Does agricultural efficiency contribute to slowdown of deforestation in the Brazilian Legal Amazon?

Historically, agricultural production in the Amazon has been painted as the most environmentally impacting activity. In this study, we investigated the relationship between the increase in agricultural efficiency and the slowdown of deforestation rates in the past decade, correlating these data with municipalities’ agricultural specialization. With the data from the 2006 and 2017 Brazilian Agricultural Census we classified municipalities according to its vegetal or animal specialization and estimated a production frontier using the Stochastic Frontier Analysis (SFA), considering a set of production factors and technological variables. Our results demonstrated that most part of municipalities have no specialization or are based in cattle ranching activities, and the overall agricultural efficiency in the Amazon municipalities grew from 69.5% in 2006 to 74.1% in 2017. The new institutional path in the 21st century contributed to slow deforestation in agricultural activities through an increase in productivity (yield/ha) in the last decade, mainly for vegetal production. Cattle ranching also increased output and efficiency, but it remains the most environmental impacting activity. However, several municipalities could not develop their agricultural production value relative to the most productive areas, suggesting that some factors —technological and productive— that could lead to output increase are not being efficiently allocated, which results in concentrating deforestation in inefficient systems and limiting the effectiveness of current policies. Technological diffusion, especially for small farmers, and private support in environmental issues could contribute to slowdown deforestation without loss of agricultural output.     

Deforestation and land use in the Brazilian Amazon

Deforestation in the Brazilian Amazon was less than 1% before 1975. Between 1975 and 1987 the rate increased exponentially. By 1985, world opinion and attention to the destruction of the richest biome on earth led to elimination of some of the major incentives that had fueled deforestation. Favorable credit policies for cattle ranchers, rather than population growth, explains the process of deforestation in the Brazilian Amazon. The paper suggests other actions that may be taken to reduce deforestation, and examines the rapid growth rates of secondary successional species in a colonization area.     

Mixing Carrots and Sticks to Conserve Forests in the Brazilian Amazon: A Spatial Probabilistic Modeling Approach

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.     

Simulating the response of land-cover changes to road paving and governance along a major Amazon highway: the Santarém–Cuiabá corridor

The spatial distribution of human activities in forest frontier regions is strongly influenced by transportation infrastructure. With the planned paving of 6000 km of highway in the Amazon Basin, agricultural frontier expansion will follow, triggering potentially large changes in the location and rate of deforestation. We developed a land‐cover change simulation model that is responsive to road paving and policy intervention scenarios for the BR‐163 highway in central Amazonia. This corridor links the cities of Cuiabá, in central Brazil, and Santarém, on the southern margin of the Amazon River. It connects important soybean production regions and burgeoning population centers in Mato Grosso State with the international port of Santarém, but 1000 km of this road are still not paved. It is within this context that the Brazilian government has prioritized the paving of this road to turn it into a major soybean exportation facility. The model assesses the impacts of this road paving within four scenarios: two population scenarios (high and moderate growth) and two policy intervention scenarios. In the ‘business‐as‐usual’ policy scenario, the responses of deforestation and land abandonment to road paving are estimated based on historical rates of Amazon regions that had a major road paved. In the ‘governance’ scenario, several plausible improvements in the enforcement of environmental regulations, support for sustainable land‐use systems, and local institutional capacity are invoked to modify the historical rates. Model inputs include data collected during expeditions and through participatory mapping exercises conducted with agents from four major frontier types along the road. The model has two components. A scenario‐generating submodel is coupled to a landscape dynamics simulator, ‘DINAMICA’, which spatially allocates the land‐cover transitions using a GIS database. The model was run for 30 years, divided into annual time steps. It predicted more than twice as much deforestation along the corridor in business‐as‐usual vs. governance scenarios. The model demonstrates how field data gathered along a 1000 km corridor can be used to develop plausible scenarios of future land‐cover change trajectories that are relevant to both global change science and the decision‐making process of governments and civil society in an important rainforest region.     

