Efficiency of spatial sampling designs in estimating abundance and species richness of carabids at the landscape level

Abstract

Abstract Context Declining biodiversity in agricultural landscapes has increased the need for research and monitoring of insect abundance and diversity at the landscape level. Objectives We investigated the accuracy of different spatial sampling designs in estimating landscape-level abundance and species richness of carabids in agricultural landscapes and, further, which sample size per landscape section was required and whether dominating land use or landscape subdivision affected accuracy and required sample size. Methods We developed a simulation model that created raster maps of agricultural landscapes, compiled local carabid communities (species composition and abundances) within raster cells and simulated the sampling of carabids with pitfall traps using different spatial sampling designs and sample sizes between 4 and 49 sampling points per landscape section. Spatial sampling designs included random, systematic grid-based, stratified and clustered schemes. Results To estimate landscape-level abundance, area-proportional stratified random sampling was most accurate followed by systematic grid-based designs. A sample size of 25 appeared to be the best trade-off between accuracy and sampling cost. Accuracy was not affected substantially by landscape characteristics in most cases. With respect to species richness, all designs except for clustered sampling had comparable accuracies, but even 49 samples were not sufficient to detect 80% of the species. Conclusion Systematic grid-based designs are generally recommendable for sampling of carabids in agricultural landscapes and, in case a carabid-specific habitat classification is available, area-proportional stratified random sampling provides optimal accuracy for estimating landscape-level abundance. For assessment of species richness, large sample size is more important than spatial sampling design.