Land use dynamics and ecosystem service valuation in the Sanmenxia Reservoir wetland of the Yellow River.

The Sanmenxia Reservoir wetland (SRW) serves as a critical ecological buffer in the middle reaches of the Yellow River. Ongoing population growth and changes in land use have placed significant pressure on the wetland's ecosystems. However, existing research has yet to establish a spatiotemporal analysis method to assess the impact of land use change on the ecosystem service value (ESV). This gap hinders the precise regulation and sustainable development of land resources. To gain a comprehensive understanding of the land use dynamics and ecological functions of the SRW, this study introduced a refined ESV evaluation method. This method revised the equivalent factors from spatial, temporal, and hydrological perspectives, with an emphasis on the impact of sediment discharge. Furthermore, the Patch-level Land Use Simulation (PLUS) model was employed to project the land use structure in 2030, and the corresponding ESV was analyzed. The study revealed the following: (1) Cropland constituted the primary land type in the SRW. Over the last two decades, the build-up area exhibited the most significant single land use dynamics, with the transformation of bare land to cropland spanning the widest range and largest area. (2) From 2000 to 2020, the ESV increased by 0.64 billion CNY, with the water body contributing almost all the increase. (3) The projected ESV for 2030 is 2.94 billion CNY, indicating an increase in ecological functions in the near future. Policy makers should recognizethe impact of land use change on ESV and implement measures to rebalance land use structure. While ensuring the preservation of cropland and the protection of lives and property, it is advisable to consider expanding the water body area to facilitate comprehensive sustainable development within SRW.

Ecological impacts and supply demand evolution of the Yangtze to Huaihe water transfer project in Anhui section.

Human activities have profound impacts on land use and the supply-demand balance of ecosystem services (ESs). Various activities, such as urban construction, urban and rural planning, and inter-basin water transfer projects, continuously reshape land use patterns. This is a case study of the Anhui section of the Yangtze-Huaihe Water Diversion Project. Data from 2000, 2010, and 2020 is analyzed. Additionally, the patch-generating land use simulation (PLUS) model is utilized to quantify the specific impacts of the water diversion project construction on the supply and demand of ESs. The results indicate that the comprehensive dynamic attitude of land use during the project construction period significantly increased, rising from 0.16 to 13.79%, and mainly affected forest, water areas, construction land, and unused land. Specifically, the construction of the project led to significant changes in water purification, biodiversity, and, especially, hydrological regulation services. Additionally, the migration of residents significantly impacted the demand for ESs. The study also found a significant correlation between land use changes and the balance of ES supply and demand: the proportion of cultivated land and construction land is positively correlated with the balance, while the proportion of forest, grassland, and water areas is negatively correlated. This study provides empirical data for understanding the environmental and socio-economic impacts of large-scale water diversion projects and offers a scientific basis for local mitigation and control of adverse impacts. Through quantitative analysis and model prediction, this research effectively bridges the gap between theory and practice, providing important references for sustainable regional development.

[Analysis of Temporal and Spatial Carbon Stock Changes and Driving Mechanism in Xinjiang Region by Coupled PLUS-InVEST-Geodector Model].

Based on the goal of "dual-carbon" strategy, it is important to explore the impacts of land use change on carbon stock and the drivers of spatial differentiation of carbon stock in Xinjiang. Here, we predicted the land use types in Xinjiang in 2035 under different scenarios and analyzed the impacts of land use on carbon stock, which is of great theoretical and practical importance for policy formulation, land use structure adjustment, and carbon neutrality target achievement in Xinjiang. The coupled PLUS-InVEST-Geodector model was used to explore the spatial and temporal patterns of carbon stock change under the scenarios of rapid development, natural change, arable land protection, and ecological protection in Xinjiang in 2035 and to quantitatively reveal the attribution of influences on the changes in carbon stock from the perspectives of land use change and the combination of nature-socioeconomic-accessibility. The results showed that： ① From 1990 to 2020, the area of arable land and construction land in Xinjiang increased, and in terms of the transfer direction, it was mainly shifted from unutilized land to grassland. ② On the time scale, the carbon stock in Xinjiang showed the fluctuation of "decrease-increase-decrease," with an overall increasing trend. The transfer of unutilized land to grassland was the main reason for the increase in carbon stock； on the spatial scale, the carbon stock in the Altai Mountains in the north, the Tianshan Mountains in the middle, and the Kunlun Mountains in the south was higher, whereas the carbon stock in the Tarim Basin and the Junggar Basin was lower. ③ In 2035, the carbon stock of the natural development and rapid development scenarios decreased by 27.24 Tg and 71.17 Tg compared with 2020, respectively, and the ecological protection and arable land protection scenarios increased by 492.55 Tg and 46.67 Tg. The ecological protection scenario could significantly increase the carbon stock of the Xinjiang Region compared with that in the other scenarios, and the distribution pattern of the carbon stock in the four scenarios was more or less the same as that in 2020. In addition to land transformation, soil erosion intensity was the main driver of spatial differentiation of carbon stocks in Xinjiang （q value of 0.3501）, followed by net primary productivity of vegetation. The results of multifactor interactions showed that the spatial differentiation of carbon stocks in Xinjiang was the result of the joint action of multiple factors. All the factors had a synergistic enhancement under the interactions. The interaction between soil erosion intensity and the net primary productivity of vegetation was the main driver of the spatial differentiation of carbon stocks in Xinjiang.

