The changes in the landscape structure within resource-dependent urban areas is influenced by a confluence of factors, potentially resulting in a decreased landscape ecological quality and a heightened ecological vulnerability. Landscape ecological quality directly influences the flow and transmission of ecological functions, rendering it a pivotal consideration in the development of landscape ecological networks. In this study, an investigation was conducted utilizing land-use data spanning from 2005 to 2020, encompassing the city of Linfen in Shanxi Province, China. A landscape ecological risk assessment model was formulated to analyze the spatiotemporal attributes of landscape ecological risk during this timeframe. Acknowledging the underlying connection between ecosystem resilience and landscape ecological quality, the 2020 landscape ecological risk assessment served as the basis for the extraction of ecological source areas using the Minimum Spanning Tree with Path Algorithm (MSPA), and the corridors were established using the Minimum Cumulative Resistance (MCR) model. This framework facilitated the construction of a landscape ecological network, and the complex network analysis was employed to scrutinize the network’s topological properties. The regions within the study area exhibiting high and extremely high ecological risk displayed an initial increase followed by a subsequent decrease, culminating in an overall reduction in risk levels. The areas surrounding urban development and mining activities displayed relatively heightened risk levels, while the regions characterized by forests and grasslands experienced relatively lower risks. The shifts in risk within the study area were predominantly attributed to various factors, including mining activities, urban expansion, governmental policies, alterations in land-use types, and village migrations. Through the optimization of the landscape ecological network using edge addition strategies and a subsequent comparison of network robustness pre- and post-optimization, it was discerned that the edge addition strategy notably improved the efficiency of energy transfer and interconnectivity among network nodes. This ecological risk assessment model, in conjunction with the development of a prospective ecological network, lends a valuable theoretical support to the enhancement of landscape structure within resource-dependent urban areas and the establishment of comprehensive ecological security systems.

Vegetation, as a crucial carbon sink, is facing extensive degradation under the mounting pressures of urbanization and excessive resource exploitation, exacerbating the imbalance between carbon sources and sinks. In response, the ecological spatial network has emerged as a comprehensive conservation strategy to establish and maintain connectivity and interactions among diverse ecosystems, ensuring the continuous provision of ecological services and preservation of biodiversity. A pivotal indicator in this context is vegetation carbon use efficiency (CUE), which elucidates the relationship between CO2 assimilation through photosynthesis and biomass growth. In this study, utilizing remote sensing data, the Yellow River Basin (YRB) was selected as a case study to analyze vegetation CUE through the Carnegie Ames Stanford Approach (CASA) and Light Use Efficiency-Normalized Difference Water Index (LUE-NDWI) models. Furthermore, the Morphological Spatial Pattern Analysis (MSPA) method and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model were employed to delineate ecological sources for woodlands, shrublands, and grasslands, while the Minimum Cumulative Resistance (MCR) model was used to identify ecological corridors, forming an ecological spatial network within the YRB. Subsequently, the interrelationship between topological metrics and vegetation CUE was analyzed, and optimization strategies were proposed based on the significance of the structure and function. The findings revealed that: (1) Vegetation CUE exhibited a spatially decreasing trend from the western to eastern regions, with spatial patterns correlated with vegetation types, temperature, and precipitation distribution; (2) The ecological spatial network demonstrated a denser configuration in the upper and middle reaches and a sparser and shorter pattern in the lower reaches, with seamless connectivity among all regions; (3) Significant correlations were observed between topological metrics and vegetation CUE, prompting the adoption of ecological construction and protection measures when functional importance is deficient, and enhancing the connectivity of ecological sources through the augmentation of ecological corridors when structural importance is lacking. The implementation of these strategies is expected to bolster the ecological functions of the network, facilitate carbon cycling, and exert a positive and far-reaching impact on the sustainable development of the ecological environment in the YRB.

