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

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

Model estimates of occupied area, population size, and mean density of jaguars in the countries of South and North America.

<p>Population estimates and 95% credible intervals for each country were derived from hierarchical combination of the best fitting jaguar occurrence and density models based on anthropogenic and environmental variables. Calculations were performed for the area of current jaguar range (Figs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194719#pone.0194719.g001" target="_blank">1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194719#pone.0194719.g006" target="_blank">6</a>).</p

Predicted probability of jaguar occurrence in North and South America.

<p>Probability values were predicted by our top occurrence model that included seven spatial variables (mean annual temperature, annual precipitation, forest cover, human density, human footprint index, area protection status, and North America—South America code). See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194719#pone.0194719.t004" target="_blank">Table 4</a> for model covariates and associated coefficients.</p

Comparison of the four best-fitting logistic regression models of jaguar presence-absence at 3,155 sites in North and South America, between 2006–2015.

<p>Models were fitted with 17 spatial variables (three anthropogenic variables, 13 environmental variables, and North America–South America code); definitions of the predictive variables are in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194719#pone.0194719.s002" target="_blank">S2 Table</a>. Selection of the best model based on the Bayesian Information Criterion (BIC); additionally Nagelkerke R² and the area under the receiver operating characteristic curve (AUC ROC) are provided. Bold indicates the best model used for spatial prediction of jaguar occurrence.</p

Posterior distribution of range-wide jaguar population estimates.

<p>Results obtained from 100,000 iterations of a hierarchical model of jaguar occurrence and density; dashed vertical lines represent a 95% credible interval.</p

Spatial variation in the mean estimates of adjusted jaguar population densities used for estimating population size within current jaguar range.

<p>Adjusted jaguar population densities were estimated using a hierarchical model combining our density and occurrence models and thus accounting for human impacts.</p

Comparison of multiple linear regression models of jaguar density from 80 sites in North and South America based on values of Bayesian Information Criterion (BIC).

<p>Presented are ten best-fitting multiple linear regression models based on 21 spatial variables (three anthropogenic variables, 13 environmental variables, an indicator variable for North and South America (NA-SA), and four variables measuring camera trap effort); definitions of the predictive variables are in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194719#pone.0194719.s001" target="_blank">S1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194719#pone.0194719.s002" target="_blank">S2</a> Tables. Density studies were conducted between 2002 and 2014. Bold indicates the model used for spatial prediction of jaguar density.</p

Parameters of the best-fitting multiple linear regression model of jaguar density from 80 sites in North and South America.

<p>Density studies were conducted between 2002 and 2014. Bias and the standard error of the regression coefficients of the bootstrapped model (10,000 replications) are shown; definitions of the predictive variables are in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194719#pone.0194719.s002" target="_blank">S2 Table</a>.</p

Study area map.

<p>Indicated are historical and current jaguar range (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194719#sec002" target="_blank">Materials and Methods</a> for definitions and sources for both) and the distribution of density study sites and presence/absence records used for modelling range-wide jaguar density and occurrence.</p

Predicted spatial variation of jaguar potential densities across North and South America.

<p>Densities were predicted with our top regression model based on four environmental variables (mean annual temperature, NPP_MEAN, NPP_SD, North America–South America code). See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194719#pone.0194719.t002" target="_blank">Table 2</a> for model covariates and associated coefficients.</p