Testing species-richness estimation methods on single-sample collection data using the Danish Diptera
Estimating species richness through extrapolation is becomingincreasingly important for conservation decision making. We present the resultsof 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 150000specimens of 47 families of Danish Diptera. All four estimators considerablyunderestimate true species richness as assessed by species distributions, expertopinions, and a species–area curve. In our samples 3326 species wererepresented. The different estimators predicted the Danish fauna to consist of3490–3805 species, although at least 4361 are already known from theliterature. Expert opinion and the species–area curve indicate that theDanish fauna likely contains 5400–5800 species. The Poisson lognormalmethod displays a rather erratic behavior, but nonetheless performs slightlybetter than the other estimators. We discuss the inherent problems concerningthe use of collection data in this context as well as the influence of patchydistributions and sample size on estimator performance. We conclude thatabundance-based estimators should preferably be applied to almost completesamples of randomly distributed organisms.