Jaguar Panthera onca Habitat Modeling in Landscapes Facing High Land‐use Transformation Pressure—Findings from Mato Grosso, Brazil

The modeling of top predators' habitats and the understanding of their environmental requirements in landscapes facing high land‐use transformation pressure have long‐standing importance for the development of conservation strategies. Multi‐distance spatial cluster analysis and logistic regression with environmental weighting for pseudo‐absence designation were applied to understand spatial patterns of jaguar occurrence in Mato Grosso state (Central Western Brazil). This location has been under intense deforestation pressure since the 1970s and is historically one of the most important jaguar habitats in the world. By using a model of five independent variables, we were able to achieve a 73.2 percent success rate of case/non‐case classification and indicate not only a general loss of habitat suitability, but also an increasing interruption of potential migration corridors in the state. Our analysis on a regional scale demonstrates the importance of forest and savannah woodland for jaguar habitat maintenance in the Mato Grosso state. The jaguar species demonstrates a sensitivity to landscape fragmentation, which can be parameterized for improved model building by metrics such as edge density and patch size. Comparisons with previous studies in South America show that parameter selection for jaguar habitat modeling is highly scale‐dependent and that habitat suitability in partially transformed landscapes could be maintained if fragmentation is minimized. Recent land‐use transformation, however, has significantly weakened the conservation status of the Pantanal‐Amazon corridor.