Search Results (40)

Urban agglomeration ecosystems are impacted by human activities and natural disasters, so analyzing the spatial and temporal evolution of landscape ecological resilience from the perspective of adaptive cycling is crucial. Using the Changsha–Zhuzhou–Xiangtan urban agglomeration in China as a case study, this research constructs a “Risk-Potential-Connectivity” framework to evaluate ecological resilience. This framework applies exploratory spatial data analysis methods to examine the spatiotemporal evolution and associated patterns of resilience and the Geodetector model to measure the driving factors of spatial variation. This study constructs an adaptive cycle model based on ecological resilience analysis, integrating potential and connectivity indices to classify the development stages of urban agglomeration regions dynamically. The results showed that the overall spatial distribution pattern of ecological risk decreased from the center outward, whereas ecological potential and connectivity increased. The average resilience index from 2000 to 2020 was 0.31, with a declining trend and shifting center of gravity from northwest to southeast. The spatial and temporal distribution of toughness exhibited high and low aggregation, with an overall Moran index greater than 0.75. Land-use intensity had the strongest explanatory power (q = 0.3662) for the spatial differentiation of landscape ecological resilience drivers and the joint effects of factor interaction had a higher explanatory power than single factors. Adaptive cycle analysis revealed that Furong District is in the protection stage, Xiangtan County in the development stage, and Liling City in the reorganization stage, with no region yet in the release stage. The findings offer a better understanding of the interactive adaptation characteristics and evolutionary patterns of social-ecological systems over extended periods, providing scientific support for the formulation of protection strategies to respond to dynamic changes in urban agglomeration ecosystems. Full article

Understanding the interdependencies among production, living, and ecological spaces (PLESs) is critical for sustainable regional development. Urban fringe areas, shaped by rapid urbanization and conflicting land-use demands, are particularly vulnerable to spatial tensions. This study analyzes the spatiotemporal dynamics and drivers of PLES conflicts in Zengcheng District, Guangzhou, a representative urban fringe region. Using land-use data from 2010 to 2020, the study applies the optimal parameter geographic detector, chosen for its ability to untangle complex spatial interactions, to quantify conflict intensity and identify key drivers. This method was chosen over other spatial analysis techniques due to its ability to effectively capture nonlinear relationships and interaction effects between variables, which traditional regression-based or spatial autocorrelation methods often fail to fully address. The results indicate that production and ecological lands dominated the landscape, while living space expansion slowed, leading to escalating conflicts, particularly in the southern and central regions. The PLES conflict index shows that severe conflict units rose from 0.89% in 2010 to 2.15% in 2020, despite over 80% of spatial units remaining stable. Moderate conflicts peaked in 2015 before declining, while stronger conflicts intensified, especially in rapidly urbanizing areas. Conflict hotspots were most pronounced in rapidly urbanizing zones, particularly at the interface of urban expansion and ecological conservation areas. Moreover, the driving forces behind these conflicts transitioned from economic and urbanization factors to a multifaceted interplay of natural and social determinants, underscoring the growing intricacy of spatial dynamics. These findings offer crucial insights into the mechanisms driving PLES conflicts, guiding urban planners and policymakers in developing strategies to balance competing land-use priorities. By quantifying conflicts and identifying key drivers, this study helps prioritize interventions that mitigate tensions between production, living, and ecological spaces, supporting policies that reconcile urban expansion with ecological preservation for sustainable development in urban fringe areas. Full article

