基于反现实情景模拟的耕地“进出平衡”政策绩效预测

    Predicting “In-out Balance” policy performance of arable land using counterfactual scenario simulation

    • 摘要: 探究情景模拟下耕地进出平衡政策实施绩效与影响,有助于完善该政策机制和促进耕地保护。该研究以广州市为例,通过构建现实情景(政策实施情景)和反现实情景(惯性发展情景)下的农用地内部转换决策效用函数、土地利用需求预测模型和基于元胞自动机(cellular automata,CA)的土地利用转换潜力综合模型,对比分析两种情景下的土地利用时空动态格局变化,对该政策未来实施绩效进行预测。结果表明:1)该政策实施有效减少了广州市耕地的流失,政策实施情景中2020—2030年耕地流向非耕农用地的面积减少了20.40km2;2)该政策实施对耕地和园地的景观格局影响较大,政策实施情景中耕地的聚集程度更高,但园地的破碎程度更大;3)政策实施情景中2020—2030年广州市农用地内部地类数量比例保持平衡,较多园地恢复为耕地,且各地类分布更加均匀。耕地进出平衡政策未来在广州市的实施绩效良好,有效减少了耕地流失,维持了农用地内部结构比例,促进了园地向耕地转换,对保持耕地数量动态平衡、保障国家粮食安全具有重要意义。

       

      Abstract: Cultivated land resources are closely related to national food security, economic development and social stability. Low yield of grain farming has confined to a large number of cultivated lands in recent years, even permanent basic farmland planting cash crops, seedlings, and forest fruits. The “In-out Balance” policy has been released on the farmland to require that "while the cultivated land is converted into forest land, garden land and other agricultural land and agricultural facilities construction land, the same quantity and quality of cultivated land that can be used stably for a long time should be added". At present, most previous studies focus mainly on the implementation path of farmland access balance. Only a few research has been implemented on the performance evaluation. The purpose of this study is to explore the implementation performance and impact of farmland “In-out Balance” policy under scenario simulation. The policy mechanism was promoted to protect the cultivated land. Taking Guangzhou City as an example, the comparison was made to analyze the spatiotemporal pattern of land use under realistic scenarios (policy implementation scenarios) and counterfactual scenarios (inertial development scenarios). The cellular automata (CA) method was also utilized to construct the decision utility function of agricultural land internal conversion, the land use demand prediction model, and the comprehensive model of land use conversion potential. The implementation performance of the policy was forecasted in the future. The results were as follows: 1) The implementation of the policy had effectively reduced the loss of cultivated land in Guangzhou. The area of cultivated land was shifted to non-cultivated land in the policy implementation scenario from 2020 to 2030, which decreased by 20.40 km2. 2) The policy posed a significant impact on the landscape pattern of cultivated and garden land. There was a higher aggregation degree of cultivated land, whereas, a greater fragmentation degree of garden land was found under the policy implementation scenario. 3) The proportion of internal land types in Guangzhou's agricultural land remained balanced in the policy implementation scenario from 2020 to 2030. More garden plots were restored into the arable land. There was the more uniform distribution of land types in different regions. In conclusion, better performance was achieved in the farmland “In-out Balance” policy in Guangzhou in the future. The loss of farmland was effectively reduced to maintain the proportion of the internal structure of farmland. The conversion of garden land to farmland was promoted to maintain the Dynamic equilibrium of the number of farmlands, particularly for the national food security. Four policy suggestions were proposed, including the expanding compensation path of cultivated land, strictly controlling the loss of cultivated land, the implementation of supporting measures, and "double balance" coordinated management. Only two scenarios were considered on the land use pattern in the urban development and cultivated land protection. More complex scenarios under the implementation of this policy can also be considered in future studies. The findings can provide the basis and suggestions for a more comprehensive and efficient implementation of the “In-out Balance” policy.

       

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