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It has been suggested that rainfall in the Amazon decreases if forest loss exceeds some threshold, but the specific value of this threshold remains uncertain. Here, we investigate the relationship between historical deforestation and rainfall at different geographical scales across the Southern Brazilian Amazon (SBA). We also assess impacts of deforestation policy scenarios on the region's agriculture. Forest loss of up to 55–60% within 28 km grid cells enhances rainfall, but further deforestation reduces rainfall precipitously. This threshold is lower at larger scales (45–50% at 56 km and 25–30% at 112 km grid cells), while rainfall decreases linearly within 224 km grid cells. Widespread deforestation results in a hydrological and economic negative-sum game, because lower rainfall and agricultural productivity at larger scales outdo local gains. Under a weak governance scenario, SBA may lose 56% of its forests by 2050. Reducing deforestation prevents agricultural losses in SBA up to US$ 1 billion annually. Deforestation in the Amazon region has suggested to influence precipitation in a non-linear way. Here, the authors show that forest loss is associated with decreasing precipitation after a scale-dependent threshold is crossed, which can cause stress on agriculture if deforestation is expanded. [ABSTRACT FROM AUTHOR]

Tropical forest conservation is considered a low-cost option for climate change mitigation. But mitigation cost assessments have featured opportunity costs, neglecting policy implementation costs. Here we use official data to identify the Brazilian federal government's operational and institutional budgets related to forest conservation policies implemented from 2000 to 2014. We distinguish the allocated and executed budgets of these policies, and provide scenario-based estimates of their cost-effectiveness. On average, Brazil spent US$ 1 billion/year on forest conservation policies at the federal level. Brazil's substantial reduction in annual forest loss after 2004 was accompanied by a higher operational budget execution of disincentive-based policy instruments, and an absolute increase in both allocated and executed institutional budgets. The post-2004 successful mitigation effort represented additional implementation costs to the Brazilian federal government of US$ 308–923/ha of avoided deforestation, or US$ 0.87–2.60/tCO 2 of avoided emissions. Factoring in also approximate municipal and state expenditures, these costs increase to US$ 385–1153/ha or US$ 1.09–3.25/tCO 2 . We conclude that implementations costs are non-trivial in size, including compared to estimates of land users' opportunity costs. This has important implications for REDD + policy design, in the sense that implementation costs need to be adequately considered. [ABSTRACT FROM AUTHOR]

Deforestation in the Brazilian Amazon has dropped substantially after a peak of over 27 thousand square kilometers in 2004. Starting in 2008, the Brazilian Ministry of the Environment has regularly published blacklists of critical districts with high annual forest loss. Farms in blacklisted districts face additional administrative hurdles to obtain authorization for clearing forests. In this paper we add to the existing literature on evaluating the Brazilian anti-deforestation policies by specifically quantifying the impact of blacklisting on deforestation. We first use spatial matching techniques using a set of covariates that includes official blacklisting criteria to identify control districts. We then explore the effect of blacklisting on change in deforestation in double difference regressions with panel data covering the period from 2002 to 2012. Multiple robustness checks are conducted including an analysis of potential causal mechanisms behind the success of the blacklist. We find that the blacklist has considerably reduced deforestation in the affected districts even after controlling for the potential mechanism effects of field-based enforcement, environmental registration campaigns, and rural credit. [ABSTRACT FROM AUTHOR]

Regulatory enforcement of forest conservation laws is often dismissed as an ineffective approach to reducing tropical forest loss. Yet, effective enforcement is often a precondition for alternative conservation measures, such as payments for environmental services, to achieve desired outcomes. Fair and efficient policies to reducing emissions from deforestation and forest degradation (REDD) will thus crucially depend on understanding the determinants and requirements of enforcement effectiveness. Among potential REDD candidate countries, Brazil is considered to possess the most advanced deforestation monitoring and enforcement infrastructure. This study explores a unique dataset of over 15 thousand point coordinates of enforcement missions in the Brazilian Amazon during 2009 and 2010, after major reductions of deforestation in the region. We study whether local deforestation patterns have been affected by field-based enforcement and to what extent these effects vary across administrative boundaries. Spatial matching and regression techniques are applied at different spatial resolutions. We find that field-based enforcement operations have not been universally effective in deterring deforestation during our observation period. Inspections have been most effective in reducing large-scale deforestation in the states of Mato Grosso and Pará, where average conservation effects were 4.0 and 9.9 hectares per inspection, respectively. Despite regional and actor-specific heterogeneity in inspection effectiveness, field-based law enforcement is highly cost-effective on average and might be enhanced by closer collaboration between national and state-level authorities. [ABSTRACT FROM AUTHOR]