Synergistic effects of drought and deforestation on the resilience of the south-eastern Amazon rainforest

The south-eastern Amazon rainforest is subject to ongoing deforestation and is expected to become drier due to climate change. Recent analyses of the distribution of tree cover in the tropics show three modes that have been interpreted as representing alternative stable states: forest, savanna and treeless states. This situation implies that a change in environmental conditions, such as in the climate, could cause critical transitions from a forest towards a savanna ecosystem. Shifts to savanna might also occur if perturbations such as deforestation exceed a critical threshold. Recovering the forest would be difficult as the savanna will be stabilized by a feedback between tree cover and fire. Here we explore how environmental changes and perturbations affect the forest by using a simple model with alternative tree-cover states. We focus on the synergistic effects of precipitation reduction and deforestation on the probability of regime shifts in the south-eastern Amazon rainforest. The analysis indicated that in a large part of the south-eastern Amazon basin rainforest and savanna could be two alternative states, although massive forest dieback caused by mean-precipitation reduction alone is unlikely. However, combinations of deforestation and climate change triggered up to 6.6 times as many local regime shifts than the two did separately, causing large permanent forest losses in the studied region. The results emphasize the importance of reducing deforestation rates in order to prevent a climate-induced dieback of the south-eastern Amazon rainforest.     

Satellite‐based estimates reveal widespread forest degradation in the Amazon

Anthropogenic and natural forest disturbance cause ecological damage and carbon emissions. Forest disturbance in the Amazon occurs in the form of deforestation (conversion of forest to non‐forest land covers), degradation from the extraction of forest resources, and destruction from natural events. The crucial role of the Amazon rainforest in the hydrologic cycle has even led to the speculation of a disturbance “tipping point” leading to a collapse of the tropical ecosystem. Here we use time series analysis of Landsat data to map deforestation, degradation, and natural disturbance in the Amazon Ecoregion from 1995 to 2017. The map was used to stratify the study area for selection of sample units that were assigned reference labels based on their land cover and disturbance history. An unbiased statistical estimator was applied to the sample of reference observations to obtain estimates of area and uncertainty at biennial time intervals. We show that degradation and natural disturbance, largely during periods of severe drought, have affected as much of the forest area in the Amazon Ecoregion as deforestation from 1995 to 2017. Consequently, an estimated 17% (1,036,800 ± 24,800 km², 95% confidence interval) of the original forest area has been disturbed as of 2017. Our results suggest that the area of disturbed forest in the Amazon is 44%–60% more than previously realized, indicating an unaccounted for source of carbon emissions and pervasive damage to forest ecosystems.     

Protected area types,strategies and impacts in Brazil's Amazon: public protected area strategies do not yield a consistent ranking of protected area types by impact

The leading policy to conserve forest is protected areas (PAs). Yet, PAs are not a single tool: land users and uses vary by PA type; and public PA strategies vary in the extent of each type and in the determinants of impact for each type, i.e. siting and internal deforestation. Further, across regions and time, strategies respond to pressures (deforestation and political). We estimate deforestation impacts of PA types for a critical frontier, the Brazilian Amazon. We separate regions and time periods that differ in their deforestation and political pressures and document considerable variation in PA strategies across regions, time periods and types. The siting of PAs varies across regions. For example, all else being equal, PAs in the arc of deforestation are relatively far from non-forest, while in other states they are relatively near. Internal deforestation varies across time periods, e.g. it is more similar across the PA types for PAs after 2000. By contrast, after 2000, PA extent is less similar across PA types with little non-indigenous area created inside the arc. PA strategies generate a range of impacts for PA types—always far higher within the arc—but not a consistent ranking of PA types by impact.     

Assessing the impacts of past and ongoing deforestation on rainfall patterns in South America

Despite recent advances in modeling forest–rainfall relationships, the current understanding of changes in observed rainfall patterns resulting from historical deforestation remains limited. To address this knowledge gap, we analyzed how 40 years of deforestation has altered rainfall patterns in South America as well as how current Amazonian forest cover sustains rainfall. First, we develop a spatiotemporal neural network model to simulate rainfall as a function of vegetation and climate inputs in South America; second, we assess the rainfall effects of observed deforestation in South America during the periods 1982–2020 and 2000–2020; third, we assess the potential rainfall changes in the Amazon biome under two deforestation scenarios. We find that, on average, cumulative deforestation in South America from 1982 to 2020 has reduced rainfall over the period 2016–2020 by 18% over deforested areas, and by 9% over non-deforested areas across South America. We also find that more recent deforestation, that is, from 2000 to 2020, has reduced rainfall over the period 2016–2020 by 10% over deforested areas and by 5% over non-deforested areas. Deforestation between 1982 and 2020 has led to a doubling in the area experiencing a minimum dry season of 4 months in the Amazon biome. Similarly, in the Cerrado region, there has been a corresponding doubling in the area with a minimum dry season of 7 months. These changes are compared to a hypothetical scenario where no deforestation occurred. Complete conversion of all Amazon forest land outside protected areas would reduce average annual rainfall in the Amazon by 36% and complete deforestation of all forest cover including protected areas would reduce average annual rainfall in the Amazon by 68%. Our findings emphasize the urgent need for effective conservation measures to safeguard both forest ecosystems and sustainable agricultural practices.     

