Understanding the relative roles of local environmental effects and spatial effects on phytoplankton community is of essential importance to study the biogeography of them at regional scale. However, the determinants ...Understanding the relative roles of local environmental effects and spatial effects on phytoplankton community is of essential importance to study the biogeography of them at regional scale. However, the determinants that driving the biogeography of phytoplankton communities in the coastal area of northern Zhejiang still remained unclear. We surveyed phytoplankton community compositions in water columns associated with environmental and spatial influences across five subzones that geographically covering this region over four seasons. Diatoms and dinoflagellates were recorded as the main dominant groups and Coscinodiscus oculs-iridis, Coscinodiscus jonesianus, and Skeletonema costatum, were identified as the major abundant species existing in all seasons.Spatially structured environmental conditions, rather than pure spatial or environmental factors, substantially shaped the biogeography of phytoplankton community, with the former mainly comprised of water temperature,dissolved oxygen, phosphate, pH, and salinity, and the latter referring to a non-negligible factor. This study was the first integrated research that combining environmental filtering with spatial factors in structuring phytoplankton communities at a complete tempo-spatial scale. Our results may facilitate to the further study of harmful algal blooms early-warning in this region.展开更多
Objective: In this study, the influence and response relationship between the seasonal freezing-thawing process of soil and the spatial factor changes in the management and utilization of water resource processes were...Objective: In this study, the influence and response relationship between the seasonal freezing-thawing process of soil and the spatial factor changes in the management and utilization of water resource processes were explored. Methods: The monitoring equipment in this study was arranged at different altitudes, gradients, and slope directions, such as the typical forest sample area in the Dayekou Basin of the Qilian Mountains. The spatial variation characteristics of the seasonal freezing-thawing process of the soil were analyzed, and a regression model was established. Results: 1) The results of this study determined that the rate of the soil’s freezing increased with the altitude in a trend of volatility. However, the rate of the thawing of the frozen soil was found to have an opposite trend. The variation degree of the freezing-thawing process increased with the altitude in a trend of volatility. The end time of the approximate soil freezing with altitude increased in a volatility trend ahead of schedule. However, the opposite was observed in the thawing rate of the frozen soil;2) The rate of the soil’s freezing under the mosses of the spruce forest at an altitude of 3028 m was found to be the lowest. However, in the sub-alpine scrub forest at an altitude of 3300 m, a maximum in the spatial ordering was observed, with an average of 1.9 cm·d-1. The thawing rate of the frozen soil in scrub-spruce forest at an altitude of 3300 m was found to be minimal. However, in the sunny slope grassland at an altitude of 2946 m, a maximum in the spatial ordering was observed, with an average of 1.5 cm·d-1. In the spatial ordering of the variation degree of the process of freezing-thawing with an average of 1.2, the scrub-grassland at an altitude of 2518 m was found to be the lowest, and the scrub-spruce forest at an altitude of 3195 m was also low;3) The soil freezing began on approximately October 20th, and the rate of soil freezing gradually became reduced. The arrival time of the frozen soil of up to 150 cm in depth in sub-alpine scrub forest was first observed at an altitude of 3028 m. However, the scrub-spruce forest at an altitude of 3100 m did not become frozen until approximately January 12th on average. Then, the thawing rate of the frozen soil increased gradually. The end time of the thawing was earliest observed in the sunny slope grassland at an altitude of 2946 m. However, the scrub-spruce forest at an altitude of 3100 m was found to be the last to thaw, and averaged approximately July 27th. The average durations of the freezing and thawing of the soil were 77 and 121 days, respectively, and the average duration of the entire process of freezing-thawing was 199 days;4) This study’s established regression models of the duration time of frozen soil’s thaw, and the rate of frozen soil’s thaw, all passed the R test of goodness of fit, F test of variance, and t test. Conclusions: The characteristics of the seasonal freezing-thawing process of the soil with the spatial changes were seasonal. However, the characteristics under the different spatial factor influences were not the same.展开更多
