Optimizing Forest Monitoring: Using Marxan to Identify Priority Patrol Areas on Guadalcanal, Solomon Islands
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deforestation, floods, illegal logging, management cost, ranger
Abstract
Illegal logging causes deforestation, depleting government revenue and exacerbating natural disasters such as landslides and floods in developing countries. Timber exports in Solomon Islands exceed sustainable levels by a factor of seven, yet monitoring remains inadequate due to acute financial and human resource constraints. This study uses Marxan, a systematic conservation planning software, to identify priority ranger patrol areas in Guadalcanal, Solomon Islands. Although studies on forest patrols have mostly looked at pathfinding algorithms, these studies have not considered conservation goals that tools like Marxan support. Using watersheds as the primary planning units, four cost-based scenarios (A–D) were modeled to achieve a conservation target of protecting 50% of the forest above 400 m—a critical zone for biodiversity and regulatory protection. The scenarios evaluated cost substitutes, including watershed area, stream network density, annual precipitation, and downstream land-use impacts. Results indicate that Scenario B (cost—stream network density) is the most effective strategy by successfully meeting the 50% target and encompassed 42.1% of the total watershed. Conversely, Scenario B provided a more concentrated, connectivity-focused spatial plan. These findings suggest that integrating Marxan’s systematic prioritization with hydrological data can transition forest management from random monitoring to data-driven, and efficient patrol routes.
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