Cost-effective REDD++ policy design in the Brazilian Amazon: How to combine incentives and control without harming the poor?
Despite recent reductions, Brazil remains among the top-three deforesting countries in the world, and is thus one of the countries where ‘reduced emission from deforestation and forest degradation’ (REDD++ 1 ) initiatives could potentially have the most tangible returns for climate-change mitigation. Some pioneer initiatives at the national and federal-state level already exist. But, assuming sufficient international funding was available, what actions on the ground can be financed to actually achieve additional forest conservation? Economic incentives, such as payments for environmental services (PES) represent one option to induce forestland stewards under appropriate property right regimes to conserve more forests. Yet, for the large part of Amazon deforestation that occurs on non-designated public lands (terra devoluta) as well as on poorly delimited private land, PES will not be viable. REDD+ will thus also require other tools, notably improved command-and control policies that enforce forest laws more rigorously. While quite a number of studies have addressed the potential costs of using PES as a REDD+ vehicle, few cost estimates of control-based REDD+ strategies exist. In this study, we develop a spatially explicit representation of the variable costs of command-and-control policies, and overlay this information with available REDD+ opportunity cost estimates. On the basis of the results, alternative REDD+ strategies and their cost and equity implications are discussed. Our findings suggest that command-and-control is often the most cost-effective REDD+ instrument from a regulator’s point of view. But given existing insecure and unequal tenure regimes in the Brazilian Amazon, equity considerations have to be taken into account. Incentives such as PES can reduce implementation costs where enforcement is expensive, while also minimizing social costs, yet both legal and institutional challenges have to be overcome to make incentives work at a larger scale
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