Despite recent success in reducing forest loss in the Brazilian Amazon, additional forest conservation efforts, for example, through ‘Reducing Emissions from Deforestation and Forest Degradation’ (REDD+), could significantly contribute to global climate-change mitigation. Economic incentives, such as payments for environmental services could promote conservation, but deforestation often occurs on land without crucial tenure-security prerequisites. Improving the enforcement of existing regulatory disincentives thus represents an important element of Brazil’s anti-deforestation action plan. However, conservation law enforcement costs and benefits have been much less studied than for conditional payments. We develop a conceptual framework and a spatially explicit model to analyze field-based regulatory enforcement in the Brazilian Amazon. We validate our model, based on historical deforestation and enforcement mission data from 2003 to 2008. By simulating the current conservation law enforcement practice, we analyze the costs of liability establishment and legal coercion for alternative conservation targets, and evaluate corresponding income impacts. Our findings suggest that spatial patterns of both deforestation and inspection costs markedly influence enforcement patterns and their income effects. Field-based enforcement is a highly cost-effective forest conservation instrument from a regulator’s point of view, but comes at high opportunity costs for land users. Payments for environmental services could compensate costs, but will increase budget outlays vis-à-vis a command-and-control dominated strategy. Both legal and institutional challenges have to be overcome to make conservation payments work at a larger scale. Decision-makers may have to innovatively combine incentive and disincentive-based policy instruments in order to make tropical forest conservation both financially viable and socially compatible.
Topic: environmental policy,forest conservation,emission,REDD+,spatial analysis,mitigation
Publication Year: 2014
Source: Global Environmental Change