Testing species-richness estimation methods on single-sample collection data using the Danish Diptera

Estimating species richness through extrapolation is becoming increasingly important for conservation decision making. We present the results of a first test of four abundance-based estimation procedures, ACE, Chao1, Lognormal and Poisson lognormal based on single-sample museum collection data consisting of more than 150000 specimens of 47 families of Danish Diptera. All four estimators considerably underestimate true species richness as assessed by species distributions, expert opinions, and a species-area curve. In our samples 3326 species were represented. The different estimators predicted the Danish fauna to consist of 3490-3805 species, although at least 4361 are already known from the literature. Expert opinion and the species-area curve indicate that the Danish fauna likely contains 5400-5800 species. The Poisson lognormal method displays a rather erratic behavior, but nonetheless performs slightly better than the other estimators. We discuss the inherent problems concerning the use of collection data in this context as well as the influence of patchy distributions and sample size on estimator performance. We conclude that abundance-based estimators should preferably be applied to almost complete samples of randomly distributed organisms.