Watershed ecosystems play a crucial role in the global carbon cycle, and the feedback effects of carbon cycling will have significant implications for future climate change. Therefore, this study utilizes MODIS data to estimate the vegetation carbon use efficiency (CUE) of the Yangtze River Basin (hereafter referred to as the YRB) aiming to explore its spatiotemporal patterns. Additionally, partial correlation analysis is employed to investigate the driving forces of climate and ecosystem types on vegetation CUE. Furthermore, an ecological network is constructed to examine the impact of CUE changes on the stability of the ecosystems.The results indicate that the CUE values in the vegetation ecosystems of the YRB exceed the threshold of 0.5, a constant CUE value commonly used in numerous ecological models. However, even within the same geographical region, different ecosystem types exhibit distinct CUE values, underscoring the complexity of the ecological landscape.Over the past 15 years, there has been an observable declining trend in CUE for the vegetation ecosystems within the YRB. Moreover, future projections suggest a continued decrease in CUE at the pixel scale, with land use changes possibly serving as a primary contributing factor. Interestingly, within the same ecosystem, higher temperatures and reduced precipitation appear to enhance CUE, implying that under adverse environmental conditions, plants may enhance their efficiency in converting atmospheric carbon into terrestrial biomass.Ultimately, an ecological network is established to investigate the influence of CUE changes on the stability of the ecosystems. Notably, alterations in CUE within the upstream ecological source areas of the Yangtze River exhibit a particularly pronounced impact on the overall ecosystem stability.These research findings hold paramount significance, deepening our understanding of carbon cycling variations in the YRB, while also providing valuable insights for safeguarding the ecological environment and formulating strategies to address the challenges posed by climate change.

Forests are vital for terrestrial ecosystems, providing crucial functions like carbon sequestration and water conservation. In the Yellow River Basin, where 70% of forest coverage is concentrated in the middle reaches encompassing Sichuan, Shaanxi, and Shanxi provinces, there exists significant potential for coal production, with nine planned coal bases. This study centered on Jincheng City, Shanxi Province, a representative coal mining area in the Yellow River Basin, and combined the MSPA analysis method and MCR model to generate the five-period forest ecological network of Jincheng City from 1985 to 2022 under the background of coal mining and calculate the degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality; the correlation between the four centralities and carbon sequestration ability is further explored. Simultaneously, employing the RAND-ESU algorithm for motif identification within forest ecological networks, this study integrates the ecological policies of the research area with the specific conditions of the coal mining region to optimize the forest ecological network in Jincheng City. Findings reveal the following. (1) Forest ecological spatial networks: Forest ecological networks exhibit robust overall ecological connectivity in the study area, with potential ecological corridors spanning the region. However, certain areas with high ecological resistance hinder connectivity between key forest ecological nodes under the background of coal mining. (2) Correlation between topological indices and carbon sequestration ecological services: From 1985 to 2022, the carbon sequestration capacity of Jincheng City’s forest source areas increased year by year, and significant positive correlations were observed between degree centrality, betweenness centrality, eigenvector centrality with carbon sequestration ecological services, indicating a strengthening trend over time. (3) Motif Recognition and Ecological Network Optimization: During the study, four types of motifs were identified in the forest ecological network of Jincheng City based on the number of nodes and their connections using the RAND-ESU network motif algorithm. These motifs are 3a, 4a, 4b, and 4d (where the number represents the number of nodes and the letter represents the connection type). Among these, motifs 3a and 4b play a crucial role. Based on these motifs and practical considerations, network optimization was performed on the existing ecological source areas to enhance the robustness of the forest ecological network.

BackgroundIn resource-based cities, long-term irrational exploitation of resources has caused severe damage to ecosystem functions, mainly manifested in the significant decline of biodiversity, land degradation, water pollution, and the deterioration of air quality. This has led to a significant decline in the cities' sustainable development capabilities. Establishing and optimizing an ecological spatial network (ESN) can promote the effective transmission of material energy and enhance the ecosystem functions, which holds fundamental importance in ensuring the ecological integrity of the region and promoting sustainable urban development. In this study, by combining the ecological environment with the landscape to determine the ecological sources, we constructed the ESN of Shenmu City, a mining city, based on the minimum cumulative resistance (MCR) model, and conducted a correlation analysis between the topological structure of the ESN and the significance of ecosystem functions. Then, the optimization strategy scheme based on ecosystem functions was proposed. Finally, robustness was used to determine the effect before and after optimization.ResultsThe results showed that the high-value ecosystem service areas in Shenmu City were predominantly located in the central and western parts, with the highest value in the southeast. There was a strong correlation between the importance of ecosystem functions and the degree and feature vector of ecological nodes.ConclusionsThe ESN can be optimized effectively by adding stepping stone nodes and new corridors. Through the robustness of the optimized ESN, we found that the optimized network has more robust connectivity and stability and can show better recovery ability after ecological function damage. This research presents an effective method for the construction and optimization of the ESN in the mining area and provides a theoretical basis for realizing the sustainability of the mining economy, regional development, and ecological protection in Shenmu City.

