4.6 Article

An empirical evaluation of four variants of a universal species-area relationship

期刊

PEERJ
卷 1, 期 -, 页码 -

出版社

PEERJ INC
DOI: 10.7717/peerj.212

关键词

Abundance; Biodiversity; Species richness; Entropy; Information theory; Scaling

资金

  1. CAREER grant from the U.S. National Science Foundation [DEB-0953694]
  2. National Science Foundation [DEB-0515520, DEB-084259, DEB-0640386, DEB-0425651, DEB-0346488, DEB-0129874, DEB-00753102, DEB-9909347, DEB-9615226, DEB-9405933, DEB-9221033,, DEB-9100058,, DEB-8906869,, DEB-8605042,, DEB-8206992,, DEB-7922197]
  3. Pepper-Giberson Chair Fund, the University of California.
  4. Center for Tropical Forest Science
  5. Smithsonian Tropical Research Institute
  6. John D and Catherine T. MacArthur Foundation
  7. Mellon Foundation
  8. Small World Institute Fund
  9. numerous private individuals
  10. NSF [BSR-8811902, DEB 9411973, DEB 0080538, DEB 0218039, DEB 0620910, DEB 0963447]
  11. Division Of Environmental Biology
  12. Direct For Biological Sciences [0953694] Funding Source: National Science Foundation

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The Maximum Entropy Theory of Ecology (METE) predicts a universal species-area relationship (SAR) that can be fully characterized using only the total abundance (N) and species richness (S) at a single spatial scale. This theory has shown promise for characterizing scale dependence in the SAR. However, there are currently four different approaches to applying METE to predict the SAR and it is unclear which approach should be used due to a lack of empirical comparison. Specifically, METE can be applied recursively or non-recursively and can use either a theoretical or observed species-abundance distribution (SAD). We compared the four different combinations of approaches using empirical data from 16 datasets containing over 1000 species and 300,000 individual trees and herbs. In general, METE accurately downscaled the SAR (R-2 > 0.94), but the recursive approach consistently under-predicted richness. METE's accuracy did not depend strongly on using the observed or predicted SAD. This suggests that the best approach to scaling diversity using METE is to use a combination of non-recursive scaling and the theoretical abundance distribution, which allows predictions to be made across a broad range of spatial scales with only knowledge of the species richness and total abundance at a single scale.

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