Climate impacts on long-term silage maize yield in Germany

Michael Peichl,Andreas Marx,Bernd Hansjürgens,Stephan Thober,Luis Samaniego

doi:10.1038/s41598-019-44126-1

Michael Peichl, Andreas Marx + Show 3 more

Open Access

https://doi.org/10.1038/s41598-019-44126-1

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Abstract

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.

Highlights

The statistical model developed here is a reduced-form panel approach that exploits the exogenous variation in key explanatory variables[33]
Endogenous variables are not included because they are considered bad control[34]. It incorporates the most influential variables identified in PTMS4
As only annual weather deviations from the average of the reference period 1951–2015 are considered by the predictors, the coefficients of the exogenous variables are determined on the basis of inter-annual fluctuations

Summary

Introduction

As only annual weather deviations from the average of the reference period 1951–2015 are considered by the predictors, the coefficients of the exogenous variables are determined on the basis of inter-annual fluctuations. Farmers are expected to optimize the entire production process at their site based on their experience of local weather conditions. By restricting the coefficients to the same values in all districts, it is implicitly assumed that the response of plants to these inter-annual stressors is the same at all sites. Differences in sensitivity to exogenous weather and soil moisture variations caused by the use of different silage maize varieties or particular soil characteristics are ignored by this modelling approac

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Conclusion