Based on Baidu search index big data mining, this article constructs China’s regional economic uncertainty index, which measures regional economic uncertainty by capturing the subjective cognitive attitudes of micro subjects’ search behaviors that reflect “uncertainty”. The Chinese regional economic uncertainty index is measured and analysed in time series at the national and provincial scales, respectively. The DY spillover index model is used to study the static spillover effect, dynamic spillover effect and net spillover effect of cross-regional economic uncertainty. On this basis, the spillover network model of inter-regional economic uncertainty is constructed using the complex network method to examine the path of inter-regional uncertainty contagion, and the main conclusions are as follows: The constructed regional economic uncertainty index is able to identify the fluctuation of uncertainty caused by major events effectively. The occurrence of major economic, geopolitical and public health events can trigger a sustained rise in regional economic uncertainty. The results of the spillover network analysis show that the middle reaches of the Yangtze River and the southwest economic zones of China are the main exporters of spillovers in the system, and other regions, such as the eastern coastal economic zone, play the role of spillover receivers. Cross-regional economic uncertainty is transmitted mainly from the southwest economic zone to the eastern coastal economic zone, and from the middle reaches of the Yangtze River to the southern coastal economic zone. Regional economic policymakers should establish and improve cross-regional economic uncertainty coping mechanisms, identify and understand the time-varying characteristics of economic uncertainty based on regional resource endowments, development levels and specificities, scientifically formulate differentiated regional economic risk prevention and control policies, and maintain policy continuity and stability. Through scientific and technological innovation and industrial upgrading, it will promote high-quality development of the regional economy and reduce its sensitivity to uncertainty shocks.
The reconfiguration of regional spatial patterns and economic layout is essential for achieving modernization with distinctive Chinese characteristics. Guided by the principles of “innovation, coordination, green development, openness, and sharing”, this paper examines the subdivision characteristics, reorientation, and methodologies for implementing innovative regional spatial patterns in China’s economic geography. The newly proposed regional spatial configuration is supported by four major geographical divisions, economic belts, key urban agglomerations, metropolitan clusters, and new urbanization initiatives, displaying characteristics of zoning, skeletonization, networking, focalization, and unitization. This transformative framework aims to reduce disparities between regional spaces, promote regional restructuring. It leverages connectivity in network spaces, trade freedom, spatial arrangement of elements, and industry collaboration. The framework focuses on narrowing spatial disparities, coordinating skeletal spaces with national territory planning, enhancing network connectivity, and fostering trade liberalization. It emphasizes spatial layouts and synergies between industries to optimize resource allocation and boost economic efficiency. Integrating urban and rural spaces with precise functional positioning ensures developmental benefits are evenly distributed. The paper suggests pathways for coordinated development through zoning and regional differentiation, enhancing ecological functionality, and promoting green development. Additionally, it outlines tasks for integrated maritime and economic expansion, digital economy advancement, and industrial security. Furthermore, it proposes mechanisms for shared development in special areas and integrating urban and rural advancements. In conclusion, the new regional spatial patterns and economic layout reshaping not only align with China’s modernization goals but also set a precedent for sustainable and inclusive regional development, providing a detailed roadmap for policymakers and stakeholders to navigate the complexities of China’s diverse landscape.
Urban inclusive innovation is the most fundamental value orientation of urban innovation in the context of Chinese path to modernization, which is more conducive to promoting equitable and sustainable urban development than traditional urban innovation. Based on the connotation of urban inclusive innovation, this paper constructs a measurement framework for urban inclusive innovation, empirically analyzes the spatial pattern and influencing factors of Beijing’s urban inclusive innovation by using entropy method, spatial autocorrelation and geographical detector model. The results show that: 1) Urban inclusive innovation is an innovative act based on inclusive innovation policies that create opportunities for the public to participate in innovation activities and share the fruits of innovation in a fair manner, so as to realize the relatively fair development of urban innovation, and its measurement dimension include inclusive innovation policies, equity of opportunity for participation and sharing of innovation outcomes. 2) The overall level of urban inclusive innovation in Beijing decreases from the central urban area to the surrounding area, and shows a phenomenon of agglomeration in spatial distribution, with high-high clusters concentrated in the Dongcheng District, the Xicheng District, the Chaoyang District and the Fengtai District, and low-low clusters concentrated in the Huairou District and the Miyun District. 3) The formation of the spatial pattern of Beijing’s urban inclusive innovation is the result of a combination of factors, with culture, education and industrial structure being the most important influencing factors, and any 2 factor interactions are bifactor enhancement or nonlinear enhancement relationships. Finally, this paper proposes policy recommendations for Beijing in developing urban inclusive innovation based on the findings of the study.
