Assessing the impact of deforestation on sedimentation using the CAMF heuristic: Application in Manicaragua, Cuba - Grethell Castillo Reyes; Dirk Roose; Gerdys Jiménez Moya; René Estrella; Pablo Vanegas Peralta; Elina Avila Ordóñe; Patricia Cazorla Vanegas; Jos Van Orshoven (Serie Científica de la Universidad de las Ciencias Informáticas)
This paper applies the CAMF (Cellular Automata-based heuristic for Minimizing Flow) method to identify, from a raster representation, the sites with highest and lowest impact of deforestation on sediment yield from a river catchment in Manicaragua, Cuba. CAMF addresses the spatial interaction in sediment flow by iteratively and incrementally selecting sites based on their marginal contribution to sediment yield, allowing decision-makers to identify critical areas where deforestation should be avoided to protect water resources and zones where deforestation would have minimal impact. The results show that deforesting the first 200 high-impact cells identified by CAMF leads to approximately 30% increase in sediment yield, indicating their high sensitivity for land use change. In contrast, deforestation of up to 50% of cells with the lowest impact results in negligible changes in sediment yield (less than 0.002%). Furthermore, this study outlines a new challenge for future research: using CAMF to identify optimal locations for afforestation as a compensatory measure for unavoidable deforestation, ensuring the continued delivery of ecosystem services with minimal land use.