and control?? 6-year period
-0.4-0.2
00.20.40.60.8
11.2
0.01 0.1 1 10 100
P/B (log scale)
Co
rre
lati
on
wit
h
Ph
yto
. bio
mas
s
12-year period
-0.4-0.2
00.20.40.60.8
11.2
0.01 0.1 1 10 100
P/B (log scale)
Co
rre
lati
on
wit
h
Ph
yto
. bio
mas
s
24-year period
-0.5
0
0.5
1
1.5
0.01 0.1 1 10 100
P/B (log scale)
Co
rre
lati
on
wit
h
Ph
yto
. bio
mas
s
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One theoretical explanation...
• Simply hitting the resonant frequencies of each model component?– Useful for model (and real life)
analysis of important terms.– “Real life” P/B values may imply
natural resonant frequencies.
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Small observations
• Missing seasonal/micronekton• Frequencies, P/B are the same unit (1/time)• Trophic Level less of a fit
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Fish must follow history or be history
• If P/B of a species is in the range that it is “excited” by the balance of top-down/bottom up, does it need extra biomass to be stable (“avoid” regimes)?
• We don’t know the frequency of primary production variation in many systems.
• Need to look at more ecosystems
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What responds to each frequency range?
• Forage fish, micronekton response peaks near ENSO-scale forcing.
– This doesn’t mean that they vary on an ENSO scale, but that they are most susceptible to crashes when the bottom-up forcing is at that scale.
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What responds to each frequency range?
• Forage fish, micronekton response peaks near ENSO-scale forcing.
• Larger commercial fish response peaks at “regime” (10-50 year) forcing.
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So what about fishing?
• General principle of surplus production As B goes down, P/B goes up, due to:
• more food per fish• smaller, faster growing fish
P PB B
P/B
P/B
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Are our fish becoming anchovies?
• Beyond “multispecies MSY”, have we changed the natural time scale of animals (P/B, replacement, generation time) without changing the natural time scale (frequency) of input variation?
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Shift happens (with a little help
from…)
• Fishing may push a species in or out of the high CV range. – Will regime changes occur MORE or
LESS frequently with fishing?– It can occur in both directions: the fin
whale control?– What is the range of fishing change
compared to natural variability in P/B?
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Preliminary until...
• More ecosystems and parameters• Devil in the details
• Model type, (L.V., ECOSIM, Spatial, parameters)
• Fishing changes (historical)• Still, true for “reasonable” forms
• Middle-out Forcing
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CONCLUSIONS
• The frequency of primary production variation may be strongly connected to P/B.
• The frequency associated with regime shifts (10-50 year period) is the frequency at which most currently fished species show the strongest response.
• Fishing may push P/B into or out of the range of greatest variation, depending on the frequency of natural forcing in the ecosystem.