Search

The carbon emissions stemming from land use in adjacent areas exert a significant influence on the ecological balance of natural reserves. Examining carbon emission patterns linked to land use enables a deeper understanding of carbon dynamics in adjacent regions, thus safeguarding the functional integrity of natural reserves as vital carbon sink zones. This study focused on the protection and development belt of Wuyi Mountain National Park,11 For convenience of presentation, the protection and development belt of Wuyi Mountain National Park is abbreviated in the article as “the Belt”. a typical adjacent area of a nature reserve. Through the integration of spatial and statistical data, it examined the intensity and distribution characteristics of carbon emissions from 2000 to 2020. Additionally, the study employed the PLUS model to forecast land use trends and overall carbon emissions across various scenarios, including natural development, carbon sink enhancement, and carbon source control, for the years 2030 and 2060. Results indicated: (1) Between 2000 and 2020, the total carbon absorption capacity of the protection and development belt of Wuyi Mountain National Park showed a diminishing trend, contrasting with the rising trend in total carbon emissions; (2) In the vicinity of the natural reserve, there was discernible spatial variation in carbon emissions associated with land use. The eastern regions exhibited elevated emissions, whereas the southern regions demonstrated comparatively lower emissions. The extent of carbon sources continued to grow, with areas exhibiting low, medium, and high carbon emissions all displaying expansion tendencies. Areas with robust carbon absorption capacities consistently showed a decreasing trend; (3) Across all three scenarios, land allocated for construction emerged as the predominant source of carbon emissions. Notably, the carbon source control scenario exhibited the smallest net carbon emissions from land use, underscoring the significance of carbon reduction as the fundamental strategy for achieving carbon neutrality goals. This research can offer insightful experience for simulating land use patterns and estimating carbon emissions in adjacent areas with similar nature reserves, contributing to the proposal of targeted carbon neutrality policies and management measures, thereby facilitating the transition of nature reserves and their surrounding areas towards a low-carbon development path.

Currently, land use simulation and optimization show a trend towards spatialization and intelligence. However, regional land use simulation and optimization often neglects the inherent uncertainty of the land use system and the actual impacts of land use practices on the ecological environment. Therefore, this study established a coupled land use simulation and optimization model based on ecosystem services and economic development, which integrates the ecosystem service evaluation model (InVEST), the interval uncertainty optimization model, and the spatial layout model of land use (PLUS), to simulate and optimize the land use allocation planning practice of Dongting Lake Ecological and Economic Zone in 2030. The objective of the coupled model is to aim at realizing regional ecological benefits and socio-economic benefits while taking into account the ecosystem service function constraints (water production, water conservation, soil and water conservation, and carbon storage), environmental protection constraints (air, water, and solid waste pollution), economic constraints (water use limitation, electricity use limitation), social constraints (food safety, fertilization), and technological constraints (total land area). economic benefits of the region. The modeling results show that the economic benefits of the optimized Dongting Lake Eco-Economic Zone range between [15622.72 × 108,19150.50 × 108] CNY, and the optimized areas of farmland, woodland, grassland, water area, construction land, and unutilized land are[25686.99,25932.61]km2, [22093.37,22295.23]km2,[837.11108,841.41]km2,[7536.86,7767.01]km2,[2660.92,2987.49]km2,[1090.72,1116.36]km2.and the ecosystem service function, pollutant emission level and ecosystem service value of the optimized Dongting Lake Eco-Economic Zone in the optimization scenario, which guarantees higher economic benefits than the status quo scenario, show a better performance than the status quo scenario as a whole. Finally, by spatially allocating the optimization results, the coupled model provides a new perspective and tool for decision-makers to develop sustainable regional land use planning.

Wetlands are among the most productive ecosystems and play crucial roles in relation to biodiversity conservation and various ecosystem services. However, rapid urbanization and environmental changes have led to the loss of a significant number of wetlands, making it imperative to understand the driving forces behind wetland changes. This study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) and the Patch-generating Land Use Simulation (PLUS) model to investigate the influences of natural factors and urbanization on wetland distribution. Based on the driving factors, simulations were conducted for three scenarios—Natural Increase Scenario (NIS), Economic Development Scenario (EDS), and Wetland Protection Scenario (WPS)—projecting the wetland distribution in the Sanjiang Plain until 2050. Results indicate that from 1990 to 2020, the wetland area increased by 9,548.58 km2, with paddy fields increasing by 12,995.73 km2 and marsh wetlands decreasing by 1,031.9 km2. The factors driving wetland distribution varied across different periods. Between 1990 and 2000, topography and urbanization significantly influenced wetland distribution, whereas climate factors became gradually more significant between 2010 and 2020. Furthermore, in addition to exerting direct impacts on wetland distribution, urbanization and climate factors can indirectly affect wetland distribution by influencing topography and soil. Future development scenarios indicate an inevitable increase in paddy field areas and decrease in wetland areas. This framework provides an effective approach for exploring regional wetland changes and supporting regional wetland conservation and future sustainable development.

The Qinghai-Xizang Plateau (QXP), the highest plateau in the world, boasts a diverse array of ecological landscapes shaped by extreme climatic conditions; however, it is currently facing significant ecological challenges. In recent years, an increase in human activities, particularly the expansion of the human footprint and grazing intensity, has significantly exacerbated the pressures on habitat risk in the region. In this context, the future habitat risk trend under different scenarios on the QXP require further investigation. To address this gap, a comprehensive multi-scenario habitat risk prediction methodology was developed to fill this gap by integrating the InVEST model, the patch-generating land use simulation model, and the multilayer perceptron model, which combined land use and land cover data with human footprint index and grazing intensity data for a thorough assessment and prediction of habitat risk. Specifically, spatiotemporal changes in habitat risk on the QXP from 2000 to 2020 were analyzed, future indicators were projected, and spatiotemporal variations in habitat risk were evaluated under multiple scenarios. The findings indicate that high-risk areas experienced a significant increase of 39% in 2005; however, this was subsequently mitigated by protective measures. In the Ecological Protection scenario, high habitat risk was reduced by over 74%, while the Urban Development scenario saw an increase of 81% in high habitat risk. The alterations in habitat risks observed between 2005 and 2010 indicate that ecological conservation efforts on the Qinghai-Xizang Plateau have been effective. Among the various development pathways, the Ecological Protection scenario appears to be the most viable for the QXP. Nonetheless, the central and eastern regions of the QXP may continue to face an upward trend in habitat risk.

The comprehensive effect of multi-source factors has altered the landscape pattern and ecological processes within the Beijing-Tianjin Sandstorm Source Control Project (BTSSCP) area, resulting in a fragile environment. Scientific evaluation of the landscape ecological risk (LER) in the project area and identification of the drivers of landscape ecological risk are crucial for preventing and resolving ecological risks and protecting the ecosystem in northern China. This study aims to establish an ecological risk assessment framework, analyze the spatiotemporal changes in the LER in the BTSSCP area from 2000 to 2020, evaluate different factors in depth using the Geodetector model, and predict the LER in 2030 under multiple development scenarios using the patch-generating land use model. The results showed that (1) the dominant land use type in the BTSSCP area was grassland, accounting for more than 50 % of the total area, followed by cropland, unused land, and woodland. (2) The average LERI values in the BTSSCP area for 2000, 2010, and 2020 were 0.023, 0.022, and 0.021, respectively. This demonstrates that the LER in the study as a whole was low and steadily declined. (3) The LER in the project area was influenced by multiple factors. Overall, the evolution of the LER in the study area was primarily affected by natural factors, and the amount of interaction among the multiple factors increased over time. Locally, the normalized difference vegetation index and mean annual temperature were both important factors in this area.