Adoption of Policy Incentives and Land Use: Lessons From Frontier Agriculture in Southeastern Peru

Literature on environmental change often highlights the importance of public policies as a key driver of land use and land cover change. However, demonstration of policy impacts in agricultural settings has been hampered by the lack of systematic analysis across landholders, who may not universally adopt government policy incentives, or time periods, which may be associated with differing policy regimes. This paper evaluates the importance of voluntary adoption of policy incentives offered by Peruvian government administrations over two decades for land-use among small farmers in the Peruvian Amazon. The analysis focuses on whether farmers adopted one or more policy incentives in order to observe the effects on land uses including mature forest, agricultural crops, cattle pasture, and secondary growth. We employ multivariate statistical models to estimate the effects of policy adoption while controlling for other factors. The findings show that distinct policies are associated with particular land-uses and largely follow expectations. Specifying policy incentives promulgated by governments and differentiating among adopters and non-adopters advances understanding of the impacts of public policies on land use.     

Socioeconomic dimensions,migration, and deforestation: An integrated model of territorial organization for the Brazilian Amazon

The territory organization of the Brazilian Amazon, understood as a socioeconomic network of municipalities, reflects the diversity of human settlements and their potentials for environmental changes, especially deforestation. This paper characterizes the urban network in the Brazilian Amazon through a model that integrates the levels of socioeconomic organization of municipalities and their interrelationships, as determined through migratory movements. The model of territorial organization combines five components: (i) the hierarchy of central places (poles) established by the concentration of urban specialized services, (ii) the geographical distance between central poles and other centers, (iii) the poles’ populations, (iv) the migratory movements among them, and (v) a socioeconomic dimension index. These components are combined into a gravitational model to produce measures and maps of the socioeconomic municipality network of the Brazilian Amazon. As a result, out of 792 municipalities in the Brazilian Amazon, 9 were classified as macro-poles, 29 were classified as meso-poles and 48 as micro-poles. The areas of influence of these poles were determined according to the three hierarchy levels. The Amazon region network comprises a nested spatial pattern of municipalities not constrained by the state boundaries. Socioeconomic space and population movements influence the mobility of the deforestation frontier. This analysis provides insights to predict deforestation as well as to guide formulation of sustainable development policies suitable for each region's specificity.     

International cooperation in conserving biological diversity: a world strategy,international convention,and framework for action

Stimulated by the growing awareness of deforestation at all latitudes, the loss of species, declines in several fisheries, pollution, and other environmental threats, governments, citizen groups, academics, and indigenous peoples have been actively seeking ways to reverse current trends of impoverishment and achieve sustainable development. This paper considers the problems which confront managers of protected areas and proposes a six-point agenda for management based upon improved international policies, funding initiatives and other support mechanisms.     

Avian ecological succession in the Amazon: A long‐term case study following experimental deforestation

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Post-Crackdown Effectiveness of Field-Based Forest Law Enforcement in the Brazilian Amazon

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.     

Intensification of cattle ranching production systems: socioeconomic and environmental synergies and risks in Brazil

Intensification of Brazilian cattle ranching systems has attracted both national and international attention due to its direct relation with Amazon deforestation on the one hand and increasing demand of the global population for meat on the other. Since Brazilian cattle ranching is predominantly pasture-based, we particularly focus on pasture management. We summarize the most recurrent opportunities and risks associated with pasture intensification that are brought up within scientific and political dialogues, and discuss them within the Brazilian context. We argue that sustainable intensification of pasturelands in Brazil is a viable way to increase agricultural output while simultaneously sparing land for nature. Since environmental degradation is often associated with low-yield extensive systems in Brazil, it is possible to obtain higher yields, while reversing degradation, by adopting practices like rotational grazing, incorporation of legumes and integrated crop-livestock-forestry systems. Technical assistance is however essential, particularly for small- and medium-scale farmers. Sound complementary policies and good governance must accompany these measures so that a ‘rebound effect’ does not lead to increased deforestation and other adverse social and environmental impacts. It is also important that animal welfare is not compromised. Although the discussion is presented with respect to Brazil, some aspects are relevant to other developing countries.     

