Spatial Autocorrelation Analysis of Genetic Structure of Zelkova schneideriana in Mailing Town,Guangxi

We analyzed the fine-scale spatial genetic structure of the individuals of Zelkova schneideriana , which were classified by age using the spatial autocorrelation method, to quantify spatial patterns of genetic variation within the population and to explore potential mechanisms that determine genetic variation in population. The spatial autocorrelation coefficient （ r ） at 13 distance classes was determined on the basis of both geographical distance and genetic distance matrix which was derived from co-dominant SSR data using GenAlEx software. The results showed that all the individuals of Z. schneideriana exhibited significantly positive spatial genetic structure at distance less than 40 m （the X -intercept was 53.568）, indicating that the average length of the smallest genetic patch for the same genotype clustering of the Z. schneideriana Mailing population was about 50 m. Limited seed dispersal is the main factor that leads to the spatial genetic variation within populations. The individuals in age Class II showed significantly positive spatial genetic structure at distance less than 30 m （the X -intercept was 47.882）, while the individuals in age Class I and age Class III showed no significant spatial genetic structure in any of the spatial distance classes. Z. schneideriana is a long-lived perennial plant; the self-thinning resulted from the cohort competition between individuals in the growing process may lead to this certain spatial structure in age Class III of Z. schneideriana population.

Spatial Analysis of the Aging Population and Socio-economic Factors of China:Global and Local Perspectives

Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China.In this study,we utilized data from national population census and statistical yearbooks in 2010 and 2020 to explore spatio-temporal patterns of aging population and its coupling correlations with socio-economic factors from both global and local perspectives.The results from Local Indicators of Spatial Association(LISA)uncover notable spatial disparities in aging population rates,with higher rates concentrated in the eastern regions and lower rates in the western areas of the Chinese mainland.The results from the global correlation analysis with the changes in aging population rates show significant positive correlations with government interventions and industrial structures,but negatively correlated with economic development,social consumption,and medical facilities.From a local perspective,a Geographically Weighted(GW)correlation analysis is employed to uncover local correlations between aging trends and socio-economic factors.The insights gained from this technique not only underscore the complexity and diversity of economic implications stemming from population aging,but also provide invaluable guidance for crafting region-specific economic policies tailored to various stages of population aging.

Measuring urban thermal environment from accessibility-based perspective:A case study in a populous city

Understanding the spatial interaction among residents,cooling service,and heat risk area in complex urban areas is conducive to developing targeted management.However,traditional urban thermal environment assessments typically relied on simple linear integration of associated indicators,often neglecting the spatial interaction effect.To explore the spatial interaction among the three elements,this study proposes an accessibility-based urban thermal environment assessment framework.Using Zhengzhou,a rapidly urbanizing city,as an example,remotely sensed images from three periods(2010,2015 and 2020)were applied to extract urban green space(UGS)and hot island area(HIA).An improved two-step floating catchment area(2SFCA)method and bivariate local Moran’s I were employed to explore whether residents’clustering locations are more likely to access cooling service or to be exposed to heat risk.The results demonstrate that the UGS in the city has been expanding,whereas the HIA shrank within the inner city in 2015 and then increased in 2020.Even though the urban thermal environment may have improved in the last decade,the spatial interaction among the residents,cooling service and heat risk area could be exacerbated.Spatial autocorrelation shows an increase in locations that are disadvantageous for resident congregation.Even when sufficient cooling services were provided,residents in these areas could still be exposed to high heat risk.The developed urban thermal environment framework provides a novel insight into the residents’heat risk exposure and cooling service accessibility,and the findings could assist urban planners in targeting the improvement of extra heat exposure risk locations.

Temporal and spatial responses of ecological resilience to climate change and human activities in the economic belt on the northern slope of the Tianshan Mountains, China

