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Zhejiang Province, one of the fastest-growing regions in China in terms of industrialization and urbanization, also faces significant challenges, including environmental degradation and a sharp increase in carbon emissions during its development. This study employed the PLUS model to analyze land use patterns in Zhejiang Province for 2017 and 2022, achieving overall accuracies of 0.903 and 0.902, and Kappa coefficients of 0.809 and 0.810, respectively. The InVEST model then projected carbon storage changes from 2026 to 2034 across four scenarios: Natural Development (ND), Cropland Protection (CP), Urban Development (UD), and Ecological Protection (EP). The main findings are as follows: (1) The distribution of carbon storage shows spatial heterogeneity, with a decreasing trend from west to east. From 2001 to 2022, changes in land use have resulted in an increase in forested areas. (2) From 2026 to 2034, carbon storage is projected to decrease by 118,800 tons in the ND scenario, 171,400 tons in the UD scenario, 166,100 tons in the EP scenario, and 200,800 tons in the CP scenario. Despite the increase in vegetation, changes in soil carbon stock, particularly the decomposition rate, may limit the expansion of carbon storage. (3) Trends suggest that carbon storage changes from 2026 to 2034 will follow this order: EP > CP > ND > UD, with stabilization projected by 2030. This study explores the relationships between carbon storage, land cover types, and development patterns, offering recommendations to optimize land use and enhance sustainability. [ABSTRACT FROM AUTHOR]

Introduction: Wetland has been exposed to tremendous stresses and hazards, leading to many potential ecological risks in the past few decades. There is an urgent need to assess the ecological risk status of the wetland, especially when examining how the intensity of socio-economic growth, policy changes, and other variables affect land use and ecological risk changes.Methods: This study models the LULC pattern in the Liaohe Estuary National Nature Wetland Reserve under various future scenarios in 2000–2040 and develops a long-term Pressure-State-Response ecological risk assessment model based on the characteristics of the northern wetland environment in China, combined with the simulated multi-scenario PLUS model.Results: As the two most distinct vegetation types in the reserve area, Phragmites australis and Suaeda glauca presented decreasing trends of 59.7 ha/year and 9.0 ha/year in the economy development scenario (EDS), higher than 57.3 ha/year, 8.2 ha/year in the natural increase scenario (NIS), and 35.4 ha/year and 5.8 ha/year in the ecological protect scenario (EPS). From the core area to the buffer area to the outer experimental area, the slope rate of vegetation deterioration rises severely. In comparison to the scenario of EDS, the area of aquiculture and oil wells can be lowered by 11.4 ha/year and 1.1 ha/year with the application of ecological protection measures. Besides, under three scenarios, mean ecological risks are all showing an increasing trend from 2000 to 2040, which is generally higher in the EDS scenario than that in the NIS and EPS scenarios. The proportion of the high and very high level of ecological risk area continually increased from 28.8% to 40.4% from 2000 to 2040, which was mainly located in the south estuary and west urban areas. In addition, among the three protected areas, the ecological risk in the core area has a lower growth rate than that in the outer buffer zone and experimental zone.Discussion: Aiming for the development of Liaohe Estuary National Park, these findings provide quantitative guidance for protecting and restoring natural resources.

Study region: The Min River basin, China. Study focus: In order to investigate the ecohydrological response under historical and future land use changes, we simulated daily runoff sequences under different land use scenarios by coupling the PLUS model with the Physical Hydrological Model and quantitatively assessed the ecohydrological impacts of different land use changes in the watershed by combining the IHA method. New hydrological insights for the region: The Min River Basin is dominated by grassland, woodland and, cultivated land which account for 94 % of the total. During the period 2000–2020, the area of cultivated land decreased by 4.47 % overall, and construction land increased by 78.68 % overall. Compared to the base year of 2010, the multi-year average monthly runoff increased under different land use scenarios. The high flow indicators (1 daymax, 7 daymax, and 30 daymax) had the largest increasing trend under the natural development scenario in 2030, 54 m3/s, 33 m3/s, and 24 m3/s, respectively, whereas their increase decreased under the ecological protection scenario in 2030; the low flow indicators (1 daymin, 7 daymin, and 30 daymin) decreased less in the 2030 eco-protection scenario than in the natural development scenario, where they decreased by − 5 m3/s, − 9 m3/s, and − 11 m3/s, respectively. The results of the study contribute to a deeper understanding of the response of watershed hydrological processes to land-use change.

