Abstract
AbstractHabitat loss and fragmentation are among the major threats to the conservation of biodiversity. Improvement of landscape connectivity becomes one of the main strategies for alleviating these threats and is an increasingly used target in management policies worldwide. However, implementation of connectivity principles in local management actions often implies great difficulties derived from the different criteria used by connectivity analysts and policy makers. We generated a management tool to incorporate connectivity criteria for large carnivores in landscape conservation planning at a local scale. Focusing on the southernmost population of jaguars Panthera onca, we use a graph‐based connectivity approach to (1) analyze habitat connectivity and availability in five areas previously identified as main corridors; (2) detect priority forest patches for maintaining connectivity, and (3) propose specific management strategies for each area matching the relative importance and role of the forest patches in it. For this purpose, we defined the patches as the local land management units (properties) and used information on land cover and jaguar movement for determining the probabilities of connectivity metric. We identified the key patches that represent 90% of the total contribution to connectivity in the study areas; these patches were less than half of the total number of patches in each corridor. Based on this forest patch prioritization, we identified the most critical areas and specific patches where urgent conservation measures need to be implemented. The percentage of patches and the total area they covered varied among the five analyzed corridors showing contrasting situations for connectivity management and highlighting the importance of the proposed approach to understand the impact of patch‐level actions in a broader connectivity context. This approach might serve as a model to account for habitat connectivity for large carnivores in the design of landscape management and land‐use plans at a local scale.
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