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Clarifying the complex relationships among ecosystem services (ESs) and the driving mechanisms of ecosystem service (ES) is essential for supporting regional ES and ecological sustainability. Although studies on ES relationships provide guidance for regional ecological management, the driving mechanisms of ES have not been adequately studied, especially in areas with complex natural environments and progressive urbanization. Combined with the data on land use, climate, NDVI, and soil data, this paper aims to explore this issue by analyzing the relationships among ESs and the driving mechanisms of ESs in the western Sichuan Plateau region of China. Firstly, the temporal and spatial distribution characteristics of five ecosystem services (food supply, water supply, habitat quality, soil conservation, and carbon storage) from 2000 to 2020 were analyzed by the InVEST model. Second, the trade-offs/synergistic relationships among ESs were analyzed using SPSS as well as the Pearson product-moment correlation coefficient method in MATLAB. Finally, the Geodetector model was further used to reveal the influencing factors of ecosystem services in the western Sichuan Plateau. The results showed that: (1) Water supply decreased in the western Sichuan Plateau from 2000 to 2020, but increased in the eastern part; habitat quality was generally good in the whole Sichuan Plateau, but decreased in some areas; carbon storage showed an overall improving trend; soil conservation showed an overall increasing and then decreasing trend, and food supply services showed an increasing trend. (2) From 2000 to 2020, food supply and other services in the western Sichuan Plateau were in a trade-off relationship; all other service pairs showed a synergistic relationship. (3) In terms of space, the relationships between ecosystem services showed spatial heterogeneity. There was a synergistic relationship between food supply and habitat quality in some areas, such as Litang County and Xinlong County, and there was a trade-off relationship between water supply and carbon storage services in some areas, such as Ruoergai County and Daocheng County, etc. (4) The Geodetector results showed that food supply and soil conservation were mainly influenced by the slope (0.682, 0.672), annual precipitation was the strongest explanation for water supply (0.967), and habitat quality and carbon storage were the most influenced by NDVI (0.876, 0.828); meanwhile, each ecosystem service was interactively influenced by multiple factors. Based on the results, we proposed ecological management recommendations for the western Sichuan Plateau, the most important one being that the western Sichuan Plateau should protect and rationally use the existing natural resources, especially the existing forest and grassland resources, and at the same time reform the agricultural structure and scientifically plan urban development, to promote the coexistence of cities and nature. We took the western Sichuan Plateau of China, where urbanization and a complex natural environment are in opposition, as an example, to explore its ecosystem services, relationships, and driving mechanisms, and then put forward suggestions on ecological management and control, providing a reference for future regional coordination between urbanization and the natural environment.

The degradation and loss of global urban habitat and biodiversity have been extensively studied as a global issue. Urban heat islands caused by abnormal land surface temperature (LST) have been shown to be the main reason for this problem. With the accelerated urbanization process and the increasing possibility of abnormal temperatures in Zhengzhou, China, more and more creatures cannot adapt and survive in urban habitats, including humans; therefore, Zhengzhou was selected as the study area. The purpose of this study is to explore the response of urban habitat quality to LST, which provides a basis for the scientific protection of urban habitat and biodiversity in Zhengzhou from the perspective of alleviating heat island effect. We used the InVEST-Habitat Quality model to calculate the urban habitat quality, combined with GIS spatial statistics and bivariate spatial autocorrelation analysis, to explore the response of habitat quality to LST. The results show the following: (1) From 2000 to 2015, the mean value of urban habitat quality gradually decreased from 0.361 to 0.304, showing a downward trend as a whole. (2) There was an obvious gradient effect between habitat quality and LST. Habitat quality’s high values were distributed in the central and northern built-up area and low values were distributed in the high-altitude western forest habitat and northern water habitat. However, the distribution of LST gradient values were opposite to the habitat quality to a great extent. (3) There were four agglomeration types between LST and habitat quality at specific spatial locations: the high-high type was scattered mainly in the western part of the study area and in the northern region; the high-low type was mainly distributed in the densely populated and actively constructed central areas; the low-low type was mainly distributed in the urban-rural intersections and small and medium-sized rural settlements; and the low-high type was mainly distributed in the western mountainous hills and the northern waters.

