Search

A healthy rural ecosystem ensures a win–win situation for both economic growth and ecological conservation. However, the impact of land use changes at the rural level on ecosystem health remains unclear. This study focuses on the rural scale of Zheng–Bian–Luo, analyzing changes in land use from 2000 to 2020. Using the “Ecosystem Vigor-Organization-Resilience-Services” model, the study evaluates the spatiotemporal patterns of ecosystem health. The Patch-generating Land Use Simulation (PLUS) model was employed to simulate land use and ecosystem health in 2035 under three scenarios: Natural Development (ND), Ecological Protection (EP), and Cropland Protection (CP). The findings are as follows: (1) From 2000 to 2020, the area of cultivated land in Zheng–Bian–Luo rural areas decreased, and the area of forest land first decreased and then increased. (2) During the study period, ecosystem health improved as ecosystem vigor, organization, and services increased. Low-value areas of ecosystem health showed a shrinking trend, most notably in Kaifeng. (3) By 2035, under the EP scenario, forest land increased by 76.794 km2, while it decreased under the CP and ND scenarios. Construction land showed an increasing trend in all three scenarios, with the ND scenario seeing the largest increase of 718.007 km2. (4) In 2035, ecosystem health is projected to decline under the ND scenario due to reduced forest land and increased construction land. The CP scenario showed no significant change in ecosystem health, but the southwestern rural areas of Luoyang improved. The EP scenario saw an overall increase in ecosystem health, highlighting land use optimization as beneficial. Local governments are encouraged to create ecological protection plans balancing ecological and cultivated land protection, focusing on sensitive areas such as the Songshan region and southwestern mountainous areas of Luoyang for coordinated development.

Investigating the evolution and drivers of multifunctional land use is essential for sustainable land management and regional biological conservation. This research focuses on the Hehuang Valley, where we developed an “ecological-social-production” evaluation system for assessing land use multifunctionality from the perspective of multifunctional landscape. Leveraging Geographic Information System technologies, we conducted a quantitative analysis of spatiotemporal variations in multifunctional land use across the valley in recently twenty years. Correlation coefficients were employed to identify trade-offs and synergies among various land use functions. Additionally, geographical detector and grey relational analysis models were utilized to pinpoint the factors influencing spatiotemporal changes in land use functions during the specified period. The results showed that: (1) During the period, the overall multifunctionality of land use in the Hehuang Valley exhibited an increasing trend. The economic production function of the land showed the highest growth, while the ecological and social functions showed lower growth. (2) In most areas of the Hehuang Valley, there was a positive correlation between social and economic production functions and a negative correlation between social and ecological functions, as well as between economic production and ecological functions. (3) Natural conditions were the main factors of spatial variation of land use comprehensive functions, but human factors, including land use intensity and the rate of farmland conversion to non-agricultural uses, were the primary drivers of temporal changes in multifunctional land use. The findings provide valuable references and scientific support for policymakers in optimizing land use and multifunctional landscape conservation.

With the increase in human activities and the acceleration of urbanization, over-exploitation of natural resources has led to a decline in ecosystem services (ESs), subsequently affecting the achievement of sustainable development goals (SDGs). As the key ecological zone of Qinghai-Tibet Plateau, the stability and enhancement of ESs in the Hehuang Valley are crucial for achieving SDGs and biodiversity conservation. This study quantifies nine SDGs for the Hehuang Valley in the last twenty years. Four ecological models were utilized to compute key ESs: net primary productivity (NPP), water yield, soil retention, and sand fixation. Panel data were analyzed using a coupling coordination model to quantify the relationship between ESs and sustainable development level (SDL) in each county. Additionally, the Geographically and Temporally Weighted Regression (GTWR) model was employed to examine the correlation between ESs and SDL. The results indicate the following: (1) During the period, NPP and water yield first increased and then decreased. The capacity for soil retention and sand fixation showed an overall increase, highlighting substantial variability among counties in their ability to deliver these ESs. (2) The SDL of counties in the Hehuang Valley increased, with Xining City showing slightly higher SDL than other counties. (3) The overall coupling coordination degree among NPP, water yield, soil retention, sand fixation, and SDL in the Hehuang Valley exhibited an upward trend in the last twenty years. SDL demonstrated the highest coordination degree with NPP, followed by soil retention, water yield, and sand fixation. (4) Most counties in the Hehuang Valley exhibited a lag in SDL relative to NPP, water yield, and soil retention in the last twenty years. In the early stage, sand fixation and SDL were primarily lagging in SDL, while in the late stages, sand fixation lagged behind SDL. (5) During the period, there was an increasing negative correlation observed between the four ESs and SDL. The positive contribution of NPP and sand fixation in some counties gradually shifted to a negative effect, and the negative effect of water yield and soil retention on SDL intensified. The impact of human activities on ecosystem function hindered local SDL. This study offers scientific theoretical backing and practical recommendations for promoting SDL and biodiversity conservation in the Hehuang Valley.