Urban heat stress is a critical issue impacting the sustainable development of urban agglomerations. Ecological land is an important factor in alleviating the heat environment stress of urban agglomerations. However, few scholars have taken a macro, interconnected perspective to consider the cooling effects of different ecological land. This study reveals that urban agglomerations have a potential hierarchical natural cooling system. Based on the heat environment assessment of the Beijing-Tianjin-Hebei (BTH) urban agglomeration and the Minimal cumulative resistance (MCR) model, we extracted the graded cooling patches and cooling corridors from 2005 to 2020. The research findings indicate that the heat environment intensity of the BTH urban agglomeration presents a spatial pattern of high intensity in the southeast and low intensity in the northwest, and the heat environment intensity of the urban agglomeration remains at a relatively high level. The number of graded patches and corridors shows a trend of first decreasing and then increasing, and the central and southern regions have relatively few corridors and patches, which require targeted optimization and improvement. Additionally, the overall length of corridors in the BTH urban agglomeration has increased, while the cooling effect of patches has decreased. The robustness and connectivity of the cooling system have both increased over 15 years, but further optimization and improvement are still needed to alleviate the heat environment intensity of urban agglomerations. This study quantifies the trends in urban agglomeration heat environment stress and the functional and topological properties of patches, corridors, and systems, providing valuable information for natural-based urban planning and management, as well as new solutions and research perspectives for alleviating heat environment stress in urban agglomerations.

Many regions on the globe are at risk of soil erosion, especially in the ecologically fragile areas of the Qinghai-Tibet Plateau. Enhancing the soil conservation capacity of regional vegetation is one of the main ways to address soil erosion. However, most studies ignore the relationship between the spatial distribution structure of vegetation and soil conservation capacity, and the construction of ecological spatial networks is an effective means to study the spatial distribution structure of vegetation. In this study, we extracted the ecological spatial network of Southeast Tibet by the minimum resistance model (MCR) and combined the ecological network with complex network theory to calculate the topological indices of the ecological spatial network and ecological nodes. Subsequently, the soil conservation capacity of ecological nodes is calculated based on the USLE model, and the relationship between it and topological indices is analyzed. It was shown that the degree, closeness centrality, betweenness centrality and eigenvector centrality of forest nodes showed a positive linear correlation with their soil conservation capacity, and the clustering coefficient of grassland nodes showed a positive linear correlation with their soil conservation capacity. This study calculates habitat quality based on the Invest model. We propose a Integrated Soil Conservation and Habitat Quality Evaluation (ISHE) Model to determine the direction of network optimization and propose an optimization strategy. We analyze the network robustness and soil conservation capacity and find that the optimized network robustness and soil conservation capacity are significantly improved. This study provides strategies and methods to protect ecologically vulnerable areas, optimize the spatial distribution of vegetation, and enhance soil conservation capacity. In addition, this can provide a theoretical reference for planning national ecological projects. We use the ISHE model to filter out three types of nodes that need to be focused on optimization and propose different optimization strategies.