Land use change in emerging nations raises landscape ecological risks (LERS), hastens the deterioration of urban and rural ecosystem services, endangers human well-being, and undermines sustainable development in the face of rapidly increasing urbanization. Here, using the Chengdu Plain as the study area and long time series data from 2000 to 2020, the optimal time span is selected for multi-context spatio-temporal simulation. The land use map of Chengdu Plain in 2025 under the four scenarios of “Natural Development” (ND), “Economic Priority Development” (END), “Ecological Priority Development” (ELD), and “Sustainable Development” (SD) was simulated, and the multi-indicator landscape ecological risk index (ERI) was generated to compare and analyze the differences between land use and landscape ecological risk under different policy preferences. Subsequently, the land use data from 2025 to 2040 were simulated, the landscape ecological risk pattern was mapped, and the spatial and temporal evolution analysis from 2010 to 2040 was conducted to explore the spatial evolution law of land use change and landscape ecological risk. Based on the results, the high ecological risk aggregation areas are prone to appear in END scenarios, whereas medium-ecological risk aggregation areas are more likely to appear in ELD scenarios, and the government should focus its policy on arable land protection. Moreover, the land use pattern of cultivated land surrounding construction land and forested land surrounding cultivated land, caused by the irrational single-core development pattern and the policy of returning farmland to forests, has exacerbated the landscape ecological risk of the Chengdu Plain, constituting a unique landscape ecological risk pattern. It’s also important to remember that the Chengdu Plain’s less economically developed regions need to focus on the high-quality development of ecological land use. We adopted high-precision simulation methods to simulate the complex land use changes in rapidly urbanizing areas and explored the spatial evolution law and causes of landscape ecological risk evolution in the context of land use changes, with the intention of offering a solid theoretical foundation for such areas’ future planning in developing nations.

Carbon storage in terrestrial ecosystems varies with land use changes, and exploring the impact of land use changes on carbon storage in regional terrestrial ecosystems is important for maintaining regional carbon balance. Data on Dalian City’s land use types from 2000 to 2020 are used in this research, to evaluate the spatio-temporal evolution of carbon storage in Dalian. Furthermore, with the scenarios of urban development, natural development, cultivated land protection, and ecological protection in 2030, this study combines the PLUS and InVEST models to emulate the dynamic adjustment at land-use types and the spatio-temporal evolution regarding carbon storage in Dalian City. The investigation shows that: 1) The carbon storage of terrestrial ecosystem in Dalian has been altered as a consequence of changes in land use, and now it shows a general decline during 2000–2020, with reductions amounting to 5.39 × 106 t. 2) From 2000 through 2020, Dalian’s land resources that are utilized for farming, forestry, and grassland decreased to different degrees. The total construction land area increased by 796.47 km2, or 6.38 %, whereas there has been no substantial improvement in water or unused land. 3) The carbon storage reduction in 2030 in comparison to 2020 for the natural development, cultivated land protection, and urban development scenarios, among which the urban development scenario was the largest, was 1.36 × 106t. It suggests that the rapid rate of urbanization and expansion of construction land is an important cause of the decline in carbon storage. 4) The cultivated land protection scenario (CPS) yields the smallest reduction of 6.50 × 105t. The structure of Dalian’s land use type is optimum under the ecological protection scenario (EPS), as seen by the 3.90 × 105t increase in carbon storage under this scenario. It speeds up the rate of recovery of carbon storage and improves the function of carbon sinks in urban terrestrial ecosystems. Hoping to provide the reference to decision makers for ecosystem carbon storage optimization from the view of land use, which is vital for making future land use policies and realizing the “dual carbon” strategic goal.

With the development of the social economy, ecological environment damage has become increasingly serious, and how to better protect ecological security has gradually attracted people’s attention. This paper takes Hubei Province in China as the research object, using the PLUS model version 1.4 to design four development scenarios to predict land use and land cover changes (LUCC) in 2035: the natural development scenario (S1), the cultivated land protection scenario (S2), the ecological protection area restriction scenario (S3), and the ecological security pattern (ESP) restriction scenario (S4). The study evaluates the ecological effects under these four different scenarios using Conefor Sensinode 2.6 software, Fragstats v4.2.1 software, and the InVEST model. The conclusions are as follows: (1) ESP has better ecological landscape connectivity. (2) Comparing the ecological security indices of the four scenarios, they are 0.5378, 0.5288, 0.5318, and 0.5405, respectively, with the S4 scenario showing the best protection effect. (3) Comparing the habitat quality of the four scenarios, high-grade habitats degrade under S1 and S2 scenarios; homogenization occurs under S3 and S4 scenarios, but the retention rate of high-grade habitat areas is the highest under the S4 scenario. In conclusion, compared to natural progression and prioritizing cultivated land protection, implementing ecological protection policies yields better ecological effects, and a planned ESP provides more targeted policy recommendations.

Land-use changes dominated by high-intensity human activities have seriously threatened regional ecosystem health (EH) and will continue to increase in the future, especially in mountainous cities. Therefore, there is a need to systematically assess the contribution and spatial effects of future land use conversion on EH from a multi-scenario simulation perspective, which is essential for ecological conservation and management. For this purpose, taking Chongqing as an example, this study assessed the static distribution and dynamic evolution of EH over historical periods (2000–2020) and future multi-scenarios in 2030 using the vigor-organization-resilience-ecosystem services balance (VORSB) framework and patch-level land use simulation (PLUS) model, then analyzed the influence of land use conversion on EH and identified sensitive areas under multiple scenarios based on the contribution index and ecological sensitivity index. The results showed that Chongqing ecosystems were generally at a moderate healthy level during 2000–2020, with an increasing trend in EH level, with high-EH located in the eastern mountainous areas, while low-EH clustered in the western urban core and its peripheral areas. From 2020 to 2030, the EH level was improved by about 0.21% under the ecological protection scenario due to the transformation from farmland to forestland, which has the largest positive contribution of 0.111. In contrast, the EH level under the natural development and economic development scenarios declined by 1.95% and 3.07%, especially in the metropolitan developed circle, which was significantly related to the occupation of farmland resources by urban land, with negative contribution of −0.103 and −0.189, respectively. In the future, these regions should strictly control the urban expansion scale and strengthen high-quality farmland protection to achieve the balance of ecological protection and economic development. The findings will provide scientific guidance for the regional ecosystem conservation, land use planning, and urban sustainable development of mountainous cities.

Changes in land-use patterns are the main driving factors of ecosystem service values (ESVs). The quantitative evaluation of ESVs is significant for the sustainable development of ecologically fragile areas. In this study, the Chishui River Basin (CRB) in China was selected as the study region, and an intensity map (IM) was used to analyze the transformation of land use/land cover (LULC). The modified equivalent coefficient value method was used to evaluate the ESVs based on the 2000, 2010, and 2020 land use datasets. The spatial and temporal distributions of ESV and its response to changes in LULC were analyzed using the Getis-Ord Gi* statistical method and Spearman’s rank correlation analysis. Moreover, spatial and temporal changes in LULC and ESV over the next 30 years in the four development scenarios were simulated using the Markov-PLUS model. The following results were obtained: 1) The farmland and forestland were the dominant LULC categories, and that the LULC pattern dramatically changed in the study area; 2) the total ESV of the CRB decreased significantly from 23.21 billion yuan in 2000 to 22.29 billion yuan in 2020; and 3) the ecological conservation scenario significantly promoted the total ESV, and the town development scenario was more conducive to the urbanization process. Therefore, although the ESV of the CRB showed a decreasing to slowly increasing trend in the context of a series of ecological restoration measures, scientific ecological protection and development policies must be continuously implemented to achieve harmony between ecological service improvement and urbanization development. Our results provide important information for making land-use decisions and facilitating sustainable development in ecologically protected basins.

Land use and cover change (LUCC) is a major driver of this rapid increase in atmospheric carbon. To reasonably plan various types of land use areas and mitigate the rate of growth of carbon emissions, this study takes Yaan, Sichuan province, as a case study. First, the calculation of Yaan's land use carbon emissions (LUCE) was approached by taking land use structure into account. Subsequently, the spatiotemporal distribution of LUCE was evaluated by employing the carbon emission risk index and the Moran index. Finally, the multi-objective linear programming (MOP), the Markov chain, and the PLUS model were used to predict the spatial distribution of LUCC in 2030, including natural development scenarios (NDS) and low-carbon optimization development scenarios (LODS). According to the findings, the impervious surface is identified as the principal contributor to LUCE, while the forest is recognized as the principal absorbers of carbon. The carbon emissions in typical mountainous areas are distributed in cities and generally concentrate towards the plains in the northeast direction. Under the LODS, LUCE decrease significantly. For both NDS and LODS, the overall trend of land development direction in Yaan is “northeast-southwest” from 2020 to 2030. These results could provide some suggestions for low-carbon land use in cities like Yaan.

