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Lenton TM, Abrams JF, Bartsch A, Bathiany S, Boulton CA, Buxton JE, Conversi A, Cunliffe AM, Hebden S, Lavergne T, Poulter B, Shepherd A, Smith T, Swingedouw D, Winkelmann R, Boers N. Publisher Correction: Remotely sensing potential climate change tipping points across scales. Nat Commun 2024; 15:1917. [PMID: 38429286 PMCID: PMC10907352 DOI: 10.1038/s41467-024-45881-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2024] Open
Affiliation(s)
| | - Jesse F Abrams
- Global Systems Institute, University of Exeter, Exeter, UK
| | - Annett Bartsch
- b.geos GmbH, Industriestrasse 1A, 2100, Korneuburg, Austria
- Austrian Polar Research Institute, Vienna, Austria
| | - Sebastian Bathiany
- Earth System Modelling, School of Engineering & Design, Technical University of Munich, Munich, Germany
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
| | | | | | - Alessandra Conversi
- National Research Council of Italy, ISMAR-Lerici, Forte Santa Teresa, Loc. Pozzuolo, 19032, Lerici (SP), Italy
| | | | - Sophie Hebden
- Future Earth Secretariat, Stockholm, Sweden
- European Space Agency, ECSAT, Harwell, Oxfordshire, UK
| | | | | | - Andrew Shepherd
- Department of Geography and Environmental Sciences, Northumbria University, Newcastle, UK
| | - Taylor Smith
- Institute of Geosciences, University of Potsdam, Potsdam, Germany
| | - Didier Swingedouw
- University of Bordeaux, CNRS, Bordeaux INP, EPOC, UMR 5805, 33600, Pessac, France
| | | | - Niklas Boers
- Global Systems Institute, University of Exeter, Exeter, UK
- Earth System Modelling, School of Engineering & Design, Technical University of Munich, Munich, Germany
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
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Lenton TM, Abrams JF, Bartsch A, Bathiany S, Boulton CA, Buxton JE, Conversi A, Cunliffe AM, Hebden S, Lavergne T, Poulter B, Shepherd A, Smith T, Swingedouw D, Winkelmann R, Boers N. Remotely sensing potential climate change tipping points across scales. Nat Commun 2024; 15:343. [PMID: 38184618 PMCID: PMC10771461 DOI: 10.1038/s41467-023-44609-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 12/18/2023] [Indexed: 01/08/2024] Open
Abstract
Potential climate tipping points pose a growing risk for societies, and policy is calling for improved anticipation of them. Satellite remote sensing can play a unique role in identifying and anticipating tipping phenomena across scales. Where satellite records are too short for temporal early warning of tipping points, complementary spatial indicators can leverage the exceptional spatial-temporal coverage of remotely sensed data to detect changing resilience of vulnerable systems. Combining Earth observation with Earth system models can improve process-based understanding of tipping points, their interactions, and potential tipping cascades. Such fine-resolution sensing can support climate tipping point risk management across scales.
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Affiliation(s)
| | - Jesse F Abrams
- Global Systems Institute, University of Exeter, Exeter, UK
| | - Annett Bartsch
- b.geos GmbH, Industriestrasse 1A, 2100, Korneuburg, Austria
- Austrian Polar Research Institute, Vienna, Austria
| | - Sebastian Bathiany
- Earth System Modelling, School of Engineering & Design, Technical University of Munich, Munich, Germany
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
| | | | | | - Alessandra Conversi
- National Research Council of Italy, ISMAR-Lerici, Forte Santa Teresa, Loc. Pozzuolo, 19032, Lerici (SP), Italy
| | | | - Sophie Hebden
- Future Earth Secretariat, Stockholm, Sweden
- European Space Agency, ECSAT, Harwell, Oxfordshire, UK
| | | | | | - Andrew Shepherd
- Department of Geography and Environmental Sciences, Northumbria University, Newcastle, UK
| | - Taylor Smith
- Institute of Geosciences, University of Potsdam, Potsdam, Germany
| | - Didier Swingedouw
- University of Bordeaux, CNRS, Bordeaux INP, EPOC, UMR 5805, 33600, Pessac, France
| | | | - Niklas Boers
- Global Systems Institute, University of Exeter, Exeter, UK
- Earth System Modelling, School of Engineering & Design, Technical University of Munich, Munich, Germany
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
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Lenton TM, Buxton JE, Armstrong McKay DI, Abrams JF, Boulton CA, Lees K, Powell TWR, Boers N, Cunliffe AM, Dakos V. A resilience sensing system for the biosphere. Philos Trans R Soc Lond B Biol Sci 2022; 377:20210383. [PMID: 35757883 PMCID: PMC9234808 DOI: 10.1098/rstb.2021.0383] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 02/28/2022] [Indexed: 12/14/2022] Open
Abstract
We are in a climate and ecological emergency, where climate change and direct anthropogenic interference with the biosphere are risking abrupt and/or irreversible changes that threaten our life-support systems. Efforts are underway to increase the resilience of some ecosystems that are under threat, yet collective awareness and action are modest at best. Here, we highlight the potential for a biosphere resilience sensing system to make it easier to see where things are going wrong, and to see whether deliberate efforts to make things better are working. We focus on global resilience sensing of the terrestrial biosphere at high spatial and temporal resolution through satellite remote sensing, utilizing the generic mathematical behaviour of complex systems-loss of resilience corresponds to slower recovery from perturbations, gain of resilience equates to faster recovery. We consider what subset of biosphere resilience remote sensing can monitor, critically reviewing existing studies. Then we present illustrative, global results for vegetation resilience and trends in resilience over the last 20 years, from both satellite data and model simulations. We close by discussing how resilience sensing nested across global, biome-ecoregion, and local ecosystem scales could aid management and governance at these different scales, and identify priorities for further work. This article is part of the theme issue 'Ecological complexity and the biosphere: the next 30 years'.