Multi-scenario prediction and attribution analysis of carbon storage of ecological system in the Huaihe River Basin, China.

Evaluating the impact of large-scale human activities on carbon storage through land use changes is of growing interest in terrestrial ecosystem assessments. The Huaihe River Basin, a vital Chinese grain production area, has undergone marked land use changes amid socio-economic acceleration. Evaluating the impacts of land use change on carbon storage and future carbon sequestration is imperative for regional ecosystem sustainability and Chinese food security, simultaneously, furnishing data support to regional land use planning and decision-making processes. Nonetheless, the mechanisms linking land use changes to carbon storage and the future carbon reservoir responses remain unclear. We utilized a multi-source dataset and representative scenarios, integrating PLUS, InVEST models, and Geodetector to assess land use change impacts on carbon storage in the Huaihe River Basin (2000-2030). The data indicates the following: (1) from 2000 to 2020, cultivated land decreased by 28,344.69 km2, construction land increased by 26,914.56 km2, and other land types changed little. (2) Land use change resulted a carbon loss of 1.17 × 108 t, primarily due to the expansion of construction land. (3) All four simulation scenarios exhibited diminished carbon storage relative to 2020, with the economic development scenario recording the lowest at 4.98 × 109 t and the ecological protection scenario the highest at 5.06 × 109 t. (4) Elevation predominantly drives carbon storage changes, with its interaction with NPP having the greatest impact. The factors synergistically enhance their explanatory power. The research provides a scientific basis for strategies aimed at augmenting regional carbon sequestration and refining low-carbon land management, safeguarding ecosystem stability.

[Prediction of Land Use and Habitat Quality in Harbin City Based on the PLUS- InVEST Model].

Analyzing the spatiotemporal evolution of urban land use and habitat quality can reveal the correlation between land use and habitat quality, aiding in rational urban land policies and high-quality ecological environment development. This study was based on land use transition matrices and an Intensity-Migration （IM） model to analyze the changes in land use in Harbin from 2000 to 2020. It combined the PLUS model to explore the driving factors of land use expansion for various land types and predicted land use scenarios for 2030 under natural development, ecological protection, farmland protection, and urban development scenarios. Finally, the InVEST model was used to complete the habitat quality analysis. The results indicated： ① The dominant land use types in Harbin were cropland, forest land, and grassland. From 2000 to 2020, there was a significant tendency of conversion into grassland, cropland, forest land, and artificial surfaces, with noticeable changes in land use intensity. Water bodies, bare land, and wetland types showed less conversion and tended to be restrictive. ② Elevation was the primary factor influencing the expansion of grassland, cropland, forest land, bare land, wetland, and water bodies. Socioeconomic factors were the main factor affecting the expansion of artificial surfaces. ③ Simulation of land use types in Harbin for 2030 under the four scenarios showed an increase in forest land area and a decrease in grassland area, with insignificant changes in wetland, water bodies, and bare land areas. Except for in the ecological protection scenario, the area of artificial surfaces increased, whereas cropland decreased. ④ Overall, habitat quality in Harbin improved from 2000 to 2020. ⑤ In 2030, the spatial pattern of habitat quality in Harbin remained consistent across all scenarios, showing an overall improvement in habitat quality. Under the ecological protection scenario, areas with low and medium habitat quality decreased, whereas areas with higher habitat quality increased, indicating a relatively significant improvement in habitat quality. The research results provide a scientific basis and insights for the development of ecological civilization and urban planning and construction in Harbin.