In the Anthropocene era,human activities have become increasingly complex and diversified.The natural ecosystems need higher ecological resilience to ensure regional sustainable development due to rapid urbanization and industrialization as well as other intensified human activities,especially in arid and semi-arid areas.In the study,we chose the economic belt on the northern slope of the Tianshan Mountains(EBNSTM)in Xinjiang Uygur Autonomous Region of China as a case study.By collecting geographic data and statistical data from 2010 and 2020,we constructed an ecological resilience assessment model based on the ecosystem habitat quality(EHQ),ecosystem landscape stability(ELS),and ecosystem service value(ESV).Further,we analyzed the temporal and spatial variation characteristics of ecological resilience in the EBNSTM from 2010 to 2020 by spatial autocorrelation analysis,and explored its responses to climate change and human activities using the geographically weighted regression(GWR)model.The results showed that the ecological resilience of the EBNSTM was at a low level and increased from 0.2732 to 0.2773 during 2010–2020.The spatial autocorrelation analysis of ecological resilience exhibited a spatial heterogeneity characteristic of"high in the western region and low in the eastern region",and the spatial clustering trend was enhanced during the study period.Desert,Gobi and rapidly urbanized areas showed low level of ecological resilience,and oasis and mountain areas exhibited high level of ecological resilience.Climate factors had an important impact on ecological resilience.Specifically,average annual temperature and annual precipitation were the key climate factors that improved ecological resilience,while average annual evapotranspiration was the main factor that blocked ecological resilience.Among the human activity factors,the distance from the main road showed a negative correlation with ecological resilience.Both night light index and PM2.5 concentration were negatively correlated with ecological resilience in the areas with better ecological conditions,whereas in the areas with poorer ecological conditions,the correlations were positive.The research findings could provide a scientific reference for protecting the ecological environment and promoting the harmony and stability of the human-land relationship in arid and semi-arid areas.

Spatiotemporal changes of eco-environmental quality based on remote sensing-based ecological index in the Hotan Oasis,Xinjiang

The rapid economic development that the Hotan Oasis in Xinjiang Uygur Autonomous Region,China has undergone in recent years may face some challenges in its ecological environment.Therefore,an analysis of the spatiotemporal changes in ecological environment of the Hotan Oasis is important for its sustainable development.First,we constructed an improved remote sensing-based ecological index(RSEI)in 1990,1995,2000,2005,2010,2015 and 2020 on the Google Earth Engine(GEE)platform and implemented change detection for their spatial distribution.Second,we performed a spatial autocorrelation analysis on RSEI distribution map and used land-use and land-cover change(LUCC)data to analyze the reasons of RSEI changes.Finally,we investigated the applicability of improved RSEI to arid area.The results showed that mean of RSEI rose from 0.41 to 0.50,showing a slight upward trend.During the 30-a period,2.66% of the regions improved significantly,10.74% improved moderately and 32.21% improved slightly,respectively.The global Moran's I were 0.891,0.889,0.847 and 0.777 for 1990,2000,2010 and 2020,respectively,and the local indicators of spatial autocorrelation(LISA)distribution map showed that the high-high cluster was mainly distributed in the central part of the Hotan Oasis,and the low-low cluster was mainly distributed in the outer edge of the oasis.RSEI at the periphery of the oasis changes from low to high with time,with the fragmentation of RSEI distribution within the oasis increasing.Its distribution and changes are predominantly driven by anthropologic factors,including the expansion of artificial oasis into the desert,the replacement of desert ecosystems by farmland ecosystems,and the increase in the distribution of impervious surfaces.The improved RSEI can reflect the eco-environmental quality effectively of the oasis in arid area with relatively high applicability.The high efficiency exhibited with this approach makes it convenient for rapid,high frequency and macroscopic monitoring of eco-environmental quality in study area.

Spatial Pattern Evolution and Influencing Factors of Cold Storage in China

Cold storage is the vital infrastructure of cold chain logistics. In this study, we analyzed the spatial pattern evolution characteristics, spatial autocorrelation and influencing factors of cold storage in China by using kernel density estimation(KDE), spatial autocorrelation analysis(SAA), and spatial error model(SEM). Results showed that: 1) the spatial distribution of cold storage in China is unbalanced, and has evolved from ‘one core’ to ‘one core and many spots’, that is, ‘one core’ refers to the Bohai Rim region mainly including Beijing, Tianjin, Hebei, Shandong and Liaoning regions, and ‘many spots’ mainly include the high-density areas such as Shanghai, Fuzhou, Guangzhou, Zhengzhou, Hefei, Wuhan, ürümqi. 2) The distribution of cold storage has significant global spatial autocorrelation and local spatial autocorrelation, and the ‘High-High’ cluster area is the most stable, mainly concentrated in the Bohai Rim;the ‘Low-Low’ cluster area is grouped in the southern China. 3) Economic development level, population density, traffic accessibility, temperature and land price, all affect the location choice of cold storage in varying degrees, while the impact of market demand on it is not explicit.

