The fingerprint of climate trends on European crop yields

Abstract

Europe has experienced a stagnation of some crop yields since the early 1990s as well as statistically significant warming during the growing season. Although it has been argued that these two are causally connected, no previous studies have formally attributed long-term yield trends to a changing climate. Here, we present two statistical tests based on the distinctive spatial pattern of climate change impacts and adaptation, and explore their power under a range of parameter values. We show that statistical power for the identification of climate change impacts is high in many settings, but that power for identifying adaptation is almost always low. Applying these tests to European agriculture, we find evidence that long-term temperature and precipitation trends since 1989 have reduced continent-wide wheat and barley yields by 2.5% and 3.8%, respectively, and have slightly increased maize and sugar beet yields. These averages disguise large heterogeneity across the continent, with regions around the Mediterranean experiencing significant adverse impacts on most crops. This result means that climate trends can account for ∼10% of the stagnation in European wheat and barley yields, with likely explanations for the remainder including changes in agriculture and environmental policies.climate change | agriculture | attribution | Europe | adaptation

Differential climate impacts for policy-relevant limits to global warming: the case of 1.5 °C and 2 °C

“…While high-latitude regions may benefit, median projections for local yields in large parts of the tropical land area are found to be negatively affected already at 1.5 • C. Risks increase substantially, if effects of CO 2 -fertilization are less substantial or counter-acted by other factors such as extreme temperature response, land degradation or nitrogen limitation (Rosenzweig et al, 2014;. In a statistical analysis of climate impacts on wheat and barley yields in Europe, Moore and Lobell (2015) report an overall negative contribution of climatic factors in line with findings of a meta-analysis by Asseng et al (2014), which questions the positive effects projected in our CO 2 -ensemble for this region and further support our approach of singling out noCO 2 -ensemble projections. Given that a 1.5 • C warming might be reached already around 2030, our findings underscore the risks of global crop yield reductions due to climate impacts outlined by Lobell and Tebaldi (2014), while giving further indications for the regional diversity of climate impacts with tropical regions being a hotspot for climate impacts on local agricultural yields .…”

An analysis of ozone damage to historical maize and soybean yields in the United States

“…This has the effect of artificially reducing variance estimates and can overestimate significance. To account for spatial correlation, a clustered bootstrap was used (37,38) as has been done in previous similar studies (39). To determine confidence limits for production loss (Table 1 and Tables S3 and S4 and Dataset S1), all counties within a state for 1 y were treated as a group.…”

The impacts of key adverse weather events on the field‐grown vegetable yield variability in the Czech Republic from 1961 to 2014

“…where Y , T mean, T min, T max, and P are the observed yield, mean temperature, minimum temperature, maximum temperature and precipitation, respectively, the subscript ‘ d ’ denotes the de‐trended values, ‘ L ’ denotes the linear fit, ‘ b ’ denotes the best fit of the yield series by a second‐order polynomial, and ‘*’ denotes the initial de‐trending value. In the third step, to determine whether an individual de‐trended climate variable and/or multiple climate variables (Equations (2)–(5)) have an effect on the observed set of de‐trended crop yields (Equation (1)), we employed the same methodology of the long‐term yield response function to temperature and precipitation changes by the theoretical relationships that were described by Moore and Lobell (): …”

“…Climate science forecasts a shift towards higher temperatures that are punctuated by unpredictable episodes of extreme weather with increasing frequency and intensity globally (Field et al, 2012;Rosenzweig et al, 2014;Gustafson et al, 2016), in central Europe and in the CZ (Brázdil et al, 2012;Huth et al, 2015). These changes could impact crop yields considerably and may require transformations of agricultural systems in the upcoming decades to sustain accessible and good production (Moore and Lobell, 2015). The results of recent studies confirm that climate change is expected to increasingly affect yields, and a statistical analysis of historical crop yield data indicates that it may already be doing so (Gornall et al, 2010;Wilby and Dessai, 2010;Elsgaard et al, 2012;Olesen et al, 2012;Challinor et al, 2014;Lobell et al, 2014;Potopová et al, 2016).…”