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Affiliation(s)
| | - Joshua E. Buxton
- Global Systems Institute, University of Exeter, Exeter EX4 4QE, UK
| | - David I. Armstrong McKay
- Global Systems Institute, University of Exeter, Exeter EX4 4QE, UK
- Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden
| | - Jesse F. Abrams
- Global Systems Institute, University of Exeter, Exeter EX4 4QE, UK
- Institute for Data Science and Artificial Intelligence, University of Exeter, Exeter EX4 4QF, UK
| | - Chris A. Boulton
- Global Systems Institute, University of Exeter, Exeter EX4 4QE, UK
| | - Kirsten Lees
- Global Systems Institute, University of Exeter, Exeter EX4 4QE, UK
- Environmental Sustainability Research Centre, University of Derby, Derby DE22 1GB, UK
| | | | - Niklas Boers
- Global Systems Institute, University of Exeter, Exeter EX4 4QE, UK
- School of Engineering and Design, Earth System Modelling, Technical University of Munich, Munich, Germany
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
| | | | - Vasilis Dakos
- ISEM, University of Montpellier, CNRS, EPHE, IRD, Montpellier, France
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Buxton JE, Abrams JF, Boulton CA, Barlow N, Rangel Smith C, Van Stroud S, Lees KJ, Lenton TM. Quantitatively monitoring the resilience of patterned vegetation in the Sahel. Glob Chang Biol 2022; 28:571-587. [PMID: 34653310 DOI: 10.1111/gcb.15939] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 09/25/2021] [Indexed: 06/13/2023]
Abstract
Patterning of vegetation in drylands is a consequence of localized feedback mechanisms. Such feedbacks also determine ecosystem resilience-i.e. the ability to recover from perturbation. Hence, the patterning of vegetation has been hypothesized to be an indicator of resilience, that is, spots are less resilient than labyrinths. Previous studies have made this qualitative link and used models to quantitatively explore it, but few have quantitatively analysed available data to test the hypothesis. Here we provide methods for quantitatively monitoring the resilience of patterned vegetation, applied to 40 sites in the Sahel (a mix of previously identified and new ones). We show that an existing quantification of vegetation patterns in terms of a feature vector metric can effectively distinguish gaps, labyrinths, spots, and a novel category of spot-labyrinths at their maximum extent, whereas NDVI does not. The feature vector pattern metric correlates with mean precipitation. We then explored two approaches to measuring resilience. First we treated the rainy season as a perturbation and examined the subsequent rate of decay of patterns and NDVI as possible measures of resilience. This showed faster decay rates-conventionally interpreted as greater resilience-associated with wetter, more vegetated sites. Second we detrended the seasonal cycle and examined temporal autocorrelation and variance of the residuals as possible measures of resilience. Autocorrelation and variance of our pattern metric increase with declining mean precipitation, consistent with loss of resilience. Thus, drier sites appear less resilient, but we find no significant correlation between the mean or maximum value of the pattern metric (and associated morphological pattern types) and either of our measures of resilience.
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Affiliation(s)
| | - Jesse F Abrams
- Global Systems Institute, University of Exeter, Exeter, UK
- Institute for Data Science and Artificial Intelligence, University of Exeter, Exeter, UK
| | | | | | | | - Samuel Van Stroud
- The Alan Turing Institute, London, UK
- Department of Physics and Astronomy, University College London, London, UK
| | - Kirsten J Lees
- Global Systems Institute, University of Exeter, Exeter, UK
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