Lecture 17 Flashcards

1
Q

population size symbol

A

N

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2
Q

population density symbol

A

N/area

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3
Q

why do we care about understanding population size, N?

A
  • natural resources management (eg size of fish stocks in the ocean, abundance of outbreaking insect pests in forests)
  • conservation: population decline of a species
  • health: monitoring populations of viruses or bacteria in humans
  • understanding and predicting human population growth
  • basic science question of what limits population growth
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4
Q

Population declines in Myotis lucifugous bats due to white nose syndrome (WNS)

A
  • novel pathogen (fungus) emerged in bat population, causing a disease caused white nosed syndrome and really high mortality.
  • steep decline in no of over-wintering bats
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5
Q

HIV population dynamics in humans - draw graph of CD4 cells over time

A
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6
Q

Malthus’ essay on population growth

A

in 1798, Malthus published an essay on the principle of population, arguing that the human population cannot grow faster than food production

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7
Q

Paul Ehlrich

A

published The Population Bomb, arguing that explosive growth in the human population would have catastrophic social and environmental consequences

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8
Q

how is the human population expected to change in the future?

A

demographers project that human population is soon going to peak, then fall dramatically (depopulation)

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9
Q

goals of most population models

A
  • predict the trajectory of population growth through time, i.e. N as a function of t
  • how many individuals are in the population now? Nt
  • how many individuals are in the population one step later? N(t+1)
  • so the general model is N(t+1) = fN(f)
  • challenge: choosing simple but realistic parameters for f
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10
Q

when using differential equations, time steps are

A

infinitesimally small: use concept of limits and calculus; growth is smooth; best suited for species with continuous reproduction

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11
Q

when using difference equations, time steps are

A

discrete units (days, years, etc); use iterated recursion equations; growth is stepwise and bumpy; best suited for episodic reproduction

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12
Q

two types of time step approaches

A

continuous-time and discrete-time

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13
Q

how do we pick between the two time-step approaches?

A

different organisms might be better fit by one or the other

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14
Q

simple bookkeeping model: how can N change from Nt to Nt+1

A

D = number who die during one time step
B = number born during one time step
E - number who emigrate during one time step
I = number who immigrate during one time step

Nt+1 = Nt - D + B - E + 1

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15
Q

what variables can we consider to be equivalent?

A
  • birth and immigration (ie individuals added to the population)
  • death and emigration (ie individuals that disappear from the population)
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16
Q

geometric growth model

A
  • assume no immigration or emigration
  • treat birth and death during one time step as per capita rates that are fixed constants
  • then, population changes by a constant factor each time step: N(t+1) = λNt
  • λ is a multiplicative factor by which population changes over one time unit = ‘finite rate of increase’
  • λ = Nt+1/Nt
17
Q

if λ>1,

A

birth exceed deaths and population grows

18
Q

if λ<1

A

deaths exceed births and population shrinks

19
Q

N1 =

A

λN0

20
Q

N2 =

A

λN1 = λλN0

21
Q

N3 =

A

λN2 = λλN1 = λλλN0

22
Q

so how can geometric growth be generalised

A

Nt = N0λ^t

23
Q

exponential growth

A
  • instantaneous, fixed per-capita rates of birth and death (b and d)
  • instantaneous, per-capita rate of population change = b-d=r (a constant)
  • r = intrinsic rate of increase
  • differential equation is dN/dt = rN
  • this model is exponential growth
24
Q

draw a table comparing discrete-time and continuous time growth models

A
25
Q

find the relationship between r and λ

A

lnλ=r

26
Q

regardless of which model is adopted, the important consequence is the same

A
  • in both models, the growth rate (λ or r) is a constant that simply reflects biology
  • but a constant positive growth rate produces a population growth size that is not constant, but rather exploding in an exponential way
27
Q

all species…

A
  • have the potential for positive population growth under good conditions (λ>1.0, births exceed deaths)
  • have the potential for negative population growth under bad conditions (λ<1.0, deaths exceed births)
  • but no species has ever sustained λ>1 or λ<1 for a long period
28
Q

why is exponential growth a bad model of reality over the long term?

A
  • some factors use tend to keep populations from exploding or going extinct
  • two kinds of factors may be acting: density dependent regulation (growth depends on N) or density-independent reduction
29
Q

how can we model the classically, density-dependent growth?

A

the logistic equation; an exponential growth with a new term added for brakes
dN/dt = rN(1-N/k)

30
Q

use bacteria as an example of two types of growth

A
31
Q

The logistic braking term models… (draw graph)

A

the simplest form of density dependence

32
Q

K

A

carrying capacity of the environment

33
Q

logistic trajectories are truly
S-shaped only when

A

starting from low numbers

34
Q

label an N vs t graph

A
35
Q

logistic model pros

A
  • Mathematically tractable model of intraspecific competition for resources
  • Simple (only one extra parameter, K, beyond exponential)
  • Can be expanded to consider multispecies competition
36
Q

logistic podel cons

A
  • Too simple: specifies one particular kind of
    density dependence
  • Always a gradual approach to carrying
    capacity
  • In reality, density-dependence is likely
    to be non-linear, may see overshoots of K