Future Land Use Simulation Research Articles

Research on the coupled evolution of LULCC and habitat quality in the Ganqing section of the Yellow River Basin based on multi-scenario simulations

IntroductionThis study focuses on the Ganqing section of the Yellow River Basin, exploring four land use scenarios: natural development, cropland protection, ecological protection, and rapid development. Given the ecological importance of this area, the research aims to evaluate how each scenario impacts habitat quality and land use sustainability by 2030.MethodsThe Future Land Use Simulation (FLUS) model and the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) model were applied to simulate land use for each scenario. A habitat quality pattern and coupling coordination degree model was used to assess the interactions between land use and land cover change (LULCC) and habitat quality under different scenarios.ResultsFindings show that over 70% of the Ganqing section of the Yellow River Basin is primarily grassland. By 2030, the ecological protection scenario is predicted to have the highest habitat quality, followed by the natural development, rapid development, and cropland protection scenarios. Between 1990 and 2030, the area demonstrates predominantly high or moderate coordination between land use and habitat quality. Spatial analysis reveals lower coordination values in the southeast and higher values in the northwest, with imbalanced recession zones distributed around valley basins.DiscussionThis study highlights the value of strategic scenario planning in enhancing habitat quality and promoting sustainable land management in the Ganqing section of the Yellow River Basin. The ecological protection scenario shows the most promise for balancing development with habitat preservation, underscoring the importance of adopting land use policies that support ecological sustainability in vulnerable areas.

Multi-Scenario land cover changes and carbon emissions prediction for peak carbon emissions in the Yellow River Basin, China

Research on future land cover changes and carbon emissions is essential for effective land resource management and developing feasible carbon mitigation strategies. This study focused on the Yellow River Basin and employed the Future Land Use Simulation (FLUS) and Autoregressive Integrated Moving Average (ARIMA) models to project future land cover and carbon emissions. Additionally, bivariate spatial autocorrelation was utilized to analyze the relationship between them. Key findings are as follows: 1) Historically, the Yellow River Basin has experienced an expansion in construction land, forests, grasslands, and water, while cropland and unused land have diminished. Notably, construction land displayed the most significant changes, whereas grasslands showed minimal modification. Looking ahead, both the ecological protection and inertial development scenarios exhibit consistent trends with historical patterns across the land type categories. In contrast, the economic priority development scenario forecasts an increase in construction land, cropland, and grasslands, indicating a distinct shift compared to the other scenarios. However, the ecological protection scenario proves to be more sustainable. 2) In the absence of intervention, the simulated carbon emissions from construction land throughout the basin display a linear increase across various scenarios, with provincial-level variations showing an increase from southwest to northeast. However, Henan and Sichuan are expected to experience slower reductions in carbon emissions, compared to other projections. There is a notable positive correlation between carbon emissions and the comprehensive index, indicating that regions with high emissions typically experience substantial land and economic development. 3) Energy consumption projections for 2030 and 2060 indicate that to align with China’s carbon goals, it is essential to reduce energy consumption and adjust the fossil to non-fossil fuel ratio to reduce carbon emissions. Substituting coal with clean energy and enhancing energy efficiency will be more effective for achieving low-carbon emission targets. In summary, this study provides significant guidance for China’s ecological conservation, low-carbon emission strategies, and global carbon emission control efforts.

Spatiotemporal Change Analysis and Multi-Scenario Modeling of Ecosystem Service Values: A Case Study of the Beijing-Tianjin-Hebei Urban Agglomeration, China

