THE TWENTY COMMONEST CENSUS SINS IN ECOLOGY

(Source: William J Sutherland – School of biological sciences, University of East Anglia, Norwich NR4 7TJ, UK).

1. Not Sampling Randomly: It is very satisfying to sample rarities or rich patches but it ruins the exercise. One common error is just to visit the best sites and use the data to estimate the population size.
2. Collecting far more samples than can possibly be analysed.
3. Changing the methodology in monitoring unless there is a careful comparison of the different methods, changing the methodology prevents comparison between the years.
4. Counting the same individuals in two locations and counting it as two individuals.
5. Not knowing your species: knowing your species is essential for considering biases and understanding the data.
6. Not having controls in management experiments. This is the greatest problem in interpreting the consequences in management.
7. Not storing information from where it can be retrieved in the future.
8. Not giving precise information as to where sampling occurred:- Give date and precise location. Site ‘A’, behind the tree’ of ‘near to the road’ may be sufficient now but mean nothing later.
9. Counting in one or more or a few large areas rather than a large number of small ones:- A single count gives no measure of the natural variation and it is then hard to see how significant any changes are. This also applies to quadrats.
10. Not being honest about the methods used:- If you only survey butterflies on warm still days or place small mammal traps in the location most like to be successful then this is fine but say so. Someone else surveying on all days or randomly locating traps, may otherwise conclude that the species has declined.
11. Believing the results: - Practically every census has biases and inaccuracies. The secrete is to evaluate how much these matter.
12. Believing that the density of trapped individuals is the same as the absolute density.
13. Not thinking about how your will analyse your data before collecting it.
14. Assuming you know where you are: - This can be one problem when marking individuals on maps or even when censusing areas, e.g. a one-kilometer square kilometer marked on a map. Population overestimates can result from incorrectly marking the same individuals as occupying very different locations or by surveying a larger block than intended.
15. Assuming sample efficiency is similar in different habitats:- Difference in physical structure or vegetation structure will influence almost every censusing technique and thus confound comparisons.
16. Thinking that someone else will identify all your samples for you.
17. Not knowing why you are censusing: - Think exactly what the question is and that what data you need to answer it. It is nice to collect additional data but will this slow down the project so that the objectives are not accomplished?
18. Deviating from transect routes:- On one reserve the numbers of green Hairstreaks Callophyrus rubi seen on the butterfly-monitoring transect increased markedly one year. It turned out that this was because the temporary warden that year climbed through the hedge to visit the colony on the far side.
19. Not having a large enough area for the numbers to be meaningful; If it is impossible to have a large enough area then question whether the effort might not be better spent on another project.
20. Assuming others will collect data exactly in the same manner and with the same enthusiasm. The international Biological Programme gave very specific instructions, yet it was hard to make such sense of data because the slight differences in interpretation led to a very different results.