Estimating large carnivore populations at global scale based on spatial predictions of density and distribution - Application to the jaguar (Panthera onca).

PLoS One. 2018 Mar 26;13(3):e0194719. doi: 10.1371/journal.pone.0194719. eCollection 2018. Jędrzejewski W1, Robinson HS2,3, Abarca M1, Zeller KA4, Velasquez G1, Paemelaere EAD2, Goldberg JF5, Payan E2, Hoogesteijn R2, Boede EO6, Schmidt K7, Lampo M1, Viloria ÁL1, Carreño R1, Robinson N8, Lukacs PM3, Nowak JJ3, Salom-Pérez R2, Castañeda F2, Boron V9, Quigley H2. Author information 1 Centro de Ecología, Instituto Venezolano de Investigaciones Científicas (IVIC), Caracas, Venezuela. 2 Panthera, New York, United States of America. 3 Wildlife Biology Program, Department of Ecosystem and Conservation Sciences, W. A. Franke College of Forestry and Conservation, University of Montana, Missoula, United States of America. 4 Department of Environmental Conservation, University of Massachusetts, Amherst, United States of America. 5 Evolution, Ecology and Organismal Biology Program, University of California, Riverside, United States of America. 6 Fundación para el Desarrollo de las Ciencias, Físicas, Matemáticas y Naturales-FUDECI, Caracas, Venezuela. 7 Mammal Research Institute, Polish Academy of Sciences, Białowieża, Poland. 8 Department of Forest Management, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, United States of America. 9 Durrell Institute of Conservation and Ecology, University of Kent, Canterbury, United Kingdom. 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. PMID: 29579129 DOI: 10.1371/journal.pone.0194719