Data from: Using areas of known occupancy to identify sources of variation in detection probability of raptors: taking time lowers replication effort for surveys
Murn, Campbell, University of Reading
Holloway, Graham J., University of Reading
Published Sep 08, 2016 on Dryad.
Cite this dataset
Murn, Campbell; Holloway, Graham J. (2016). Data from: Using areas of known occupancy to identify sources of variation in detection probability of raptors: taking time lowers replication effort for surveys [Dataset]. Dryad. https://doi.org/10.5061/dryad.72j20
Species occurring at low density can be difficult to detect and if not properly accounted for, imperfect detection will lead to inaccurate estimates of occupancy. Understanding sources of variation in detection probability and how they can be managed is a key part of monitoring. We used sightings data of a low-density and elusive raptor (white-headed vulture Trigonoceps occipitalis) in areas of known occupancy (breeding territories) in a likelihood-based modelling approach to calculate detection probability and the factors affecting it. Because occupancy was known a priori to be 100%, we fixed the model occupancy parameter to 1.0 and focused on identifying sources of variation in detection probability. Using detection histories from 359 territory visits, we assessed nine covariates in 29 candidate models. The model with the highest support indicated that observer speed during a survey, combined with temporal covariates such as time of year and length of time within a territory, had the highest influence on the detection probability. Averaged detection probability was 0.207 (s.e. 0.033) and based on this the mean number of visits required to determine within 95% confidence that white-headed vultures are absent from a breeding area is 13 (95% CI: 9–20). Topographical and habitat covariates contributed little to the best models and had little effect on detection probability. We highlight that low detection probabilities of some species means that emphasizing habitat covariates could lead to spurious results in occupancy models that do not also incorporate temporal components. While variation in detection probability is complex and influenced by effects at both temporal and spatial scales, temporal covariates can and should be controlled as part of robust survey methods. Our results emphasize the importance of accounting for detection probability in occupancy studies, particularly during presence/absence studies for species such as raptors that are widespread and occur at low densities.
Murn C, Holloway, G (2016) Data from: Using areas of known occupancy to identify sources of variation in detection probability of raptors: taking time lowers replication effort for surveys. Royal Society Open Science
Contains encounter rates and values for covariates used in the modelling programme PRESENCE.