• Energy Research

Farmland is the most basic material condition for guaranteeing rural livelihoods and national food security, and exploring management strategies that take both stable rural livelihoods and sustainable farmland use into account has vital significance in theory and practice. Farmland is a complex and self-adaptive system that couples human and natural systems, and natural and social factors that are related to its changing process need to be considered when modeling farmland changing processes. This paper uses Qianjingou Town in the Inner Mongolian farming–pastoral zone as a study area. From the perspective of the relationship between household livelihood and farmland use, this study establishes the process mechanism of farmland use change based on questionnaire data, and constructs a multi-agent simulation model of farmland use change using the Eclipse and Repast toolbox. Through simulating the relationship between natural factors (including geographical location) and household behavior, this paper systematically simulates household farmland abandonment and rent behaviors, and accurately describes the dynamic interactions between household livelihoods and the factors related to farmland use change. These factors include natural factors (net primary productivity, road accessibility, slope and relief amplitude) and social factors (household family structures, economic development and government policies). Ultimately, this study scientifically predicts the future farmland use change trend in the next 30 years. The simulation results show that the number of abandoned and sublet farmland plots has a gradually increasing trend, and the number of non-farming households and pure-outworking households has a remarkable increasing trend, whereas the number of part-farming households and pure-farming households has a decreasing trend. Household livelihood sustainability in the study area is confronted with increasing pressure, and household non-farm employment has an increasing trend, while regional appropriate-scale agricultural management is maintained. The research results establish the theoretical foundation and a basic method for developing sustainable farmland use management that can meet the willingness of households and guarantee grain and ecological security.

Urban livability is an important factor affecting the sustainable development of modern cities. Safe livability is an important part of urban livability. In view of this, this paper takes security as an example, and based on the actual data of Futian District, Shenzhen City, China, establishes a multi-agent simulation model of urban safe livability. The dynamic interaction feedback mechanism between decision-making behaviors of residents and urban safe livability under the influence of environment and policies has been explored, and residents’ decision-making simulation of the change of urban safe livability is realized. Finally, the main factors influencing urban safe livability are summarized through simulation conclusions. The research can not only provide scientific suggestions for improving the safe livability of Shenzhen, it also provides strong support for the sustainable development of the city.

Sustainable ecosystem services consumption is of vital importance to the survival and development of human society. How to balance the conflicts between ecosystem protection and ecosystem services consumption by local residents has been a serious challenge, especially in ecologically vulnerable areas. To explore the reasonable ecosystem services consumption approaches of grassland ecosystems for sustainable land system management, this study takes Hulun Buir of the Inner Mongolia Autonomous Region as a case study region and develops an EcoC-G (ecological consumption of grassland) model based on herders’ livelihood behaviors using the agent-based model technique to simulate the dynamics of ecosystem pressure, livestock production, and living quality of herders under different grassland management scenarios over the next 30 years. The EcoC-G model links the supply and consumption of grassland ecosystem services by calculating the ecosystem net primary productivity (NPP) supply and household NPP consumption. The model includes three sub-models, namely, the individual status transferring sub-model, the households’ grassland-use decision sub-model, and the ecosystem pressure sub-model. In accordance with multi-objective grassland management practices, the following four land management scenarios were simulated: (1) baseline scenario, (2) increasing household’s living standard, (3) ecosystem protection, and (4) balancing living standard improvement with the protection of the ecosystem. The result indicates that by focusing on the NPP supply and consumption of the grassland ecosystem, the EcoC-G is capable of simulating the impacts of herders’ livelihood behaviors on grassland ecosystems. If timely grassland management strategies are implemented, it is possible to relieve the ecosystem pressure and improve the livelihood of local herders. The specific scenario simulation results are: (1) Under the current grassland management mode, the pasture could never be overgrazed, and herders could achieve the basic living standard, but the accumulated wealth decreased due to the decline of livestock. (2) With grazing control, herders can accumulate wealth by increasing the breeding amount and reducing the marketing rate, but the ecosystem consumption pressure can reach a maximum of 2.3 times. (3) With strict restrictions on the livestock number, the pressure on the ecosystem decreases; however, herders might not achieve basic living standards. (4) Modest regulation leads to rational ecological consumption intervals, meaning the ecosystem pressure will become stable and herders can gradually accumulate wealth with the achievement of basic living standards in advance.