The land is the material basis for human survival, and the contradiction between people and land has become increasingly prominent. The land ecological problem has gradually become a hot spot of concern. It is imperative to make a scientific evaluation of the land ecological quality and propose reasonable and feasible improvement measures and recommendations. At present, domestic research on environmental cost and environmental cost degradation mostly focuses on theoretical discussion, and there are few applications and practical research on enterprise environmental cost management. Based on the principle of protecting the ecological environment, this paper creates an ecological service assessment model to assess the real economic cost of land use development projects. From small community projects to large-scale national projects, because environmental costs are difficult to estimate, this paper uses the recovery cost method and the preventive expenditure method to quantify environmental costs. The cost of environmental degradation mainly comes from water pollution and air pollution. This paper uses the pollution function method to quantify the cost of environmental degradation. The InVEST model is used to evaluate the value of ecosystem services, and the BP neural network method is used to optimize the ecosystem service model, and the sensitivity analysis of the data is used to feedback the impact of the project on ecosystem services. The ecosystem service model based on neural network optimization makes the accuracy of data measurement results reaching 99.7%, which makes the model having a good generalization. Taking a paper mill as an example, this paper evaluates environmental costs by resource consumption cost, environmental degradation value and environmental governance cost, and estimates environmental degradation costs by major environmental governance costs. Finally, the environmental cost and environmental degradation cost are integrated, and the ecosystem service model is established. The neural network model was established in the Matlab environment based on the InVEST model, and the model simulation results of the ecosystem service system were obtained. Compared with the InVEST results, the results of this paper have better authenticity and market utilization value. Although a paper mill was used as an example, the system was evaluated and the evaluation results were analysed. Compared with the actual situation, there is a certain reliability. However, due to the limited data, the number of verifications is insufficient for the system. It is hoped that more data can be verified later to ensure its reliability.

The contribution of biodiversity to the global economy, human survival, and welfare has been increasing significantly, but the anthropogenic pressure as a threat to the pristine habitat has followed. This study aims to identify habitat suitability, analyze the change in habitat quality from 1988 to 2018, and to investigate the correlation between impact factors and habitat quality. The InVEST habitat quality model was used to analyze the spatiotemporal change in habitat quality in individual land-use types in the Winike watershed. Remote sensing data were used to analyze the land use/land cover changes. Nine threat sources, their maximum distance of impact, mode of decay, and sensitivity to threats were also estimated for each land-use cover type. The analysis illustrates that habitat degradation in the watershed was continuously increasing over the last three decades (1988 to 2018). Each threat impact factor and habitat sensitivity have increased for the last 30 years. The most contributing factor of habitat degradation was the 25.41% agricultural expansion in 2018. Population density, land-use intensity, elevation, and slope were significantly correlated with the distribution of habitat quality. Habitat quality degradation in the watershed during the past three decades suggested that the conservation strategies applied in the watershed ecosystem were not effective. Therefore, this study helps decision makers, particularly regarding the lack of data on biodiversity. It further looks into the conflict between economic development and conservation of biodiversity.

Urban green space is a direct way to improve the carbon sink capacity of urban ecosystems. The carbon storage assessment of megacity green spaces is of great significance to the service function of urban ecosystems and the management of urban carbon zoning in the future. Based on multi-period remote sensing image data, this paper used the CASA model and the InVEST model to analyze the spatio-temporal variation and driving mechanism of carbon storage in Shenzhen green space and discussed the applicability of the two models to the estimation of carbon storage in urban green space. The research results showed that, from 2008 to 2022, in addition to the rapid expansion of construction land, the area of green space and other land types in Shenzhen showed a significant decrease trend. The estimation results of the carbon storage model showed that the carbon storage of green space shows a significant trend of reduction from 2008 to 2022, and the reduction amounts are 0.8 × 106 t (CASA model) and 0.64 × 106 t (InVEST model), respectively. The evaluation results of the model show that, in megacities, the spatial applicability of InVEST model is lower than that of CASA model, and the CASA model is more accurate in estimating the carbon storage of urban green space. The research results can provide a scientific basis for the assessment of the carbon sink capacity of megacity ecosystems with the goal of \"dual carbon\".

