Effect of detection heterogeneity in occupancy‐detection models: an experimental test of time‐to‐first‐detection methods

Abstract

Imperfect detection can bias estimates of site occupancy in ecological surveys but can be corrected by estimating detection probability. Time‐to‐first‐detection (TTD) occupancy models have been proposed as a cost–effective survey method that allows detection probability to be estimated from single site visits. Nevertheless, few studies have validated the performance of occupancy‐detection models by creating a situation where occupancy is known, and model outputs can be compared with the truth. We tested the performance of TTD occupancy models in the face of detection heterogeneity using an experiment based on standard survey methods to monitor koala Phascolarctos cinereus populations in Australia. Known numbers of koala faecal pellets were placed under trees, and observers, uninformed as to which trees had pellets under them, carried out a TTD survey. We fitted five TTD occupancy models to the survey data, each making different assumptions about detectability, to evaluate how well each estimated the true occupancy status. Relative to the truth, all five models produced strongly biased estimates, overestimating detection probability and underestimating the number of occupied trees. Despite this, goodness‐of‐fit tests indicated that some models fitted the data well, with no evidence of model misfit. Hence, TTD occupancy models that appear to perform well with respect to the available data may be performing poorly. The reason for poor model performance was unaccounted for heterogeneity in detection probability, which is known to bias occupancy‐detection models. This poses a problem because unaccounted for heterogeneity could not be detected using goodness‐of‐fit tests and was only revealed because we knew the experimentally determined outcome. A challenge for occupancy‐detection models is to find ways to identify and mitigate the impacts of unobserved heterogeneity, which could unknowingly bias many models.

Can time‐to‐detection models with fewer survey replicates provide a robust alternative to traditional site‐occupancy models?

“…Our study suggests that a single TTD is unlikely to be adequate in many field studies. Recent work testing the efficacy of five different TTD occupancy models (each with a different assumption about the underlying detection rate) with known occupancy probability showed that parameter estimates were highly biased (Medina‐Romero et al, ). In this case detection was overestimated while occupancy was underestimated (Medina‐Romero et al, )—findings that corroborate with our field results using a single TTD survey.…”

Time‐to‐detection occupancy methods: performance and utility for improving efficiency of surveys

“…All rights reserved al. 2019), and mammals (Medina-Romero et al 2019). Nonetheless, an empirical test of time-todetection methods against known occurrence found overestimates of detection probability and underestimates of occupancy when heterogeneity in detection probability was not accounted for (Medina-Romero et al 2019).…”

Landbird trends in protected areas using time‐to‐event occupancy models

“…We found that estimates of detection rates were more accurate and precise for simulations with higher occupancy. In contrast, time to first detection models for scat surveys overestimated detection probability and underestimated occupancy when there was unexplained heterogeneity in the detection process (Medina-Romero et al 2019). Conversely, estimates of occupancy had higher variability when w equaled 0.5.…”

“…models overestimated occupancy when time to detection approached or exceeded the sampling window (Garrard et al 2013). In contrast, time to first detection models for scat surveys overestimated detection probability and underestimated occupancy when there was unexplained heterogeneity in the detection process (Medina-Romero et al 2019). Parameter estimates for detection rates could be further improved if the studies recorded the time of all detections rather than just the first detection.…”

“…The cumulative probability of detection increases with survey duration and decreases with mean time to detection. Time-to-event occupancy models have been applied to plant surveys (Garrard et al 2008, Bornand et al 2014, scat surveys (Medina-Romero et al 2019), electrofishing surveys (Ferreira et al 2016), and pond surveys for amphibians (Halstead et al 2018). Time-to-event models have not been applied to songbird populations, although McCarthy et al (2013) found that detection rates were closely linked to abundance.…”