What is Population Ecology ?
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What is Population Ecology? 1
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What is Population Ecology ?. Ecology is. the study of interactions among organisms with each other and with their environment. Ecology studies these interactions at different levels, called levels of organization . So....Population Ecology is. - PowerPoint PPT Presentation
Transcript of What is Population Ecology ?
1 What is Population Ecology?
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Ecology is... the study of
interactions among organisms with each other and with their environment
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Ecology studies these interactions at different levels, called levels of organization.
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Level of Organizati
on
Definition Example
Species individuals that can breed with one another
Population all the individuals of the same species in an area
Community
all the different species in an area
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Level of Organizati
on
Definition Example
Ecosystem the community plus the physical factors in an area
Biome large area that has a particular climate and particular species of plants and animals
Biosphere the part of the earth that supports life
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So....Population Ecology is the study of how the population sizes
of species living together in groups change over time and space
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Population Characteristics There are three
characteristics that all populations have:
1) population density,
2) spatial distribution,
3) and growth rate.
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1. Population Density Refers to the number of individuals in
relation to the space
Population Density =
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1. Population Density Example: What is the density of a rabbit
population of 200 living in a 5 km2 range?
Solution: Population Density =
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1. Population Density Example: What is the density of a rabbit
population of 200 living in a 5 km2 range?
Solution: Population Density =
Population Density =
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1. Population Density Example: What is the density of a rabbit
population of 200 living in a 5 km2 range?
Solution: Population Density =
Population Density =
Population Density = 40 rabbits / km2
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1. Population Density Density – dependent factors – factors
that can affect a population growth because of its density. E.g. Food supply, competition for mates, spread of disease.
Density- independent factors – factors that can affect a population growth regardless of its density. E.g. Forest fires, Flood, Habitat destruction, Pollution
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2. Spatial Distribution Refers to the pattern of spacing of a
population within an area
3 types: clumped, uniformly spaced, and random
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2. Spatial Distribution Results from dispersion – the spreading of
organisms from one area to another
Three types of barriers prevent dispersal: Physical barriers (e.g. mountains, oceans) Ecological barriers (e.g. grassland animals do
not move into forests) Behavioural barriers (e.g. birds that prefer tall
trees over short trees will not disperse into short trees)
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3. Growth Rate Refers to how fast a population grows
4 factors determine how a population changes:
Natality (birth rate) Mortality (death rate) Immigration (individuals moving into a
population) Emigration (individuals moving out of a
population)
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3. Growth Rate Population change can be calculated as:
Birth rate – death rate + immigration - emigration
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3. Growth Rate Example: In a given year, a pack of timber
wolves experiences the birth of 3 pups and the death of a lone wolf. No animals moved into the pack but 1 wolf did leave.
Solution:
Birth rate – death rate + immigration - emigration
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3. Growth Rate Example: In a given year, a pack of timber
wolves experiences the birth of 3 pups and the death of a lone wolf. No animals moved into the pack but 1 wolf did leave.
Solution:
Birth rate – death rate + immigration - emigration
= 3 – 1 + 0 – 1
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3. Growth Rate Example: In a given year, a pack of timber wolves
experiences the birth of 3 pups and the death of a lone wolf. No animals moved into the pack but 1 wolf did leave.
Solution:
Birth rate – death rate + immigration - emigration = 3 – 1 + 0 – 1 = 1 Meaning that in this year, the wolf pack experienced a
growth of 1 wolf.
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How do know how many organisms make up a population?
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Yes, we count them!
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But what about…?
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Population Sampling Methods
When the number of organisms in a population is hard to count, scientists estimate the total population size
They do this by first sampling the population and then calculating a population size based on the data
There are 3 methods: Mark-Recapture, Quadrat, and Random Sampling
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1. Mark-Recapture Sampling Also called ‘tagging’
A sample of organisms is captured and marked and then returned unharmed to their environment
Over time, the organisms are recaptured and data is collected on how many are captured with marks
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1. Mark-Recapture Sampling
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1. Mark-Recapture Sampling
Example: In order to estimate the population of sturgeon fish in the river, biologists marked 10 sturgeon fish and released them back into the river. The next year, 15 sturgeon were trapped and 3 were found to have marks.
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1. Mark-Recapture Sampling
Example: In order to estimate the population of sturgeon fish in the river, biologists marked 10 sturgeon fish and released them back into the river. The next year, 15 sturgeon were trapped and 3 were found to have marks.
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1. Mark-Recapture Sampling
Example: In order to estimate the population of sturgeon fish in the river, biologists marked 10 sturgeon fish and released them back into the river. The next year, 15 sturgeon were trapped and 3 were found to have marks.
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1. Mark-Recapture Sampling
Example: In order to estimate the population of sturgeon fish in the river, biologists marked 10 sturgeon fish and released them back into the river. The next year, 15 sturgeon were trapped and 3 were found to have marks.
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1. Mark-Recapture Sampling Best for mobile
populations, such as fish and birds
Problems occur when no marked organisms are captured
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2. Quadrat Sampling A sampling frame
(quadrat, usually 1m2) is used to count the individuals in a mathematical area
Population size is then estimated based on the data from the quadrat
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2. Quadrat Sampling Example: A biologist counts
13 mushrooms in a 1m x 1m quadrat. The area of study is 12m2.
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2. Quadrat Sampling Example: A biologist counts
13 mushrooms in a 1m x 1m quadrat. The area of study is 12m2.
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2. Quadrat Sampling Example: A biologist counts
13 mushrooms in a 1m x 1m quadrat. The area of study is 12m2.
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2. Quadrat Sampling Example: A biologist counts
13 mushrooms in a 1m x 1m quadrat. The area of study is 12m2.
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Quadrat Sampling Best for small
stationary populations, such as plants & mushrooms
Problems occur when the quadrats are placed in ‘abnormal’ locations
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3. Random Sampling The number of organisms
within a small area (plot) is counted.
The plots are often placed randomly throughout the sampling area
Population size and density are then estimated based on the plot representation.
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3. Random Sampling1. Find the average # of individuals in the
areas you sampled.
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3. Random Sampling 1. Find the average # of individuals in the
areas you sampled.
2. Multiply the average by the # of plots to find the population estimate
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3. Random SamplingExample: A sample was taken to count the
number of silver maple trees in the forest. The number of trees counted in the grid is shown below.
5 3
4 4
1
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3. Random SamplingExample: A sample was taken to count the
number of silver maple trees in the forest. The number of trees counted in the grid is shown below.
1.5 3
4 4
1
per plot
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3. Random SamplingExample: A sample was taken to count the
number of silver maple trees in the forest. The number of trees counted in the grid is shown below.
1.5 3
4 4
1
per plot
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3. Random SamplingExample: A sample was taken to count the
number of silver maple trees in the forest. The number of trees counted in the grid is shown below.
1.5 3
4 4
1
per plot
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3. Random SamplingExample: A sample was taken to count the
number of silver maple trees in the forest. The number of trees counted in the grid is shown below.
2.5 3
4 4
1
per plot
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3. Random SamplingExample: A sample was taken to count the
number of silver maple trees in the forest. The number of trees counted in the grid is shown below.
2.5 3
4 4
1
per plot
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3. Random SamplingExample: A sample was taken to count the
number of silver maple trees in the forest. The number of trees counted in the grid is shown below.
2.5 3
4 4
1
per plot
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3. Random Sampling Best for large
stationary populations, such as trees or coral
Problems occur when random sampling is not followed
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Now it’s your turn…
