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Minimising Observer Error

Increasing the reliability of a monitoring project
  • Clive Hurford
Chapter

5. In Summary

In this chapter we have discussed various forms of field assessment available for monitoring the quality of a habitat, concentrating on three principal components: vegetation cover, species composition, and vegetation height.

The results from multiple-observer sampling trials have indicated that the most reliable measures for monitoring habitats are presence and absence data; simple counts of abundance; and using a drop disc to record vegetation height.

As a general rule, we should try to avoid using estimates of vegetation cover in a monitoring project unless absolutely necessary. If we decide that it is essential, then we should monitor against cover targets. The results from sampling trials suggest that if we set up a monitoring project where the result can depend solely on estimates of vegetation cover, then the reliability of the monitoring result will be compromised by unacceptable levels of observer bias.

For this reason, we should think carefully about what we need to know about the vegetation that we are monitoring before deciding how to monitor it. If we consider, within any broad habitat type, which examples of a habitat we regard to be of high conservation interest, and why, we will probably begin to focus on those with a good representation of stress tolerating species (Chapter 8). These species will become scarcer as the more competitive species achieve dominance. This suggests that, in most cases at least, it is actually the presence of the stress tolerators (and associated species) that dictates the conservation value of the habitat, rather than the cover of the potentially dominant competitors. If we accept this, then the most efficient and reliable approach to monitoring the condition of a habitat is to focus on the frequency (or abundance) of the stress tolerating associate species, and not the cover of the dominants.

Keywords

Vegetation Height Cover Target Observer Bias Sampling Trial Monitoring Project 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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6. References

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Copyright information

© Springer 2006

Authors and Affiliations

  • Clive Hurford
    • 1
  1. 1.Countryside Council for Wales, Plas Penrhos, Ffordd PenrhosBangor, Gwynedd

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