Past studies on the adoption of integrated pest management (IPM), analyzed the significance of non-spatial factors (social, economic, institutional and management factors etc.) in influencing farmers’ decision to ado...Past studies on the adoption of integrated pest management (IPM), analyzed the significance of non-spatial factors (social, economic, institutional and management factors etc.) in influencing farmers’ decision to adopt IPM while the present study analyzed spatial factors in addition to these non-spatial factors to address the questions-i. Do the spatial factors significantly influence the farmers to adopt IPM? If yes, then to what extent they do affect IPM adoption? The data were collected from 331 vegetable farmers of Narsingdi district, Bangladesh, by conducting a household survey. Farmers’ nineteen characteristics under five broad groups, namely social, economic, institutional, management and spatial factors were analyzed. The result of the binary logistic regression model revealed that two spatial factors namely the distance of farmers’ house from the nearest market and the distance from agriculture office, along with some specific social, economic, institutional and management factors, significantly influenced the farmers’ to use IPM. It is also observed from the model that the role of spatial factors was important in influencing IPM adoption. However, with regard to the level of importance, their contribution was less than those of economic and institutional factors but more than those of social and management factors. The influences of these factors in practicing IPM are discussed individually as well as group based. The findings show significance in domestic policy making.展开更多
Understanding the spatial pattern of plant species diversity and the influencing factors has important implications for the conservation and management of ecosystem biodiversity. The transitional zone between biomes i...Understanding the spatial pattern of plant species diversity and the influencing factors has important implications for the conservation and management of ecosystem biodiversity. The transitional zone between biomes in desert ecosystems, however, has received little attention in that regard. In this study, we conducted a quantitative field survey （including 187 sampling plots） in a 40-km2 study area to determine the spatial pattern of plant species diversity and analyze the influencing factors in a Gobi Desert within the Heihe River Basin, Northwest China. A total of 42 plant species belonging to 16 families and 39 genera were recorded. Shrub and semi-shrub species generally represented the major part of the plant communities （covering 90% of the land surface）, while annual and perennial herbaceous species occupied a large proportion of the total recorded species （71%）. Patrick richness index （R）, Shannon-Wiener diversity index （H）, Simpson＇s dominance index （D）, and Pielou＇s evenness index （I） were all moderately spadaUy variable, and the variability increased with increasing sampling area. The semivariograms for R and H＇ were best fitted with Gaussian models while the semivariograms for D andJ were best fitted with exponential models. Nugget-to-still ratios indicated a moderate spatial autocorrelation for R, H＇, and D while a strong spatial autocorrelation was observed for J. The spatial patterns of R and H＇ were closely related to the geographic location within the study area, with lower values near the oasis and higher values near the mountains. However, there was an opposite trend for D. R, H＇, and D were significantly correlated with elevation, soil texture, bulk density, saturated hydraulic conductivity, and total porosity （P〈0.05）. Generally speaking, locations at higher elevations tended to have higher species richness and diversity and the higher elevations were characterized by higher values in sand and gravel contents, bulk density, and saturated hydraulic conductivity and also by lower values in total porosity. Furthermore, spatial variability of plant species diversity was dependent on the sampling area.展开更多
Soil bulk density is a basic but important physic soil property related to soil porosity,soil moisture and hydraulic conductivity,which is crucial to soil quality assessment and land use management.In this study,we ev...Soil bulk density is a basic but important physic soil property related to soil porosity,soil moisture and hydraulic conductivity,which is crucial to soil quality assessment and land use management.In this study,we evaluated the spatial variability of soil bulk density in the 0–20,20–40,40–60 and 60–100 cm layers as well as its affecting factors in Southwest China’s agricultural intensive area.Results indicated the mean value of surface soil bulk density(0–20 cm)was 1.26 g cm^(–3),significantly lower than that of subsoil(20–100 cm).No statistical difference existed among the subsoil with a mean soil bulk density of 1.54 g cm^(–3).Spatially,soil bulk density played a similar spatial pattern in soil profile,whereas obvious differences were found in details.The nugget effects for soil bulk density in the 0–20 and 20–40 cm layers were 27.22 and27.02%while 12.06 and 3.46%in the 40–60 and 60–100 cm layers,respectively,gradually decreasing in the soil profile,indicating that the spatial variability of soil bulk density above 40 cm was affected by structural and random factors while dominated by structural factors under 40 cm.Soil organic matter was the controlling factor on the spatial variability of soil bulk density in each layer.Land use and elevation were another two dominated factor controlling the spatial variability of soil bulk density in the 0–20 and 40–60 cm layers,respectively.Soil genus was one of the dominated factors controlling the spatial variability of soil bulk below 40 cm.展开更多
