Lake sediments contain rich information on climatic and environmental changes, making them ideal archives for studying the climate and environmental changes since the last deglaciation. Lakes are widespread on the Tibetan Plateau. Scientists have conducted paleolimnological studies in hundreds of these lakes. Using various proxy indicators in sediment cores, numerous records have been acquired on past changes in climate, environment, ecosystems, and human activities at different timescales on the plateau. This has promoted a deeper understanding of the processes and mechanisms of climate and environmental changes on the plateau. However, some problems have emerged with rapid increase in paleolimnological records in past decades. For instance, contradictions between different records have caused interference in further integrated studies. This article suggests that this may be due to neglecting some fundamental scientific issues in limnology, such as unclear lake types (lake water stratification and mixing and lake classification), ambiguous implication of proxy indicators, and unknown histories of lake status changes (e.g., open and closed lakes). Using paleolimnological records from typical lakes on the Tibetan Plateau, this paper illustrates how these issues affect the interpretation of different proxy records. A deeper understanding of fundamental scientific issues in limnology not only helps in reasonably interpreting proxy records and accurately reconstructing past lake processes and climate and environmental changes but also contributes significantly to a better understanding of the processes and mechanisms of climate and environmental changes. This paper attempts to discuss the impact of the thermodynamic characteristics of lakes on the Tibetan Plateau, the implications of climate environment change proxies, and the lake status on the interpretation of lake sediment records. The thermodynamic characteristics of the lake determine the ecological niche of proxy producers and implications of the proxies; the change in lake status (taking the conversion between open and closed states as an example in this paper) directly affects the lake sediment system, thereby influencing the sediment records. If there is no in-depth understanding of the basic information of the lake, it may lead to unreasonable interpretations of the lake sediment records. Therefore, in paleolake studies, full attention should be given to the basic information of the lake. This is not only applicable to paleolake studies on the Qinghai-Tibet Plateau but also relevant to related studies in other regions.
Changes in cropland are affected or restricted by natural resource endowment, economy, society, technology and other factors, and are a comprehensive index reflecting the change of human-land relationship. With the rapid development of society and economy, the changes of cropland in China present significant regional differentiation characteristics. Studying the characteristics is very important for grasping the future development trend of cropland, formulating cropland protection policies according to local conditions, and improving the implementation effect of policies. Based on land use maps interpreted by remote sensing images and national land survey data, this paper analyzes the spatial changes of cropland in China in the past 30 years, and proposes the geographical dividing line of cropland increase and decrease in China: 40°N. In the north and south sides of this line, the changes of cropland showed an opposite trend. According to the national Land survey, from 2009 to 2019, cropland in the south decreased by 14.5% and increased by14.0% in the north. And the proportion of cropland in the north of the total cropland area in the whole country increased from 31.5% in 2009 to 38.1% in 2019, which significantly increased its importance in China’s agricultural production. The fastest reduction of cropland in the south is mainly distributed in the southeast coast and the southern section of the second stage, which is a “horseshoe” area. Finally, this paper systematically analyzes the causes of cropland change on both sides of the north and south, and puts forward the corresponding policy suggestions on cropland use. In arid and semi-arid areas of China with better irrigation conditions, drip irrigation technology should be widely adopted, and water-fertilizer integration should be implemented to tap the potential of existing cropland. In the “horseshoe” area, due to the occupation of construction land and the adjustment of agricultural structure, the speed of the reduction of cultivated land is fast, and the policy aim of balancing the total cropland in this area has been difficult to achieve, so the policy of protecting cropland should be adjusted correspondingly. In the south of the 40°N line, especially in the north China Plain and inside the “horseshoe” area, priority should be given to protecting high-quality, flat farmland suitable for large-scale operations for grain production, strictly controlling the expansion and occupation of construction land and non-grain agricultural land, and preventing the fragmentation of cropland.
