Estimating species richness of pitfall catches by non-parametric estimators

Abstract

Summary In consequence of accelerated applications of new land-use systems, agricultural landscape research is challenged to provide results on their sustainability. Studies on biodiversity that are carried out with minimal sampling programs have become increasingly popular. However, concerning insects, the observed number of species in these studies underestimates the true species richness. In such studies, the non-parametric estimators might provide a more reliable tool to gain information about the true species richness. The objective of this paper is to evaluate how accurately and precisely estimates of species richness in studies with few pitfall samples correlate with those of studies with higher sampling intensity. This indicates how much effort could be saved in collecting data on species richness of insect communities. The species richness of carabid beetles at ten temporary wetlands in the East-German agricultural landscape was surveyed by nine pitfall traps per site. Estimates of species richness were calculated in scenarios with four, five or six pitfall traps per site. The observed number of species and the non-parametric estimators, Chao2, Bootstrap, Jacknife1 and Jacknife2, were included in the study to estimate species richness in each scenario, respectively. The estimates in the scenarios were compared with estimations based on the whole data set. While Chao2 was the most accurate and precise estimator, the Bootstrap estimator performed only slightly better than the number of observed species. Jacknife1 and 2 performed intermediately. Only Chao2 performed more precisely than the observed number of species. In conclusion, the number of samples might be reduced to five or six pitfall traps per site in studies carried out in small habitats with minimal sampling programs. The non-parametric estimators provide possibilities to carry out studies on species richness with reduced sampling efforts as well as, to gain more reliable information on species richness re-analyzing studies already carried out.