Temporal continuity of visual attention for future gaze prediction in immersive virtual reality

Background Eye tracking te chnology is receiving increased attention in the field of virtual reality.Specifically,future gaze prediction is crucial in pre-computation for many applications such as gaze-contingent rendering,advertisement placement,and content-based design.To explore future gaze prediction,it is necessary to analyze the temporal continuity of visual attention in immersive virtual reality.Methods In this paper,the concept of temporal continuity of visual attention is presented.Subsequently,an autocorrelation function method is proposed to evaluate the temporal continuity.Thereafter,the temporal continuity is analyzed in both free-viewing and task-oriented conditions.Results Specifically,in free-viewing conditions,the analysis of a free-viewing gaze dataset indicates that the temporal continuity performs well only within a short time interval.A task-oriented game scene condition was created and conducted to collect users'gaze data.An analysis of the collected gaze data finds the temporal continuity has a similar performance with that of the free-viewing conditions.Temporal continuity can be applied to future gaze prediction and if it is good,users'current gaze positions can be directly utilized to predict their gaze positions in the future.Conclusions The current gaze's future prediction performances are further evaluated in both free-viewing and task-oriented conditions and discover that the current gaze can be efficiently applied to the task of short-term future gaze prediction.The task of long-term gaze prediction still remains to be explored.

Ecosystem service values of gardens in the Yellow River Basin,China

Studies on the ecosystem service value(ESV)of gardens are critical for informing evidence-based land management practices based on an understanding of the local ecosystem.By analyzing equivalent value factors(EVFs),this paper evaluated the values of 11 ecosystem services of gardens in the Yellow River Basin of China in 2019.High-precision land use survey data were used to improve the accuracy of the land use classification,garden areas,and spatial distribution of the ESVs of gardens.The results showed that garden ecosystem generally had high ESVs,especially in terms of the ESV of food production,which is worthy of further research and application to the practice of land use planning and management.Specifically,the value of one standard EVF of ecosystem services in 2019 was 3587.04 CNY/(hm^(2)·a),and the ESV of food production of gardens was much higher than that of croplands.Garden ecosystem provided an ESV of 1348.66×10^(8)CNY/a in the Yellow River Basin.The areas with the most concentrated ESVs of gardens were located in four regions:downstream in the Shandong-Henan zone along the Yellow River,mid-stream in the Shanxi-Shaanxi zone along the Yellow River,the Weihe River Basin,and upstream in the Qinghai-Gansu-Ningxia-Inner Mongolia zone along the Yellow River.The spatial correlation of the ESVs in the basin was significant(global spatial autocorrelation index Moran's I=0.464),which implied that the characteristics of high ESVs adjacent to high ESVs and low ESVs adjacent to low ESVs are prominent.In the Yellow River Basin,the contribution of the ESVs of gardens to the local environment and economy varied across regions.We also put forward some suggestions for promoting the construction of ecological civilization in the Yellow River Basin.The findings of this study provide important contributions to the research of ecosystem service evaluation in the Yellow River Basin.

Characteristics of rural domestic sewage discharge and their driving mechanisms: evidence from the Northern Region, China

The traits of rural domestic sewage emission are unclear,negatively affecting rural domestic sewage treatment and sewage management.This study used data from the Second National Pollution Source Census Bulletin to establish a data set.The spatial distribution characteristics and main factors influencing rural sewage discharge in the Northern Region were studied using spatial autocorrelation analysis and structural equations.The findings demonstrated that(l)a significant Spearman correlation between drainage water volume(DwV),chemical oxygen demand(COD),ammonia nitrogen(NH_(3)-N),total nitrogen(TN),and total phosphorus(TP)and that the correlation coefficients between DWV and COD,NH,-N,TNand TP were 0.87**,1.0**,0.99**,0.99**,respectively;(2)rural sewage discharge showed spatial autocorrelation,and rural domestic sewage discharge in the districts and counties with an administration was significantly higher than in the surrounding areas;and(3)social development was the main driver rural domestic sewage changes(path coefficient was 0.407**),and the main factors influencing rural domestic sewage discharge were the urbanization rate,years of education,and population age structure.This study obtained the spatial variation law and clarified the main influencing factors of rural domestic sewage to provide data support and a theoretical basis for subsequent rural sewage collection and treatment.Use of the Inner Mongolia Autonomous Region in northern China as a typical case,provides a theoretical foundation for scientific decision-making on rural domestic sewage treatment at the national and regional levels and offers new perspectives for managing pollutants.

