Uncovering the evolution process of rural revitalization level (RRL) in China and elucidating the complex driving mechanism hold significant implications for implementing rural revitalization strategy and advancing rural modernization. This study analyzes the spatio-temporal evolution of China’s RRL from 2002 to 2022 and reveals its complex driving mechanism. The results show that China’s RRL steadily increased from 0.1083 to 0.4463, and the provincial RRL exhibited the characteristic of decreasing successively in the eastern region, the central region, and the western region. The overall differences of RRL are shrinking, and intra-group differences contribute almost 1/3 of the overall variation, more than the contribution of inter-group differences. Although the influencing factors show nonlinear characteristics, on the whole, economic level and human capital exhibit positive effects, while relief degree, urbanization, industrialization, and opening degree exhibit negative effects. Farmland resources and investment intensity exhibit the characteristics of positive effect and negative effect equilibrium. At the regional scale, influencing factors exhibit significant spatio-temporal heterogeneity. In the future, to achieve comprehensive rural revitalization, it is vital to implement systemic policy measures, such as enhancing industrial competitiveness, supplementing rural talents, and optimizing the relations between urban and rural areas as well as between industry and agriculture.
Data centers operate as physical digital infrastructure for generating, storing, computing, transmitting, and utilizing massive data and information, constituting the backbone of the flourishing digital economy across the world. Given the lack of a consistent analysis for studying the locational factors of data centers and empirical deficiencies in longitudinal investigations on spatial dynamics of heterogeneous data centers, this paper develops a comprehensive analytical framework to examine the dynamic geographies and locational factors of techno-environmentally heterogeneous data centers across Chinese cities in the period of 2006-2021. First, we develop a “supply-demand-environment trinity” analytical framework as well as an accompanying evaluation indicator system with Chinese characteristics. Second, the dynamic geographies of data centers in Chinese cities over the last decades are characterized as spatial polarization in economically leading urban agglomerations alongside persistent interregional gaps across eastern, central, and western regions. Data centers present dual spatial expansion trajectories featuring outward radiation from eastern core urban agglomerations to adjacent peripheries and leapfrog diffusion to strategic central and western digital infrastructural hubs. Third, it is empirically verified that data center construction in Chinese cities over the last decades has been jointly influenced by supply-, demand-, and environment-side locational factors, echoing the efficacy of the trinity analytical framework. Overall, our findings demonstrate the temporal variance, contextual contingency, and attribute-based differentiation of locational factors underlying techno-environmentally heterogeneous data centers in Chinese cities.
Agricultural greenhouse gas (GHG) emissions are influenced by a combination of climate, soil and agricultural management practices. Over the past 30 years, approximately 5% of China’s cropland has shifted from the south to the north. This shift has significantly altered the geographical environment, with potential substantial impacts on agricultural GHG emissions. This study used the DeNitrification DeComposition (DNDC) process-based model to simulate GHG emissions (CH4 and N2O) from the production of China’s 10 major food crops and explored changes in agricultural GHG emissions caused by the spatial shift of cropland in China. Results from the validated DNDC model indicate that total emissions from the major food crop production in China were approximately 343 Tg CO2-eq yr-1 with CH4 emissions accounting for about 74%. Meanwhile, the spatial shift of cropland from 1990 to 2020 resulted in a 3% decrease in average CH4 emissions per unit cropland area and an 8% increase in average N2O emissions per unit cropland area, respectively. The expansion of dryland in the Northwest Arid Region emitted less CH4 but significantly more N2O, thereby driving changes in national GHG emissions. This study provides a scientific foundation for the sustainable use of cropland and the formulation of strategies to reduce agricultural GHG emissions.
Dryland regions face complex interactions between urbanization and ecological changes, where effective coordination is essential for enhancing sustainability and resilience. However, most studies concentrate on the national or provincial scales, with insufficient research on county-level coordination, limiting the ability to provide targeted policies from a precise perspective. This study addresses this gap by analyzing 39 counties within the Hohhot-Baotou-Ordos-Yulin Urban Agglomeration (HBOYUA), a typical dryland urban cluster in China. We use daytime and nighttime remote sensing images to track the spatio-temporal evolution of urbanization and ecological conditions from 1992 to 2023. A novel quantitative framework based on an improved coupling coordination degree (CCD) is proposed to assess their coordination relationship. The results reveal that: (1) Urbanization and ecological quality both exhibited fluctuating upward trends, with spatial heterogeneity increasing for urbanization and decreasing for the eco-environment. Regions with better ecological conditions had higher urbanization levels. (2) The overall coordinated level improved from imbalance (0.36) to low-level coordination (0.55), although its spatial distribution remained uneven, with central urban areas showing higher CCD than surrounding counties. (3) Socioeconomic factors exerted greater effects on CCD than natural factors, with GDP and land surface temperature (LST) playing a significant role in interaction analysis. (4) In western arid regions, urbanization did not necessarily harm ecosystems; instead, ecological conditions improved alongside urbanization. This research offers targeted and valuable references for county and city governments in resource allocation and sustainable development. The proposed methodology is also adaptable for urban resilience studies in other regions.
