Regional habitat quality is a proxy of biodiversity. Simulating changes in land use and habitat quality in urban agglomerations is the scientific basis for promoting the optimal allocation of land resources and building ecological civilizations in urban agglomerations. Therefore, we established a research framework mainly consisting of the Future Land Use Simulation (FLUS) model with the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) model to predict the spatial and temporal distribution of habitat quality. In addition, we set three scenarios which were a natural development scenario, a cultivated land protection scenario, and an ecological protection scenario to analyze the changes of habitat quality in the Guanzhong Plain urban agglomeration in 2035. The results showed that: (1) the FLUS model had an excellent effect on the simulation of land-use change in the Guanzhong Plain urban agglomeration, with an overall accuracy of 0.952 and a kappa coefficient of 0.924. (2) From 2000 to 2035, the cultivated land area of the study area, which was mainly transferred into construction land and grassland, shrank due to the process of urbanization. (3) The habitat quality score of this region gradually decreased from 2000 to 2020, and it continued to decrease to 0.6921 in 2035 under the natural development scenario, while it increased under the other two scenarios. The low-value areas of habitat quality were mainly located in the middle of this region with Xi’an as the core, whereas the high-value areas were mainly distributed in the southern Qinling Mountains and the northern Loess Plateau. (4) Of the different scenarios, the ecological protection scenario had the highest habitat quality, while the natural development scenario had the lowest. Besides this, we also found that the cultivated protection scenario had high habitat quality, which was mainly because the rate of occupation of ecological land was controlled. The results are expected to provide a scientific basis for optimizing the spatial allocation of land resources and promoting the sustainable use of land space in other ecologically fragile urban agglomerations.

As areas of dense populations and high economic activity, urban agglomerations have driven an overall increase in economic efficiency; however, the associated ecological risks are becoming increasingly apparent. The construction of ecological security patterns (ESPs) is an important approach for ensuring the ecological security of urban agglomerations, thereby achieving coordinated development of society, economy and ecology. Previous studies on ESPs have rarely considered the demand for ecosystem services at multiple scales and have accordingly failed to accurately identify important ecological sources. Here, we propose a novel method based on multi-scale ecosystem service demand to identify ecological sources, which can more accurately identify the ecological source meeting the regional sustainable development. Selecting the Guanzhong Plain urban agglomeration (GPUA) as study area, we constructed a resistance surface by comprehensively considering natural and anthropogenic disturbances. We found high resistance areas are mainly concentrated in highly urbanized areas with Xi’an as the core. In addition, we performed minimum cumulative resistance and gravity model to obtain and classify ecological corridors. The results revealed that the ecological sources identified in this study can enhance the connectivity of the inner regions of the GPUA and the linkage between north and south ecological corridors. The ecological sources were found to be concentrated in the southern Qinling Mountains, with an area of 28,780.02 km², accounting for 26.85% of entire region. Furthermore, we identified 121 potential ecological corridors, 47 ecological nodes, and 49 ecological breakpoints, and established that the extent of land with a high level of ecological security accounts for 21.98% of the entire regional area. This study offers a new perspective for ESPs construction, which can provide a scientific basis and policy guidance for the optimization of spatial structure and the maintenance of ecological security in ecologically fragile urban agglomerations.

Population is the foundation of socio-economic development. However, continued population shrinkage has made the problem of unbalanced and insufficient regional development more prominent, threatening human well-being. How to solve the contradiction between population shrinkage and regional development has become an urgent scientific problem. Therefore, taking a typical underdeveloped mountainous region, the North–South Transitional Zone of China, as an example, we analyzed the spatial and temporal evolution of regional population shrinkage from 2000 to 2020, classified the types of regional population shrinkage, and revealed the key influencing factors and driving mechanisms for the formation of population shrinkage patterns in poor mountainous counties. The results showed that: (1) From 2000 to 2020, the number of counties in the North–South Transitional Zone of China with population shrinkage grew, and the degree of shrinkage increased. The shrinking counties were mainly municipal counties, and the shrinkage types were mainly continuous shrinkage and expansion followed by shrinkage. (2) Spatially, the shrinking counties had significant and strengthening spatial autocorrelation, with obvious characteristics of the contiguous shrinkage of county units, and the shrinkage center of gravity and shrinkage agglomeration areas showed an evolutionary trend of shifting from east to west. The shrinking counties had obvious divergence in both the “east–west” and “north–south” directions. (3) Natural factors had an endogenous rooting role, while human factors had a strong driving role, and the impact of different influencing factors varied significantly. (4) The formation and evolution of the spatial pattern of county population shrinkage was subject to the synergistic effect of natural factors and human factors. The interaction between natural and human factors had a non-linear enhancement effect and a two-factor enhancement effect. The results of this study are expected to provide a scientific basis for coordinating regional human–land relations in order to optimize population-flow governance and sustainable regional development in the North–South Transitional Zone and less-developed regions of China.