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||Size||Format||ResearchPaper.pdf||File only available to GIS staff and students||3.95 MB||Adobe PDF||TechnicalReport.pdf||File only available to GIS staff and students||973.28 kB||Adobe PDF|
|Title: ||Correcting for sampling effort variation in analysis of bio-diversity hotspots: a GIS approach|
|Authors: ||Dear, Thomas Robert|
|Supervisor(s): ||Legg, Colin|
|Issue Date: ||Oct-2008|
|Abstract: ||The designation of species richness hotspots is becoming increasingly important as the United Kingdom attempts to meet it’s conservation obligations under the United Nations Convention on Biological Diversity. The theory is that by preserving small areas of land it is possible to conserve a disproportionately large number of species.
A high proportion of UK species records used to designate areas as hotspots is sourced from volunteer and archived records which have the potential to contain sampling biases. This project looked at the affects of recorder effort on overall species richness levels with the expectation that increased effort will result in increased species richness for a given area.
It was found that the amount of sampling effort was highly variable amongst volunteer records resulting in poor correlation between sampling effort and species richness. A model was proposed based upon standardisation of individual sites to have received five visits. The model also estimated the expected rate of species accumulation at each site based upon the average rate for the study region as a whole. This technique highlighted a shift in the overall distribution of species hotspots with a number of new sites identified for further sampling. In total 75 sites were predicted to have higher species richness than at present and 59 sites were found to decrease in richness.
The results were explored using three different visualisation styles: grid based hotspot maps, Thiessen polygon maps and Kernel Density Estimation maps. Thiessen polygons were found to be useful in highlighting areas of high or low sampling intensity however the more traditional grid square maps presented a higher degree of accuracy for interpretation of results.|
|Keywords: ||Sampling Effort Bias|
|Appears in Collections:||MSc Geographical Information Science thesis collection|
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