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3.
Science ; 379(6630): eabp8622, 2023 01 27.
Article in English | MEDLINE | ID: mdl-36701452

ABSTRACT

Approximately 2.5 × 106 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year-1), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year-1). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest.


Subject(s)
Carbon , Conservation of Natural Resources , Rainforest , Biodiversity , Carbon Cycle , Brazil
4.
Glob Chang Biol ; 26(2): 319-321, 2020 02.
Article in English | MEDLINE | ID: mdl-31729092

ABSTRACT

This article clarifies the different types of fire in the Amazon, their different drivers and the positive feedbacks that can lead to more fires in the region. It then explores evidence regarding the peak in active fire detections in August 2019, showing that these were linked to the highest levels of deforestation since 2008. Finally, we examine the solutions needed to reduce the prevalence of uncontrolled or illegal fire in the Brazilian Amazon.


Subject(s)
Conservation of Natural Resources , Trees , Brazil
5.
PLoS One ; 11(2): e0149292, 2016.
Article in English | MEDLINE | ID: mdl-26886207

ABSTRACT

Tropical forests are experiencing a growing fire problem driven by climatic change, agricultural expansion and forest degradation. Protected areas are an important feature of forest protection strategies, and sustainable use reserves (SURs) may be reducing fire prevalence since they promote sustainable livelihoods and resource management. However, the use of fire in swidden agriculture, and other forms of land management, may be undermining the effectiveness of SURs in meeting their conservation and sustainable development goals. We analyse MODIS derived hot pixels, TRMM rainfall data, Terra-Class land cover data, socio-ecological data from the Brazilian agro-census and the spatial extent of rivers and roads to evaluate whether the designation of SURs reduces fire occurrence in the Brazilian Amazon. Specifically, we ask (1) a. Is SUR location (i.e., de facto) or (1) b. designation (i.e. de jure) the driving factor affecting performance in terms of the spatial density of fires?, and (2), Does SUR creation affect fire management (i.e., the timing of fires in relation to previous rainfall)? We demonstrate that pre-protection baselines are crucial for understanding reserve performance. We show that reserve creation had no discernible impact on fire density, and that fires were less prevalent in SURs due to their characteristics of sparser human settlement and remoteness, rather than their status de jure. In addition, the timing of fires in relation to rainfall, indicative of local fire management and adherence to environmental law, did not improve following SUR creation. These results challenge the notion that SURs promote environmentally sensitive fire-management, and suggest that SURs in Amazonia will require special attention if they are to curtail future accidental wildfires, particularly as plans to expand the road infrastructure throughout the region are realised. Greater investment to support improved fire management by farmers living in reserves, in addition to other fire users, will be necessary to help ameliorate these threats.


Subject(s)
Conservation of Natural Resources , Fires/prevention & control , Humidity , Tropical Climate , Brazil , Geography , Humans , Population Density , Rain , Spatio-Temporal Analysis
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