This study constructs and assesses the digital economy development index and the carbon intensity of human well-being (CIWB) in China from 2011 to 2020, elucidates the driving mechanism and spatial spillover effect of digital economy on the CIWB in China. The findings indicate that: 1) From 2011 to 2020, there is a marked advancement in the level of digital economic development in China, delineating a spatial distribution characterized by “lower in the west and higher in the east”. Concurrently, the CIWB displayed a notable decline, exhibiting a “higher in the north and lower in the south” spatial pattern. 2) The cultivation of the digital economy significantly diminishes the CIWB in China. For every unit increase in the digital economy development index, the CIWB decreases by 1.138 units. The digital economy curtails the CIWB through the reduction of electricity consumption and industrial structural upgrades. An increase of one unit in the per capita electricity consumption and tertiary industry’s proportion leads to a decrease in the CIWB by 0.645 and 0.083 units, respectively, with the former demonstrating a more pronounced mitigating impact. 3) The digital economy’s efficacy in reducing the CIWB in China exhibits spatial spillover effects, evident in its significant contributory reduction in both the province and its neighboring regions. It is advised to concentrate efforts on narrowing the east-west gap in the level of development of digital economy and the north-south difference in the CIWB in China, to bring into play the spatial spillover effect of the digital economy, and to reduce electricity energy consumption and promote the upgrading of industrial structure, so as to reduce the CIWB in China.
As environmental health risks increase in China, environmental regulation has become an important option to protect public health. Based on the panel data of 30 provinces in China from 2003 to 2021, this article uses the entropy weight-Topsis method to comprehensively evaluate the level of public health from the perspective of health outcomes, environmental exposure risks, and health protection. The impact and mechanisms of environmental regulation on public health are systematically investigated using the double-fixed effects model, the mediation model, the threshold model, and the panel error correction model (PECM). The results show that: 1) Environmental regulation has an improving effect on public health, while the moderation of environmental regulation should be emphasized to effectively exert its public health-improving effect. An appropriate intensity of environmental regulation is necessary to achieve the optimal public health improvement effect. 2) The public health-improving effect of environmental regulation is more obvious in coastal provinces than in inland provinces, while the public health-improving effect of environmental regulation is not significantly improved in provinces with a high coal consumption ratio compared with provinces with a low coal consumption ratio. 3) Technological innovation, industrial structure upgrading, and energy efficiency play a mediating role in the impact of environmental regulation on public health. 4) As the degree of marketization increases, the public health-improving effect of environmental regulation gradually decreases, while the public health-improving effect of environmental regulation gradually increases under the influence of aging. 5) There is a long-term, stable relationship and one-way Granger causality between environmental regulation and public health. The PECM results confirm that environmental regulation has public health-improving effects in both the short and long term. This article provides reference for China's modernization process, which promotes harmonious cohabitation between humans and nature, as well as the “Healthy China” strategy.
Perceiving street vitality from multiple dimensions and exploring the relationship between the built environment and multidimensional street vitality are fundamental to enhancing street vitality. With the Futian District of Shenzhen as the study area, this study is based on Baidu heatmap data, Dianping data, and POI data to perceive street vitality in 3 dimensions: social vitality, economic vitality, and cultural vitality. Combining the XGBoost and SHAP analyses, the nonlinear relationship between multidimensional street vitality and the built environment is examined. The results show that: 1) There are significant spatial distribution differences in street vitality across different dimensions. The overall spatial distribution of social vitality and economic vitality exhibits a multi-centered spatial structure, while cultural vitality shows a multi-centered patchy structure. The spatial distribution differentiation between social vitality and economic vitality is minimal, while the differentiation between economic vitality and cultural vitality is large. 2) The built environment significantly impacts multidimensional street vitality. Among them, the importance of 4 built environment indicators, including functional density, distance to the nearest business circle, distance to the nearest subway station, and building density, is higher for multidimensional street vitality, and their cumulative explanatory power reaches 60%. 3) The built environment exhibits evident nonlinear effects and threshold effects on the multidimensional street vitality, with both commonalities and differences in its impact across different dimensions. Overall, multidimensional street vitality demonstrates a positive correlation with functional density, building density, floor area ratio, and bus stop density, while demonstrating a negative correlation with the distance to the nearest subway station. Additionally, there is an observed positive correlation between a high functional mix, a high green view ratio, and cultural vitality, while there is a negative correlation between social and economic vitality. These research findings can provide a basis for enhancing street vitality, optimizing urban resource allocation, and promoting sustainable urban development.
