Researchers and managers of natural resource conservation have increasingly emphasized the importance of maintaining a connected network of important ecological patches to mitigate landscape fragmentation, reduce the decline of biodiversity, and sustain ecological services. This research aimed to guide landscape management and decision-making by developing an evaluation framework to construct ecological security patterns. Taking the Jianghan Plain as the study area, we identified key ecological sources by overlaying the spatial patterns of ecological quality (biodiversity, carbon storage, and water yield) and ecological sensitivity (habitat sensitivity, soil erosion sensitivity, and water sensitivity) using the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) model and the Chinese Soil Loss Equation Function. Ecological corridors were obtained by the least-cost path analysis method and circuit theory. A total of 48 ecological sources (3812.95 km²), primarily consisting of water area, forestland, and cropland, were identified. Ninety-one ecological corridors were derived, with a total length of 2036.28 km. Forty barriers and 40 pinch points with the highest improvement coefficient scores or priority scores were selected. There were 11 priority corridors with very high levels of connectivity improvement potential and conservation priority, occupying 16.15% of the total length of corridors. The overall potential for ecological connectivity is high on the Jianghan Plain. Our framework offers a valuable reference for constructing ecological security patterns and identifying sites for ecological restoration at the regional scale.

In order to control the development of urban space, it is important to explore scientific methods to provide a reference for regional territorial space planning. On the basis of the minimum cumulative resistance (MCR) model and the cellular automaton (CA)-Markov model, we constructed a new technical method for delineating urban development boundaries, exploring the temporal and spatial distribution characteristic of land use in Wuhan from 2010 to 2020 through nighttime and remote sensing images, and simulating the urban development boundaries of Wuhan from 2025 to 2035. The results show that: (1) the scales of Wuhan City’s built-up areas in 2010, 2015, and 2020 were 500 km², 566.13 km², and 885.11 km², respectively, and the trends of expansion run to the east and southeast, and (2) on the basis of the MCR model, the urban development boundary scale of Wuhan City in 2025, 2030, and 2035 from the perspective of actual supply will be 903.52 km², 937.48 km², and 1021.44 km², respectively, and based on the CA-Markov model, the urban development boundary scales of Wuhan City in 2025, 2030, and 2035 from the perspective of ideal land demand will be 912.75 km², 946.40 km², and 1041.91 km², respectively. By combining the results of the two methods, we determined areas of 901.62 km², 944.39 km², and 1015.36 km² as the urban development boundaries of Wuhan City in 2025, 2030, and 2035, respectively. According to the principle of supply–demand balance, the urban development boundary delineated by the integration of the MCR model and CA-Markov model, which is in line with the spatial expansion trend of growing cities, could optimize the urban development pattern; solve the contradiction between urban development, farmland protection, and ecological protection; and provide a methodological reference and decision-making basis for planning practice.

Accelerated land use and land cover changes affect regional landscape patterns and change the ecological environment, including soil conservation capabilities. This is not conducive to the sustainable development of human society. In this research, we explored the land use change pattern and landscape change pattern in western Hubei from 2000 to 2020. Using the Chinese soil loss equation and stepwise regression, we measure how landscape patterns affect soil erosion under land use and cover changes in western Hubei Province. The results show that average soil erosion in the mountainous areas of western Hubei tended to increase from 2000 to 2010 and decrease from 2010 to 2020; soil erosion was higher in the western than in the eastern part of the study area. The land in areas with high-intensity and low-intensity soil erosion was mainly waterfront/grassland and cropland/forestland, respectively, and the area of moderate to severe soil erosion was greatest when the slope was 10–20°. When the slope exceeded 20°, the soil erosion area of each grade tended to decrease; thus, 20° is the critical slope for soil erosion in the study area. The landscape pattern in mountainous areas changed dramatically from 2000 to 2020. At the landscape level, landscape fragmentation increased and connectivity decreased, but the area of landscape diversity was stable. Soil erosion in western Hubei was positively correlated with the contiguity index, aggregation index and largest patch index but negatively correlated with the Shannon evenness index. The higher the landscape fragmentation and the greater the accumulation of single land-use types, the more severe the soil erosion is, while the higher the landscape connectivity and the richer the landscape diversity, the less severe the soil erosion is. The results can inform regional landscape management and soil conservation research.

Understanding the spatial pattern of soil chemical properties (SCPs) together with topological factors and soil management practices is essential for land management. This study examines the spatial changes in soil chemical properties and their impact on China’s subtropical mountainous areas. In 2007 and 2017, 290 and 200 soil samples, respectively, were collected in Hefeng County, a mountainous county in central China. We used descriptive statistics and geostatistical methods, including ANOVA, semivariance, Moran’s I, and fractal dimensions, to analyze the characteristics and spatial autocorrelation changes in soil organic matter (OM), available phosphorus (AP), available potassium (AK), and pH value from 2007 to 2017. We explored the relationship between each SCP and the relationship between SCPs with topographic parameters, soil texture, and cropping systems. The results show that the mean value of soil OM, AP, AK, and pH in Hefeng increased from 2007 to 2017. The spatial variation and spatial dependency of each SCP in 2007, excluding AP and AK in 2007, were higher than in 2017. The soil in areas with high topographic relief, profile curvature, and planform curvature had less AP, AK, and pH. Soil at higher elevation had lower OM (r = −0.197, p < 0.01; r = −0.334, p < 0.01) and AP (r = −0.043, p < 0.05; r = −0.121, p < 0.05) and higher AK (r = −0.305, p < 0.01; r = 0.408, p < 0.01) in 2007 and 2017. Soil OM and AK in 2007 were significantly (p < 0.05) correlated with soil texture (p < 0.05). In contrast, oil AP and soil pH in 2007 and all SCPs in 2017 were poorly correlated with soil texture. The cropping systems played an important role in affecting all SCPs in 2007 (p < 0.01), while they only significantly affected AK in 2017 (p < 0.05). Our findings demonstrate that both topological factors, that is, the changes in cropping management and the changes in acid rain, impact soil chemical properties. The local government should place more focus on reducing soil acid amounts, soil AP content, and soil erosion by improving water conservancy facilities.

The Yangtze River (YZR) regions have experienced rapid changes after opening up to economic reforms, and human activities have changed the land cover, ecology, and wildlife habitat quality. However, the specific ways in which those influencing factors changed the habitat quality during different periods remain unknown. This study assessed the wildlife habitat quality of the middle and lower YZR in the past (1980–2018) and in future scenarios (2050, 2100). We analyzed the relationships between habitat quality and various topological social-economic factors, and then mapped and evaluated the changes in habitat quality by using the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) model. The results show that the slope (R = 0.502, P < 0.01, in 2015), elevation (R = 0.003, P < 0.05, in 2015), population density (R = –0.299, P < 0.01, in 2015), and NDVI (R = 0.366, P < 0.01, in 2015) in the study area were significantly correlated with habitat quality from 2000 to 2015. During the period of 1980–2018, 61.93% of the study area experienced habitat degradation and 38.07% of the study area had improved habitat quality. In the future, the habitat quality of the study area will decline under either the A2 scenario (high level of population density, low environmental technology input, and high traditional energy cost) or the B2 scenario (medium level of population density, medium green technology and lack of cooperation of regional governments). The results also showed that habitat in the lower reaches or north of the YZR had degraded more than in the middle reaches or the south of YZR. Therefore, regional development should put more effort into environmental protection, curb population growth, and encourage green technology innovation. Inter-province cooperation is necessary when dealing with ecological problems. This study can serve as a scientific reference for regional wildlife protection and similar investigations in different areas.