Improving the green total factor productivity (GTFP) is the key to the green transformation of industry and the main path to promote high-quality industrial development. Taking the Huaihai Economic Zone as an example, this paper integrates the SBM model, geographically weighted regression model, and so on to analyze the spatio-temporal characteristics and influencing factors of the industrial green transformation performance of adjacent areas at provinces or regions in 2001—2020, and identifies the types of problem areas. The findings are as follows: 1) The industrial GTFP in the Huaihai Economic Zone shows an overall upward trend during the study period, and regional differences are widening and spatial agglomeration is increasing; 2) The industrial green total factor productivity is concentrated in the border areas of Jiangsu and Shandong, and the counties along the Beijing–Shanghai line have the largest industrial green total factor productivity, while those along the Beijing–Kowloon line have the lowest green total factor productivity. The industrial green total factor productivity of rural areas is larger than that of urban areas. For spatial correlation, the low-low type county-level regions are concentrated in the Jiangsu-Anhui-Henan border area; 3) The improvement of industrial GTFP in the Huaihai Economic Zone results of the collective action of various factors. The roles of informatization level, industrial agglomeration, and transportation infrastructure level have changed from promotion to inhibition, while the roles of opening to the outside world and energy security have changed from inhibition to promotion; 4) There are 6 types of problem areas for the green transformation and development of industries in the Huaihai Economic Zone, namely, the lagging of technical efficiency and technological progress, the lagging of technological progress and industrial GTFP, the lagging of technical efficiency and industrial GTFP, the lagging of technological progress, the lagging of technical efficiency, and the stable growth of industrial green total factor productivity. Accordingly, differentiated regulatory measures for the green transformation and development of industrial zones in the Huaihai Economic Zone have been proposed, tailored to the specific types of problematic areas.
Overseas energy investments serve as a critical safeguard for China’s energy security. Understanding the spatiotemporal dynamics and spillover effects of China’s global energy layout provides valuable insights for optimizing investment strategies and refining planning policies. This study utilizes the China Global Energy Investment Tracker, a fixed panel regression model, the geopolitical risk index, and GIS spatial analysis to examine the structural evolution and multifaceted impacts of China’s global energy investments. The key findings are as follows: 1) China’s global energy layout follows a “rise-then-decline” temporal pattern characterized by significant fluctuations. Renewable energy has emerged as the primary growth driver, while project failure rates have steadily decreased. 2) The energy layout remains predominantly led by state-owned enterprises (SOEs), although the role of private enterprises has grown substantially. The regional specialization of enterprises has weakened, showing a trend toward more balanced overseas site selection. 3) The role of developed countries in China’s global energy layout has significantly diminished, while the proportion of projects located in Belt and Road Initiative (BRI) countries has increased markedly. Renewable energy projects are actively expanding into international markets, facing relatively lower geopolitical risks, whereas traditional energy projects remain stable but are increasingly exposed to heightened geopolitical challenges. 4) China’s global energy layout exhibits implicit carbon transfer effects. Investments in traditional energy contribute to oil and gas import effects, while renewable energy projects play a pivotal role in advancing energy transition efforts. These findings offer critical perspectives for enhancing China’s overseas energy strategies in response to global energy transitions and the growing complexity of geopolitical risks.