The role of digital technology entrepreneurship in the high-quality development of regional economies is becoming increasingly significant. The locational choice has emerged as a critical issue in current regional development, however, there is limited researches on the nationwide spatial-temporal distribution of digital technology entrepreneurship. This paper employed methods such as kernel density analysis and standard deviation ellipses to analyze the spatial-temporal patterns of digital technology entrepreneurship in China at the urban scale. Simultaneously, a spatial Durbin model was established using panel data to explore the influencing factors of digital technology entrepreneurship. The results show that: 1) Since 2008, China’s digital technology entrepreneurship has been developing continuously, and its spatial distribution shows the characteristics of “east is strong, west is weak, and center is rising”, and “small agglomeration and large dispersion”. Different types of digital technology entrepreneurships are continuously dividing upward spread from the east to the central and western regions. 2) The regional gravity of digital technology entrepreneurship in China is moving from northeast to southwest. 3) Factors such as the scale of digital users, venture capital, government scientific and technical support, digital infrastructure level, knowledge thickness, and market size have positive impacts on the development of digital technology entrepreneurship, and the intensity and relative importance of the different influencing factors are different in different regions. At the same time, different types of digital technology entrepreneurship exhibit varying degrees of dependence on each influencing factor, with regional differences also present.
Regional economic resilience has become a core topic in current economic geography to explore regional development dynamics, and improving economic resilience is of great significance to the high-quality development of regional economies. Based on the invention patent authorization data in China from 1999 to 2018, this article analyzes the structural characteristics of technology networks in 297 cities in China through the lens of network robustness, and explores the mechanism of technology network structures on regional economic resilience through panel regression, in order to provide a new insight into improving China’s regional economic resilience through the lens of technology networks. The results show that: 1) the urban technology network robustness of China showed an increasing trend regardless of random removal or targeted removal, especially after 2008. Beijing and Shanghai had always with relatively high technology network robustness. The technology network robustness of several regional central cities such as Shenzhen, Guangzhou, Suzhou, Nanjing, and Wuhan were growing rapidly, and there were obvious regional differences in the technology network robustness in China. 2) The technology networks robustness with completely random removal and completely targeted removal both had a significant positive effect on improving urban economic resilience, and the related diversification of the technology structure had a significant positive effect on economic resilience. 3) The regression of different proportions of targeted and random removals showed that as the proportion of targeted removals increased, the regression coefficient of the impact of urban technology network robustness on urban economic resilience increased, which means the degree of impact increased. These findings underscore the critical role of resilient technology network structures in enhancing regional adaptability and recovery capacity, and suggest that fostering diversified and robust urban innovation systems can serve as an effective strategy for promoting long-term regional sustainability and stability.
Urban agglomerations strengthen the economic and social ties between cities in the region, forming an integrated whole and is conducive to resisting risks and maintaining stable development, while the spatial relationship between cities within urban agglomerations, i.e., the structure of urban agglomerations, has yet to be explored in terms of its impact on economic resilience. This article measures and analyzes the spatial structure characteristics of urban agglomerations and economic resilience levels using multi-year data from 15 urban agglomerations in China as samples, and utilizes a two-way fixed effects model and an intermediary effect model to test and evaluate the impact mechanism of spatial structure of urban agglomerations on their economic resilience. The findings indicate that: 1) The average value of spatial structure index of urban agglomerations increased from 0.0611 in 2009 to 0.0758 in 2019, which suggests that the spatial structure of China’s 15 urban agglomerations as a whole shows a slight trend of monocentrism. 2) There is a large gap in the economic resilience of urban agglomerations during the study period, compared with inland agglomerations, urban agglomerations in the eastern coastal areas had greater economic resilience. 3) There is a significant linear negative correlation between the spatial structure of urban agglomerations and economic resilience, which suggests that multi-centralization of the spatial structure of urban agglomerations improves economic resilience. After a series of robustness tests such as changing variables, limiting samples and eliminating endogeneity, this conclusion still holds. 4) The intermediary effect model reveals that industrial structure upgrading plays an indirect intermediary role in the process of the spatial structure of urban agglomerations influencing economic resilience. Heterogeneity analysis shows that compared with high-level development stage urban agglomerations, multi-centralization of medium and low development stage urban agglomerations is more beneficial to their economic resilience, and the polycentric structure has a more obvious effect on the enhancement of economic resilience of urban agglomerations when the level of economic resilience of urban agglomerations is high. This article transcends the inherent administrative divisions, extends the research scale to the level of urban agglomerations, empirically analyzes the impact of spatial structure characteristics on regional economic resilience in a larger range, and provides some empirical evidence for improving the economic resilience of urban agglomerations from the perspective of spatial development patterns.