Based on the case study of peripheral urban areas in Beijing, this paper aims to identify the factors which will influence the spatial distribution of peri-urban recreation areas, by analyzing the collected data from ...Based on the case study of peripheral urban areas in Beijing, this paper aims to identify the factors which will influence the spatial distribution of peri-urban recreation areas, by analyzing the collected data from questionnaires, online survey, documentation and field investigations （2007）. In order to achieve sound information, relevant data from different management departments, owners and land-use types involved in the case study area are collected. A sampling database for peri-urban recreation areas in Beijing is established, and GIS spatial analyses as well as statistic analyses are applied. The result indicates that spatial distribution of recreation areas is majorly influenced by four factors, e.g. tourism attractions and environmental conditions, policy and spatial governance, consumption demand and preference, land price and availability. Tourism attractions and environmental conditions are dominant factors for public recreation areas. Commercial recreation areas are highly related with accessibility. Agricultural recreation areas are usually attached to special farmlands near large-scaled scenic areas. Meanwhile, recreational business clusters have appeared in sub- urbs influenced by mass recreation market growth. Controlled by the land price, commercial recreation areas are differentiated on their scales and developing intensity. Policy and spatial governance have made arrangements of recreation areas more balancing and more hu- man-oriented. A peri-urban recreation area model is therefore established on the basis of this analysis, which can guide urban planning and designing, land-use planning and recreation resource development.展开更多
Herbaceous plants are widely distributed on islands and where they exhibit spatial heterogeneity.Accurately identifying the impact factors that drive spatial heterogeneity can reveal typical island biodiversity patter...Herbaceous plants are widely distributed on islands and where they exhibit spatial heterogeneity.Accurately identifying the impact factors that drive spatial heterogeneity can reveal typical island biodiversity patterns.Five southern islands in the Miaodao Archipelago,North China were studied herein.The spatial distribution of herbaceous plant diversity on these islands was analyzed,and the impact factors and their degree of impact on spatial heterogeneity were identified using CCA ordination and ANOVA.The results reveal 114 herbaceous plant species,belonging to 94 genera from 34 families in the50 plots sampled.The total species numbers on different islands were significantly positively correlated with island area,and the average a diversity was correlated with human activities,while the(3 diversity among islands was more affected by island area than mutual distances.Spatial heterogeneity within islands indicated that the diversities were generally high in areas with higher altitude,slope,total nitrogen,total carbon,and canopy density,and lower moisture content,pH,total phosphorus,total potassium,and aspect.Among the environmental factors,pH,canopy density,total K,total P,moisture content,altitude,and slope had significant gross effects,but only canopy density exhibited a significant net effect.Terrain affected diversity by restricting plantation,plantation in turn influenced soil properties and the two together affected diversity.Therefore,plantation was ultimately the fundamental driving factor for spatial heterogeneity in herbaceous plant diversity on the five islands.展开更多
This research examines the distribution features of 4960 caves across Guizhou Province, while probing the relationship between the caves＇ spatial patterns and geographic elements. This study is based on hydrogeologic...This research examines the distribution features of 4960 caves across Guizhou Province, while probing the relationship between the caves＇ spatial patterns and geographic elements. This study is based on hydrogeological and topographic maps of Guizhou. ArcGIS software was used to process the adjacent index, spatial analysis, and coupling analysis of the caves altitude and longitude, as well as the rock properties, lithology, drainage and tec- tonic division of almost 5000 caves. Based on a point pattern analysis of Guizhou caves, the adjacent index is 0.53, and the coefficient of variation verified by Tyson polygon reached 72.469%. This figure reflects the clustered distribution pattern of the caves. Across the entire province, caves are divided into four concentrated areas and one weakly affected area. The four concentrated areas are Zunyi-Tongren, Bijie, Qianxinan-Liupanshui, and Gui- yang-Anshun-Qinan. The one weakly affected zone is Qiandongnan. The most concentrated among them is the Guiyang-Anshun-Qiannan area, which covers 24.67% of the total province area, and accounts for 36.63% of the total province＇s caves. Cave distribution in Guizhou is characterized as dense in the western part and sparse in the eastern part. Under this study background, the natural elements of formation, including lithology, structure, climate, hydrol- ogy, and altitude, and their effects on the distribution, number, and spatial pattern of cave development is analyzed.展开更多
Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China’s agricultural carbon emissions. Based on 23 k...Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China’s agricultural carbon emissions. Based on 23 kinds of major carbon emission sources including agricultural materials inputs, paddy ifeld, soil and livestock breeding, this paper ifrstly calculated agricultural carbon emissions from 1995 to 2010, as well as 31 provinces and cities in 2010 in China. We then made a decomposed analysis to the driving factors of carbon emissions with logarithmic mean Divisia index （LMDI） model. The results show：（1） The amount of agricultural carbon emissions is 291.1691 million t in 2010. Compared with 249.5239 million t in 1995, it increased by 16.69%, in which, agricultural materials inputs, paddy ifeld, soil, enteric fermentation, and manure management accounted for 33.59, 22.03, 7.46, 17.53 and 19.39%of total agricultural carbon emissions, respectively. Although the amount exist ups and downs, it shows an overall trend of cyclical rise; （2） There is an obvious difference among regions：the amount of agricultural carbon emissions from top ten zones account for 56.68%, while 9.84%from last 10 zones. The traditional agricultural provinces, especially the major crop production areas are the main source regions. Based on the differences of carbon emission rations, 31 provinces and cities are divided into ifve types, namely agricultural materials dominant type, paddy ifeld dominant type, enteric fermentation dominant type, composite factors dominant type and balanced type. The agricultural carbon emissions intensity in west of China is the highest, followed by the central region, and the east zone is the lowest; （3） Compared with 1995, efifciency, labor and structure factors cut down carbon emissions by 65.78, 27.51 and 3.19%, respectively;while economy factor increase carbon emissions by 113.16%.展开更多
Aim: To investigate the spatial and temporal expression of germ cell nuclear factor (GCNF) in mouse and rat epididymis during postnatal period. Methods: The epididymal sections from different postnatal days were stain...Aim: To investigate the spatial and temporal expression of germ cell nuclear factor (GCNF) in mouse and rat epididymis during postnatal period. Methods: The epididymal sections from different postnatal days were stained for GCNF by the indirect immunofluorescence technique and digital photographs were taken by a Carl Zeiss confocal microscope. Results: GCNF was first detected on day 12 in mouse epididymis and day 14 in rat epididymis. The highest expression of GCNF was observed on day 35 in both mouse and rat epididymis. In adults, GCNF exhibited a region-specific expression pattern, i.e., it was expressed predominantly in the initial segment, caput and proximal corpus of rat epididymis and was abundant in the proximal corpus of mouse epididymis. GCNF could be found in the nuclei of the principal, apical, narrow, clear and halo cells. Conclusion: GCNF may play an important role in epididymal differentiation and development and in sperm maturation.展开更多
Runoff generation is an important part of water retention service, and also plays an important role on soil and water retention. Under the background of the ecosystem degradation, which was caused by the vulnerable ka...Runoff generation is an important part of water retention service, and also plays an important role on soil and water retention. Under the background of the ecosystem degradation, which was caused by the vulnerable karst ecosystem combined with human activity, it is necessary to understand the spatial pattern and impact factors of runoff generation in the karst region. The typical karst peak-cluster depression basin was selected as the study area. And the calibrated and verified Soil and Water Assessment Tool (SWAT) was the main techniques to simulate the runoff generation in the typical karst basin. Further, the spatial variability of total/surface/groundwater runoff was analyzed along with the methods of gradient analysis and local regression. Results indicated that the law of spatial difference was obvious, and the total runoff coefficients were 70.0%. The groundwater runoff was rich, about 2–3 times the surface runoff. Terrain is a significant factor contributing to macroscopic control effect on the runoff service, where the total and groundwater runoff increased significantly with the rising elevation and slope. The distribution characteristics of vegetation have great effects on surface runoff. There were spatial differences between the forest land in the upstream and orchard land in the downstream, in turn the surface runoff presented a turning point due to the influence of vegetation. Moreover, the results of spatial overlay analysis showed that the highest value of total and groundwater runoff was distributed in the forest land. It is not only owing to the stronger soil water retention capacity of forest ecosystem, and geologic feature of rapid infiltration in this region, but also reflected the combining effects on the land cover types and topographical features. Overall, this study will promote the development and innovation of ecosystem services fields in the karst region, and further provide a theoretical foundation for ecosystem restoration and reconstruction.展开更多