Clarifying the issues related to the supply, demand, and flow of ecosystem services is crucial for regional landscape management. This study employs the equivalence factor method and demand index quantification to analyze the supply and demand of ecosystem services in the Zheng-Bian-Luo region in 2000 and 2020. We used hotspot analysis tools and the minimum cumulative resistance model to establish the ecological corridors, identifying the spatial flow paths of ecosystem services in our site. By calculating the flow volume of the key corridor value through the breakpoint formula and field strength theory and combining this with the ratio of the regulating service value, we computed the ecological compensation amount, thereby realizing the value of the ecosystem service. The results indicate that the area of balance between ecosystem service supply and demand gradually decreased and the deficit area in the Zheng-Bian-Luo region increased 43.62% from 2000 to 2020 along with rapid urbanization. The total value flow of ecosystem services by the important ecological corridors in 2000 and 2020 was USD 242.40 million and USD 365.92 million, respectively. In 2020, it was predicted that Luanchuan County would receive ecological compensation totals of USD 237.76 million from each ecological demand area, and mainly from Jinshui District. Our findings support enhancing the quality of the ecological environment and optimizing the landscape management of the Yellow River’s Henan section.

Landscape connectedness, ecosystem service value (ESV), and resident welfare are intricately interconnected, and understanding their relationships is crucial for promoting regional sustainable development. Utilizing six stages of land use data from 1995, 2000, 2005, 2010, 2015, and 2020 in Xining City, Qinghai Province, this study identified landscape connectedness changes by landscape pattern indices, calculated ecosystem service value by the equivalent factor method, and quantified residents’ well-being by comprehensive evaluation indices. To investigate the coupled and coordinated states among the three, a coupling coordination model is adopted. Furthermore, the relative development degree model is employed to reveal the relative developmental level of the three, clarify the lagging factors in their coupling coordination. The gray relational model is employed to identify key factors affecting the coupling mechanism. Key findings include the following: (1) The development trend of landscape types was moving toward diversification and balance, and the total value of ecosystem services has been declining. The comprehensive level of resident welfare has increased annually, but the structure has changed. (2) The coupling relationship among landscape connectedness, ecosystem service value, and resident welfare is strong and has remained at a high correlation level but has been in a state of discord. (3) The main constraint of the discord in the early stage was resident welfare, but the constraining factors in the later stage shifted to ecosystem services and landscape connectedness. The largest patch index and water resource supply were the key influencing factors in the system coupling mechanism. The research findings can provide a reference for the sustainable development of Xining City, regional land use policies, and ecological intervention planning.