Ecosystem service value (ESV) assessment is a crucial indicator of regional ecological quality and ecological management effectiveness. Ecosystem services (ES) provide the environmental foundation for human existence and social advancement. However, the future course of land use change (LUC) in urban agglomerations and its implications for human society remains uncertain, which presents a challenge to maintaining a balance between ecological service functions and regional socioeconomic growth. This paper took the Beijing-Tianjin-Hebei (BTH) urban agglomeration as an example and used the future land use simulation (FLUS) model to project the spatial distribution of land use under the natural development scenario (NDS), food security scenario (FSS), and ecological priority scenario (EPS) of BTH in 2030, 2040, and 2050. Next, the changes to ESV under various scenarios were investigated through the equivalent coefficient method. In order to make more targeted recommendations for regional development, the study also used hotspot analyses to explore the impacts of LUCs on ESV. The results showed that: (1) from 2000 to 2020, the LUC in the BTH was dramatic and mainly focused on the interconversions among the three land use categories of cropland, grassland, and built-up land. The total ESV demonstrated the tendency to decrease from CNY 386,859.89 × 106 in 2000 to CNY 371,968.78 × 106 in 2020. (2) Compared with 2020, the ESV in BTH in 2050 under the FSS loses 16,568.78 × 106 CNY, followed by the NDS (CNY 10,960.84 × 106), while the ESV under the EPS increases by CNY 9373.74 × 106. The results of the scenario simulation showed that there was significant variability in ESV under different political orientations. (3) Hotspot analysis indicated that the ESV changes were clustered in the northeastern part and the eastern coastal region of the BTH. On this basis, we identified Chengde, Beijing, Tianjin, and Zhangjiakou as the key cities to focus on and made meaningful suggestions for their future regional environmental protection and sustainable development. This research can serve as a guide in creating sustainable BTH development policies and offer fresh perspectives for investigating how land use patterns affect the ecological environment’s regional quality under various policy trajectories.

Comparison of various models for multi-scenario simulation of land use/land cover to predict ecosystem service value: A case study of Harbin-Changchun Urban Agglomeration, China

Understanding the intricate changes in land use and land cover (LULC) transformations, as well as accurately quantifying the ecosystem services value (ESV), holds paramount importance in achieving sustainable development goals. However, previous studies have notably neglected conducting empirical evaluations across various LULC prediction models under identical conditions within the same geographical region. Additionally, the majority of relevant studies primarily concentrate on local scales. In this study, we used CA-Markov, Future Land Use Simulation (FLUS) and Patch-generating Land Use Simulation (PLUS) models to simulate the dynamics of LULC, respectively. Subsequently, we successfully projected the future LULC patterns and corresponding ESV within the Harbin-Changchun Urban Agglomeration (HCUA), China. During the period spanning from 2000 to 2020, a persistent reduction of 2067 km2 in farmland was witnessed within the HCUA, while an accompanying expansion of 4081 km2 in built-up land occurred concurrently. The ESV in HCUA experienced a fluctuating trend. There was an initial decline of 7.443 × 109 yuan during the first decade, which was subsequently followed by an increase of 4.615 × 109 yuan during the latter decade. PLUS, FLUS, and CA-Markov models can all simulate the LULC of HCUA, but in decreasing order of accuracy and ease of use, with OA values of 0.8987, 0.8944 and 0.8651, and Kappa values of 0.8217, 0.8150 and 0.7860, respectively. The PLUS model was chosen to predict the future LULC. Then four development scenarios were set. Our optimization results indicate that it is advisable to restrict the area of built-up land within 17000 km2 in 2030. Moreover, under the economic and ecological balance (EEB) scenario, both ESV and economic benefits are projected to increase compared to the business as usual (BAU) scenario. This study offers valuable insights and serves as a significant reference for future research endeavors focused on optimizing land use.

Construction, assessment, and protection of green infrastructure networks from a dynamic perspective: A case study of Dalian City, Liaoning Province, China

The green infrastructure (GI) network, an important nature-based solution (NBS) strategy, is pivotal for sustainable urban development. However, current research perspectives focus on constructing a static GI network, and research on evaluating and protecting GI networks in the context of spatiotemporal changes has been limited. This research aims to comprehensively characterise the spatio-temporal changes in the GI network and protect its efficiency. We selected Dalian City as a case study and applied the Future Land-use Simulation (FLUS) model to predict its land use for 2030 and 2040. Based on predicted and historical land-use data, the 1990–2040 GI network of Dalian City was constructed utilising the Integrated valuation of ecosystem services and trade-offs (InVEST), morphological spatial pattern analysis (MSPA) and minimum cumulative resistance (MCR) model, while its spatiotemporal changes were evaluated. The results revealed that the hub area exhibited positive growth over time, whereas the link lengths showed an opposite trend. Furthermore, the overall position of the GI network shifted toward the southwest. The flatness indicator detected that the direction of the GI network shape gradually became less pronounced. Consequently, the structure of the GI network shifted from multi-centre to mono-centre. Additionally, priority protection for hubs is mainly in the northeast, while links are primarily in the coastal regions. The urgency of protection for both increases over time. This research developed a dynamic GI network construction and assessment method, providing a scientific basis and reference for future rational GI network planning, ecological protection planning, and related land policy formulation.

