Transcript Chapter 42

Chapter 42: Population ecology
Copyright  2005 McGraw-Hill Australia Pty Ltd
PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint
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What is a population?
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‘A number of organisms of the same species in a
defined geographical area’
Properties of populations include
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number of individuals
area they occupy
age structure
sex ratio
Different processes (e.g. fire, herbivory) may be
important at different times in the life cycle (e.g. fire
destroys adult golden wattle trees, but the seeds
often need fire to germinate)
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Distribution and abundance
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Biotic and abiotic factors control populations
A direct factor (e.g. water availability) may be
controlled by several indirect factors (e.g. temp,
rainfall, see Fig. 42.2a)
The probability of occurrence of a species plotted
against an environmental gradient defines the
realised distribution, or niche, of the species in
environmental space
The realised niche is a subset of the fundamental
niche
Space and time cause population fluctuations too
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Fig. 42.2a: Probability of occurrence of
different eucalypts
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Measuring the size of animal
populations
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The mark–release–recapture method estimates
the total population size from a sample proportion
of a mobile species
• Uses the proportion of recaptures to estimate
whole population size
• Assumptions are hard to satisfy
– closed population (i.e. no immigration, no emigration)
– all individuals equally likely to be marked
– marked individuals do not lose their mark
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Technique has been used successfully on whales,
lizards
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Density-independent population
dynamics
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Population size changes are due only to birth,
death, immigration and emigration
When birth and death rates are not affected by
population size, they are ‘density-independent’
Closed populations have no immigration or
emigration
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Exponential population growth
in discrete time
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Number of females in a closed population at time
(t + 1) is N(t+1) and is related to the number at the
previous time (t) by:
Nt 1  Nt bt  Nt (1  dt )
so
Nt 1  Rt Nt
(where b,d, are birth, death rates respectively)
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If Rt, the growth factor each year, is constant
Nt  Rt N0
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Small changes in R have major effects on
population size, see Fig. 42.4
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42-7
Fig. 42.4: Different growth factors
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Environmental variability and
exponential growth
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Mean exponential growth rate over several years
is given by the geometric (not arithmetic) mean,
called ‘R’
To calculate R, find the nth root of the product of R
values for n years
A closed, density-independent population will
either grow or reduce exponentially depending on
whether R is >1 or <1 respectively
If R = 1, the population size will remain constant
See Table 42.1
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The average growth rate
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Geometric mean of R = ½ (correct: population declining), but
arithmetic mean of R = 1.0625 is incorrect: population not increasing
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Exponential growth in
continuous time
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For organisms that breed throughout the year,
differential equations best describe population
growth
This gives the intrinsic rate of increase, denoted by
a lower case ‘r’
dN t
 (b  d ) N t  rN t
dt
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In the continuous time model of exponential
growth, the intrinsic rate of growth r determines the
fate of the population
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Range expansions
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Initial expansion of a species is often exponential
• The boundary often spreads at a constant rate
• Rate of spread is proportional to the growth rate of
the population
• This phenomenon has been observed for many
plant and animal species (e.g. mangrove
Avicennia marina in New Zealand, see
Fig. 42.6 (a), (b))
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Fig. 42.6a: Expansion of a population of Avicennia
marina
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Fig. 42.6b: Avicennia estuary
Copyright © G R Roberts, Photo Library, New Zealand
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Density-dependent population
dynamics
Population size does not increase indefinitely…
• Negative density-dependent population growth
results from lowered birth rate or higher death rate
when a resource becomes limiting
• The logistic growth curve is S-shaped because
resource limitation lowers the growth rate to zero
where the curve levels out to an asymptote
• The value of the asymptote on the y-axis is the
carrying capacity, K, of the population
• See Figs 42.7(b) and 42.8
(cont.)
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42-15
Fig. 42.7a: Antechinus stuartii
Copyright © C A Henley/AUSCAPE
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Fig. 42.7b: Poulation size of Antechinus
stuartii
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Fig. 42.8: Logistic growth
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Density-dependent population
dynamics (cont.)