Landslide dynamic susceptibility mapping in urban expansion area considering spatiotemporal land use and land cover change.

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.

Assessing land-use changes and carbon storage: a case study of the Jialing River Basin, China.

Land-use change is the main driver of carbon storage change in terrestrial ecosystems. Currently, domestic and international studies mainly focus on the impact of carbon storage changes on climate, while studies on the impact of land-use changes on carbon storage in complex terrestrial ecosystems are few. The Jialing River Basin (JRB), with a total area of ~ 160,000 km2, diverse topography, and elevation differences exceeding 5 km, is an ideal case for understanding the complex interactions between land-use change and carbon storage dynamics. Taking the JRB as our study area, we analyzed land-use changes from 2000 to 2020. Subsequently, we simulated land-use patterns for business-as-usual (BAU), cropland protection (CP), and ecological priority (EP) scenarios in 2035 using the PLUS model. Additionally, we assessed carbon storage using the InVEST model. This approach helps us to accurately understand the carbon change processes in regional complex terrestrial ecosystems and to formulate scientifically informed land-use policies. The results revealed the following: (1) Cropland was the most dominant land-use type (LUT) in the region, and it was the only LUT experiencing net reduction, with 92.22% of newly designated construction land originating from cropland. (2) In the JRB, total carbon storage steadily decreased after 2005, with significant spatial heterogeneity. This pattern was marked by higher carbon storage levels in the north and lower levels in the south, with a distinct demarcation line. The conversion of cropland to construction land is the main factor driving the reduction in carbon storage. (3) Compared with the BAU and EP scenarios, the CP scenario demonstrated a smaller reduction in cropland area, a smaller addition to construction land area, and a lower depletion in the JRB total carbon storage from 2020 to 2035. This study demonstrates the effectiveness of the PLUS and InVEST models in analyzing complex ecosystems and offers data support for quantitatively assessing regional ecosystem services. Strict adherence to the cropland replenishment task mandated by the Chinese government is crucial to increase cropland areas in the JRB and consequently enhance the carbon sequestration capacity of its ecosystem. Such efforts are vital for ensuring the food and ecological security of the JRB, particularly in the pursuit of the "dual-carbon" objective.

[Impact of Land Use Change on Carbon Storage in Urban Agglomerations in the Guanzhong Plain].

It is important to study the impact of land use change on terrestrial ecosystem carbon stocks in urban agglomerations for the optimization of land use structure and sustainable development in urban agglomerations. Based on the patch-generating land use simulation (PLUS) model and integrated valuation of ecosystem services and trade-offs (InVEST) model, a simulation was developed that predicted the land use change and carbon stock of the Guanzhong Plain urban agglomeration in 2040 under different scenarios and further analyzed the impact of land use change on carbon stock. The results showed that:① The land use types of the Guanzhong Plain urban agglomeration were mainly cultivated land, forest land, and grassland, which accounted for more than 90 % of the total study area. ② From 2000 to 2020, the carbon stock in the Guanzhong Plain showed a continuous downward trend, with cropland, woodland, and grassland being the main sources of carbon stock in the Guanzhong Plain, and the overall carbon stock declined by 15.12×106 t, with the spatial distribution presenting the distribution characteristics of "high in the north and south and low in the middle." ③ By 2040, the carbon stock would decrease the most under the urban development scenario, with a total reduction of 27.08×106 t, and the least under the ecological development scenario, with a total reduction of 4.14×106t. The research results can provide data support for the high-quality development and rational land use planning of the Guanzhong Plain urban agglomeration.

[Temporal and Spatial Evolution and Prediction of Ecosystem Carbon Storage in Jiangxi Province Based on PLUS-InVEST Model].

