Observers are a key source of detection heterogeneity and biased occupancy estimates in species monitoring

Reliable assessments of population status and trends underpin conservation management efforts but are complicated by the fact that imperfect detection is ubiquitous in monitoring data. We explore the most commonly considered variables believed to influence detection probabilities, quantifying how they influence detectability and assessing how occupancy rates are impacted when a variable is ignored. To do so, we used data from two multi-species amphibian monitoring programmes, collected by volunteers and professional surveyors. Our results suggest that although detection rates varied substantially in relation to commonly considered factors such as seasonal and annual effects, ignoring these factors in the analysis of monitoring data had negligible effect on estimated occupancy rates. Variation among surveyors in detection probabilities turned out to be most important. It was high and failing to account for it led to occupancy being underestimated. Importantly, we identified that heterogeneity among observers was as high for professional surveyors as for volunteers, highlighting that this issue is not restricted to citizen-science monitoring. Occupancy modelling has greatly improved the reliability of inference from species monitoring data, yet capturing the relevant sources of variation remains a challenge. Our results highlight that variation among surveyors is a key source of heterogeneity, and that this issue is just as pertinent to data collected by experts as by volunteers. Detection heterogeneity should be accounted for when analysing monitoring data. Furthermore, efforts to increase training of field crews and collecting data to quantify differences between observer abilities are important to avoid biased inference resulting from unmodelled observer differences. •Imperfect detection of species is common in species monitoring.•The detection process is influenced by many factors.•Detection heterogeneity among observers was very strong.•Unmodelled detection heterogeneity led to biased estimates of occupancy.