Based on the panel data of the city cluster in the middle reaches of the Yangtze River in 2006—2020, we constructed the index of urban renewal and ecological resilience, measured the urban renewal and ecological resilience by using entropy-weighted TOPSIS method, analyzed the evolution of the spatial network structure of urban renewal and ecological resilience by utilizing the method of social network analysis, and detailed the spillover effect of urban renewal on ecological resilience by means of the spatial econometric model. The social network analysis method is used to analyze the evolution of the spatial network structure between urban renewal and ecological resilience, and the spatial measurement model is used to analyze the spillover effect of urban renewal on ecological resilience. Firstly, there is a spatial correlation network between urban renewal and ecological resilience, and there is a spatial spillover effect of urban renewal on ecological resilience. Secondly, the empirical results show that: 1) From the perspective of spatial and temporal patterns, urban renewal in the urban agglomeration in the middle reaches of the Yangtze River presents the spatial distribution characteristics of “small agglomeration and large dispersion”, and the ecological resilience presents the spatial distribution situation of dispersion to agglomeration. 2) The urban renewal and ecological resilience of the city cluster in the middle reaches of the Yangtze River have obvious spatial spillover effect and network correlation, but the stability of the network as a whole has been reduced during the study period; in addition, the individual characteristics show that the spatial correlation and spatial spillover effect of urban renewal and ecological resilience of each node have been weakened, and the ability to radiate and receive external radiation has been reduced. 3) The regression results of the spatial measurement model show that urban renewal has a significant negative impact on ecological resilience, and the decomposition results show that urban renewal has a significant positive spatial spillover effect on ecological resilience. Finally, relevant suggestions are made to strengthen the collaborative environmental governance, optimize the development mode of urban renewal, and explore the multidimensional path of urban renewal to enhance ecological resilience.
Human activities have led to land use changes, greatly affecting ecosystem health. Exploring the non-linear relationship between these changes and ecosystem health is vital for the superior regulation of territory spatial. Existing studies insufficiently addresses how land use structure affects ecosystem health and whether different land use types have threshold effects on ecosystem health, and it is difficult to reflect the role of key land use types in ecosystem health. In this study, the Changsha-Zhuzhou-Xiangtan Urban Agglomeration is the study subject with gird scale as units. And we built a ecosystem health assessment framework to reveal the spatial-temporal patterns of ecosystem health changes in the study area from 2000 to 2020, and we used random forest and piecewise linear regression model to identify the threshold effect of ecosystem health on the response to land use changes. Results are as follows: 1) Over the study period, built-up land significantly increased with its share escalating by 8.10%, mainly due to conversion from cropland and forest land, with the conversion rates being 11.87% and 6.83% respectively. Construction land expansion leads to loss of ecological and grain production land. 2) Ecosystem health level showed a decline then an upward trend over time. Spatially, spatial heterogeneity is significant, tied to land use types, with different levels showing clustered distribution. Ecosystem vigor, ecosystem organization, and ecosystem services showed clear differentiation trends. 3) Cultivated, forest, and construction lands are pivotal for ecosystem health, with thresholds affecting it. Ecosystem health reached medium levels with cropland at or above 1.98%, forest land at or above 7.58%, and construction land at or less than 19.80%. Exceeding these thresholds altered the impact trends on ecosystem health. Cultivated and forest lands benefited ecosystem health, while construction land expansion harmed it. Thus, the structure and layout of different land use types should be reasonably determined to promote the balance of ecological, agricultural and urban space in the optimization and control of territory spatial.
Using the panel data of 41 prefecture-level and above cities in the Yangtze River Delta (YRD) urban agglomeration from 2010 to 2021, the spatio-temporal pattern of the level of integrated urban-rural development in the study area is analyzed by constructing a multidimensional comprehensive evaluation system, and the influencing factors are resolved by using a Geodetector model. The results show that: first, the overall integrated urban-rural development level of the YRD urban agglomeration shows a steadily increasing trend, rising from 0.499 7 in 2010 and
Based on the formation mechanism of tourism ecological system adaptability, the evaluation index system of tourism ecosystem adaptability is constructed from 2 subsystems of tourism industry adaptability and ecological system adaptability, and 3 dimensions of sensitivity, stability and response. The entropy-weighted TOPSIS method, adaptation model, exploratory spatial data analysis, standard deviatioin ellipse and Geo-detector were used to analyze the spatiotemporal pattern and influencing factors of tourism ecological system adaptability in 130 municipalities in the Yangtze River Economic Zone in 2012—2021. The results indicate that: 1) In the past 10 years, the tourism ecological system adaptability has been weak, showing trend of “rising-declining-rising”, consistent with tourism industry adaptability; the spatial difference of tourism ecological system adaptability is significant, showing spatial distribution characteristics of downstream area>upstream area>midstream area. 2) Tourism ecological system adaptability has a significant positive global spatial autocorrelation, showing a trend of increasing and then decreasing; local spatial autocorrelation exists in 4 types of clustering: high-high, high-low, low-high and low-low. 3) Adaptation shows a spatial distribution pattern of “north-east to south-west”, with the centre of gravity located in Changde City, and gradually moving to the southwest. 4) Tourism resources, economic development, ecological governance, government regulation and ecological elasticity are the main influences driving the adaptive spatiotemporal patterns of tourism ecological system.
