Deforestation In Amazon Research Articles

Assessment of deforestation and fire in groups of protected areas of the Amazon

The creation of protected areas was conceived as a global strategy of protecting natural habitats against anthropogenic interventions . This work aimed to evaluate deforestation and fires in protected areas of the Amazon. The groups were: indigenous territories, fully protected conservation units, public sustainable use conservation units, public/private sustainable use conservation units , and non-protected areas. For each group, deforestation and fire density was determined annually in the 2000-2017 period. The most efficient groups to contain deforestation were fully protected conservation units and indigenous territories. The sustainable use conservation units - public/private domain group was ineffective in containing deforestation. Regarding fires, the fully protected conservation units’ group was the most efficient in their containment. The only group that was not effective in containing fire was public/private sustainable use conservation units . The correlation between deforestation and fires was low for protected areas, indicating that fire is mainly related to agropastoral management. In order to more efficiently contain deforestation and fires in Amazon, the creation of fully protected conservation units should be prioritized. Alternatively, more indigenous territories and public sustainable use conservation units could be created; although less effective in containing deforestation and fires, they are nevertheless important for preserving Amazonian sociodiversity.

The effects on deforestation of conditional cash transfers: a study among the Khĩsêtjê Amazonian indigenous people

Smallholders' contribution to Amazonian deforestation is currently increasing. In Indigenous Lands, changes in land uses might be partially due to the unintended effects of anti-poverty strategies, including the Conditional Cash Transfers (CCTs), which may promote the conversion of forests to agricultural lands. Despite that, little is known about whether and how CCTs affect long-term deforestation rates. Thus, this study has assessed whether CCTs influenced long-term land-use changes from forests to agriculture, considering alternative time allocation assumptions (i.e., Time Optimisation and Time Budget). Transfers from the Brazilian Bolsa Família Program to the Khĩsêtjê indigenous people of the Amazon were evaluated with two agent-based models. Results suggest CCTs will likely decrease the area deforested in the long term without changing Khĩsêtjê's population size. When market-purchased products replace local products, people's time allocated to agriculture is expected to fall. The intensity of CCT effects on deforestation varied according to time allocation assumptions, highlighting the importance of considering them carefully to improve the predictions from model simulations.

From Extreme Weather Events to ‘Cascading Vulnerabilities’: Participatory Flood Research Methodologies in Brazil During COVID-19

Extreme weather events are entangled with each other and with other extreme events, such as the COVID-19 pandemic, anti-racist protests, drought, a housing crisis, strikes, or climate emergencies, as well as with more general inadequacies due to national, economic, and political upheavals and accreted vulnerabilities from long-term policies or inactions. Effects of extreme weather events are intensified by ongoing social injustices like poverty and structural racism, a housing deficit, and the consequent informal and unplanned occupation of hazardous areas, such as riverbanks, and areas of previous social-environmental disasters. In the context of Brazil, the ongoing deforestation in the Amazon (agribusiness, mining and illegal wood) provoking droughts and energy shortages in the region creates further vulnerabilities that are felt globally. In this paper, our primary contribution to these inter-connected scenarios is to describe methodological interventions that were made in response to COVID-19, and to show how those changes provided new insights into vulnerability processes of both subjects and researchers. During a larger project (Waterproofing Data), focused on the case study research areas of São Paulo and Acre (Brazil) wherein our wider team conducted flood-risk community research, we were forced to rethink our approach. We moved away from the singularity of the flood event and its impacts toward acknowledging the cascading conditions of social vulnerability (caused by weather, health, social and political conditions). In this paper, we directly address the ‘cascade of vulnerabilities’ that the flood-prone communities already encounter when researchers seek to engage with them. We open new avenues to reconsider citizenship, space, and innovation in terms of the key challenges that our methods encountered when conducting participatory flood research methodologies, particularly during the first phase of the COVID-19 pandemic from March 2020 to November 2021. Through flood research in Brazil, we articulate methodological contributions from the arts, humanities, and social sciences for more realistic, just, and caring research practices within and about weather in the context of ‘slow violence’ [Nixon, R (2013). Slow Violence and the Environmentalism of the Poor. Cambridge, MA: Harvard UP].

