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The construction of The Three Gorges Reservoir has changed land use structure and reconstituted landscape pattern as imparts significant influence upon the land use structure and ecological environment of Three Gorges Reservoir Regions. The ecological safety of reservoir area is extremely dependent on unique location and special geological conditions of Zhongxian County, the center of Three Gorges Reservoir Regions in Chongqing, and therefore, ecological environment of reservoir area will be changed with the transition of land use in Zhongxian County. Based on land use data in 2000, 2005, 2010, this paper chooses influencing factors from aspects of natural topographic and geomorphological conditions, accessibility to economic development and land use expansion, and then establishes Logistic-CA-Markov (Logistic-Cellular Automata-Markov) and WLC-CA-Markov (Weighted Linear Combination- Cellular Automata- Markov) models so as to simulate spatial pattern of land use of Zhongxian County. The results demonstrate that WLC-CA-Markov model established here has better controllability and higher simulation precision (the kappa coefficient is 0.9295). In the future development of Zhongxian County, the area of grassland and plow land will be reduced continuously, the area of construction land will be expanded obviously mostly because of the added area both near the water and in the north of Zhongxian county, the area of woodland will be increased to a little extent, the area of water area and unused land has gentle change. In the sustainable scenario, the area of grassland will be reduced slightly, the area of water area keeps steady, the area of plow land is reduced but higher than red line of plow land, the area of construction land is increased with significantly smaller increase amplitude than that in the natural development scenario, and the woodland is increased. This scenario coordinates ecological environment with economic development of regional society and turns out to be the best development scenario of land use.

Land use/cover change (LUCC) accompanied by climate change and human activities will have unpredictable impacts on watershed ecosystems. However, the extent to which these land use changes affect the spatial and temporal distribution of ecosystem services (ESs) in different regions remains unclear. The impact of LUCC on ESs in the Qingjiang Watershed (QJW), an ecologically sensitive area, and LUCC’s role in future ESs under different land use scenarios are crucial to promoting ecological conservation and land use management. This paper assessed water yield (WY), soil conservation (SC), carbon storage (CS) and habitat quality (HQ) using the InVEST model, and their responses to LUCC in the QJW from 1990 to 2018 using the geodetector and multiscale geographically weighted regression. We predicted land use patterns using the Logistic–CA–Markov model and their effects on ESs in 2034 under business as usual (BAU), ecological land protection (ELP), arable land protection (ALP) and ecological economic construction (EEC) scenarios. From 1990 to 2018, the area of cropland and woodland decreased by 28.3 and 138.17 km2, respectively, while the built-up land increased by 96.65 km2. The WY increased by 18.92%, while the SC, CS and HQ decreased by 26.94%, 1.05% and 0.4%, respectively. The increase in the arable land area led to a increase in WY, and the decrease in forest land and the increase in construction land led to a decrease in SC, CS and HQ. In addition to being influenced by land use patterns, WY and SC were influenced mainly by meteorological and topographical factors, respectively. In 2034, there was an obvious spatial growth conflict between cropland and construction land, especially in the area centered on Lichuan, Enshi and Yidu counties. Under four scenarios, WY and SC were ranked ALP > BAU > EEC > ELP, while CS and HQ were ranked ELP > EEC > BAU > ALP. Considering the sustainable eco-socio-economic development of the QJW, the EEC scenario can be chosen as a future development plan. These results can indicate how to rationally improve the supply of watershed ESs through land resource allocation, promoting sustainable regional development in mountainous watershed areas.

To satisfy an increasing need for living space and food while preserving ecosystem services remains one of today’s biggest challenges. Oases in arid areas have gradually become the main sources for new cultivated land, affecting the supply and transmission of ecosystem services. Yet, little assessment on predicting the effects of oasis expansion on ecosystem service value (ESV) has been available to guide policy makers and ecologists. Here we addressed the connections between oasis expansion and ESV in the middle reaches of the Heihe River Basin in northwest China by linking the Logistic-CA–Markov model and the benefit transfer method. The results showed that the oasis was expected to expand by 419.02 km 2 from 2015 to 2029, with the area of farmland and construction land increasing by 18.87% and 39.05%, respectively. With oasis expansion, the total ESV was expected to increase by 104.25 million RMB from 2015 to 2029. However, oasis expansion encroaches on vegetation, resulting in decline of the values of climate regulation, waste treatment, and biodiversity protection. This study will provide a reference for decision-making in trade-offs involved in land management.