The provision of an age-friendly rail transit environment is one of the effective measures to solve the aging problem. Although several studies have explored the impacts of built environment on rail transit travel behavior, the temporal and spatial heterogeneity effects of rail transit travel behavior have rarely been considered. Taking Wuhan as an example, the rail transit travel behaviors of the elderly and built environment factors were accurately characterized by integrating multi-source big data, including bus intelligent cards, land use, point of interest (POI), and housing prices. Several geographical regression models with different spatial weights were constructed to investigate the impact of built environment on travel time of elderly rail transit riders. The spatial lag model (SLM) with the best fitting was selected to further reveal the spatial heterogeneity in built environment that affects elderly travel time on weekdays and weekends in different urban geographical circles. The results show that: 1) The average travel time of weekday and weekend for the elderly is 29.45 minutes and 31.18 minutes, respectively, but there are more elderly riders living in the new town circle with travel time over 45 minutes. 2) The travel time of the elderly on weekdays is strongly correlated with the accessibility of grade-A tertiary hospitals, but that on weekends is more related to the accessibility of urban parks. 3) For the old town circle, built environments have relatively slight impact on the travel time of the elderly, the transfer of rail transit is the main factor contributing to the long travel time of the elderly. 4) As the geographical location gradually expands to urban periphery, the number of built environment factors that affect travel time of the elderly in the middle and new town circle is gradually increasing, including floor area ratio, land use mix, road density, and accessibility of public service facilities. Based on the modeling results, the optimization suggestions on built environment and rail transit environment in different urban circles were proposed, thus providing a reference for megacities to formulate age-appropriate rail transit policies and improve the low-carbon travel services for elderly riders.
The strategy of “strengthen provincial capital” is an important point to improve the comprehensive competitiveness of provincial capital, and the industrial structure is the core index to measure the comprehensive competitiveness of a city. So, can the administrative division adjustment, which is the most direct means of the strategy of “strengthen provincial capital”, promote the upgrading of the industrial structure of the provincial capital? Based on the panel data of 26 provincial capital cities in China from 2003 to 2020, this paper uses the difference-in-differences method (DID) to find that the administrative division adjustment under the strategy of “strengthen provincial capital” has a significant role in upgrading industrial structure, but the driving effect of administrative division adjustment on upgrading industrial structure of provincial capital was only 3 years. The mechanism test shows that the administrative territorial entity adjustment will through both easing the bottleneck of resource constraints and improving the level of technological innovation to promote the industrial upgrading of provincial capital cities. Specifically, compared with the merger of administrative regions, the promotion of the industrial upgrading of provincial capital cities is stronger; compared with the vice-provincial cities or the multi-center layout mode in a province, the industrial structure upgrading effect after the administrative division adjustment of the general provincial capital cities or the single-center layout mode in a province is more obvious.
