Estimating Species Richness: Sensitivity to Sample Coverage and Insensitivity to Spatial Patterns

The number of species in an area is critical to the development of evolutionary and ecological theory from mass extinctions to island biogeography. Still, the factors influencing the accuracy of estimators of species richness are poorly understood. We explored these factors by simulating landscapes that varied in species richness, relative abundances, and the spatial distribution. We compared the extrapolations of nine nonparametric estimators and two species accumulation curves under three sampling intensities. Community evenness of species' abundances, sampling intensity, and the level of true species richness significantly influenced bias, precision, and accuracy of the estimations. Perhaps most surprisingly, the effects of gradient strength and spatial autocorrelation type were generally insignificant. The nonparametric estimators were substantially less biased and more precise than the species accumulation curves. Observed species richness was most biased. Community evenness, sampling intensity, and the level of true species richness influenced the performance of the nonparametric estimators indirectly via the fraction of all species found in a sample or “sample coverage.” For each particular level of sample coverage, a single estimator was most accurate. Choice of estimator is confounded by a priori uncertainty about the sample coverage. Accordingly, researchers can extrapolate species richness by various estimators and base the estimator choice on the mean estimated sample coverage. Alternatively, the most reliable estimator with respect to community evenness can be chosen. These predictions from our simulations are confirmed in two field studies.