China's ecosystem service value in 1992-2018: Pattern and anthropogenic driving factors detection using Bayesian spatiotemporal hierarchy model

Dynamics of ecosystem services and nonlinear responses to increased anthropogenic pressure

Escalating global human activities elicit diverse ecosystem service responses, yet understanding remains limited. This study establishes a framework to clarify these responses, focusing on the Yangtze River Economic Belt in China. Analyzing 2000-2020 data, it calculates ecosystem service economic value and human footprint index. It introduces the ecosystem services response index and comprehensive responsiveness index to assess response characteristics and intensity to anthropogenic pressures. Results show a fluctuating decline in ecosystem services and an increase in anthropogenic pressures. There is a nonlinear relationship: ecosystem services decline with rising pressures, following a U-shaped trend. Notably, nonurban agglomerations experience more significant ecosystem service evolution than urban agglomerations due to differing environmental conditions. This highlights regional disparities in human activity impacts on ecosystems, crucial for planning.

Spatial scale effects on the value of ecosystem services in China's terrestrial area

Identifying the response characteristics of ecosystem service value (ESV) to changes in spatial scales, known as spatial scale effects, is crucial in guiding the development of corresponding management strategies. This paper examines ESV in China's terrestrial area during the year 2020, revealing the spatial aggregation characteristics of ESV and the trade-off and synergistic relationships of ecosystem services at different spatial scales, ranging from 1 km × 1 km-10 km × 10 km, with a gradient of 1 km. The results indicate: 1) The distribution pattern of ESV in China's terrestrial area is "high in the southeast and low in the northwest." 2) The spatial characteristics of ESV in China's terrestrial area undergo a distinct transition at the 3 km × 3 km scale. In detail, the spatial clustering features show a trend of first rising and then falling with the increase in spatial scale, while the synergistic relationships between different ecosystem services strengthen and the trade-off relationships weaken with the increase of the spatial scale. These findings can inform the formulation of differentiated ecological protection compensation policies and enable cross-area trading of ecological values in China.

Ecosystem degradation or restoration? The evolving role of land use in China, 2000-2020

Dramatic land use change in China affects ecosystem degradation and restoration. Identifying the evolving role of land use in ecosystem degradation and restoration in China is essential for sustainable land policy making. However, it is not clear how land use affects ecosystem degradation and restoration over time. Here, we used the revised benefit transfer approach and spatial statistics based on land use data to determine the evolving role that land use plays in ecosystem degradation and restoration in China during 2000-2020. The study results pointed out that the deterioration of the forestland ecosystem during the study period was the main reason for ecosystem degradation, while the conversion of arable land to forestland was the main cause for ecosystem restoration. Every 1% increase of land use intensity in the periods 2000-2005, 2005-2010, 2010-2015, and 2015-2020 resulted in -1.754%, 0.697%, 1.098%, and -0.058% of the changes in ecosystem services, respectively. This study provided important policy implications for future sustainable land use management in China.

Land resource management patterns and urban air quality-evidence from the "land for development" model with Chinese characteristics

Based on panel data of 282 prefecture-level and above cities in China from 2013 to 2020, this paper investigates the impact and transmission paths of the "LFD" land disposal model on urban air quality at the theoretical and empirical levels using dynamic fixed-effects and dynamic spatial Durbin models. The results show that the way land is allocated in a city has a lagging and long-term impact on air quality not only locally but also in neighboring cities. The type of land supply by local governments to different sectors is an important pathway to influence urban air quality. Extended analysis shows that land market reforms in China can significantly reduce urban air quality index (AQI) and effectively mitigate urban air quality, with long-term effects. This paper provides a theoretical and scientific basis for correcting the mismatch of land resources and promoting urban ecological environment in China.

Exploring interactions in water-related ecosystem services nexus in Loess Plateau

Scientific understanding of the driving relationship between water-related ecosystem services (WESs) and influencing factors, as well as the trade-off and synergy relationship between WESs and WESs, is the premise of reasonably bringing them into management decisions. However, the existing research often separates the above-mentioned two relationships and conducts independent research, which leads to the conflict of research conclusions and cannot be well adopted by managers. Therefore, based on the panel data of Loess Plateau in 2000-2019, this paper uses the simultaneous equation model to combine the two kinds of relationships existing between WESs and influencing factors, establish a feedback loop, and reveal the interactions mechanism of WESs nexus. The results show that: (1) The fragmentation of land use leads to the uneven spatial-temporal distribution of WESs. (2) Vegetation factors and land factors are the main driving factors that affect WESs, and the impact of climate factors on WESs is decreasing year by year. (3) The increase of water yield ecosystem services will lead to the obvious increase in soil export ecosystem services, and there is a synergistic relationship between soil export ecosystem services and nitrogen export ecosystem services. The conclusion can provide an important reference for implementing the strategy of ecological protection and high-quality development.