In response to the shortcomings of research on the development of poverty-eliminated counties during the period of effective connection between poverty alleviation and rural revitalization, this article, based on the theoretical perspective of geographical capital, uses random forest and coupling coordination model methods to evaluate the geographical capital of poverty-eliminated counties, and identifies the development priorities, types, and strategies of poverty-eliminated counties during the transitional period. Findings are shown as follows. First, the geographical capital level of poverty-eliminated counties generally shows a decreasing spatial difference pattern from southeast to northwest. The phenomenon of imbalances in economic and social geographical capital, as well as social and ecological geographical capital, is relatively significant, with the proportion of incongruous counties accounting for 62.8% and 56.4%. Most of these counties are constrained by social geographical capital. Second, it is identified that 326 of poverty-eliminated counties should take preventing the return of regional poverty as priority while 426 of them should take promoting rural revitalization as priority during the transition period. The former counties is divided into 5 sub-types with different development strategies, which are mainly located in the central and western regions on the northwest side of Hu Line; the latter is divided into 6 types, which are mainly located on the southeast side of Hu Line. Third, it is suggested that promoting positive interaction of various geographical capital is important for the sustainable development of poverty-eliminated counties. For the poverty-eliminated counties with preventing the return of regional poverty as priority, external support should be strengthened to break through the dilemma of low-level constraints from geographical capital; for those counties which take promoting rural revitalization as the development priority, emphasis should be placed on the enhancement of social geographical capital and transformation of economic development into people’s well-being.
Realizing the effective adaptation between territorial space development and urban-rural integration is an urgent need for building a beautiful China, and it is of great significance for promoting the realization of common prosperity in urban and rural areas. Using sequence matching degree and Kernel density to analyze the spatio-temporal adaptation relationship between territorial development intensity and urban-rural integration in the Wuling Mountain Area, and establishing a spatial equation model to investigate the spatial interaction between the two. The results show that: 1) From 2010 to 2020, the adaptation type of territorial development intensity and urban-rural integration in the Wuling Mountain Area shifted from intermediate adaptation to primary adaptation, and the absolute differences of districts have convergence characteristics; the stability of the spatial structure of adaptation still needs to be improved. 2) There is a positive interaction between territorial development intensity and urban-rural integration, the effect of urban-rural integration on territorial development intensity is greater than the effect of territorial development intensity on urban-rural integration, and there is a “mimicry effect” between districts in the pattern of territorial development and urban-rural integration. 3) There is a negative spatial spillover effect in the interaction between territorial development intensity and urban-rural integration. The territorial development intensity in neighboring areas has an inhibitory effect on local urban-rural integration, and similarly, the improvement of urban-rural integration in neighboring areas will reduce local territorial development intensity. In the process of territorial space development and promoting urban-rural integration, local governments must adhere to the human-land coupling system theory to reshape the territorial space structure, meet the demands of regional coordinated development, and realize the effective adaptation of territorial space development and urban-rural integration.
At 23:59 on December 18, 2023, an earthquake with a magnitude of MS 6.2 occurred in Jishishan County, Gansu Province, and at the same time a mudflow secondary geologic disaster broke out in Qijiagou, Zhongchuan Township, Minhe County, Qinghai Province, which is a typical secondary geological disaster of the same earthquake and transformed into a disaster by the coupling and superposition of multiple disasters such as earthquake, landslide and mudflow, and its impact and effect are much greater than that of a single disaster. Through all kinds of methods such as field survey and measurement, remote sensing image analysis, empirical formula estimation and villagers’ interviews so as to recover and reappear the chain process consisting of “agricultural irrigation-static liquefaction-local plastic deformation-potential slip formation” and “earthquake-dynamic liquefaction-seismic slip through-slump slip-mudflow”. This article discusses the geomorphological characteristics and occurrence process of mudflow in Qijiagou, and conducts a preliminary discussion on its causes. The results showed that: 1) The Qijiagou mudflow, with a total length of about 3.0 km and a disaster-forming area of about 0.478 km2, there are all kinds of types of landforms, so it is a typical mudflow-hazard geomorphologic process with a full range of geomorphologic types. 2) the instantaneous maximum flow rate of the first wave of viscous mudflow in Qijiagou was above 10 m/s, and the mudflow head reaches Caotan Village in Zhongchuan Township almost at the same time as the earthquake, and the subsequent intermittent mudflow velocity was about 7.1, 6.0 and 5.8 m/s, compared with the mudflow head, it’s twice as small and gradually decreased; 3) Irrigation over a long period of time, leakage of water channels and pre-earthquake winter irrigation led to the pre-saturation of loess layer in mudflow formation area, and seismic oscillation load causes the liquefaction of underground saturated loess layer, earthquake triggered a sudden increase of excess pore water, the mudflow high speed, low slope drag reduction movement pressure may be the key mechanism for the formation of high-speed mudflow. 4) Winter irrigation on agricultural land and failure to close the electric switch in time after earthquake were the main hydrodynamic conditions of subsequent intermittent mudflow, as well as the human factors that led to mudflow disasters. The co-seismic mudflow is formed by the coupling of multiple factors so it’s very special for research, we should increase our efforts to protect this rare geological site. It is recommended to be protected as geological disaster relics, we should carry out protection zoning, and strengthen the assessment of geologic disaster risk of water conservancy projects in the Yellow River plateau irrigation area, pay attention to preventing the occurrence of loess landslides.