Habitat quality is the key to regional ecological restoration and green development, and land use change is an essential factor affecting habitat quality. Studying the spatial and temporal evolution characteristics of land use change and habitat quality under multiple scenarios is significant for regional ecological restoration and management, and for preventing future ecological and environmental risks. We used the improved Logistic-CA-Markov (Logistic-Cellular Automata-Markov) and InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) models to establish the spatial patterns of habitat quality in the Yellow River Basin from 2000 to 2040 and analyzed the characteristics of land use and habitat quality changes under scenarios of natural development (S1), ecological protection (S2), and urban expansion (S3). The results showed that in 2000, 2005, 2010, 2015, and 2020, the main land use types in the watershed were dryland and grassland, accounting for more than 72%. Paddy land, dryland, woodland, middle-coverage grassland, and unused land all showed decreasing trends, whereas all other land types showed increasing trends. Influenced by human activities and the environment, the watershed habitat quality was low, with 80% of the areas with middle to low grades, but the overall trend was rising. The spatial variability in habitat quality of the watershed was significant, with habitat quality improvements in the central and northern regions and continued deterioration around the cities in the southern and western parts. The spatial autocorrelation and aggregation of habitat quality in the watershed were strong, and future land use patterns in the study area had a significant relationship with human activities. Simulation of future scenarios revealed ecological conservation catalytic effects on habitat quality in the study area, whereas urban expansion deteriorated watershed habitat quality. This study could provide support for future ecological conservation decisions.

The urban fringe is the transitional area from rural form to urban form, and it is also the urban space reserve land in the Territorial Spatial Plan. However, few researchers predict its overall evolution and guide the implementation of the Territorial Spatial Plan. This study attempts to explore the dynamic evolution law of urban fringe, analyze its driving factors, predict its future development, and put forward management suggestions for the implementation of the Territorial Spatial Plan. In this paper, the land use data of Wuhan in 2000, 2010 and 2020 are applied to delimit the urban fringe area of Wuhan by means of a sliding t-test. Fifteen driving factors are selected from three dimensions, natural factors, socio-economic factors and traffic accessibility, and brought into the Logistic model to explore the driving factors of its spatial evolution. The CA–Markov model is used to predict the fringe area of Wuhan in 2035. The results show that the transformation of rural hinterland into urban fringe is obviously affected by the distance from railway stations, highways, commercial centers and urban main roads. It is predicted that the outer boundary of Wuhan’s fringe area in 2035 will be basically the same as the planned urban development boundary. In order to realize the intention of land space planning, the development and construction of the northwest of the Huangpi District, the East Lake Scenic Area, and the west side of the Jiangxia District should be restricted. From the perspective of the evolution of the fringe area, this paper puts forward some management suggestions for the implementation of the Territorial Spatial Plan and makes a beneficial attempt in theory and method to understand the development characteristics of the fringe area and promote the implementation of the Territorial Spatial Plan.

Soil organic carbon (SOC) constitutes a critical component of carbon reservoirs within terrestrial ecosystems. The ramifications of urban land use transitions on SOC dynamics, particularly in rapidly urbanizing regions such as Shanghai, remain insufficiently elucidated. This investigation synergizes a predictive land use change model (Logistic-CA-Markov) with an ecosystem service quantification framework (InVEST), aiming to delineate the interplay between SOC variability and Land Use and Land Cover Change (LUCC) under natural development and ecological protection scenarios. Empirical observations from 2010 to 2020 reveal a contraction in Shanghai’s agricultural land of 34,912.76 hectares, juxtaposed with an expansion of urban built-up areas of 36,048.24 hectares. Projections for 2030 under an ecological protection scenario indicate a moderated urban sprawl, reducing built-up area expansion by 13,518 hectares relative to the natural development scenario. Notably, the net carbon sequestration capacity of Shanghai is anticipated to diminish by approximately 0.418 million tons between 2020 and 2030. This trend is observed under both considered scenarios, forecasting a cumulative reduction in SOC stocks exceeding 1 million tons by 2030. The natural development pathway portends a more pronounced and accelerated depletion of SOC reserves. Although ecological conservation measures show the potential to decelerate this loss, they appear insufficient to reverse the ongoing decline in SOC stocks. This study advocates for strategic urban planning interventions focused on constraining the growth of building densities and augmenting the preservation and management of eco-lands. Such measures are imperative for bolstering Shanghai’s carbon sequestration capacity.