Abstract
Extrapolative nonparametric estimators of species density are commonly used in community ecology. However, they are dependent on either (1) their use on non-dispersive taxa, or (2) the ability to separate tourists from residents in dispersive taxa. We undertook ten years of leaf litter sampling in an ancient woodland in the New Forest, Southern England. We identified all the beetles from those samples and assigned them a residency status (residents, stratum tourists, and habitat tourists). Extrapolations, using the Chao 2, first- and second-order jackknife, and bootstrap approaches, of all sampled beetles all showed large overestimates of species richness when compared with extrapolations based on just residents. We recommend that the estimators should be used with caution as estimates of actual species density for dispersive taxa unless the natural history of most species in a community is well known. This applies especially to tropical ecosystems where many species have not been described. This reinforces the need for more descriptive natural history.
Highlights
One of the most comprehensible of measurable variables in any defined area is the area’s species density
We reviewed beetles in a single selfcontained stratum—the leaf litter
We show that extrapolated species density estimates that include species that are known not to be habitual occupants of the litter stratum are strongly biased and that paradoxically the bias increases with increased sampling
Summary
One of the most comprehensible of measurable variables in any defined area is the area’s species density (i.e. the total number of species in that area, often referred to loosely as “species richness”). This measure is understood by a range of stakeholders, and among the conservation community. A well-established and popular way of estimating total species pools from subsamples is using nonparametric estimators (Colwell & Elsensohn, 2014). These statistical methods rely on expected properties (and proposed underlying distributions) of the relative abundances of biological assemblages (Colwell et al, 2012). Many of the methods attempt to estimate totals from the numbers of “incidence-of-one” species (occurring in only one sample/ site) and “incidence-of-two” species (species that occur only in two samples/sites). (Melo, 2004)
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