Although it promotes national economic development, urbanization causes regional ecosystems to suffer from disturbances and impacts that cannot be completely avoided. Ecosystems urgently need to improve their resilience; however, existing studies lack an analysis of the interaction between urbanization and ecological resilience. In this study, the interaction between urbanization and ecological resilience is investigated, taking the urban agglomeration on the north slope of Tianshan Mountain (UANST) as a study area and using the entropy value method to construct an urbanization evaluation system. Based on land use change data, an ecological resilience evaluation model is constructed using the InVSET model, the landscape pattern index, and the unit area value equivalent factor method. The degree of coupling and coordination of the interaction coupling between urbanization and ecological resilience are measured for the years 1990–2020, and their internal action mechanisms are analyzed. The results show that (1) with the development of urbanization, ecological resilience shows a decreasing and then increasing double “U”-shaped change characteristic. (2) The coupling degree of urbanization and ecological resilience in the UANST increased from 0.6888 to 0.9485, and the coordination degree increased from 0.3367 to 0.4410. (3) There are three types of coupling coordination: basic coordination, basic dysfunction, and serious dysfunction. Basic coordination is mainly distributed in the central part of the urban agglomeration, and basic dysfunction and serious dysfunction are mainly concentrated on the east and west sides; the overall trend is to shift from dysfunction to coordination. (4) Economic urbanization plays a driving role, and population urbanization, spatial urbanization, and social urbanization have an inhibitory role in the degree of coupling coordination; base quality and structural stability have a driving role in the degree of coupling coordination, while ecological services have an inhibitory role; and the population density, the proportion of built-up area to the total land area of the city, and the value of ecosystem services have a stronger influence on the level of coupling coordination. Full article

The source region of the Yellow River (SRYR) serves as a crucial ecological barrier on the Qinghai–Tibet Plateau in China. In recent decades, the ecological condition of the SRYR has deteriorated, resulting in a state of ecological insecurity. This state of affairs endangers the region’s living environment, aggravates poverty, and seriously hinders the region’s sustainable ecological, social, and economic development. Ecosystems, landscape patterns, ecological carrying capacity (ECC), and drivers interact with each other in the region, shaping the regional ecological pattern’s past, present, and future. However, the specific mechanisms underlying these interactions have yet to be elucidated. Based on the land use type data of the SRYR in China for the last 30 years in seven periods (1990, 1995, 2000, 2005, 2010, 2015, and 2020), and combined with the ecological footprint method, we carried out a study of spatial and temporal changes at the county scale and the source region scale, used the landscape pattern index to describe the changes in ECC, and analyzed the main drivers that affect the ECC of the source region. The results indicate the following: (1) Over the past 30 years, the greatest changes in the area have occurred in grasslands and unused lands. Between 2005 and 2010, a significant conversion of unused lands to grasslands occurred in the SRYR, amounting to 7382.33 km², mainly distributed in Maduo County and Maqin County. (2) The absolute ecological carrying capacity (AECC) of grasslands in the SRYR has shown an upward trend, while that of forests has declined. The ECC of the source region has generally increased, with higher ECC observed in Maqin County, Maduo County, and Xinghai County. (3) The spatial distribution of ECC in the SRYR has shown non-uniform changes, with an increasing trend observed across all county-level areas. The spatial heterogeneity of AECC is high, with minor overall spatial distribution changes. (4) There is a positive correlation between the ECC of the SRYR with SPLIT, PARA_MN, and COHESION (p < 0.05). The impact of landscape pattern indices on ECC ranked as COHESION > PARA_MN > SPLIT. (5) Principal component analysis indicates that the primary driving forces of the SRYR’s ECC are social factors, such as urban population (X₅) and per capita GDP (X₈), with natural factors being less significant than social factors. This research is crucial for maintaining ECC in the SRYR, protecting and restoring the ecological environment, and ensuring the sustainable development of the economy and society. Full article

The terrain in the loess hilly area of western Henan is fragmented, with steep slopes and weak soil erosion resistance. The substantial soil erosion in this region results in plenty of problems, including decreased soil productivity and ecological degradation. These problems significantly hinder the social and economic development in the region. Soil conservation planning and ecological development require accurate soil erosion surveys. However, the studies of spatio-temporal patterns, evolution, and the driving force of soil erosion in this region are insufficient. Therefore, based on a multi-stage, unequal probability, systematic area sampling method and field investigation, the soil erosion of the loess hilly area of western Henan was quantitatively evaluated by the Chinese Soil Loss Equation (CSLE) in 2022. The impact forces of soil erosion were analyzed by means of a geographic detector and multiple linear regression analysis, and the key driving factors of the spatio-temporal evolution of soil erosion in this region were revealed. The results were as follows. (1) The average soil erosion rate of the loess hilly area in western Henan in 2022 was 5.94 t⋅ha⁻¹⋅a⁻¹, with a percentage of soil erosion area of 29.10%. (2) High soil erosion rates mainly appeared in the west of Shangjie, Xingyang, and Jiyuan, which are related to the development of production and construction projects in these areas. The areas with a high percentage of soil erosion area were in the north (Xinan and Yima), west (Lushi), and southeast (Songxian and Ruyang) of the study area. Moreover, areas with the most erosion were found in forest land, cultivated land, and areas with a slope above 25°. (3) At the landscape level, the number and density of patches of all land types, except orchard land, increased significantly, and the boundary perimeter, landscape pattern segmentation, and degree of fragmentation increased. (4) The geographical detector and multiple linear regression analysis indicated that the driving forces of soil erosion are mainly topographic and climatic (slope length, elevation, precipitation, and temperature). Soil erosion was significantly influenced by the density of landscape patches. These maps and factors influencing soil erosion can serve as valuable sources of information for regional soil conservation plans and ecological environment improvements. Full article

