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Lecture 5

Density-dependent population growth




WILD3810 (Spring 2021)

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Readings

Mills 126-141

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Density-independence vs density-dependence

In lecture 3, we learned about population growth models that assume demographic rates are unrelated to population size

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Density-independence vs density-dependence

We also learned that this assumption leads to exponential population growth

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Limitless population growth?

No population can grow exponentially forever (or even for relatively short periods of time)

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Limitless population growth?

No population can grow exponentially forever (or even for relatively short periods of time)
Thomas Malthus was the first to propose that no population could grow without bound forever (1798)

  • At some point, resources will be become limited and populations must either stop growing or decline

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Limitless population growth?

No population can grow exponentially forever (or even for relatively short periods of time)
Thomas Malthus was the first to propose that no population could grow without bound forever (1798)

  • At some point, resources will be become limited and populations must either stop growing or decline

Malthus' work inspired Darwin (1859) to suggest that limitation of resources is what drives evolution by natural selection

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Stochasticity and extinction risk over time

We also learned that, given enough time, populations that experience stochasticity will eventually go extinct

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Stochasticity and extinction risk over time

We also learned that, given enough time, populations that experience stochasticity will eventually go extinct

Why isn't extinction more common?

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Density-dependence

The tendency of population vital rates, and therefore population growth rate, to change (increase or decrease) as a function of population size

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Density-dependence

The tendency of population vital rates, and therefore population growth rate, to change (increase or decrease) as a function of population size

At small population sizes, individual organisms may be able to acquire all of the resources they need to survive and reproduce

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Density-dependence

The tendency of population vital rates, and therefore population growth rate, to change (increase or decrease) as a function of population size

At small population sizes, individual organisms may be able to acquire all of the resources they need to survive and reproduce

As the population grows, competition, disease, and predation increase

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Competition

At small population sizes, individual organisms may be able to acquire all of the resources they need to survive and reproduce

As N increases, the availability of resources per organism will decrease, leading to increased competition

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Competition

At small population sizes, individual organisms may be able to acquire all of the resources they need to survive and reproduce

As N increases, the availability of resources per organism will decrease, leading to increased competition
Intra-specific competition:

interaction between individuals of a single species brought about by the need for a shared resource

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Competition

At small population sizes, individual organisms may be able to acquire all of the resources they need to survive and reproduce

As N increases, the availability of resources per organism will decrease, leading to increased competition
Intra-specific competition:

interaction between individuals of a single species brought about by the need for a shared resource

Intra-specific competition can arise in multiple ways:

Animals

  • food
  • shelter
  • breeding sites
  • mates

Plants

  • space
  • light
  • water
  • nutrients
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Competition

Ecologists generally distinguish between two types of competition:

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Competition

Ecologists generally distinguish between two types of competition:
1) Exploitation competition

  • consumption of limited resource by individuals depletes the amount available for others

  • also known as: depletion, consumption, or scramble competition

  • indirect

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Image courtesy of U.S. Fish and Wildlife Service Headquarters, via Wikimedia Commons

Competition

Ecologists generally distinguish between two types of competition:

1) Exploitation competition

2) Interference competition

  • individuals actively prevent others from attaining a resource in a given area or territory

  • also known as: encounter or contest competition

  • direct

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Image courtesy of Muhammad Mahdi Karim, via Wikimedia Commons

Competition

As population size increases, the resources available to each individual will eventually shrink to the point where demographic parameters are negatively effected

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Competition

As population size increases, the resources available to each individual will eventually shrink to the point where demographic parameters are negatively effected

  • Increased density can also increase rates of disease transmission or predation

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Population regulation

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Population regulation

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Left of the intersection, population growth rate is positive so the population will grow

Population regulation

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Right of the intersection, population growth is negative so the population will shrink

Population regulation

Carrying capacity K:

the population size that the environment can maintain 1

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1 At the intersection, population growth is 0 so the population will be stable

Population regulation vs limitation

The density-dependent processes we just learned about are called regulating factors

  • Regulating factors keep population size from going too far above or below K 2

Limiting factors determine the actual value of K

  • Limiting factors can be density-dependent (competition) or density independent (disturbance or extreme weather)
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2 Think of regulating factors like a thermostat - if the temperature goes below the desired temperature ($N < K$), the heater kicks on ($b$ increases). If once the temperature increases above the set temperature ($N > K$), the heater turns off ($d$ increases)

Modeling density-dependent population growth

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Modeling D-D population growth

Remember the (continuous time) density-independent model of population growth:

dNdt=N×r

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Modeling D-D population growth

Remember the (continuous time) density-independent model of population growth:

dNdt=N×r

How can we modify this equation to include density-dependence?