A comprehensive understanding of vegetation responses to climate extremes is essential for predicting ecological risks. The Tianshan Mountains, the world’s largest arid mountain system, are ecologically vulnerable to climate extremes, yet the spatiotemporal heterogeneity of vegetation responses is not well understood. To address this, we assessed changes in vegetation phenophases using the green-up date (GUD) and the monthly maximum vegetation index (MVI). Their relationship with climate extremes across seasons and geographic units was analyzed using Classification and Regression Tree and Principal Component Analysis. Results indicate that GUD advanced by 0.276 days/year, with MVI increasing in spring and decreasing in summer. On a yearly scale, nighttime heatwaves advanced GUD in all vegetation types at lower altitudes with higher snow cover, whereas daytime heatwaves delayed GUD in grasslands. On a monthly scale, early spring heatwaves generally benefitted vegetation, with positive effects decreasing from forests to grasslands: forests benefitted from March to May, forest-grassland from March to April, and grasslands only in March. By late summer, heatwaves were negatively correlated with MVI across all vegetation types. This study highlights the complex responses of vegetation to climate extremes and underscores the vulnerability of high-altitude, low snow-covered grasslands, which is crucial for guiding restoration efforts.
Urban lakes are vital components of the modern urban water system and landscape design. They play an important role in the construction of urban ecological civilization. However, in recent years, the urban lake ecosystem has been increasingly degraded, especially with the frequent cyanobacteria blooms, which directly threatens the maintenance of ecosystem service function and sustainable urban development. In this study, several sedimentary cores were collected from Hudie Lake located in the Yangtze River Delta in China that had not been dredged for centuries. Using one of the sediment cores that spans the past 200 years, we reconstructed the long-term environmental changes and examined the driving mechanisms of both human activities and natural factors affecting the lake’s dynamics. Our results indicated that, with the growth of the city, organic matter and nutrients in the lake had gradually increased. Notably, the significant increase in phosphorus had been a key factor driving cyanobacteria blooms in Hudie Lake. Since the 1960s, urban development and changes in land use around the lake had severely disturbed its natural habitats, leading to peak nutrient levels during the period from 2000 to 2010.
Lacustrine sedimentary nitrogen isotope (δ15N) records offer crucial insights into the impacts of regional anthropogenic activities and environmental changes on nitrogen cycling dynamics within the context of global climate change. This study summarized δ15N data from 27 Chinese lakes since 1750 CE, categorizing them into Types I (eastern and southern China, densely populated area) and II (Northwestern China [NWC] and the Qinghai-Tibet Plateau [QTP], sparsely populated area). The results showed pronounced regional and temporal variability in nitrogen isotope trends. Type I lakes exhibited a significant positive δ15N deviation post-1950 CE, linked to population growth (r=0.91, p<0.01) and economic development, with mitigation after 2000 CE likely due to enhanced environmental policies. Conversely, Type II lakes showed coherent δ15N variations with natural climate change from 1750 to 1950 CE, followed by a post-1950 CE decline exceeding natural variability. This shift is attributed to a “warming-wetting trend” in NWC and the QTP, which presumably increased terrestrial productivity, altered nitrogen cycling, and enhanced 15N-depleted nitrogen input via surface runoff. Rising temperatures may have enhanced the activity and abundance of nitrogen-fixing microorganisms, jointly driving a negative δ15N shift. This study highlights climate conditions and anthropogenic activities as key drivers of nitrogen cycle perturbations in China, with their influences varying spatiotemporally, thereby providing crucial insights into the nitrogen cycling dynamics in Chinese lakes.