In the Yellow River Basin (YRB), there exists a rich biodiversity of species that has been shaped by its unique geography, climate, and human activities. However, the high speed of economic development has resulted in the fragmentation and loss of habitats that are crucial for the survival of these species. To address this problem, constructing ecological networks has emerged as a promising approach for biodiversity preservation. In the study, we centered on the YRB and employed bird communities as an indicator species to identify ecological sources by combining bioclimatic variables and land use data with the Maximum Entropy (MaxEnt) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models. We generated a resistance surface using various data such as Digital Elevation Model (DEM), the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), nighttime light, road density, railway density, and waterway density. So, we then simulated ecological corridors applying the Minimum Cumulative Resistance (MCR) model and constructed a bird diversity protection network. The results we found suggested that bird hotspots were predominantly clustered upstream and downstream in the YRB. We identified 475 sources covering a total area of 65,088 km2, 681 corridors with a total length of 11,495.05 km. This network served as a critical ecological facility to sustain and protect biodiversity. The bird ecological corridors in the YRB showed that a dense east-west pattern in the central area, with a short length in the west and east and a long length in the central area. Although the central region lacked ecological sources, the east and west were still connected as a tight whole. Two scenarios showed adding ecological stepping stones had a better optimization effect than enhancing ecological connectivity.

The conservation of forest ecosystems and the enhancement of carbon sequestration capacity play a crucial role in maintaining ecological balance and human development. However, with excessive deforestation, the flow of energy and information within the ecosystemhas changed, which in turn has led to changes in the topological properties and carbon sequestration capacity of forest ecosystems. In order to better investigate the nature and carbon sequestration capacity of forest ecological space in mainland China during 2000-2018, we constructed a time-series Chinese forest ecological spatial network based on complex network theory and graph theory, combined with the modified minimal cumulative resistance model (MCR). By combining the net primary productivity (NPP) values obtained from the Boreal Ecosystem Productivity Simulator (BEPS) model of existing scholars, we further explored the relationship between topology and carbon sequestration capacity within forest ecosystems, and proposed strategies and suggestions for optimization. The results show that forest ecological sources and ecological corridors showed an increasing trend and resistance values decreased year by year during 2000-2018, especially in the western region, indicating that ecological restoration projects inwestern China have achieved certain effects. However, the stability of forest ecosystems has been decreasing year by year, and the forest carbon sequestration capacity in western China is also decreasing. Through correlation analysis, we found that carbon sequestration capacity showed highly significant positive correlation with closeness centrality, harmonic closeness centrality, clustering, and eigen centrality, and carbon sequestration capacity showed highly significant negative correlation with betweeness centrality. Through Principal Components Analysis (PCA), we suggest that consolidating small patches in the northeast, reducing the number of redundant ecological corridors, adding stepping stone patches to shorten the length of ecological corridors, and increasing ecological corridors in non-northeast areas are conducive to enhancing plant carbon sequestration capacity. This study provides theoretical support and ecological engineering recommendations for China to achieve its strategic goals of carbon neutrality and carbon peaking.

In recent years, the accelerated pace of urbanization has increased patch fragmentation, which has had a certain impact on the structure and ecological environment of forest–grass ecological networks, and certain protection measures have been taken in various regions. Therefore, studying the spatiotemporal changes and correlations of ecological service functions and forest–grass ecological networks can help to better grasp the changes in landscape ecological structure and function. This paper takes the Wuding River Basin as the research area and uses the windbreak and sand fixation service capacity index, soil conservation capacity, and net primary productivity (NPP) to evaluate the ecological service capacity of the research area from the three dimensions of windbreak and sand fixation, soil conservation, and carbon sequestration. The Regional Sustainability and Environment Index (RSEI) is used to extract ecological source areas, and GIS spatial analysis and the minimum cumulative resistance (MCR) model are used to extract potential ecological corridors. Referring to complex network theory, topology metrics such as degree distribution and clustering coefficient are calculated, and their correlation with ecological service capacity is explored. The results show that the overall ecological service capacity of sand fixation, soil fixation, and carbon sequestration in the research area in 2020 has increased compared to 2000, and the ecological flow at the northern and northwest boundaries of the river basin has been enhanced, but there are still shortcomings such as fragmented ecological nodes, a low degree of clustering, and poor connectivity. In terms of the correlation between topology indicators and ecological service functions, the windbreak and sand fixation service capacity index have the strongest correlation with clustering and the largest grasp, while the correlation between soil conservation capacity and eigencentrality is the strongest and has the largest grasp. The correlation between NPP and other indicators is not obvious, and its correlation with eccentricity and eigencentrality is relatively large.