Land Cover Simulation and Carbon Storage Assessment in Daqing City based on FLUS-InVEST Model

Considering Daqing City as the research area, the impact of land cover change on carbon storage in the future was discussed, and the hot spots of carbon sequestration capacity were identified. The future land use simulation （FLUS） model was used to simulate the land cover pattern of a natural succession scenario, ecological protection scenario, urban development scenario, and comprehensive development scenario in 2030, and the integrated valuation of ecosystem services and trade-offs （InVEST） model was combined to estimate carbon storage in 2010, 2020, and 2030. Finally, the hot spot analysis tool was used to identify the cold hot spots of carbon sequestration capacity. The results showed the following： ① From 2010 to 2020, the area of cultivated land, water, and artificial surface increased, whereas the area of other land cover types decreased, and the total carbon storage decreased by 8.6×105 t. ② The land cover change of the natural succession scenario and urban development scenario in 2030 was similar to that of 2010-2020, with carbon storage decreasing by 1.16×106 t and 1.20×106 t, respectively. The carbon storage of the comprehensive development scenario decreased by 1.00×106 t compared with that in 2020, and carbon storage of the ecological protection scenario was 5.677 7×108 t, which increased by 2.53×106 t compared with that in 2020. ③ The conversion of grassland and wetland to cultivated land was the main cause of carbon storage loss, and the main contributor of carbon storage in the ecological protection scenarios was wetland. ④ The hot spots of carbon sequestration capacity were mainly located in the wetland area, and the cold spots were mainly distributed in the central part of Daqing City. The carbon sequestration capacity of cultivated land was not significant. According to the research results, to realize the urban transformation of Daqing City, we should insist on returning farmland to forest and grass, increase the intensity of returning moisture, improve the utilization rate of urban land, and increase green infrastructure in the main urban area.

Balancing Economic Growth, Carbon Emissions, and Sequestration: A Multi-Objective Spatial Optimization in Zhengzhou Metropolitan Area in China

As China’s “Dual Carbon” strategy is implemented and the new urbanization advances, balancing economic development, emission reduction, and carbon sequestration has become an important issue during the growth of emerging metropolitan areas, and it is also important for achieving high-quality urban development. Therefore, this study had three major objective functions: economic growth, carbon emission reduction, and increased carbon storage. The multi-objective land use quantity structure was solved using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), and the best solution in the solution set was introduced using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for evaluation. Finally, combined with the Future Land Use Simulation (FLUS) model, the low-carbon evolution of the metropolitan area was predicted on a spatial scale. The trade-off plan results show that by 2035, the economic benefits will reach CNY 7.65 trillion, carbon emissions will be kept under 99.24 million tons, and carbon storage will steadily increase by 15.2 million tons. Therefore, optimizing land use from the perspective of balancing carbon emissions, carbon sequestration, and economic development can provide valuable references for planning low-carbon development and the rational use of spatial resources in future metropolitan areas.

Spatial and Temporal Characteristics of Land Use Changes in the Yellow River Basin from 1990 to 2021 and Future Predictions

