Integrating Plant Science and Crop Modeling: Assessment of the Impact of Climate Change on Soybean and Maize Production

Abstract

Increasing global CO2 emissions have profound consequences for plant biology, not least because of direct influences on carbon gain. However, much remains uncertain regarding how our major crops will respond to a future high CO2 world. Crop models inter-comparison studies have identified large uncertainties and biases associated with climate change. The need to quantify uncertainty has drawn the fields of plant molecular physiology, crop breeding and biology and climate change modelling closer together. Comparing data from different models that have been used to assess the potential climate change impacts on soybean and maize production, future yield losses have been predicted for both major crops. However, when CO2 fertilisation effects are taken into account significant yield gains are predicted for soybean, together with a shift in global production from the Southern to the Northern hemisphere. Maize production is also forecast to shift northwards. However, unless plant breeders are able to produce new hybrids with improved traits, the forecasted yield losses for maize will only be mitigated by agro-management adaptations. In addition, the increasing demands of a growing world population will require larger areas of marginal land to be used for maize and soybean production. We summarise the outputs of crop models, together with mitigation options for decreasing the negative impacts of climate on the global maize and soybean production, providing an overview of projected land-use change as a major determining factor for future global crop production.3

Modelling predicts that soybean is poised to dominate crop production across Africa

“…The projected yield and sowing area gains suggest a large expansion in global soybean production, even though such shifts in production areas will depend largely upon GHG emissions and the success of mitigation strategies (Tai et al, ; Tai & Martin ). Major changes in policy, agricultural practice, and diet indicate that there will be major changes in the land areas dedicated to soybean production (Fodor et al, ). Although effective adaptation actions are required to mitigate the harmful impacts of climate change across Europe and other continents, Africa is at the other end of the spectrum.…”

“…A value 1.0 is given if the area is perfectly suitable for producing the crop (Zabel, Putzenlechner, & Mauser, ). When projected climate data are fed into such models, they are capable of predicting the possible changes in harvest area (Fodor et al, ). Crop models are designed to calculate crop yield (and other important parameters of the plant–soil system) as a function of weather and soil conditions, or plant‐specific characteristics, as well as the choice of agricultural management practices.…”

“…The projected yield and sowing area gains suggest a large expansion in global soybean production, even though such shifts in production areas will depend (2017), driven by climate projections from a global climate model for two future scenarios following the Representative Concentration Pathways (RCP4.5 and RCP8.5) largely upon GHG emissions and the success of mitigation strategies (Tai et al, 2014;Tai & Martin 2017). Major changes in policy, agricultural practice, and diet indicate that there will be major changes in the land areas dedicated to soybean production (Fodor et al, 2017).…”

Response of maize biomass and soil water fluxes on elevated CO2 and drought—From field experiments to process‐based simulations

“…In line with Durand et al (2017), we emphasize the importance of an explicit stomatal control on transpiration in crop models. Further optimization of the model might be achieved by including for instance CO 2 effects on plant architecture and partitioning between roots and shoots as indicated by Fodor et al (2017). We emphasize the importance of up-to-date FACE data for calibrating CO 2 response factors.…”

“…Most commonly, process-based crop models are applied, in which the most important processes of the soil-plant system are represented (Fodor et al, 2017). Most commonly, process-based crop models are applied, in which the most important processes of the soil-plant system are represented (Fodor et al, 2017).…”