A watershed ecosystem is a compound ecosystem composed of land and rivers, and its health is closely related to the sustainable development of the region it is located in. The Yihe River Basin (YRB) in central China’s Henan province, which is located in the north–south transition zone and has a mountain–hill–plain landscape from the upstream to the downstream, is adopted as the research area in this study. A watershed ecosystem health assessment system is constructed based on an ecosystem vigor–organization–resilience–service supply and demand harmony (EVORSH) framework and utilized to assess the ecosystem health in the YRB by taking a 3 km × 3 km grid as the evaluation unit. Thirteen factors are selected from natural and human social factors, and from them, the factors that influence watershed ecosystem health through the generation of spatial heterogeneity are identified using the geographical detector model. The following findings are obtained. (1) The mean value of ecosystem health levels in the YRB is 0.65 and at the good level. The ecosystem health has considerable spatial heterogeneity. The areas with high–high concentration are distributed in the mountains in the upper reaches of the YRB, and the areas with low–low concentration are mainly distributed in the plain areas in the middle reaches of the YRB. (2) The geographical detector result shows that 9 of 13 factors have a considerable impact on the spatial distribution of the YRB’s ecosystem health. The interaction between two factors is enhanced synergically. The decisive power of population density, rainfall, and potential evapotranspiration are more than 0.5, so these three are the main factors that influence the distribution of ecosystem health in the YRB. (3) The EVORSH framework is suitable for the measurement of ecosystem health in the YRB. The evaluation result is consistent with the actual situation in the YRB. A 3 km × 3 km grid is used as the basic research unit, and it can more accurately and scientifically express the spatial heterogeneity of ecosystem health in the YRB compared with the macro evaluation unit. This study can provide a scientific basis for ecological protection and high-quality development planning in the YRB. By integrating multi-dimensional data and methods, the EVORSH framework proposed in this study can quickly and scientifically assess the status of ecosystem health, identify the influencing factors of spatial heterogeneity, and could be applied in other similar watersheds.

The Yellow River Basin assumes an important ecological and economic function in China. The study of carbon emissions from land use in the nine provinces (regions) of the pathway is important to achieve carbon reduction. Based on the dynamic data of land use, energy, and economic changes in nine provinces (regions) for the past 30 years from 1990 to 2018, this study analyzed the spatial and temporal evolution characteristics of land-use carbon emissions by using the carbon emission coefficient method in the IPCC inventory method and evaluating the low-carbon development model of the nine provinces (regions) by land-use carbon emission intensity. Finally, the LMDI model was used to analyze the factors influencing land-use carbon emissions. The results showed that: (1) in the past 30 years, the net carbon emissions have shown a continuously increasing trend, and the difference in the spatial distribution of carbon emissions in different periods was obvious. The carbon sink effect was not significant enough to offset the carbon emissions generated. (2) The continuously decreasing carbon emission intensity values per unit of GDP indicate that the coordination between land-use and economic development was getting better. (3) The factors of population size, economic size, and land-use structure accelerated land-use carbon emissions, whereas land-use efficiency limited land-use carbon emissions. Accordingly, this paper puts forward some corresponding policy suggestions.

The unique high/cold environment of the Qinghai–Tibet Plateau (QTP) limits the natural distribution of the population living there and threatens local residents’ health. Thus, exploring the quality of human settlements in this area is of great significance. In this study, 5 first-level indicators and 25 second-level indicators were initially selected, and the entropy TOPSIS method was used to determine the weight of each indicator and evaluate the quality of the human settlements in each county of the QTP. Then, the coefficient of variation and spatial autocorrelation were used to analyze the spatial differences in human settlement quality. Finally, the obstacle degree model was used to identify those obstacles that affect the quality of the human settlements in the QTP. This study has gathered important findings. (1) The human settlement quality in these counties can be divided into 18 high-level areas, 45 mid- and high-level areas, 44 mid-level areas, 79 mid- and low-level areas, and 28 low-level areas. (2) In terms of spatial patterns, the north is higher than the south, the east is slightly higher than the west, and the surrounding area is higher than the interior. (3) In the clustering model, the high–high clustering trend is mainly concentrated in the north of the QTP, whereas the south-central part of the QTP and the zone where Tibet, Qinghai, and Sichuan meet exhibit obvious low–low clustering. (4) The variability of human settlement quality occurs in the order of Sichuan < Yunnan < Gansu < Xinjiang Autonomous Region < Tibet Autonomous Region < Qinghai. (5) The main first-level obstacles affecting human settlement quality in the counties of the QTP are living conditions, construction level of public service facilities, and infrastructure. The main second-level obstacles are the number of living service facilities, the number of residential districts, and the density of the road networks.