Studying spatial and temporal characteristics of land use changes and the driving factors in the Yellow River Basin as well as simulating and predicting future land use is crucial for resource management, ecological protection, and regional sustainable development in the Yellow River Basin. Based on the China Land Cover Dataset (CLCD) of the Yellow River Basin from 1990 to 2021, this study employs various methods such as the Mann–Kendall test and sliding t-test, land use dynamics, the land use transfer matrix, the standard deviation ellipse, the center of gravity migration model, and a geographic detector to explore the spatial and temporal characteristics of land use changes and driving forces in the Yellow River Basin over the past 30 years. Additionally, the study predicts land use types in the study area for the year of 2030 by using the Future Land Use Simulation (FLUS) model. The results show the following: (1) From 1990 to 2021, the area of forest, grassland, water, and impervious surfaces increased significantly, while the area of cropland, shrub, barren land, and wetlands decreased significantly. The most actively changing land use types are cropland, grassland, barren land, and impervious surfaces. (2) The center of gravity for shrub and impervious surfaces shifted westward, while wetlands showed a trend of obvious concentrated distribution, and the remaining land use types exhibited stable directional distributions. (3) Economic factors had a stronger driving effect on land use changes than topographic and climatic factors. The land use changes in the Yellow River Basin are influenced by the coordinated driving forces of multiple factors. (4) In 2030, the main land use types in the Yellow River Basin are still expected to be cropland, grassland, and forest. However, there will be a significant expansion of impervious surfaces and forest land, with substantial encroachment on cropland and grassland.

Spatiotemporal characteristics and multi-scenario simulation of land use change and ecological security in the mountainous areas: Implications for supporting sustainable land management and ecological planning

The acceleration of global urbanization has intensified land use activities, which threaten the ecological environment and hinder the achievement of sustainable socioeconomic development goals. With the background of continuous land use expansion, the reasonable management of land use and ecological protection has increasingly become an important issue. This study constructs an ecological security (ES) index to evaluate the ES pattern, and employs the Future Land-Use Simulation (FLUS) model for multi-scenario simulation of land use patterns in mountainous areas. The results showed that from 2000 to 2020, cultivated land and grassland showed a sharp decrease, with areas of −128.64 and −228.18 km² respectively, while forest land, urban land, and other construction land increased, with areas of 116.12, 31.21, and 120.69 km² respectively. Over time, the mountainous areas mainly exhibited low and moderate ES patterns. Furthermore, for 2020–2030, under the natural development scenario, cultivated land, forest land, and grassland will show a decrease, while urban and other construction land will show a sharp increase. In contrast, under the ecological protection scenario, ecological land will show significant increase, and the patch expansion of urban construction land will be smaller. These results confirm the positive contribution of ES protection effects to improving the land use development, and support insightful guidance for formulating policies on ecological management in mountainous areas.

Spatial spillover effects of ecosystem service values in northeast China tiger and leopard national park based on spatial Durbin model

National parks are public green spaces planned and managed by the state, with the primary purpose of protecting natural ecosystems and cultural heritage. Evaluating the Ecosystem Service Value (ESV) of national parks and clarifying their ecological benefits can provide important scientific basis for the ecological protection and restoration of national parks. Therefore, taking the Northeast China Tiger and Leopard National Park (NCTLNP) as the study area, this research constructs an ESV assessment model based on Land Use and Land Cover Change (LUCC), using vegetation net primary productivity（NPP）as a biomass correction factor to modify the Equivalent Factor Approach (EFA). It aims to explore the spatial–temporal pattern changes of the ESV in the NCTLNP from 2000 to 2022. Additionally, the Future Land Use Simulation (FLUS) model is utilized to simulate the future LUCC pattern and ESV evolution trend under ecological protection. Finally, the spatial Durbin model (SDM)is employed, combining socio-economic and environmental factors such as population, GDP, and PM10 and so on, to reveal the driving mechanism of spatial spillover effects of ESV in the NCTLNP. The results indicate that:①The accuracy of the FLUS model is 93.12% with a Kappa coefficient of 0.87. The main LUCC of the NCTLNP is forest. Before 2020, the ecological land had a shrinking trend, while impervious is in a significant increasing trend. After 2020, there is an opposite trend.The most significant changes in LUCC were found in Wangqing County and Hunchun City. ②The ESV of the NCTLNP shows a fluctuating and increasing trend from 2000 to 2022. It increased from 69.315 billion yuan to 69.809 billion yuan. The main service function of the ecosystem in the study area is the regulatory services, which provide 58.03% of the ESV to the NCTLNP. The Hunchun City and Wangqing County have the fastest increasing rate. ③The ESV of the NCTLNP had a significant negative spillover effect, with spatial spillover coefficients of −0.135 and −0.236, respectively, which led to a siphoning phenomenon in the NCTLNP. Overall, by assessing the ESV of the NCTLNP and revealing the spatial spillover effects in the study area, it can provide a vital scientific foundation for the conservation and management of the national park, which will help to fulfill the sustainable development of the ecosystem and the conservation of biodiversity.

