Samuel L. Goldberg, Morgan J. Schmidt, Joshua D. Himmelstein, Michael Heckenberger, Bruna Franchetto, Helena Lima, Jennifer Watling, Bruno Moraes, Wetherbee B. Dorshow, Carlos Fausto, Kumessi Waura, Huke Kuikuro, Taku Wate Kuikuro, Afukaka Kuikuro, J. Taylor Perron
{"title":"Widespread Amazonian dark earth in the Xingu Indigenous Territory","authors":"Samuel L. Goldberg, Morgan J. Schmidt, Joshua D. Himmelstein, Michael Heckenberger, Bruna Franchetto, Helena Lima, Jennifer Watling, Bruno Moraes, Wetherbee B. Dorshow, Carlos Fausto, Kumessi Waura, Huke Kuikuro, Taku Wate Kuikuro, Afukaka Kuikuro, J. Taylor Perron","doi":"10.1038/s41893-024-01399-3","DOIUrl":null,"url":null,"abstract":"Amazonian dark earth (ADE) is highly nutrient- and carbon-rich soil created by past inhabitants of the Amazon. It would be valuable to know the extent of ADE because of its cultural and environmental importance, but systematic efforts to map its distribution and extent are impractical with traditional field methods. We use remote-sensing imagery and a machine-learning classifier with ground-truthed training data to predict the occurrence of ADE across the 26,000 km2 Território Indígena do Xingu (TIX) in the southeastern Amazon region of Brazil. We find widespread ADE across the TIX, well beyond previously studied archaeological sites, occupying at least 3–4% of the land area. We further estimate that the TIX may sequester 9 Mt of carbon within ADE deposits from past human inputs. Our findings show that ancient inhabitants of the TIX substantially modified their environment, highlighting the importance of conserving this natural and cultural resource given threats from climate change and deforestation. Past human land modification in the Amazon has resulted in nutrient- and carbon-rich soil deposits of great cultural and environmental value. A new remote-sensing and machine-learning approach reveals the extent of Amazonian dark earth and its potentially substantial carbon reservoir.","PeriodicalId":19056,"journal":{"name":"Nature Sustainability","volume":"7 10","pages":"1304-1312"},"PeriodicalIF":25.7000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Sustainability","FirstCategoryId":"93","ListUrlMain":"https://www.nature.com/articles/s41893-024-01399-3","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Amazonian dark earth (ADE) is highly nutrient- and carbon-rich soil created by past inhabitants of the Amazon. It would be valuable to know the extent of ADE because of its cultural and environmental importance, but systematic efforts to map its distribution and extent are impractical with traditional field methods. We use remote-sensing imagery and a machine-learning classifier with ground-truthed training data to predict the occurrence of ADE across the 26,000 km2 Território Indígena do Xingu (TIX) in the southeastern Amazon region of Brazil. We find widespread ADE across the TIX, well beyond previously studied archaeological sites, occupying at least 3–4% of the land area. We further estimate that the TIX may sequester 9 Mt of carbon within ADE deposits from past human inputs. Our findings show that ancient inhabitants of the TIX substantially modified their environment, highlighting the importance of conserving this natural and cultural resource given threats from climate change and deforestation. Past human land modification in the Amazon has resulted in nutrient- and carbon-rich soil deposits of great cultural and environmental value. A new remote-sensing and machine-learning approach reveals the extent of Amazonian dark earth and its potentially substantial carbon reservoir.
期刊介绍:
Nature Sustainability aims to facilitate cross-disciplinary dialogues and bring together research fields that contribute to understanding how we organize our lives in a finite world and the impacts of our actions.
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