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      Impact of extreme weather conditions on European crop production in 2018

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          Abstract

          Extreme weather increases the risk of large-scale crop failure. The mechanisms involved are complex and intertwined, hence undermining the identification of simple adaptation levers to help improve the resilience of agricultural production. Based on more than 82 000 yield data reported at the regional level in 17 European countries, we assess how climate affected the yields of nine crop species. Using machine learning models, we analyzed historical yield data since 1901 and then focus on 2018, which has experienced a multiplicity and a diversity of atypical extreme climatic conditions. Machine learning models explain up to 65% of historical yield anomalies. We find that both extremes in temperature and precipitation are associated with negative yield anomalies, but with varying impacts in different parts of Europe. In 2018, Northern and Eastern Europe experienced multiple and simultaneous crop failures—among the highest observed in recent decades. These yield losses were associated with extremely low rainfalls in combination with high temperatures between March and August 2018. However, the higher than usual yields recorded in Southern Europe—caused by favourable spring rainfall conditions—nearly offset the large decrease in Northern European crop production. Our results outline the importance of considering single and compound climate extremes to analyse the causes of yield losses in Europe. We found no clear upward or downward trend in the frequency of extreme yield losses for any of the considered crops between 1990 and 2018.

          This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

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          Global scale climate–crop yield relationships and the impacts of recent warming

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            Climate variation explains a third of global crop yield variability

            Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability.
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              pdp: An R Package for Constructing Partial Dependence Plots

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                Author and article information

                Journal
                Philos Trans R Soc Lond B Biol Sci
                Philos. Trans. R. Soc. Lond., B, Biol. Sci
                RSTB
                royptb
                Philosophical Transactions of the Royal Society B: Biological Sciences
                The Royal Society
                0962-8436
                1471-2970
                26 October 2020
                7 September 2020
                7 September 2020
                : 375
                : 1810 , Theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’ compiled and edited by Wouter Peters, Ana Bastos, Philippe Ciais, Alex Vermeulen and Werner Kutsch
                : 20190510
                Affiliations
                [1 ]CIRAD, UPR HortSys , 34398 Montpellier, France
                [2 ]HortSys, University Montpellier, CIRAD , Montpellier, France
                [3 ]Potsdam Institute for Climate Impact Research (PIK) , 14473 Potsdam, Germany
                [4 ]Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre-Simon Laplace (IPSL) , 91191 Gif sur Yvette, France
                [5 ]Ludwig-Maximilans-Universität Munich , Luisenstrasse 37, 80333 München, Germany
                [6 ]INRAE, AgroParisTech, UMR 211 Agronomie, Université Paris-Saclay , 78850 Thiverval-Grignon, France
                [7 ]CIRED - Centre international de recherche sur l'environnement et le développement , UMR 8568, Nogent-sur-Marne, France
                Author notes

                Electronic supplementary material is available online at https://doi.org/10.6084/m9.figshare.c.5077861.

                Author information
                http://orcid.org/0000-0003-2014-3482
                Article
                rstb20190510
                10.1098/rstb.2019.0510
                7485097
                32892735
                6c0fe8b4-5079-4c2b-9f38-9e2206fc20a8
                © 2020 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : 28 February 2020
                Funding
                Funded by: CLAND;
                Award ID: ANR under the "Investissements d'avenir" program
                Categories
                1001
                204
                44
                Articles
                Research Article
                Custom metadata
                October 26, 2020

                Philosophy of science
                climate extremes,crop yields,drought,yield anomalies,wheat,random forest
                Philosophy of science
                climate extremes, crop yields, drought, yield anomalies, wheat, random forest

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