Putting the effectiveness of streamlining to the test: a spatial and statistical analysis of self-declared impacted areas in simplified impact assessment of livestock projects in Brazil

Environmental impact assessment (EIA) systems are being increasingly simplified worldwide. Among the most controversial approaches to simplification is the requirement of simple self-declarations of impacted areas, as opposed to comprehensive impact assessment reports. This approach, which makes development licensing much faster and less costly, is particularly prominent in Brazil. Yet, empirical evidence on the reliability of self-declared information and its likely outcomes to decision-making is lacking. This study examines how self-declarations of impacted areas are provided and verified in simplified environmental licensing processes. Drawing on spatial and statistical analyses of 576 extensive livestock farming projects licensed over a 6-year period in the Brazilian state of Minas Gerais, we found that 84% of the total impacted area was licensed without any formal impact assessment. Proponent’s declarations of areas based on spatial information were significantly larger than the textual ones. If spatially self-declared areas were used for screening, a much greater proportion of projects would trigger EIA requirements. Results suggest that insufficient scrutiny, ambiguous regulatory guidance and lack of training contribute to systemic underestimation of potential environmental impacts. Overall, the study indicates that decisions have been based on unreliable self-declarations. We present recommendations for improving data verification in simplified licensing systems.