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Connectivity of natural areas through biological corridors is essential for ecosystem resilience and biodiversity conservation. However, robust assessments of biodiversity in corridor areas are often hindered by logistical constraints and the statistical challenges of modeling data from multiple species. Herein, we used a hierarchical community occupancy model in a Bayesian framework to evaluate the status of medium and large-sized mammals in a critical link of the Mesoamerican Biological Corridor (MBC) in Costa Rica. We used camera traps deployed from 2013-2017 to detect 18 medium (1-15 kg) and 6 large (>15 kg) mammal species in a portion of two Jaguar Conservation Units (JCUs) and the Corridor linking them. Camera traps operated for 16,904 trap nights across 209 stations, covering an area of 880 km2. Forest cover was the most important driver of medium and large-sized mammal habitat use, with forest specialists such as jaguars (Panthera onca) and pumas (Puma concolor) strongly associated with high forest cover, while habitat generalists such as coyotes (Canis latrans) and raccoons (Procyon lotor) were associated with low forest cover. Medium and large-sized mammal species richness was lower in the Corridor area ([Formula: see text] = 9.78±1.84) than in the portions evaluated of the two JCUs ([Formula: see text] = 11.50±1.52). Puma and jaguar habitat use probabilities were strongly correlated with large prey species richness (jaguar, r = 0.59, p

Broad scale population estimates of declining species are desired for conservation efforts. However, for many secretive species including large carnivores, such estimates are often difficult. Based on published density estimates obtained through camera trapping, presence/absence data, and globally available predictive variables derived from satellite imagery, we modelled density and occurrence of a large carnivore, the jaguar, across the species' entire range. We then combined these models in a hierarchical framework to estimate the total population. Our models indicate that potential jaguar density is best predicted by measures of primary productivity, with the highest densities in the most productive tropical habitats and a clear declining gradient with distance from the equator. Jaguar distribution, in contrast, is determined by the combined effects of human impacts and environmental factors: probability of jaguar occurrence increased with forest cover, mean temperature, and annual precipitation and declined with increases in human foot print index and human density. Probability of occurrence was also significantly higher for protected areas than outside of them. We estimated the world's jaguar population at 173,000 (95% CI: 138,000-208,000) individuals, mostly concentrated in the Amazon Basin; elsewhere, populations tend to be small and fragmented. The high number of jaguars results from the large total area still occupied (almost 9 million km2) and low human densities (< 1 person/km2) coinciding with high primary productivity in the core area of jaguar range. Our results show the importance of protected areas for jaguar persistence. We conclude that combining modelling of density and distribution can reveal ecological patterns and processes at global scales, can provide robust estimates for use in species assessments, and can guide broad-scale conservation actions.