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Population approaches an equilibrium state at the
carrying capacity, K
The logistic growth equation is
dN
 N
 rN 1  
dt
 K
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As N approaches K the growth rate decreases
When N = K, the growth rate is zero
Variability in environment may override the effect
of K, as the population size may never reach it
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Is density-dependent control
important or not?
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This has been a controversial topic
• Plants often do show density-dependent control
• In animals, environmental conditions may be
primary control, density-dependence less likely
• Birds and vertebrates maintain fairly constant
population sizes
• Invertebrates display density-vague population
dynamics, numbers fluctuate widely and resource
limitation may be rare e.g. locusts
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Space-limited populations
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Sessile (fixed) organisms may compete for space
more than food e.g. mussels, barnacles (see Fig.
42.10); plants
• Sessile populations live in habitats that experience
disturbance
• These species have good dispersal ability
• Successful recruitment depends on disturbance to
provide a new space to settle
• Ecological disturbance results from death of
individuals or from any space-liberating process
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Fig 42.10: Competition for space
Copyright © Paddy Ryan/ANT Photo Library
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The law of constant yield
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Plant growth patterns often show self-thinning
• Seedling growth rate depends on their initial
sowing density
• Plant yield (biomass x density) is constant
• The ‘law of constant yield’ is used to determine
optimal sowing density for a species
• With time, plants in denser plots begin to die
according to the –3/2 self-thinning rule (see Fig.
B42.2)
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Fig. B42.2: The rule of constant yield
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Age- and size-structured
population dynamics
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Age and/or size of an individual affects its fecundity
(probability of giving birth) and survival
Treating all members of a population as identical is
unrepresentative of natural population structure
Fig. 42.11 shows how an imbalanced initial age
structure generates age and number cycles
Life tables are used to show survivorship probability
at each age, but long-term studies are the key to
understanding population dynamics
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Fig. 42.11a: Age-structured population
dynamics
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Fig. 42.11b: Age-structured population
dynamics
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Australia’s human population
dynamics
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This is the study called ‘human demography’
Changes in human population size is mostly due to
behavioural changes e.g. one-child policy in China
Economists need to know future age structure to
enable building more nursing homes or schools in
the right places
The current trend is toward an ageing population
Growth rate of many western countries is now
below the replacement rate, so population
numbers will slowly begin to level out and then fall
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Bio-economics
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This theory addresses the problem of harvesting a
population for maximum economic and social
benefit
• The maximum sustainable yield (MSY) is the
harvesting rate that can be maintained indefinitely
• It is prudent to harvest below the MSY rate due to
uncertainty about species’ biology and stochastic
(unpredictable) events
• Highly mobile species may be hard to harvest
when there are only a few left, but sessile species
are vulnerable to extinction
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Leadbeater’s possum
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Gymnobelideus leadbeateri live in mountain ash
forests where they nest in old tree hollows (Fig.
B42.4)
• Fire and logging both reduce availability of hollows
• Lindenmayer and Possingham carried out a
detailed population viability analysis of the species
• Included study of habitat attributes and dynamics
• These data were used to develop a population
simulation model
• Enabled a suitable management plan to be
implemented to ensure survival of the possum,
even with environmental and demographic
uncertainty
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Fig. B42.4: Leadbeater’s possum
(Gymnobelideus leadbeateri)
Copyright © Fredy Mercay/ANT Photo Library
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Viable population sizes for
conservation
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The minimum viable population size (MVP) is
different for each species, and for each set of
circumstances
All species will eventually become extinct
Four chance processes may cause extinction
– genetic stochasticity, i.e. sufficient heterozygosity is
needed in the population
– demographic stochasticity, i.e. the random nature of
births and deaths can wipe out a small population
– environmental stochasticity and catastrophes, e.g. fire,
drought, flood can unpredictably exterminate entire
populations
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Fig. 42.16: Sumatran rhinoceros
(Dicerorhinus sumatrensis)
Copyright © Jean-Paul Ferrero/AUSCAPE
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