Spatio-temporal characteristics and multi-scenario simulation analysis of ecosystem service value in coastal wetland: A case study of the coastal zone of Hainan Island, China

Coastal wetland ecosystems harbor rich biodiversity and possess significant ecosystem service value (ESV). Therefore, it offers a range of crucial ecosystem services (ES) for human well-being and socio-economic development. Taking the Hainan Island coastal zone (HICZ) as a case study, the spatio-temporal characteristics of land use and land cover change (LULCC), and its associated ESV in wetland landscapes were analyzed over three time points (2000, 2010 and 2020). We explored the spatio-temporal evolution trajectory of ESV on the basis of geo-information tupu. Then, future land use simulation (FLUS) was employed to predict wetland patterns and ESV under three different scenarios: business as usual (BAU), ecological conservation first (ECF), and economic development first (EDF). The results showed that over the past two decades, a significant proportion (exceeding 80%) of the overall wetland region was comprised of offshore and coastal wetlands (OCW) as well as constructed wetlands (CW); these formed the matrix of the landscape. The area of building land (BL) continued to exhibit a consistent upward trend. Expanding by 2.18 times, it represented the most significant increase in the rate of dynamic changes in BL. The main ES in the HICZ corresponded to the regulation services (53.57%) and the support services (27.58%). The ESV of wetland losses accounted for 45.17% (43.08 × 108 yuan) of the total loss. The spatial differentiation of ESV in the HICZ was larger in the southwest and the northeast regions, while it was comparatively lower in the north. The transformation in the area of early and late change types accounted for 236.46 km2 and 356.69 km2, respectively. The scenario ECF was achieved with an optimal development of ESV (1807.72 × 108 yuan), which was coordinated with the high-level of development of regional ES functions and the economy. These findings provide valuable information for the sustainable development as well as the protection of ecology and environment of the coastal zone under the background of the construction of Hainan pilot free trade zone in the future.

Construction of Ecological Security Patterns and Evaluation of Ecological Network Stability under Multi-Scenario Simulation: A Case Study in Desert–Oasis Area of the Yellow River Basin, China

Land use change has a significant impact on the sustainability of ecosystems, and ecological security patterns (ESPs) can improve environmental quality through spatial planning. This study explored a multi-scenario ESP framework by integrating future land use simulation (FLUS) and minimum cumulative resistance (MCR) for urban agglomeration along the Yellow River Basin (YRB) in Ningxia. The research involved simulating land use change in 2035 under four development scenarios, identifying ecological security networks, and evaluating network stability for each scenario. The study revealed that the ecological sources under different development scenarios, including a natural development scenario (NDS), an economic development scenario (EDS), a food security scenario (FSS), and an ecological protection scenario (EPS), were 834.82 km2, 715.46 km2, 785.56 km2, and 1091.43 km2, respectively. The overall connectivity values (OG) for these scenarios were 0.351, 0.466, 0.334, and 0.520, respectively. It was found that under an EPS, the ESPs had the largest area of ecological sources and the most stable ecological network structure, which can effectively protect natural habitats. This study provides a valuable method for identifying ESPs that can respond to diversity and the uncertainty of future development. It can assist decision-makers in enhancing the ecological quality of the study area while considering various development scenarios.

Trade-offs between grain supply and soil conservation in the Grain for Green Program under changing climate: A case study in the Three Gorges Reservoir region