Peak fires in the Amazon worry actions against climate change

Deforestation in the Amazon is (or should be) one of the most important topics in the political debate of the Brazilian elections , this year 2022. The subject increasingly worries the country's public opinion and the international media. In this post, we will analyze the current situation of fires and deforestation in Brazilian biomes, with emphasis on the Amazon, as well as its relationship with the climate change process.

Logging intensity affects growth and lifespan trajectories for pioneer species in Central Amazonia

Management of tropical forest in the form of timber harvesting is a viable alternative to deforestation in Amazonia. Nevertheless, a significant challenge for timber management in the Amazon is the maintenance or establishment of commercial timber species, after logging operations are completed. This is because fast-growing non-commercial pioneer species outcompete the slower growing timber species. To determine the challenges posed to commercial species in the context of the cutting cycle in the Brazilian Amazon of 25–35 years, growth and cumulative survival rates of six abundant pioneer species were assessed. This was accomplished with 30 years of growth data from permanent plots established in the Central Amazon in the 1980′s and logged in 1987 and 1988 at various intensities. In terms of relative growth rates, pioneer species dominated the post-logging site by 2 to 5 times, when compared to commercial species, throughout the evaluation period. This was regardless of the various logging intensities of 5, 8 or 16 trees harvested per hectare. Two commercial pioneer species, Jacaranda copaia and Simarouba amara, presented rapid growth rates similar to non-commercial pioneer species. Three pioneer species survived beyond 30 years to continue into a potential 2nd cutting cycle. Therefore, to maintain or establish commercial timber species while there is a continued and expanding site occupancy of non-commercial pioneer species after logging presents numerous challenges for sustainable forest management.

Assessment of the effect of landowner type on deforestation in the Brazilian Legal Amazon using remote sensing data

SummaryThe Brazilian Legal Amazon contains important reservoirs of forest that are threatened by stakeholders’ behaviour. The Cadastro Ambiental Rural (CAR; Rural Environmental Registry) database was used to define the limits and classes of landowner according to private property size. For each class, we identified the annual forest-cover/cover-loss profile at 2-year intervals from 2000 to 2020 based on Brazilian Annual Land Use and Land Cover Mapping Project (MapBiomas) and Program for Deforestation Monitoring (PRODES) data. The analysis revealed that very large landowners dominate the CAR-registered area and that deforestation is influenced by landowner type. The cumulative contributions to deforestation were 2 916 245.96, 1 234 216.79, 2 871 400.36, 2 805 058.62 and 2 637 485.60 ha for very large landowners, large landowners, medium landowners, small landowners and very small landowners, respectively. Very large landowners (1.7% of the total number of properties) had more forest on their properties but caused the greatest amount of deforestation in total, often associated with agribusiness. Small and very small landowners were more numerous (21.0% and 68.3% of the total number of properties, respectively), but they owned a small total area and contributed less to total deforestation. Property size and landownership asymmetry should be considered in deforestation control policies and commitments to the Sustainable Development Goals agenda.

Using deep convolutional neural networks to forecast spatial patterns of Amazonian deforestation

Abstract Tropical forests are subject to diverse deforestation pressures while their conservation is essential to achieve global climate goals. Predicting the location of deforestation is challenging due to the complexity of the natural and human systems involved but accurate and timely forecasts could enable effective planning and on‐the‐ground enforcement practices to curb deforestation rates. New computer vision technologies based on deep learning can be applied to the increasing volume of Earth observation data to generate novel insights and make predictions with unprecedented accuracy. Here, we demonstrate the ability of deep convolutional neural networks (CNNs) to learn spatiotemporal patterns of deforestation from a limited set of freely available global data layers, including multispectral satellite imagery, the Hansen maps of annual forest change (2001–2020) and the ALOS PALSAR digital surface model, to forecast deforestation (2021). We designed four model architectures, based on 2D CNNs, 3D CNNs, and Convolutional Long Short‐Term Memory (ConvLSTM) Recurrent Neural Networks (RNNs), to produce spatial maps that indicate the risk to each forested pixel (~30 m) in the landscape of becoming deforested within the next year. They were trained and tested on data from two ~80,000 km2 tropical forest regions in the Southern Peruvian Amazon. The networks could predict the location of future forest loss to a high degree of accuracy (F1 = 0.58–0.71). Our best performing model (3D CNN) had the highest pixel‐wise accuracy (F1 = 0.71) when validated on 2020 forest loss (2014–2019 training). Visual interpretation of the mapped forecasts indicated that the network could automatically discern the drivers of forest loss from the input data. For example, pixels around new access routes (e.g. roads) were assigned high risk, whereas this was not the case for recent, concentrated natural loss events (e.g. remote landslides). Convolutional neural networks can harness limited time‐series data to predict near‐future deforestation patterns, an important step in harnessing the growing volume of satellite remote sensing data to curb global deforestation. The modelling framework can be readily applied to any tropical forest location and used by governments and conservation organisations to prevent deforestation and plan protected areas.