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Modeling D-D population growth

Remember the (continuous time) density-independent model of population growth:

dNdt=N×r

How can we modify this equation to include density-dependence?

To start, remember what density-dependence means:

the rate of population growth changes as population size increases

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Modeling D-D population growth

First, let's modify the density-independent model is a small but useful way:

1NdNdt=r

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Modeling D-D population growth

First, let's modify the density-independent model is a small but useful way:

1NdNdt=r (Note that all we did was divide both sides by N)

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Modeling D-D population growth

First, let's modify the density-independent model is a small but useful way:

1NdNdt=r (Note that all we did was divide both sides by N)

How do we interpret this equation?

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Modeling D-D population growth

1NdNdt=r

There are r new individuals added to the population

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Modeling D-D population growth

1NdNdt=r

There are r new individuals added to the population

every time step (e.g., hour, day, week, etc.)

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Modeling D-D population growth

1NdNdt=r

There are r new individuals added to the population

every time step (e.g., hour, day, week, etc.)

per individual currently in the population

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Modeling D-D population growth

1NdNdt=r

There are r new individuals added to the population

every time step (e.g., hour, day, week, etc.)

per individual currently in the population

So this formulation tells us the per capita (i.e., per individual) rate of growth when there are N individuals currently in the population

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Modeling D-D population growth

1NdNdt=r

There are r new individuals added to the population

every time step (e.g., hour, day, week, etc.)

per individual currently in the population

So this formulation tells us the per capita (i.e., per individual) rate of growth when there are N individuals currently in the population

  • For example, if r=1, each individual replaces itself at each time step
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Modeling D-D population growth

1NdNdt=r

There are r new individuals added to the population

every time step (e.g., hour, day, week, etc.)

per individual currently in the population

So this formulation tells us the per capita (i.e., per individual) rate of growth when there are N individuals currently in the population

  • For example, if r=1, each individual replaces itself at each time step
  • Note that the growth rate will always be r, no matter how many individuals are in the population
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Modeling D-D population growth

It's also helpful to visualize this equation:

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Modeling D-D population growth

How do we add density-dependence to our model?

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Modeling D-D population growth

How do we add density-dependence to our model?

Remember the equation for a line: 3

y=a+bx

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Modeling D-D population growth

How do we add density-dependence to our model?

Remember the equation for a line: 3

y=a+bx

So one way to include density-dependence is: 4

1NdNdt=r+cN.

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3 a is the y-intercept (the value of y when x=0) and b is the slope (the change in y per unit change is x).

4I changed the slope to c to ensure that it is not confused with the birth rate b

Modeling D-D population growth

Again, it might help to visualize this equation:

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Modeling D-D population growth

Again, it might help to visualize this equation:

So now, the per capita growth rate (1NdNdt) decreases as N increases

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Modeling D-D population growth

In the new population model, r represents the rate of increase when the population size is 0 (i.e., the y-intercept)

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Modeling D-D population growth

In the new population model, r represents the rate of increase when the population size is 0 (i.e., the y-intercept)

We can see in the figure that this is the largest value of r the population can experience

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Modeling D-D population growth

In the new population model, r represents the rate of increase when the population size is 0 (i.e., the y-intercept)

We can see in the figure that this is the largest value of r the population can experience

  • Call that r0
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Modeling D-D population growth

In the new population model, r represents the rate of increase when the population size is 0 (i.e., the y-intercept)

We can see in the figure that this is the largest value of r the population can experience

  • Call that r0
  • Because r0 the maximum rate of increase (nothing limiting population growth), it is equivalent to r in the D-I model

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Modeling D-D population growth

What is c?

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Modeling D-D population growth

What is c?

  • The slope of the relationship between 1NdNdt and N

  • i.e., the amount by which population growth changes for every individual added to the population

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Modeling D-D population growth

What is c?

  • The slope of the relationship between 1NdNdt and N

  • i.e., the amount by which population growth changes for every individual added to the population

  • In this case, it has to be negative (growth rate decreases as N increases)

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Modeling D-D population growth

What is c?