Understanding the trade-offs between ecological benefits and cost of grain supply caused by ecosystem restoration is essential for decision-making. Nevertheless, due to climate change, the benefits of ecosystem restoration and cost of grain supply change across various spatial locations, thereby complicating the trade-offs. Taking one of China's largest scale ecosystem restorations, the Grain for Green Program (GGP), as an example, this study used the Three Gorges Reservoir (TGR) region as the case study area and combined the crop environment resource synthesis (CERES)-Crop model, future land-use simulation (FLUS), and the revised universal soil loss equation (RUSLE) to simulate future grain supply and soil erosion during 2021–2050 under three climate change and socioeconomic development scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) in the TGR region. The results showed that: (1) Until 2050, the implementation of GGP would bring a large soil conservation benefit by reducing soil erosion of 2.47–5.68 million tons, at the cost of 130,277–660,279 tons decrease in grain production in the TGR region. (2) Under SSP5-8.5 climate change scenario with the highest rainfall in the future, the GGP would maintain the greatest soil conservation benefits, resulting in a total amount of soil erosion decrease by 2.55 to 5.68 million tons. (3) Trade-offs between benefit of reducing soil erosion and cost of grain supply vary considerably across income. Specifically, GGP benefits are greater under low-income and higher-emission scenarios, with significant gains in soil erosion control and less impact on grain supply. In contrast, in high-income and low-emission scenarios, the GGP results in less soil erosion control and greater impact on grain supply.

A spatially explicit framework for assessing ecosystem service supply risk under multiple land‐use scenarios in the Xi'an Metropolitan Area of China

AbstractRapid global urbanization has perturbed ecosystem structures and functions, resulting in ecological risk and threatening sustainable human well‐being and socioeconomic development. However, scientific indicators to analyze ecosystem service (ES) risk patterns need to be explored in detail. In addition, studies on ES supply risk are stagnating on historical or status explorations, especially from the view of disturbance from land‐use changes. This study seeks to develop a framework for modeling past‐future ES supply risk pattern evaluation and probing into ES risk patterns under different future land‐use scenarios. To achieve this objective, the framework integrates the Future Land Use Simulation (FLUS) model, the Intelligent Urban Ecosystem Management System (IUEMS) model, and an established indicator system incorporating ES supply trend, hotspots and coldspots, and ES trade‐offs, and synergies. The results show that: (1) In 2050, the supply of climate regulation in the Xi'an Metropolitan Area (XMA) will increase, while that of carbon sequestration and recreation will decrease. In 2050, the supply of climate regulation is the highest under ecological protection (EP) scenario, while the supply of carbon sequestration and recreation are the highest under cropland protection (CP) scenario. (2) From 2000 to 2050, the hotspots and coldspots of climate regulation increase in both natural development (ND) scenario and CP scenario. Notably, CP scenario experiences the most significant reduction in extremely significant hotspots and coldspots of carbon sequestration. From 2000 to 2050, at the regional and pixel scales, climate regulation and carbon sequestration mainly show trade‐offs, and carbon sequestration and recreation show synergies. (3) ES supply risk in XMA is high in the center and low in the north and south. The ES supply risk from 2000 to 2050 is increasing, with expanding “extremely high risk”, “high risk”, and “extremely safe” areas. ES supply risk management should adhere to more strict land‐use policies and guidelines, management zoning for areas with different levels of ES risk, and an accurate understanding of ES trade‐offs and synergies for scientific risk management. This study could provide theoretical and technical references for ES risk assessment research and promote scientific ecological risk management.

A Multi-Objective Scenario Study of County Land Use in Loess Hilly Areas: Taking Lintao County as an Example

Land use serves as a connecting link between human activities and the natural ecology of the surface; under the multi-objective background of national policies and dual-carbon tasks, land use transformation is studied and simulated in multiple scenarios, and carbon stock changes are analyzed based on future land use to explore the path for a region to achieve multi-objective coordination. Drawing upon land use data from 2000 to 2020 in Lintao County, Gansu Province, we conducted an in-depth analysis of the dynamics governing land use transformation. Subsequently, employing the FLUS (Future Land Use Simulation) model, we simulated the projected land use for Lintao County in 2035 under various scenarios. Furthermore, we utilized the InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model to assess the change in carbon stock within the study area under each scenario. These analyses aim to furnish a robust scientific foundation for future land use planning endeavors in Lintao County. The conclusions are as follows: (1) The land use transition in Lintao County from 2000 to 2020 showed the strongest motivation for construction land growth, with continued rapid growth in the scale of urban land and other construction land and relatively slow growth in the land for rural settlement areas, while cropland and water areas continued to decrease, forest land grew slowly, the magnitude of land use change exhibited a higher intensity in river townships compared with mountainous townships. (2) The simulation results of cropland protection scenario (CPS), ecological protection scenario (EPS), economic development scenario (EDS), and comprehensive development scenario (CDS) in 2035 are better. Among them, the CDS, which considers various types of higher-level strategic requirements and can compensate for the single-goal nature of the single-demand scenario, demonstrates a higher level of rationality in the land use pattern. (3) The total carbon stock in descending order is the EPS, CDS, EDS, and CPS. Among these, the CDS is at a higher level of total carbon stock, and the changes in carbon stock in each land use site are more balanced, which is an ideal carbon stock state and a scenario more in line with multi-objective coordination.

