Willcock, S. orcid.org/0000-0001-9534-9114, Cooper, G.S. orcid.org/0000-0001-6268-6608, Addy, J. et al. (1 more author) (2023) Earlier collapse of Anthropocene ecosystems driven by multiple faster and noisier drivers. Nature Sustainability, 6 (11). pp. 1331-1342. ISSN 2398-9629
Abstract
A major concern for the world’s ecosystems is the possibility of collapse, where landscapes and the societies they support change abruptly. Accelerating stress levels, increasing frequencies of extreme events and strengthening intersystem connections suggest that conventional modelling approaches based on incremental changes in a single stress may provide poor estimates of the impact of climate and human activities on ecosystems. We conduct experiments on four models that simulate abrupt changes in the Chilika lagoon fishery, the Easter Island community, forest dieback and lake water quality—representing ecosystems with a range of anthropogenic interactions. Collapses occur sooner under increasing levels of primary stress but additional stresses and/or the inclusion of noise in all four models bring the collapses substantially closer to today by ~38–81%. We discuss the implications for further research and the need for humanity to be vigilant for signs that ecosystems are degrading even more rapidly than previously thought.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Climate-change ecology; Computer modelling; Geography; Projection and prediction |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Geography (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 23 Jun 2023 13:31 |
Last Modified: | 22 Nov 2023 17:24 |
Status: | Published |
Publisher: | Springer Science and Business Media LLC |
Refereed: | Yes |
Identification Number: | 10.1038/s41893-023-01157-x |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:200848 |