The unique high-frigid environment and poor natural conditions of Qinghai–Tibet Plateau (QTP) have limited sustainable economic and social development. The construction of the beautiful QTP is a concrete implementation of the United Nations Sustainable Development Goals. However, identifying the progress and system coupling relationships of beautiful QTP construction entails some barriers due to data and methodological issues. To evaluate beautiful QTP construction and achieve a coordinated development regime, this paper employs an analytic hierarchy process and coupling model to quantify the comprehensive index and the coupling relationships of five subsystems (i.e., ecological environment, cultural inheritance, social harmony, industrial development, and institutional perfection) based on point of interest (POI) data, which are highly accurate, containing quantity and location information. Meanwhile, spatial autocorrelation analysis is conducted on the comprehensive index and coupling coordination degree for identifying the spatial clustering characteristics of the two. Results show that the progress of the beautiful QTP construction in most counties are under a very low or low level. For the system coupling perspective, 86% of counties are under the coupling stage indicating a strong interaction among the subsystems. However, coordination is out of harmony in most counties. For the spatial clustering characteristics, the comprehensive index and the system coupling relationships of beautiful QTP construction show a positive spatial correlation, indicating an aggregation effect. The aggregation is mostly “low–low” and “high–high” aggregation indicating the spatial differences and regional imbalances. The government should adopt measures to make the five subsystems of beautiful QTP construction more synergistic to achieve the sustainable development of the QTP. Our study formed a sample case of special areas where statistical data are scarce while constructing a technical framework of Beautiful China construction that is applicable to these areas. The findings of this study can serve as a reference for improving the beautiful QTP or other similar areas of construction.

In fragile and impoverished areas, identifying the interrelationship between livelihoods and ecosystem services can help protect the ecological environment and improve human well-being. This study selected the “One River and Two Tributaries” region (ORTTR) in Tibet with a fragile, sensitive ecological environment as the study area. With the years 2000, 2005, 2010, 2015, and 2020 as the research time points, a coupled evaluation model of residents’ livelihood and land ecosystem services was constructed to study the relationship between the two. Results showed that from 2000 to 2020, the coupling degree and coupling coordination degree between the two continued to increase because of the improvement in residents’ livelihood and ecosystem services. The level of coupling coordination gradually changed from a reluctant coordination stage to a moderate coordination stage. The coupling coordination degree showed more revealing results than the coupling degree in time scale. The relative development type between the two was mainly of the type lagging residents’ livelihood. By considering the physical geography and socio-economic characteristics and the relative development types, the counties and districts in the ORTTR are divided into ecological conservation areas, ecological restoration areas, and ecological reconstruction areas. The coupled model can evaluate the relationship between livelihoods and ecosystem services from a systematic integration perspective and provide scientific support for the improvement of regional human well-being.

Urbanization has an important effect on ecosystem services (ESs) and identifying the relationship between urbanization and ESs can provide a decision-making reference for regional ecological protection and management. Taking the areas along the Yellow River of Henan Province (AYRHP) as a research area, a coupling system of ESs and urbanization is established in this study to reveal the coupling relationship between the two. ESs are estimated by using Carnegie–Ames–Stanford approach, revision universal soil loss equation, and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models. The urbanization level is evaluated from three dimensions, namely, population, economy, and land. The coupling coordination relationship between various ESs and urbanization in AYRHP is quantified from 2000 to 2018 on the county scale based on the coupling coordination degree (CCD) model. The lead–lag relationship between ESs and urbanization is identified by using the relative development degree model, and ecological management zoning is conducted. Results show that in the study period, net primary production (NPP), soil conservation, and food production are increased, whereas water yield is decreased. In the study period, population, economy, and land urbanization level are increasing, and the comprehensive urbanization level is increased by 51.63%. The total CCD between NPP, food production, and water yield and comprehensive urbanization is basic or moderate coordination, whereas that between soil conservation and comprehensive urbanization is moderate maladjustment. In the research period, the coupling coordination between NPP and food production and comprehensive urbanization is increasing; that between water yield and comprehensive urbanization is fluctuated; and that between soil conservation and comprehensive urbanization is decreasing. The result of the research into the relative development degree in 2018 showed that food production, water yield, and soil conservation lag behind the urbanization level in most regions and counties along the Yellow River of Henan Province. On the basis of the lead–lag relationship between different ESs and urbanization level, the AYRHP are divided into ecological reconstruction area, ecological and agricultural improvement area, and ecological conservation area. CCD and relative development degree models can be used to evaluate the coordination relationship between ESs and urbanization, which provides scientific support for regional ES management.

