bsc 417/517 environmental modeling predator-prey oscillations on the kaibab plateau
TRANSCRIPT
BSC 417/517 Environmental Modeling
Predator-Prey Oscillations on the Kaibab Plateau
The Predator-Prey Relationship
• Predator-prey relationships have always occupied a special place in ecology
• Ideal topic for systems dynamics• Examine interaction between deer and
predators on Kaibab Plateau• Learn about possible behavior of predator
and prey populations if predators had not been removed in the early 1900s
Deer and Predators on Kaibab Plateau
• Information on deer population irruption is not reliable
• Data on predators is even more sketchy• Gain insight into predator prey relationship
on the Plateau from a more well-documented system: the snowshoe hare-lynx system in Canada
• Time series available on number of lynx pelts purchased by the Hudson Bay Co.
Snowshoe Hare-Lynx System
7
6
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4
3
2
1
Hares
Lynx
Snowshoe Hare-Lynx System• Records show peak in number of lynx pelts every 9-10
years• Data suggest that populations have oscillated in a
cyclical manner for over 100 years• Data are viewed as a classical example of predator-
prey interaction• Oscillations are not related to seasonal or other
obvious annual changes• Best examples of predator-prey oscillations in mammal
populations show periodicity of 3-4 or 9-10 years
Reference Mode for Kaibab Deer-Predator System
• Use hare-lynx example to draw a reference mode for deer-predator relationship
• Should the oscillations be sustained, damped, or growing?
• Intuition says sustained, but many other types of behavior have been observed
• For sake of simplicity, go with sustained oscillation with 9-10 year periodicity as reference mode
• Peaks in predator (cougar) populations should lag behind peaks in deer population by a few years
Initial Model – Equilibrium Conditions
deer populationpredation
predator population
predator net births
~
deer net birth rate
fraction forage needs met
area in 1000 acres
deer density
~
deer killed per predator per yr
~
predators net birth rate
net deer births
40002000
0.5
1.0
5
800
40
0.0
2000
0.0
50
Model Structure
• Ignore biomass impact of deer growth
• Assume ample forage is present by setting fraction forage needs met equal to 1.0
• Predator stock is dependent on deer density vis-à-vis deer density-dependent kill rate and kill-rate dependent net birth rate
Predator Kill Rate Functional Response
• Number of deer killed per predator per year is 60 if there are more than 10 deer/1000 acres… ~1 kill/week = satiation limit
• Shape of graphical function reflects a combination of “Type I” and “Type II” functional response
Type I Type IIKil
l rat
e
Kil
l rat
e
Prey density Prey density
Predator Kill Rate Graphical Function
0
10
20
30
40
50
60
70
0 2 4 6 8 10
deer density
dee
r ki
ller
per
pre
dat
or
per
yr
Predator Birth Rate Response
• Net birth rate is dependent on kill rate: higher kill rate => higher net birth rate
• Maximum net birth rate = 0.45/yr
• Cougars start to breed young (2-3 years age)
• Breed every 2 years with an average of 3 kittens
• Maximum net birth rate for predators and prey are comparable and relatively high…implications for potential oscillation?
Predator Birth Rate Graphical Function
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0 10 20 30 40 50 60 70 80
deer killed per predator per yr
pre
dat
or
net
bir
th r
ate
Initial Model Results Verify Equilibrium Conditions
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Initial predator density = 50
Initial Model Results - Nonequilibrium Initial Prey Density
• Set initial predator density at 45• System displays unstable behavior (as
illustrated by 30 vs. 50 year simulation)• Predators virtually annihilate prey after ca.
25 year, which lead to ensuing unstable behavior
• Question: why doesn’t such unstable behavior typically occur in nature?
