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Ocelots (Leopardus pardalis) are listed as least concern on the International Union for Conservation of Nature (IUCN) Red list of Threatened Species, yet we lack knowledge on basic demographic parameters across much of the ocelot's geographic range, including population density. We used camera‐trapping methodology and spatially explicit capture‐recapture (SECR) models with sex‐specific detection function parameters to estimate ocelot densities across 7 field sites over 1 to 12 years (from data collected during 2002–2015) in Belize, Central America. Ocelot densities in the broadleaf rainforest sites ranged between 7.2 and 22.7 ocelots/100 km2, whereas density in the pine (Pinus spp.) forest site was 0.9 ocelots/100 km2. Applying an inverse‐variance weighted average over all years for each broadleaf site increased precision and resulted in average density ranging from 8.5 to 13.0 ocelots/100 km2. Males often had larger movement parameter estimates and higher detection probabilities at their activity centers than females. In most years, the sex ratio was not significantly different from 50:50, but the pooled sex ratio estimated using an inverse weighted average over all years indicated a female bias in 1 site, and a male bias in another. We did not detect any population trends as density estimates remained relatively constant over time; however, the power to detect such trends was generally low. Our SECR density estimates were lower but more precise than previous estimates and indicated population stability for ocelots in Belize.

This article is protected by copyright. All rights reserved. With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August - 24 November of 2019). We sampled wildlife at 1509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the USA. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as well as future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication. Publisher PDF

The impact of predation on prey populations has long been a focus of ecologists, but a firm understanding of the factors influencing prey selection, a key predictor of that impact, remains elusive. High levels of variability observed in prey selection may reflect true differences in the ecology of different communities but might also reflect a failure to deal adequately with uncertainties in the underlying data. Indeed, our review showed that less than 10% of studies of European wolf predation accounted for sampling uncertainty. Here, we relate annual variability in wolf diet to prey availability and examine temporal patterns in prey selection; in particular, we identify how considering uncertainty alters conclusions regarding prey selection.Over nine years, we collected 1,974 wolf scats and conducted drive censuses of ungulates in Alpe di Catenaia, Italy. We bootstrapped scat and census data within years to construct confidence intervals around estimates of prey use, availability and selection. Wolf diet was dominated by boar (61.5 ± 3.90 [SE] % of biomass eaten) and roe deer (33.7 ± 3.61%). Temporal patterns of prey densities revealed that the proportion of roe deer in wolf diet peaked when boar densities were low, not when roe deer densities were highest. Considering only the two dominant prey types, Manly's standardized selection index using all data across years indicated selection for boar (mean = 0.73 ± 0.023). However, sampling error resulted in wide confidence intervals around estimates of prey selection. Thus, despite considerable variation in yearly estimates, confidence intervals for all years overlapped. Failing to consider such uncertainty could lead erroneously to the assumption of differences in prey selection among years. This study highlights the importance of considering temporal variation in relative prey availability and accounting for sampling uncertainty when interpreting the results of dietary studies.