Study On The Driving Mechanism Of Macroscopical Land Use Function Change In Ecologically Fragile Area

It has been the focus for the research on the microscopic driving mechanism of the Land use function change in the fragile area.Not only did this research may contribute to revealing the change of LUF,but understanding the farmers' behaviors will be contributed to as well.The relationship between the macro change of LUF and the farmers' land use behavior will be explored in this dissertation,and a case study of Mizhi County of Shaanxi Province will be carried on.First,the change of the LUF is explored based on the LUF index system.The typical communities were selected after analyzing the cold and hot spots of the LUF,and exploring the LUF's importance of the communities in the study area.Second,based on the farmer investigation and the practical PRA,the CA-BDI(Capability and Ability Belief-Desire-Intention)model which was used to simulate the farmer land use behavior was constructed,and the scaling conversion method was explored from the individual farmer to the village after classified the different farmers and analyzing the decision-making of the different farmer groups.Third,the verification of the land use change of the community among the methods of the Classification of The Villages and the coupling model of CA-BDI+CLUE-S was explored.Finally,the LUF of the Dujiashigou Community was simulated based on the CA-BDI+CLUE-S model from 2018 to 2020,and the effect on the policy for rural poverty alleviation on the LUF of the typical community and the land use change of their villages were analyzed.Then,several conclusions were drawn as the following:The index system of the LUF was constructed,and could be effectively represent the land use function and its change in the research area.Four indicators were included in the production function,namely the proportion of the livestock,the per unit area yield of grain,the vegetable and fruit production,the visiting income of the agricultural sightseeing garden and ethnic tourism included.Five indicators were used to express the ecological function,which were the forest and grass land area ratio,the Pesticide use and fertilizer use,the effective irrigated area rate and the proportion of the terraced field and dam land and the irrigable land.The social function was expressed by the proportion of labor employment in the primary industry,the visiting reception of the agricultural sightseeing garden and ethnic tourism rural population,and rural population density.The weights of the indicators were assigned by the entropy method.The weights of the production function,the ecological function and the social function were 0.24,0.39 and 0.37 respectively.The index system of the LUF may be conveniently related to the farmers' land use behavior.The typical communities were identified which were used to explore the relationship between the macro LUF change and the change of the farmers' land use behavior.The cold and hot spot of the multiple LUF and the importance of LUF of the study area were analyzed.Then Gaoqu Communities and Dujiashigou Community were identified.The type of cold and hot spot of LUF of Gaoqu Community was changed from the others type to hot type from 2011 to 2015,and the type of Dujiashgou Community was from hot type to the other type.The result showed that the importance of LUF of Gaoqu Community was increased,and the importance of LUF of Dujiashigou Community was decreased.The CA-BDI model was effectively represented the bounded rational decision-making of the farmer household,and the mechanism of multi-scale decision transformation can be revealed by the Different Weight Scaling Conversion Method.Based on the ODD framework,the farmers' land use decision-making model was analyzed.Compared to the traditional BDI model,the parameters of Capability and Ability were added in this model.The Capability parameter was used to express the potential land use plan of the farmers,and the Ability parameters was use to express the possibility of the actual land use plan of the farmers.Four typical villages were simulated by this model,the accuracy rates were more than 79% except the village Gaoxigou in year of 2017.The effect of land use decision-making of the individual farmer on the farmer groups were expressed effectively by the Different Weight Scaling Conversion Method,and the result can be shown in the space.Not only did the land use change of village was revealed by this method,but also the micro driving mechanism was illustrated.The micro-driving mechanism of macroscopic land use change can be revealed by the CA-BDI+CLUE-S model.After compared the simple scaling typical village method,the classification of different village method and the coupling model of CA-BDI+CLUE-S,the result was shown that the classification of different village method was better than the simple scaling typical village method,and the coupling CA-BDI+CLUE-S model was better than the classification of the different village method.The reason was benefit by land use change rule summarized by CA-BDI model,and by the land use demand from bottom to up.The attention of CLUE-S model was focus on the whole area,nor on the individual village,therefore,land use change rule identified by CLUE-S model was better than CA-BDI.Under the different policy scenarios,the effect of farmer behavior change on land use function was quite different.Simulated by the CLUE-S + CA-BDI model,the land use change of Gaoqu Community was simulated.The result showed that the land use change of Gaoqu Community was neither the copy of the village type ?,nor the reproduction of the village type ?,but mixed the quantity of the different crop,the plant structure and the order of the importance of crops of the village type ? and the village type ?.The villages,which should be paid more attention to,were identified after analyzing the change of the cold and hot spot of LUF and the change of the importance of LUF.However,the similarities between the two policy scenarios were less than the differences.Compared by the policy scenario ?,the household farmers' land use behavior had a considerable effect on the change of the cold-hot categories and the importance of land use function in policy scenario ?.