In the current context of urbanization, urban agglomerations face complex challenges in maintaining an ecological balance. This study uses remote sensing images of the Central Yunnan urban agglomeration from 2000 to 2020, along with socioeconomic data, to analyze the spatiotemporal characteristics of the green space evolution. Utilizing dynamic geographically weighted regression analysis based on principal components (PCA-GWR), we identify the key socioeconomic factors influencing these changes and quantitatively analyze the driving forces in each stage. Our findings reveal a continuing trend of decreasing total green space alongside increasing individual forest types and pronounced regional disparities in green space dynamics. The results indicate that socioeconomic factors exert both positive facilitative effects and negative pressures, with evident spatial and temporal variability. Urbanization and economic development promote forest expansion in certain areas, while contributing to the reduction in farmland and shrub–grass lands. Significant variations are influenced by factors such as the urbanization rate, the agricultural population, the industrial composition, and fiscal revenue. This study enhances the in-depth understanding of the relationship between the spatiotemporal dynamics of green spaces and socially driven mechanisms, offering significant insights for sustainable urban planning and landscape management and harmonizing urban agglomeration development. Full article

The interaction of human activity in national parks and their surrounding areas with natural landscapes is an important factor in the formulation of strategies for the protection and management of protected areas. From an integrated ecological and social perspective, this study aims to develop a human–land coupling model to reveal the ecological threats of human activities to national park and their surrounding areas under rapid urbanization. We first established a four-quadrant model based on the coupling relationship between human activity intensity (HAI) and the landscape pattern index (LPI). On this basis, we analyzed the spatial coupling characteristics of these indices from 2000 to 2020, preliminarily assessed the human–land relationship in Lushan National Park and its surrounding areas (LNPSA), and then explored the driving factors of the coupling relationship. The results show the following. (1) The proportion of regions with high and extremely high human activity intensity increased from 6.02% to 16.41% over the past two decades. These regions are mainly distributed in the surroundings of Lushan National Park, showing a gradually spreading trend to the core protected area. (2) The surroundings had higher landscape fragmentation, landscape diversity, and total variation in the landscape pattern compared with the core protected area. (3) Vegetation coverage and distance to Lushan have the most significant effect on the human–land coupling relationship in LNPSA, and human activity and natural evolution together shape the characteristics of this relationship in the study area. (4) Utilizing administrative divisions as the fundamental framework, the study area is delineated into four distinct zones based on the results of the human–land coupling analysis—harmonious development zones, stable transformation zones, environmental regulation zones, and risk prevention zones—with tailored optimization strategies proposed for each zone’s characteristics. These findings can facilitate the optimized formulation of schemes for different regions and provide a comprehensive methodology to guide the planning and management of natural protected areas. Full article

Rural areas provide ecosystem services (ESs) to urban metropolitan regions. These services are threatened by the constant pressure of urbanisation and new interest in rural development. This has heightened the conflict between environmental concerns and developmental needs, thereby presenting significant land management and rural planning challenges. Employing a quantitative measurement and optimisation framework, we investigate six representative ES variables to assess planning strategies that can address this contradiction. We used a suburban rural area around Nanjing, China, as our study area. We collected spatial data from 2005 to 2020 at two scales (village level and 500 m grid) to map ESs, quantify interactions (trade-offs and synergies among ES bundles), and identify the social, ecological, and landscape drivers of rural change. Based on this, rural planning strategies for optimising ESs at different scales have been proposed. Our findings include (1) spatial heterogeneity in the distribution of ESs, (2) the identification of seven synergistic and eight trade-off pairs among ESs, (3) a spatial scale effect in suburban rural areas, and (4) the spatial trade-offs/synergies of ESs exhibiting a ‘Matthew effect’. The identification of key trade-offs and synergistic ES pairs and the categorisation of ES bundles form the basis for a multi-scale hierarchical management approach for ESs in the region. By examining the commonalities and variations in drivers across diverse scales, we established connections and focal points for spatial planning. We use these findings to propose spatial planning and landscape policy recommendations for rural suburban areas on multiple scales. This study aims to provide a comprehensive and detailed spatial optimisation strategy for rural areas that can help contribute to their revitalisation. Full article

