Seasonal variation in detectability of butterflies surveyed with Pollard walks

Monitoring protocols should be designed to maximize the probability of detecting target species with limited resources. Most species are imperfectly detected, hence, they will often be overlooked at sites where they actually occur, resulting in false-negative errors (i.e. false absences). Uncertain detection of target species has profound implications for conservation, but can be dealt with by using adequate survey designs and statistical models. Butterflies often are monitored with repeated, fixed-route transect counts (Pollard walks). Even though this survey method is widely used in temperate regions, its efficiency in terms of detection probability has never been rigorously assessed in part owing to a lack of suitable analysis methods. Here, I use site-occupancy models to explore the seasonal patterns in detection probability of four California butterflies using Pollard walks. In an effort to inventory the butterfly fauna in two natural areas in the eastern foothills of the Santa Cruz mountains (California), I surveyed twelve 250 m long transects weekly for 22 weeks. I estimated the detection probability (the probability of recording a species during a single transect walk, given it is present) of four species. The probability of detecting each species depended mostly on the monitoring week. Average detection probability across the season was 64% for Cercyonis pegala, 56% for Limenitis lorquini, 76% for Euphydryas chalcedona, and 50% for Lycaena arota. Based on the mean detection probability, I then inferred the number of visits necessary to be statistically confident that a given species was indeed absent from a transect where it was not observed (i.e. obtaining a false absence rate <5%). Knowledge of detection probabilities is fundamental to the optimal design of monitoring programs and the interpretation of their results. The methods applied in this study provide an efficient and evidence-based method to optimally allocate butterfly monitoring resources across space (number of transects) and time (number and timing of visits).