The construction of urban agglomerations is an important way to promote the high-quality development of regional integration and build a new development pattern of double-cycle, and the optimisation of the network structure of urban agglomerations can enhance the resilience of urban agglomerations, and promote the high-quality development of cities between urban agglomerations and the integration of high level. Based on complex network theory and resilience theory, we measure the network structure and robustness characteristics of the 3 major urban agglomerations in China: the Yangtze River Delta (YRD) urban agglomeration, the Beijing-Tianjin-Hebei (BTH) urban agglomeration, and the Guangdong-Hong Kong-Macao Greater Bay Area (GHMA). The results found that: 1) there are significant differences in the basic scale and complex network characteristics of the 3 urban agglomerations, and the urban agglomeration traffic, economic and information flows, the maximum and average values of the four types of centrality indicators, and the network density links between city pairs in Guangdong, Hong Kong and Macao Greater Bay Area are stronger than those between the remaining 2 urban agglomerations; 2) the connectivity robustness of the 3 urban agglomerations all performs poorly, and maliciously attacking the number of the top 20% of the cities in the clusters would result in the connectivity robustness plummeting to 0.2, and the network structure is on the verge of collapse. While the recovery robustness decreases to 0.5 and below, random attacks or malicious attacks are required to destroy 80% and 50% of the city nodes in the urban agglomeration, indicating that the 3 major urban agglomerations have strong post-destructive recovery capability. 3) Network density and robustness show a positive correlation. It is worth noting that the centrality eigenvalue shows a positive correlation with robustness when randomly attacking city nodes of the urban agglomeration, while it shows a negative correlation when malicious attack exposes the vulnerability more easily due to focusing on attacking the core nodes. 4) We should improve the hierarchical system of urban agglomerations, give full play to the strong radiating role of the core cities as well as enhance the connection between any cities in the clusters, and build an inverted ‘U’ shape. The inverted ‘U’-shaped urban agglomeration hierarchy structure, i.e., reducing the high and low values and increasing the number of cities in the middle level, can effectively enhance the robustness. The characteristics of the complex network of urban agglomerations and the influencing factors of robustness can effectively identify the links between urban agglomerations and the stability of the urban agglomeration network, so as to put forward more targeted planning strategies, which is conducive to the construction of high-quality integrated development of China’s urban agglomerations.
Island village is a special geographical unit that is most closely related to human activities in Marine and land systems. Exploring island village spatial evolution path is one of the important contents of rural geography. This article uses the actor-network theory and qualitative research methods such as in-depth interview and non-participatory observation to analyze the spatial evolution path of Beigang village on Pingtan International Tourism Island. The findings are as follows: 1) The spatial evolution of Beigang village is a process of multi-stage, multi-subject participation, mutual competition and negotiation. In this process, an actor network of human actors and non-human actors, local actors and external actors are gradually formed, and a road of rural revitalization on island is explored with “island leisure, cultural tourism integration” as the main line. 2) In the process of the transformation of actor network in Beigang village, the participation of human actors and non-human actors causes problematization, interest endowment, recruitment, mobilization and dissidence of the rural network to be re-interpreted and roles changed, and the key actors are replaced from local governments to talented people, foreign operators, tourists and Pingtan Comprehensive Experimental Zone Tourism Co., LTD. The Obligatory Passage Point (OPP) has changed from “improving the living environment, optimizing the industrial structure, and increasing economic income” to “building a Beigang characteristic theme village and a pioneering template for rural revitalization”. 3) Due to the intermingling of internal and external forces, the spatial evolution of Beigang village has undergone a transformation from “top-down administrative driving” to “up-down interactive multi-subject participation”, which reflects the passive response and active adaptation of rural heterogeneous actors in the process of adapting to social changes. The actor-network theory is suitable for presenting the multi-subject participation process and revealing the path of the spatial evolution of island village, which is of great significance for promoting the sustainable development of island village and expanding the research paradigm of rural geography.