Conditional incentives are a promising complementary approach to conserve tropical forests, for example, in multiple-use protected areas. In this paper we analyze the environmental impacts of Bolsa Floresta , a forest conservation program that combines direct conditional payments with livelihood-focused investments in 15 multiple-use reserves in the Brazilian state of Amazonas. We use grid-based data, nearest-neighbor matching, and panel data econometrics to compare three forest-related program outcomes – deforestation, degradation, and fires – of participating and non-participating reserve areas. Forest threats were low before and after treatment, because the program prioritized low-pressure sites. Thus, we find significant but small additional conservation effects from the implementation of the program. Notwithstanding, treatment effects are relatively larger in areas with higher deforestation pressure and higher potential agricultural income. Our findings add to the growing body of evidence showing that adverse spatial targeting of conservation incentives, i.e. disproportionally enrolling low–pressure sites, is a prime cause for the low additionality found in rigorous impact evaluations of many existing initiatives. [ABSTRACT FROM AUTHOR]

Reducing emissions from agriculture, forestry, and other land uses is considered an essential ingredient of an effective strategy to mitigate global warming. Required changes in land use and forestry, however, often imply foregoing returns from locally more attractive resource use strategies. We assess and compare the prospects of mitigating climate change through emission reductions from forestry and agriculture in the Brazilian Amazon. We use official statistics, literature, and case study material from both old and new colonization frontiers to identify the scope for emission reductions, in terms of potential additionality, opportunity costs, technological complexity, transaction costs, and risks of economic and environmental spillover effects. Our findings point to a comparative advantage in the Brazilian Amazon of forest conservation-based over land-use modifying mitigation options, especially in terms of higher potential additionality in emission reductions. Low-cost mitigation options do exist also in use-modifying agriculture and forestry, but tend to be technologically complex thus requiring more costly intervention schemes. Our review points to a series of regional development deficits that may come to hamper attempts to tap into the large-scale climate change mitigation potential often associated with the Amazon. Low-hanging fruits for mitigation do exist, but must be carefully identified based on the performance indicators we discuss. [ABSTRACT FROM AUTHOR]

Abstract: Land reform settlements (LRS) in the Brazilian Amazon have been suggested to hold promise for the successful implementation of incipient efforts to reducing emissions from deforestation and degradation (REDD). However, differences in forest cover, deforestation behaviour and settler welfare plus the inevitable overlap of upcoming REDD efforts with existing conservation policies, mean that scope and impact of REDD in LRS will not be uniform across settlements. Based on evidence from a case study of four LRS and a Brazilian Amazon regional analysis of opportunity costs, this paper explores the actual scope for targeting initial Brazilian REDD efforts to LRS and discusses potential welfare and equity implications based on scenario analysis. While our findings confirm considerable economic scope for compensation-based schemes for avoided degradation and deforestation, the pre-existence of legal use right limitations in combination with the distribution of forest cover among LRS means that less than half of settlements – poorer – will be able to derive economic gains. Exploring a mix between incentives and disincentives seems to offer the most promising future regarding efficiency and equity successful results. The paper concludes with the implications of the results in the international debate on the constraints ahead to implement the REDD principles. [Copyright &y& Elsevier]