Interactions among Amazon land use, forests and climate: prospects for a near-term forest tipping point

Some model experiments predict a large-scale substitution of Amazon forest by savannah-like vegetation by the end of the twenty-first century. Expanding global demands for biofuels and grains, positive feedbacks in the Amazon forest fire regime and drought may drive a faster process of forest degradation that could lead to a near-term forest dieback. Rising worldwide demands for biofuel and meat are creating powerful new incentives for agro-industrial expansion into Amazon forest regions. Forest fires, drought and logging increase susceptibility to further burning while deforestation and smoke can inhibit rainfall, exacerbating fire risk. If sea surface temperature anomalies (such as El Niño episodes) and associated Amazon droughts of the last decade continue into the future, approximately 55% of the forests of the Amazon will be cleared, logged, damaged by drought or burned over the next 20 years, emitting 15–26 Pg of carbon to the atmosphere. Several important trends could prevent a near-term dieback. As fire-sensitive investments accumulate in the landscape, property holders use less fire and invest more in fire control. Commodity markets are demanding higher environmental performance from farmers and cattle ranchers. Protected areas have been established in the pathway of expanding agricultural frontiers. Finally, emerging carbon market incentives for reductions in deforestation could support these trends.     

Predictive Modelling of Contagious Deforestation in the Brazilian Amazon

Tropical forests are diminishing in extent due primarily to the rapid expansion of agriculture, but the future magnitude and geographical distribution of future tropical deforestation is uncertain. Here, we introduce a dynamic and spatially-explicit model of deforestation that predicts the potential magnitude and spatial pattern of Amazon deforestation. Our model differs from previous models in three ways: (1) it is probabilistic and quantifies uncertainty around predictions and parameters; (2) the overall deforestation rate emerges “bottom up”, as the sum of local-scale deforestation driven by local processes; and (3) deforestation is contagious, such that local deforestation rate increases through time if adjacent locations are deforested. For the scenarios evaluated–pre- and post-PPCDAM (“Plano de Ação para Proteção e Controle do Desmatamento na Amazônia”)–the parameter estimates confirmed that forests near roads and already deforested areas are significantly more likely to be deforested in the near future and less likely in protected areas. Validation tests showed that our model correctly predicted the magnitude and spatial pattern of deforestation that accumulates over time, but that there is very high uncertainty surrounding the exact sequence in which pixels are deforested. The model predicts that under pre-PPCDAM (assuming no change in parameter values due to, for example, changes in government policy), annual deforestation rates would halve between 2050 compared to 2002, although this partly reflects reliance on a static map of the road network. Consistent with other models, under the pre-PPCDAM scenario, states in the south and east of the Brazilian Amazon have a high predicted probability of losing nearly all forest outside of protected areas by 2050. This pattern is less strong in the post-PPCDAM scenario. Contagious spread along roads and through areas lacking formal protection could allow deforestation to reach the core, which is currently experiencing low deforestation rates due to its isolation.     

Forest transition in an ecologically important region: Patterns and causes for landscape dynamics in the Niger Delta

The influence of human related actives such as oil and gas exploration, intensified logging of trees and over exploitation of forest resources for food, have negatively impacted the once flourishing and ecologically diverse forest system of the Niger Delta region in Nigeria. Relevant information on the transitional changes of forested landscapes in the delta is poor compared to other tropical forests such as the Brazilian and Columbian Amazonian forest where numerous research studies have been conducted. Consequently, this study aimed at investigating the spatial extent and rates of forest transition in the Niger Delta region taking into consideration the patterns, causes and implications of the landscape dynamics. The study determined the spatial extent and rates of forest transition in the study area using remotely sensed data from 1986 and 2007. The results indicated that the spatial extent of deforestation, unchanged forest cover and afforestation were 1.38, 2.39, and 1.15 million hectares, respectively, while the annual deforestation and afforestation rates were 0.95 and 0.75% which are high compared to other areas in the humid tropics. The annual rate of change in forest cover was determined as ?0.13% indicating an overall reduction in the spatial extent of forest cover for the entire delta. Changes in the spatial structure of forests were investigated using landscape metrics and the results showed there was a substantial increase in forest fragmentation. The variations in population dynamics and poverty indicators between different states of the Niger Delta were unable to explain the observed patterns of forest change. Instead, the authors observed that the main determinants of forest dynamics were the variations in state forest management policies and the influence of the oil and gas industry on the economies of the states. High rates of afforestation were found in states that have limited oil resources and were more economically dependent on forest products, while states with high deforestation rates were found in the main oil-producing parts of the study site. Using the present trend of forest transition dynamics, a 20-year forward simulation was generated using the Markov algorithm. The results concerning forest transition in the study area point to the urgent need for appropriate environmental policy development and implementation for the Niger Delta region.     

