IUCN / SSC Cat Specialist Group - Digital Cat Library |
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| Plotkin, J.B.; Potts, M.D.; Yu, D.W.; Bunyavejchewin, S.; Condit, R.; Foster, R.; Hubbell, S.; LaFrankie, J.; Manokaran, N.; Seng, L.H.; Sukumar, R.; Nowak, M.A.; Ashton, P.S. | |
| Predicting species diversity in tropical forests | |
| 2000 Pnas (97): 10850-10854 | |
A fundamental question in ecology is how many species occur within a given area. Despite the complexity and diversity of different ecosystems, there exists a surprisingly simple, approximate answer: the number of species is proportional to the size of the area raised to some exponent. The exponent often turns out to be roughly 1y4. This power law can be derived from assumptions about the relative abundances of species or from notions of self-similarity. Here we analyze the largest existing data set of location-mapped species: over one million, individually identified trees from five tropical forests on three continents. Although the power law is a reasonable, zeroth-order approximation of our data, we find consistent deviations from it on all spatial scales. Furthermore, tropical forests are not self-similar at areas <50 hectares. We develop an extended model of the species-area relationship, which enables us to predict large-scale species diversity from small-scale data samples more accurately than any other available method. |
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