From the ecological perspective of grain production, carbon emissions from grain production were selected as the index of non-expected output, and based on estimating green grain production efficiency and traditional grain production efficiency with non-expected output SBM model and DEA model, a deviation rate model was constructed to quantify the deviation between the two, and used to describe the spatial-temporal characteristics of the deviation of grain production efficiency at county level in Jilin Province in 2000—2019. The influence factors' effects in Jilin Province and sub-regions were analyzed using the geographical detector in our study. The results showed that: The change trends of traditional grain production efficiency and green grain production efficiency in Jilin Province were both U-shaped, but the traditional grain production efficiency was better overall. The spatial distribution pattern of traditional grain production efficiency and green grain production efficiency both showed the characteristics of stable high values in the west-central regions, sharp fluctuations in the central and eastern regions, and slight fluctuations in the marginal regions. Then, from an ecological perspective of grain production, the grain production efficiency in east, middle and west of Jilin Province was all negative deviation, which the deviation degree of grain production efficiency increased in the early stage and eased slightly in the later stage. Spatially, the deviation in the marginal areas of Jilin Province had always been heavy. While areas with higher and stability grain production efficiency of both two types demonstrated smaller efficiency deviations. Moreover, greater disparities between these two types resulted in more pronounced changes in deviation. The influence of the three factors was spatially consistent in the east, middle and west of Jilin Province, but the effect intensity had obvious regional heterogeneity. The input level of production factors was the main factor affecting the efficiency deviation in eastern region of Jilin Province and should be valued. However, social and economic status indirectly affects the efficiency deviation. As the basic factor affecting the deviation, the natural environment factor had a strong uncertainty. Therefore, the complex and strong effects of three kinds of factors should be considered comprehensively in the central region of Jilin Province, and the balanced weak influence of three factors in the western region of Jilin Province should be considered. To achieve a better balance between grain production and green development, it is imperative to explore and implement practical modern agricultural techniques tailored to regional control alongside preferential policies and scientific-technological support for agricultural modernization.
There has long been a discursive separation between workspace and home. Based on the geography of home theory, this article explores the process of constructing home within the livelihood space of operational migrants through in-depth interviews and participatory observation. The findings reveal that the home-making practices of business migrants illustrate the coexistence of workspace and home. Firstly, a stable business location is central to the home-making efforts of business migrants, providing them with a sense of ontological security and belonging. Secondly, the practice of domesticating business space is crucial for the construction of a “livelihood home”. Through self-employment and family management, business migrants can flexibly navigate their business and family responsibilities,thereby integrating the boundaries between work and life. Thirdly, through their business activities, migrants develop a local network of business relationships, express a positive local identity,and integrate into their new environment. Business cooperation reinforces existing kinship and geographic networks, thereby maintaining close ties to their original home. This article enriches the study of the geography of home, enhances our understanding of the multiple functions and scales of home, and constructs a theoretical framework for the “home of livelihood” contributing to the comprehension of business-oriented migration from a geographic perspective.
Industrial heritage is an important resource and cultural carrier of industrial tourism. How to realize the organic integration between industrial heritage and tourism utilization has become an urgent problem for the sustainable development of industrial heritage. In this paper, industrial heritage in northeast China is selected as the research object, and ArcGIS spatial analysis, concentration index and resource dominance are used to analyze its spatial distribution characteristics, and the relationship between industrial heritage resources and tourism utilization is discussed. The following conclusions are drawn: Industrial heritage in northeast China is dominated by heavy industry and less light industry, and the type distribution is significantly different among provinces. The spatial distribution type of industrial heritage in northeast China is clustered, and it shows an obvious unbalanced structure at city scale. The superiority degree of industrial heritage resources in northeast China is quite different, which mainly has the distribution characteristics of polar core area, highly dense area, sub-dense area and sparse area. Based on this, the author puts forward the utilization methods of industrial heritage tourism from the aspects of promoting the overall balanced development of industrial heritage resources, accelerating the transformation of industrial heritage resources into products, and promoting the brand building of industrial heritage resources products, so as to provide reference for the sustainable development and utilization of industrial heritage.The industrial heritage resources in northeast China exhibit spatial distribution differences, low levels of resource to product conversion, and weak brand effects. Based on this, promote the overall balanced development of industrial heritage resources in the region, form an effective connection and interaction of regional industries with “industrial culture+”, and enhance the potential and efficiency of linkage; Accelerate the transformation of industrial heritage resources into products, and in the process of preserving, changing, and restructuring the functions of various industrial heritage resources, adapt to the needs of urban functional development, and promote the cross-border integration of cultural and tourism resources; Promote the branding of industrial heritage resource products, fully explore industrial cultural elements in the branding of various industrial heritage resources, and propose industrial heritage tourism utilization methods in terms of creating themed, diverse, and experiential industrial tourism products, providing reference for the sustainable development and utilization of industrial heritage.
