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Achieving the 1.5–2.0 °C temperature targets of the Paris climate agreement requires not only reducing emissions of greenhouse gases (GHGs) but also increasing removals of GHGs from the atmosphere1,2. Reforestation is a potentially large-scale method for removing CO2 and storing it in the biomass and soils of ecosystems3–8, yet its cost per tonne remains uncertain6,9. Here, we produce spatially disaggregated marginal abatement cost curves for tropical reforestation by simulating the effects of payments for increased CO2 removals on land-cover change in 90 countries. We estimate that removals from tropical reforestation between 2020–2050 could be increased by 5.7 GtCO2 (5.6%) at a carbon price of US$20 CO2–1, or by 15.1 GtCO2 (14.8%) at US$ 50 tCO2–1. Ten countries comprise 55% of potential low-cost abatement from tropical reforestation. Avoided deforestation offers 7.2–9.6 times as much potential low-cost abatement as reforestation overall (55.1 GtCO2 at US $20 tCO2–1 or 108.3 GtCO2 at US$ 50 tCO2–1), but reforestation offers more potential low-cost abatement than avoided deforestation at US$20 tCO2–1 in 21 countries, 17 of which are in Africa.There is a growing need to find cost-effective options for greenhouse gas abatement. In this study, spatially disaggregated marginal abatement cost curves are developed to facilitate economic appraisal of tropical reforestation.

More than 15% of global terrestrial area is under some form of protection and there is a growing impetus to increase this coverage to 30% by 2030. But not all protection is effective and the reasons some countries’ protected areas (PAs) are more effective than others’ are poorly understood. We evaluate the effectiveness of national PA networks established between 2000 and 2012 globally in avoiding forest loss, taking into account underlying deforestation threats using a combination of matching methods and cross-sectional regressions. We then assess which demographic, agricultural, economic, and governance factors are most strongly associated with national PA effectiveness using machine learning methods. We estimate that national PAs established between 2000 and 2012 reduced deforestation in those areas by 72%, avoiding 86 062 km 2 of forest loss. The effectiveness of national PAs varied by strictness of protection based on International Union for Conservation of Nature category. Strictly PAs reduced forest loss by 81% compared to what would have occurred without protection, while less strictly PAs reduced forest loss by 67%. Thus, the 26% of new PAs that were strictly protected contributed 39% of the total forest loss avoided within PAs between 2000 and 2012. If every country’s PAs were as effective as the country with the most effective PAs within the same region, they would have increased the area of deforestation avoided by 38%, saving a further 119 082 km 2 of forest. Part of the variation in PA effectiveness across countries is explained by the placement of PA in areas facing higher deforestation threat. Countries with lower agricultural activity, higher economic growth and better governance are most strongly associated with greater country-level PA effectiveness.

Reducing tropical deforestation is potentially a large-scale and low-cost strategy for mitigating climate change. Yet previous efforts to project the cost-effectiveness of policies to reduce greenhouse gas emissions from future deforestation across the tropics were hampered by crude available data on historical forest loss. Here we use recently available satellite-based maps of annual forest loss between 2001-2012, along with information on topography, accessibility, protected status, potential agricultural revenue, and an observed inverted-U-shaped relationship between forest cover loss and forest cover, to project tropical deforestation from 2016-2050 under alternative policy scenarios and to construct new marginal abatement cost curves for reducing emissions from tropical deforestation. We project that without new forest conservation policies 289 million hectares of tropical forest will be cleared from 2016-2050, releasing 169 GtCO2. A carbon price of US$20/tCO2 ($50/tCO2) across tropical countries would avoid 41 GtCO2 (77 GtCO2) from 2016-2050. By comparison, we estimate that Brazil's restrictive policies in the Amazon between 2004-2012 successfully decoupled potential agricultural revenue from deforestation and reduced deforestation by 47% below what would have otherwise occurred, preventing the emission of 5.2 GtCO2. All tropical countries enacting restrictive anti-deforestation policies as effective as those in the Brazilian Amazon between 2004-2012 would avoid 58 GtCO2 from 2016-2050.

