Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon

The need for accurate information to characterize the evolution of forest cover at the tropical scale is widely recognized, particularly to assess carbon losses from processes of disturbances such as deforestation and forest degradation1. In fact, the contribution of degradation is a key element for REDD+ activities and is presently mostly ignored in national reporting due to the lack of reliable information at such scale. Recently Vancutsem et al.2 produced a dataset at 30m resolution which delineates the tropical moist forest (TMF) cover changes from 1990 to 2019. The use of the Landsat historical time-series at high temporal and spatial resolution allows accurate monitoring of deforestation and degradation, from which the carbon losses from disturbances in TMFs can be estimated. A degradation event is defined here as temporary absence of tree cover (visible within a Landsat pixel during a maximum of three years duration) and includes impacts of fires and logging activities. We quantify the annual losses in above-ground carbon stock associated to degradation and deforestation in TMF over the period 2011-2019 by combining the annual disturbances in forest cover derived from the Landsat archive the pan-tropical map of aboveground live woody biomass density (AGB) from Santoro et al.3 at 100 m. To reduce the local variability within the estimation of AGB values, we apply a moving average filter under the TMF cover for the year 2010.&#160; The carbon loss due to degradation is accounted as full carbon loss within a pixel (like a deforestation). The reason is that logging activities usually remove large trees with higher biomass densities than the average value of the disturbed pixel indicated by the pan-tropical maps. To avoid double counting of carbon removal, deforestation happening after degradation is not accounted as carbon loss. Our results are compared with estimates of previous studies that cover different periods and forest domains: (i) Tyukavina et al.4&#160;provide estimates of carbon loss from deforestation for the period 2000-2012 for all forests (evergreen and deciduous) discriminating natural forests from managed forests, and (ii) Baccini et al.5 provide estimates of carbon loss from deforestation and degradation for the period 2003-2014 for both evergreen and deciduous forests.In a further step, we will analyze the sensitivity of the results to the input AGB values by applying the same approach to other AGB maps (e.g. Baccini et al. 20126). Finally we intend to use Sentinel-2 data (10 m) for monitoring the location and extent of logging activities and burnt areas and further improve the estimates of carbon losses from forest degradation.&#160;1. Achard F, House JI 2015 doi 10.1088/1748-9326/10/10/101002 2. Vancutsem C. et al. 2019 Submitted to Nat. Geoscience 3. Santoro M et al. 2018 doi 10.1594/PANGAEA.894711 4. Tuykavina A et al 2018 http://iopscience.iop.org/1748-9326/10/7/074002 5. Baccini A et al. 2017 doi 10.1126/science.aam5962 6. Baccini A et al. 2012 doi 10.1038/nclimate1354

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Modelling fire probability in the Brazilian Amazon using the maximum entropy method

International Journal of Wildland Fire ◽

10.1071/wf15216 ◽

2016 ◽

Vol 25 (9) ◽

pp. 955 ◽

Cited By ~ 9

Author(s):

Marisa G. Fonseca ◽

Luiz Eduardo O. C. Aragão ◽

André Lima ◽

Yosio E. Shimabukuro ◽

Egidio Arai ◽

...

Keyword(s):

Land Use ◽

Land Use Change ◽

Maximum Entropy ◽

Forest Fires ◽

Maximum Entropy Method ◽

Management Practices ◽

Brazilian Amazon ◽

Forest Degradation ◽

Entropy Method ◽

Monthly Basis

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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Participatory forest carbon assessment in south-eastern Tanzania: experiences, costs and implications for REDD+ initiatives

Oryx ◽

10.1017/s0030605315000174 ◽

2015 ◽

Vol 50 (3) ◽

pp. 523-532 ◽

Cited By ~ 2

Author(s):

Josiah Z. Katani ◽

Irmeli Mustalahti ◽

Kusaga Mukama ◽

Eliakimu Zahabu

Keyword(s):

Anthropogenic Activities ◽

Forest Degradation ◽

Local Communities ◽

Forest Carbon ◽

Large Area ◽

Carbon Loss ◽

Closed Canopy ◽

Baseline Cost ◽

The Cost

AbstractThe aim of this study was to determine the changes in forest carbon in three village forests in Tanzania during 2009–2012 using participatory forest carbon assessment, and to evaluate the capability of the local communities to undertake the assessment, and the costs involved. The results show that forest degradation is caused not only by disturbance as a result of anthropogenic activities; other causes include natural mortality of small trees as a result of canopy closure, and the attraction of wild animals to closed-canopy forests. Thus, mechanisms are required to compensate communities for carbon loss that is beyond their control. However, an increase in the abundance of elephants Loxodonta africana and other fauna should not be considered negatively by local communities and other stakeholders, and the importance of improved biodiversity in the context of carbon stocks should be emphasized by those promoting REDD+ (Reduced Emissions from Deforestation and Forest Degradation). This case study also shows that the cost per ha of USD < 1 for participatory forest carbon assessment is less than that reported for Tanzania and elsewhere (USD 3–5); this is attributed to the large area of forest studied. However, the cost of data analysis and reporting in 2012 (USD 4,519) was significantly higher than the baseline cost (USD 1,793) established in 2009 because of the involvement of external experts.

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A multidisciplinary approach for assessing forest degradation in the Brazilian Amazon

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) ◽

10.1109/igarss.2015.7326175 ◽

2015 ◽

Author(s):

Rosana Cristina Grecchi ◽

Rene Beuchle ◽

Yosio Edemir Shimabukuro ◽

Frederic Achard

Keyword(s):

Multidisciplinary Approach ◽

Brazilian Amazon ◽

Forest Degradation

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