Andrea Cattaneo

The End of Deforestation in the Brazilian Amazon

Government commitments and market transitions lay the foundation for an effort to save the forest and reduce carbon emission. Brazil has two major opportunities to end the clearing of its Amazon forest and to reduce global greenhouse gas emissions substantially. The first is its formal announcement within United Nations climate treaty negotiations in 2008 of an Amazon deforestation reduction target, which prompted Norway to commit

Indigenous Lands, Protected Areas, and Slowing Climate Change

1 billion if it sustains progress toward this target (1). The second is a widespread marketplace transition within the beef and soy industries, the main drivers of deforestation, to exclude Amazon deforesters from their supply chains (2) [supplementary online material (SOM), section (§) 4]. According to our analysis, these recent developments finally make feasible the end of deforestation in the Brazilian Amazon, which could result in a 2 to 5% reduction in global carbon emissions. The

Comparing climate and cost impacts of reference levels for reducing emissions from deforestation.

7 to

Robust design of multiscale programs to reduce deforestation

18 billion beyond Brazils current budget outlays that may be needed to stop the clearing [a range intermediate to previous cost estimates (3, 4)] could be provided by the REDD (Reducing Emissions from Deforestation and Forest Degradation) mechanism for compensating deforestation reduction that is under negotiation within the UN climate treaty (5), or by payments for tropical forest carbon credits under a U.S. cap-and-trade system (6).

On international equity in reducing emissions from deforestation

Recent climate talks in Copenhagen reaffirmed the crucial role of reducing emissions from deforestation and degradation (REDD). Creating and strengthening indigenous lands and other protected areas represents an effective, practical, and immediate REDD strategy that addresses both biodiversity and climate crises at once.

Guidelines for cost-effective agri-environmental policy measures

The climate benefit and economic cost of an international mechanism for reducing emissions from deforestation and degradation (REDD) will depend on the design of reference levels for crediting emission reductions. We compare the impacts of six proposed reference level designs on emission reduction levels and on cost per emission reduction using a stylized partial equilibrium model (the open source impacts of REDD incentives spreadsheet; OSIRIS). The model explicitly incorporates national incentives to participate in an international REDD mechanism as well as international leakage of deforestation emissions. Our results show that a REDD mechanism can provide cost-efficient climate change mitigation benefits under a broad range of reference level designs. We find that the most effective reference level designs balance incentives to reduce historically high deforestation emissions with incentives to maintain historically low deforestation emissions. Estimates of emission reductions under REDD depend critically on the degree to which demand for tropical frontier agriculture generates leakage. This underscores the potential importance to REDD of complementary strategies to supply agricultural needs outside of the forest frontier.

Green auctions with joint environmental benefits

A framework is provided for structuring programs aimed at reducing emissions from deforestation and forest degradation (REDD). Crediting reference levels and the coordination among different implementing entities at multiple geographic scales are discussed. A crediting reference level has an error component if it differs from the business-as-usual (BAU) without REDD. Both the BAU emissions and the impact of REDD actions are uncertain, implying that participating in REDD entails stakeholder risk, the distribution of which depends on REDD program design. To categorize REDD architectures we define scale-neutrality whereby, for a given REDD design, crediting relative to the reference level at a given scale is not affected by errors in reference levels at scales below it. Sufficient conditions are derived for scale-neutrality to hold. A Brazilian Amazon example is provided, comparing potential REDD architectures, and highlighting how a cap-and-trade approach may match the environmental outcome obtainable with perfect foresight of the BAU emissions.