This article looks into the scope and equity implications of applying payments for environmental services (PES) as a REDD implementation mechanism in the Brazilian Amazon. We establish a set of economic and institutional preconditions for PES to become a feasible and cost-effective conservation mechanism. We proceed with a macro-scale spatial analysis and overlay of opportunity costs, deforestation patterns, carbon services, and land tenure, in order to assess where these conditions hold. We then screen how the benefits of potential PES schemes might be distributed across different socioeconomic groups of service providers in different land tenure categories. Our economic–quantitative analysis, though sensitive to documented assumptions, suggests that under current carbon prices the economic preconditions are in place to pay for avoided deforestation in over half of threatened forests over the next decade. Unfortunately, the same optimism does not apply to institutional preconditions. Land grabbing, insecure tenure, overlapping claims, and lacking information on private tenure constitute real medium-term impediments to PES. If payments were to accrue to current landholders regardless of current tenure insecurities, large landowners who account for about 80% of all deforestation would reap the highest benefits, though per-capita benefits other tenure categories are also high. Schemes that closely align payments with opportunity costs are preferable for cost-effectiveness, and not necessarily more inequitable in outcomes. Essentially, PES systems cannot substitute command-and-control measures: the former depend on the latter for basic governance systems to secure effective rights of exclusion, which land stewards essentially need in order to become reliable service providers. [Copyright &y& Elsevier]

• Spatially-explicit CO 2 emissions of Brazilian soy exports using new bottom-up LCA. • Carbon footprint of MATOPIBA states is 2–6 times larger than Brazil average. • Cerrado has the largest footprint (1.00 tCO 2 -eq.t−1soy-eq.) followed by the Amazon. • Carbon footprint of EU (0.77 tCO 2 -eq.t−1soy-eq.) is 13.8% larger than China's. • Total CO 2 emissions are 223.46 Mt in 2010–2015, of which China imports 51%. Reliable estimates of carbon and other environmental footprints of agricultural commodities require capturing a large diversity of conditions along global supply chains. Life Cycle Assessment (LCA) faces limitations when it comes to addressing spatial and temporal variability in production, transportation and manufacturing systems. We present a bottom-up approach for quantifying the greenhouse gas (GHG) emissions embedded in the production and trade of agricultural products with a high spatial resolution, by means of the integration of LCA principles with enhanced physical trade flow analysis. Our approach estimates the carbon footprint (as tonnes of carbon dioxide equivalents per tonne of product) of Brazilian soy exports over the period 2010–2015 based on ~90,000 individual traded flows of beans, oil and protein cake identified from the municipality of origin through international markets. Soy is the most traded agricultural commodity in the world and the main agricultural export crop in Brazil, where it is associated with significant environmental impacts. We detect an extremely large spatial variability in carbon emissions across sourcing areas, countries of import, and sub-stages throughout the supply chain. The largest carbon footprints are associated with municipalities across the MATOPIBA states and Pará, where soy is directly linked to natural vegetation loss. Importing soy from the aforementioned states entailed up to six times greater emissions per unit of product than the Brazilian average (0.69 t t−1). The European Union (EU) had the largest carbon footprint (0.77 t t−1) due to a larger share of emissions from embodied deforestation than for instance in China (0.67 t t−1), the largest soy importer. Total GHG emissions from Brazilian soy exports in 2010–2015 are estimated at 223.46 Mt, of which more than half were imported by China although the EU imported greater emissions from deforestation in absolute terms. Our approach contributes data for enhanced environmental stewardship across supply chains at the local, regional, national and international scales, while informing the debate on global responsibility for the impacts of agricultural production and trade. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Protected areas (PAs) are important policy instruments for forest conservation, but it is unclear if improved management can increase PA effectiveness. In Brazil, formal management plans are required to be in place shortly after the creation of a PA. This requirement is rarely enforced and, as a result, several PAs undergo many years without approved plans. We take advantage of this variation among PAs to study the impact of management plans on deforestation. We provide estimates from two quasi-experimental evaluation approaches based on the generalization of the difference-in-differences estimator: (1) matching-based methods for time-series cross-sectional data analysis and (2) the generalized synthetic control (GSC) method. We find weak, yet generally consistent, evidence across these two methods suggesting that PAs with approved management plans protect forests more effectively over time. Significant impact estimates from the matching-based approach ranged more widely than the GSC method (0.01%–0.09% versus 0.04%–0.05% of avoided deforestation per year, respectively). The effect size of these impacts is relatively substantial given that the average annual forest loss from our PA sample was 0.07% (±0.40%). To the extent that PAs with approved management plans reflect actual differences in PA management quality, our findings suggest that investments in improving PA management could result in positive conservation gains over time. [ABSTRACT FROM AUTHOR]