The urban landscape is being affected by rapid urbanization, leading to a complexity of land features and a fragmentation of patches. However, many studies have focused on the prediction of land-use change with a lack of research on the landscape character types which have more integrated descriptions of land features. Hence, this study predicts and identifies landscape character types (LCTs) in different periods based on the PLUS model and the K-Medoids algorithm, taking the central city of Chongqing as an example, to reveal the differences in the influence of driving factors on LCTs. The results show that (1) the urban landscape characteristic types present a gradient change from the built-up area to the outward expansion. (2) The SHDI and LPI of landscape character types decreased significantly with the expansion of construction land. (3) Nighttime light, distance from water bodies, and distance from the motorways are the main factors affecting the change of landscape character types. This study predicts and identifies urban landscape character types and quantifies the impact of urban expansion on landscape character. It can be used to guide urban planning and help governments to make more informed decisions on sustainable urban development and ecological conservation. [ABSTRACT FROM AUTHOR]

Rapid urbanization has caused changes in climate and environment and threatened the ecosystem with multiple risks. The ecosystem services capacity has shown a downward trend accordingly. It is significant to explore the spatio‐temporal evolution of land use and ecosystem services value (ESV) in mountainous counties at small scales, as it coordinates economic growth and ecological protection, and promotes sustainable and high‐quality development. Based on the SD‐PLUS model, the study simulated three scenarios of land‐use change in Qianshan city from 2019 to 2035: high‐growth rate, medium‐growth rate, and low‐growth rate, and studied the impacts of land‐use change on the ESV. Results showed that: (1) Under the three scenarios, the construction land in the study area increased significantly, the forest and water have a decreasing trend, and the scale of gardens partly increased. (2) In the urban built‐up areas, a significant amount of construction land is centrally expanded, whereas, in mountainous regions, construction land exhibits sporadic point expansion. And among the various factors that influence land‐use change, the impact of roads at all levels is the most significant, followed by elevation. (3) The overall ESV shows a downward trend, with the low‐growth rate scenario dropping the least (4.91%). The value distribution changes little at the space scale, and different regions demonstrate different degrees of change. From the perspective of value type, the service values of water conservation and waste treatment are significantly reduced, while that of food production is relatively stable; from the perspective of various lands with their ESV, cultivated land and forest remain stable. The study results can provide technical ideas for the coordinated economic development and ecological protection of mountainous cities and boost the implementation of green development. [ABSTRACT FROM AUTHOR]

The urban landscape is being affected by rapid urbanization, leading to a complexity of land features and a fragmentation of patches. However, many studies have focused on the prediction of land-use change with a lack of research on the landscape character types which have more integrated descriptions of land features. Hence, this study predicts and identifies landscape character types (LCTs) in different periods based on the PLUS model and the K-Medoids algorithm, taking the central city of Chongqing as an example, to reveal the differences in the influence of driving factors on LCTs. The results show that (1) the urban landscape characteristic types present a gradient change from the built-up area to the outward expansion. (2) The SHDI and LPI of landscape character types decreased significantly with the expansion of construction land. (3) Nighttime light, distance from water bodies, and distance from the motorways are the main factors affecting the change of landscape character types. This study predicts and identifies urban landscape character types and quantifies the impact of urban expansion on landscape character. It can be used to guide urban planning and help governments to make more informed decisions on sustainable urban development and ecological conservation.