Land-use changes are an important factor affecting the change in carbon storage in terrestrial ecosystems. Exploring the relationship between land-use changes and carbon storage provides reliable data support for optimizing regional land-use structure and maintaining regional carbon balance. Taking Jiangxi Province as an example, we first analyzed the land-use changes; then simulated the land-use pattern under three scenarios (i.e., natural development, ecological priority, and economic development scenarios) in 2030 based on the PLUS model; and finally estimated the carbon storage change in the past (i.e., 1990-2020) and future periods (i.e., three scenarios in 2030) using the InVEST model, analyzed the spatial-temporal characteristics, and proposed the corresponding suggestions. The results showed:① The carbon storage in Jiangxi Province showed a downward trend from 1990 to 2020, with a total reduction of 4.58×107 t. The increase in the water bodies and construction land and the decrease in cultivated land, woodland, grassland, and unused land was the major cause. ② The carbon storage under natural development, ecological priority, and economic development scenarios in Jiangxi Province in 2030 were 2.20×109, 2.24×109 and 2.19×109 t, respectively. ③ The carbon storage under the three scenarios showed similar spatial characteristics, wherein the high carbon storage was distributed in northern, northwest, and western regions, and the low carbon storage was distributed near the central region. These results can provide data support for future land spatial planning and improving the carbon storage of terrestrial ecosystems in Jiangxi Province.

[Spatio-temporal Evolution and Prediction of Carbon Storage in Huaibei City Based on InVEST-PLUS Model].

This study aimed to investigate the impact of spatiotemporal changes in land use on ecosystem carbon storage. The study analyzed the spatiotemporal changes in carbon storage in the study area based on land use data from five periods (1985, 1995, 2005, 2015, and 2020) using the InVEST model. The PLUS model was used to predict land use changes in the study area under four different scenarios (natural development, farmland protection, ecological protection, and double protection of farmland and ecology) in 2035, and the ecosystem carbon storage under different scenarios was estimated. The results of the study indicated that the farmland in the area under investigation had been decreasing consistently from 1985 to 2020, with a more rapid rate of change observed between 2015 and 2020. During this period, the overall dynamic attitude towards land use reached 34.62 %. Additionally, the carbon storage in the area showed a decreasing trend over the years, with a decrease of 1.55×105 t from 1985 to 2020. Between 2005 and 2015, the carbon storage showed a decrease of 1.22×105 t, with an average annual decrease of 1.22×104 t. The areas with higher carbon storage were located in the eastern part of the study area, whereas areas with lower carbon storage were found in the central and northwestern parts. Although the proportion of carbon storage in farmland decreased from 66.89 % to 57.73 %, farmland remained the most important carbon pool in the study area. The conversion of other land use types to grassland and forestland was advantageous for increasing ecosystem carbon storage. Finally, the study projected that by 2035, the carbon storage in the natural development scenario, the farmland protection scenario, the ecological protection scenario, and the dual protection scenario would be 81.77×105, 82.45×105, 82.82×105, and 82.51×105 t, respectively.

Multiple scenario land use simulation based on a coupled MOGA-PLUS model: a case of the Yellow River Basin.

Land use changes have profoundly influenced global environmental dynamics. The Yellow River (YR), as the world's fifth-longest river, significantly contributes to regional social and economic growth due to its extensive drainage area, making it a key global player. To ensure ecological stability and coordinate land use demand, modeling the future land allocation patterns of the Yellow River Basin (YRB) will assist in striking a balance between land use functions and the optimization of its spatial design, particularly in water and sand management. In this research, we used a multi-objective genetic algorithm (MOGA) with the PLUS model to simulate several different futures for the YRB's land use between 1990 and 2020 and predict its spatial pattern in 2030. An analysis of the spatiotemporal evolution of land use changes in the YRB indicated that construction land expansion is the primary driver of landscape pattern and structure changes and ecological degradation, with climate change also contributing to the expansion of the watershed area. On the other hand, the multi-scenario simulation, constrained by specific targets, revealed that economic development was mainly reflected in land expansion for construction. At the same time, grassland and woodland were essential pillars to support the region's ecological health, and increasing the development of unused land emerged as a potential pathway towards sustainable development in the region. This study could be used as a template for the long-term growth of other large river basins by elucidating the impacts of human activities on land use and rationalizing land resource allocation under various policy constraints.

Spatio-temporal evolution and prediction of carbon balance in the Yellow River Basin and zoning for low-carbon economic development.