Better land stewardship is needed to achieve the Paris Agreement's temperature goal, particularly in the tropics, where greenhouse gas emissions from the destruction of ecosystems are largest, and where the potential for additional land carbon storage is greatest. As countries enhance their nationally determined contributions (NDCs) to the Paris Agreement, confusion persists about the potential contribution of better land stewardship to meeting the Agreement's goal to hold global warming below 2°C. We assess cost-effective tropical country-level potential of natural climate solutions (NCS)—protection, improved management and restoration of ecosystems—to deliver climate mitigation linked with sustainable development goals (SDGs). We identify groups of countries with distinctive NCS portfolios, and we explore factors (governance, financial capacity) influencing the feasibility of unlocking national NCS potential. Cost-effective tropical NCS offers globally significant climate mitigation in the coming decades (6.56 Pg CO2e yr−1 at less than 100 US$ per Mg CO2e). In half of the tropical countries, cost-effective NCS could mitigate over half of national emissions. In more than a quarter of tropical countries, cost-effective NCS potential is greater than national emissions. We identify countries where, with international financing and political will, NCS can cost-effectively deliver the majority of enhanced NDCs while transforming national economies and contributing to SDGs. This article is part of the theme issue ‘Climate change and ecosystems: threats, opportunities and solutions’.

Introduction: The central premise underlying international payments for Reducing Emissions from Deforestation and forest Degradation (REDD+) is that offering governments ex post payments for verified success in reducing emissions will motivate them to protect and restore forests. However, the extent to which performance-based payments motivate governments to protect and restore forests has yet to be evaluated quantitatively. Researchers have only quantitatively evaluated performance-based payments to non-governments for forest outcomes (e.g. payments for ecosystem services) and to governments for non-forest outcomes (e.g. results-based aid). Methods: We describe how researchers now have an opportunity to more easily evaluate performance-based payments to governments for forest outcomes thanks to India's new ecological fiscal transfers (EFTs), which provide $6-12 billion per year to Indian states in proportion to their forest cover. Discussion: India's EFTs differ from REDD+ programs in that they pay for states' stock of forest area in the recent past rather than reductions in the rate of forest carbon loss in the near-future. Nevertheless, India's EFTs focus on a single outcome and have many recipient governments, significant financial scale, lack of contemporaneous confounding policy changes, universal participation, and long-term data collection. Conclusion: These features make India's EFTs especially useful for testing the payment-for-performance premise of REDD+.

Significance Our paper is significant in a number of respects. First, we expand the literature on quasi-experimental evaluation of the causal impact of conservation measures to include agricultural concessions. Second, our report is rare in that we use panel data and techniques in a literature on spatially explicit land-use change econometrics that has necessarily relied upon cross-sectional analyses because of data-availability constraints. Third, our report is rare among land-use change scenario analyses in that we calibrate the effect of land-use designations empirically, rather than assuming idealized perfect effectiveness of conservation measures or complete conversion without such measures. Finally, we compare the effectiveness of place-based policies with alternative price-based instruments for climate-change mitigation within a globally significant landscape. To reduce greenhouse gas emissions from deforestation, Indonesia instituted a nationwide moratorium on new license areas (“concessions”) for oil palm plantations, timber plantations, and logging activity on primary forests and peat lands after May 2011. Here we indirectly evaluate the effectiveness of this policy using annual nationwide data on deforestation, concession licenses, and potential agricultural revenue from the decade preceding the moratorium. We estimate that on average granting a concession for oil palm, timber, or logging in Indonesia increased site-level deforestation rates by 17–127%, 44–129%, or 3.1–11.1%, respectively, above what would have occurred otherwise. We further estimate that if Indonesia’s moratorium had been in place from 2000 to 2010, then nationwide emissions from deforestation over that decade would have been 241–615 MtCO ₂e (2.8–7.2%) lower without leakage, or 213–545 MtCO ₂e (2.5–6.4%) lower with leakage. As a benchmark, an equivalent reduction in emissions could have been achieved using a carbon price-based instrument at a carbon price of $3.30–7.50/tCO ₂e (mandatory) or $12.95–19.45/tCO ₂e (voluntary). For Indonesia to have achieved its target of reducing emissions by 26%, the geographic scope of the moratorium would have had to expand beyond new concessions (15.0% of emissions from deforestation and peat degradation) to also include existing concessions (21.1% of emissions) and address deforestation outside of concessions and protected areas (58.7% of emissions). Place-based policies, such as moratoria, may be best thought of as bridge strategies that can be implemented rapidly while the institutions necessary to enable carbon price-based instruments are developed.

