Studying Ecosystems: Ecological Experiments, Sampling Techniques, Statistical Methods

Investigations into ecosystems are very complicated since there are so many different factors that need to be considered. We can broadly group factors influencing ecosystems into: biotic factors - living factors affecting an organism, such as food, composting or disease, and abiotic factors, non-living factors. Some of these, how they can be recorded and their importance are outlined in the table below.

It is not possible to survey an entire area, so small areas called samples are taken, these are two methods used.

Quadrat Sampling

Quadrat sampling takes small areas, randomly chosen from an ecosystem. These areas are bounded by a metal frame called a quadrant. Where to place the quandrat is usually decided by dividing an area in a grid, and then randomly selecting co-ordinates (throwing isn't scientific enough!). For instance, below point (2,3) has been chosen to be sampled.

Quadrats are more useful for comparing species in two different areas, and for practical purposes are used in ecosystems without tall vegetation - such as meadows or shores. A problem occurs when counting plants because they grow in clumps. This is overcome by calculating the density or the percentage of ground covered.

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   Transect Sampling

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   Transect sampling is used to measure the change from one area to another. It is carried out by laying a line along an area, and then recording species the line touches, or placing a quadrat at regular intervals.

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   1. A slightly different method is a belt transect, where two parallel lines are laid and the conditions between these measured.

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Once you have performed an ecological investigation, you will have a lot of data and need to represent and interpret it somehow; to do this we use statistics. One method of interpreting the mean that you may be familiar with, is the standard deviation. This is a measure of how spread out the data is. For instance, 10, 11 ,12, 13, 14 have a mean of 12, but 1, 1, 1, 1, 56 also have a mean of 12, this is where the standard deviation is useful.

The equation for standard deviation is:

So to calculate for 10, 11, 12, 13, 14, we square each number and add them together (100 + 121 + 144 + 169 + 196) to give us Σx2 which = 730. The mean=12, mean2 = 144 and n*mean2 = 720. Therefore the standard deviation is:

Now compare this with the standard deviation for the second set of data.

To Indicate How Spread Out The Data Is

In our examples it was clearly obvious, but if you have thousands of pieces of data it becomes very important. If you notice a change in two conditions, is this merely down to chance, or something else? This is where statistical tests are used - they tell us whether a change is significant. One such test that is commonly used is the Chi squared test.

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