Re-MEDIAting distant impacts - how Western media make sense of deforestation in different Brazilian biomes

ABSTRACT Brazil plays a central role in Western depictions of and narratives on tropical deforestation. In this contribution, we gather a large text corpus from Western media outlets with articles on deforestation in the Brazilian Amazon and Cerrado biomes. The sources include outlets from Europe, the US, Canada and Australia and span a time period from the late 1980s to 2020. Leveraging several text-mining approaches, such as topic modeling and automated narrative network analysis, we disentangle the way that Western media have tried to make sense of deforestation in the Amazon and the Cerrado biomes. We show that the former has received disproportionately more news coverage, specifically in times of international concern over the Brazilian government’s commitment to tackle deforestation. Further, Western media frequently report on the struggles of indigenous populations in the Amazon, often following an essentialist depiction of these communities, while in the case of the Cerrado, traditional populations are hardly mentioned at all. Our findings provide a methodologically innovative and empirically grounded case for the often raised concern over a relative invisibility of the Cerrado biome and its traditional populations, which may help explain observed disparities in governance interventions.

Biases and limitations of Global Forest Change and author-generated land cover maps in detecting deforestation in the Amazon.

Studying land use change in protected areas (PAs) located in tropical forests is a major conservation priority due to high conservation value (e.g., species richness and carbon storage) here, coupled with generally high deforestation rates. Land use change researchers use a variety of land cover products to track deforestation trends, including maps they produce themselves and readily available products, such as the Global Forest Change (GFC) dataset. However, all land cover maps should be critically assessed for limitations and biases to accurately communicate and interpret results. In this study, we assess deforestation in PA complexes located in agricultural frontiers in the Amazon Basin. We studied three specific sites: Amboró and Carrasco National Parks in Bolivia, Jamanxim National Forest in Brazil, and Tambopata National Reserve and Bahuaja-Sonene National Park in Peru. Within and in 20km buffer areas around each complex, we generated land cover maps using composites of Landsat imagery and supervised classification, and compared deforestation trends to data from the GFC dataset. We then performed a dissimilarity analysis to explore the discrepancies between the two remote sensing products. Both the GFC and our supervised classification showed that deforestation rates were higher in the 20km buffer than inside the PAs and that Jamanxim National Forest had the highest deforestation rate of the PAs we studied. However, GFC maps showed consistently higher rates of deforestation than our maps. Through a dissimilarity analysis, we found that many of the inconsistencies between these datasets arise from different treatment of mixed pixels or different parameters in map creation (for example, GFC does not detect reforestation after 2012). We found that our maps underestimated deforestation while GFC overestimated deforestation, and that true deforestation rates likely fall between our two estimates. We encourage users to consider limitations and biases when using or interpreting our maps, which we make publicly available, and GFC’s maps.

