Open AccessAboveground carbon emissions from gold mining in the Peruvian Amazon
Author(s) -
Ovidiu Csillik,
Gregory P. Asner
Publication year - 2020
Publication title -
environmental research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.37
H-Index - 124
ISSN - 1748-9326
DOI - 10.1088/1748-9326/ab639c
Subject(s) - deforestation (computer science) , greenhouse gas , environmental science , amazon rainforest , gold mining , carbon sequestration , carbon fibers , lidar , biodiversity , reducing emissions from deforestation and forest degradation , climate change , agroforestry , carbon stock , remote sensing , geography , carbon dioxide , ecology , chemistry , materials science , composite number , computer science , composite material , biology , programming language
In the Peruvian Amazon, high biodiversity tropical forest is underlain by gold-enriched subsurface alluvium deposited from the Andes, which has generated a clash between short-term earnings for miners and long-term environmental damage. Tropical forests sequester important amounts of carbon, but deforestation and forest degradation continue to spread in Madre de Dios, releasing carbon to the atmosphere. Updated spatially explicit quantification of aboveground carbon emissions caused by gold mining is needed to further motivate conservation efforts and to understand the effects of illegal mining on greenhouse gases. We used satellite remote sensing, airborne LiDAR, and deep learning models to create high-resolution, spatially explicit estimates of aboveground carbon stocks and emissions from gold mining in 2017 and 2018. For an area of ∼750 000 ha, we found high variations in aboveground carbon density (ACD) with mean ACD of 84.6 (±36.4 standard deviation) Mg C ha −1 and 83.9 (±36.0) Mg C ha −1 for 2017 and 2018, respectively. An alarming 1.12 Tg C of emissions occurred in a single year affecting 23,613 hectares, including in protected zones and their ecological buffers. Our methods and findings are preparatory steps for the creation of an automated, high-resolution forest carbon emission monitoring system that will track near real-time changes and will support actions to reduce the environmental impacts of gold mining and other destructive forest activities.