AUTHOR=Li Zhijie , Ma Ziyi , Zhou Guoyan TITLE=Impact of land use change on habitat quality and regional biodiversity capacity: Temporal and spatial evolution and prediction analysis JOURNAL=Frontiers in Environmental Science VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2022.1041573 DOI=10.3389/fenvs.2022.1041573 ISSN=2296-665X ABSTRACT=

The ecological stability of a region and the promotion of its coordinated environmental and economic development depend on habitat quality, which is a key indicator of the territory’s biodiversity capacity. A case study is done in Suzhou City, Jiangsu Province, to determine how land use changes affect habitat quality. The types of land use in 2030 are simulated based on 2000, 2010, and 2020. The InVEST and CA-Markov models analyze and predict how land use will change in Suzhou. Spatial analysis methods, such as the standard deviation ellipse, the center of gravity analysis, spatial autocorrelation, and random forest models, were used to reveal the spatial and temporal variation characteristics of habitat quality and to analyze its influencing factors. The bare land, building lands, and non-construction lands significantly increased in Suzhou city’s land use types between 2000 and 2030 due to land use changes, while the water bodies and forests gradually decreased. Most of the high-quality habitats in this region are found in the water bodies and the mountains. In contrast, the poor habitat quality in this area is mainly concentrated in urban construction lands. The habitat quality gradually declined over time, and its center of gravity followed the migration path from northeast to southwest. The temporal and spatial distribution of habitat degradation in Suzhou reveals a trend of habitat degradation from downtown to suburban areas. This degradation is most common in mountainous and forest areas where the landscape is highly fragmented. Habitat quality in Suzhou city has changed over time and space due to spatial patterns, socioeconomic factors, land use, and the natural environment, with land use having the most significant impact.