Fully Spatial Capture-Recapture Models

Royle, J. Andrew; Chandler, Richard B.; Sollmann, Rahel; Gardner, Beth

doi:10.1016/b978-0-12-405939-9.00005-0

Cited by 304 publications

(552 citation statements)

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“…Our results highlight the strength of SCR as a framework for estimating population size, or density, without having to define the effective trapping or observation area (Royle et al . ), which can otherwise complicate and bias population estimation at large scales (Foster & Harmsen ).…”

Section: Discussionmentioning

confidence: 99%

“…We estimated giraffe population parameters using SCR with a search‐encounter design (Royle et al . ). We divided the survey region, defined by the accessible road network, into discrete grid cells (1 km × 1 km) and considered any grid cells overlapping a survey unit (road transect) as ‘traps’ within which a giraffe could be encountered.…”

Section: Methodsmentioning

confidence: 97%

“…Calves were eliminated from consideration because their movements depended upon their mother, thus violating the assumption of individual independence necessary for SCR models (Royle et al . ). We also did not consider the number of legs with mild or moderate GSD lesions, assuming severe lesions would have the greatest effect on behaviour.…”

Section: Methodsmentioning

confidence: 97%

“…; Royle et al . ). Non‐invasive survey techniques can facilitate accurate estimation of wildlife population abundance and density (Gompper et al .…”

Section: Introductionmentioning

confidence: 97%

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Examining disease prevalence for species of conservation concern using non‐invasive spatial capture–recapture techniques

Muneza

Linden

Montgomery

et al. 2016

Journal of Applied Ecology

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Designed and produced by Robin Bijlani 1. The Institute of Food and Agricultural Sciences (IFAS) is an Equal Opportunity Institution authorized to provide research, educational information and other services only to individuals and institutions that function with non-discrimination with respect to race, creed, color, religion, age, disability, sex, sexual orientation, marital status, national origin, political opinions or affiliations. For more information on obtaining other UF/IFAS

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 97%

Section: Methodsmentioning

confidence: 97%

“…; Royle et al . ). Non‐invasive survey techniques can facilitate accurate estimation of wildlife population abundance and density (Gompper et al .…”

Section: Introductionmentioning

confidence: 97%

See 2 more Smart Citations

Examining disease prevalence for species of conservation concern using non‐invasive spatial capture–recapture techniques

Muneza

Linden

Montgomery

et al. 2016

Journal of Applied Ecology

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“…Following the spatial capture–recapture literature (Efford ; Royle et al . ), we will use the term ‘session’ for each primary sampling period (camera trap survey, i.e. the total duration cameras were active at a particular study site in a particular year, called ‘season’ in the occupancy literature) while ‘sampling day’ will be used for the secondary period (‘survey’ in the occupancy literature).…”

Section: Methodsmentioning

confidence: 99%

Spatiotemporal hierarchical modelling of species richness and occupancy using camera trap data

Tobler

Hartley²,

Carrillo‐Percastegui

et al. 2015

Journal of Applied Ecology

154

143

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Summary1. Over the last two decades, a large number of camera trap surveys have been carried out around the world and camera traps have been proposed as an ideal tool for inventorying and monitoring medium to large-sized terrestrial vertebrates. However, few studies have analysed camera trap data at the community level. 2. We developed a multi-session multi-species occupancy model that allows us to obtain estimates for species richness and occupancy combining data from multiple camera trap surveys (sessions). By estimating species presence at the session-level and modelling detection probability and occupancy for each species and sessions as nested random effects, we could improve parameter estimates for each session, especially for species with sparse data. We developed two variants of our model: one was a binary latent states model while the other used a Royle-Nichols formulation for the relationship between detection probability and abundance.3. We applied both models to data from eight camera trap surveys from south-eastern Peru including six study sites, 263 camera stations and 17 423 camera days. Sites covered protected areas, a logging concession and Brazil nut concessions. We included habitat (terra firme vs. floodplain) as a covariate for occupancy and trail vs. off-trail as a covariate for detection. 4. Among-camera heterogeneity was a serious problem for our data and the Royle-Nichols variant of our model had a much better fit than the binary-state variant. Both models resulted in similar species richness estimates showing that most of the sites contained intact large mammal communities. Detection probabilities and occupancy values were more variable across species than across sessions within species. Three species showed a habitat preference and four species showed preference or avoidance of trails. 5. Synthesis and applications. Our multi-session multi-species occupancy model provides improved estimates for species richness and occupancy for a large data set. Our model is ideally suited for integrating large numbers of camera trap data sets to investigate regional and/ or temporal patterns in the distribution and composition of mammal communities in relation to natural or anthropogenic factors or to monitor mammal communities over time.

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Wildcat population density in NE Portugal: A regional stronghold for a nationally threatened felid

et al. 2021

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Population density data on depleted and endangered wildlife species are essential to assure their effective management and, ultimately, conservation. The European wildcat is an elusive and threatened species inhabiting the Iberian Peninsula, with fragmented populations and living in low densities. We fitted spatial capture–recapture models on camera‐trap data, to provide the first estimate of wildcat density for Portugal and assess the most influential drivers determining it. The study was implemented in Montesinho Natural Park (NE Portugal), where we identified nine individuals, over a total effort of 3,477 trap‐nights. The mean density estimate was 0.032 ± 0.012 wildcat/km2, and density tended to increase with distance to humanized areas, often linked to lower human disturbance and domestic cat presence, with forest and herbaceous vegetation cover and with European rabbit abundance. Although, this density estimate is within the range of values estimated for protected areas elsewhere in the Iberian Peninsula, our estimates are low at the European level. When put in context, our results highlight that European wildcats may be living in low population densities across the Iberian Mediterranean biogeographic region. No phenotypic domestic or hybrid cats were detected, suggesting potentially low admixture rates between the two species, although genetic sampling would be required to corroborate this assertion. We provide evidence that Montesinho Natural Park may be a suitable area to host a healthy wildcat population, and thus be an important protected area in this species' conservation context.

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Fully Spatial Capture-Recapture Models

Cited by 304 publications

References 0 publications

Examining disease prevalence for species of conservation concern using non‐invasive spatial capture–recapture techniques

Examining disease prevalence for species of conservation concern using non‐invasive spatial capture–recapture techniques

Spatiotemporal hierarchical modelling of species richness and occupancy using camera trap data

Wildcat population density in NE Portugal: A regional stronghold for a nationally threatened felid

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