The research refers to the features of production-living-ecological land use transformation in the Zhengzhou metropolitan area from 1990 to 2020, applies the PLUS (patch-generating land use simulation) model and ESV(Ecosystem Service Value)accounting to set three scenarios, and analyzes the spatiotemporal features of ecosystem service value via multi-scenario simulation, aiming to provide technical support to territorial spatial planning and ecological restoration. The results show that: (1) From 1990 to 2020, agricultural production land has the highest transform volume; the supply, regulation, and cultural services along the Yellow River continued to increase, while support services continued to decrease in the metropolitan areas of Zhengzhou and Xinzheng. (2) Compared with 2020, the supply and regulation services under the ecological protection scenario show an upward trend, and the comprehensive benefits of ecosystem services reach the best. (3) The ecological protection scenario reduces the probability of converting ecological land into living land, making the total ESV grow constantly.

Water bodies provide humans with important hydrological ecosystem services (HESs), directly or indirectly. Water yield, water conservation, and soil conservation are essential to HESs. Since China's reform and opening up, and with its rapid socio-economic development, land use in Jiangxi Province has undergone drastic change, resulting in threats to the ecological environment. This paper evaluates three HESs, water yield, water conservation, and soil conservation, in Jiangxi Province based on land use and rainfall data, quantifies the impacts of different land classes on each ecosystem, predicts future land use using the patch-generating land use simulation (PLUS) model, and finally, discusses the ecological risks in the study area. The following results were obtained: (1) The HESs in the basin increased and then decreased from 2000 to 2020, and the spatial distribution of water yield and water conservation was greatly influenced by rainfall. Soil conservation was mostly consistent with the elevation distribution. (2) Over time, the overall aggregation of HESs in the study area increased. There were small differences in the effects of various land uses on water yield and water conservation, and large differences in the effects on soil conservation. (3) The distribution of ecological risks was not affected by different land use strategies, with the lower ecological risk level 1 dominating. Most risk areas were present in Ganzhou, Ji'an, Shangrao, and Jiujiang. The ecological risk from urban sprawl (US) accounted for the most significant proportion, and that from the ecological protection (EP) strategy accounted for the lowest proportion. This study provides reference for sustainable land use development and ecological risk prevention in the study area.

The scientific determination of crucial regions for ecological land restoration and reasonable early warnings for ecologically weak areas are vital for implementing land ecological restoration. Five major plateau lake basins in central Yunnan (China) are selected as the study area in this research. An ecological security pattern (ESP) is constructed using the source-resistance surface-corridor-pinch point framework to effectively identify crucial areas for ecological restoration. Finally, the land use/cover change (LUCC) in the study region in 2030 is simulated in terms of the natural development prospect (NDP), with priority given to urban development (PUD) and priority given to ecological protection (PEP) scenarios, and identify areas where future urban expansion poses a threat to current ecological source areas and corridors as early warning regions. The results indicate the following: (1) There are 15 ecological source regions in the Five Lakes Basin, mainly forestland and waters, with a total area of 787.54 km2. The ecological corridor spans 245.72 km, with a total area of 439.90 km2. (2) The key ecological restoration areas include 72.87 km2 of ecological pinch points, 70.46 km2 of barrier points of ecological, and 71 breakpoints. (3) The ecological land under the NDP scenario and the PUD scenario were damaged to varying degrees. The ecological land dominated by forestland and water area under the PEP scenario is effectively protected. (4) The seven ecological protection space early warning points are mainly distributed in the eastern part of Dianchi Lake and the northern part of Fuxian Lake, which have good economic development and better habitat quality. The comprehensive analysis identified key ecological restoration areas and identified future ecological stresses due to land use change in the Five-Lakes Basin. Restoration strategies are proposed based on current land use and future scenarios to enhance the ESP in central Yunnan's Five Lakes Basin.

Accurately assessing future land use/cover change (LUCC) and habitat quality (HQ) is vital for ensuring sustainable use of coastal ecosystem services, but most studies ignore the effects of seawater inundation. This study developed a framework based on the PLUS model and InVEST-HQ model that considers seawater inundation due to sea level rise (SLR) and land subsidence. We used this framework to simulate future LUCC and HQ under different scenarios in the Yellow River Delta (YRD). The results showed: (1) From 1991 to 2020, natural wetlands decreased by 39.87 %, non-wetlands decreased by 3.06 %, and artificial wetlands increased by 730.71 %. The overall HQ showed a decreasing trend, with the largest decrease in non-wetlands. (2) Land subsidence occurred in 93.26 % of the YRD, with a subsidence rate of −36.55 mm/year. Underground brine mining is the most important driving factor. About 6.81 %∼11.16 % of the area will be inundated in 2035, and about 9.39 %∼19.27 % of the area will be inundated in 2050. (3) Future multi-scenario simulations show that the Ecological-Protection scenario can minimize the ecological losses caused by seawater inundation. The simulation of future HQ will be underestimated when seawater inundation is not considered. Our study shows that seawater inundation caused by land subsidence and SLR must be taken into account when simulating LUCC and HQ in coastal areas.

A scientific understanding of the trends of water-related ecosystem services (WESs) under different scenarios is crucial to improving WESs and maintaining ecological security. However, there is a lack of high-resolution land use simulation and assessment of WESs under the SSP-RCP scenarios, and the impacts of different land-use change (LUC) on WESs are not clear. This study focused on the Poyang Lake Basin (PYLB), utilizing the SSP-RCP scenarios, the PLUS model and the InVEST model to explore the dynamic changes of land use and WESs historically and in the future, and to reveal the impacts of specific LUC on WESs from 2000 to 2020. The results demonstrated that: (1) The forest land increased under both SSP1-2.6 and SSP2-4.5 scenarios but increased first and then decreased under SSP5-8.5 scenarios; Cropland increased significantly under SSP5-8.5 scenarios, and the construction land showed an expansion trend under the three scenarios. (2) From 2000 to 2020, only the water purification capacity decreased, while the rest of the WESs increased. Under the SSP1-2.6 scenario, the overall benefits of the WESs in the PYLB were the highest. (3) Between 2000 and 2020, deforestation in the PYLB brought about the greatest increase in the water yield (+9.06 × 108 m3). The increase in the construction land brought about the most water conservation loss (−18.19 × 108 m3). Additionally, the forest expansion and cropland reduction brought about the largest increase in soil retention (+3.94 × 105 t and +4.79 × 105 t) and enhanced water purification, and the opposite was true for deforestation. The conclusions can provide an important basis for the ecological protection and high-quality development of the PYLB.

Urbanisation affects the health and stability of ecosystem significantly. Constructing a scientific ecological security pattern (ESP) is of paramount importance for safeguarding the health of ecosystems within a region, optimising ecological spaces, and ensuring sustainability. To investigate the effect of urbanisation on the ESP, we utilised the Vigour–Organisation–Resilience-Services (VORS) model to analyse the changes in ecosystem health (EH) and identify degraded areas in the city of Chengdu. In this case study. We used the Patch-generating Land Use Simulation (PLUS) Model to predict the urban expansion trends in 2035 and evaluate the changing ESP. Additionally, we used the minimum cumulative resistance (MCR) model and circuit theory to construct an ecological network to facilitate multilayer planning of ESP. We identified an ecological source area of approximately 4484.29 km2 and a recovery zone of 1608.35 km2 for managing EH degradation within the ecological source. An ecological conservation zone of 987.48 km2 with restricted development outside the ecological source, and a restoration zone of 71.66 km2 to mitigate the impact of urban expansion on ecological security were also identified. Seven stable corridors with consistent spatial patterns and pressure levels and six potential corridors await restoration. Based on the analysis of changes in ecosystem health and dynamic ESPs, different scenarios were simulated for 2035. The findings suggested significant variations in EH and ESP around 2010 despite rapid expansion in Chengdu. The ecological environment was partially restored by increasing the land area and controlling its contraction. Therefore, scientific planning of ESPs, limiting the boundaries of urban expansion, and accurately assessing the health of ecosystems are crucial for ensuring ecological security.

