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models and estimators linking individual-based and sample-based rarefaction, extrapolation and comparison of assemblages

引用

Journal of Plant Ecology 2012年第1期5卷 3-21页

作者： Robert K.Colwell Anne Chao Nicholas J.Gotelli Shang-Yi Lin Chang Xuan Mao Robin L.Chazdon John T.Longino Department of Ecology and Evolutionary Biology University of ConnecticutStorrsCT 06269USA Institute of Statistics National Tsing Hua UniversityHsin-Chu 30043Taiwan Department of Biology University of VermontBurlingtonVT 05405USA School of Statistics and Management Shanghai University of Finance and EconomicsShanghai 200433China Department of Biology University of UtahSalt Lake CityUT 84112USA

Aims In ecology and conservation biology,the number of species counted in a biodiversity study is a key metric but is usually a biased underestimate of total species richness because many rare species are not ***,comparing species richness among sites or samples is a statistical challenge because the observed number of species is sensitive to the number of individuals counted or the area *** individual-based data,we treat a single,empirical sample of species abundances from an investigator-defined species assemblage or community as a reference point for two estimation objectives under two sampling models:estimating the expected number of species(and its unconditional variance)in a random sample of(i)a smaller number of individuals(multinomial model)or a smaller area sampled(Poisson model)and(ii)a larger number of individuals or a larger area *** sample-based incidence(presence–absence)data,under a bernoulli product model,we treat a single set of species incidence frequencies as the reference point to estimate richness for smaller and larger numbers of sampling *** The first objective is a problem in interpolation that we address with classical rarefaction(multinomial model)and Coleman rarefaction(Poisson model)for individual-based data and with sample-based rarefaction(bernoulli product model)for incidence *** second is a problem in extrapolation that we address with sampling-theoretic predictors for the number of species in a larger sample(multinomial model),a larger area(Poisson model)or a larger number of sampling units(bernoulli product model),based on an estimate of asymptotic species *** published methods exist for many of these objectives,we bring them together here with some new estimators under a unified statistical and notational *** novel integration of mathematically distinct approaches allowed us to link interpolated(rarefaction)curves and extrapolated curves to plot a unified

关键词： bernoulli product model Coleman curve multinomial model Poisson model random placement species–area relation

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