Exploring the spatial distribution of land use/cover change (LUCC) and ecosystem carbon storage under future climate change scenarios can provide the scientific basis for optimizing land resource redistribution and formulating policies for sustainable socioeconomic development. We proposed a framework that integrates the patch-generating land use simulation (PLUS) model and integrated valuation of ecosystem services and tradeoffs (InVEST) model to assess the spatiotemporal dynamic changes in LUCC and ecosystem carbon storage in Guangdong based on shared socioeconomic pathways and representative concentration pathways (SSP-RCP) scenarios provided by the Coupled Model Intercomparison Project 6 (CMIP6). The future simulation results showed that the distribution patterns of LUCC were similar under SSP126 and SSP245 scenarios, but the artificial surface expanded more rapidly, and the increase in forest land slowed down under the SPP245 scenario. Conversely, under the SSP585 scenario, the sharply expanded artificial surface resulted in a continuous decrease in forest land. Under the three scenarios, population, elevation, temperature, and distance to water were the highest contributing driving factors for the growth of cultivated land, forest land, grassland, and artificial surface, respectively. By 2060, the carbon storage in terrestrial ecosystems increased from 240.89 Tg in 2020 to 247.16 Tg and 243.54 Tg under SSP126 and SSP245 scenarios, respectively, of which forest ecosystem carbon storage increased by 17.65 Tg and 15.34 Tg, respectively; while it decreased to 226.54 Tg under the SSP585 scenario, and the decreased carbon storage due to forest destruction accounted for 81.05% of the total decreased carbon storage. Overall, an important recommendation from this study is that ecosystem carbon storage can be increased by controlling population and economic growth, and balancing urban expansion and ecological conservation, as well as increasing forest land area.

The past decades were witnessing unprecedented habitat degradation across the globe. It thus is of great significance to investigate the impacts of land use change on habitat quality in the context of rapid urbanization, particularly in developing countries. However, rare studies were conducted to predict the spatiotemporal distribution of habitat quality under multiple future land use scenarios. In this paper, we established a framework by coupling the future land use simulation (FLUS) model with the Intergrated Valuation of Environmental Services and Tradeoffs (InVEST) model. We then analyzed the habitat quality change in Dongying City in 2030 under four scenarios: business as usual (BAU), fast cultivated land expansion scenario (FCLE), ecological security scenario (ES) and sustainable development scenario (SD). We found that the land use change in Dongying City, driven by urbanization and agricultural reclamation, was mainly characterized by the transfer of cultivated land, construction land and unused land; the area of unused land was significantly reduced. While the habitat quality in Dongying City showed a degradative trend from 2009 to 2017, it will be improved from 2017 to 2030 under four scenarios. The high-quality habitat will be mainly distributed in the Yellow River Estuary and coastal areas, and the areas with low-quality habitat will be concentrated in the central and southern regions. Multi-scenario analysis shows that the SD will have the highest habitat quality, while the BAU scenario will have the lowest. It is interesting that the ES scenario fails to have the highest capacity to protect habitat quality, which may be related to the excessive saline alkali land. Appropriate reclamation of the unused land is conducive to cultivated land protection and food security, but also improving the habitat quality and giving play to the versatility and multidimensional value of the agricultural landscape. This shows that the SD of comprehensive coordination of urban development, agricultural development and ecological protection is an effective way to maintain the habitat quality and biodiversity.