The rapid growth of gross domestic product (GDP) in developing countries may lead to the overconsumption of ecosystem services (ESs). This situation presents as the imbalance of ecological conservation and economic development, as is the case in areas of West China, such as Guiyang city. This study utilized the PLUS model to simulate future land use/land cover (LULC) scenarios and the InVEST model to assess the ESs in relation to rapid GDP growth in Guiyang city. The research findings reveal the following: 1) the growth of developed land contributes to ecosystem degradation and increased potential ecological hazards. The implementation of GDP growth policies may be the potential driver of land use change and a factor influencing changes in ESs. For example, between 2010 and 2020, the area of developed land increased by 339%, but the soil retention and carbon storage decreased by 2.04% and 3.26%, respectively. 2) The changes in GDP and ESs showed spatial heterogeneity. From 2020 to 2030, the general hot spot distribution of ESs and GDP was consistent, which was closely related to land use change. 3) Trade-offs and synergistic effects exist between GDP and ESs, including a trade-off between GDP and soil retention and synergy between GDP and water yield. GDP growth comes at the expense of ESs. The study emphasizes the need to prioritize ecological conservation in the degraded areas of southern Guiyang city. It urges stronger management of ecological redlines, stricter construction land policies, and a balanced approach to economic development and ecological protection.

Since the changes in paddy areas would significantly affect food security and agricultural sustainability, it has received worldwide attention guided by the United Nations 2030 Sustainable Development Goals. However, the process of paddy field change was complex, which was affected by both climate change and anthropogenic activities. Most existing studies focused on the spatial–temporal evolution of paddy field in different regions, while the quantitative separation of climatic and anthropogenic contributions to paddy field expansion was rare but imperative. This study adopted the patch-generating land use simulation (PLUS) model to simulate the paddy field expansion under different scenarios. Based on satellite-based land use data, meteorological data, socioeconomic data, physical geographical data, and transport data, it proposed four indicators, including ACI (anthropogenic contribution index), CCI (climatic contribution index), RII (relative importance index), and CEI (combined effects index) to quantitatively disentangle the climatic and anthropogenic contribution at different scales, and further determined the relative importance and combined effects of climate change and anthropogenic activities. These indicators were applied to the case of northern Sanjiang Plain of China and found that the total area of paddy fields in this area expanded greatly from 2638.88 km2 in 1995 to 19363.80 km2 in 2020. 1) At the regional scale (the northern Sanjiang Plain of China), the effect of climate change was slightly larger than that of anthropogenic activities on the paddy field expansion, with an inhibitory interactive effect of climate change and anthropogenic activities. 2) At the city scale (Hegang, Jiamusi and Shuangyashan), the effect of climate change was slightly stronger than anthropogenic activities in Hegang and Jiamusi, whereas Shuangyashan was the opposite. 3) At the county scale (15 counties), paddy field expansion of the central NSP was dominated by anthropogenic activities, while the northern part was disturbed more by climate change. 4) At the grid scale (30-m resolution), 51.17% of the grids had anthropogenic activities contributing more than climate change to paddy field expansion, and 88.60% of the grids presented an inhibitory interactive effect of climate change and anthropogenic activities. Thus, the indicators established for in this study can not only provide a better understanding of the relative effects of climate change and anthropogenic activities on paddy field expansion, but also give some policy implications for sustainable agricultural practice in both China and other developing countries.

The ecosystem services value (ESV) is an important basis for measuring ecological environment quality and efficient management of ecosystems. Although there have been many studies devoted to the measurement of ESV, the research on the key influencing factors of ESV and the prediction of future development scenarios is still limited. This study coupled the Deep Forest model and Patch-generating Land Use Simulation (PLUS) model to identify the key factors of ESV, and simulated the change trend of ESV under the Shared Socioeconomic Pathways (SSPs). Taking the cluster cities around the Yellow River floodplain area as the research object, this study quantitatively analyzed the spatiotemporal evolution characteristics of its ESV from 2000 to 2020, and identified the key factors affecting ESV using the Deep Forest model. The results showed that: (1) The ESV showed an overall upward trend from 2000 to 2020, with strong spatial heterogeneity; (2) The key factors affecting ESV were construction land ratio, distance to railway, SHDI, etc.; (3) The best development pathway of ESV in 2025, 2030 and 2035 would be SSPs5, SSPs2 and SSPs4 respectively. This study can provide theoretical support for the management of maximizing the overall benefits of ecosystem services in the study area.

Ecological carrying capacity is key to evaluating sustainable development capacity, and land use change has varying degrees of impact on ecosystems. This study explores the ecological carrying capacity based on land use change, which is important for the conservation and scientific and rational use of ecosystems. Therefore, in this study, three machine learning classification 3algorithms, namely support vector machine, random forest and artificial neural network, were selected for accuracy comparison and analysis based on multi-source data, using Southwest Guangxi Karst-Beibu Gulf as the study area. The Patch-generating Land Use Simulation Model is used to dissect the spatial and temporal changes in ecological carrying capaciyt from 1990 to 2040 and future trends. The results showed that (1) Coupling multiple sources of data and machine learning classification algorithms can ultimately improve land use classification accuracy. The RF is compared and found to be the optimal classification algorithm for this study. (2) The area of arable and grassland gradually decreases between 1990 and 2040, mainly encroached upon by build land; the area of forested land gradually recovers, the watershed fluctuates up and down, and the area of build land gradually increases. (3) The ecological carrying capacity from 1990 to 2040 shows a trend of decreasing and then increasing, and the area of low and medium–low decreases from 2020 to 2040, with arable land and forest land having a stronger potential to increase ecological carrying capacity. Nanning City, Qinzhou City and Chongzuo City are severely damaged. The framework provides an effective tool for exploring future ecological carrying capacity to support the ecological conservation and future sustainable development of the region.

The carbon storage service of terrestrial ecosystems has an veritable impact on the global carbon cycle and, in turn, on global climate change. Hence, both assessing and predicting the impact of land use changes on carbon storage are necessary to reduce carbon emissions and mitigate climate change. Therefore, using integrated valuation of ecosystem services and tradeoffs (InVEST) model with remote sensing data, this study systematically analyzes the land use/cover change (LUCC) and the carbon storage response characteristics of land types in Henan Province, China in the 1990–2020 period. The study also uses patch-generating land use simulation (PLUS) model to predict the LUCC and carbon storage in Henan Province from 2023 to 2050 under different scenarios, including Business as Usual (BAU), Ecological Conservation (EC), and Urban Development (UD) scenarios. The following results are noted: (1) The LUCC mainly comprises the conversion of farmland to construction land. Presently, Henan Province’s carbon storage is found to have decreased by 339.72 Tg due to LUCC, which is characterized as “high in the west and low in the east.” (2) Regarding the three aforementioned scenarios, the province’s construction land is predicted to increase to its greatest extent under the UD scenario. Under the EC scenario, its woodland and farmland areas will be effectively protected. Therefore, the highest level of carbon reserves will likely be found in the EC scenario, followed by that in the BAU scenario, while the lowest level of carbon reserves should be seen in the UD scenario. The carbon reserves of Henan Province in 2050 will be 312.07 Tg, 233.43 Tg, and 394.49 Tg lower than that in 2020 under the BAU, EC, and UD scenarios, respectively. In sum, this study provides the scientific basis of the decisions aimed at the facilitation of low-carbon development, the optimal utilization of land spaces, and the development of an ecological civilization in Henan Province.

