基于多元国土空间整治情景模拟的生态系统服务功能分区

生态系统服务功能分区是科学管理生态系统的重要手段。国土空间整治能够通过综合治理闲置、低效和生态退化国土资源，改变国土空间结构与布局，从而对生态系统功能产生影响。现有研究较少关注土地整治措施对未来生态系统服务空间集聚模式的潜在影响作用，整治措施的生态导向性有待提升。因此，该研究以山东招远市为例，设计了基准情景、废弃矿区修复情景以及城乡建设用地整治情景，定量化预测生态系统服务变化特征，并运用模糊C均值聚类算法开展生态系统功能区划定。结果表明，整治情景下土地利用数量结构变化显著，各生态系统服务能力均有所提升。全域可以划分为生态综合区、生境保育区、固碳释氧区、固碳产粮区、生态维护区5个生态功能区。与基准情景相比，废弃矿区修复情景下各生态功能区60%生态系统服务水平持平，28%处于劣势，仅12%显著提升。城乡建设用地整治则能够显著提升全域自然娱乐能力，总体增长了1.89%。生境保育区的水源涵养和粮食生产能力平均值分别增加了0.25和0.10，固碳释氧区的生境质量、水源涵养能力分别增长了20.69%和100%。研究表明全面提升生态系统多功能性需要综合开展多元的国土空间整治措施。

Zoning of the ecosystem service functions under multiple land consolidation scenarios

Abstract: Ecosystem services can greatly contribute to human health and well-being. It is critical to delineate the ecosystem services into the function zones for the decision-making space management in sustainable development. Different management measures can also be implemented to improve the ability of ecosystem services, according to the type of ecological function zones. A land consolidation has posed diverse influences on the ecosystem in recent years, particularly on the idle, inefficient use and ecological degradation of land resources. However, only a few studies have focused on the impacts of land consolidation on the spatial agglomeration of ecosystem services. It is still lacking in the perceptiveness of consolidation policies. Taking the Zhaoyuan City, Shandong Province of China as an example, three scenarios of land consolidation were designed to realize the functional zoning of ecosystem services, according to territorial spatial planning. The specific three scenarios included the Business-as-Usual scenario (BAU), reclamation of abandoned mining areas scenario (RAM), as well as the scenarios of an increasing-decreasing balance of urban and rural construction land (BCL). A Markov-FLUS model was utilized to project the future demands of land use and spatial distribution under the three scenarios. A scenario simulation was also carried out to calculate the multiple ecosystem services. Furthermore, a fuzzy C-means clustering was selected to identify the ecological function zones, thereby exploring the ecosystem service capacity of function zones. The results showed there were significant changes in the land use structure and the improvement of ecosystem services under all scenarios of land consolidation. The cultivated land increased 76.32 hm2 and 1 516.86 hm2 in the RAM and BCL. The forestland also experienced a significant increase of 221.49 hm2 and 2 280.60 hm2 in the RAM and BCL, compared with BAU. The scale of construction land was effectively managed to improve the total amount of ecosystem in the RAM and BCL. There was a spatial heterogeneity of the RAM and BCL improvement. Not all the sub-districts (towns) improved ecosystem services. For example, most ecosystem services in the Quanshan sub-district and Biguo town decreased in the RAM, while the total carbon storage in the Mengzhi and Wenquan sub-districts decreased by 0.02% and 0.32% in the BCL, respectively. According to the function structure of ecosystem services, five ecological functional zones were divided, i.e., habitat conservation, carbon storage, carbon storage-food production, ecological maintenance, and comprehensive ecological zone. Compared with the BAU, the RAM was partially improved ecosystem services of functional zones. 60% of ecosystem services in the five ecological functional zones under the RAM were on the average level, similar to those in the BAU, and 28% of those were inferior, while only 12% of those were superior. The BCL significantly promoted the natural recreation service of all ecological functional zones, with an overall increase of 1.89%. The average value of water conservation and food production increased by 0.25 and 0.10, respectively, in the habitat conservation zones. The average value of habitat quality and water conservation increased by 20.69% and 100%, respectively, in the carbon storage zones. A comprehensive consolidation potential can be taken in the different sub-districts (towns) to enhance the multiple services capacity of ecosystems, thereby delving into the potential of the key sources of rural land for a lower expansion rate of urban construction land.