A multidisciplinary approach for assessing forest degradation in the Brazilian Amazon

Fires are both a cause and consequence of important changes in the Amazon region. The development and implementation of better fire management practices and firefighting strategies are important steps to reduce the Amazon ecosystems’ degradation and carbon emissions from land-use change in the region. We extended the application of the maximum entropy method (MaxEnt) to model fire occurrence probability in the Brazilian Amazon on a monthly basis during the 2008 and 2010 fire seasons using fire detection data derived from satellite images. Predictor variables included climatic variables, inhabited and uninhabited protected areas and land-use change maps. Model fit was assessed using the area under the curve (AUC) value (threshold-independent analysis), binomial tests and model sensitivity and specificity (threshold-dependent analysis). Both threshold-independent (AUC = 0.919 ± 0.004) and threshold-dependent evaluation indicate satisfactory model performance. Pasture, annual deforestation and secondary vegetation are the most effective variables for predicting the distribution of the occurrence data. Our results show that MaxEnt may become an important tool to guide on-the-ground decisions on fire prevention actions and firefighting planning more effectively and thus to minimise forest degradation and carbon loss from forest fires in Amazonian ecosystems.

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Rapid Recent Deforestation Incursion in a Vulnerable Indigenous Land in the Brazilian Amazon and Fire-Driven Emissions of Fine Particulate Aerosol Pollutants

Forests ◽

10.3390/f11080829 ◽

2020 ◽

Vol 11 (8) ◽

pp. 829

Author(s):

Gabriel de Oliveira ◽

Jing M. Chen ◽

Guilherme A. V. Mataveli ◽

Michel E. D. Chaves ◽

Hugo T. Seixas ◽

...

Keyword(s):

Respiratory Health ◽

Human Health Risk ◽

Agricultural Practices ◽

Brazilian Amazon ◽

Forest Degradation ◽

Climate Feedback ◽

Emission Model ◽

Annual Average ◽

Fire Emissions ◽

Indigenous Land

Deforestation in the Brazilian Amazon is related to the use of fire to remove natural vegetation and install crop cultures or pastures. In this study, we evaluated the relation between deforestation, land-use and land-cover (LULC) drivers and fire emissions in the Apyterewa Indigenous Land, Eastern Brazilian Amazon. In addition to the official Brazilian deforestation data, we used a geographic object-based image analysis (GEOBIA) approach to perform the LULC mapping in the Apyterewa Indigenous Land, and the Brazilian biomass burning emission model with fire radiative power (3BEM_FRP) to estimate emitted particulate matter with a diameter less than 2.5 µm (PM2.5), a primary human health risk. The GEOBIA approach showed a remarkable advancement of deforestation, agreeing with the official deforestation data, and, consequently, the conversion of primary forests to agriculture within the Apyterewa Indigenous Land in the past three years (200 km2), which is clearly associated with an increase in the PM2.5 emissions from fire. Between 2004 and 2016 the annual average emission of PM2.5 was estimated to be 3594 ton year−1, while the most recent interval of 2017–2019 had an average of 6258 ton year−1. This represented an increase of 58% in the annual average of PM2.5 associated with fires for the study period, contributing to respiratory health risks and the air quality crisis in Brazil in late 2019. These results expose an ongoing critical situation of intensifying forest degradation and potential forest collapse, including those due to a savannization forest-climate feedback, within “protected areas” in the Brazilian Amazon. To reverse this scenario, the implementation of sustainable agricultural practices and development of conservation policies to promote forest regrowth in degraded preserves are essential.

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Fire Occurrences and Greenhouse Gas Emissions from Deforestation in the Brazilian Amazon

Remote Sensing ◽

10.3390/rs13030376 ◽

2021 ◽

Vol 13 (3) ◽

pp. 376

Author(s):

Claudia Arantes Silva ◽

Giancarlo Santilli ◽

Edson Eyji Sano ◽

Giovanni Laneve

Keyword(s):