Carbon dioxide emission is an important driving factor of global warming and it has threatened the ecological environment and human survival. Among them, land use has led to significant carbon emissions that profoundly affect climate system change. The Yellow River Basin (YRB) is one of the regions with the most concentrated contradictions in population, resources, and environment in China; thus, studying the current situation and land use carbon emissions (LUCE) is significant for mitigating global warming, promoting coordinated emission reduction among different regions in the basin, and achieving ecological conservation and high-quality development of the YRB. This study based on land use and socio-economic data, and is carried out from the perspective of social network analysis. The spatiotemporal variation of LUCE in the YRB was analyzed using the carbon emission coefficient method. The spatial spillover effects of LUCE were discussed using social network analysis methods. The PLUS model was used to simulate the differences in LUCE under different scenarios. The results indicate that: (1) The LUCE in the YRB showed an increasing trend during the study period, with significant differences in spatial distribution. (2) There is a significant spatial spillover effect and correlation between cities in the YRB LUCE network, and cities with superior economic had a greater impact on other cities. (3) In 2030, under the ecological protection scenario, the LUCE in the YRB were the lowest, with a reduction of 2.7 × 106 tons compared to the natural development scenario, further illustrating the importance of ecological land. Compared with previous studies, this study explores the spatial correlation between LUCE in various cities of the YRB from a new perspective of social network analysis. On the other hand, it makes land use prediction for 2030 by setting different land use development scenarios. The research results have broadened the application scope of social network analysis methods, and have important practical significance for promoting carbon reduction in major river basins and scientifically formulating land use policies.

As one of the world’s critical ecological regions – often called the “Third Pole” – the Qinghai-Tibet Plateau (QTP) has outstanding ecosystem service values (ESV). However, its variable climate and fragile environmental conditions make it vulnerable to disturbance by human activities. Based on land use data from 2000, 2010, and 2020, we developed three simulated scenarios of land use distribution on the QTP: business as usual (BAU), farmland protection (FP), and ecological protection (EP). Finally, we employed the Sharpe Index to evaluate ecological risk across the QTP. The results showed that from 2000 to 2020, land use change was mainly in the form of conversion of grassland to unused land, totaling an area of 63,717 km2. The ecosystem service value showed an increasing trend, from US$752.6 billion to US$783.0 from 2010 to 2020. The simulation results from the three scenarios revealed significant differences. Farmland area shows a declining trend in both the EP and BAU scenarios, while exhibiting an increasing trend in the FP scenario. Forest area on the plateau experiences a decreasing trend in the EP and BAU scenarios, but shows an increase in the FP scenario, predominantly in the southeastern region, including Sichuan and Yunnan provinces. The ecological risk assessment results indicate that the eastern region has higher ecological risk compared to the western region, highlighting the western region as a priority area for risk control. The expansion of built-up land and unused land has had significant impacts on regional ecological risk. Integrating risk assessment outcomes with land use planning to identify focal areas can provide guidance for the sustainable development of this globally important ecoregion.

Many studies on mitigation of the surface urban heat island (SUHI) are conducted from the perspective of landscape patch allocation, and few studies have investigated the overall impact of network connectivity on SUHI. In this study, an ecological network framework is proposed to identify the key patches and cooling corridors. Based on surface temperature inversion data, morphological spatial pattern analysis (MSPA) and landscape connectivity indexes are used to identify heat island and cold island patches with high ecological value on which to construct the network. The innovative patch-generating land use simulation (PLUS) model is introduced to construct a resistance surface, and Circuit theory (CT) is used to connect cold islands and heat islands in cooling corridors. The results show that from 1999 to 2019, land surface temperature (LST) increased significantly in the city of Haikou, the extreme LST became more and more significant, and the area with the highest temperatures showed a southward trend. The connectivity between cold and heat island patches declined, and the Loop, Bridge and Branch areas in heat islands increased. The latter scenario is conducive to the construction of cooling corridors. The land cover index had a great influence on SUHI, and the resistance surface presented a distribution pattern with high values in the northwest and low values in the southeast, which is consistent with the distribution of LST. Finally, we extracted the resultant cold-heat island cooling network, which was mainly concentrated along the southern edge of the study area, and found that corridor construction faced fewer obstacles in 2019 than in 1999. This study can guide urban planners to reinforce the parts of ecological networks that will mitigate the urban heat island effect.

Changes in land use and land cover (LULC) promote regional carbon storage capacity or trigger carbon depletion, which in turn exhibited significant impact on global climate change. Understanding the impacts of LULC on changes of carbon storage in coastal areas plays a critical role in the conservation of regional ecosystems and sustainable socio-economic development. The present study acted the coastal area of Shandong Province as an example to analyze the relationship between LULC and carbon storage combined with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Patch-generating Land Use Simulation (PLUS) model. We further predicted the variation of carbon storage through the change of LULC types under three scenarios in 2030. Our results showed that cropland (which decreased by 9.41%) and built-up land (which increased by 7.66%) underwent the most significant changes over the past 20 years, while forest, grassland, wetland, water and bare land underwent less changes. As the dominant land type, cropland was also the most important carbon pool with medium carbon storage. Areas with high carbon storage were distributed in the mountains and hills, where the main land types were grassland and forest. In addition, wetland located in the Yellow River Delta also stores large amounts of carbon. Accordingly, areas with low carbon storage were widely distributed in built-up land of urban metropolitan regions. We pinpointed that the carbon storage in the coastal area of Shandong Province lost 47.96×106Mg due to the increasing of built-up land and the decreasing of cropland and forest, while ecological protection measures would effectively enhance regional carbon storage. Specifically, the regional carbon storage could be increased by 6.64×106Mg when the conversion of cropland, forest and grassland into built-up land was reduced by 20% and the conversion of wetland and water into built-up land was reduced by 30% (under the ecological priority scenario (EP)). We believe the present study could be a valid reference for administrators to develop policies in more reasonable planning of land use and urban development to achieve carbon peaking and carbon neutrality (“Dual Carbon” goals).

The construction of wetland ecological security pattern has important guiding significance for balancing urban development and ecological restoration. In this paper, the PLUS model was used to simulate the land use change under the business as usual scenario (BAU), economic development scenario (ED) and expansionary conservation scenario (EC) in 2030. Coupled with the wetland ecological security pattern, four wetland ecological networks were constructed for vertical and horizontal comparative analysis. The optimal network was selected and ecological pinch points and obstacles were identified. The results showed that: (1) The land use change mainly occurred in the main urban area of Haikou. Under BAU and ED scenarios, the area of construction land increased greatly. Under EC scenarios, the overall ecological land in Haikou would expand, but the area of wetland showed a downward trend. (2) In 2030, the overall ecological wetland network will be improved, the number and length of corridors will increase significantly, and the network structure under EC scenario will be more stable. (3) The number and area of ecological pinch points and obstacle points under the EC scenario in 2020 and 2030 increased significantly, and this area should be regarded as a priority area for ecological protection. This study provides a new perspective for ecological protection and restoration, and provides a reference for clarifying the direction of wetland ecological restoration work and formulating urban construction and development policies.

The study of long-term changes to urban green space reveals the reasons for changes in the spatial pattern of urban green space and predicts the future development trends, which is of great importance for urban green space protection and integrated urban development. This study used Markov Chain and PLUS models to explore the spatial and temporal patterns of changes to green space in urban and rural areas in Jinan City during recent rapid urbanization and the driving forces behind them. The results show that from 2000 to 2020, the decrease in urban green space in Jinan City slowed down gradually, and that elevation and population density were the primary factors influencing changes in urban green space. In the simulation projections, the ecologically protected development scenario had a relatively low rate of site change and was more protective of arable land and green space. Ecological conservation development was predicted to result in a decrease in unused urban land and to reflect the advantages of intensive land use. The findings will provide decision-makers with ideas related to the sustainable development of urban green space.