According to Drought and Flood Atlas (DFA) based on bibliography, tree-ring reconstructed Palmer drought severity index (PDSI) and GPCC precipitation dataset, 5 precipitation sequences in the Yangtze River Basin (YRB) of China have been reconstructed from 1470 to 2020, and the precipitation characteristics was discussed further. Spatially, the YRB can be divided into 5 precipitation sub-regions based on modern meteorological precipitation, namely: the source region of the Yangtze River (Region Ⅰ), the Sichuan-Han basin region (Region Ⅱ), the southwest mountainous region (Region Ⅲ), the Hubei-Chongqing mountainous region (Region Ⅳ) and the eastern plain region (Region Ⅴ). Significant negative correlations between DFA and the adjacent tree ring reconstructed PDSI in each sub-region have been detected (P<0.01), establishing the basis for the extraction of precipitation information. The R2 of reconstructed precipitation by multiple regression model ranged from 0.16 to 0.68 (P<0.01), and has been further evaluated by effective coefficient, relative deviation (RD), showing that the model was acceptable. The reconstructed precipitation was well comparable to the measured precipitation during the verification period (1951—2000) (0.70<r<0.83, P<0.01). The RD varied between ±30% without obvious bias. More wet events occurred during 1470—1540 and 1660—1705. The precipitation in Region Ⅰ and Ⅱ changed synchronously (r=0.27, P<0.01), with more flood events during 1935—1985 for Region Ⅰ and during 1845—1950 for Region Ⅱ, respectively. The precipitation in region Ⅲ was significant drought at the intervals of 1620—1655, 1933—1945 and 1986—1994. The precipitation in Region Ⅳ and Ⅴ highly correlated (r=0.47, P<0.01). Several short periodicities of precipitation (2-7 a) revealed by multi-taper method of periodicity analysis in the YRB have been obtained. In addition, there were additional periodicities for precipitation in each region, that is, 9 a, 31-51 a in Region Ⅰ; 22 a, 36 a and 256 a in Region Ⅱ; about 21 a in Region Ⅳ ; about 256 a in Region Ⅴ.
Using the observation data of minute rainfall at Kunming Station from 1961 to 2020, the reasonable minimum rainfall interval in Kunming area was determined by comparing the changes in the number of rainfall fields, effective rainfall contribution rate, and autocorrelation coefficient distinguished by different minimum rainfall intervals at the station. On this basis, the minute rainfall observation data of the rural representative station (Taihuashan Station) was introduced to divide the rainfall processes of Kunming Station and Taihuashan Station with the minimum rainfall interval, to compare the different changes in urban and rural rainfall processes in Kunming City, and to analyze the possible reasons for the changes in urban rainfall characteristics. The following conclusions were drawn: 1) The minimum rainfall interval for the natural rainfall process in Kunming area was set at 3 hours, which is the most reasonable. 2) The effective rainfall process in Kunming area accounted for more than 40% of the total rainfall process, and the contribution rate of rainfall had exceeded 95%; Compared with rural areas, the number of annual rainfall events in urban areas has shown interdecadal changes since the 1990s, with an increasing trend of heavy rainfall, especially the growth rate of extremely heavy rainfall processes above 100.0 mm, which was much higher than in rural areas. 3) After the 1990s, except for the decrease of trace rainfall, other rainfall in Kunming city has increased. The duration of urban rainfall was shortened and the peak of rainstorm was advanced. The heavy rainfall lasting about 1 hour changed from a bimodal rain pattern to a unimodal rain pattern. 4) The intensification of urban heat island effect caused by climate change and urban expansion leads to an increase in underlying surface temperature, accelerated surface evaporation, local near surface convective activity, and changes in air moisture conditions, which were important reasons for the changes in rainfall characteristics in Kunming City.
