Evaluating and benchmarking biodiversity monitoring: Metadata-based indicators for sampling design, sampling effort and data analysis

The biodiversity crisis has led to a surge of interest in the theory and practice of biodiversity monitoring. Although guidelines for monitoring have been published since the 1920s, we know little on current practices in existing monitoring schemes. Based on metadata on 646 species and habitat monitoring schemes in 35 European countries, we developed indicators for sampling design, sampling effort, and data analysis to evaluate monitoring practices. We also evaluated how socio-economic factors such as starting year, funding source, motivation and geographic scope of monitoring affect these indicators. Sampling design scores varied by funding source and motivation in species monitoring and decreased with time in habitat monitoring. Sampling effort decreased with time in both species and habitat monitoring and varied by funding source and motivation in species monitoring. The frequency of using hypothesis-testing statistics was lower in species monitoring than in habitat monitoring and it varied with geographic scope in both types of monitoring. The perception of the minimum annual change detectable by schemes matched spatial sampling effort in species monitoring but was rarely estimated in habitat monitoring. Policy implications: Our study identifies promising developments but also options for improvement in sampling design and effort, and data analysis in biodiversity monitoring. Our indicators provide benchmarks to aid the identification of the strengths and weaknesses of individual monitoring schemes relative to the average of other schemes and to improve current practices, formulate best practices, standardize performance and integrate monitoring results.