The Amazon Epiphyte Network: A First Glimpse Into Continental-Scale Patterns of Amazonian Vascular Epiphyte Assemblages

Epiphytes are still an understudied plant group in Amazonia. The aim of this study was to identify distributional patterns and conservation priorities for vascular epiphyte assemblages (VEA) across Amazonia. We compiled the largest Amazonian epiphyte plot database to date, through a multinational collaborative effort of 22 researchers and 32 field sites located across four Amazonian countries – the Amazonian Epiphyte Network (AEN). We addressed the following continental-scale questions by utilizing the AEN database comprising 96,448 epiphyte individuals, belonging to 518 vascular taxa, and growing on 10,907 tree individuals (phorophytes). Our objectives here are, first, to present a qualitative evaluation of the geographic distribution of the study sites and highlight regional lacunae as priorities for future quantitative inventories. Second, to present the floristic patterns for Amazonia-wide VEA and third, to combine multivariate analyses and rank abundance curves, controlled by major Amazonian habitat types, to determine how VEA vary geographically and ecologically based on major Amazonian habitat types. Three of the most striking patterns found are that: (1) VEA are spatially structured as floristic similarity decays with geographic distance; (2) a core group of 22 oligarchic taxa account for more than a half of all individuals; and (3) extensive floristic sampling gaps still exist, mainly across the highly threatened southern Amazonian deforestation belt. This work represents a first step toward unveiling distributional pattern of Amazonian VEA, which is important to guide future questions on ecology and species distribution ranges of VEA once the collaborative database grows allowing a clearer view of patterns.

Cutting Down Trees Does not Build Prosperity: On the Continued Decoupling of Amazon Deforestation and Economic Development in 21st Century Brazil

Background and Aims We present evidence examining spatial and temporal patterns in forest cover changes and economic indicators in Brazilian Amazonia. Specifically, we tested two predictions embedded in arguments used by influential interest groups: (i) indicators of economic progress should increase where there is less forest and (ii) areas with most recent deforestation should have increased economic indicators. Methods Complementary methods assessed annual variation in economic indicators across 794 administrative districts (municipalities) covering 4.9 Mkm2 of the Brazilian Amazon from 2002 to 2019. A representative subset of municipalities was used to compare economic and socioeconomic indicators across municipalities with contrasting forest cover. Results Contrasting results between the full and a representative subset of municipalities suggested that municipality-level economic indicators cannot be directly attributed to the loss of natural forests. There was no association between forest loss and economic (average salary) or socioeconomic indicators (existence of sanitation plans and internet connectivity). The economic indicators of municipalities with less than 40% forest cover in 1986 were no different to that of similar municipalities with more than 60% forest cover from 1986 to 2019. Conclusion The evidence contradicted both predictions tested. Reducing forest cover does not appear to directly promote socioeconomic progress. Any localized associations between forest cover and poverty most likely result from other more plausible alternatives including lack of opportunity and a widespread failure to effectively implement and enforce existing policies within the local socioeconomic context. Implications for Conservation Our findings support evidence from across the tropics that shows deforestation does not necessarily generate transformative and equitable food production systems or lead to poverty alleviation.

Science‐based planning can support law enforcement actions to curb deforestation in the Brazilian Amazon

AbstractWhile Brazil publicly committed to reduce deforestation in Amazonia at the 26th Conference of the Parties (COP26), the Brazilian parliament is moving toward weakening environmental laws. Deforestation rates continue ascending, reaching in 2021 the highest value since 2006 (13,235 km2). To overcome this paradox, strategies to curb deforestation are mandatory. The current strategy, “Plano Amazônia 21/22,” prioritizes law enforcement actions to curb illegal deforestation in only 11 Amazonian municipalities. Here, we show that this prioritization is likely to be insufficient since these municipalities account for just 37% of the current deforestation rate. This strategy may also be undermined by the leakage of deforestation actions to unmonitored municipalities. Using a set of spatially explicit datasets integrated into a deforestation‐prediction modeling approach, we propose a science‐based alternative method for ranking deforestation hotspots to be prioritized by law enforcement actions. Our prioritization method accounts for more than 60% of the deforestation, detecting larger deforested areas in both private and public lands, while covering 27% less territory than “Plano Amazônia 21/22.” Optimizing the detection of priority areas for curbing deforestation, as proposed here, is the first step to reducing deforestation rates and comply with the Brazilian legal commitment of 3925 km2 year−1.

What's governance got to do with it? Examining the relationship between governance and deforestation in the Brazilian Amazon.

