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Species abundance distributions: moving beyond single prediction theories to integration within an ecological framework
Authors:McGill Brian J  Etienne Rampal S  Gray John S  Alonso David  Anderson Marti J  Benecha Habtamu Kassa  Dornelas Maria  Enquist Brian J  Green Jessica L  He Fangliang  Hurlbert Allen H  Magurran Anne E  Marquet Pablo A  Maurer Brian A  Ostling Annette  Soykan Candan U  Ugland Karl I  White Ethan P
Affiliation:Department of Biology, McGill University, 1205 Ave Dr Penfield, Montreal, QC H3A 1B1, Canada;
Community and Conservation Ecology Group, University of Groningen, Haren, The Netherlands;
Department of Biology, University of Oslo, Oslo, Norway;
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA;
Department of Statistics, University of Auckland, Auckland, New Zealand;
Gatty Marine Laboratory, University of St Andrews, Fife, Scotland;
Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA;
School of Natural Sciences, University of California Merced, Merced, CA, USA;
Department of Renewable Natural Resources, University of Alberta, Edmonton, Alberta, Canada;
National Center for Ecological Analysis and Synthesis, University of California Santa Barbara, Santa Barbara, CA, USA;
Center for Advanced Studies in Ecology &Biodiversity (CASEB), Departamento de Ecología, Facultad de Ciencias Biolígicas, Pontificia Universidad Católica de Chile, Alameda 340, Santiago, Chile;
Instituto de Ecología y Biodiversidad (IEB), Departamento de Ciencias Ecológicas. Facultad de Ciencias, Universidad de Chile. Casilla 653, Santiago, Chile;
Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA;
School of Life Sciences, Arizona State University, Tempe, AZ, USA
Abstract:
Species 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.
Keywords:Environmental indicators    macroecology    scientific inference    species abundance distributions
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