Optimization of Fish Aggregating Device (FAD) Distribution Using a Geospatial Approach Based at Pasar Lama Fish Landing Site, Kaur Regency - Akbar Abdurrahman Mahfudz; Muhammad Antonio Fidel Astra; Ali Muqsit; Ferdy Gustian Utama (Sustainability (STPP) Theory, Practice and Policy, 2025)
Kaur Regency is a coastal area in Bengkulu Province with capture fisheries activities dominated by tuna commodities. The use of fish aggregating devices (FADs) by fishermen at the Pasar Lama Fish Landing Site is the main tool for collecting fish. However, increasing the number of FADs without proper management has the potential to cause conflicts in the use of marine space and the degradation of aquatic ecosystems. This study aims to analyze the spatial distribution of FADs and determine the ideal number of FADs based on geospatial and spatial statistical approaches. Data were collected through interviews, participatory mapping, and GPS tracking of fishermen, then analyzed using ArcGIS through the stages of analyzing the distance between FADs (pairwise distance), buffers, overlays with conservation areas and shipping lanes, and scoring based on three criteria: distance between FADs ≥10 nautical miles, outside the conservation area, and the shipping lane. The results showed that all 38 existing FAD points did not meet the distance criteria of ≥10 nautical miles, with 75% of the distance being between 5–10 nautical miles and 2% <1 nautical miles. Scoring also showed that there were no optimal points, and several FADs were in conservation areas. Based on the total distribution area of 9,695.21 km² and the ideal zone area per fish aggregating device of 813.78 km² (calculated based on the 10-nautical-mile minimum distance radius), the ideal number of fish aggregating devices is 12 points. This study emphasizes the importance of Education and supervision of FADs management to support the sustainability of fisheries and the protection of marine ecosystems fairly and sustainably. The findings also offer a spatially driven approach to inform evidence-based policy and support the digital transformation of FADs monitoring systems in coastal fisheries management.