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• W2562603121 abstract "Although the Amazon rainforest houses much of Earth's biodiversity and plays a major role in the global carbon budget, estimates of tree biodiversity originate from fewer than 1,000 forest inventory plots, and estimates of carbon dynamics are derived from fewer than 200 recensus plots. It is well documented that the pre-European inhabitants of Amazonia actively transformed and modified the forest in many regions before their population collapse around 1491 AD; however, the impacts of these ancient disturbances remain entirely unaccounted for in the many highly influential studies using Amazonian forest plots. Here we examine whether Amazonian forest inventory plot locations are spatially biased toward areas with high probability of ancient human impacts. Our analyses reveal that forest inventory plots, and especially forest recensus plots, in all regions of Amazonia are located disproportionately near archaeological evidence and in areas likely to have ancient human impacts. Furthermore, regions of the Amazon that are relatively oversampled with inventory plots also contain the highest values of predicted ancient human impacts. Given the long lifespan of Amazonian trees, many forest inventory and recensus sites may still be recovering from past disturbances, potentially skewing our interpretations of forest dynamics and our understanding of how these forests are responding to global change. Empirical data on the human history of forest inventory sites are crucial for determining how past disturbances affect modern patterns of forest composition and carbon flux in Amazonian forests." @default.
• W2562603121 created "2017-01-06" @default.
• W2562603121 creator A5001280108 @default.
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• W2562603121 date "2017-01-03" @default.
• W2562603121 modified "2023-10-12" @default.
• W2562603121 title "Ancient human disturbances may be skewing our understanding of Amazonian forests" @default.
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• W2562603121 doi "https://doi.org/10.1073/pnas.1614577114" @default.
• W2562603121 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5255623" @default.
• W2562603121 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28049821" @default.
• W2562603121 hasPublicationYear "2017" @default.
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