  • The slope of the relationship between 1NdNdt and N

  • i.e., the amount by which population growth changes for every individual added to the population

  • In this case, it has to be negative (growth rate decreases as N increases)

Notice also that there is a point where the line crosses the x-axis (growth rate = 0):

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Modeling D-D population growth

What is c?

  • The slope of the relationship between 1NdNdt and N

  • i.e., the amount by which population growth changes for every individual added to the population

  • In this case, it has to be negative (growth rate decreases as N increases)

Notice also that there is a point where the line crosses the x-axis (growth rate = 0):

1NdNdt=r0+cN=0

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Modeling D-D population growth

What is c?

  • The slope of the relationship between 1NdNdt and N

  • i.e., the amount by which population growth changes for every individual added to the population

  • In this case, it has to be negative (growth rate decreases as N increases)

Notice also that there is a point where the line crosses the x-axis (growth rate = 0):

1NdNdt=r0+cN=0solving for N, we can see that:

N=r0c

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Modeling D-D population growth

What is c?

  • The slope of the relationship between 1NdNdt and N

  • i.e., the amount by which population growth changes for every individual added to the population

  • In this case, it has to be negative (growth rate decreases as N increases)

Notice also that there is a point where the line crosses the x-axis (growth rate = 0):

1NdNdt=r0+cN=0

solving for N, we can see that:

N=r0c=K

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Modeling D-D population growth

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Models of D-D population growth

We now have a full equation for the relationship between 1NdNdt and N:

1NdNdt=r0+cN

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Models of D-D population growth

We now have a full equation for the relationship between 1NdNdt and N:

1NdNdt=r0+cNHow does this work?

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Models of D-D population growth

We now have a full equation for the relationship between 1NdNdt and N:

1NdNdt=r0+cNHow does this work?

If r0=1 and c=0.001, what is the population growth rate when N=100?

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Models of D-D population growth

We now have a full equation for the relationship between 1NdNdt and N:

1NdNdt=r0+cNHow does this work?

If r0=1 and c=0.001, what is the population growth rate when N=100?

  • 1NdNdt=10.001×100= 0.9
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Models of D-D population growth

We now have a full equation for the relationship between 1NdNdt and N:

1NdNdt=r0+cNHow does this work?

If r0=1 and c=0.001, what is the population growth rate when N=100?

  • 1NdNdt=10.001×100= 0.9

What about when N=500?

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Models of D-D population growth

We now have a full equation for the relationship between 1NdNdt and N:

1NdNdt=r0+cNHow does this work?

If r0=1 and c=0.001, what is the population growth rate when N=100?

  • 1NdNdt=10.001×100= 0.9

What about when N=500?

  • 1NdNdt=10.001×500= 0.5
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Models of D-D population growth

We now have a full equation for the relationship between 1NdNdt and N:

1NdNdt=r0+cNHow does this work?

If r0=1 and c=0.001, what is the population growth rate when N=100?

  • 1NdNdt=10.001×100= 0.9

What about when N=500?

  • 1NdNdt=10.001×500= 0.5

When N=1000?

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Models of D-D population growth

We now have a full equation for the relationship between 1NdNdt and N:

1NdNdt=r0+cNHow does this work?

If r0=1 and c=0.001, what is the population growth rate when N=100?

  • 1NdNdt=10.001×100= 0.9

What about when N=500?

  • 1NdNdt=10.001×500= 0.5

When N=1000?

  • 1NdNdt=10.001×1000= 0
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Models of D-D population growth

How do we use the density-dependent growth rate model to project population size?

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Models of D-D population growth

How do we use the density-dependent growth rate model to project population size?

Multiply both sides by N

dNdt=N×(r0+cN)

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Models of D-D population growth

How do we use the density-dependent growth rate model to project population size?

Multiply both sides by N

dNdt=N×(r0+cN)

Now read this as:

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Models of D-D population growth

How do we use the density-dependent growth rate model to project population size?

Multiply both sides by N

dNdt=N×(r0+cN)

Now read this as:

The change in population size per time step

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Models of D-D population growth

How do we use the density-dependent growth rate model to project population size?

Multiply both sides by N

dNdt=N×(r0+cN)

Now read this as:

The change in population size per time step

equals the current population size

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Models of D-D population growth

How do we use the density-dependent growth rate model to project population size?

Multiply both sides by N

dNdt=N×(r0+cN)

Now read this as:

The change in population size per time step

equals the current population size

times the growth rate when population size equals N

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Models of D-D population growth

How do we use the density-dependent growth rate model to project population size?

