Pitfall trap sampling bias depends on body mass, temperature, and trap number: insights from an individual‐based model

Abstract

AbstractThe diversity and community composition of ground arthropods is routinely analyzed by pitfall trap sampling, which is a cost‐ and time‐effective method to gather large numbers of replicates but also known to generate data that are biased by species‐specific differences in locomotory activity. Previous studies have looked at factors that influence the sampling bias. These studies, however, were limited to one or few species and did rarely quantify how the species‐specific sampling bias shapes community‐level diversity metrics. In this study, we systematically quantify the species‐specific and community‐level sampling bias with an allometric individual‐based model that simulates movement and pitfall sampling of 10 generic ground arthropod species differing in body mass. We perform multiple simulation experiments covering different scenarios of pitfall trap number, spatial trap arrangement, temperature, and population density. We show that the sampling bias decreased strongly with increasing body mass, temperature, and pitfall trap number, while population density had no effect and trap arrangement only had little effect. The average movement speed of a species in the field integrates body mass and temperature effects and could be used to derive reliable estimates of absolute species abundance. We demonstrate how unbiased relative species abundance can be derived using correction factors that need only information on species body mass. We find that community‐level diversity metrics are sensitive to the particular community structure, namely the relation between body mass and relative abundance across species. Generally, pitfall trap sampling flattens the rank‐abundance distribution and leads to overestimations of ground arthropod Shannon diversity. We conclude that the correction of the species‐specific pitfall trap sampling bias is necessary for the reliability of conclusions drawn from ground arthropod field studies. We propose bias correction is a manageable task using either body mass to derive unbiased relative abundance or the average speed to derive reliable estimates of absolute abundance from pitfall trap sampling.