Deforestation of the Amazon rainforest is a threat to global climate, biodiversity, and many other ecosystem services. In order to address this threat, an understanding of the drivers of deforestation processes is required. Indirect impacts and determinants that eventually differ across locations and over time are important factors in these processes. These are largely disregarded in applied research and thus in the design of evidence-based policies. In this study, we employ a flexible modelling framework to gain more accurate quantitative insights into the complexities of deforestation phenomena. We investigate the impacts of agriculture in Mato Grosso, Brazil, for the period 2006-2017 and explicitly consider spatial spillovers and varying impacts over time and space. Spillover effects from croplands in the Amazon appear as the major driver of deforestation, with no direct effects from agriculture in later years. This suggests moderate success of the Soy Moratorium and Cattle Agreements, but highlights their inability to address indirect effects. We find that neglect of spatial dynamics and the assumption of homogeneous impacts leads to distorted inference. Researchers need to be aware of the complex and dynamic processes behind deforestation, in order to facilitate effective policy design.
|Name||Ecological Economic Papers|
- Ecological Economic Papers