Studying the carbon effect of land use in watersheds is important for mitigating global warming, promoting coordinated emission reduction in different regions within the watersheds, and realizing high-quality development of the watersheds. Although a number of scholars have carried out relevant studies in the past, they mainly focused on carbon emissions, rarely involved the carbon balance formed by carbon sources and sinks, and lacked relevant studies on the development of low-carbon economy sub-region. Based on this, this study takes the Yellow River Basin as an example, explores the spatial and temporal evolution of carbon emissions from land use in counties in the Yellow River Basin from 1980 to 2020, and predicts the spatial pattern of carbon income and expenditure from land use under natural conditions in 2030 and 2060 using the PLUS model; and then superimposes on the main functional area planning, divides 735 counties in the Yellow River Basin into six low-carbon economic development subregions, and analyzes their economic development The model of their economic development is analyzed. The results show that: (1) the spatial and temporal differentiation of land use carbon balance in the Yellow River Basin has changed greatly over the past 40 years, (2) the spatial distribution pattern of land use carbon balance in the natural context in 2030 and 2060 is more similar to that in 1990, (3) the carbon emission reduction potentials and pattern optimization of the different low-carbon economic development subregions differ greatly, and they have different low-carbon economic development patterns. The results of this study provide a theoretical basis for scientifically and rationally formulating economic policies for low-carbon development in the counties of the Yellow River Basin, and also provide an important reference for related studies in other similar basins or regions in the world.

Habitat quality evaluation and pattern simulation of coastal salt marsh wetlands.

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.

Spatiotemporal evolution and driving factors of ecosystem service bundle based on multi-scenario simulation in Beibu Gulf urban agglomeration, China.

Rapid urbanization is profoundly impacting the ecological environment and landscape patterns, leading to a decline in ecosystem services (ES) and posing threats to both ecological security and human well-being. This study aimed to identify the spatial and temporal patterns of ecosystem service bundles (ESB) in the Beibu Gulf urban agglomeration from 2000 to 2030, analyze the trajectory of ESB evolution, and elucidate the drivers behind ESB formation and evolution. We utilized the Patch-generating Land Use Simulation (PLUS) model to establish baseline (BLS), carbon sequestration priority (CPS), and urbanization priority (UPS) scenarios for simulating land use patterns in 2030. Following the assessment of ecosystem service values (ESV) through the equivalent factor method, we identified the spatiotemporal distribution patterns of ESB using the K-means clustering algorithm. By employing stability mapping and landscape indices, we identified and analyzed various types of ESB evolutionary trajectories. Redundancy analysis (RDA) was employed to pinpoint the drivers of ESB formation and evolution. The results revealed that from 2000 to 2030, land use changes were primarily observed in cropland, forestland, and construction land. Between 2000 and 2020, 92.88% of the region did not experience shifts in ESB types. In UPS, the ESB pattern in the study area underwent significant changes, with only 76.68% of the region exhibiting stabilized trajectories, while the other two scenarios recorded percentages higher than 80%. Key drivers of ESB-type shifts included initial food provision services, elevation, slope, changes in the proportion of construction land, and population change. This multi-scenario simulation of ESB evolution due to land use changes aids in comprehending potential future development directions from diverse perspectives and serves as a valuable reference for formulating and changing ecological management policies and strategies.

Evolution characteristics and multi-scenario prediction of habitat quality in Yulin City based on PLUS and InVEST models.

As a major energy city in China, Yulin City has faced huge challenges to the ecological environment with its rapid economic development and rapid urbanization. Therefore, it is of great significance to study the impact of land use changes on habitat quality. Based on three periods of land use data in Yulin City in 1995, 2005 and 2015, the PLUS model was used to simulate the land use changes in 2015. The measured kappa coefficient was 0.8859, which met the simulation accuracy requirements. By setting development zone boundaries and adjusting parameters, three progressive scenarios are designed to predict the spatial distribution of land use in Yulin City in 2035. The InVEST model was used to analyze the spatiotemporal evolution of Yulin City's habitat quality in the past 20 years and evaluate the distribution of Yulin City's habitat quality under three scenarios after 20 years. The results are as follows: (1) During the study period, construction land in Yulin City expanded rapidly, with an area increase of 380.87 km2 in 20 years, and ecological land gradually shrank. (2) The land use simulation results of Yulin City under various scenarios in 2035 show that future land use changes in Yulin City will mainly be concentrated in the central and western regions. (3) During the study period, the habitat quality of Yulin City was at a medium level and the overall habitat quality showed a downward trend. Spatially, the degree of habitat quality degradation in Yulin City showed a characteristic of gradually decreasing from West to East. (4) By 2035, under the scenario of suitable urban economic development, Yulin City's habitat quality has been improved to a certain extent, which not only protects ecological security but also meets the demand for construction land for urban development. The results of this study help the government better understand the evolution of land use and habitat quality in Yulin City in the past 20 years, and provide theoretical support and reference for the formulation of Yulin City's ecological environment protection policies and the implementation of ecological protection work under the current land spatial planning.

