Authors:
A. Chiarucci University of Siena BIOCONNET, Biodiversity and Conservation Network, Department of Environmental Science “G. Sarfatti” Via P.A. Mattioli 4 53100 Siena Italy

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G. Bacaro University of Siena BIOCONNET, Biodiversity and Conservation Network, Department of Environmental Science “G. Sarfatti” Via P.A. Mattioli 4 53100 Siena Italy

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D. Rocchini Environment and Natural Resources Area IASMA Research and Innovation Centre, Fondazione Edmund Mach Via E. Mach 1 38010 S. Michele all’Adige, TN Italy

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C. Ricotta La Sapienza, University Department of Plant Sciences P.le Aldo Moro 5 00100 Roma Italy

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M. Palmer Oklahoma State University Department of Botany Stillwater OK 74078 USA

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S. Scheiner National Science Foundation Division of Environmental Biology 4201 Wilson Blvd. Arlington VA 22230 USA

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Rarefaction is a widely applied technique for comparing the species richness of samples that differ in area, volume or sampling effort. Despite widespread adoption of sample-based rarefaction curves, serious concerns persist. In this paper, we address the issue of the spatial arrangement of sampling units when computing sample-based rarefaction curves. If the spatial arrangement is neglected when building rarefaction curves, a direct comparison of species richness estimates obtained for areas that differ in their spatial extent is not possible, even if they were sampled with a similar intensity. We demonstrate a major effect of the spatial extent of the samples on species richness estimates through the use of data from a temperate forest. We show that the use of Spatially Constrained Rarefaction (SCR) results in species richness estimates that are directly comparable for areas that differ in spatial extent. As expected, standard rarefaction curves tend to overestimate species richness because they ignore the spatial autocorrelation of species composition among sampling units. This spatial autocorrelation is captured by the SCR, thus providing a useful technique for characterizing the spatial structure of biodiversity patterns. Further work is necessary to determine how species richness estimates and the shape of the SCR are affected by the method of spatial constraint and sampling unit density and distribution.

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Community Ecology
Language English
Size A4
Year of
Foundation
2000
Volumes
per Year
1
Issues
per Year
3
Founder Akadémiai Kiadó
Founder's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245
Publisher Akadémiai Kiadó
Springer Nature Switzerland AG
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 1585-8553 (Print)
ISSN 1588-2756 (Online)

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