Multiply both sides by N

dNdt=N×(r0+cN)

Now read this as:

The change in population size per time step

equals the current population size

times the growth rate when population size equals N

  • This is called the logistic growth model
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Models of D-D population growth

How does this work? Again, r0=1 and c=0.001

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Models of D-D population growth

How does this work? Again, r0=1 and c=0.001

What is dNdt when N=100?

  • dNdt=100×(10.001×100)= 90
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Models of D-D population growth

How does this work? Again, r0=1 and c=0.001

What is dNdt when N=100?

  • dNdt=100×(10.001×100)= 90

What about when N=500?

  • dNdt=500×(10.001×500)= 250
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Models of D-D population growth

How does this work? Again, r0=1 and c=0.001

What is dNdt when N=100?

  • dNdt=100×(10.001×100)= 90

What about when N=500?

  • dNdt=500×(10.001×500)= 250

When N=1000?

  • dNdt=1000×(10.001×1000)= 0
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What happens to dNdt when N>K?

Models of D-D population growth

How does this work? 6

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6 Thickness and color of line correspond to magnitude of population change (thicker and darker red correspond to larger rate of change)

Models of D-D population growth

How does this work? 6

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6 Thickness and color of line correspond to magnitude of population change (thicker and darker red correspond to larger rate of change)

Rate of change is largest when abundance is at half of the carrying capacity (N=K2)

Above K, the rate of change becomes negative

Models of D-D population growth

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Allee effects

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Allee effects

So far, we have assumed that b and d (and therefore r) decrease as population size increases

  • This is called negative density dependence

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Allee effects

So far, we have assumed that b and d (and therefore r) decrease as population size increases

  • This is called negative density dependence

In some cases, the slope could also be positive

  • Positive relationships between N and d or b generally occur at small population sizes

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Allee effects

Why might the death rate be high at small N?

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Allee effects

Why might the death rate be high at small N?

  • Group signaling breaks down, predation increases
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Allee effects

Why might the death rate be high at small N?

  • Group signaling breaks down, predation increases
  • Cooperative foraging becomes less efficient
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Allee effects

Why might the death rate be high at small N?

  • Group signaling breaks down, predation increases
  • Cooperative foraging becomes less efficient
  • Inbreeding depression
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Allee effects

Why might the death rate be high at small N?

  • Group signaling breaks down, predation increases
  • Cooperative foraging becomes less efficient
  • Inbreeding depression

Why might the birth rate be low at small N?

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Allee effects

Why might the death rate be high at small N?

  • Group signaling breaks down, predation increases
  • Cooperative foraging becomes less efficient
  • Inbreeding depression

Why might the birth rate be low at small N?

  • Pollination failure
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Allee effects

Why might the death rate be high at small N?

  • Group signaling breaks down, predation increases
  • Cooperative foraging becomes less efficient
  • Inbreeding depression

Why might the birth rate be low at small N?

  • Pollination failure
  • Unable to find mates because of rarity
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Allee effects

Why might the death rate be high at small N?

  • Group signaling breaks down, predation increases
  • Cooperative foraging becomes less efficient
  • Inbreeding depression

Why might the birth rate be low at small N?

  • Pollination failure
  • Unable to find mates because of rarity
  • Unable to find mates because of skewed sex ratio
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Allee effects

Why might the death rate be high at small N?

  • Group signaling breaks down, predation increases
  • Cooperative foraging becomes less efficient
  • Inbreeding depression

Why might the birth rate be low at small N?

  • Pollination failure
  • Unable to find mates because of rarity
  • Unable to find mates because of skewed sex ratio
  • Inbreeding depression
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Allee effects

When abundance drops below the minimum viable population (MVP), the population will likely approach extinction without help!

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Discrete dynamics

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Discrete dynamics

Remember the discrete-time model of density-independent growth

Nt+1=Ntλ

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Discrete dynamics

Remember the discrete-time model of density-independent growth

Nt+1=Ntλ

As before, we need to account for possible changes in λ caused by changes in population density

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Discrete dynamics

Remember the discrete-time model of density-independent growth

Nt+1=Ntλ

As before, we need to account for possible changes in λ caused by changes in population density

Remember that:

λ=er

and:

r=1NdNdt=r0+cN

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Discrete dynamics

Therefore, one discrete-time density-dependent growth model is:

Nt+1=Nte[r0+cN]

This known as the Ricker model

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Readings

Mills 126-141

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