Strategies to boost global food production: Modelling socioeconomic policy scenarios
2017
Krishna Bahadur KC | Evan D.G. Fraser
Current research on food security is dominated by crop, climate and demographic modellers who project how changes in weather and population may affect the global demand and supply of food. But socioeconomic factors also play a crucial role in determining the amount of food we produce. In this paper, we present spatially explicit multiple regression models that demonstrate 65% of maize, 49% of rice and 35% of wheat harvests (globally) can be explained by four socioeconomic variables: income distribution, gross domestic product/capita, human development index and fertilizer use. Using these insights, we model the effect that different hypothetical policy scenarios may have on boosting yields and demonstrate that it could be possible to increase global cereal harvests by 70%. This research demonstrates that to understand threats to global food security, and develop strategies to avert problems, scientists must integrate socio-economic data with biological and demographic factors if they want to provide comprehensive advice to policy makers.
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