Ecotourism destinations face the critical challenge of balancing the provision of high-quality tourism experiences for diverse tourist types with the scientific management and optimization of their spatio-temporal behaviors to minimize environmental disturbances. This study aims to advance the precision management of tourists by categorizing and analyzing their spatio-temporal behavior characteristics, thus developing a more nuanced understanding of tourist management. The Shennongjia Forest Region, renowned for its diverse ecological landscape and significant tourism activity, is selected as the representative case site for this study. Tourists are classified based on their self-reported activities using activity segmentation methods, offering a comprehensive framework for understanding varied tourist behaviors. Employing grid analysis, behavioral chain analysis, and other advanced methodologies, the study analyzes the characteristics of tourists’ spatio-temporal behaviors. The K-Means algorithm is utilized to cluster tourists’ spatio-temporal behavior patterns, facilitating the identification of distinct behavioral groups. The research findings provide several key insights. Firstly, tourists in Shennongjia can be categorized into eight primary types: self-driving, cycling, hiking, sightseeing and photography, skiing, mountaineering, trail running, and others. These activities are concentrated within specific daily periods, with higher visitor numbers observed in spring and summer, significantly influenced by holiday seasons. Notably, mountaineering and hiking tourists tend to spend more time in ecological protection areas, indicating potential risks for these sensitive regions. Secondly, unlike the highly concentrated distribution of traditional scenic area tourists, the classification perspective highlights prominent characteristics of “dispersed concentration” and “decentralization”. The flow structure exhibits features of “growth along roads” and “small area clusters”, suggesting that tourist activities are not confined to traditional hotspots but are distributed across various segments of the landscape. Thirdly, tourists’ spatio-temporal behavior patterns can be categorized into three types:“hotspot sightseeing tours”“in-depth jungle trekking tours”, and “leisure vacation short tours”. Within the in-depth jungle trekking tours, a significant proportion of tourists (39.82%) penetrate undeveloped ecological protection areas, underscoring the urgent need for strategic management responses to protect these vulnerable regions. The research findings enhance theoretical perspectives on the spatio-temporal behaviors of tourists in ecotourism destinations by providing a detailed understanding of how tourists interact with the environment across different activity types. Additionally, they provide a robust theoretical foundation for the precise management of large-scale mountainous ecotourism areas. By offering actionable insights into tourists’ behaviors, this study contributes to the development of strategies that balance high-quality tourism experiences with the preservation of ecological integrity. The insights from this research are crucial for ensuring the sustainable development of ecotourism destinations like the Shennongjia Forest Region, where careful management of tourist behaviors is essential to maintaining the ecological and aesthetic value of these natural landscapes.
Exploring the logical path of tourism-driven traditional village system reconstruction is a positive exploration to promote the protective development of such villages and accelerate the implementation of rural revitalization strategy in the context of the deep integration of culture and tourism development. In addition, it is also a key breakthrough to solve the practical difficulties of hollowing out traditional villages, cultural memory gaps,and weak endogenous development. It is an important practical innovation to achieve the dynamic inheritance of cultural heritage and sustainable rural development. By establishing a theoretical framework for the reconstruction of traditional village systems driven by tourism, the core elements and operational mechanisms of the system are systenatically deconstructed. Firstly, establish a multidimensional goal system that unifies protective development and sustainable development, covering core demands such as cultural heritage inheritance, spatial function optimization,and economic vitality activation; Secondly, starting from the synergistic effect of endogenous and exogenous driving forces, analyze the reconstruction characteristics of core dimensions such as material space, production mode, cultural ecology, and social relations; Furthermore, by revealing the dynamic coupling mechanism between various subsystems, the evolutionary logic of traditional village spatial reproduction, functional reorganization, and value creation under the background of tourism intervention is elucidated; Finally, representative typical village were selected for empirical research, and a systematic reconstruction path was proposed based on regional resource endowment and cultural tourism integraion characteristics. The results show that:1) The driving force for the reconstruction of traditional villages mainly comes from the support of natural background conditions of resources and location, the tourism market demand of national culture experience, the investment of corporate capital in pursuit of profits, the demand of local residents for improving people’s livelihood and the promotion of tourism industry support policies under the rural revitalization strategy. Compared with the general driving force for the reconstruction of the countryside, it is necessary to pay attention to the spillover effect of the common driving elements and the enhancement of the effect in this kind of special geographical area. 2) Reconstruction objects include spatial pattern, production mode, social relations, natural and humanistic environment and other dimensions, and there are interactions and mutual influences among the dimensions, which jointly promote the reconstruction of the traditional village system; 3) Based on systematic reconstruction thinking, this article explores the reconstruction path of Laodong Village from the aspects of spatial scope, landscape characteristics, production types, tourism development subjects, benefit distribution, and ethnic cultural inheritance. Combining the characteristics of material spatial landscape and protection and development froms, it is divided into authentic landscape core protection zone, transitional landscape buffer zone,and constructive landscape coordination zone. In response to the differences in production materials and production objects in each district, the production logic and value orientation are reshaped, cultural tourism resources are integrated,market development mode is optimized, ecological service value is emphasized to empower production mode transformation of production relations from single subject to multi subject co governance, forming a composite social relationship network, and then guiding cultural and ecological reconstruction in each district.
