Pervasive gaps in Amazonian ecological research
Carvalho, Raquel L., Resende, Angelica F., Barlow, Jos, França, Filipe M., Moura, Mario R., Maciel, Rafaella, Alves-Martins, Fernanda, Shutt, Jack, Nunes, Cassio A., Elias, Fernando, Silveira, Juliana M., Stegmann, Lis, Baccaro, Fabricio B., Juen, Leandro, Schietti, Juliana, Aragão, Luiz, Berenguer, Erika, Castello, Leandro, Costa, Flavia R.C., Guedes, Matheus L., Leal, Cecilia G., Lees, Alexander C., Isaac, Victoria, Nascimento, Rodrigo O., Phillips, Oliver L., Schmidt, Fernando Augusto, ter Steege, Hans, Vaz-de-Mello, Fernando, Venticinque, Eduardo M., Vieira, Ima Célia Guimarães, Zuanon, Jansen, The Synergize Consortium, [Laurance, William], [Laurance, Susan], and [Rechetelo, Juliana] (2023) Pervasive gaps in Amazonian ecological research. Current Biology, 33 (16). 3495-3504.e4.
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Abstract
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost.
Item ID: | 82959 |
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Item Type: | Article (Research - C1) |
ISSN: | 1879-0445 |
Keywords: | biodiversity, biological diversity, Brazil, community assessment, conservation science, information deficits, knowledge gap, spatial bias |
Copyright Information: | © 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Additional Information: | William Laurance; Susan Laurance and Juliana Rechetelo are all members of the The Synergize Consortium. |
Date Deposited: | 12 Jun 2024 00:48 |
FoR Codes: | 31 BIOLOGICAL SCIENCES > 3103 Ecology > 310308 Terrestrial ecology @ 100% |
SEO Codes: | 18 ENVIRONMENTAL MANAGEMENT > 1806 Terrestrial systems and management > 180606 Terrestrial biodiversity @ 100% |
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