Deforestation continues at rapid rates despite global conservation efforts. Evidence suggests that governance may play a critical role in influencing deforestation, and while a number of studies have demonstrated a clear relationship between national-level governance and deforestation, much remains to be known about the relative importance of subnational governance to deforestation outcomes. With a focus on the Brazilian Amazon, this study aims to understand the relationship between governance and deforestation at the municipal level. Drawing on the World Bank Worldwide Governance Indicators (WGI) as a guiding conceptual framework, and incorporating the additional dimension of environmental governance, we identified a wide array of publicly available data sources related to governance indicators that we used to select relevant governance variables. We compiled a dataset of 22 municipal-level governance variables covering the 2005-2018 period for 457 municipalities in the Brazilian Amazon. Using an econometric approach, we tested the relationship between governance variables and deforestation rates in a fixed-effects panel regression analysis. We found that municipalities with increasing numbers of agricultural companies tended to have higher rates of deforestation, municipalities with an environmental fund tended to have lower rates of deforestation, and municipalities that had previously elected a female mayor tended to have lower rates of deforestation. These results add to the wider conversation on the role of local-level governance, revealing that certain governance variables may contribute to halting deforestation in the Brazilian Amazon.

National policies encounter municipal realities: A critical analysis of the outcomes of the List of Priority Municipalities in curbing deforestation in the Brazilian Amazon

At the peak of Amazonian deforestation in the mid-2000s, a suite of initiatives to curb deforestation was implemented, narrowing their scopes to particular agents, critical municipalities, and economic activities and supply chains. The List of Priority Municipalities (LPM) launched in 2008 became a central tenet of these efforts. It requires local agents in listed municipalities to individually and collectively reduce deforestation and implement a comprehensive farm-geocoding registry across the municipality. We combine region-wide spatial–temporal land-cover analysis and census data with in-depth fieldwork to examine the LPM policy at regional and municipal levels, discussing the policy's limitations in inducing effective responses across diverse municipalities. At the regional level, our study presents a new historical-geographic categorization and map of 530 Amazonian municipalities. We propose four regional clusters of municipalities according to patterns of deforestation, agricultural activities, demographic and agrarian structures, emancipation history, and socioenvironmental protection. We draw on this analysis to contextualize the trajectories of the 62 listed municipalities within the region’s moving deforestation frontier and discuss why many of the achievements observed locally have not been replicated regionally. At the municipal level, we investigate four case studies in-depth to unveil the factors underlying the LPM policy mixed outcomes. We discuss how local agents’ responses to the LPM policy are context-specific, reflecting their perception of trade-offs between the economic impacts of sanctions, incentives to collaborate, and potential benefits arising from environmental compliance. We detail and discuss how dynamic macro-political and institutional settings altering law enforcement mechanisms and market incentives interact with subnational environmental governance, either facilitating or inhibiting individual and collective actions locally. Finally, we discuss the role of inter-institutional collaboration and coordination among command-and-control policies, market-oriented initiatives, and incentives for local collective actions in triggering incentives for land-use and governance innovations against deforestation, both locally and regionally.

Integrating climate, ecophysiology, and forest cover to estimate the vulnerability of sloths to climate change

AbstractGlobal change imposes multiple challenges on species and, thus, a reliable prediction of current and future vulnerability of species must consider multiple stressors and intrinsic traits of species. Climate, physiology, and forest cover, for example, are required to evaluate threat to thermolabile forest-dependent species, such as sloths (Bradypus spp.; Mammalia: Xenarthra). Here, we estimated future changes in the distribution of three sloth species using a metabolic-hybrid model focused on climate (climatic only, i.e., CO approach) and adding forest cover constraints to distribution of species (climate plus land cover, i.e., CL approach). We used an innovative method to generate estimates of physiological parameters for endotherms, validated with field data. The CF approach predicted a future net expansion of distribution of B. torquatus and B. variegatus, and a future net contraction of distribution of B. tridactylus. The inclusion of forest cover constraints, however, reversed the predictions for B. torquatus, with a predicted net distribution contraction. It also reduced expansion of B. variegatus, although still showing a large net expansion. Thus, B. variegatus is not predicted to be threatened in the future; B. tridactylus emerges as the species most vulnerable to climate change, but with no considerable forest losses, while B. torquatus shows the opposite pattern. Our study highlights the importance of incorporating multiple stressors in predictive models in general. To increase resilience of species to climate change, it is key to control deforestation in the Amazon for B. tridactylus, and to promote reforestation in the Atlantic Forest for B. torquatus.