A coupling model based on spatial characteristics and evolution of terrestrial ecosystem carbon storage: a case study of Hanzhong.

Ecosystem carbon storage (ECS) is a critical consideration in reducing the impact of global warming and tackling environmental challenges, positioning it at the forefront of contemporary research. Due to the significant differences in the influence of land usage patterns on ECS in various policy contexts and China's commitment to attaining a carbon-neutral status, a model simulating different scenarios is needed to analyze the spatiotemporal characteristics and evolutionary process of carbon storage in terrestrial ecosystems accurately. To address this challenge, this study established a coupling model of "Geographical analysis -Evolution analysis -Predicting (GEP)" for assessing ecosystem ECS and analyzing its spatial characteristics and evolutionary patterns and projecting the spatial distribution of ECS under various developmental scenarios, which analyzed variations in ECS across different levels of magnitude and delineated the changing areas across a range of varying scenarios in the future additionally. The outcomes suggested that the ECS decreased by 1.17 × 106 t from 1990 to 2020, which pertaining to the utilization transfer of land in the area, whose change in ECS levels with a positive trend. It is predicted that the ECS will grow by 1.15 × 106 t and 1.44 × 106 t, in 2030 and 2060 compared with 2020 within the framework of natural development scenario (NDS), while within the framework of ecological protection scene (EPS), ECS will increase significantly, increasing by 3.06 × 106 t and 4.44 × 106 t. There will be more areas where ECS increases within the framework of EPS, by comparing with the NDS. This study offers a comprehensive analysis of Hanzhong City's carbon storage trends, demonstrating its significant impact on climate change mitigation and serving as a predictive model for similar regions, which underscores the importance of localized carbon management strategies, offering valuable insights for local governments in formulating effective climate adaptation and mitigation policies.

Integrating historical patterns and future trends for ecological management zone identification and validation: A case study in Beijing, China.

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.

[Land Change Simulation and Grassland Carbon Storage in the Loess Plateau Based on SSP-RCP Scenarios].

Exploring the spatial distribution of land use/coverage (LUCC) and ecosystem carbon reserves in the future of climate change can provide a scientific basis for optimizing the distribution of land resources and formulating social economic sustainable development policies. In this study, we integrated the plaques generating land use simulation (PLUS) model and ecosystem services and weighing comprehensive evaluation (InVEST) model. Based on the CMIP6-based sharing socio-economic path and representative concentration path (SSP-RCP), we evaluated the Loess Plateau for time and space dynamic changes in LUCC and ecosystem carbon reserves, analyzed the impact of driving factors on different regions, and explored the correlation between carbon reserves in various regions. The results showed:① In the future, the three scenarios were similar to the LUCC changes. The area of cultivated land, grassland, and unused land would be reduced to varying degrees, and the construction land had expanded sharply. The increase in the three scenarios was 29.23%-53.56% (SSP126), 34.59%-63.28% (SSP245), and 42.80%-73.27% (SSP585). ② Compared with that in 2020, the carbon reserves of SSP126 sites in 2040 increased by 1.813 8×106 t, and in the remaining scenarios it would continue to decline. By 2060, the grassland carbon reserves in the three scenarios decreased by 13.391×106, 33.548×106, and 85.871×106 t, respectively. ③ From the perspective of space correlation, the carbon reserves of the Loess Plateau were correlated between cities. The difference in future scenarios was not significant. The hotspots were distributed in the middle and north of the research area. There was no obvious cold spot area. ④ The changes in land use were predicted to increase or lose carbon reserves. Forestry, cultivated land, and grassland had more carbon reserves those in than other land types. Increasing their area and restrictions on the conversion of other land types should increase the ecosystem carbon reserves.

[Multi-scenario Simulation of Construction Land Expansion and Its Impact on Ecosystem Carbon Storage in Beijing-Tianjin-Hebei Urban Agglomeration].

