Exploring the Spatiotemporal Pattern Evolution of Carbon Storage in Northwestern China

A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects

Land use and land cover (LULC) change has greatly altered ecosystem carbon storage and exerted an enormous impact on terrestrial carbon cycling. Characterizing its impact on ecosystem carbon storage is critical to balance regional carbon budgets and make land use decisions. However, due to the availability of LULC data and the strong variability in LULC change, uncertainty remains high in quantifying the effect of LULC change on the historical and future carbon stock. Based on four historical LULC maps and one future LULC projection, this study combined the Land Use and Carbon Scenario Simulator (LUCAS) with a process-based CENTURY model to evaluate the historical and future LULC change and its impact on grassland carbon storage from 1991 to 2050 in northern China. Results showed that grassland experienced a drastic decrease of 16.10 × 103 km2 before 2005, while agriculture and barren land increased by 16.91 × 103 km2 and 3.73 × 103 km2, respectively. After that, grassland was projected to increase, agriculture kept steady, and barren land decreased. LULC change has resulted in enormous total ecosystem carbon loss, mainly in agro-pasture areas; the maximum 8.54% of carbon loss happened in 2000, which was primarily attributed to agriculture to grassland, forest to grassland, grassland to agriculture, and grassland to barren. Before 2000, the grassland net biome productivity was projected to be −15.54 Tg C/yr and −2.69 Tg C/yr with and without LULC change. After 2001, the LULC change showed a positive impact on the grassland carbon balance, and the region was projected to be a carbon sink. Ecological projects have made a significant contribution to grassland carbon storage. The paper provides a framework to account for the effects of LULC change on ecosystem carbon and highlights the importance of improving grassland management in balancing the grassland carbon budget, which is helpful to understand the regional carbon budget and better inform local land use strategies.

Climate change and land use land cover (LULC) changes are recognised as two of the most significant causes of environmental change. Climate change and LULC changes are related to one another. Land use change may drive climate change, and a changing climate may result in land cover changes. Climate change and LULC changes are believed to influence soil erosion. This chapter analyses the impacts of climate and LULC changes on soil erosion. The causes and effects of climate change on precipitation, temperature, solar radiation, atmospheric CO2 concentrations, and radiative forcing are discussed. The chapter includes the impacts of climate change on soil characteristics, vegetation cover, runoff, floods, and droughts and extends the impacts of these changes on water and wind erosion. The chapter explores the human alterations of LULC changes in terms of changes in the forest cover, alterations in agricultural lands, increase in urban areas, and decrease in wetland areas. The influence of the LULC changes on soil erosion and sediment production processes is discussed. Also, the combined impact of climate and LULC changes on soil erosion is explored, and mitigation strategies like sustainable land management practices and appropriate policy incentives to conserve soil are discussed.

This study researched the individual and combined impacts of future LULC and climate changes on water balance in the upper reaches of the Beiluo River basin on the Loess Plateau of China, using the scenarios of RCP4.5 and 8.5 of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). The climate data indicated that both precipitation and temperature increased at seasonal and annual scales from 2020 to 2050 under RCP4.5 and 8.5 scenarios. The future land use changes were predicted through the CA-Markov model. The land use predictions of 2025, 2035, and 2045 indicated rising forest areas with decreased agricultural land and grassland. In this study, three scenarios including only LULC change, only climate change, and combined climate and LULC change were established. The SWAT model was calibrated, validated, and used to simulate the water balance under the three scenarios. The results showed that increased rainfall and temperature may lead to increased runoff, water yield, and ET in spring, summer, and autumn and to decreased runoff, water yield, and ET in winter from 2020 to 2050. However, LULC change, compared with climate change, may have a smaller impact on the water balance. On an annual scale, runoff and water yield may gradually decrease, but ET may increase. The combined effects of both LULC and climate changes on water balance in the future were similar to the variation trend of climate changes alone at both annual and seasonal scales. The results obtained in this study provide further insight into the availability of future streamflow and can aid in water resource management planning in the study area.

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

Predicting the joint effects of future climate and land use change on ecosystem health in the Middle Reaches of the Yangtze River Economic Belt, China

Evaluating the joint effects of climate and land use change on runoff and pollutant loading in a rapidly developing watershed

<p>Human activities and climate affect the hydrology of a basin. The effect of Land Use Land Cover (LULC) change and climate change on streamflow are basin specific. In this study, an attempt has been made to evaluate the effects of LULC and climate change on streamflow in the Netravathi basin, Karnataka, India. The SWAT model, which reasonably simulates the streamflow of a basin, is used for this study. The analysis was done from the year 1990 to 2018. The watershed is delineated by using ALOS PALSAR DEM. Rainfall and temperature obtained from IMD are used as the climate variables. LULC maps were prepared using Landsat images of 1990 and 2018 in order to assess the LULC changes in the basin. The results showed that the spatial extent of the LULC classes of built-up (3.82%–6.51%), water bodies (0.76%–0.99%), and agriculture (11.96%–17.89%) increased, whereas that of forest (66.56%–51.7%), fallow (3.82%–6.13%), and barren land (13.07%–16.76%) decreased from 1990 to 2018. The streamflow increased steadily (5.02%) with changes in LULC from 1990 to 2018. The results indicate that LULC changes in urbanisation and agricultural intensification have contributed to the increase in runoff, in the catchment during this period. Thus, hydrological modelling integrating climate change and LULC can be used as an effective tool in estimating streamflow of the basin.</p>

The global land surface cover is undergoing extensive changes in the context of global change, especially in the Loess Plateau, where ecological restoration policies have been vigorously implemented since 2000. Evaluating the impact of these policies on land cover is of great significance for regional sustainable development. Nonetheless, there are few quantitative assessment studies of the impact of ecological restoration policies on land use and land cover change (LULCC). In this study, a relative contribution conceptual model (RCCM) was used to explore the contribution of the policies to LULCC under the influence of natural background change, which was based on the Markov chain and the future land use simulation (FLUS) model. The results show that LULCC is influenced by ecological restoration policies and the natural environment, of which the policies contribute about 72.37% and natural change contribute about 27.63%. Ecological restoration policies have a profound impact on LULCC, changing the original direction of LULCC greatly. Additionally, these policies regulate the pattern of LULCC by controlling the amount of cropland as a rebalanced leverage. These findings provide useful information for facilitating sustainable ecological development in the Loess Plateau and theoretically supporting environmental decision-making.

