Accounting for false positive detection error induced by transient individuals

Abstract

Context. In metapopulations, colonisation is the result of dispersal from neighbouring occupied patches, typically juveniles dispersing from natal to breeding sites. When occupancy dynamics are dispersal driven, occupancy should refer to the presence of established, breeding populations. The detection of transient individuals at sites that are, by definition, unoccupied (i.e. false positive detections), may result in misleading conclusions about metapopulation dynamics. Until recently, the issue of false positives has been considered negligible and current efforts to account for such error have been restricted to the context of species misidentification. However, the detection of transient individuals visiting multiple sites while dispersing is a distinct source of false positives that can bias estimates of occupancy because visited sites do not contribute to metapopulation dynamics in the same way as do sites occupied by established, reproducing populations. Although transient-induced false positive error presents a challenge to occupancy studies aiming to account for all sources of detection error and estimate occupancy without bias, accounting for it has received little attention.Aims. Using a novel application of an existing occupancy model, we sought to account for false positives that result from transient individuals being observed at truly unoccupied sites (i.e. where no establishment has occurred).Methods. We applied a Bayesian multi-season occupancy model correcting for false negative and false positive errors, to 3 years of detection or non-detection data from a metapopulation of water voles, Arvicola amphibious, in which both types of patch-state misclassification are suspected.Key results. We provide evidence that transient individuals can cause false positive detection errors. We then demonstrate the flexibility of the occupancy model to account for both false negative and false positive detection errors beyond the typical application to species misidentification. Accounting for both types of observation error reduces the bias in estimates of occupancy and avoids misleading conclusions about the status of (meta) populations by allowing for the distinction to be made between resident and transient occupancy.Conclusion. In many species, transience may result in patch-state misclassification which needs to be accounted for so as to draw correct inference about metapopulation status. Making the distinction between occupancy by established populations and visitation by transients will influence how we interpret patch occupancy dynamics, with important implications for the management of wildlife.Implications. The ability to estimate occupancy free of bias induced by false positive detections can help ensure that downward trends in occupancy are detected despite such declines being accompanied by increasing frequency of transients associated with, for example, reductions in mate availability or failure to establish. Our approach can be applied to any occupancy study in which false positive detecti...

Quantifying data quality in a citizen science monitoring program: False negatives, false positives and occupancy trends

“…However, we may consider a second source of false-positives, termed ecological false-positives by Berigan, Jones, Whitmore, Gutiérrez, and Peery (2019), when detections are also made of individuals which are temporarily making use of a site outside of their home range-for example, when individuals are dispersing (Sutherland, Elston, & Lambin, 2013), or foraging outside of their normal home range (Berigan et al, 2019). The first, which we can consider as sampling false-positives, arise when surveyors report seeing a species when it is not in fact present at (e.g., through misidentification or wrong field notes).…”

“…Ribbons for the FNO and FNFP models represent the 95% credible interval. In situations where ecological false-positives cannot be prevented during the planning stage of monitoring, models such as ours-which can account for both forms of false-positive observations-are recommended in order to improve inference of occupancy dynamics and trends (Altwegg & Nichols, 2019;Sutherland et al, 2013). Over large numbers of sites, this effect can lead to many sites being falsely classified as occupied, even if there are no detections made at the site.…”

Fishing for mammals: Landscape‐level monitoring of terrestrial and semi‐aquatic communities using eDNA from riverine systems

“…Water voles use prominently placed latrines for territory marking (Figure a). Using latrine surveys, a reliable method of detection (Sutherland et al, ), water vole occupancy status was determined by the detection of latrines that are used for territory marking (Sutherland, Elston, & Lambin, ). During the breeding season (July and August), latrine surveys were conducted twice at each site.…”

Quantifying group size in the red fox: impacts of definition, season and intrusion by non‐residents

“…Although social relationships are an obvious consideration, hitherto red fox group size estimates have been based on capture and/or space use data (Harris, ; Harris & Rayner, ; Poulle, Artois & Roeder, ; Baker et al ., , ; Iossa et al ., ). These techniques limit the accuracy of group‐size estimates because low capture rates and infrequent recaptures make it difficult to identify all the members of a social group, and to monitor the rates of territorial intrusion by non‐group members (Baker, Newman & Harris, ; Baker et al ., ; Soulsbury et al ., ), which can lead to population density being overestimated (Sutherland, Elston & Lambin, ). While camera traps have great potential to compile individual sighting histories, thus far they have not been used to define red fox group sizes and composition (Sarmento et al ., ; Bengsen, ; Ramsey, Caley & Robley, ).…”