RESUMEN
Global food security can be threatened by short-term extreme events that negatively impact food production, food purchasing power, and agricultural economic activity. At the same time, environmental pollutants like greenhouse gases (GHGs) can be reduced due to the same short-term extreme stressors. Stress events include pandemics like COVID-19 and widespread droughts like those experienced in 2015. Here we consider the question: what if COVID-19 had co-occurred with a 2015-like drought year? Using a coupled biophysical-economic modeling framework, we evaluate how this compound stress would alter both agricultural sector GHG emissions and change the number of undernourished people worldwide. We further consider three interdependent adaptation options: local water use for crop production, regional shifts in cropland area, and global trade of agricultural products. We find that GHG emissions decline due to reduced economic activity in the agricultural sector, but this is paired with large increases in undernourished populations in developing nations. Local and regional adaptations that make use of natural resources enable global-scale reductions in impacted populations via increased global trade.
RESUMEN
CONTEXT: The COVID-19 pandemic has resulted in immediate and wide impacts on human and agricultural systems. While some of the positive and negative impacts of COVID-19 on the environment and economies are emerging, there is not a comprehensive understanding of the potential impacts of COVID-19 on the most vulnerable farmers. OBJECTIVE: The purpose of this study is to evaluate the immediate impacts of COVID-19 on agricultural and food systems in the United States. Our aim is to quantify the impacts on labor productivity in crops and livestock production considering the heterogenous vulnerability of different farmworkers. We are interested in measuring the production that is not realized due to COVID-19. METHODS: In this paper, we introduce IMLAP, Immediate impact Model of Local Agricultural Production. This model is an economic framework considering short-term agricultural production responses to economic, environmental, and policy changes. We investigate the potential impacts of COVID-19 on the farmers in the U.S. for each county with a special focus on female, Hispanic, black and African American, and small-scale producers. RESULTS AND CONCLUSIONS: Considering the impacts of COVID-19 on labor, the findings of this study suggest a decline in agricultural output in all the U.S. counties ranging from 1.18% to 7.14% of total production. Our simulation results show that counties with a higher number of small-scale farms, non-white farmers, and female-operated farms are the most vulnerable to COVID-19. Also, we argue that the stimulus policies and support packages must target these communities of producers to ensure that their livelihood is protected. The findings suggest that productivity growth (technological improvements) and international trade can eliminate the negative impacts of pandemics. SIGNIFICANCE: The proposed quantitative framework of this study is a simple yet novel model that empowers diverse research communities to provide a quick analysis of the impacts of unprecedented events. It offers a holistic framework to evaluate the response of agricultural production to changes in availability and productivity of labor, machinery & equipment, land, fertilizer, seeds, and other inputs. This study presents new foundations for agricultural research communities to provide solutions to agricultural resilience challenges and highlights the significance of demand drivers, technological growth, and international trade in strengthening the food system.