Beacons, also known as “Fengsui”, represent a key manifestation of the central Chinese dynasties’ ability to exert control over frontier regions. The Keyakekuduke Beacon Site, located in Yuli County, Xinjiang, was an important military outpost in the border areas of China during Tang Dynasty. Excavations at this site have provided valuable artifacts, which offer significant insights into the military organization, institutional frameworks, and daily life of soldiers during various historical periods. These artifacts are crucial for reconstructing how the Tang Dynasty administered and defended its frontier regions. In this study, gas chromatography-mass spectrometry (GC-MS) was employed to analyze sterol compounds extracted from 9 coprolite samples discovered at the Keyakekuduke Beacon Site. Sterols, as lipid biomarkers, are useful indicators for identifying the presence and types of animals in archaeological contexts. The analysis of these sterols can reveal the diet, species, and potentially the role of animals in historical human activities. By comparing the sterol profiles obtained from the coprolites with modern herbivore fecal sterol compositions, the origins of the coprolites were examined in detail. The analytical results indicate the presence of sterol markers consistent with herbivores, specifically horses and sheep, as well as omnivores such as canines. This suggests that various animals played distinct and significant roles in the daily life and military operations at the site. Horses, given their mobility and endurance, likely served crucial roles in transportation and logistics, possibly carrying both personnel and supplies across the challenging terrain of the frontier. Their presence is consistent with the known military practices of the Tang Dynasty, where cavalry units were a vital component of military strategy, especially in remote border regions such as Xinjiang. Canines, on the other hand, were likely involved in security-related tasks. This study confirms that for sites with poorly preserved skeletal remains, using coprolite lipid records to determine the types of animals present in the site can help understand human utilization of animal resources. While for sites with well preserved skeletal remains, the conclusions drawn by the two independent methods can also be mutually confirmed.
Against the backdrop of global climate warming, the frequency and intensity of droughts are increasing, exerting significant stress on vegetation, reducing productivity, and consequently impacting the carbon cycle of entire ecosystems. The black soil region of Northeast China, one of the world’s 4 major black soil zones, is more sensitive to climate change than the global average, and as China’s most important grain repository, playing a crucial role in ensuring the country’s food security. Therefore, examining time lag effects and cumulative effects of drought on vegetation in the black soil region of Northeast China is of significant importance for promoting agricultural production, advancing environmental protection, and maintaining ecosystem services. This study focuses on the black soil region of Northeast China , utilizing the NIRv-GPP and SPEI datasets, and employs Pearson correlation analysis to explore time lag effects and cumulative effects of drought on different types of vegetation from 1982 to 2018. The results indicate that: 1) The SPEI and GPP in the black soil region of Northeast China exhibited fluctuating changes from 1982 to 2018, with general dicline from 1990 to 2010, followed by a significant upward trend after 2010; 2) Drought caused time lag effects on 99.4% of the vegetation in the Northeast black soil region, with lag time scales predominantly spanning 1-2 months and 9-10 months; as drought severity increased, the lag months increased while the intensity of time lag effects weakened; time lag effects were more significant on grasslands and forests; 3) 96.38% of the vegetation in the black soil region of Northeast China was affected by cumulative effects, with cumulative time scales concentrated within 2-3 months; as drought severity increased, the cumulative time scales increased while the intensity of cumulative effects weakened; cumulative effects were more significant on grasslands and croplands; 4) The dominant effects of drought on different vegetation types in the black soil region of Northeast China varied, with 79.88% of grasslands being primarily affected by cumulative effects, while 55.6% of croplands and 85.64% of forests were primarily affected by time lag effects.
