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  Caring for the future can turn tragedy into comedy for long-term collective action under risk of collapse

Barfuss, W., Donges, J. F., Vasconcelos, V. V., Kurths, J., Levin, S. A. (2020): Caring for the future can turn tragedy into comedy for long-term collective action under risk of collapse. - Proceedings of the National Academy of Sciences of the United States of America (PNAS), 117, 23, 12915-12922.
https://doi.org/10.1073/pnas.1916545117

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Barfuss, Wolfram1, Autor              
Donges, Jonathan Friedemann1, Autor              
Vasconcelos, Vitor V.2, Autor
Kurths, Jürgen1, Autor              
Levin, Simon A.2, Autor
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Zusammenfassung: One of the greatest challenges in addressing global environmental and social problems is achieving cooperation, in which social and environmental processes are increasingly interlinked. Yet, most theoretical studies investigate cooperation within social dilemma settings, using normal form games with effectively only one environmental state. This paper extends the concept of a purely social to a coupled social–ecological dilemma by studying cooperation within stochastic games with multiple environmental states. The particular stochastic game we investigate enables us to study how time preferences influence long-term collective action under risk of collapse. We find that under certain conditions, caring for the future alone can transform this collective action challenge from a tragedy up to a comedy of the commons where cooperation dominates.

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 Datum: 2020-04-212020-05-202020
 Publikationsstatus: Final veröffentlicht
 Seiten: -
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 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: PIKDOMAIN: RD1 - Earth System Analysis
PIKDOMAIN: RD4 - Complexity Science
eDoc: 9017
DOI: 10.1073/pnas.1916545117
MDB-ID: yes - 2951
Research topic keyword: Tipping Elements
Research topic keyword: Planetary Boundaries
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Climate Policy
Model / method: Game Theory
Model / method: Machine Learning
Regional keyword: Global
Organisational keyword: FutureLab - Earth Resilience in the Anthropocene
Organisational keyword: RD1 - Earth System Analysis
Organisational keyword: RD4 - Complexity Science
Working Group: Whole Earth System Analysis
Working Group: Network- and machine-learning-based prediction of extreme events
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Titel: Proceedings of the National Academy of Sciences of the United States of America (PNAS)
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 117 (23) Artikelnummer: - Start- / Endseite: 12915 - 12922 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals410
Publisher: National Academy of Sciences (NAS)