Studying the spatiotemporal evolution and driving forces behind construction land amidst the intricate ecological and geological setting on the eastern edge of the Qinghai–Tibet Plateau offers invaluable insights for local sustainable development in a landscape transition zone and ecologically fragile area. Using construction land data from four phases, spanning 1990 to 2020, in Mianning County, this study employs methodologies like the Landscape Expansion Index (LEI) and land use transfer matrix to delineate the spatiotemporal evolution characteristics of construction land. A comprehensive set of 12 influencing factors across five categories—geomorphology, geological activity, climate, river and vegetation environment, and social economy—were examined. The Geographically Weighted Regression (GWR) model was then employed to decipher the spatial distribution pattern of construction land in 1990 and 2020, shedding light on the driving mechanisms behind its changes over the three decades. The research reveals distinct patterns of construction land distribution and evolution in Mianning County, shaped by the ecological and geological landscape. Notably, the Anning River wide valley exhibits a concentrated and contiguous development mode, while the Yalong River deep valley showcases a decentralized development pattern, and the Dadu River basin manifests an aggregation development mode centered around high mountain lakes. Over the study period, all three river basins witnessed varying degrees of construction land expansion, transitioning from quantitative expansion to qualitative enhancement. Edge expansion predominantly characterizes the expansion mode, complemented by leapfrog and infilling modes, accompanied by conversions from cropland and forest land to construction land. An analysis of the spatial pattern and drivers of construction land change highlights human-induced factors dominating the Anning River Basin, contrasting with natural factors prevailing in the Yalong River Basin and the Dadu River Basin. Future efforts should prioritize climate change considerations and environmental capacity, aiming for an ecologically resilient spatial pattern of construction land. Full article

The mainstream basin of the Tarim River serves as a vital ecological security barrier that prevents the merging and expansion of deserts and an important strategic corridor directly linking Qinghai and Xinjiang. With society’s development and climate change, ecological issues such as river interruption, vegetation degradation, and land desertification in the basin have notably intensified, and the ecological security is facing a critical test. Exploring the characteristics of landscape changes and their driving factors within the basin is crucial in improving the ecological environment system’s management. Based on land use data from 1980 to 2020, this study analyzed the characteristics of the spatiotemporal changes and pattern evolution of the landscape through a landscape transfer matrix and landscape pattern indices. It further revealed the impact factors of the landscape pattern through canonical correspondence analysis. The results showed that (1) in 1980–2020, the areas of desert, forest, farmland, and settlement landscapes increased, while the area of grassland landscape decreased, and the water landscape showed an “increasing–decreasing–recovery” pattern. The landscape transition types mainly included the transition from grassland to desert; mutual transitions among farmland, grassland, and forests; mutual transitions between water and grassland; and the transition from farmland to settlements. (2) The overall landscape pattern demonstrated increased fragmentation, shape complexity, and evenness with decreased aggregation. Furthermore, different landscapes exhibited distinct characteristics of landscape pattern changes; for instance, grassland landscape showed severe fragmentation, while desert landscape displayed the strongest dominance. (3) The landscape pattern was a result of the combined impact of natural and human factors, with the soil thickness (SOT), road density (ROD), annual actual evapotranspiration (AAE), population density (POD), and mean annual temperature (MAT) exhibiting significant influences. Specifically, the settlement and farmland landscapes were mainly influenced by the mean annual relative humidity (MAH), POD, GDP density (GDP), and distance to artificial water (DAW); the forest, grassland, and water landscapes were mainly influenced by the SOT, soil organic matter content (SOM), AAE, ROD, elevation (ELE), MAT, slope (SLP), and distance to natural water (DNW); and the desert landscape was mainly influenced by the DAW, DNW, SLP, AAE, SOT, SOM, and ROD. These findings can provide a scientific reference for landscape management and restoration, as well as sustainable social and economic development, in the mainstream basin of the Tarim River. Full article

