Population ecology: Theory, methods, lenses Dr. Bill … · Population Ecology & Spatial Ecology A)...
Transcript of Population ecology: Theory, methods, lenses Dr. Bill … · Population Ecology & Spatial Ecology A)...
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Population ecology: Theory, methods, lenses
Dr. Bill Fagan
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Population Ecology & Spatial Ecology
A) Core principles of population growth
B) Spatial problems and methods for modeling them
C) Integrodifference equations as a robust platform
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Population Ecology & Spatial Ecology
A) Core principles of population growth
B) Spatial problems and methods for modeling them
C) Integrodifference equations as a robust platform
Socio – Environmental Issues:1. Fisheries2. Invasive Species3. Biological Control4. Ecological Footprints5. Critical Patch Size / Reserve Design
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Berryman: On principles, laws, and theory in population ecology. Oikos. 2003
1) Exponential population growth as a null baseline. What causes deviations from that ?
A) Core principles of population growth
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where N is the thing you are measuring
and t is an index representing blocks of time.
Constant time step = 1 unit (year, month, day, second)
The Basics of Discrete Time Models
Have Form
Time is discrete, #’s need not be
...,,, 211 tttt NNNfN
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In many cases
tt NfN 1 Reduced Form
Status next time step depends only on where system is now.
history is unimportant
Alternatively: history is important ...,, 211 tttt NNNfN
wide applicability
1) Many ecological phenomenon change discretely
- insects don’t hatch out all day long, only in morning
- rodents are less mobile near full moon
- seeds germinate in spring
2) Data were collected at discrete times censusesdaily
censusesyearly
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The Simplest Discrete Time Model
t
t
N
NN tt
1
Equation provides basis for structured population models
“Geometric” Growth Equation
Thing we are counting (e.g., Panda Bears)
Time index
“Time Step” or “Time Interval”
“Population Multiplier”
“Geometric per capita rate of growth”
“Discrete per capita rate of growth”
“Lambda”
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Population Change:
N = Number
Of Individuals
Births
Deaths
Imm
igra
tio
nE
mig
ratio
n
• Populations closed vs open to movement
• Populations with recruitment & mortality
• Structured vs Unstructured populations
Perspectives:
+
+
-
-
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With simple linear models like:
Populations will not just
stay constant but still stay constant forever
grow but will grow toward infinity
shrink but will shrink toward zero
Only 3 options
Usable as short term approximations only
Other factors will eventually kick in
(e.g., density dependence)
tt NN 1
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Berryman: On principles, laws, and theory in population ecology. Oikos. 2003
1) Exponential population growth as a null baseline. What causes deviations from that ?
2) Cooperation among individuals: Allee effects and thresholds
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Anazawa. Theoretical Population Biology. 2009
Nt
Nt+1 1:1 line
No cooperation
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Anazawa. Theoretical Population Biology. 2009
Nt
Nt+1 1:1 line
No cooperation
Cooperation Type I
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Anazawa. Theoretical Population Biology. 2009
Nt
Nt+1 1:1 line
No cooperation
Cooperation Type II
Cooperation Type I
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Anazawa. Theoretical Population Biology. 2009
Nt
Nt+1 1:1 line
No cooperation
Cooperation Type II
What is this ?
Cooperation Type I
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Anazawa. Theoretical Population Biology. 2009
Nt
Nt+1 1:1 line
No cooperation
Cooperation Type II
What is this ?
A
Cooperation Type I
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Anazawa. Theoretical Population Biology. 2009
Nt
Nt+1 1:1 line
No cooperation
Cooperation Type II
What is this ?
A
Cooperation Type I
“Weak Allee Effect”“Strong
Allee Effect”
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Allee effects
conceptualized as a critical threshold
where dynamics change
“positive density dependence”
Interactions among individuals of a species are
advantageous to further growth of the population
Applicable to organisms, cells, molecules,
even groups of people & cultures
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Allee effects
Ecological mechanisms:
Mutual shading by plants
Mutual defense by groups of animals
Molecules that facilitate the production
of more of their own kind
proteins that impact RNA synthesis
Commonality is “autocatalysis”
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Berryman: On principles, laws, and theory in population ecology. Oikos. 2003
1) Exponential population growth as a null baseline. What causes deviations from that ?
2) Cooperation among individuals: Allee effects and thresholds
3) Competition among individuals: Too much of a good thing
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Competition for “Resources” Triggers “Changes” in a Population
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Competition for “Resources” Triggers “Changes” in a Population
Resources Changes
Plants /Animals /Fungi /Microbes
WithinHuman Populations
BetweenHuman Societies
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Forms of density dependence:
Some component(s) of population
increases or decreases (or ‘changes’)
as a function of density
Population Density, (Nt or …)
Bir
th R
ate
Density dependent birth rates
Density independent
birth rate
Or death rates, or movement rates …
Monotonic vs.
Humped ?
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Anazawa. Theoretical Population Biology. 2009
Nt
Nt+1
Nt+1 = Nt
Contest: Individual winners & losers
Scramble: Everybody suffers to some extent
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Anazawa. Theoretical Population Biology. 2009
Nt
Nt+1Nt+1
Nt
Nt+1 = Nt
Nt+1 = Nt
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Density Dependence – Mathematical View
r
t
t eN
N 1
Easiest to see in terms of transitions (population ratios):
)(1t
t
t NfN
N
Density
Independent
Density
Dependent
Example: “Ricker model”
KN
r
t
tt
eN
N 11
No N
Appears
on right hand side
so no
dependence
on density
“Carrying Capacity”
= Upper bound on positive population growth
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How does density dependence work in the Ricker model ? (cont’d)
KN
r
t
tt
eN
N 11
Behavior of Ricker
equation as a
function of r
Nt
K
t
Slow r
K
Nt
t
Faster
r
“Damped
Oscillations”
“Overcompensation” Nt above K is
forced down not to K but below K
Mechanisms ??
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Strength of Density Dependence Can Itself be a Tunable Parameter
Shepherd Model
quantifies density - dependence
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But it is NOTORIOUSLY difficult to estimate the strength of density dependence …
WHY ?
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But it is NOTORIOUSLY difficult to estimate the strength of density dependence …
Problems:
1) Need for long term datasets
2) Must observe behavior under high (and low) density conditions
3) Complicated by environmental stochasticity (year to year variability)
4) Ignores ecosystem context
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Model for a ‘Set’ of Species
Models for Individual Species
Multiple Populations (Each with little data)
Aggregating DatasetsYields Increasingly Strong
InferenceBut at Cost of ‘Coarseness’
One partial solution: Fit models hierarchically
Foss-Grant et al. Ecology. In revision
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Stre
ngt
h o
f D
en
sity
Dep
en
den
ce
Growth Rate at Low Population Densities
261 populationsaggregated into51 species
Foss-Grant et al. Ecology. In revision
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Foss-Grant et al. Ecology. In revision
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Berryman: On principles, laws, and theory in population ecology. Oikos. 2003
1) Exponential population growth as a null baseline. What causes deviations from that ?
2) Cooperation among individuals: Allee effects and thresholds
3) Competition among individuals: Too much of a good thing
4) Interactions with other species
5) Limiting factors change in time and space