PERENNIAL PATHS: MAPPING ECOLOGICAL NETWORKS TO ENHANCE PREDATOR MOVEMENT AND PEST CONTROL IN COFFEE LANDSCAPES IN LIPA, BATANGAS

Perennial crop landscapes play a critical role in sustaining agricultural productivity, yet their ecological function is often weakened by habitat fragmentation that limits the movement of natural predators responsible for biological pest control. In the perennial-dominated landscape of Lipa City, Batangas, the primary challenge lies in improving predator connectivity between forest source habitats and crop feeding areas within an intensively managed agricultural matrix. This study employs a biotope-based ecological assessment and network modeling approach to address this issue through spatial planning. Using geographic information systems (GIS), the researcher generated a biotope map by integrating land cover, landform, soil, and watershed data, which served as the core spatial framework of the analysis. Each biotope was evaluated based on ecological criteria including area, rarity, habitat structure, and successional stage, allowing the classification of landscape units into creative, connective, integrative, and protective management strategies. Building on this assessment, an ecological network was constructed through predator source identification, perennial feeding target mapping, resistance surface modeling, and least cost path analysis.The resulting ecological network highlights functional corridors, connectivity gaps, and priority intervention zones where hedgerows, stepping stones, and buffer areas can enhance predator movement into perennial crops. Findings indicate that forested areas function as essential source habitats under protective management ,while extensive perennial crop biotopes require integrative strategies to embed ecological function within production systems.Overall, the study demonstrates how combining biotope assessment with ecological network modeling can translate ecological analysis into actionable spatial strategies that strengthen biological pest control and support sustainable agricultural landscape planning.