Russell Graham Russell Graham Russell Graham

It is very important not to over-interpret any information that you may have collected. Unless you are absolutely sure that you have counted every single individual or every single species (depending on the question you are asking) in your study area, you will not and cannot know how many there are. Remember this. It is very important. If you have collected numerous, representative samples from different sites within your area, you will have a good estimate of how many there are but you will still not know the true number. Information about numbers is usually presented as a measure of density (number per unit area) or the percentage cover (the amount of space they occupy). There will always be some error in how well your estimate measures the true abundance or cover, no matter how well you sample. This is called sampling error. Any difference between two estimates of abundance, for example the number of gum trees in two bushland parks, might therefore be due to sampling error (that is, how well your samples measure the true number of trees) or to the fact that one park really does have less trees than the other. Unless differences really are clear-cut, e.g. there are only a few trees in one park but apparently hundreds in the other, statistical tests are necessary to tell whether different estimates of abundance are likely to show real differences between different places (or different times). These tests take into account the number of samples used to estimate the abundances, the variability among them and the difference between the different sets of samples, e.g. the different areas.

Similarly, you might see what appear to be strong associations between species or between species and patches of habitat. There may seem to be more blue wrens in areas where there are few ravens; more thistles in patches where there are lots of blackberry bushes than where there are few blackberry bushes. Sea anemones may appear to be more common in rock pools than in deep crevices. Dandelions may appear more common next to roadways than in forests. Again unless these relationships are extremely obvious, you need statistical tests to indicate whether they represent real associations. Otherwise you are just guessing and anyone's guess is as good as anyone else's. Guessing is not science and not ecology.

So there are problems with interpreting whether any patterns in abundances of different animals and plants are indeed real, or whether they appear because of the ways that you have measured them. More detail about measuring and interpreting these patterns is given in Appendix 3. The next question that people are most interested in is Why? Why are animals found here and not there? Here the scientific basis of many apparently valid "ecological" studies founders - even if the patterns themselves are correct. There are a number of ways of approaching such questions, but only one is really useful so let's deal with the others first.

You can guess. That is what some people do, but it is dishonest and wastes all the effort you put into collecting the information in the first place.

Second, you can ask someone else and they can guess? This doesn't help much.

You can ask "an expert" and they can tell you the answer - a common approach. This is often the same as guessing unless they really do know what they are talking about. An honest "expert" may tell you that people do not know the answer. Do not dismiss such advice - there is a lot more that is not known about animals and plants in Australia than what is known.

Finally, he or she may be able to tell about some field experiments that have been done to try to answer the same or similar questions elsewhere. These are really the only way to investigate interactions between different species and their habitats and, thereby, even to begin to answer such complex questions about why something is found where it is. If these experiments have been done a number times in different places, you may feel justified in thinking that the same processes might apply to your study site. Unfortunately, such field experiments are not common, except for a few habitats such as intertidal rocky shores in New South Wales. These have been extensively studied using field experiments and there is a wealth of data available about them in the scientific literature. This cannot be said for most other habitats. Unfortunately, these studies frequently show that similar patterns can be caused by different processes from place to place. Therefore an experiment done once in one place may not necessarily tell you anything much about your own study site.

This is not the place to go into much detail about the need for field experiments to interpret patterns of different species in nature. A brief outline about the way in which science in general and ecology in particular is done to answer such questions is given in Appendix 3.

Finally, a last note about the advantages of networking.

  1. You can make your study part of a larger study, either by looking at a number of different study areas or looking at one or more areas a number of times. This will allow you to think about your study area in relation to other similar habitats and, more importantly, will introduce you to the way the world really is -naturally variable from place to place or time to time.

  2. You can spread the work load by allocating different questions to different people. Some might look at the diversity of species in a habitat. Others might look at densities of certain interesting species and yet others might examine how people interact with habitats.

  3. You can meet and talk to other groups of people who have similar interests and concerns.

  4. You can make your information more widely available and of more general use.

 Networking will not, however, work unless you

  1.  Talk to each other about what you want to do. Make sure that the questions you are asking are clearly understood by everyone. All agree as to why you are doing it.

  2. Know where the study area is, what habitats or sites are going to be sampled and when and how they will be sampled. Do not change your minds after you start

  3. Summarize the data into a digestible format so that you all understand what it is about.

  4. Get together to discuss your findings in a workshop or series of meetings. Information to help you to do this is given in Sheet 9.

GOOD LUCK!


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Centre for Research on Ecological Impacts of Coastal Cities
email: rgraham@pacific.net.au