The future of the Amazon: new perspectives from climate, ecosystem and social sciences

The potential loss or large-scale degradation of the tropical rainforests has become one of the iconic images of the impacts of twenty-first century environmental change and may be one of our century's most profound legacies. In the Amazon region, the direct threat of deforestation and degradation is now strongly intertwined with an indirect challenge we are just beginning to understand: the possibility of substantial regional drought driven by global climate change. The Amazon region hosts more than half of the world's remaining tropical forests, and some parts have among the greatest concentrations of biodiversity found anywhere on Earth. Overall, the region is estimated to host about a quarter of all global biodiversity. It acts as one of the major 'flywheels' of global climate, transpiring water and generating clouds, affecting atmospheric circulation across continents and hemispheres, and storing substantial reserves of biomass and soil carbon. Hence, the ongoing degradation of Amazonia is a threat to local climate stability and a contributor to the global atmospheric climate change crisis. Conversely, the stabilization of Amazonian deforestation and degradation would be an opportunity for local adaptation to climate change, as well as a potential global contributor towards mitigation of climate change. However, addressing deforestation in the Amazon raises substantial challenges in policy, governance, sustainability and economic science. This paper introduces a theme issue dedicated to a multidisciplinary analysis of these challenges.     

Environmental change and the carbon balance of Amazonian forests

Extreme climatic events and land‐use change are known to influence strongly the current carbon cycle of Amazonia, and have the potential to cause significant global climate impacts. This review intends to evaluate the effects of both climate and anthropogenic perturbations on the carbon balance of the Brazilian Amazon and to understand how they interact with each other. By analysing the outputs of the Intergovernmental Panel for Climate Change (IPCC) Assessment Report 4 (AR4) model ensemble, we demonstrate that Amazonian temperatures and water stress are both likely to increase over the 21st Century. Curbing deforestation in the Brazilian Amazon by 62% in 2010 relative to the 1990s mean decreased the Brazilian Amazon's deforestation contribution to global land use carbon emissions from 17% in the 1990s and early 2000s to 9% by 2010. Carbon sources in Amazonia are likely to be dominated by climatic impacts allied with forest fires (48.3% relative contribution) during extreme droughts. The current net carbon sink (net biome productivity, NBP) of +0.16 (ranging from +0.11 to +0.21) Pg C year^?1 in the Brazilian Amazon, equivalent to 13.3% of global carbon emissions from land‐use change for 2008, can be negated or reversed during drought years [NBP = ?0.06 (?0.31 to +0.01) Pg C year^?1]. Therefore, reducing forest fires, in addition to reducing deforestation, would be an important measure for minimizing future emissions. Conversely, doubling the current area of secondary forests and avoiding additional removal of primary forests would help the Amazonian gross forest sink to offset approximately 42% of global land‐use change emissions. We conclude that a few strategic environmental policy measures are likely to strengthen the Amazonian net carbon sink with global implications. Moreover, these actions could increase the resilience of the net carbon sink to future increases in drought frequency.     

Amazon's vulnerability to climate change heightened by deforestation and man‐made dispersal barriers

Species migrations in response to climate change have already been observed in many taxonomic groups worldwide. However, it remains uncertain if species will be able to keep pace with future climate change. Keeping pace will be especially challenging for tropical lowland rainforests due to their high velocities of climate change combined with high rates of deforestation, which may eliminate potential climate analogs and/or increase the effective distances between analogs by blocking species movements. Here, we calculate the distances between current and future climate analogs under various climate change and deforestation scenarios. Under even the most sanguine of climate change models (IPSL_CM4, A1b emissions scenario), we find that the median distance between areas in the Amazon rainforest and their closest future (2050) climate analog as predicted based on just temperature changes alone is nearly 300 km. If we include precipitation, the median distance increases by over 50% to >475 km. Since deforestation is generally concentrated in the hottest and driest portions of the Amazon, we predict that the habitat loss will have little direct impact on distances between climate analogs. If, however, deforested areas also act as a barrier to species movements, nearly 30% or 55% of the Amazon will effectively have no climate analogs anywhere in tropical South America under projections of reduced or Business‐As‐Usual deforestation, respectively. These ‘disappearing climates’ will be concentrated primarily in the southeastern Amazon. Consequently, we predict that several Amazonian ecoregions will have no areas with future climate analogs, greatly increasing the vulnerability of any populations or species specialized on these conditions. These results highlight the importance of including multiple climatic factors and human land‐use in predicting the effects of climate change, as well as the daunting challenges that Amazonian diversity faces in the near future.