Population Ecology (Ecology and Conservation)

Lectures 2, 3, 4

Why population biology is important

It provides a bridge between the way individuals function, behave and interact, and larger scale organisation - the community and ecosystem. It helps us to understand how organisms are dispersed in space and time.

Example of why population biology is important

It helps adjust and advise on the common fishery policy to ensure that overfishing does not happen.

Population

A group of individuals of the same species occupying a given area at a given time (often arbitrary boundaries).

A group of organisms that share a common gene pool.

Metapopulation

A group of spatially separated populations linked by dispersal.

Population dynamics are determined by

…population structure (demography)

What is included in population structure?

Size (abundance)

Density (abundance per unit area)

Distribution (dispersion in space)

Age structure (proportion in each age category)

Genetic structure (including inbreeding levels)

Birth and death rates (gains and losses to population)

Immigration and emigration rates (dispersal)

Why estimating population abundance is important to population ecology

We need to know whether our population is large (a pest) or small (endangered).

We need to know whether our population is changing over time (stable, growing or declining), in order to determine appropriate management strategies.

Examples of how we determine population size

Total counts

Estimate absolute numbers

Indices of relative abundance

Population size

Abundance

It is often only interesting when we are dealing with relatively small or isolated populations (e.g. endangered species or species on islands)

Population density

Individuals per unit area or volume.

It is generally more interesting because population regulation depends on density-dependent processes.

The relationship between population size and population density depends on…

the spatial dispersion and dispersal patterns of individuals.

Dispersion of individuals within a population =

their spacing with respect to one another

The 3 extreme patterns of population distribution

Random

Uniform

Clumber/aggregated

Population distribution - random

Plants like daisies and ferns and most tree species. This is due to the random seed dispersal being reliant on the wind which changes

Population distribution - uniform

Most territorial birds, red wood trees and penguins. Red wood trees block out the light around them so new plants have to be a minimum distance away to be able to compete for sunlight. Penguins will peck their neighbours if they aren’t far enough away.

Population distribution - clumped

Shoaling fish and flocking birds do this for protection to make themselves appear bigger. Oak trees, acorns are not wind dispersed seeds so end up falling straight down.

Factors influencing population change

Relative birth, death, immigration and emigration rates (i.e. proportional change)

Relative change in population in a specific time (Triangle N) =

Birth - Death.

This can mask changes in birth and death if the changes are equal and opposite.

Basic population growth model in a closed population

Nt + B - D = Nt+1

The population add the births and minus the deaths = the population at a different time.

Basic population growth model in an open population

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

Population at a time in the future = population now + births + imegration - deaths - emigration

Example of unconstrained population growth - pest populations

Early stages of population growth in aphids introduced onto an uninfected plant.

Unconstrained population growth - closed circuit microbial populations

Early stages of population growth in yeast (Saccharomyces) inoculated into a fresh culture. 5 replicates and they all fitted the curve showing exponential growth.

Unconstrained population growth - closed system introduced animals

Reindeers reintroduced to an island. Native animals include vole and polar bear so some predators. They were released in 1944 and their population grew exponentially to around 6,000, until 1966 when in crashed off and only 42 reindeer left.

Exponential decline example

Blue Whale (Balaenoptera musculus). Lives in the southern hemisphere and North Pacific. Pre-whaling populations where estimated to be around 300,00 but by the mid 1900s there were less than 1000 due to the commercial whaling industry.

Exponential growth example - numbers have now improved

Predicted to go extinct by mid 1980s, hunting ceased in 1967 and now 10,000-25,000 blue whales worldwide.

Relative growth rate (R)

Technical term (fundamental net reproductive rate = proportional change in population size from time (t) to time (t+1).

Relative growth rate equation

R = Nt+1 / N+t = net difference in birth rate and death rate

Sometimes R is replaced with lambda (upside down y)

R and population growth

R is always positive with it being less than 1 meaning the population declines and it being more than one meaning it is growing.

If R = 1.2 then what does that mean for the population?

It is increasing by 20% each year.

When R = 2…

the population grows by 100% each generation (it doubles and is growing exponentially)

Musk Oxen (Ovibos moschatus) on Nunivak Island Alaska

Musk oxen extinct in Alaska in 1850 and 31 were reintroduced in 1936. It was a good habitat for them with no predators. By 1966 there were 610 animals

What sort of system was the Musk Oxen reintroduction?

A closed system

Musk Oxen and Relative growth rate

R = N1966 / N1965 and this is the population of 1 divided by the population of the year before and you do this for all the years and find the mean for R. The growth for the Musk Oxen is estimated to be 1.14.

Equation to project population size in the future.

Nt+1 = Nt * R

Problems with the simple R model

Populations cannot grow exponentially forever and in some cases we can see population crashes which this model doesn’t take into account. In others we see populations stabilising at a particular size while others we see chaotic fluctuations.