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  Non‐Linear Climate Change Impacts on Crop Yields May Mislead Stakeholders

Ruane, A. C., Phillips, M., Jägermeyr, J., Müller, C. (2024): Non‐Linear Climate Change Impacts on Crop Yields May Mislead Stakeholders. - Earth's Future, 12, 4, e2023EF003842.
https://doi.org/10.1029/2023EF003842

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Earth s Future - 2024 - Ruane - Non‐Linear Climate Change Impacts on Crop Yields May Mislead Stakeholders.pdf (Verlagsversion), 3MB
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 Urheber:
Ruane, Alex C.1, Autor
Phillips, Meridel1, Autor
Jägermeyr, Jonas1, Autor
Müller, Christoph2, Autor              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: We utilize a global warming level (GWL) lens to evaluate global and regional patterns of agricultural impacts as global surface temperature increases, providing a unique perspective on the experience of stakeholders with continued warming in the 21st century. We analyze crop productivity outputs from 11 crop models simulating 5 climate models under 3 emissions scenarios across 4 crops within the AgMIP/ISIMIP Phase 3 ensemble. We categorize regional productivity changes (without adaptation) into 9 characteristic climate change response patterns, identifying consistent increases and decreases as well as non-linear (peak or dip) responses indicative of inflection points reversing trends as GWLs increase. Many maize regions and pockets of wheat, rice and soybean show peak decrease patterns where initial increases may lull stakeholders into complacency or maladaptation before productivity shifts to losses at higher GWLs. Although the GWL perspective has proven useful in connecting diverse climate models and emissions scenarios, we identify multiple pitfalls that recommend proceeding with caution when applying this approach to climate impacts. Chief among these is that carbon dioxide (CO2) concentrations at any GWL depend on a climate model's transient climate response (TCR). Higher CO2 concentrations generally benefit crop productivity, so this leads to more pessimistic agricultural projections for so-called “hot” models and can skew multi-model ensemble results as models with high TCR are disproportionately likely to reach higher GWLs. While there are strong connections between many climatic impact-drivers and GWLs, vulnerability and exposure components of food system risk are strongly dependent on development pathways.

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Sprache(n): eng - Englisch
 Datum: 2023-05-232024-02-062024-04-122024-04-01
 Publikationsstatus: Final veröffentlicht
 Seiten: 18
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1029/2023EF003842
Organisational keyword: RD2 - Climate Resilience
PIKDOMAIN: RD2 - Climate Resilience
Working Group: Land Use and Resilience
MDB-ID: No data to archive
Research topic keyword: Food & Agriculture
Regional keyword: Global
Model / method: LPJmL
OATYPE: Gold Open Access
 Art des Abschluß: -

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Titel: Earth's Future
Genre der Quelle: Zeitschrift, SCI, Scopus, p3, oa
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 12 (4) Artikelnummer: e2023EF003842 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/170925
Publisher: Wiley