# Investigating populations

• Created by: Joanna
• Created on: 20-10-13 12:15

## Investigating populations

Sampling techniques include:

> Systematic sampling along transects.

Factors to be considered when using quadrats:

> Size of the quadrat - depends on size of plants/animals being counted and how they are distributed within the area.

> The number of sample quadrats to record in the study area - the greater the number of sample quadrats used, the more reliable results are likely to be.

> The position of each quadrat within the study area - random sampling must be used to produce statistically significant results.

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## Random Sampling

Random sampling helps avoid bias which will ensure data is valid.

Random sampling method:

1. Lay out 2 long tape measures at right angles, along 2 sides of the study area

2. Obtain a series of coordinates by using random numbers taken from a table or generated by a computer

3. Place a quadrat at the intersection of each pair of coordinates and record the species within it

Systematic sampling:

1. Line transect - a tape stretched across the ground in a straight line - any organism over which the line passes is recorded

2. Belt transect - a ***** (1m wide) marked by putting a second line parallel to the first - the species found within the belt between the lines are recorded

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## Measuring abundance

Abundance is the number of individuals of a species within a given area. Measured by:

1. Frequency - the liklihood of a particular species occurring in a quadrat

2. Percentage cover - an estimate of the area within a quadrat that a particular plant species covers.

The larger the number of quadrats used, the more representative the results are of the community

Mark-release-recapture techniques:

A known number of animals are caught & marked in some way & then released back into the community. After some time a given number of individuals is collected randomly & the number of marked individuals is recorded. The size of the population is then calculated as follows:

Estimated population size =

(total number of individuals in first sample x total number of individuals in second sample) /

number of marked individuals recaptured

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## The mark-release-recapture technique

The Mark-release-recapture technique relies on the following assumptions:

> The proportion of marked to unmarked individuals in the second sample is the same as the proportion of marked to unmarked individuals in the population as a whole.

> The marked individuals released from the first sample distribute themselves evenly among the remainder of the population and have sufficient time to do so.

> The population has a definite boundary so that there is no immigration into/emigration out of the population

> There are few if any deaths & births within the poulation

> The method of marking is non toxic to the individual nor does it make the individual more conspicuous and therefore more liable to predation

> The mark or label is not lost or rubbed off during the investigation

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## The mark-release-recapture technique

The Mark-release-recapture technique relies on the following assumptions:

> The proportion of marked to unmarked individuals in the second sample is the same as the proportion of marked to unmarked individuals in the population as a whole.

> The marked individuals released from the first sample distribute themselves evenly among the remainder of the population and have sufficient time to do so.

> The population has a definite boundary so that there is no immigration into/emigration out of the population

> There are few if any deaths & births within the poulation

> The method of marking is non toxic to the individual nor does it make the individual more conspicuous and therefore more liable to predation

> The mark or label is not lost or rubbed off during the investigation

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## Analysing data

> First stage = present data in graph / table

> Calculate the standard deviation

> Detect whether differences between groups of data are due to a particular factor or down to chance

> Analyse for possible correlations & causes

> Statistical tests can be used to calculate th strength & direction of any correlation between two variables

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