Exploring future ecosystem service changes and key contributing factors from a “past-future-action” perspective: A case study of the Yellow River Basin

Understanding the impacts of climate change and human activities on ecosystem services (ESs) and taking actions to adapt to and mitigate their negative impacts are of great benefit to sustainable regional development. In this paper, we integrate the System Dynamics Model (SD), the Future Land Use Simulation (FLUS) model, the Integrated Valuation and Trade-offs of ESs (InVEST) model, and the Structural Equation Model (SEM). We select three scenarios, SSP1–1.9, SSP2–4.5, and SSP5–8.5, from the Coupled Model Intercomparison Project 6 (CMIP6) to forecast future changes under these scenarios in the Yellow River Basin (YRB) by 2030. We predict future changes in water yield (WY), carbon storage (CS), soil retention (SR), and habitat quality (HQ) in the YRB. The results show that: (1) Under the SSP1–1.9 scenario, ecological land types such as forests, grasslands, and water bodies are protected and restored to a certain extent; under the SSP2–4.5 scenario, the degree of land spatial development occupies an intermediate state among the three scenarios; and under the SSP5–8.5 scenario, there is an obvious increase in the artificialization of the watershed's land use. (2) Under scenario SSP1–1.9, there is a comprehensive approach to sustainable development that significantly improves all ESs in the watershed, while the SSP5–8.5 and SSP2–4.5 scenarios demonstrate an increase in trade-offs between WY, HQ, and CS, especially in the downstream area. (3) Anthropogenic factors having more significant impacts in the SSP5–8.5 scenario. In this paper, we not only summarize the differences in trade-offs among various ESs but also provide an in-depth analysis of the key factors affecting future ESs, providing new ideas and insights for the sustainable development of ES in the future. In summary, we propose a prioritized development pathway for the future, a reduction of trade-offs between ESs, and an improved capacity to respond to challenges.

Future land use simulation model-based landscape ecological risk prediction under the localized shared socioeconomic pathways in the Xiangjiang River Basin, China.

Landscape ecological risk (LER) is an effective index to identify regional ecological risk and measure regional ecological security. The localized shared socioeconomic pathways (LSSPs) can provide multi-scenario parameters of social and economic development for LER research. The research of LER under LSSPs is of scientific significance and practical value in curbing the breeding and spread of LER risk areas. In this study, land-cover raster files from 2010 to 2020 were used as the foundational data. Future land use simulation (FLUS), regression, and Markov chain models were used to predict the land cover patterns under the five LSSP scenarios in the Xiangjiang River Basin (XJRB) in 2030. Thus, an evaluation model was established, and the LER of the watershed was evaluated. We found that the rate of land cover change (LCC) in the XJRB between 2010 and 2020 had a higher intensity (increasing at an average of 18.89% per decade) than that projected under the LSSPs for 2020-2030 (averaging an increase of 8.58% per decade). Among the growth rates of all land use types in the XJRB, that of urban land was the highest (33.3%). From 2010 to 2030, the LER in the XJRB was classified as lower risk (33.73%), lowest risk (33.11%), and moderate risk (24.13%) for each decade. Finally, the LER exhibited significant heterogeneity among different scenarios. Specifically, the percentages of regions characterized by the highest (9.77%) and higher LER (9.75%) were notably higher than those in the remaining scenarios. The higher-level risk area under the localized SSP1 demonstrated a clear spatial reduction compared to those of the other four scenarios. In addition, in order to facilitate the differential management and control of LER by relevant departments, risk zoning was carried out at the county level according to the prediction results of LER. And we got three types of risk management regions for the XJRB under the LSSPs.

