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Rarefaction (ecology)
About: Rarefaction (ecology) is a research topic. Over the lifetime, 752 publications have been published within this topic receiving 48646 citations.
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TL;DR: A series of common pitfalls in quantifying and comparing taxon richness are surveyed, including category‐subcategory ratios (species-to-genus and species-toindividual ratios) and rarefaction methods, which allow for meaningful standardization and comparison of datasets.
Abstract: Species richness is a fundamental measurement of community and regional diversity, and it underlies many ecological models and conservation strategies. In spite of its importance, ecologists have not always appreciated the effects of abundance and sampling effort on richness measures and comparisons. We survey a series of common pitfalls in quantifying and comparing taxon richness. These pitfalls can be largely avoided by using accumulation and rarefaction curves, which may be based on either individuals or samples. These taxon sampling curves contain the basic information for valid richness comparisons, including category‐subcategory ratios (species-to-genus and species-toindividual ratios). Rarefaction methods ‐ both sample-based and individual-based ‐ allow for meaningful standardization and comparison of datasets. Standardizing data sets by area or sampling effort may produce very different results compared to standardizing by number of individuals collected, and it is not always clear which measure of diversity is more appropriate. Asymptotic richness estimators provide lower-bound estimates for taxon-rich groups such as tropical arthropods, in which observed richness rarely reaches an asymptote, despite intensive sampling. Recent examples of diversity studies of tropical trees, stream invertebrates, and herbaceous plants emphasize the importance of carefully quantifying species richness using taxon sampling curves.
5,706 citations
United Nations Environment Programme1, American Museum of Natural History2, Imperial College London3, Swansea University4, University College London5, National University of Cordoba6, Tel Aviv University7, Max Planck Society8, University of Oldenburg9, Microsoft10, University of Oxford11, University of Wisconsin–Eau Claire12
TL;DR: A terrestrial assemblage database of unprecedented geographic and taxonomic coverage is analysed to quantify local biodiversity responses to land use and related changes and shows that in the worst-affected habitats, pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%.
Abstract: Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.
2,532 citations
TL;DR: A within-habitat analysis was made of the bivalve and polychaete components of soft-bottom marine faunas which differed in latitude, depth, temperature, and salinity, and it was indicated that species number is the more valid diversity measurement.
Abstract: In this paper a methodology is presented for measuring diversity based on rarefaction of actual samples. By the use of this technique, a within-habitat analysis was made of the bivalve and polychaete components of soft-bottom marine faunas which differed in latitude, depth, temperature, and salinity. The resulting diversity values were highly correlated with the physical stability and past history of these environments. A stability-time hypothesis was invoked to fit these findings, and, with this hypothesis, predictions were made about the diversities present in certain other environments as yet unstudied. The two types of diversity, based on numerical percentage composition and on number of species, were compared and shown to be poorly correlated with each other. Our data indicated that species number is the more valid diversity measurement. The rarefaction methodology was compared with a number of diversity indexes using identical data. Many of these indexes were markedly influenced by sample size. Good...
2,354 citations
TL;DR: In this article, the authors present an R package iNEXT (iNterpolation/EXTrapolation) which provides simple functions to compute and plot the seamless rarefaction and extrapolation sampling curves for the three most widely used members of the Hill number family.
Abstract: Summary
Hill numbers (or the effective number of species) have been increasingly used to quantify the species/taxonomic diversity of an assemblage. The sample-size- and coverage-based integrations of rarefaction (interpolation) and extrapolation (prediction) of Hill numbers represent a unified standardization method for quantifying and comparing species diversity across multiple assemblages.
We briefly review the conceptual background of Hill numbers along with two approaches to standardization. We present an R package iNEXT (iNterpolation/EXTrapolation) which provides simple functions to compute and plot the seamless rarefaction and extrapolation sampling curves for the three most widely used members of the Hill number family (species richness, Shannon diversity and Simpson diversity). Two types of biodiversity data are allowed: individual-based abundance data and sampling-unit-based incidence data.
Several applications of the iNEXT packages are reviewed: (i) Non-asymptotic analysis: comparison of diversity estimates for equally large or equally complete samples. (ii) Asymptotic analysis: comparison of estimated asymptotic or true diversities. (iii) Assessment of sample completeness (sample coverage) across multiple samples. (iv) Comparison of estimated point diversities for a specified sample size or a specified level of sample coverage.
Two examples are demonstrated, using the data (one for abundance data and the other for incidence data) included in the package, to illustrate all R functions and graphical displays.
2,170 citations
TL;DR: A computer program is introduced that performs rarefaction on private alleles and hierarchical sampling designs to compensate for the sampling disparity between large and small samples.
Abstract: The number of alleles in a sample (allelic richness) is a fundamental measure of genetic diversity. However, this diversity measure has been difficult to use because large samples are expected to contain more alleles than small samples. The statistical technique of rarefaction compensates for this sampling disparity. Here I introduce a computer program that performs rarefaction on private alleles and hierarchical sampling designs.
2,055 citations