Imperfect detection and sampling effort shape ground beetle (Carabidae) diversity indicators in large-scale monitoring

Abstract

Soil biodiversity indicators are increasingly used to inform environmental assessment and policy, yet their robustness is often constrained by heterogeneous sampling designs and imperfect species detection. Surface-active arthropods, such as ground beetles (Carabidae), are widely monitored using pitfall-based methods, but differences among trapping protocols and sampling effort complicate comparisons across sites and programmes. Using data from the French Soil Quality Monitoring Network (RMQS-Biodiversity), we analysed how sampling protocol and trapping intensity shape species detectability and how these effects propagate to inventory completeness and taxonomic diversity estimates. We applied species-level occupancy models to explicitly estimate detection probabilities as functions of sampling protocol, effort and species traits, and propagated these estimates to community-level diversity metrics using coverage-based standardisation. Detection probability increased strongly and monotonically with sampling effort, approaching saturation under the 10-pitfall traps configuration. GPDs exhibited detectability comparable to intermediate pitfall configurations (6 pitfall traps), but remained below 8 and 10 pitfall traps. Body size showed a consistent positive effect on detectability across protocols, whereas wing development effects were weak. Coverage-based standardisation substantially reduced protocol effects on diversity estimates, but species richness (Hill q = 0) remained more sensitive to protocol identity than Shannon or Simpson diversity. Together, our results show that harmonising sampling effort alone is insufficient to ensure comparability among biodiversity monitoring protocols. Instead, combining detection-aware modelling with coverage based standardisation provides a robust framework for improving the comparability and policy relevance of biodiversity indicators under heterogeneous monitoring schemes. More broadly, this study highlights the importance of explicitly integrating observation processes into large-scale soil biodiversity monitoring frameworks.