Climate smart agriculture and global food-crop production

Results also show the importance of understanding how changes caused by the widespread adoption of CSA practices may play on a global scale. The indirect effects arising from the reorganization of global production can lead to larger agricultural areas being allocated to other crops, and to an expansion in the global livestock herd due to cheaper feedstock prices. These effects can be large enough to limit the emission abatement effectiveness of CSA prac- tices. In addition, the heterogeneous changes in countries’ GHG emissions, even in the pres- ence of a global positive outcome, shows the importance of global coordination. Such coordination should also consider the interaction between agricultural land and carbon-rich environments such as forests and peatlands to avoid emission leakage [76,77]. Beyond the specifics of CSA, our results are strongly suggestive that using alternative prac- tices the agriculture sector can increase its output and reduce its carbon footprint under future climate scenarios. However, many are the assumptions that underly our work and much more research must be undertaken to evaluate the global effects of changes in food production sys- tems. Simulating alternative agricultural futures requires a model representation of the main structural drivers of demand and supply of food products and this requires significant assump- tions about producers’ and consumers’ behavior. Scenario analyses based on model simula- tions, of which this study is an example, are not a prediction of the future. They are a

representation of possible alternative futures given our current knowledge and assumptions about trends in climate, technology, population, income and other drivers, and about how they may interact in an economic system. Scenarios also rely heavily on existing global data- sets, which come with many limitations. One way to test the robustness of the scenarios pro- duced by models that do not generate confidence intervals or goodness-of-fit metrics, like the one we used, is to undertake a sensitivity analysis for some of the key variables. We have done this for climate, adoption levels, and yield performance but many more could be explored. Results from the sensitivity analysis point to the qualitative robustness of some of the findings (e.g. agriculture can withstand the negative impact of climate change using alternative prac- tices, sustainable increase in production while reducing the carbon food print is possible), oth- ers indicate where additional research is necessary (e.g. investigate the multiple pathways that link agricultural output with the food security status of vulnerable people, move beyond the emphasis on yield gains and model the effects of crop rotations). Other results reveal the limits of the modeling environment that was used. A perfect example of this are our findings about land use change. The overall effects of higher yields and lower prices is to reduce the need for additional harvested area to fulfill the increasing demands for maize, wheat and rice. This sug-

gests a reduced pressure to expand cropland and potential land-sparing effects. However, IMPACT does not model explicitly the competing demands of all land uses. It only considers cropland area and its agricultural output. While the idea that agricultural intensification reduces agricultural land’s encroachment into other natural areas is not new, it was famously put forward by Borlaug [78], whether this happens in reality is the subject of some controversy [79–81] and our model cannot directly resolve these questions. More research in this issue is therefore necessary. One way to verify and test the validity of these scenarios is also to use alternative models after proper calibration [82] and compare results across them. Although this requires consider- able resources, these types of comparisons have been done to assess global issues related to cli- mate change such as agricultural production under future climate regimes [82], agricultural production and mitigation [83], and future nutritional challenges [84]. It would be advisable that a similar exercise is undertaken to explore the merits and benefits of alternative produc- tion systems like the one proposed by CSA. PLOS ONE Climate smart agriculture and global food-crop production PLOS ONE | https://doi.org/10.1371/journal.pone.0231764 April 29, 2020 13 / 19