Scientifically measuring the quantitative coupling relationship between urban–rural construction land (URCL) and population and formulating URCL utilization countermeasures are needed for protecting cultivated land resources, intensive utilization of land resources, and sustainable socioeconomic development. This study proposed an improved transition process theory of URCL and population and a coupling model of polar coordinates. Then, the coupling model was applied to Henan Province in China to analyze the coupling relationship between URCL and population, showing that the coupling relationship between URCL and urban–rural population (URP) in the province was unreasonable. However, the coupling rationality between rural construction land (RCL) and rural population (RP) had a significant improvement tendency. Furthermore, the coupling relationship between URCL and the population of prefecture-level cities in Henan province was analyzed, and the coupling model of polar coordinates proposed in this study achieved satisfactory results. Thus, compared with the commonly used Tapio’s decoupling model of elasticity, the coupling model further extends the concept of coupling analysis to the coupling type, coupling strength, and coupling rationality. The extension makes the measurement of the quantitative coupling relationship between URCL and population more scientific, comprehensive, and accurate.

With the rise of the strategy of Coordinated Development for the Beijing-Tianjin-Hebei Region, it is necessary to evaluate the trade-offs/synergies of the survival environment and human well-being in Hebei, the capital region of China. However, existing methods cannot analyze and express trade-offs/synergies of two or more variables simultaneously. Therefore, this paper proposes a new framework to express the trade-offs/synergies among land-use intensity, ecosystem services, and human well-being. In this paper, we first identified the land-use intensity change and land-use transformation and evaluated ecosystem services and human well-being in Hebei from 2000–2015 under the Millennium Ecosystem Assessment framework. Then, the trade-offs/synergies of the three indicators were determined by GIS-based methods and MATLAB. The results show that land-use intensity and human well-being mainly present a synergistic relationship, while ecosystem services and land-use intensity mainly present a trade-off relationship, and ecosystem services and human well-being also present a trade-off relationship in Hebei during 2000–2015. In addition, some regional solutions to achieve sustainable development were proposed: region 1 needs to adjust land-use structure, region 2 needs to protect the ecological environment to improve the supply of ecosystem services, and region 3 needs to commit to improving the regional comprehensive human well-being. This study not only proposes a new framework for analyzing trade-offs/synergies of land use intensity, ecosystem services, and human well-being, but it also provides regional solutions for Hebei to achieve sustainable development.

Accurate supply and demand matching of ecosystem services (ESs) is important for managing regional ecosystems. On the basis of remote-sensing, meteorological, and socio-economic data, we mapped the supply, demand, and matching status of four ESs (i.e., water production, carbon sequestration, food supply, and soil conservation) using biophysical models and the ArcGIS spatial analysis module within the Zhengzhou–Kaifeng–Luoyang (ZKL) urban agglomeration in 2018. Four-quadrant analysis was employed to identify the spatial matching types of supply-demand relationships within the study region. The results are as follows. The supply-demand ratios of different ESs in the cell scale exhibit different spatial characteristics because of major influencing factors, including the natural environment (e.g., precipitation and temperature) and social development (e.g., urbanization level). Analysis of the supply-demand imbalances of the four ESs indicates that water production is deficient across the entire research area, whereas the whole research area’s carbon sequestration, food supply, and soil conversation are in the surplus state. Regarding the spatial matching types for supply and demand of the four ecosystem services, water production is dominated by the “low–low (low supply and low demand)” type. Carbon sequestration is dominated by the “low–low” and “high–low (high supply and low demand)” types. The “low–low” type dominates food supply and soil conservation. Due to the severity of the deficit in water production, all districts and counties in the ZKL urban agglomeration are identified as areas requiring ecological conservation, ecological restoration, or ecological improvement. Development guidance strategies and planning suggestions are proposed in different ecological areas. These policies could also be applied in other similar urban agglomerations.

