Authors: Anika Berger*, Clark University, Florencia Sangermano, Clark University, John Rogan, Clark University
Topics: Land Use and Land Cover Change, Hazards, Risks, and Disasters, Natural Resources
Keywords: gold mining, deforestation, Peru, Madre de Dios, land change
Session Type: Poster
Presentation File: No File Uploaded
Peru generates much of its gold production from illegal Artisanal and Small-scale mining (ASM) which results in deforestation as well as river pollution and consequent health threats from mercury waste. Many ASM operations are located in Madre de Dios, one of the most biodiverse tropical regions on the planet. Illegal gold mining is difficult to detect due to its undocumented nature, and by the time its impacts are visible from space, the destruction is too extensive for meaningful intervention. This study aimed to develop a model that predicts where gold mining is likely to occur in the future, utilizing the conditions that characterize historical mining sites. The data for this project included presence of deforestation due to mining from 1984 to 2017 in Madre de Dios, Peru. To identify areas suitable for mining exploitation, an artificial neural network model related past deforestation due to mining to a set of explanatory variables that included distance to roads, distance to rivers, soil type, slope, and elevation. The results displayed on this poster show areas of Madre de Dios with the highest suitability for land change from mining as well as the most important variables in determining the areas’ deforestation risk. Mapping the suitability for future mining can inform enforcing agencies to target resources to monitor illegal operations in specific areas and allows the identification of potential damage to the biodiversity in those regions.
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