Initial Model Results - Nonequilibrium Initial Prey Density
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Natural Predator-Prey Systems
• Predators don’t normally hunt prey to zero• Rather, select individuals from prey population
that are easiest to catch (young, old, weak)• Minimum threshold concept: prey density limit
below which predators would no longer find it profitable to hunt the prey and would switch to different prey
• Threshold is determined by availability of prey hiding places (refuge) and prey social behavior
Revising The Model• Should we revise the model to take into account the
threshold concept, effect of prey refuge, and prey social behavior?
• Perhaps expand deer population to multiple stocks to simulate deer age structure, and then allow predators to concentrate on young and old deer
• Sounds good, but…complexity would increase dramatically in face of limited data…
• Better to consider if combined effect of these factors could be taken into account within existing, simple model structure
Revised Model
• Try using a different functional response for density-dependent kill rate which incorporates the concept of threshold prey density
• No kills if deer density falls below 2 deer per 1000 acres, e.g. because of the ability of deer to find safe refuge when overall density is low
• S-shaped function response corresponds to “Type III” functional response
Type III Functional Response
0
10
20
30
40
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70
0 2 4 6 8 10 12
deer density
dee
r ki
lled
per
pre
dat
or
per
yr
Revised Model Results
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Revised Model Results
• Initial predator population is set at 100• Large predator population causes an initial
decline in deer population, but predator population declines quickly
• Damped oscillatory behavior ensues with periodicity of ca. 10 years
• Result essentially corresponds to the original reference mode
Further Interpretation
• The initial “dynamic hypothesis” was that the cougar and deer populations could interact to produce stable cycles with a period similar to the classic 9-10 year cycle observed in other mammalian predator-prey systems
• Requirement for a Type III functional response to produce stable behavior can be interpreted as an indication of the importance of prey refuge or threshold levels
State Space (Phase Plane) Diagram
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0
50
100
predator popul… v. deer population: 1 -
Point attractor
Patterns of Oscillation
• Previous simulations show possibility for both damped and growing oscillations, depending on the nature of the predator functional response
• What about potential for sustained oscillation, as state in the reference mode?
• Could random disturbances lead to persistent cycles?
Influence of Random Variation
• Introduce randomness into the deer net birth rate via the following equations• net birth rate = 0.5 + random factor
• random factor = random(-0.2,0.2,123)
• The random factor allows net birth rate to vary randomly from a low of 0.3 to a high of 0.7
• The value 123 is a “seed” for the random number generator
Influence of Random Variation
• System shows sustained oscillation over long time scales, with periodicity of ca. 10 years
• Reference mode has been generated
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Policy Test: Selective Removal of Predators
• Results of revised model with random variation in deer birth rate suggests that stable predator-prey interactions would have been possible if the predators had not been removed from the Kaibab Plateau
• Although predator population averages 50, substantially higher numbers occur in some years, which could pose problem for ranchers livestock
• Test influence of allowing hunters to kill some predators to protect live stock
Model With Selective Removal of Predators
deer populationpredation
predator population
predator net birthsdeer net birth rate
random factor
area in 1000 acres
deer density
~
deer killed per predator per yr
~
predators net birth rate
net deer births
predator kills
start year
maximum acceptable predators
New Equations
predator_kills = IF(TIME>start_year) THEN (predator_population-maximum_acceptable_predators) ELSE 0
start_year = 1920
maximum_acceptable_predators = 55
Simulation Results With Selective Removal of Predators
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Interpretation
• Results suggest that it might have been possible to reduce peak values of predator population without destroying the stability of the predator-prey system
• However, managers in early 1900s had essentially no knowledge of predator-prey dynamics
• Even today, other factors besides predator-prey population dynamics are know to be important in governing response of the system…
Current Interpretation of the Hare-Lynx Predator Prey System
• Krebs et al. (Bioscience 2001) (see PDF on web-site) conclude that Lotka and Volterra were only partly correct when the concluded that the snowshoe hare cycle was the product of a predator-prey oscillation
• Missed critical point that the cycle can only be understood by considering three trophic levels rather than just two
• Hare cycle is produced by interaction between predation and food supplies
• Dependence on food supply ripples across many species of predators and prey in boreal forest