Greenhouse Gas ◽

Ghg Emissions ◽

Brazilian Amazon ◽

Forest Degradation ◽

Primary Forest ◽

Steady Increase ◽

Strong Impact ◽

Ecosystem Degradation ◽

Slash And Burn ◽

Forest Clearing

This work presents the dynamics of fire occurrences, greenhouse gas (GHG) emissions, forest clearing, and degradation in the Brazilian Amazon during the period 2006–2019, which includes the approval of the new Brazilian Forest Code in 2012. The study was carried out in the Brazilian Amazon, Pará State, and the municipality of Novo Progresso (Pará State). The analysis was based on deforestation and fire hotspot datasets issued by the Brazilian Institute for Space Research (INPE), which is produced based on optical and thermal sensors onboard different satellites. Deforestation data was also used to assess GHG emissions from the slash-and-burn practices. The work showed a good correlation between the occurrence of fires in the newly deforested area in the municipality of Novo Progresso and the slash-and-burn practices. The same trend was observed in the Pará State, suggesting a common practice along the deforestation arch. The study indicated positive coefficients of determination of 0.72 and 0.66 between deforestation and fire occurrences for the municipality of Novo Progresso and Pará State, respectively. The increased number of fire occurrences in the primary forest suggests possible ecosystem degradation. Deforestation reported for 2019 surpassed 10,000 km2, which is 48% higher than the previous ten years, with an average of 6760 km2. The steady increase of deforestation in the Brazilian Amazon after 2012 has been a worldwide concern because of the forest loss itself as well as the massive GHG emitted in the Brazilian Amazon. We estimated 295 million tons of net CO2, which is equivalent to 16.4% of the combined emissions of CO2 and CH4 emitted by Brazil in 2019. The correlation of deforestation and fire occurrences reported from satellite images confirmed the slash-and-burn practice and the secondary effect of deforestation, i.e., degradation of primary forest surrounding the deforested areas. Hotspots’ location was deemed to be an important tool to verify forest degradation. The incidence of hotspots in forest area is from 5% to 20% of newly slashed-and-burned areas, which confirms the strong impact of deforestation on ecosystem degradation due to fire occurrences over the Brazilian Amazon.

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Tropical forest degradation in the Brazilian Amazon: relation to fire and land-use change

Advances in forest fire research ◽

10.14195/978-989-26-0884-6_174 ◽

2014 ◽

pp. 1582-1591 ◽

Cited By ~ 1

Author(s):

Ana Cano-Crespo ◽

Paulo J. C. Oliveira ◽

Manoel Cardoso ◽

Kirsten Thonicke

Keyword(s):

Land Use ◽

Land Use Change ◽

Tropical Forest ◽

Brazilian Amazon ◽

Forest Degradation

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Dispersal limitation induces long-term biomass collapse in overhunted Amazonian forests

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1516525113 ◽

2016 ◽

Vol 113 (4) ◽

pp. 892-897 ◽

Cited By ~ 164

Author(s):

Carlos A. Peres ◽

Thaise Emilio ◽

Juliana Schietti ◽

Sylvain J. M. Desmoulière ◽

Taal Levi

Keyword(s):

Tropical Forests ◽

Biological Diversity ◽

Forest Biomass ◽

Dispersal Limitation ◽

Brazilian Amazon ◽

Forest Degradation ◽

Neotropical Tree ◽

Game Hunting ◽

Amazonian Forests

Tropical forests are the global cornerstone of biological diversity, and store 55% of the forest carbon stock globally, yet sustained provisioning of these forest ecosystem services may be threatened by hunting-induced extinctions of plant–animal mutualisms that maintain long-term forest dynamics. Large-bodied Atelinae primates and tapirs in particular offer nonredundant seed-dispersal services for many large-seeded Neotropical tree species, which on average have higher wood density than smaller-seeded and wind-dispersed trees. We used field data and models to project the spatial impact of hunting on large primates by ∼1 million rural households throughout the Brazilian Amazon. We then used a unique baseline dataset on 2,345 1-ha tree plots arrayed across the Brazilian Amazon to model changes in aboveground forest biomass under different scenarios of hunting-induced large-bodied frugivore extirpation. We project that defaunation of the most harvest-sensitive species will lead to losses in aboveground biomass of between 2.5–5.8% on average, with some losses as high as 26.5–37.8%. These findings highlight an urgent need to manage the sustainability of game hunting in both protected and unprotected tropical forests, and place full biodiversity integrity, including populations of large frugivorous vertebrates, firmly in the agenda of reducing emissions from deforestation and forest degradation (REDD+) programs.

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Robust design of multiscale programs to reduce deforestation

Environment and Development Economics ◽

10.1017/s1355770x11000040 ◽

2011 ◽

Vol 16 (4) ◽

pp. 455-478 ◽

Cited By ~ 8

Author(s):

ANDREA CATTANEO

Keyword(s):

Robust Design ◽

Sufficient Conditions ◽

Brazilian Amazon ◽

Forest Degradation ◽

Error Component ◽

Reference Level ◽

Reference Levels ◽

Business As Usual ◽

The Impact ◽

Environmental Outcome

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

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