Urban expansion, especially the construction of megacities, increases carbon emissions and adversely affects the carbon storage of terrestrial ecosystems. However, scientific land-use management policies can increase carbon storage. This study takes two megacities at different stages of development, Beijing and Tianjin, as examples to explore the impact of different ecological conservation scenarios on both urban land use and carbon storage to provide recommendations for the construction planning of large cities with low-carbon development as the goal. Furthermore, we coupled the patch-generating land use simulation (PLUS) model with the integrated valuation of ecosystem services and tradeoffs (InVEST) model to simulate land use and carbon storage under a natural development scenario, a planned ecological protection scenario (PEPS), and a policy-based ecological restoration scenario (PERS). From 2000 to 2020, both cities had different degrees of construction land expansion and carbon loss, and Tianjin's dynamic degree of construction land was 0.94% higher than Beijing's, with a carbon loss 183,536.19 Mg higher than Beijing's; this trend of reducing carbon reserves will continue under the natural development scenario (NDS). Under the PEPS and PERS, the carbon stock of both cities increases, and the impact on Tianjin is greater, with an increase of 4.51% and 8.04%, respectively. Under PERS, the carbon stock increases the most, but the dynamic degree of construction land use is negative for both cities. Beijing's carbon stock is 0.40% lower than Tianjin's, which deviates slightly from the trend of urban economic development. Megacities in the rapid development stage can refer to Tianjin, strictly following the ecological protection land planning scope and vigorously implementing ecological restoration policies to effectively increase regional carbon stock. Megacities in the mature stage of development can refer to Beijing, and flexibly implement ecological restoration policies to increase regional carbon stock without affecting the city's economic development.

As the largest global carbon pool system, terrestrial ecosystems have an important role to maintain the stability of ecosystems. Human activities affect the structural changes in the ground surface and interfere with terrestrial ecosystem evolution, and consequently, carbon stock is changed in the region. Therefore, forecasting future carbon stock changes under different land use scenarios has important research implications for promoting stable evolution and cycling of terrestrial ecosystems. This study is conducted with the land use data from 2000 to 2020, and incorporates the Patch-generating Land Use Simulation model with the Integrated Valuation of Ecosystem Services and Trade-Offs model to analyze the changes in land use in Hefei, and its influence on the carbon stock in Hefei in various scenarios. During the study period, the mutual conversion between different land types in Hefei City made the land structure change within the study area more significant. The rapidly evolving surface structure is the reason for the decrease of carbon storage in terrestrial ecosystems, with a cumulative decrease of 1.2 × 108 t. The spatial distribution in carbon storage in the study area shows a distribution pattern of low in the north and high in the south. The high carbon storage area is obviously banded in the study area. The area with obvious changes in surface structure has more obvious changes in carbon storage. Compared with the natural development scenario, the downward trend of carbon storage in the ecological protection scenario and the comprehensive development scenario has slowed down due to the restrictions on the structural transformation of land types and the implementation of relevant ecological protection policies. Therefore, this study will support the future management and policy making of Hefei City with the background of China's “double carbon” target and the significant position of Hefei City.

Exploring future land use/cover change (LULC) and ecosystem service values (ESV) dynamics is crucial for sustainable development from regional to global scales. However, ESV dynamics is significantly affected by economic development and policy changes, and future projections of ESV are generally characterized by large uncertainties due to complexity in LULC dynamics. Mining activities are supposed to exert significant effects on ESV dynamics, while the patterns and controls of ESV in mining-dominated basins are still less understood, especially under different land-use scenarios. Here, based on multi-source remote sensing data and land-use data in the Fenhe River Basin, we integrated the SD model, Markov model and PLUS model to simulate LULC in the Fenhe River Basin under four scenarios, i.e., the economic development priority (EDP), natural development priority (ND), cultivated land protection priority (CLP), and ecological protection priority (EPP). Based on ESV equivalent coefficient method and geographical detector, we further determined the patterns and controls of ESV. Results showed that construction land and cultivated land were mainly concentrated in the central parts of the basin, and grassland and woodland were concentrated in the edge area of the basin. Over the past two decades, construction land and woodland have experienced significant expansion, while the areas of grasslands and cultivated lands have declined due to mining activities. The high-value and sub-high-value areas of ESV were concentrated in woodland, grassland, reservoir and concentrated water area of mainstream and tributary. The low-value area was mainly located in the gathering area of construction land. The total ESV showed a downward trend with time, and the highest decline in the total ESV under the four land use scenarios was the EDP, while the lowest drop was the EPP. The highest contribution rate of ESV was woodland, which was equivalent to the contribution rate of cultivated land, grassland and water area, totally accounting for 58.54% of the whole ESV. The geographical detector method indicated that distance to the residential area, soil erodibility, distance to the river, soil type and annual average temperature were the main driving factors affecting the spatial patterns of ESV. Our results highlighted the fundamental role of mining activity in affecting LULC characterized by grassland and cultivated land shrinkage, and suggested that mining areas rehabilitation should be given priority in terms of further improving ESV in mining-dominated basins.

Changes in land use significantly contribute to carbon emissions and other environmental problems. Regional carbon emissions changes from land use have been affected by rapid urbanization. To dynamically assess land use change and the spatiotemporal characteristics of carbon emissions from 1990 to 2020, this study used the PLUS, grey back-propagation neural network, and related carbon emission accounting models as well as four distinct 2030 scenario simulations. According to the findings, the urbanization of the urban agglomeration on the northern slope of the Tianshan Mountains (UANSTM) developed rapidly from 1990 to 2020 with a noticeable transfer of diverse types of land. In particular, the quantity of construction land and cropland belonging to carbon source land increased by 153.271% and 55.072% respectively. Simultaneously, carbon emissions showed a trend of continuous increase and demonstrated an S-shaped curve growth, with relatively rapid growth from 2000 to 2015, that has tended to be stable in recent years. If this carbon emission trend continues, an inflection point will appear around 2028. Land use simulations for 2030 reveal that the ecological security (ES) scenario, which slows the expansion of construction land and cropland while increasing ecological land, is most likely to reduce the negative environmental consequences of urbanization. This is because higher potential peak carbon emissions per unit area that may be obtained with carbon sink land. Consequently, the ES scenario of the study region is comparable to the future urban agglomeration development model. The results provide a reference for territorial space planning and dual carbon target recommendations in the UANSTM.

In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal changes from 2000 to 2060 in Pingyao, Gucheng, She and Langzhong, where the Four Ancient Cities of China are located. First, we found the spatiotemporal changes and the driving factors with land use transfer matrix, landscape metrics and a random forest analysis strategy. Furthermore, we simulated and predicted the spatiotemporal patterns in 2030 and 2060 by applying a CA model and landscape indexes, testing the carbon peak and carbon neutralization target achieved. The results demonstrate that urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity, as well as adversely affecting the landscape pattern of ecological land. Altitude, socioeconomic conditions, and policies regarding the development and utilization of land resources all significantly impact the four cities’ spatiotemporal changes. Both the land use pattern and the landscape pattern will become more complex significantly in the future. This study offers a new insight to compare and analyze the spatiotemporal changes of different CHPCs.

The Yellow River basin is an important area for China to implement ecological protection policies. Studying the habitat quality of the Yellow River floodplain area is of great significance to the ecological security and sustainable development of the entire basin. This study primarily investigated the spatial pattern of habitat quality in the Yellow River floodplain area from 2000 to 2020, then, we also simulated changes of habitat quality in 2025–2035 and analyzed the influencing factors by coupling the PLUS (Patch-generating Land Use Simulation) model, InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model and RF (Random Forest) model. The results showed that:(1) From 2000 to 2020, cultivated land and build-up land constituted an important part of the Yellow River floodplain area, and the growth rate of build-up land was fast. (2) We also found that the ecological land (forest land, grassland, waterbody) had a higher contribution value to the habitat quality, while the build-up land had a lower contribution value to the habitat quality. (3) Overall, the habitat quality of the floodplain area showed a degradation trend from 2000 to 2020. In addition, the regions with low habitat quality accounted for the major proportion. (4) Based on the calculation results of the Random Forest (RF) model, we found that topographical relief (TR) and land use intensity (LUI) were the two most important factors affecting habitat quality of the floodplain area. (5) According to the four scenarios from 2025 to 2035, it is found that the habitat quality level would be the highest under the ecological protection scenario, while under the urban development scenario its level would be the lowest. This study attempts to combine the RF model with PLUS model to improve the objectivity and accuracy of the future prediction scenario of habitat quality, which can provide scientific reference for ecological governance and policy formulation in the Yellow River floodplain area.