To support the “dual-carbon” strategy and develop a carbon-sink-oriented coastal spatial planning framework, this study applies the coupled InVEST–PLUS model to Qingdao using 30 m resolution land-use data. Six spatial drivers (DEM, slope, GDP, population, road, and water proximity) are used to simulate land-use change and evaluate its impact on carbon storage. Model validation results indicate that the PLUS model shows good performance (Kappa ≈ 0.79, FoM = 0.168). The results indicate that (1) during 2010–2020, land-use patterns in the study area changed markedly, characterized by a decrease in farmland and an expansion of architecture area, while forest increased slightly and overall ecological land declined. (2) Total carbon storage dropped from 5.3174 × 10 7 t (2010) to 5.2749 × 10 7 t (2020), with a net loss of 4.25 × 10 5 t. Spatially, carbon storage showed a “clustered-high, contiguous-medium, radial-low” pattern. (3) DEM and water proximity primarily drove the expansion of farmland, forest, grassland, and waters, while population density and DEM dominated architecture growth; bare land expansion was mainly driven by population. Based on these findings, carbon storage transfer pathways are quantified, providing a scientific basis for low-carbon-oriented territorial spatial governance in coastal zones.

Studying the spatiotemporal distribution pattern of carbon storage, balancing land development and utilization with ecological protection, and promoting urban low-carbon sustainable development are important topics under China’s “dual carbon strategy” (Carbon emissions stabilize and harmonize with natural carbon absorption). However, existing research has paid little attention to the impact of land use changes under different spatial policies on the provincial-scale ecosystem carbon storage. In this study, we established a carbon density database for Liaoning Province and obtained the spatial and temporal distribution of carbon storage over the past 20 years. Then, based on 16 driving factors and multiple spatial policies in Liaoning Province, we predicted land use and land cover changes (LUCC) under three scenarios for 2050 and analyzed the spatiotemporal distribution characteristics and response mechanisms of carbon storage under different scenarios. The results showed that (1) LUCC directly affected carbon storage, with a 35.61% increase in construction land and a decrease in carbon storage of 0.51 Tg over the 20-year period. (2) From 2020 to 2050, the carbon storage varied significantly among the natural trend scenario (NTS), ecological restoration scenario (ERS), and economic priority scenario (EPS), with values of 2112.05 Tg, 2164.40 Tg, and 2105.90 Tg, respectively. Carbon storage in the ecological restoration scenario exhibited positive growth, mainly due to a substantial increase in forest area. (3) The spatial pattern of carbon storage in Liaoning Province was characterized by “low in the center, high in the east, and balanced in the west”. Therefore, Liaoning Province can consider rationally formulating and strictly implementing the spatial policy of ecological protection in the future land planning so as to control the disorderly growth of construction land, realize the growth of ecological land area, effectively enhance carbon storage, and ensure the realization of the goal of “dual carbon strategy”.

Research on habitat quality change is of great significance for regional ecological security. Analysis of spatiotemporal change of habitat quality based on different geomorphic types can restore the background of ecological environment in historical periods and provide scientific support for revealing the evolution law of regional ecological environment quality and ecological restoration. This study aimed to identify the change in habitat quality under different geomorphic types from 1995 to 2018. Based on DEM data, geomorphic types of different scales were divided. The InVEST habitat quality model was used to analyze the spatiotemporal change in habitat quality in individual land use types in the Altay region. The spatiotemporal changes and main influencing factors of habitat quality under the background of different geomorphic types were explored. Remote sensing data was used to analyze the land use/cover changes. Sixteen threat sources, their maximum distance of impact, mode of decay, and sensitivity to threats were also estimated for each land use type. The results showed that habitat quality decreased significantly in 2015, which was related to the rapid expansion of cultivated and construction land as threat sources, as well as the decrease of forestland and grassland as sensitive factors. However, habitat quality improved significantly in 2018, because of the implementation of ecological restoration policy in 2015. Affected by elevation and topographic relief, the geomorphic type with the best habitat quality index was the large undulating middle mountain (0.927) and the worst was the medium altitude platform (0.351). Woodland contributed the most to habitat quality in large undulating middle mountain (35.07), and bare rock gravel land contributed the most to medium altitude platform (127.68). Habitat quality of different geomorphic types showed obvious spatial aggregation, and from high altitude to low altitude showed a banded ladder-like distribution. Changes in habitat quality during the past three decades suggested that the conservation and restoration strategies applied in regional ecosystem were effective. On the basis of the analysis results, four types of zoning management schemes were divided, and the ecological management and conservation measures were put forward. Therefore, this study can help decision makers, especially regarding the lack of data on biodiversity.