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Towards a unified descriptive theory for spatial ecology: predicting biodiversity patterns across spatial scales

Zugehörigkeit
Department of Applied Mathematics, School of Mathematics, University of Leeds, Leeds LS2 9JT, UK
Azaele, Sandro;
Zugehörigkeit
Dipartimento di Fisica ‘G. Galilei’ & CNISM, INFN, Università di Padova, Via Marzolo 8, 35131 Padova, Italy
Maritan, Amos;
Zugehörigkeit
Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK
Cornell, Stephen J.;
GND
1221084011
Zugehörigkeit
Dipartimento di Fisica ‘G. Galilei’ & CNISM, INFN, Università di Padova, Via Marzolo 8, 35131 Padova, Italy
Suweis, Samir;
Zugehörigkeit
Department of Physics, University of Maryland, College Park,MD 20742, USA
Banavar, Jayanth R.;
GND
132356449
Zugehörigkeit
Julius Kühn-Institute (JKI), Institute for Crop and Soil Science, Germany; School of Biology, University of Leeds, Leeds LS2 9JT, UK
Gabriel, Doreen;
GND
115837576X
Zugehörigkeit
School of Biology, University of Leeds, Leeds LS2 9JT, UK
Kunin, William E.

1. A key challenge for both ecological researchers and biodiversity managers is themeasurement and prediction of species richness across spatial scales. Typically, biodiversity is assessed at fine scales (e.g. in quadrats or transects) for practical reasons, but often we are interested in coarser-scale (field, regional, global) diversity issues. Moreover, the pressures affecting biodiversity patterns are often scale specific, making multiscale assessment a crucialmethodological priority. As species richness is not additive, it is difficult to translate from the scale ofmeasurement to the scale(s) of interest. A number of methods have been proposed to tackle this problem, but most are toomodel specific or too rigid to allow general application. Here, we present a general framework (and a specific implementation of it) that allows such scale translations to be performed. 2. Building on the intrinsic relationships among patterns of species richness, abundance and spatial turnover, we introduce a framework that links and predicts the profile of the species-area relationship and the speciesabundance distributions across scales when a limited number of fine-scale scattered samples are available. Using the correlation in species’ abundances between pairs of samples as a function of the distance between them, we are able to link the effects of aggregation, similarity decay, species richness and species abundances across scales. 3. Our approach allows one to draw inferences about biodiversity scaling under very general assumptions pertaining to the nature of interactions, the geographical distributions of individuals and ecological processes. 4. We demonstrate the accuracy of our predictions using data from two well-studied forest stands and also demonstrate the potential value of such methods by examining the effects of management on farmland insects across scales. The framework has important applications to biodiversity research and conservation practice.

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