It is of great practical significance for regional sustainable development and ecological construction to quantitatively analyze the impact of construction land expansion on terrestrial ecosystem carbon storage and to explore the optimization scheme of simulating construction land expansion to improve future ecosystem carbon storage. Based on the land use and cover change (LUCC) and other geospatial data of the Beijing-Tianjin-Hebei Urban Agglomeration from 2000 to 2020, this study utilized the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and the patch-generating land-use simulation (PLUS) model to assess and analyze the changes in ecosystem carbon stocks and spatial patterns regionally. In this study, we performed linear regression analysis to investigate the relationship between urban land expansion and changes in ecosystem carbon stocks for varying urban land proportion levels during two distinct time intervals, 2000-2010 and 2010-2020, which was conducted at a spatial resolution of 2 km. Three distinct urban land expansion scenarios were subjected to simulation to forecast the prospective land use pattern by 2030. Subsequently, we quantified the ramifications of these scenarios on ecosystem carbon stocks during the period from 2020 to 2030. The results were as follows:① In the Beijing-Tianjin-Hebei Urban Agglomeration, the ecosystem carbon stocks exhibited notable variations over the study period, with values of 2 088.02, 2 106.78, and 2 121.25 Tg recorded for the years 2000, 2010, and 2020, respectively, resulting in a cumulative carbon sequestration of 33.23 Tg C during the study duration. It is noteworthy that forest carbon storage emerged as the dominant contributor, with an increase from 1 010.17 Tg in 2000 to 1 136.53 Tg in 2020. Throughout the study period, the spatial distribution of carbon stocks displayed relative stability. Regions characterized by lower carbon content were concentrated in the vicinity of the Bohai Rim region and in proximity to cities such as Beijing, Tianjin, and Shijiazhuang, as well as rural settlements. In contrast, grid units with moderate and high carbon stocks were predominantly situated in the western Taihang Mountain and the northern Yanshan Mountain. Additionally, there was a tendency of increasing carbon stocks in the Taihang Mountain and Yanshan Mountain region, whereas those surrounding major urban centers such as Beijing, Tianjin, Shijiazhuang, and Tangshan experienced a notable decline in carbon stocks. Such reductions were most pronounced in regions undergoing urban land expansion during the study period. ② In grid units with an urban land proportion exceeding 10% at each level, a strong correlation was observed between urban land expansion and changes in carbon stocks during both the 2000-2010 and 2010-2020 periods. The changes in urban land proportion adequately explained the variations in carbon stocks. However, the explanatory power of urban land on carbon stocks decreased during the 2010-2020 period, indicating that other factors played a more substantial role in influencing carbon stocks during this time. The regression coefficients for both periods exhibited a fluctuating upward trend. In comparison to that during the 2000-2010 period, the impact of urban land expansion on carbon stocks was relatively smaller during 2010-2020, indicating a weakening influence. ③ In light of three distinct development scenarios, namely natural development (Scenario Ⅰ), a 15% reduction in the rate of urban land expansion (Scenario Ⅱ), and a 30% reduction in the rate of urban land expansion (Scenario Ⅲ), the projected ecosystem carbon stocks for the Beijing-Tianjin-Hebei Urban Agglomeration in the year 2030 were estimated to be 2 129.12, 2 133.55, and 2 139.10 Tg, respectively. These projections indicated an increase of 7.88, 12.30, and 17.85 Tg in comparison to the current carbon stocks. All scenarios demonstrated that the terrestrial ecosystem would play a role of carbon sink, particularly with the greatest carbon sink observed in the scenario with a 30% reduction in urban land expansion. The fit performance between urban land expansion and carbon stock changes during the 2020-2030 period was significantly better than that during the 2000-2010 and 2010-2020 periods, and the regression coefficients showed a fluctuating increase with an increase in urban land proportion. Across grid units with different urban land proportion levels, the regression coefficients exhibited the order of Scenario Ⅰ < Scenario Ⅱ < Scenario Ⅲ. In pursuit of the carbon peaking and carbon neutrality goals, the Beijing-Tianjin-Hebei Urban Agglomeration should prioritize scenarios with reduced rates of urban land expansion, especially in regions with higher urban land proportions.

Impacts of climate and land use change on terrestrial carbon storage: A multi-scenario case study in the Yellow River Basin (1992-2050).

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 dual­carbon target. Overall, this study provides a scientific basis for promoting low-carbon development, land-use optimization, and ecological civilization construction in YRB, China.