Maintaining grass coverage increases methane uptake in Amazonian pastures, with a reduction of methanogenic archaea in the rhizosphere

Cattle ranching is the largest driver of deforestation in the Brazilian Amazon. The rainforest-to-pasture conversion affects the methane cycle in upland soils, changing it from sink to source of atmospheric methane. However, it remains unknown if management practices could reduce the impact of land-use on methane cycling. In this work, we evaluated how pasture management can regulate the soil methane cycle either by maintaining continuous grass coverage on pasture soils, or by liming the soil to amend acidity. Methane fluxes from forest and pasture soils were evaluated in moisture-controlled greenhouse experiments with and without grass cover (Urochloa brizantha cv. Marandu) or liming. We also assessed changes in the soil microbial community structure of both bare (bulk) and rhizospheric pasture soils through high throughput sequencing of the 16S rRNA gene, and quantified the methane cycling microbiota by their respective marker genes related to methane generation (mcrA) or oxidation (pmoA). The experiments used soils from eastern and western Amazonia, and concurrent field studies allowed us to confirm greenhouse data. The presence of a grass cover not only increased methane uptake by up to 35% in pasture soils, but also reduced the abundance of the methane-producing community. In the grass rhizosphere this reduction was up to 10-fold. Methane-producing archaea belonged to the genera Methanosarcina sp., Methanocella sp., Methanobacterium sp., and Rice Cluster I. Further, we showed that soil liming to increasing pH compromised the capacity of forest and pasture soils to be a sink for methane, and instead converted formerly methane-consuming forest soils to become methane sources in only 40–80 days. Liming reduced the relative abundance of Beijerinckiacea family in forest soils, which account for many known methanotrophs. Our results demonstrate that pasture management that maintains grass coverage can mitigate soil methane emissions, compared to bare (bulk) pasture soil.

Global health and health promotion processes: an integrative literature review

Global Health is a polysemic expression, but strongly identified as a response to relatively new Health problems and with accelerated growth in the number of cases, which affect the population of both rich and poor countries, such as the emergence of diseases that can be avoided by through exercise practices or physical or sports activities. These diseases can be: Obesity, Diabetes, Cardiopathies, Kidney dysfunctions, Metabolic syndromes, among others. These diseases can also be avoided through food control, social programs such as the Family Health Program, vaccination campaigns, control of health and humanitarian crises. Another factor that has contributed to the imbalance of Global Health is the unrestricted use of natural resources, the growing and unrestrained exploitation of deforestation in the Amazon rainforest, among others. In this sense, this article aims to show in the current literature how the Global Health field is being configured, linked to contemporary globalization processes. Methodologically, the study took place through an integrative view of the literature, with emphasis on scientific productions published from the 2000s onwards. The main results of the article show that Global Health is a field that involves diplomatic relations between countries, role remodeling of agencies considered hegemonic in the 20th century, such as the World Health Organization (WHO), horizontal proximity between countries in the formulation of health policies, participation of actors from civil society and the second sector, recognition of cultural, political and social diversity , and the need to understand the environmental determinants of health. On the other hand, it shows its limits of practical action in contexts marked by neoliberal principles, of minimal state intervention, since investments in Global Health depend on the performance of strong national health systems.

