Identification and characteristic analysis of semi-natural habitats in China's economically developed areas: New insights to inform cultivated land system ecological conservation

Abstract

Identifying and characterizing semi-natural habitats (SNHs) are important to the ecological conservation of cultivated land systems and implementing China's ecological civilization strategy. This study revealed the concept and characteristics of SNHs in Chinese cultivated land systems regarding human activities, resource types, and spatial landscape patterns. The resource quantity, landscape quality, and spatial distribution of SNHs in Southern Jiangsu's cultivated land system were analyzed by constructing the identification model of “land use/land cover type-cultivated land use intensity-spatial landscape pattern”. The results showed that the area of SNHs in Southern Jiangsu's cultivated land system was 25.35%, significantly influenced by cultivated land intensification and expansion. The higher the cultivated land use intensity, the lower the quantity of SNHs, and the proportion of SNHs in the intensive-use pattern was only 2.97%. 68.18% of the SNHs in Southern Jiangsu were water, and habitats for important species, such as woodland, grassland, wetlands, and bare land, were scarce. A small patch area, high landscape fragmentation, poor landscape richness and diversity, and low connectivity accompanied increased cultivated land use intensity. From the extensive to intensive utilization, the spatial spread of SNHs from low-value aggregation to high-value scatter areas, with hotspot areas of cultivated land use intensity and SNHs existing only in a small part of Nanjing and Changzhou. This study provides a scientific reference for the rehabilitation and restoration of SNHs in the context of the ecological transformation of land use. It promotes the sustainable intensification of cultivated land systems. It also provides new ideas for linking ecological and urban spaces to form a stable and systematic national ecological safety network.