There is considerable pressure on conservation planners to use existing data from herbarium and museum collections for planning and monitoring, despite the weaknesses of such data. It is thus important to be able to assess the quality of this information. One application of these data is the production of species richness maps. However, sampling effort is generally not consistent throughout a region for maps generated from collections data, and it is thus desirable to identify geographic grid cells (such as quarter degree squares: QDS) for which there has been low sampling effort. We describe a technique that can be used to identify QDS that are likely to have low species richness that is due to insufficient sampling effort rather than to low actual species richness. The technique exploits relationships between climate and species richness to detect QDS that are poorly sampled. This approach offers advantages over the current practice of applying a single threshold across the entire map region to detectQDSthat are poorly sampled. Here we report on the application of our technique to plant species richness data in the PRECIS database. Results reveal that the majority of QDS in the Flora of Southern Africa region can be considered to be poorly sampled, even when using conservative thresholds for richness values. The advantages and weaknesses of the technique are discussed and issues requiring further investigation are highlighted.
| Identifer | oai:union.ndltd.org:Rhodes/oai:eprints.ru.ac.za:325 |
| Date | January 2006 |
| Creators | Robertson, M.P., Barker, N.P. |
| Source Sets | Rhodes University SA |
| Detected Language | English |
| Type | Article, PeerReviewed |
| Format | application/pdf |
| Relation | http://eprints.ru.ac.za/325/ |
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