Marked non-compliance with deforestation embargoes in the Brazilian Amazon

Advances in monitoring capacity and strengthened law enforcement have helped to reduce deforestation in the Brazilian Amazon since the early 2000s. Embargoes imposed on the use of deforested land are important instruments for deterring deforestation and enabling forest recovery. However, the extent to which landowners respect embargoes in the Brazilian Amazon is unknown. In this study, we evaluated the current recovery status of embargoes due to deforestation imposed between 2008 and 2017 to conduct the first large-scale assessment of compliance with embargo regulations. We observed forest recovery in only 13.1% (±1.1%) of embargoed polygons, while agriculture and pasture activities were maintained in 86.9% (±1.8%) of embargoed polygons. Thus, landowners openly continue to disrespect environmental legislation in the majority of embargoed areas. We attribute the marked non-compliance observed to limited monitoring of embargoed areas, as environmental agents seldom return to verify the status of embargoed lands after they have been imposed. Recent advances in remote sensing provide low-cost ways to monitor compliance and should form the basis of concerted efforts to ensure that the law is observed and that those responsible for illegal deforestation do not benefit from it.

Taxation aiming environmental protection: The case of Brazilian Rural Land Tax

Ensuring the protection of natural vegetation is a complex challenge that demands a mix of policies. In Brazil, conservation on private land relies on large-scale command-and-control instruments and a few Payments for Ecosystem Services schemes, with taxation playing a minimal role for conservation. The Rural Land Tax (Imposto Territorial Rural, ITR) is a long-established rural tax created to stimulate pasture productivity and promoting social, agricultural, and environmental benefits. Despite the potential for environmental protection, several problems lead to low achievement of ITR's goals. Such problems include low revenue, the difficulty in inspecting declarations, obsolete productivity criteria, and intrinsic environmental distortions. In this work, we analyze current ITR and show that distortions can potentially occur even for properties that adopt deforestation in the Amazon. We also built a spatially explicit model that estimate tax revenue at a property level under different scenarios. Then, we simulate two scenarios: the first corresponds to the existing Law, and the second, to a legal revision we propose to overcome some of its current problems. We found that total tax collection under the current Law should be BRL 5.75 bi per year, almost four times the actual value collected in 2017 (BRL 1.5 bi). The results suggest that the low achievement of goals follows from a large group paying meager tax rates and another group being overpenalized. Results for the proposed revision highlight its inherent potential to address ITR's central challenges, and for a given set of parameters, the revenue under the new formulation could rise to BRL 16.8 bi per year. Our results provide a concrete and science-based alternative for ITR. The application of the proposals of revision we suggest could promote additional environmental protection, consequently strengthening the role of taxation as an instrument for the maintenance of natural vegetation in Brazil.

LULC zoning in the “Madeira river” settlement, legal Amazon, Brazil, before and after implementation of the rural environmental registry (CAR) (2008-2018)

The Madeira River Settlement at Rondônia state is one of the various Federal projects in the Legal Amazon created by the National Institute for Colonization and Agrarian Reform (INCRA). Over the years, fire practices such as slash-and-burn agriculture in the Legal Amazon have been converting the remained forest into pastures and croplands. According to the Brazilian New Forest Code, the rural environmental registry (CAR) became mandatory for monitoring the land occupations, aiming at maintaining forests and legal reserves preserved. The study goal was to analyze socioenvironmental aspects of the land-use and land-cover (LULC) dynamic at Madeira River settlement and its surroundings before and after the registry implementation, between July 2008 and July 2018. Thematic classes and altimetry were overlaid using algebraic operators to create a zoning model with 21 zoning classes. The highest reduction in forested areas was observed in zone six, between SRTM heights of 90 and 100 m, with a forest loss of 1684 ha and forest gain of 638 ha. Transition map results showed the most forest conversion into secondary vegetation of 57.29 km2 in ten years (2008–2018). The occupation increased at zones 11 and 12, showing the movement of settlers into the rainforest, with higher altimetry. The remained settlement lots located at low altimetry in the permanent protection area (PPA) are subject to the risk of flooding. The results also showed that the correlation between lot size and deforestation was not significant, suggesting that a set of social and environmental driver variables may be responsible for both losses and gains in the vegetated area in each lot. Family farming needs assistance for sustainable food production and to avoid soil degradation and abandonment, with an integrated effort of institutions, government and society. The manuscript serves as a regional case study that provides a relevant issue related to public policies concerning Legal Amazonian settlements occupation and deforestation, which may support the monitoring and controlling actions in the region.