Agent农业土地变化模型研究进展

Abstract

Agricultural use and cover change(Agri-LUCC) is one of the key issues among global and sustainability studies.Year-on-year progress makes change to be an emerging interdisciplinary science.As an effective tool for understanding the driver,process and consequence of Agri-LUCC,spatially-explicit models have successfully applied in representing agricultural landscapes and its possible developments across scales.Although several breakthroughs have been achieved by traditional modeling,there are still many crucial issues remain unsolved,especially the insufficient cognition on the complexity and dynamics of agricultural systems.Recently,some researchers begin to combine agent-based models(ABM,one of the key tools for complex system studies) with models,bringing a new emergence of model series in the agricultural community,which are called as Agri-ABM/LUCCs.Progress in this field can be summarized as:(1) Based on the complexity system theory,most of these models bring theoretical and methodological innovations in analyzing the complexity of agricultural systems.(2) These models innovatively take use decisions at individual level into consideration,based on which to recognize the role of decision makers bringing about changes,through their choices,on regional level landscapes.Such modeling with stakeholders underlines the role of farmers in agricultural transformation,facilitating the expression of diversified decisions on agricultural use from heterogeneous farmers.(3) Agri-ABM/LUCC links land driving forces with land use consequences as an endogenous feedback loop in agricultural processes.This tightly coupled method describes a better feature of agricultural dynamics,which is essential for analyzing the vulnerabilities,impacts,and adaptation in agricultural context.(4) From the recent literature,a wild range of issues related to farmer′s decisions on their were discussed,including deforestation,agricultural expansion,crop allocation,resource management,and settlement and livelihood decisions.In these studies,various methods and approaches were used in representing farmer′s decisions.Methods include linear programming model,optimization model,heuristic imitative and innovative decision-making algorithms,utility function,decision tree,evolutionary programming,probabilistic method,participatory modeling,role playing game,bounded-rational approach,spatial multi-nominal logistic functions,among others.(5) This new perspective provides a way to dynamically link agricultural assessments for integrated human-natural studies.On one hand,consequence of agricultural can be used to forecast crop production then to develop food security scenarios;on the other hand,the same result is valuable for predicting carbon-nitrogen cycling processes,consequently for projecting carbon sequestration within large scale agricultural landscapes.Scenarios of food and ecological security provide feedbacks to individual farmers to alter their decisions of use in turn.Beside the progress,however,problems of current Agri-ABM/LUCCs still exist,such as theory divorced from practice,deficiency in cross-site comparison,and difficulties in carrying out large-scale modeling.The most critical problem is that other than the common characteristics of complex adaptive systems,some of the special features of agricultural systems exit in their spatial-temporal dynamics,scaling effects,coupled human and natural issues,and multi-dimension feedbacks.These features are still not well examined in the current studies,which require further in-depth discussions in the future.