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

Abstract

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.

Throat Patch Variation in Tayra (Eira barbara) and the Potential for Individual Identification in the Field

“…While there is no specific guidance on absolute lower thresholds, the nine individuals identified here is likely near the minimum number of individuals required for SECR models. Based on our field study and others, capture rates (independent photo events per 100 camera-nights) for tayra vary widely (this study: 1.14; Campeche, Mexico: 0.67 (Á. J. Villafañe-Trujillo, unpublished data); Iguacu National Park, Brazil: 0.40, [42]) and are typically similar or below capture rates for jaguar in the same areas (this study, [43,44]). Estimation of jaguar densities using camera traps, while common, has been challenging to implement without bias due to low capture rates and large jaguar home ranges [45].…”

“…Because our tayra capture rates appear to be at the higher end of those reported, our camera effort (3068 camera-nights) should be seen as a minimum required to accrue sufficient tayra captures, and in some areas twice this value may be necessary. There is some indication that tayra may be more likely to be captured off trails [44], and so future studies may consider this option to further increase capture rates. SECR studies also require that a large percentage of captured individuals be captured at multiple camera stations to allow estimation of an animal movement parameter [41].…”

Study of biological communities subject to imperfect detection: bias and precision of communityN‐mixture abundance models in small‐sample situations

“…7-9. We note that the same algorithmic equivalence in a community abundance model with data augmentation has independently been discovered by Tobler et al (2015). For this analysis, we subtracted overall c diversity from the mean site-level a diversity, and thus obtained b diversity.…”

Using certified timber extraction to benefit jaguar and ecosystem conservation

“…Long-term capture-recapture studies assess influence of environmental and management factors on density, distribution, survivorship, and numerical trends of female and male jaguars, but require considerable external investments of expertise and resources (Karanth et al 2011a;Sollman et al 2011;Tobler and Powell 2013;Polisar et al 2014a;Royle et al 2014;Bahaa-el-Din et al 2016;Boron et al 2016). The next level down in cost is detection probability-based presence-absence occupancy of jaguar and prey (Karanth et al 2011b;Sollman et al 2012;Sunarto et al 2012;Polisar et al 2014a;Tobler et al 2015). At the lowest level of complexity and rigor (Tobler et al 2008;Sollman et al 2013;Polisar et al 2014b), but also the most cost-feasible, is simple proof of the presence or counts of jaguars in a management area and prey frequencies (Fig.…”