Urban land has been expanding under the background of rapid urbanization, which leads to the increasingly prominent problem of regional ecological security in multi-mountainous cities. In order to scientifically formulate land use policies and maintain regional ecological security pattern, it is necessary to assess regional landscape ecological risk (LER), explore its influencing factors, and simulate the LERs under different scenarios in the future. This study takes Guiyang, a typical mountainous city in the karst area of southwest China, as the study area. Based on the three-phase remote sensing images, the landscape pattern index and the Geodetector method (GDM) were used to assess LER and the corresponding driving factors from 2000 to 2020, and the PLUS model was used to simulate LER under different urban development scenarios in 2030. The results showed: (1) The average landscape ecological risk index (LERI) in 2000, 2010, and 2020 were 0.0341, 0.0320, and 0.0304, respectively. This shows that the overall LER of Guiyang is low and gradually decreases over time. (2) The LER pattern has significant positive spatial autocorrelation, but the autocorrelation decreases with the development of the city. (3) From 2000 to 2020, ecological driving factors were the main influencing factors of LER, but the impact of social driving factors on LER was growing with time. (4) The LER change of Guiyang in 2030 varies significantly under different scenarios, among which the area of the risk up zone in the natural development scenario is the largest, followed by the farmland protection scenario, and the ecological priority scenario is the smallest. This study will provide a scientific basis and reference for the overall development planning of multi-mountainous cities, regional ecological protection planning, and the formulation of relevant land use policies.

The improvement of habitat quality is of great significance to biodiversity conservation. Irrational development activities lead to the degradation of habitat quality and loss of biodiversity, especially in arid inland areas where the ecological environment is fragile. In this study, the InVEST model is used to evaluate the habitat quality and degradation degree of the Ebinur Lake Basin from 1990 to 2020, while the PLUS model is used to predict the land use change in the Ebinur Lake Basin under various scenarios. Combined with the results of ecological zoning planning, the spatial distribution of land use and habitat quality under the inertia development (ID) and ecological protection (EP) scenarios in 2030 were compared and analyzed, and the optimal scenario was selected. The following four conclusions are drawn: (1) From 1990 to 2020, cultivated land, grassland, and construction land significantly increased, while forest land, water bodies, and unused land significantly decreased. (2) The habitat quality of the watershed showed an increasing trend followed by a decreasing trend. The area proportion of high habitat quality has always exceeded 50 % of the total area of the watershed with a high level of habitat quality. (3) Furthermore, combined with habitat quality and the human footprint index (HFI), ecological zoning planning for the basin was conducted. The three ecological zones were divided into key protected areas, key restoration areas, and moderate development zones, with area proportions of 53.69 %, 29.37 %, and 16.93 %, respectively. (4) By comparing habitat quality under the ID scenario and the EP scenario in 2030, we found that the area of high habitat quality increased by 2730.06 km2 under the EP scenario, which improved the overall level of habitat quality, and was more conducive to the ecological security protection of the basin. The results of this study may benefit the analysis of the temporal and spatial variation characteristics of habitat quality in the Ebinur Lake Basin and provide a reference for the improvement of habitat quality in the inland arid region.

The simulation and future prediction of spatial and temporal land use and land cover change (LUCC) have long been the focus (and challenge) of research on land use change and sustainable development. However, the existing research lacks empirical comparisons among different simulation models under the same conditions in the same region; hence, the most accurate simulation results cannot be obtained through the optimal model. In this paper, taking the Fuxian Lake basin as an example, the CA-Markov, FLUS, and PLUS models are adopted to explore the optimal model for simulating LUCC in this basin by integrating restricted areas of LUCC. This study shows the following. (1) The simulation results are more accurate under the joint restrictions of open water, prohibited development zones and ecological protection red lines than under a single restriction. (2) All three models can simulate the LUCC in the Fuxian Lake basin. Among these models, the PLUS model has the highest simulation accuracy in simulating LUCC at the basin scale and offers the best match of land types in terms of their quantity and spatial distribution. (3) The PLUS model can accurately predict the changes of LULC in the Fuxian Lake basin. The results of this study should help decision makers evaluate land use development patterns and provide a reference for the formulation of regional sustainable development policies.

Landslides pose a noteworthy threat in urban settlements globally, especially in areas experiencing extreme climate and rapid engineering. However, researches focusing on the long-term uninterrupted land use and land cover change (LULCC) impacted on landslide susceptibility mapping (LSM) in rapid urban expansion areas remains limited, let alone different temporal scenarios adjacency thresholds. This work aims to refine the temporal LSM considering spatiotemporal land use and land cover (LULC) and to provide decision makers with governing factors in landslides control during urbanization in mountainous areas. Herein, annual LULC data and landslide inventory spanning from 1992 to 2022 were utilized to map dynamic landslide susceptibility in Wanzhou District of the Three Gorges Reservoir Area, China. Initially, the landslide-related factors were filtered as input features of random forest (RF) model before diagnosis via multicollinearity test and Pearson Correlation Coefficient (PCC). The advanced patch-generating land use simulation (PLUS) model was then invited to fuel temporal susceptibility prediction powered by LULCC projections. Finally, the performance of various scenarios was evaluated using Receiver Characteristic Curve (ROC) curves and Shapley Additive exPlanation (SHAP) technique, with discussions on LULCC temporal adjacency thresholds and mutual feedback mechanism between territorial exploitation and landslide occurrences. The results indicate that the precision of LSM is positively correlated with the time horizon, acted by incorporating the latest LULC and LULCC achieving an area under the curve (AUC) of 0.920. The transition of land from forest to cropland and impervious areas should be avoided to minimize the increase in landslide susceptibility. Moreover, a one-year adjacency threshold of LULCC is recommended for optimal model accuracy in future LSM. This dynamic LSM framework can serve as a reference for decision makers in future landslide susceptibility mitigation and land resources utilization in rapid urban expansion areas worldwide., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Coastal salt marsh wetlands not only sequester a large amount of organic carbon, mitigating the effect of climate change, but also nurture rich wetland resources and diverse ecological environments. In this study, habitat pattern and quality of the Jiangsu Yancheng Wetland Rare Birds National Nature Reserve were studied. The evolution of habitat patterns was analyzed using the U-Net model and Sentinel-2 data. The habitat quality was evaluated using the InVEST model, while the future habitat pattern in 2027 under different scenarios were simulated using the PLUS model. Our results showed that, during 2017-2022, the Suaeda salsa habitat showed a net decrease in area of 2077.61 ha, while Spartina alterniflora and Phragmites australis habitats manifested a net increase in different degrees. The overall habitat pattern was characterized by fragmentation decline and regularization enhancement. The habitat quality decreased from 0.75 to 0.72, mainly due to the loss of the S. salsa habitat and the expansion of the P. australis habitat. The simulation results indicated that, the habitat quality is expected to further decline to 0.71 under the natural development scenario, and 390.27 ha of S. salsa habitat will convert to P. australis. While in government control scenario, the habitat quality is expected to improve to 0.78, which was 0.07 higher than that in natural development scenario, and S. salsa habitat can be restored well. This study provides a scientific basis for the protection of suitable habitats for waterfowl and is crucial for the ecological conservation and management planning of nature reserves and coastal salt marsh wetlands., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Social-economic development and urbanization greatly modify landscape patterns and their associated ecological processes at regional scales, resulting in serious landscape ecological risk (LER). Effectively evaluating the LER is the basis for sustainable land use and development of regions. Because of the uncertainties in future socioeconomic development, precisely projecting future LER distribution is still challenging. To overcome this weakness, by using the Fujian Delta region as a case study, we employed patch-generating land use simulation (PLUS) model coupled with multiple linear regression and a Markov chain model to project the landscape patterns in 2050. The Shared Socioeconomic Pathways (SSPs) proposed by the Intergovernmental Panel on Climate Change (IPCC) were selected as the scenario framework. Thus, the spatiotemporal characteristics of the landscape pattern changes and LER from 2000 to 2020 and the projections for 2050 under different localized SSPs scenarios were explored. The results show that the cropland and water areas changed remarkably during 2000–2020. The PLUS model based on the couple of multiple linear regression and Markov chain model has higher prediction accuracy (FoM = 0.244) than that without the multiple linear regression (FoM = 0.146). The simulation results show that the urban land continued to expand westward and northward in 2050. Large amounts of cropland will be transformed into urban land in the eastern part. The conversion area is the largest under the SSP2 scenario, and the smallest area occurs under the SSP4 scenario. From 2000 to 2020, the LER exhibited the characteristics of an east–west polarized spatial distribution, and the LER gradually increased. The localized SSP4 scenario is projected to have the largest LER, and the smallest LER occurs under the SSP1 scenario. The conversions from cropland to urban land will lead to the most significant increases in LER, followed by the conversion of grassland to urban land.