Spatial Matching Degree Between Education, Healthcare, Elderly Care Facilities and the Built Environment in Megacities Based on POI Data: A Case Study of Chengdu Central Urban Area

During rapid urbanization, megacities see disparities in the spatial distribution of basic public service facilities and the urban built environment. Current research on basic public service facilities focuses on equal spatial distribution, leading to the overlook of their match with the surrounding built environment. Based on a case study on education, healthcare, and elderly care facilities in Chengdu central urban area, this paper analyzes the spatial distribution of these facilities and the built environment, and examines their spatial matching degree using a bivariate spatial autocorrelation model. The findings reveal the following insights: firstly, education and healthcare facilities present a “one core and multi-center” spatial distribution pattern, with the city center serving as the core and suburban subdistricts acting as the multiple centers, while elderly care facilities present a core-edge distribution pattern in contrast;secondly, the built environment presents a core-edge radial distribution pattern, with the city center acting as the nucleus that connects suburban subdistricts;thirdly, the spatial matching degree between the facilities and the urban built environment from the city center outwards is characterized by high, low, medium, and high levels. Notably, a significant spatial mismatch is observed in urban-rural transitional zones. In light of these findings, the paper comes to a conclusion that during urbanization, the efforts to equalize basic public service facilities in the urban-rural transitional zones may lead to spatial mismatches, to which urban planners and managers should pay close attention.

Spatiotemporal patterns in urbanization efficiency within the Yangtze River Economic Belt between 2005 and 2014

The question of how to generate maximum socio-economic benefits while at the same time minimizing input from urban land resources lies at the core of regional ecological civilization construction. We apply stochastic frontier analysis （SFA） in this study to municipal input-output data for the period between 2005 and 2014 to evaluate the urbanization efficiency of 110 cities within the Yangtze River Economic Belt （YREB） and then further assess the spatial association characteristics of these values. The results of this study initially reveal that the urbanization efficiency of the YREB increased from 0.34 to 0.53 between 2005 and 2014, a significant growth at a cumulative rate of 54.07%. Data show that the efficiency growth rate of cities within the upper reaches of the Yangtze River has been faster than that of their counterparts in the middle and lower reaches, and that there is also a great deal of ad- ditional potential for growth in urbanization efficiency across the whole area. Secondly, results show that urbanization efficiency conforms to a ＂bar-like＂ distribution across the whole area, gradually decreasing from the east to the west. This trend highlights great intra-provincial differences, but also striking inter-provincial variation within the upper, middle, and lower reaches of the Yangtze River. The total urbanization efficiency of cities within the lower reaches of the river has been the highest, followed successively by those within the middle and upper reaches. Finally, values for Moran＇s / within this area remained higher than zero over the study period and have increased annually; this result indicates a positive spatial correlation between the urbanization efficiency of cities and annual increments in agglomeration level. Our use of the local indicators of spatial association （LISA） statistic has enabled us to quantify characteristics of ＂small agglomeration and large dispersion＂. Thus, ＂high- high＂ （H-H） agglomeration areas can be seen to have spread outwards from around Zhejiang Province and the city of Shanghai, while areas characterized by ＂low-low＂ （L-L） patterns are mainly concentrated in the north of Anhui Province and in Sichuan Province. The framework and results of this research are of considerable significance to our understanding of both land use sustainability and balanced development.

Geographic distribution of echinococcosis in Tibetan region of Sichuan Province,China

Background:Echinococcosis is a parasitic zoonosis caused by Echinococcus larvae parasitism causing high mortality.The Tibetan Region of Sichuan Province is a high prevalence area for echinococcosis in China.Understanding the geographic distribution pattern is necessary for precise control and prevention.In this study,a spatial analysis was conducted to explore the town-level epidemiology of echinococcosis in the Sichuan Tibetan Region and to provide guidance for formulating regional prevention and control strategies.Methods:The study was based on reported echinococcosis cases by the end of 2017,and each case was geo-coded at the town level.Spatial empirical Bayes smoothing and global spatial autocorrelation were used to detect the spatial distribution pattern.Spatial scan statistics were applied to examine local clusters.Results:The spatial distribution of echinococcosis in the Sichuan Tibetan Region was mapped at the town level in terms of the crude prevalence rate,excess hazard and spatial smoothed prevalence rate.The spatial distribution of echinococcosis was non-random and clustered with the significant global spatial autocorrelation(I=0.7301,P=0.001).Additionally,five significant spatial clusters were detected through the spatial scan statistic.Conclusions:There was evidence for the existence of significant echinococcosis clusters in the Tibetan Region of Sichuan Province,China.The results of this study may assist local health departments with developing better prevention strategies and prompt more efficient public health interventions.