To address the contradiction between the rapid development of ski tourism and effective protection of the ecological environment, this study constructed the DPSIR-EES (Drive-Pressures-State-Impact-Response-Environment-Economy-Society) model and Ski Tourism Destination Ecological Security System (STDESS) framework system. They form an integrated methodology system based on the “entropy weighting-hierarchical analysis-gray correlation projection” composite weighting method that can be used to clarify the intrinsic mechanism of ecological security in ski tourism destinations. Taking Chongli as a case study, this study evaluated the evolution of its ecological security from 1995 to 2023, predicted the ecological security early warning levels from 2024 to 2050, and analyzed the mechanism of influences on regional ecological security. The findings indicate that the ecological security of ski tourism destinations shows a significant “stepped leap - dynamic equilibrium” evolutionary path. The dynamic response mechanism of the subsystems is characterized by significant heterogeneity. The ecological security early warning system revealed the temporal and sequential differentiation of risk transmission. The factors influencing ecological security show the significant dual dominance of policy and climate. This paper enhances the applicability of ecological security systems within ski tourism contexts by analyzing their evolutionary characteristics, predicted future changes and impact factors, and it provides an effective case study for ecological improvement.
Investigating the spatial distribution of vegetation in monsoonal-climate-dominated high mountain area and detecting its changes that occurred in paraglacial areas is crucial for understanding the cascading environmental effects of shrinking glaciers. We used Landsat images from 1994 to 2022, obtained landscape distribution patterns of glaciers and vegetation in Mt. Gongga, and detected paraglacial vegetation changes under deglaciating environments. We observed there is a pronounced difference in glacier and vegetation coverage between the eastern and western slopes in Mt. Gongga, the eastern slope occupies 78.68% of vegetation area and 61.02% of glacier area, whilst the western slope occupies lower area. Exaggerate warming accelerated glacier retreat, and proglacial areas are generally characterized by very fast primary succession, resulting in an increase of 0.32 km2 in vegetation area within two typical glacier forefields on the eastern slope. The phenomenon of paraglacial slope failure following glacier thinning is widespread in Mt. Gongga, resulting in vegetation area decreased by 0.34 km2. Concurrently, the fast retreat of glaciers and changes in ice surface geomorphology have caused rapid dynamics in supraglacial vegetation developed on its lower debris-covered sections. We suggested that rapid changes of temperate glaciers can significantly influence paraglacial landform, leading to rapid dynamic changes of vegetation in a balance between colonization and destruction.
With the continuous evolution of urban surface types, the impact of the urban heat island effect on the human population has intensified. Investigating the factors influencing urban thermal environments is crucial for providing theoretical support to urban planning and decision-making. In this study, Shenyang was selected to comprehensively analyse multiple factors, including topography, human activity, vegetation and landscape. Moreover, we used the random forest algorithm to explore nonlinear factors influencing land surface temperature (LST) over four years in the study area. The results revealed that from 2005 to 2020, the total areas with sub-high and high-temperature zones in northern Shenyang steadily increased. The area ratio of these zones increased from 20.18% in 2005 to 24.86% in 2020. Additionally, significant and strong correlations were observed between LST and variables such as the enhanced vegetation index (EVI), normalised difference vegetation index (NDVI), population density, proportion of cropland and proportion of impervious land. In 2010, proportion of impervious land exhibited the strongest correlation with LST at the 5 km scale, reaching 0.852 (p<0.01). The 4 km grid scale was identified as the optimal grid size for this study, while the 2 km grid performed the worst. In 2020, NDVI emerged as the most significant factor influencing LST. These findings provide valuable guidance for improving urban planning and developing sustainable strategies.
The conversion of subtropical red soils into farmland involves complex transformations of iron oxides. Investigating iron mineralogy can enhance understanding of magnetic minerals in relation to soil formation on farmland in subtropical regions. In this study, we investigated the properties of iron oxide and its environmental implications in the farmland of Meizhou city, Guangdong province. The results showed that farmland soils had higher magnetism than the red soils developed from the same metamorphic rock. The red soils displayed significantly higher concentrations of goethite and hematite than the farmland soils. The dominant factor influencing the magnetic changes in farmland and red soils was the concentration of fine-grained ferromagnetic minerals. Red soil magnetism is an indicator of soil weathering intensity, whereas farmland soil magnetism is closely related to human cultivation activities. In contrast to the red soils, the farmland soils lacked the pronounced transformation of ferromagnetic minerals into hematite and goethite. A vigorous oxidation process catalyzes the transformation of strong magnetic minerals into significant amounts of hematite and goethite, which promotes the reduced magnetism of red soils. The conversion of red soils into farmland soils initially increased the accumulation of ferromagnetic materials due to cultivation processes. However, long-term cultivation led to the gradual loss of fine-grained ferromagnetic minerals, while goethite and lepidocrocite became the dominant magnetic mineral types.