Climate change exhibits significant spatial heterogeneity, leading to relative climatic variations that have substantial impacts on vegetation. However, there is currently no quantitative method to assess the effects of relative climate change in time and space on vegetation. This study proposes using the ranking of Vapor Pressure Deficit (VPD) differences (VPDr) as an index for relative climate change, with VPD, Carbon Dioxide (CO2) concentration, and annual precipitation (Pre) as climate change indicators. Using ridge regression and correlation analysis, the study quantitatively estimates the impacts of VPDr, VPD, CO2, and Pre on the Normalized Difference Vegetation Index (NIRv) in the arid and semi-arid regions of northwest China. The results demonstrate that VPDr, derived from VPD, is a feasible index for assessing relative climate change and estimating its effects on vegetation. Regional analysis further validates the results. Relative climate change has a significant impact on vegetation, with this impact being more pronounced than the effect of VPD alone. In arid and semi-arid regions of northwest China, the rate of aridification exceeds that of humidification, resulting in an overall trend of relative aridification, which negatively affects vegetation. An increase in VPDr across most regions indicates relative aridification, suppressing vegetation growth, particularly in areas such as the western Tarim Basin, Tianshan Mountains, and central Inner Mongolia Plateau. Conversely, regions with decreasing VPDr indicate stable or relatively humid climates, which enhance climate suitability and promote vegetation growth, notably in areas like the Taklimakan Desert hinterland, Hexi Corridor-Badain Jaran Desert, and Hulunbuir Plateau-Northern Da Hinggan Mountains. In these regions, vegetation shows a growth trend, largely driven by CO2 fertilization effects and increased precipitation. This study introduces an innovative quantitative index for relative climate change and provides a method for estimating its impact on vegetation, thus expanding our understanding of climate change’s effects on vegetation. More importantly, the study shows that even in regions with relatively stable climate, the climate will also have relative changes in time and space, and vegetation is also affected by the relative changes in time and space of climate, and the impact of climate change on vegetation is very different. All regions can not be immune to climate change, and should work together to cope with climate change.
Improving the simulation accuracy of land surface models for regional vegetation dynamics is of great significance for studying the mutual influences between vegetation and land surface water-heat cycles, and it further aids in predicting regional vegetation and carbon cycles under climate change scenarios. Parameter optimization is an effective approach to enhance the simulation accuracy of land surface models. This study focuses on the application of the Noah-MP land surface model in the Yellow River Basin. By adjusting five parameters related to dynamic vegetation simulation and conducting multiple repeated simulation experiments, we analyzed the impact of parameter variations on vegetation simulation performance using satellite remote sensing-derived leaf area index (LAI) products as a reference. The results indicate that the default parameters of Noah-MP lead to a severe underestimation of simulated vegetation, primarily caused by the excessively high vegetation turnover rate parameter (LTOVRC). Finally, an optimal parameter set was selected.The parameter optimization significantly addressed the underestimation and seasonal lag issues in LAI simulations for certain regions under the original default parameters. The improvements were evident in the correlation coefficient (R), Nash-Sutcliffe efficiency coefficient (NSE), and root mean square error (RMSE) across various vegetation types. For example, for deciduous broadleaf forests, R increased from 0.489 to 0.879, NSE improved from −0.83 to 0.46, and RMSE decreased from 2.22 to 1.21. A comparison with corresponding remote sensing products further demonstrated that this parameter optimization also enhanced the model's simulation performance for gross primary productivity (GPP) in the Yellow River Basin.
