Deforestation drivers in the Brazilian Amazon: assessing new spatial predictors
Alex Mota Dos Santos1, Carlos Fabricio Assunção da Silva2, Pedro Monteiro de Almeida Junior3
1Center of Agroforestry Sciences and Technologies, Federal University of Southern Bahia, Rodovia Ilhéus/Itabuna, Km 22, Itabuna, 45604-811, Brazil.
Journal of Environmental Management
|June 14, 2021
Summary
Large-scale Amazon deforestation is driven by extensive cattle ranching, particularly in southern Amazonia. This study used Geographically Weighted Regression to analyze deforestation causes from 2010-2019.
Area of Science:
- Environmental Science
- Geography
- Ecology
Background:
- Amazon deforestation is a significant global issue, intensified by recent policy shifts in Brazil.
- Understanding the drivers of deforestation is crucial for effective conservation and policy-making.
Purpose of the Study:
- To analyze the spatial variability of deforestation causes in the Brazilian Amazon Biome between 2010 and 2019.
- To identify the primary economic and environmental factors contributing to deforestation.
Main Methods:
- Selection and regression modeling of 14 relevant variables.
- Utilized a geographic information system to structure a spatial database.
- Employed Geographically Weighted Regression (GWR) for spatial analysis.
Main Results:
- The GWR model achieved an adjusted R-squared of 0.96, explaining 96% of deforestation variations.
- The number of oxen (cattle) showed the highest correlation with deforestation.
- Deforestation hotspots were identified in a cluster within the southern Amazon's "arc of deforestation".
Conclusions:
- Extensive cattle ranching is the main economic driver pressuring large areas for deforestation in southern Amazonia.
- Geographically Weighted Regression significantly improved the understanding of spatial deforestation patterns.
- Policy interventions targeting the livestock sector are essential for mitigating Amazon deforestation.
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