Demand-side restrictions on high-deforestation commodities are expanding as a climate policy, but their impact on reducing tropical deforestation and emissions has yet to be quantified. Here we model the effects of demand-side restrictions on high-deforestation palm oil in Europe on deforestation and emissions in Indonesia. We do so by integrating a model of global trade with a spatially explicit model of land-use change in Indonesia. We estimate a European ban on high-deforestation palm oil from 2000 to 2015 would have led to a 8.9% global price premium on low-deforestation palm oil, resulting in 21 374 ha yr −1 (1.60%) less deforestation and 21.1 million tCO 2 yr −1 (1.91%) less emissions from deforestation in Indonesia relative to what occurred. A hypothetical Indonesia-wide carbon price would have achieved equivalent emission reductions at $0.81/tCO 2 . Impacts of a ban are small because: 52% of Europe’s imports of high-deforestation palm oil would have shifted to non-participating countries; the price elasticity of supply of high-deforestation oil palm cropland is small (0.13); and conversion to oil palm was responsible for only 32% of deforestation in Indonesia. If demand-side restrictions succeed in substantially reducing deforestation, it is likely to be through non-price pathways.

This paper presents an overview of the state of measurement and monitoring capabilities for forests in the context of REDD+ needs, with a focus on what is currently possible, where improvements are needed, and what capabilities will be advanced in the near-term with new technologies already under development. We summarize the role of remote sensing (both satellite and aircraft) for observational monitoring of forests, including measuring changes in their current and past extent for setting baselines, their carbon stock density for estimating emissions in areas that are deforested or degraded, and their regrowth dynamics following disturbance. We emphasize the synergistic role of integrating field inventory measurements with remote sensing for best practices in monitoring, reporting and verification. We also address the potential of remote sensing for enforcing safeguards on conservation of natural forests and biodiversity. We argue that capabilities exist now to meet operational needs for REDD+ measurement, reporting, and verification and reference levels. For some other areas of importance for REDD+, such as safeguards for natural forests and biodiversity, monitoring capabilities are approaching operational in the near term. For all REDD+ needs, measurement capabilities will rapidly advance in the next few years as a result of new technology as well as advances in capacity building both within and outside of the tropical forest nations on which REDD+ is primarily focused.

The authority of state- and province-level governments (“second-tier governments”) to make decisions related to slowing deforestation independently of national governments varies widely across countries. Here we systematically catalog whether second-tier governments in 30 tropical countries with high projected future emissions from deforestation possess 14 distinct types of general and forest-related authority. We compile this information in a free, open-access database. Second-tier governments have broadest authority to reduce deforestation in India, Brazil, Indonesia, Malaysia, Papua New Guinea, Peru, China, Laos, Mozambique, and Vietnam. Second-tier governments have the least authority in Central African Republic, Gabon, Angola, Madagascar, Bolivia, Cambodia, Cameroon, Guyana, Suriname, Thailand, and Venezuela. Second-tier governments have intermediate authority in Democratic Republic of Congo, Ecuador, Mexico, the Philippines, Colombia, Myanmar, Tanzania, Zambia, Mexico, and Republic of Congo. Authorities that second-tier governments most commonly possess include development planning, taxation, budgeting, and roads. Authorities that second-tier governments least commonly possess include land ownership, police, permits for mining, Indigenous affairs, and protected areas. Authorities possessed by an intermediate number of second-tier governments include spatial planning, elections, courts, and permits for agriculture. More than one-quarter of future emissions from deforestation between 2020 and 2050 is projected to come from just seven out of 678 second-tier jurisdictions: Amazonas, Pará, and Mato Grosso (Brazil), Équateur and Orientale (Democratic Republic of Congo), Loreto (Peru), and El Beni (Bolivia). After weighting for authority, our list of the 50 second-tier jurisdictions in the tropics that are the highest priority for reducing emissions from deforestation shifts to include fewer second-tier jurisdictions in Africa (where second-tier governments have 4.2 authorities out of 14 in the average country) and Latin America (6.3 authorities out of 14) and more second-tier jurisdictions in Asia (8.5 authorities out of 14). Second-tier jurisdictions that have formally expressed interest in reducing emissions from deforestation, e.g., through the Governors' Climate and Forest Task Force, Under2 Coalition, or New York Declaration on Forests, possess greater authority to reduce deforestation on average than other jurisdictions. Information on second-tier governmental authority, when complemented with deeper country-specific knowledge, can help initiatives for reducing emissions from deforestation (REDD+) prioritize support across regions and across sectoral interventions.