Optimizing wildlife monitoring through cost-effective distribution of observatories

Effective wildlife management and conservation require reliable information on species distribution and abundance.Here, we present a scalable and transferable methodology designed to capture the ecological and management heterogeneity of any study area, thereby optimizing wildlife monitoring programs.By delineating homogeneous sampling units based on key environmental and management factors, this approach enables focused monitoring in a strategically selected subset of areas ("observatories"), ensuring robust data collection while optimizing resource use.Our procedure consists of three stages.First, we apply multivariate techniques to assess the main environmental, management, or biodiversity patterns across the study area.Second, clustering methods are used to identify homogeneous regions or management units.Finally, optimization algorithms establish a network of well-distributed monitoring points to ensure a cost-effective solution.This structured, adaptable framework is highly applicable across regions and scales.