Spatial assessment of biodiversity and conservation priorities in Hamedan Province, Iran, using a landscape ecology approach

Systematic conservation planning is a framework that has been developed over the past decade to prioritize the management of key habitats and conserve biodiversity values. Artificial intelligence has been proposed to operate within this framework by using computer algorithms based on an objective function to identify and prioritize protected area networks. In this context, our objective was to determine the optimal conservation network for biodiversity in the Hamedan Province of Iran. Using a Tabu search algorithm, we determined which area would accommodate the greatest number of biodiversity targets within the smallest area possible. The selected conservation patches were investigated for their connectivity and compactness using landscape composition and configuration metrics. In addition, we applied redundancy analysis (RDA) to determine the relationship between conservation targets and landscape parameters such as land use/cover types, and species richness. The results indicated that the existing protected area network is insufficient to attain conservation goals in Hamedan Province, Iran. The landscape metrics analysis revealed that patches with more contiguity, compaction, and fractal dimension hold a higher conservation value and RDA showed a clear relation between landscape metrics and conservation targets. We thus suggest that our results be used by land managers and land use planners to better align conservation and management strategies in an effort to maximize biodiversity conservation.