42-1Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Chapter 42: Population ecology

42-2Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

What is a population?

• ‘A number of organisms of the same species in a defined geographical area’

• Properties of populations include– 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)

42-3Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Distribution and abundance

• 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

42-4Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. 42.2a: Probability of occurrence of different eucalypts

42-5Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Measuring the size of animal populations• 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

• Technique has been used successfully on whales, lizards

42-6Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Density-independent population dynamics• 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

42-7Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Exponential population growth in discrete time• 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:

so

(where b,d, are birth, death rates respectively)

• If Rt, the growth factor each year, is constant

• Small changes in R have major effects on population size, see Fig. 42.4

)1(1 ttttt dNbNN

ttt NRN 1

0NRN tt

42-8Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. 42.4: Different growth factors

42-9Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Environmental variability and exponential growth

• 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

42-10Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

The average growth rate

• Geometric mean of R = ½ (correct: population declining), but arithmetic mean of R = 1.0625 is incorrect: population not increasing

42-11Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Exponential growth in continuous time• 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’

• In the continuous time model of exponential growth, the intrinsic rate of growth r determines the fate of the population

ttt

rNNdbdt

dN )(

42-12Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Range expansions

• 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))

42-13Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. 42.6a: Expansion of a population of Avicennia marina

42-14Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. 42.6b: Avicennia estuary

Copyright © G R Roberts, Photo Library, New Zealand

42-15Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

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.)

42-16Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. 42.7a: Antechinus stuartii

Copyright © C A Henley/AUSCAPE

42-17Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. 42.7b: Poulation size of Antechinus stuartii

42-18Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. 42.8: Logistic growth

42-19Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Density-dependent population dynamics (cont.)• Population approaches an equilibrium state at the

carrying capacity, K• The logistic growth equation is

• 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

K

NrN

dt

dN1

42-20Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Is density-dependent control important or not?

• 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

42-21Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Space-limited populations

• 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

42-22Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig 42.10: Competition for space

Copyright © Paddy Ryan/ANT Photo Library

42-23Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

The law of constant yield

• 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)

42-24Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. B42.2: The rule of constant yield

42-25Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Age- and size-structured population dynamics• 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

42-26Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. 42.11a: Age-structured population dynamics

42-27Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. 42.11b: Age-structured population dynamics

42-28Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Australia’s human population dynamics• 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

42-29Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Bio-economics

• 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

42-30Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Leadbeater’s possum• 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

42-31Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. B42.4: Leadbeater’s possum (Gymnobelideus leadbeateri)

Copyright © Fredy Mercay/ANT Photo Library

42-32Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Viable population sizes for conservation• 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

42-33Copyright 2005 McGraw-Hill Australia Pty Ltd PPTs t/a Biology: An Australian focus 3e by Knox, Ladiges, Evans and Saint

Fig. 42.16: Sumatran rhinoceros (Dicerorhinus sumatrensis)

Copyright © Jean-Paul Ferrero/AUSCAPE