Integrating spatiotemporal co-evolution patterns of land types with cellular automata to enhance the reliability of land use projections

Land use and land cover change (LUCC) simulation aids the interpretation of the causes and consequences of future landscape dynamics under various scenarios, which in turn supports policy decisions. The essence of LUCC simulation lies in representing complex spatiotemporal associations among land types, including competitions and interactions. Currently, analyses of complex spatiotemporal LUCC associations mainly focus on the spatial configuration of land use while ignoring the intricate spatiotemporal co-evolution patterns of land types. Therefore, by integrating spatiotemporal co-evolution pattern mining (STC) in a future land use simulation (FLUS) model, a land use change simulation model named STC-FLUS was developed in this study. The proposed model is innovative because it can accurately quantify the spatiotemporal co-evolution patterns of land types, which can be effectively incorporated into LUCC simulations. A set of simulations indicate that the STC-FLUS model is more accurate than the classical FLUS model, with a figure of merit score of 0.135 compared with 0.114. Simulation results under five localized shared socioeconomic pathway scenarios from 2020 to 2040 demonstrate that the proposed model is effective for future LUCC simulation under a set of development scenarios. We conclude that spatiotemporal co-evolution patterns of land types can enhance the reliability of land use projections. Moreover, the STC-FLUS model can serve as a useful tool to understand future land use dynamics.

Urban Land Expansion Simulation Considering the Increasing versus Decreasing Balance Policy: A Case Study in Fenghua, China

Under the political dominance of urbanization, the policy of increasing versus decreasing balance (IVDB) between urban and rural construction land has had a profound influence on urban land expansion in China. The purpose of this study is to reveal the impact of the IVDB policy on the process of urban land expansion. Considering the transition process among different land use types under the IVDB policy, this study proposes two situations of urban land expansion. A future land use simulation (FLUS) model is applied to simulate the expansion process over three steps. A case study of Fenghua District in Ningbo City, China, shows the following: (1) In the first situation of village land directly transformed into urban land, the transformation is concentrated in the northern and western parts of Fenghua District. The expansion trends are particularly pronounced along existing urban land and main traffic lines. (2) In the second situation of village land reclamation for agricultural land and urban land occupation for agricultural land, the spatial differences in village land conversion to arable land or other agricultural land are relatively small, and the degree of concentration of arable land is significantly increased after reclamation. Urban land expansion mainly occurs close to Ningbo City. With the help of transfer quotas “produced” by other areas, expansion land can be balanced within Fenghua District. This research helps to shed light on the urban land use growth process and provides beneficial insights for stock spatial planning in China.

Optimizing land use patterns to improve the contribution of land use planning to carbon neutrality target

Land use planning has the potential to diminish carbon storages and exacerbate carbon emissions, and therefore improving its contribution to achieve carbon neutrality should be a priority. In this study, we proposed an integrated framework to reveal the interrelation between land use and carbon neutrality. We employed the Linear Programming Model (LPM), Markov, Future Land Use Simulation (FLUS), emission coefficients and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) to predict land use patterns in Hainan Island, China and assessed the potential for reducing carbon emissions and increasing carbon storages under four scenarios: natural development (ND), spatial planning (SP), low-carbon emission (LE), and high-carbon storage (HS) by 2035. The results demonstrate that the new Territory Spatial Planning in 2035 can effectively reduce carbon emissions and increase carbon sinks. Specifically, compared to the ND scenario, carbon emissions will decrease by 5.37 % and carbon storages increase by 0.11 % in the SP scenario. Furthermore, the optimized land use patterns in the low-carbon scenarios will result in a greater reduction in carbon emissions and a larger increase in carbon sinks than the SP scenario. Specifically, compared to the SP scenario, carbon emissions will decrease by 11.83 % in the LE scenario, and carbon storages increase by 4.81 % in the HS scenario. Through the integration of planning and carbon neutrality via land use optimization, this study broadened the theoretical analysis framework and deepened our comprehension of the relationship between land use and carbon neutrality. Moreover, the insights derived from our findings offer valuable information to policymakers on carbon neutrality policy-making and land use planning in Hainan and other regions facing the similar challenges.