The destruction of vegetation structure and quantity leads to the weakening of the carbon sequestration capacity of the ecosystem. Building an ecological spatial network is a potent method for studying vegetation spatial distribution structures. The relationship between the spatial distribution structure of vegetation networks and carbon sequestration, as approached from the perspective of complex network theory, is understudied. This study uses the minimum resistance model (MCR) and morphological spatial pattern analysis (MSPA) to study the eco-space network and ecological node spatial structure and topological characteristics of vegetation in the ecologically sensitive area of the middle reaches of the Yellow River (ESAMRYR). Based on the Carnegie-Ames-Stanford approach (CASA) model, the vegetation Net Primary Productivity (NPP) of the study area is calculated, and the ecological carbon sequestration function of the ecological node is estimated, and the relationship between the ecological node and the topological indicators is analyzed. The study shows that the forest land carbon storage in the regions situated toward the south and east of the Yellow River ecologically sensitive area is the highest, accounting for twice the proportion of the area, and is very important in terms of increasing carbon storage. Most of the ecological sources in the study area have a higher topological importance than functional importance, and the sources with low coordination are mainly distributed in the southwest and northeast. We construct a topology and function coupling optimization model (TFCO) to explore the coordination between vegetation structure and carbon sequestration function, to determine the network optimization direction, and to propose optimization solutions. Analysis of network robustness and carbon sequestration capacity shows that the sturdiness and carbon sequestration of the enhanced network are significantly improved. This study provides strategies and methods for protecting ecological sensitive areas, optimizing vegetation spatial distribution, and enhancing carbon sequestration capacity.

Land use/cover change (LUCC) is the primary source of carbon storage changes in the ecosystem. Up to now, there are few studies about the impacts and driving mechanisms of LUCC for carbon storage in the ecosystem at spatial–temporal scales. Characterizing LUCC of the Yellow River Basin (YRB) and its role in carbon storage are very important and necessary to elucidate the results of human activities on ecosystems. The policies to address potential future risks should be formulated in advance to achieve effective development. In the paper, we regarded the YRB as the study area, analyzed its LUCC during 2000 to 2020, predicted land use patterns in 2040 under the scenarios of natural trend (NT), ecological degradation (ED), and ecological restoration (ER) using Markov model with Patch-generating Land Use Simulation (PLUS) model, and quantified carbon storage in the ecosystems over the last 20 years and under future scenarios according to Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The outcome was as follows: (1) During 2000 to 2040, LUCC in the YRB changed markedly, with cropland being transformed into woodland, grassland and built-up land; (2) During 2000 to 2040, carbon storage in the YRB was on an upward trend with a mean annual increase of 1.93×106Mg C, and woodland was the answer to increasing carbon storage, while unused land could induce carbon storage to decrease; (3) Carbon storage in the YRB varied to different degrees under three scenarios, but under the premise of not causing large-scale damage, the conversion of built-up land was an important means of improving carbon storage, greatly enhancing the carbon sequestration efficiency and capacity of the YRB. In conclusion, the future environmental management of the YRB should be continuously oriented to ecological protection and low-carbon development, so that carbon storage in the basin will be able to develop in a benign direction.

The Yellow River Basin serves as a crucial ecological barrier in China, emphasizing the importance of accurately examining the spatial distribution of forest carbon stocks and enhancing carbon sequestration in order to attain “carbon peaking and carbon neutrality”. Forest patches have complex interactions that impact ecosystem services. To our knowledge, very few studies have explored the connection between these interactions and carbon stock. This study addressed this gap by utilizing complex network theory to establish a forest ecospatial network (ForEcoNet) in the Yellow River Basin in which forest patches are represented as nodes (sources) and their interactions as edges (corridors). Our objective was to optimize the ForEcoNet’s structure and enhance forest carbon stocks. First, we employed downscaling technology to allocate the forest carbon stocks of the 69 cities in the study area to grid cells, generating a spatial distribution map of forest carbon density in the Yellow River Basin. Next, we conducted morphological spatial pattern analysis (MSPA) and used the minimum cumulative resistance model (MCR) to extract the ForEcoNet in the basin. Finally, we proposed optimization of the ForEcoNet based on the coupling coordination between the node carbon stock and topological structure. The results showed that: (1) the forest carbon stocks of the upper, middle, and lower reaches accounted for 42.35%, 54.28%, and 3.37% of the total, respectively, (2) the ForEcoNet exhibited characteristics of both a random network and a scale-free network and demonstrated poor network stability, and (3) through the introduction of 51 sources and 46 corridors, we optimized the network and significantly improved its robustness. These findings provide scientific recommendations for the optimization of forest allocation in the Yellow River Basin and achieving the goal of increasing the forest carbon stock.

