The future of ecosystem assessments is automation, collaboration, and artificial intelligence

dc.contributor.author Galaz García, Carmen
dc.contributor.author Bagstad, Kenneth J
dc.contributor.author Brun, Julien
dc.contributor.author Chaplin-Kramer, Rebecca
dc.contributor.author Dhu, Trevor
dc.contributor.author Murray, Nicholas J
dc.contributor.author Nolan, Connor J
dc.contributor.author Ricketts, Taylor H
dc.contributor.author Sosik, Heidi M
dc.contributor.author Sousa, Daniel
dc.contributor.author Willard, Geoff
dc.contributor.author Halpern, Benjamin S
dc.date.accessioned 2023-07-11T20:00:51Z
dc.date.available 2023-07-11T20:00:51Z
dc.date.issued 2023-01-04
dc.description © The Author(s), 2023. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Galaz García, C., Bagstad, K., Brun, J., Chaplin-Kramer, R., Dhu, T., Murray, N., Nolan, C., Ricketts, T., Sosik, H., Sousa, D., Willard, G., & Halpern, B. The future of ecosystem assessments is automation, collaboration, and artificial intelligence. Environmental Research Letters, 18(1), (2023): 011003, https://doi.org/10.1088/1748-9326/acab19.
dc.description.abstract The world faces unprecedented environmental change, a global biodiversity crisis, and an urgent need for sustainable human development [1]. International and national bodies have set ambitious agendas to help overcome these environmental challenges, such as the United Nations' (UN) Decade on Ecosystem Restoration, the 2030 Agenda for Sustainable Development, and the pending conservation of 30% of U.S. land and ocean by 2030 (30 by 30). Promptly assessing the status of ecosystems worldwide is essential to evaluate whether we are meeting these programs' objectives and to identify where further progress and targeted action are needed. Ecosystem assessments enable necessary understanding of ecological status by synthesizing multiple aspects of ecological change, including relations between people and ecosystems. However, such assessments have major limitations, as they are often infrequent, multi-year projects that are difficult to repeat and have limited in-situ and human data integration.
dc.description.sponsorship This work was supported by a gift from Microsoft (funding code 8-448755-17211-EC417). Heidi M Sosik gratefully acknowledges support from the Simons Foundation (Grant #561126). Support for Kenneth J Bagstad's time was provided by the U.S. Geological Survey's Land Change Science Program.
dc.identifier.citation Galaz García, C., Bagstad, K., Brun, J., Chaplin-Kramer, R., Dhu, T., Murray, N., Nolan, C., Ricketts, T., Sosik, H., Sousa, D., Willard, G., & Halpern, B. (2023). The future of ecosystem assessments is automation, collaboration, and artificial intelligence. Environmental Research Letters, 18(1), 011003.
dc.identifier.doi 10.1088/1748-9326/acab19
dc.identifier.uri https://hdl.handle.net/1912/66422
dc.publisher IOP Publishing
dc.relation.uri https://doi.org/10.1088/1748-9326/acab19
dc.rights Attribution 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ *
dc.title The future of ecosystem assessments is automation, collaboration, and artificial intelligence
dc.type Article
dspace.entity.type Publication
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relation.isAuthorOfPublication.latestForDiscovery af9533ca-3ac1-40c9-97f0-4acba30a0569
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