• Proposed a methodology for ecological zoning classification based on the ESV and LER. • In 2000–2020, the ESV increased 2.34 billion yuan, and LER exhibited an upward trend. • In 2040, the area of ecological conservation zone will decrease by 10.48 %. • Efficient zoning management strategies were proposed to promote regional development. Rapid urbanization has caused numerous environmental issues, constraining regional sustainable development. Constructing ecological zoning is conducive to scientific ecological protection and management. Taking the Anhui section of the water and soil conservation functional area in the Dabie Mountains of China as an example, this study calculated the ecosystem service value (ESV) and landscape ecological risk (LER) from 2000 to 2020 using the value equivalent method and the landscape ecological risk index, respectively, and analyzed their spatio-temporal evolution characteristics. Considering the vulnerability of ecosystem and its service functions, four types of ecological zones were constructed based on ESV and LER, and the PLUS model was used to predict the ecological zones in 2030 and 2040. The results indicated that: (1) The main land use type in the study area was forestland, accounting for 75 % of the total area. During the study period, the most significant increase in land use was observed in cropland, with an increase of 268.03 km2, while the most significant decrease was in grassland, with a total reduction of 645.26 km2. (2) Low and medium-low risk zones were the main LER types in the study area, accounting for approximately 85 % of the total area. The LER gradually shifted towards medium-high risk zones, showing a slight upward trend. The ESV showed a continuous increasing trend, with a total increase of 2.34 billion yuan. The ESV was dominated by medium ESV, and the area was expanding. (3) The ecological zoning was primarily dominated by ecological conservation zone, with a rapid expansion of 21.83 %. In contrast, the ecological protection zone had the smallest area and the largest decrease, reaching 48.55 %. It was expected that the spatial distribution of ecological zones will remain similar to that of 2020 from 2030 to 2040, with the largest decrease in the area of ecological conservation zones. The accelerating urbanization process may be the main reason for this phenomenon. [ABSTRACT FROM AUTHOR]

Numerous scholars have warned that many cities in the Greater Bay Area (GBA) are threatened by severe flood risk, which is often underestimated. Considering this, we provide a scenario-based Strategic Environmental Assessment (SEA) approach to analyse the roles of adaptation strategies on the environment in response to climate change and flooding risk. Three strategies are proposed including a non-Nature-based Solutions strategy (non-NbS), and two Nature-based Solutions strategies (NbS 1.0 and NbS 2.0). The non-NbS strategy refers to the way of promoting urban development yet no additional environmental concerns. The NbS 1.0 strategy focuses on ensuring arable lands for food security, and the NbS 2.0 strategy acquires further regulations on ecology protection. The analysis consists of two steps. First, this paper simulates the land use scenarios in 2030 and 2050, respectively, following non-NbS and NbS (1.0 & 2.0) strategies. This process is developed based on a patch-generating land use simulation (PLUS) model, which allows users to explore various future land use scenarios on account of different spatial development strategies, environmental conditions, and socio-economic trends. Second, the study overlays the land use scenarios with potential sea flooding scopes to reveal how different landscapes (e.g., forests and wetlands) are affected by carbon emissions in RCP 2.6 and RCP 8.5. Further research is suggested to incorporate the 2020 GDP data to refine the findings of this study and consider the impacts of dykes on flood-prone area mapping. The analysis finds that the NbS (1.0 & 2.0) strategies play an active role in decreasing the future flood risk of built-up areas in the GBA regionally, especially under the high-emission RCP 8.5 projection. However, their impacts vary between cities. (1) The NbS 2.0 strategy is effective in reducing the risk of built-up areas in Shenzhen, Hong Kong, and Macao, while the effectiveness of the NbS 1.0 strategy is not apparent. (2) The NbS 1.0 and 2.0 strategies are both effective in Dongguan, Guangzhou, Huizhou, Jiangmen, Zhuhai, Zhaoqing, and Zhongshan in reducing the flood risk of built-up areas. In addition, the NbS 2.0 strategy is more productive than the NbS 1.0 strategy either in 2030 or 2050. (3) The NbS 1.0 and 2.0 strategies generate subtle different effects in Foshan in 2030 and 2050. The NbS 2.0 strategy is more productive in 2050, while less productive in 2030. This study provides a comprehensive insight into the distributed flood risk following the non-NbS or NbS strategies in the context of climate change, which is useful to policymakers and urban planners. • SEA advances the consideration of climate adaptation in land use management and urban planning. • The PLUS model simulates 2030 and 2050 scenarios for the Greater Bay Area, focusing on growth and environmental sustainability. • This study reveals the distributed flood risk on different land use scenarios in RCP 2.6 and 8.5. • The study assesses how various adaptation strategies impact flood risk under climate change at regional and municipal scales. • Nature-based solutions do not work the same way in reducing the flood risk between cities. [ABSTRACT FROM AUTHOR]