Uncertainty in soil data can outweigh climate impact signals in global crop yield simulations.

Christian Folberth,Ligia B Azevedo,Rastislav Skalský,Juraj Balkovič,Marijn Van Der Velde,Elena Moltchanova,Michael Obersteiner

doi:10.1038/ncomms11872

Abstract

Global gridded crop models (GGCMs) are increasingly used for agro-environmental assessments and estimates of climate change impacts on food production. Recently, the influence of climate data and weather variability on GGCM outcomes has come under detailed scrutiny, unlike the influence of soil data. Here we compare yield variability caused by the soil type selected for GGCM simulations to weather-induced yield variability. Without fertilizer application, soil-type-related yield variability generally outweighs the simulated inter-annual variability in yield due to weather. Increasing applications of fertilizer and irrigation reduce this variability until it is practically negligible. Importantly, estimated climate change effects on yield can be either negative or positive depending on the chosen soil type. Soils thus have the capacity to either buffer or amplify these impacts. Our findings call for improvements in soil data available for crop modelling and more explicit accounting for soil variability in GGCM simulations.

Highlights

Global gridded crop models (GGCMs) are increasingly used for agro-environmental assessments and estimates of climate change impacts on food production
As GGCMs usually run at a spatial resolution of 0.5° Â 0.5°2,6, various soil types or combinations of soil parameters may in both cases occur within one simulation unit
The yield variability over a 10-year period and the total range of possible soil types CVtot is substantially higher than the solely climate-driven 10-year yield variability CVdom under most crop management configurations across the different climate regions (Fig. 1a–f and Table 1)

Summary

Introduction

Global gridded crop models (GGCMs) are increasingly used for agro-environmental assessments and estimates of climate change impacts on food production. Forcing an ensemble of seven global gridded crop models (GGCMs) with the same set of GCM projections resulted in comparable present-day yield levels but relative climate change impacts on crop yields ranged from about À 40 to þ 25% by the 2090s for a high CO2 emission pathway[6]. The findings of recent regional studies that investigated how selection or extrapolation of soil data influences simulated crop yields are conflicting: Zhang et al.[17] found that finer resolution soil data improve model performance in high-resolution crop simulations in the US mid-west, with only small differences in average crop yields but large deviations in the spatial representation of yields and carbon fluxes. Angulo et al.[18] found only marginal differences in simulated yields when aggregating soil data They attributed their findings to high precipitation in the study region (Northwest Germany) and the algorithms used for estimating hydraulic parameters.

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Conclusion