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1. Combining airborne lidar and acoustic remote sensing to characterize the impacts of Amazon forest degradation

   Rappaport, D.I.; Morton, D.C. (May 2017, Anais do Simpósio Brasileiro de Sensoriamento Remoto)

   Frontier forests in the Brazilian Amazon have been heavily altered by nearly a half-century of deforestation for agriculture and degradation from fire and logging. The long-term effects of forest degradation on habitat structure and habitat use remain poorly understood, largely due to the limitations of traditional field methods for characterizing heterogeneity at relevant spatial and temporal scales. This work demonstrates the opportunity to assess degradation impacts on ecosystem structure and biodiversity at landscape scales (200 km2) by combining airborne lidar and acoustic remote sensing across two municipalities in Mato Grosso, Feliz Natal and Nova Ubiratã. Among degradation classes, our results indicate that repeated fire events have the most destructive legacy for both habitat structure and habitat use. Lidar analyses reveal that repeated fire events can result in a total loss of original canopy trees. Similarly, our acoustic analyses suggest that repeated fires may fundamentally transform animal community composition. The combination of remote sensing approaches bridges the scale gap between ground-based and satellite observations to support a regional-scale investigation into the complex consequences of Amazon forest degradation. 

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

   https://doi.org/10.3390/f11080829  

   de Oliveira, Gabriel; Chen, Jing M.; Mataveli, Guilherme A.; Chaves, Michel E.; Seixas, Hugo T.; Cardozo, Francielle da; Shimabukuro, Yosio E.; He, Liming; Stark, Scott C.; dos Santos, Carlos A. (August 2020, Forests)

   null (Ed.)

   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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3. Intercomparison of Burned Area Products and Its Implication for Carbon Emission Estimations in the Amazon

   https://doi.org/10.3390/rs12233864  

   Pessôa, Ana Carolina; Anderson, Liana O.; Carvalho, Nathália S.; Campanharo, Wesley A.; Junior, Celso H.; Rosan, Thais M.; Reis, João B.; Pereira, Francisca R.; Assis, Mauro; Jacon, Aline D.; et al (December 2020, Remote Sensing)

   Carbon (C) emissions from forest fires in the Amazon during extreme droughts may correspond to more than half of the global emissions resulting from land cover changes. Despite their relevant contribution, forest fire-related C emissions are not directly accounted for within national-level inventories or carbon budgets. A fundamental condition for quantifying these emissions is to have a reliable estimation of the extent and location of land cover types affected by fires. Here, we evaluated the relative performance of four burned area products (TREES, MCD64A1 c6, GABAM, and Fire_cci v5.0), contrasting their estimates of total burned area, and their influence on the fire-related C emissions in the Amazon biome for the year 2015. In addition, we distinguished the burned areas occurring in forests from non-forest areas. The four products presented great divergence in the total burned area and, consequently, total related C emissions. Globally, the TREES product detected the largest amount of burned area (35,559 km2), and consequently it presented the largest estimate of committed carbon emission (45 Tg), followed by MCD64A1, with only 3% less burned area detected, GABAM (28,193 km2) and Fire_cci (14,924 km2). The use of Fire_cci may result in an underestimation of 29.54 ± 3.36 Tg of C emissions in relation to the TREES product. The same pattern was found for non-forest areas. Considering only forest burned areas, GABAM was the product that detected the largest area (8994 km2), followed by TREES (7985 km2), MCD64A1 (7181 km2) and Fire_cci (1745 km2). Regionally, Fire_cci detected 98% less burned area in Acre state in southwest Amazonia than TREES, and approximately 160 times less burned area in forests than GABAM. Thus, we show that global products used interchangeably on a regional scale could significantly underestimate the impacts caused by fire and, consequently, their related carbon emissions. 

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4. Thinner bark increases sensitivity of wetter Amazonian tropical forests to fire

   https://doi.org/10.1111/ele.13409  

   Staver, Ann Carla; Brando, Paulo M.; Barlow, Jos; Morton, Douglas C.; Paine, C. E. Timothy; Malhi, Yadvinder; Araujo Murakami, Alejandro; del Aguila Pasquel, Jhon; Penuelas, ed., Josep (October 2019, Ecology Letters)

   Abstract Understory fires represent an accelerating threat to Amazonian tropical forests and can, during drought, affect larger areas than deforestation itself. These fires kill trees at rates varying from < 10 to c. 90% depending on fire intensity, forest disturbance history and tree functional traits. Here, we examine variation in bark thickness across the Amazon. Bark can protect trees from fires, but it is often assumed to be consistently thin across tropical forests. Here, we show that investment in bark varies, with thicker bark in dry forests and thinner in wetter forests. We also show that thinner bark translated into higher fire‐driven tree mortality in wetter forests, with between 0.67 and 5.86 gigatonnes CO₂lost in Amazon understory fires between 2001 and 2010. Trait‐enabled global vegetation models that explicitly include variation in bark thickness are likely to improve the predictions of fire effects on carbon cycling in tropical forests. 

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5. Quantifying Fire-Induced Surface Climate Changes in the Savanna and Rainforest Biomes of Brazil

   https://doi.org/10.3390/fire6080311  

   De Sales, Fernando; Werner, Zackary; de Souza Ribeiro, João Gilberto (August 2023, Fire)

   This study uses a combined research approach based on remote-sensing and numerical modeling to quantify the effects of burned areas on the surface climate in the two Brazilian biomes most affected by fires: the tropical savanna and the Amazon rainforest. Our estimates indicate that between 2007 and 2020, approximately 6% of the savanna and 2% of the rainforest were burned on average. Non-parametric regressions based on 14-year climate model simulations indicate that latent heat flux decreases on average by approximately 0.17 W m−2 in the savanna and 0.60 W m−2 in the rainforest per each 1 km2 burned, with most of the impacts registered during the onset of the wet season. Sensible and ground heat fluxes are also impacted but at less intensity. Surface air is also warmer and drier, especially over rainforest burned sites. On average, fire reduced gross primary production in the savanna and rainforest by 12% and 10%, respectively, in our experiments. 

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