The continuous supply of ecosystem services is the foundation of the sustainable development of human society. The identification of the supply–demand relationships and risks of ecosystem services is of considerable importance to the management of regional ecosystems and the effective allocation of resources. This paper took the Yihe River Basin as the research area and selected water yield, carbon sequestration, food production, and soil conservation to assess changes in the supply and demand of ecosystem services and their matching status from 2000 to 2018. Risk identification and management zoning were also conducted. Results show the following: (1) The spatial distribution of the four ecosystems service supply and demand in the Yihe River Basin was mismatched. The food production supply levels in the middle and lower reaches and the upstream water yield, carbon sequestration, and soil conservation supply levels were high. However, most of the areas with high demand for ecosystem services were concentrated downstream. (2) From 2000 to 2018, the supply of water yield and carbon sequestration in the Yihe River Basin decreased, while that of food production and soil conservation increased. The demand for the four ecosystem services also increased. (3) Water yield faced considerable supply–demand risks. Fifty percent of the sub-basins were at a high-risk level, and the risk areas were concentrated in the middle and lower reaches. The three remaining services were mainly at low-risk levels. The Yihe River Basin was divided into eight types of supply–demand risk spatial management zones based on the ecosystem service supply and demand levels, which will help promote refined regional ecosystem management and sustainable development. The supply and demand assessment of ecosystem services from a risk perspective can integrate the information of natural ecosystems and socio-economic systems and provide scientific support for watershed spatial management.

Analyzing the temporal variation of runoff and vegetation and quantifying the impact of anthropic factors and climate change on vegetation and runoff variation in the source area of the Yangtze River (SAYR), is of great significance for the scientific response to the ecological protection of the region. Therefore, the Budyko hypothesis method and multiple linear regression method were used to quantitatively calculate the contribution rates of climate change and anthropic factors to runoff and vegetation change in the SAYR. It was found that: (1) The runoff, NDVI, precipitation, and potential evaporation in the SAYR from 1982 to 2016 all showed an increasing trend. (2) The mutation year of runoff data from 1982 to 2016 in the SAYR is 2004, and the mutation year of NDVI data from 1982 to 2016 in the SAYR is 1998. (3) The contribution rates of precipitation, potential evaporation and anthropic factors to runoff change of the SAYR are 75.98%, −9.35%, and 33.37%, respectively. (4) The contribution rates of climatic factors and anthropic factors to vegetation change of the SAYR are 38.56% and 61.44%, respectively.

The use of the spatiotemporal data fusion method as an effective data interpolation method has received extensive attention in remote sensing (RS) academia. The enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) is one of the most famous spatiotemporal data fusion methods, as it is widely used to generate synthetic data. However, the ESTARFM algorithm uses moving windows with a fixed size to get the information around the central pixel, which hampers the efficiency and precision of spatiotemporal data fusion. In this paper, a modified ESTARFM data fusion algorithm that integrated the surface spatial information via a statistical method was developed. In the modified algorithm, the local variance of pixels around the central one was used as an index to adaptively determine the window size. Satellite images from two regions were acquired by employing the ESTARFM and modified algorithm. Results showed that the images predicted using the modified algorithm obtained more details than ESTARFM, as the frequency of pixels with the absolute difference of mean value of six bands’ reflectance between true observed image and predicted between 0 and 0.04 were 78% by ESTARFM and 85% by modified algorithm, respectively. In addition, the efficiency of the modified algorithm improved and the verification test showed the robustness of the modified algorithm. These promising results demonstrated the superiority of the modified algorithm to provide synthetic images compared with ESTARFM. Our research enriches the spatiotemporal data fusion method, and the automatic selection of moving window strategy lays the foundation of automatic processing of spatiotemporal data fusion on a large scale.

Studying the characteristics, trends, and evolution of carbon emissions in agricultural related sectors is of great significance for rational formulation of carbon emission reduction policies. However, as an important carbon emission reduction policy, carbon tax has been controversial over whether or not it should be levied on China. Based on this consideration, this paper takes China’s agricultural related sectors as an example and analyzes the degree of carbon tax on macro-environment, macroeconomy, and agricultural sectors during the period 2020–2050 by constructing a 3EAD-CGE (economy-energy-environmental-agricultural-dynamics Computable General Equilibrium) model. The results show that: (1) carbon tax has a time effect, specifically, the short-term effect is better than the long-term. (2) If the incremental rate of carbon tax is carried out alone, it will exert a great influence on the macroeconomy as well as on most of the agricultural related sectors. (3) If a carbon tax is introduced at the same time as indirect taxes are cut (proportionally), the policy will exert a negative impact on agriculture-related sectors that are subsidized. However, the policy will have a positive impact on those nonsubsidized sectors. Finally, based on the results, we put forward some suggestions that are more suitable for the introduction of a carbon tax in China’s agricultural-related sectors.