Integrating Spatial Heterogeneity into an Analysis between Ecosystem Service Value and Its Driving Factors: A Case Study of Dalian, China

Human demand for natural resources has grown, leading to ecological debasement and related ecological system administration. Using Dalian as an example, we estimated the changes in the ecosystem service value (ESV) in 2005 and 2020. We used ArcGIS and spatial statistics to conduct estimations and change analyses of the ESV. Based on the results of the ESV, the geographical detector and geographically weighted regression (GWR) elucidated the contributions of different driving factors of the ESV in a 2 km grid. In summary, these results indicated that: (1) from a holistic perspective, the ESV of Dalian fell by 206.8009 billion CNY over 15 years, and the hot spots were concentrated in both the northern and the western parts, whereas the cold spots were distributed in the central part; (2) according to the results from the geographical detector, land use structure factors influenced the ESV most significantly, followed by socio-economic factors, and the impact of natural factors was relatively small; and (3) according to the results of the GWR, land use structure factors negatively affected the ESV, and the positive impact of the proportion of the natural land area was the most obvious. We conclude that the decline in the ESV reflects the impact of human activities on the ecosystem in the studied landscape. Understanding ESV changes should be made a priority in ecosystem management, and evaluating ESV drivers can contribute to developing land use strategies for policy-making.

Natural and anthropogenic factors on China's ecosystem services: Comparison and spillover effect perspective

With the development of urbanization, ecological space is increasingly disturbed and invaded by human activities. From 2000 to 2020, the value of ecosystem services in China decreased from 28.05 to 27.77 trillion yuan. This paper combines the natural and social data of 370 administrative units in China from 2000 to 2020 with the GTWR model. Our results show that in most regions of China, the coefficient value of factor GDP or POP is significantly higher than that of other factors. The regions with higher natural factors coefficient value are concentrated in the northwest and southeast. In addition, this study found that the driving factors and ESV have geographical spillover effects. The above conclusions have important practical significance for planning policies according to local conditions.

Ecological risk changes and their relationship with exposed surface fraction in the karst region of southern China from 1990 to 2020

Due to anthropogenic disturbances, the karst region in southern China is vulnerable to ecological problems such as soil erosion and surface exposure. However, limited studies on variations in large-scale ecological risk (ER) and their influencing factors, particularly the coupling/decoupling relationship with an exposed surface fraction (ESF), make ER regulations and ecological restoration challenging. The present study evaluates the ER of eight typical karst provinces in Southern China from 1990 to 2020 using the technique for order preference by similarity to an ideal solution (TOPSIS) model and ecosystem services (habitat quality, water yield, carbon storage, soil conservation, and food production), and extracts the contemporaneous ESF using Landsat satellite data in Google Earth Engine (GEE). The spatiotemporal change of ER and ESF are analyzed, and their coupling/decoupling relationship and driving mechanism are explored using coupling coordination degree (CCD) and multi-scale geographically weighted regression (MGWR) models. The results show that: (1) Over the past 30 years, the ER has increased until 2010 and subsequently declined, with an increasing mean value (0.463-0.503), except in Chongqing municipality. The ESF decreased significantly (the mean value dropped from 44.7% to 38.7%), except that in Sichuan province. (2) The average CCD between ER and ESF decreased with fluctuation of -0.017, with a decoupling relationship (58.18%). The coupling area is larger than the decoupling area in the Sichuan area, while other provinces are opposite. (3) The coupling/decoupling relationship in the study area is mainly driven by terrain (elevation, slope) and socio-economic (population density, per capita GDP) factors. More attention should be paid to the role of these factors in the continuous reduction and control of ESF and ER. This study can serve as a reference for similar studies in karst regions, such as risk assessment and surface monitoring, rocky desertification control, ecological engineering layout, and territorial planning.

