Abstract
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.
Highlights
Broad scale population estimates are desired for setting conservation goals and priorities [1], [2]
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
Based on the original (58 studies, 36 study sites) and reconstructed (59 studies, 44 study sites) Spatially explicit capture-recapture (SCR) density estimates we developed a set of regression models explaining spatial variation in jaguar population density
Summary
Broad scale population estimates are desired for setting conservation goals and priorities (e.g. for IUCN assessments) [1], [2]. When direct censuses are not possible, population estimates may be derived from known species distributions and spatial variation in population densities. Species distribution models have become a powerful tool in animal conservation They can help to estimate current species range, identify factors determining species distribution, and indicate ecological corridors [10], [11]. Population density estimates based on camera trap data have become increasingly common for species that are individually identifiable such as jaguars, leopards, and tigers P. tigris [15,16,17]. In many early camera-trapping studies, densities were estimated with non-spatial capture-recapture models, which have been criticised recently as leading to overestimation [18], [19]. Spatial capture-recapture models have been shown to produce more accurate density estimates [20] and are slowly replacing non-spatial methods
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