Species abundance distributions: moving beyond single prediction theories to integration within an ecological framework

Ecology Letters - Tập 10 Số 10 - Trang 995-1015 - 2007
Brian J. McGill1, Rampal S. Etienne2, John S. Gray3, David Alonso4, Marti J. Anderson5, Habtamu Benecha2, María Dornelas6, Brian J. Enquist7, Jessica L. Green8, Fangliang He9, Allen H. Hurlbert10, Anne E. Magurran6, Pablo A. Marquet11,12,10, Brian A. Maurer13, Annette Ostling4, Candan U. Soykan14, Karl Inne Ugland3, Ethan P. White7
1McGill University
2University of Groningen
3University of Oslo#TAB#
4UNIVERSITY OF MICHIGAN
5University of Auckland
6University of St Andrews
7University of Arizona
8University of California Merced
9University of Alberta
10University of California at Santa Barbara
11Pontificia Universidad Catolica de Chile
12Universidad de Chile
13Michigan State University
14Arizona State University**

Tóm tắt

AbstractSpecies abundance distributions (SADs) follow one of ecology’s oldest and most universal laws – every community shows a hollow curve or hyperbolic shape on a histogram with many rare species and just a few common species. Here, we review theoretical, empirical and statistical developments in the study of SADs. Several key points emerge. (i) Literally dozens of models have been proposed to explain the hollow curve. Unfortunately, very few models are ever rejected, primarily because few theories make any predictions beyond the hollow‐curve SAD itself. (ii) Interesting work has been performed both empirically and theoretically, which goes beyond the hollow‐curve prediction to provide a rich variety of information about how SADs behave. These include the study of SADs along environmental gradients and theories that integrate SADs with other biodiversity patterns. Central to this body of work is an effort to move beyond treating the SAD in isolation and to integrate the SAD into its ecological context to enable making many predictions. (iii) Moving forward will entail understanding how sampling and scale affect SADs and developing statistical tools for describing and comparing SADs. We are optimistic that SADs can provide significant insights into basic and applied ecological science.

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