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  Understanding the weather signal in national crop-yield variability

Frieler, K., Schauberger, B., Arneth, A., Balkovič, J., Chryssanthacopoulos, J., Deryng, D., Elliott, J., Folberth, C., Khabarov, N., Müller, C., Olin, S., Pugh, T. A. M., Schaphoff, S., Schewe, J., Schmid, E., Warszawski, L., Levermann, A. (2017): Understanding the weather signal in national crop-yield variability. - Earth's Future, 5, 6, 605-616.
https://doi.org/10.1002/2016EF000525

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Frieler, Katja1, Autor              
Schauberger, Bernhard1, Autor              
Arneth, Almut2, Autor
Balkovič, Juraj2, Autor
Chryssanthacopoulos, James2, Autor
Deryng, Delphine2, Autor
Elliott, Joshua2, Autor
Folberth, Christian2, Autor
Khabarov, Nikolay2, Autor
Müller, Christoph1, Autor              
Olin, Stefan2, Autor
Pugh, Thomas A. M.2, Autor
Schaphoff, Sibyll1, Autor              
Schewe, Jacob1, Autor              
Schmid, Erwin2, Autor
Warszawski, Lila1, Autor              
Levermann, Anders1, Autor              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Zusammenfassung: Year‐to‐year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather‐induced crop‐yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state‐of‐the‐art, process‐based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop‐yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process‐based crop models not only account for weather influences on crop yields, but also provide options to represent human‐management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.

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 Datum: 2017
 Publikationsstatus: Final veröffentlicht
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 Identifikatoren: DOI: 10.1002/2016EF000525
PIKDOMAIN: Climate Impacts & Vulnerabilities - Research Domain II
PIKDOMAIN: Earth System Analysis - Research Domain I
PIKDOMAIN: Sustainable Solutions - Research Domain III
eDoc: 7629
Working Group: Earth System Model Development
Working Group: Terrestrial Safe Operating Space
Working Group: Land Use and Resilience
Working Group: Impacts of Climate Change on Human Population Dynamics
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Titel: Earth's Future
Genre der Quelle: Zeitschrift, SCI, Scopus, p3, oa
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Seiten: - Band / Heft: 5 (6) Artikelnummer: - Start- / Endseite: 605 - 616 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/170925