Exploring future changes in land use and carbon storage (CS) under different climate scenarios is important for optimizing regional ecosystem service functions and formulating sustainable socioeconomic development policies. We proposed a framework that integrates the system dynamics (SD) model, patch-generating land use simulation (PLUS) model, and Integrated Valuation of Ecosystem Service and Tradeoffs (InVEST) model to dynamically simulate changes in land use/cover change (LUCC) and CS at the city level based on SSP-RCP scenarios provided by the CMIP6. The simulations were applied to Bortala Mongol Autonomous Prefecture in Xinjiang. Changes in LUCC were similar under the SSP126 and SSP245 scenarios, but woodland expansion was more rapid under the SSP126 scenario. Changes in LUCC under the SSP585 scenario were different from those under the other two scenarios, and this was mainly caused by the continuous reduction in woodland area and the rapid expansion of construction land and cultivated land. By 2050, the simulation results revealed that CS was highest under the SSP126 scenario (193.20 Tg), followed by the SSP245 scenario (192.75 Tg) and SSP585 scenario (185.17 Tg). Overall, the results of this study suggest that increases in CS could be achieved by controlling economic growth and population growth, promoting an energy transition, and expanding woodland in the study area.

Currently, socioeconomic development and climate change pose new challenges to the assessment and management of terrestrial carbon storage (CS). Accurate prediction of future changes in land use and CS under different climate scenarios is of great significance for regional land use decision-making and carbon management. Taking the Yellow River Basin (YRB) in China as the study area, this study proposed a framework integrating the land use harmonization2 (LUH2) dataset, the patch-generating land use simulation (PLUS) model, and the integrated valuation of ecosystem services and trade-offs (InVEST) model. Under this framework, we systematically analyzed the spatiotemporal evolution characteristics of land use and their impact on CS in the YRB from 1992 to 2050. The results showed that (1) CS was highest in forestland and lowest in construction land, with a spatial distribution of high in the south and low in the north. From 1992 to 2020, construction land, forestland, and grassland increased while cropland decreased, reducing the total CS by 74.04 Tg. (2) From 2020 to 2050, under SSP1-2.6 scenario, forestland increased by 158.87 %; under SSP2-4.5 scenario, unused land decreased by 65.55 %; and under SSP5-8.5 scenario, construction land increased by 13.88 %. By 2050, SSP1-2.6 scenario exhibited the highest CS (8105.25 Tg), followed by SSP2-4.5 scenario (7363.61 Tg), and SSP5-8.5 scenario was the lowest (7315.86 Tg). (3) Forestland and construction land were the most critical factors affecting the CS. Shaanxi and Shanxi had the largest CS in all scenarios, and Qinghai had a huge carbon sink potential under SSP1-2.6 scenario. Scenario modeling demonstrated that future climate and land-use changes would have significant impacts on terrestrial CS in the YRB, and green development pathways could strongly contribute to meeting the dual‑carbon target. Overall, this study provides a scientific basis for promoting low-carbon development, land-use optimization, and ecological civilization construction in YRB, China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Ecological management zones (EMZs) are pivotal in improving the management of ecosystem services (ESs) and promoting sustainable regional development. In this study, we developed a comprehensive framework aimed at identifying EMZs and substantiating their efficacy through the amalgamation of historical evolutionary patterns and future trends. We applied this framework to Beijing, China, and selected five vital ESs for the study area namely, water yield (WY), carbon sequestration (CS), habitat quality (HQ), soil conservation (SC) and water purification (WP). The framework involves two key components. Firstly, the identification of EMZs is based on the historical evolution of five types of ESs and the dynamic assessment of ES bundles. Subsequently, it enables a simulation of various scenarios to predict future alterations in land use and ESs, thereby validating the effectiveness of the identified EMZs. Our findings reveal notable spatial heterogeneity among different ESs, and that CS, HQ, SC, and WP exhibited synergies, while WY and showed trade-offs with the remaining four types of ESs. Based on an analysis of ES bundle evolution trajectories, we identified four types of EMZs: ecological conservation zone, ecological restoration zone, ecological transition zone and sustainable construction zone. Through strategic EMZ planning, it becomes possible to augment the area of forestland and grassland, alleviate the contradiction between arable land and construction land, and enhance the supply of various ESs. The proposed framework not only offers a novel perspective on the scientific management of ESs but also furnishes decision-makers and planners with an intuitive understanding of the tangible benefits associated with EMZ planning., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

To foster an ecological civilization and ensure sustainable development of population resources, a critical focus of China's land spatial planning initiatives is the complex interplay among the prudent utilization of regional natural resources, stable socio-economic growth, and ecological environment preservation and governance. This interplay is vital for improving the population's quality of life, enhancing national resilience, and fostering the development of an ecological civilization. Within this context, this research focuses on the Chang-Ji-Tu region, employing a hybrid InVEST-Bayesian Belief Network-PLUS model. This approach facilitates a comprehensive assessment of habitat quality (HQ), carbon sequestration (CS), soil conservation (SC), crop production (CP), and total ecosystem services (TES) spanning 2005 to 2020, to optimize spatial structures based on these assessments. The findings indicate significant insights: (1) temporally, both HQ and CS exhibit an initial ascent followed by a subsequent decline, while SC demonstrates a rise, subsequent decrease, and then a gradual increase. CP shows a consistent increase, and TES initially decreases before experiencing a rise. Spatially, regions exhibiting high CP are primarily located in the northwest, in contrast to the southeast, demonstrating lower values. Conversely, HQ, CS, and SC exhibit lower values in the northwest and higher values in the southeast. TES exhibits considerable variability in the northwest and a more equilibrated distribution in the southeast. (2) A positive correlation is observed between land use/cover changes (LUCC) and HQ, CS, and SC, while a negative correlation is noted with CP and TES. (3) In exploring potential scenarios for economic development (ED), natural development (ND), and ecological protection (EP) in 2035, our study categorizes TES into distinct zones: ecological protection prohibited zones, ecological buffer prohibited zones, construction and development suitable zones, and restricted zones for arable land protection. This study, grounded in the current ecosystem status, thoroughly analyzes spatial structural optimization, offering crucial insights for future land spatial planning and ecological restoration., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

A land use simulation model with coupling constraints of ecological security patterns (ESPs) and multiple scenarios (MSs) was developed using the PLUS model. The research scale was zoned with environmental functional regions, where land management policies were formulated. A case study in Anji County successfully demonstrated the application of the ESP-MS-PLUS model. First, we constructed three different levels of ESPs as ecological constraints by utilizing ecosystem services evaluation and circuit theory. Second, four scenarios of land use and land cover changes (LUCCs) in 2034 were assumed, namely business as usual (BAU), priority given to urban development (PUD), priority given to ecological protection (PEP), and balanced urban development and ecological protection (BUE). Then, the basic ecological constraints (ecological red line areas and waters) and three types of ESPs were coupled with the four scenarios. The results of the simulation and analysis of landscape metrics under each scenario showed that the PEP and BUE scenarios would effectively reduce the degree and speed of ecological destruction. In addition, there were three environmental functional areas that could be used as priority areas for urban construction to ensure economic development. This study provides a new mechanism for land use optimization in the context of ecological protection at scales conducive to practice., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)