Understanding the dynamics of ecosystem services (ESs) in arid landscapes and socio-ecological systems is crucial for sustainable development and human well-being. This study uses the Invest model to quantify the spatio-temporal changes in four key ecosystems services in Altay from 1990 to 2020: water yield (water yield), carbon stock (carbon stock), soil retention (soil retention), and habitat quality (habitat quality). The trade-offs/synergies between different ESs were investigated via Spearman’s correlation analysis. Ecosystem service bundles (ESBs) were mapped using self-organizing mapping (SOM), and the key drivers of ES relationships and the spatio-temporal dynamics of ESBs were revealed through redundancy analysis. The results showed that water yield increased by 33.7% and soil retention increased by 1.2%, while carbon stock and habitat quality decreased by 3.5% and 1.24%, respectively. The spatial distribution pattern had a clear zonal pattern, with the northern mountainous areas higher than the southern desert areas. The six pairs of ESs, in general, showed mainly low trade-off and high synergistic relationships, with trade-offs between water yield and carbon stock, soil retention and habitat quality, and a decreasing trend of trade-offs over time. Four types of ESBs were distinguished, and the compositional differences and spatial distribution within each ESB were determined by interactions between ESs and landscape types. There are complex non-linear relationships between the drivers and the four ESBs in different years. Before 2010, ecological factors were the key drivers influencing the spatio-temporal changes in ESBs, whereas social and environmental factors combined to drive changes in ESB allocations after 2010. Additionally, this study found that the implementation of conservation measures, such as reforestation and sustainable land management practices, positively influenced the provision of ecosystem services in the Altay region. These findings underscore the importance of integrating conservation efforts into land use planning and decision-making processes to ensure the sustainable delivery of ecosystem services in arid landscapes. Full article

With the continuous implementation of the rural revitalisation strategy, the social and economic landscape of China’s countryside has undergone significant changes and the structure and functions of rural production space have gradually become more complex and diversified. The theory of rural production space and its multifunctionality provides a new perspective for the study of rural human–land relationship patterns. Taking Western Chongqing, one of the national pilot zones for integrated urban–rural development, as an example, a scientific evaluation index system is established from the perspective of rural production space and its multifunctionality. The evaluation takes into account the consensus indicators of existing academic results, the regional characteristics of Western Chongqing, and relevant policies. On this basis, a regression model is constructed to investigate the factors influencing multifunctional regional differentiation, and a weighted clustering algorithm is used to classify the units in the study area into functional zones. The results of the study are as follows: (1) A multifunctional evaluation system with 24 indicators in five dimensions was constructed through the principle of scientific selection of indicators. (2) All functions in the rural production space of Western Chongqing have the respective geographical differentiation characteristics. In particular, the high-value and low-value agglomerations are generally distributed in strips or clusters, and the high-value and low-value agglomerations are intermingled, with each influencing factor driving the differentiation process of each function in the form of inhibition and reinforcement. (3) Western Chongqing can be divided into four types of functional areas: balanced development, lagging development–ecological recreation, urban development, and modern agriculture. Differentiated development strategies are proposed for different types of functional areas. We conclude that the study of the multifunctional spatial differentiation of rural production and functional zoning can provide a clearer analysis of the current status of rural development in Western Chongqing, and also enriches the perspective and methodology of the study of rural areas in western China. Full article