Assessing the impacts of future land use cover change (LUCC) and climate change (CC) on hydrological ecosystem services (HESs) is important for regional hydrological ecosystem protection and management. However, the current understanding of the combined effects of CC and LUCC on HESs remains insufficient, especially in the ecologically fragile karst regions. Based on this, this study takes a typical karst region as the study area, and based on the shared socioeconomic pathway (SSP) and representative concentration pathway (RCP) scenarios, the system dynamics (SD) model and the patch-generation land use model (PLUS) are used to simulate the future land use changes, and the spatial and temporal dynamics of the key HESs, such as water yield (WY), soil conservation (SC), and water purification (WP), are assessed. Results indicate that (a) under SSP126, WY and WP increase remarkably in the southeast and northwest, while SC improves in the southwest; however, under SSP585, SC declines and WP exhibits only limited improvement. (b) Synergistic relationships are observed between WY and WP across all scenarios, while trade-offs between SC and other services vary by scale, being more pronounced at the raster level and less so at the watershed scale. (c) Finally, ecosystem service bundles are used to define hydro-ecological management zones at multiple scales, informing adaptive water management strategies. These findings provide valuable insights into dynamic HES prediction and zonal management, offering practical guidance for managing water resources and conserving ecosystems in karst regions.

Detecting vulnerability of humid tropical forests to multiple stressors

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.

Impact of land use change on carbon storage based on the PLUS–InVEST model: A case study in the urban belt along the Yellow River, China

This study addresses the significant factors contributing to warming during the 20th century, namely Greenhouse Gases (GHG) and Land Use (LU), emphasizing the need for localized hydrological impact assessments. Recognizing the limitations of Global Climate Models (GCMs) in predicting local-scale phenomena, the research employs a downscaling approach for hydrological impact studies. Observed datasets and downscaled GCM data are utilized to analyze temperature, precipitation, and potential evapotranspiration (PET) trends. The study integrates downscaled GCM data from the Coupled Model Inter-comparison Project 6 (CMIP6) to project future climate scenarios under Representative Concentration Pathways (RCPs) 4.5 and 8.5. Runoff data from three stations within the Jhelum Basin is collected and analyzed over various time scales, providing a comprehensive understanding of historical and future hydrological trends. Future climate projections are corrected using the Daily Bias Correction (DBC) method). The study then employs the Soil & Water Assessment Tool (SWAT) model, given its suitability for hydrological studies with limited data availability. SWAT is calibrated and validated using SWAT CUP, incorporating observed river discharge. The impact assessment on runoff considers different climate change and land use change scenarios. Future Land Use and Land Cover (LULC) predictions are made for 2025 to 2100, and the model is rerun to analyze the combined impact of changing climate and LULC on runoff. The study aims to achieve a robust understanding of future water resource dynamics for runoff generation; the integrated assessment of climate and land use impact on the hydrological dynamics of the Jhelum Basin uncovers substantial shifts in runoff patterns. The combination of changing climate conditions and evolving Land Use/Land Cover (LULC) scenarios reveals intricate interactions, influencing the basin's hydrological response. Future projections highlight the nuanced interplay between climate scenarios and LULC changes, offering valuable insights into the complex dynamics of water resource management. These results provide essential information for policymakers and decision-makers, guiding the formulation of adaptive strategies to address the evolving challenges in runoff generation within the Jhelum Basin. The research explores runoff responses to LULC and climate change through scenario-based setups. By quantitatively analyzing the effects on runoff and peak discharge across different periods, the study provides valuable insights for policymakers and decision-makers in water resources. This integrated assessment contributes to a more informed and sustainable approach to water resource management in the Jhelum Basin amidst changing climatic and land use conditions.

Accurate prediction of land use and land cover (LULC) change is essential for sustainable development and climate change adaptation planning. This study projects LULC changes across 17 administrative regions of South Korea from 2020 to 2050 using the Future Land Use Simulation (FLUS) model under four integrated SSP-RCP scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The model was calibrated with land cover data for 2000–2010 and validated against observations for 2010–2020 using socioeconomic variables together with CMIP6 climate projections. In practical terms, FLUS produces scenario-based maps of future land patterns that inform land regulation, infrastructure planning, and climate adaptation. Across all scenarios, urban areas expanded by 488,000–585,000 ha, mainly through the conversion of agricultural land, which accounted for 10–24% of transitions in high-growth regions. Agricultural land decreased by 124,000–174,000 ha, and forests declined by 473,000–572,000 ha. Transformation intensity peaked around 2030 and then slowed in later decades. Urban expansion was greatest under SSP5-8.5, followed by SSP3-7.0, SSP1-2.6, and SSP2-4.5. Gyeonggi Province exhibited the most pronounced spatial change, whereas Seoul showed limited additional growth consistent with its already saturated urban structure. Validation results indicated an overall accuracy range of 57–83% with metropolitan areas generally outperforming provincial regions. These findings reveal spatial and temporal hotspots of land cover change and provide region-specific information that can guide urban development, land and ecosystem management, climate adaptation policy, and progress toward carbon neutrality.