Here, we analyze critical changes in environmental law enforcement in the Brazilian Amazon between 2000 and 2020. Based on a dataset of law enforcement indicators, we discuss how these changes explain recent Amazon deforestation dynamics. Our analysis also covers changes in the legal prosecution process and documents a militarization of enforcement between 2018 and 2022. From 2004 to 2018, 43.6 thousand land-use embargoes and 84.3 thousand fines were issued, targeting 3.3 million ha of land, and totaling USD 9.3 billion in penalties. Nevertheless, enforcement relaxed and became spatially more limited, signaling an increasing lack of commitment by the State to enforcing the law. The number of embargoes and asset confiscations dropped by 59% and 55% in 2019 and 2020, respectively. These changes were accompanied by a marked increase in enforcement expenditure, suggesting a massive efficiency loss. More importantly, the creation of so-called conciliation hearings and the centralization of legal processes in 2019 reduced the number of actual judgments and fines collected by 85% and decreased the ratio between lawsuits resulting in paid fines over filed ones from 17 to 5%. As Brazil gears up to crack-down on illegal deforestation once again, our assessment suggests urgent entry points for policy action., (© 2024. The Author(s).)

Reducing emissions from deforestation and forest degradation (REDD+) has gained international attention over the past decade, as manifested in both United Nations policy discussions and hundreds of voluntary projects launched to earn carbon-offset credits. There are ongoing discussions about whether and how projects should be integrated into national climate change mitigation efforts under the Paris Agreement. One consideration is whether these projects have generated additional impacts over and above national policies and other measures. To help inform these discussions, we compare the crediting baselines established ex-ante by voluntary REDD+ projects in the Brazilian Amazon to counterfactuals constructed ex-post based on the quasi-experimental synthetic control method. We find that the crediting baselines assume consistently higher deforestation than counterfactual forest loss in synthetic control sites. This gap is partially due to decreased deforestation in the Brazilian Amazon during the early implementation phase of the REDD+ projects considered here. This suggests that forest carbon finance must strike a balance between controlling conservation investment risk and ensuring the environmental integrity of carbon emission offsets. Relatedly, our results point to the need to better align project- and national-level carbon accounting., Competing Interests: The authors declare no competing interest.

Annual forest loss in the Brazilian Amazon had in 2012 declined to less than 5,000 sqkm, from over 27,000 in 2004. Mounting empirical evidence suggests that changes in Brazilian law enforcement strategy and the related governance system may account for a large share of the overall success in curbing deforestation rates. At the same time, Brazil is experimenting with alternative approaches to compensate farmers for conservation actions through economic incentives, such as payments for environmental services, at various administrative levels. We develop a spatially explicit simulation model for deforestation decisions in response to policy incentives and disincentives. The model builds on elements of optimal enforcement theory and introduces the notion of imperfect payment contract enforcement in the context of avoided deforestation. We implement the simulations using official deforestation statistics and data collected from field-based forest law enforcement operations in the Amazon region. We show that a large-scale integration of payments with the existing regulatory enforcement strategy involves a tradeoff between the cost-effectiveness of forest conservation and landholder incomes. Introducing payments as a complementary policy measure increases policy implementation cost, reduces income losses for those hit hardest by law enforcement, and can provide additional income to some land users. The magnitude of the tradeoff varies in space, depending on deforestation patterns, conservation opportunity and enforcement costs. Enforcement effectiveness becomes a key determinant of efficiency in the overall policy mix.