The Yellow River Basin holds significance as a vital ecological shield and economic hub within China. Adapting land utilization practices and optimizing landscape patterns are of paramount significance in preserving the ecological equilibrium of the Yellow River Basin while fostering high-quality economic development. In this study, we selected the Yellow River Basin in Henan Province as our research area. We use a land use transition matrix and FRAGSTATS 4.2 software to analyze changes in land use and landscape patterns within the study area from 1990 to 2020. Furthermore, Geographical Detector is employed to explore the impact of different natural and social economic factors that have influenced the progress of the landscape surface pattern in the study area. Finally, to identify the zonal aggregation effects of primary components in connection with landscaping feature indices at the city dimension, we use bivariate local spatial autocorrelation. The results are as follows: (1) In terms of land use change characteristics, the area of cultivated land, grassland, shrubs, and bare land shows a decreasing tendency, the area of construction land and forest land shows an increasing tendency, and the water area fluctuates and changes. Most of the cultivated land is shifted to construction land, followed by forest land, construction land, and cultivated land mainly transferred from grassland. (2) At the level of type in terms of shifting landscape patterns, cultivated land, forest land, water, and construction land have a more complex landscape shape, reduced fragmentation, and better natural connectivity. At the overall level, the overall landscape pattern indices are relatively stable, with more patch types and a more balanced distribution. (3) The findings regarding influencing factors reveal that the primary industry output value, population, secondary industry output value, and temperature are the principal driving forces behind the progress of the landscape surface pattern. The main drivers have changed over time in different regions. As indicated by the findings from bivariate local spatial autocorrelation analysis, at the city scale, the leading cause of landscape fragmentation in Luoyang is the primary industry output value, while in Xinxiang, landscape fragmentation is primarily driven by the secondary industry output value and temperature. In this study, we introduce the bivariate local spatial autocorrelation method to analyze the clustering effects of key influencing factors and landscape patterns at the city scale. This is crucial for the harmonized growth of land use planning and the urban economy in the Yellow River Basin. Full article

Watershed ecosystems are crucial to the overall sustainable development of a region, and a scientific and effective grasp of the characteristics of land-use change in a watershed, and the factors affecting land change, is an important prerequisite for the high-quality construction of watershed ecology, which needs to be emphasized. As the second largest inland river in the arid zone of Western China, the Heihe River Basin (HRB) has been affected by human and natural factors in recent years, and the ecological environment is relatively fragile, and there is an urgent need to analyze the ecological characteristics of the basin and to explore the relevant influencing factors in order to provide a basis for subsequent ecological management. Therefore, this article applies the landscape index, the landscape ecological risk index (ERI) model and the geodetector tools to analyze the land-use data from 2000 to 2020 in the Zhangye area of the HRB to study the characteristics of the ecological risk evolution and the driving forces affecting the ecological risk differentiation. The results show the following: (1) the area of the regional land-use change accounts for 4.99% of the total area, and the landscape pattern as a whole shows an increasing degree of fragmentation and a decreasing trend of aggregation; (2) the distribution of the ERI in the region shows a trend of being low in the center and high in the periphery, with an increase of 2.11% in the area of the lowest and lower risk and a decrease of 1.77% in the highest and higher, and the temporal change shows an increase followed by a significant decrease; (3) the human interference degree is the dominant factor influencing the spatial differentiation of the ERI in the basin area. There are significant differences between social factors, climate factors and land factors. Full article

Landscape ecological risk is considered the basis for regional ecosystem management decisions. Thus, it is essential to understand the spatial and temporal evolutionary patterns and drivers of landscape ecological risk. However, existing studies lack exploration of the long-term time series and driving mechanisms of landscape ecological risk. Based on multi-type remote sensing data, this study assesses landscape pattern changes and ecological risk in the Three Gorges Reservoir Area from 1990 to 2020 and ranks the driving factors using a geographical detector. We then introduce the geographically weighted regression model to explore the local spatial contributions of driving factors. Our results show: (1) From 1990 to 2020, the agricultural land decreased, while forest and construction land expanded in the Three Gorges Reservoir Area. The overall landscape pattern shifted toward aggregation. (2) The landscape ecological risk exhibited a decreasing trend. The areas with relatively high landscape ecological risk were primarily concentrated in the main urban area in the western region of the Three Gorges Reservoir Area and along the Yangtze River, with apparent spatial aggregation. (3) Social and natural factors affected landscape ecological risk. The main driving factors were human interference, annual average temperature, population density, and annual precipitation; interactions occurred between the drivers. (4) The influence of driving factors on landscape ecological risk showed spatial heterogeneity. Spatially, the influence of social factors (human interference and population density) on landscape ecological risk was primarily positively correlated. Meanwhile, the natural factors’ (annual average temperature and annual precipitation) influence on landscape ecological risk varied widely in spatial distribution, and the driving mechanisms were more complex. This study provides a scientific basis and reference for landscape ecological risk management, land use policy formulation, and optimization of ecological security patterns. Full article