Assessing the impacts of the changes in farming systems on food security and environmental sustainability of a Chinese rural region under different policy scenarios: an agent-based model

Abstract

Since China has undergone a series of economic reforms and implemented opening up policies, its farming systems have significantly changed and have dramatically influenced the society, economy, and environment of China. To assess the comprehensive impacts of these changes on food security and environmental sustainability, and establish effective and environment-friendly subsidy policies, this research constructed an agent-based model (ABM). Daligang Town, which is located in the two-season rice region of Southern China, was selected as the case study site. Four different policy scenarios, i.e., "sharply increasing" (SI), "no-increase" (NI), "adjusted-method" (AM), and "trend" (TD) scenarios were investigated from 2015 to 2029. The validation result shows that the relative prediction errors between the simulated and actual values annually ranged from -20 to 20%, indicating the reliability of the proposed model. The scenario analysis revealed that the four scenarios generated different variations in cropping systems, rice yield, and fertilizer and pesticide inputs when the purchase price of rice and the non-agricultural income were assumed to increase annually by 0.1 RMB per kg and 10% per person, respectively. Among the four different policy scenarios in Daligang, the TD scenario was considered the best, because it had a relatively high rice yield, fairly minimal use of fertilizers and pesticides, and a lower level of subsidy. Despite its limitations, ABM could be considered a useful tool in analyzing, exploring, and discussing the comprehensive effects of the changes in farming system on food security and environmental sustainability.

Bibliometric analysis of publications discussing the use of the artificial intelligence technique agent-based models in sustainable agriculture

“…Group 1 (agent-based model, computational methods, autonomous agents, agricultural robots, simulation platform, land usage changes, policy, interested, food supply, crops, economic sciences, environmental impact, populational statistics, water management): The first group refers to the research articles where the agent-based method was used to simulate public policies bearing in mind the interest of stakeholders on whether to implement agricultural robots [94] , [95] , [96] , [97] , [98] , [99] , [100] , the changes in land usage [84] , [87] , [100] , [101] , [102] , water management [81] , [98] , [103] , [104] ; crop behavior [105] , [106] , food supply chains [94] , [101] , [107] , [108] ; and environmental impact [94] , [106] , [107] , [109] . The first group ( Fig.…”

“…Group 2 (agriculture, decision-making, models, crop system, article, theoretical, agricultural activities, human, theoretical model): This group encompassed research articles where human decision-making models were analyzed [107] , [110] , [111] , [112] , [113] to determine agricultural activities [97] , [104] , [114] and crop systems [107] , [109] , [110] . The second group of researchers has a more humanistic approach where agent-based models were implemented to model decision-making processes that have an impact in the agricultural system and determine the future behavior regarding current agricultural activities and crop systems in place.…”

Exploring the Drivers and the Interventions towards Sustainable Food Security in the Food Supply Chain

“…The literature indicated the most common driver of sustainable food security is the food security governance decisions [43][44][45][46][47][48], which subsidy and assistance programs are the most implemented interventions globally. The state of government policy, transformation programs, and subsidies, positively leaned towards attaining the "availability" domain in food security [47].…”

Reshaping the Sustainable Geographical Pattern: A Major Function Zoning Model and Its Applications in China

“…With the development of research on sustainability, land use sustainability based on an understanding of ecosystems has become the focus for optimizing the geographical pattern. A particular area of interest has been the development and improvement of predictive simulation models, such as the agent-based model (Matthews et al, 2007;Yuan et al, 2017), the cellular automata model and its evolved models based on grid neighborhood relationship analysis (Grinblat et al, 2016;Van Vliet et al, 2017), or the dynamics of land system model and state-and-transition simulation model based on analyses of changes in land system structures and spatial configuration succession (Wilson et al, 2016;Daniel et al, 2016;Najmuddin et al, 2017). Using these simulation models, it is possible to construct rational scenarios for different sustainability objectives, such as maximizing economic effects (Wu et al, 2012), minimizing pollutant emissions or environmental impacts (Bohnes et al, 2017;Degraeuwe et al, 2017), prioritizing ecological security (Brunner et al, 2017;Eitelberg et al, 2016), limiting climate change and carbon emissions (Anaya-Romero et al, 2015;Prestele et al, 2017), as well as for other sustainability scenarios, such as water resources (Proskuryakova et al, 2018), agricultural production (Chaudhary et al, 2018;Krasa et al, 2010;Van Vliet et al, 2017), or environmental protection (Najmuddin et al,2017;Zarandian et al, 2017).…”