Predicting species diversity in tropical forests

Plotkin, Joshua B. ; Potts, Matthew D. ; Yu, Douglas W. ; Bunyavejchewin, Sarayudh ; Condit, Richard ; Foster, Robin ; Hubbell, Stephen ; LaFrankie, James ; Manokaran, N. ; Seng, Lee Hua ; Sukumar, Raman ; Nowak, Martin A. ; Ashton, Peter S. (2000) Predicting species diversity in tropical forests PNAS, 97 (20). pp. 10850-10854. ISSN 0027-8424

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Official URL: http://www.pnas.org/content/97/20/10850.abstract?s...

Related URL: http://dx.doi.org/10.1073/pnas.97.20.10850

Abstract

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 1/4. 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.

Item Type:Article
Source:Copyright of this article belongs to National Academy of Sciences.
ID Code:51891
Deposited On:01 Aug 2011 07:42
Last Modified:18 May 2016 05:39

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