Abstract

Summary Complete sampling of all dimensions of biodiversity is a formidable task, even for small areas. Undersampling is the norm, and the underquantification of diversity is a common outcome. Estimators of taxon diversity (TD) are widely used to correct for undersampling. Yet, no similar strategy has been developed for phylogenetic (PD) or functional (FD) diversity. We propose three ways of estimating PD and FD, building on estimators originally developed for TD: (i) correcting PD and FD values based on the completeness of TD; (ii) fitting asymptotic functions to accumulation curves of PD and FD; and (iii) adapting nonparametric estimators to PD and FD data. Using trees as a common framework for the estimation of PD and FD, we tested the approach with European mammal and Azores Islands arthropod data. We demonstrated that different methods were able to considerably reduce the undersampling bias and often correctly estimated true diversity using a fraction of the samples necessary to reach complete sampling. Besides the utility of knowing the true diversity of an assemblage from incomplete samples, the use of estimators may present further advantages. For instance, comparisons between sites or time periods are possible only if either sampling is complete or sampling effort is equivalent and sufficient to allow sensible comparisons. Also, as PD and FD asymptote faster than TD, comparisons between these different dimensions may require unbiased values. The framework now proposed combines taxon, phylogenetic and functional diversity into a single framework, offering a tool for future developments involving these different facets of biological diversity.

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