Climate impacts on long-term silage maize yield in Germany

In this study, we examine the impacts of climate change on variations in the long-term mean silage maize yield using a statistical crop model at the county level in Germany. The explanatory variables, which consider sub-seasonal effects, are soil moisture anomalies for June and August and precipitation and temperature for July. Climate projections from five regional climate models (RCMs) are used to simulate soil moisture with the mesoscale Hydrologic Model and force the statistical crop model. The results indicate an average yield reduction of −120 to −1050 (kilogram/hectare)/annum (kg ha−1 a−1) for the period 2021–2050 compared to the baseline period 1971–2000. The multi-model yield decreases between −370 and −3910 kg ha−1 a−1 until the end of the century (2070–2099). The maximum projected mean loss is less than 10% in magnitude of average yields in Germany in 1999–2015. The crop model shows a strong ability to project long-term mean yield changes but is not designed to capture inter-annual variations. Based on the RCM outcomes, July temperature and August soil moisture anomalies are the main factors for the projected yield anomalies. Furthermore, effects such as adaptation and CO2 fertilization are not included in our model. Accounting for these might lead to a slight overall increase in the future silage maize yield of Germany.

[1]  T. Hertel,et al.  New science of climate change impacts on agriculture implies higher social cost of carbon , 2017, Nature Communications.

[2]  W. Schlenker,et al.  Reduced-Form Versus Structural Modeling in Environmental and Resource Economics , 2009 .

[3]  S. Robbins.  Infancy to Maturity , 1943 .

[4]  W. Schlenker,et al.  Empirical studies on agricultural impacts and adaptation , 2014 .

[5]  J. Hansen,et al.  Perception of climate change , 2012, Proceedings of the National Academy of Sciences.

[6]  D. Lobell.  Errors in climate datasets and their effects on statistical crop models , 2013 .

[7]  Frank Wechsung,et al.  Statistical regression models for assessing climate impacts on crop yields: A validation study for winter wheat and silage maize in Germany , 2016 .

[8]  F. Wechsung,et al.  Extending and improving regionalized winter wheat and silage maize yield regression models for Germany: Enhancing the predictive skill by panel definition through cluster analysis , 2016 .

[9]  Thomas W. Hertel,et al.  Economic impacts of climate change on agriculture : a comparison of process-based and statistical yield models , 2017 .

[10]  Luis Samaniego,et al.  Implications of Parameter Uncertainty on Soil Moisture Drought Analysis in Germany , 2013 .

[11]  Maximilian Auffhammer,et al.  Using Weather Data and Climate Model Output in Economic Analyses of Climate Change , 2013, Review of Environmental Economics and Policy.

[12]  W. Michael Hanemann,et al.  The economic impacts of climate change: Evidence from agricultural output and random fluctuations in weather: Comment , 2014 .

[13]  P. Linden,et al.  ENSEMBLES: Climate Change and its Impacts - Summary of research and results from the ENSEMBLES project , 2009 .

[14]  Michael Greenstone,et al.  The Economic Impacts of Climate Change: Evidence from Agricultural Output and Random Fluctuations in Weather: Reply , 2012 .

[15]  A. Wahid,et al.  Heat tolerance in plants: An overview , 2007 .

[16]  Volker Meyer,et al.  The effect of soil moisture anomalies on maize yield in Germany , 2017 .

[17]  R. Naylor,et al.  Future warming increases probability of globally synchronized maize production shocks , 2018, Proceedings of the National Academy of Sciences.

[18]  Hans-Joachim Weigel,et al.  Interactive effects of free-air CO2 enrichment and drought stress on maize growth , 2014 .

[19]  W. Collins,et al.  Global climate projections , 2007 .

[20]  David B. Lobell,et al.  Climate change adaptation in crop production: Beware of illusions , 2014 .

[21]  Michael Greenstone,et al.  The Economic Impacts of Climate Change: Evidence from Agricultural Profits and Random Fluctuations in Weather , 2004 .

[22]  A. Daccache,et al.  Meta-analysis of climate impacts and uncertainty on crop yields in Europe , 2016 .

[23]  D. Lobell,et al.  Projected temperature changes indicate significant increase in interannual variability of U.S. maize yields , 2012, Climatic Change.

[24]  Ram Fishman,et al.  More uneven distributions overturn benefits of higher precipitation for crop yields , 2016 .

[25]  P. Venugopal,et al.  A letter , 2009, Indian journal of urology : IJU : journal of the Urological Society of India.

[26]  T. Sinclair,et al.  Crop Modeling: From Infancy to Maturity , 1996 .

[27]  A. Rogers,et al.  Elevated CO2 effects on plant carbon, nitrogen, and water relations: six important lessons from FACE. , 2009, Journal of experimental botany.

[28]  S. Attinger,et al.  Multiscale parameter regionalization of a grid‐based hydrologic model at the mesoscale , 2010 .

[29]  D. Lobell,et al.  A meta-analysis of crop yield under climate change and adaptation , 2014 .

[30]  Joshua D. Angrist,et al.  Mostly Harmless Econometrics: An Empiricist's Companion , 2008 .

[31]  J. Ritchie,et al.  Weather impacts on maize, soybean, and alfalfa production in the Great Lakes region, 1895-1996 , 2001 .

[32]  P. Mahadevan,et al.  An overview , 2007, Journal of Biosciences.

[33]  D. Lobell,et al.  Synthesis and Review: an inter-method comparison of climate change impacts on agriculture , 2018, Environmental Research Letters.

[34]  Luis Samaniego,et al.  Toward computationally efficient large‐scale hydrologic predictions with a multiscale regionalization scheme , 2013 .

[35]  S. Long,et al.  Food for Thought: Lower-Than-Expected Crop Yield Stimulation with Rising CO2 Concentrations , 2006, Science.

[36]  Luis Samaniego,et al.  A high-resolution dataset of water fluxes and states for Germany accounting for parametric uncertainty , 2016 .

[37]  Alexei G. Sankovski,et al.  Special report on emissions scenarios : a special report of Working group III of the Intergovernmental Panel on Climate Change , 2000 .

[38]  D. Lobell,et al.  Comparing estimates of climate change impacts from process-based and statistical crop models , 2017, Environmental Research Letters.

[39]  S. Hsiang.  Climate Econometrics , 2016 .

[40]  Public Perception of Climate Change and the New Climate Dice , 2012, 1204.1286.

[41]  J. Soussana,et al.  Crop and pasture response to climate change , 2007, Proceedings of the National Academy of Sciences.

[42]  E. Wood,et al.  Anthropogenic warming exacerbates European soil moisture droughts , 2018, Nature Climate Change.

[43]  J. Angrist.  Mostly Harmless Econometrics , 2008 .

[44]  J. M. de Jager,et al.  A meteorological approach to the identification of drought sensitive periods in field crops , 1978 .

[45]  David B. Lobell,et al.  Comparing and combining process-based crop models and statistical models with some implications for climate change , 2017 .