Interactive influences of meteorological and socioeconomic factors on ecosystem service values in a river basin with different geomorphic features

Ecosystem service value (ESV) is influenced by land use and land cover (LULC), and is closely related to natural conditions and human activities. However, the interactions between human and natural systems and ESV remain unclear, especially concerning widely discussed meteorological and socioeconomic factors. In this study, three periods of LULC patterns (2000, 2010, and 2020) in the Haihe River Basin, northern China, were collected to determine the relationship between changes in LULC and ESV over time. Natural and socioeconomic data associated with ESV were obtained and the structural equation model was used to decouple interactions between these factors. Results showed that the total value of regional ecosystem services has decreased as cultivated land shrunk and artificial surfaces increased over the past two decades. The ESV was significantly decreased in the middle of the basin. The direct effects of meteorological factors and socioeconomic factors on ESV were positive (0.094) and negative (-0.203), respectively. The indirect effect of socioeconomic factors on ESV through meteorological and LULC factors was 0.149. Structural equation modeling demonstrated that under the dominance of LULC, interactions between natural and socioeconomic factors affected ESV in a complex manner. These results implied that identifying the direct and indirect effects of economic development and human activities on ESV could guide and implement effective land management policies.

Health and Human Wellbeing in China: Do Environmental Issues and Social Change Matter?

How to mitigate greenhouse gas emission and achieve human development remain major sustainability issues, particularly in China. Empirical research on the effects of climate warming and social change on human health and wellbeing is quite fragmented. This study examines the impact of environmental issues and social changes on health and human wellbeing using a time series data of China from 1991 to 2020. Findings show that environmental issues have a negative impact on health and human wellbeing in long run. While the internet is a form of social change that tends to improve health and human wellbeing in the long run. FDI exerts a positive effect on human health, but it does not improve wellbeing in the long run. In contrast, financial development does not improve human health but it has a significant positive impact on wellbeing in the long run. Our empirical insights have important implications for achieving human wellbeing through the pursuit of environmental sustainability and social change.

Identifying Urban Wetlands through Remote Sensing Scene Classification Using Deep Learning: A Case Study of Shenzhen, China

Urban wetlands provide cities with unique and valuable ecosystem services but are under great degradation pressure. Correctly identifying urban wetlands from remote sensing images is fundamental for developing appropriate management and protection plans. To overcome the semantic limitations of traditional pixel-level urban wetland classification techniques, we proposed an urban wetland identification framework based on an advanced scene-level classification scheme. First, the Sentinel-2 high-resolution multispectral image of Shenzhen was segmented into 320 m × 320 m square patches to generate sample datasets for classification. Next, twelve typical convolutional neural network (CNN) models were transformed for the comparison experiments. Finally, the model with the best performance was used to classify the wetland scenes in Shenzhen, and pattern and composition analyses were also implemented in the classification results. We found that the DenseNet121 model performed best in classifying urban wetland scenes, with overall accuracy (OA) and kappa values reaching 0.89 and 0.86, respectively. The analysis results revealed that the wetland scene in Shenzhen is generally balanced in the east–west direction. Among the wetland scenes, coastal open waters accounted for a relatively high proportion and showed an obvious southward pattern. The remaining swamp, marsh, tidal flat, and pond areas were scattered, accounting for only 4.64% of the total area of Shenzhen. For scattered and dynamic urban wetlands, we are the first to achieve scene-level classification with satisfactory results, thus providing a clearer and easier-to-understand reference for management and protection, which is of great significance for promoting harmony between humanity and ecosystems in cities.

Scale Effects on the Calculation of Ecosystem Service Values: A Comparison among Results from Different LULC Datasets

Land use/land cover (LULC) has an important impact on the ecological environment and is crucial for calculating ecosystem service values (ESVs). However, whether and to what extent the ESVs vary when calculated by LULC product data at different spatial scales remain unclear. Data from two LULC products were used in this study, and two datasets with different spatial scales were obtained by resampling. Then, the ESVs were calculated by the equivalent factor method. Finally, the impacts of LULC on ESVs at different scales were studied, revealing the following: (1) The ESVs calculated by LULC products and by the same products at different scales are different. (2) The difference in the ESVs calculated by the two LULC datasets is approximately 28%, and the difference tends to decrease with increasing scale. (3) With an increase in the LULC scale, the overall change trend of ESVs also increases, and the increasing trend gradually moderates. In addition, the ESVs and LULC scale conform to a logarithmic relationship, and the coefficient of determination (R2) is greater than 0.7. These results have important reference value for obtaining reliable ESVs.