To explore the distribution characteristics and the determining factors of soil inorganic carbon (SIC) content in coastal wetlands, along with their mechanisms, this research was conducted in three distinct wetland types (mudflat, the Spartina alterniflora wetland, and the Suaeda salsa wetland) in the Yanghe River estuary at Jiaozhou Bay. Uniformly distributed sampling was carried out to determine the SIC content, soil dissolved inorganic carbon (SDIC) content and soil physical and chemical properties (pH、BD、SC、WC、Ca2+、Mg2+、SOC). The Duncan method was applied for assessing differences in data significance, while the Pearson correlation method was deployed to analyze relationships between SIC content and soil physicochemical attributes. Furthermore, machine learning models, together with structural equation modeling, were utilized to predict SIC content performance, determine the influence of various factors, and dissect their interactive pathways. The findings indicate that 1) The SIC and SDIC contents of the wetland varied from 0.28 g/kg to 10.9 g/kg and from 41.92 mg/kg to 163.15 mg/kg, respectively, with coefficients of variation indicating high variability (58.97%) for SIC and medium variability (18.94%) for SDIC; 2) The SIC content was highest in the mudflat (3.49 g/kg), followed by the Spartina alterniflora wetland (2.37 g/kg), and lowest in the Suaeda salsa wetland (2.32 g/kg), with significant differences observed between the mudflat and the other two wetland types. The SDIC contents of the Suaeda salsa wetland (91.9 mg/kg) > the Spartina alterniflora wetland (88.2 mg/kg) > the mudflat (84.3 mg/kg), and there was no significant difference between them; 3) The SIC content exhibited a decrease with increasing soil depth, whereas the SDIC content initially decreased before subsequently increasing as soil depth increased. Nevertheless, these trends were not statistically significant; 4) SIC content was significantly and positively correlated with all other soil physicochemical properties, except for a significant negative correlation with soil bulk density (BD) (P<0.01). The order of importance of the influencing factors was as follows: pH>SC>SOC>BD>Mg2+>WC>Ca2+. And the Random Forest (RF) model, based on relevant soil physicochemical properties, excelled in predicting SIC content (R2=0.73, RMSE=0.11g/kg); 5) Soil pH, salinity, and moisture content are the main factors affecting SIC content, which can directly influence its concentration. Additionally, salinity was found to indirectly affect SIC content via its impact on soil pH, while soil bulk density influenced SIC content indirectly through modulating soil porosity and moisture content. This investigation provides valuable insight into the determining factors of SIC content and their mechanisms, offering robust data support and methodological guidance for the evaluation of carbon cycling and carbon sequestration dynamics in coastal wetland soils-a pivotal aspect for understanding future shifts in soil inorganic carbon dynamics.
Clarifying the influence mechanism of blue-green landscape patterns on urban thermal environment is of great importance to mitigate urban heat island effect. However, the current researches lack a quantitative analysis of the spatial effect of blue-green landscape patterns and detailed discussion on the difference of the influence characteristics of blue-green landscape patterns in different geographic units. In order to solve this problem, three kinds of geographic units including grid, city block, and district, are selected, and the main urban area of Jinan City is taken as the study area. The blue-green landscape patterns are measured from land use data in 2021, and the land surface temperature (LST) data are obtained from Landsat Collection 2 Level-2 Surface Temperature (LC2L2ST) product. On this basis, the cooling effects of blue-green landscape patches are investigated by decay model. Then, the marginal effect, interactive relationship and spatial effect of blue-green landscape patterns on LST are analyzed respectively employing boosted regression trees model, Geodetector and spatial Durbin model in different geographic units. The results show that: 1) Various grades of blue-green landscape patches generally have the cooling effects. The cooling effects of water are significant, while the cooling effects of greenspaces are relatively weak. With the increase of patch area, the cooling amplitude and influence distance of blue-green landscape fluctuate and increase. The cooling effects of water may be more sensitive to the change for area, while the cooling effects of greenspaces are probably less affected by the change for area. 2) Percentage and mean core area of blue-green landscape generally have the significant influences on LST, but demonstrate a distinct threshold effect. Contagion index and Shannon’s evenness index of blue-green landscape have the weak influences. Edge density, patch density and cohesion index of blue-green landscape probably have opposite effects on the LST in the local geographic unit and neighboring geographic units. 3) Marginal effects, interactions and spatial effects of blue-green landscape patterns on LST vary significantly among various geographic units. In the 200 m grid units, LST variation is more likely to be influenced by percentage and mean core area of blue-green landscape. As the increase of grid unit scale, the interactions of blue-green landscape patterns decrease, and the influence mechanism of blue-green landscape patterns on LST became more complex. Moreover, the spatial effects of blue-green landscape indies are generally weakened. But the effect of edge density and patch density of greenspace and blue-green landscape shape index on LST is prominent in the large grid units. In the block and district units, blue-green landscape patterns of local areas show more significant effect on local LST than that on neighboring spaces. Percentage of greenspaces have the prominent impact on LST in the block units, while the effects of water landscape patterns on LST are relatively significant in the district units.
