Comparative survey study reveals detectability bias distorts population trends in common quail, indicating species-specific calibration prevents false conservation warnings in prime habitats.
Bird Monitoring Schemes (BMS) provide the backbone of large-scale biodiversity assessment and are widely used to inform conservation policy and management. However, for species with low or variable detectability, abundance-based indicators derived from generic monitoring schemes may not accurately reflect population dynamics. This limitation is particularly relevant for species whose detectability varies strongly across space or time. Using the common quail ( Coturnix coturnix ), a widespread farmland game bird, we evaluated how detectability bias influences abundance estimates and long-term population indicators derived from volunteer-based monitoring. We compared data from a generic breeding bird monitoring scheme and a species-specific survey designed to maximize quail detectability. The species-specific survey frequently detected common quail in surveys where the generic monitoring scheme recorded no individuals and consistently recorded higher abundances when both methods detected the species. A calibration model incorporating vegetation greenness (NDVI) was used to derive abundance indicators from generic survey counts and showed that differences between monitoring approaches depended on habitat conditions. Although overall long-term trends were broadly similar between monitoring approaches, substantial differences emerged in high-quality habitats, where detectability bias was strongest and uncorrected indicators suggested population declines that were not supported by calibrated estimates. These results indicate that detectability bias can influence population trend indicators and potentially affect conservation assessments. Integrating species-specific and volunteer-based monitoring provides a practical framework for improving biodiversity indicators without sacrificing the spatial and temporal coverage of large-scale monitoring programs.
No takes yet. Share an insight, caveat, or question.
Sardà‐Palomera et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: