Galaz García, Carmen, Bagstad, Kenneth J., Brun, Julien, Chaplin-Kramer, Rebecca, Dhu, Trevor, Murray, Nicholas J., Nolan, Connor J., Ricketts, Taylor H., Sosik, Heidi M., Sousa, Daniel, Willard, Geoff, and Halpern, Benjamin S. (2023) The future of ecosystem assessments is automation, collaboration, and artificial intelligence. Environmental Research Letters, 18 (1). 011003.

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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.

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