The transformation of the landscape structure in mining cities is influenced by a combination of various factors, resulting in a decline in the ecological quality of the landscape and an increased vulnerability of the ecological environment. The quality of landscape ecology directly impacts the flow and transmission of ecosystem functions, underscoring the need for careful consideration in the establishment of landscape ecological networks. In this study, an analysis was conducted using land-use data from 2005 to 2020 in Linfen City, Shanxi Province, China. A network optimization strategy was established, focusing on the capacity for ecosystem self-restoration and the connectivity of ecological patches. Additionally, the spatiotemporal characteristics of landscape ecological risk between 2005 and 2020 were examined. Taking into account the influence of the ecological value of the landscape on the resilience of the ecosystem, the Minimum Cumulative Resistance (MCR) model was employed to construct the landscape ecological network. The structural characteristics of the landscape ecological network were explored using complex network methods. In addition, an optimization strategy based on ecosystem functionality and connectivity (EC) was adopted, and by comparing the connectivity and robustness of the network before and after the optimization, it was found that the method enhanced the smoothness of energy transfer and interconnectivity among nodes of the network, and significantly enhanced the stability of the ecological network. Within the study area, local levels of risk increased due to coal mining and urban expansion. (The maximum value in 2005 was 335.) However, overall risk levels improved with the progress of land reclamation efforts. (The maximum value in 2020 was 325.) Higher risks were observed in the vicinity of urban construction and mining areas, while forested and grassland areas exhibited relatively lower risks. The changes in risk within the study area were primarily influenced by factors such as mining activities, urban expansion, government policies, changes in land use types, and village relocation. The findings of this study provide theoretical support for the optimization of the landscape structure in mining cities, the construction of systems of ecological security as well as the restoration of ecosystems.

Optimizing the connectivity-carbon sequestration coupling coordination of forest and grassland ecological spaces (F & GES) is a crucial measure to enhance carbon sequestration effectively in mining areas. However, the prevailing strategies for optimizing F & GES often overlook the connectivity-carbon sequestration coupling coordination of the network. Therefore, this study aimed to propose a novel restoration plan to improve the connectivity-carbon sequestration coupling coordination of existing networks. Taking a typical mining area in northwestern China (Eyu County) as an example, we extracted the existing F & GES based on remote sensing ecological indicators and ecological risk assessments. Subsequently, we optimized the network using the connectivity-carbon sequestration coupling coordination degree (CSCCD) model from the perspective of connectivity carbon sequestration coupling coordination, proposed potential alternative optimization schemes, and evaluated the optimization effects. The results showed that the range of Eyu County's F & GES structure had been determined. Ecological source sites with better carbon sequestration effects were primarily distributed in the central and northeastern parts of Eyu County. After optimization, the network added 26 ecological patches, and the added area reached 641.57 km(2). Furthermore, the connectivity robustness, edge restoration robustness, and node restoration robustness of the optimized network were significantly improved, and the carbon sequestration effect of the forest and grassland ecological space was increased by 6.78%. The contribution rate of ecological source sites was 97.66%, and that of ecological corridors was 2.34%. The CSCCD model proposed in this study can effectively improve the carbon sequestration effect in mining areas, promote carbon neutrality, and save network optimization time while improving efficiency. This restoration strategy is also applicable to forest and grassland ecosystem management and optimization of ecological spaces in other mining areas, which has positive implications for promoting ecological civilization construction and sustainable development.