Analysis of casualties due to landslides from 2000 to 2012 revealed that their spa- tial pattern was affected by terrain and other natural environmental factors, which resulted in a higher distribution of landslide ca...Analysis of casualties due to landslides from 2000 to 2012 revealed that their spa- tial pattern was affected by terrain and other natural environmental factors, which resulted in a higher distribution of landslide casualty events in southern China than in northern China. Hotspots of landslide-generated casualties were in the western Sichuan mountainous area and Yunnan-Guizhou Plateau region, southeast hilly area, northern part of the loess hilly area and Tianshan and Qilian Mountains. However, local distribution patterns indicated that land- slide casualty events were also influenced by economic activity factors. To quantitatively analyse the influence of natural environment and human-economic activity factors, the Probability Model for Landslide Casualty Events in China （LCEC） was built based on logistic regression analysis. The results showed that relative relief, GDP growth rate, mean annual precipitation, fault zones, and population density were positively correlated with casualties caused by landslides. Notably, GDP growth rate ranked only second to relative relief as the primary factors in the probability of casualties due to landslides. The occurrence probability of a landslide casualty event increased 2.706 times with a GDP growth rate increase of 2.72%. In contrast, vegetation coverage was negatively correlated with casualties caused by land- slides. The LCEC model was then applied to calculate the occurrence probability of landslide casualty events for each county in China. The results showed that there are 27 counties with high occurrence probability but zero casualty events. The 27 counties were divided into three categories： poverty-stricken counties, mineral-rich counties, and real-estate overexploited counties; these are key areas that should be emphasized in reducing landslide risk.展开更多
Flood disasters pose serious threats to human life and property worldwide.Exploring the spatial drivers of flood disasters on a macroscopic scale is of great significance for mitigating their impacts.This study propos...Flood disasters pose serious threats to human life and property worldwide.Exploring the spatial drivers of flood disasters on a macroscopic scale is of great significance for mitigating their impacts.This study proposes a comprehensive framework for integrating driving-factor optimization and interpretability,while considering spatial heterogeneity.In this framework,the Optimal Parameter-based Geographic Detector(OPGD),Recursive Feature Estimation(RFE),and Light Gradient Boosting Machine(LGBM)models were utilized to construct the OPGD–RFE–LGBM coupled model to identify the essential driving factors and simulate the spatial distribution of flood disasters.The SHapley Additive ExPlanation(SHAP)interpreter was employed to quantitatively explain the driving mechanisms behind the spatial distribution of flood disasters.Yunnan Province,a typical mountainous and plateau area in Southwest China,was selected to implement the proposed framework and conduct a case study.For this purpose,a flood disaster inventory of 7332 historical events was prepared,and 22 potential driving factors related to precipitation,surface environment,and human activity were initially selected.Results revealed that flood disasters in Yunnan Province exhibit high spatial heterogeneity,with geomorphic zoning accounting for 66.1%of the spatial variation in historical flood disasters.The OPGD–RFE–LGBM coupled model offers clear advantages over a single LGBM in identifying essential driving factors and quantitatively analyzing their impacts.Moreover,the simulation performance shows a slight improvement(a 6%average decrease in RMSE and an average increase of 1%in R2)even with reduced factor data.Factor explanatory analysis indicated that the combination of the essential driving factor sets varied across different subregions;nevertheless,precipitation-related factors,such as precipitation intensity index(SDII),wet days(R10MM),and 5-day maximum precipitation(RX5day),were the main driving factors controlling flood disasters.This study provides a quantitative analytical framework for the spatial drivers of flood disasters at large scales with significant heterogeneity,offering a reference for disaster management authorities in developing macro-strategies for disaster prevention.展开更多
Attended collection and delivery points are vital components of ‘last-mile logistics’.Based on point of interest(POI) data for Cainiao Stations and China Post stations in Changsha City, China, this paper provides a ...Attended collection and delivery points are vital components of ‘last-mile logistics’.Based on point of interest(POI) data for Cainiao Stations and China Post stations in Changsha City, China, this paper provides a detailed exploration of the basic features, spatial distribution, and location influencing factors of attended collection and delivery points.Specifically, analyses of the types, service objects and location distributions of the attended collection and delivery points alongside a discussion of their spatial pattern and influencing factors provides a reference for their general geographic layout and characteristics.The findings of this study indicate that: 1) The main mode of operation of attended collection and delivery points is franchises, with other modes of operation rely on supermarkets and other individual shop types.2) The main service targets of attended collection and delivery points are communities, schools, and businesses, followed by townships, enterprises, scenic spots, and administrative units.3) Approximately 77.44% of the attended collection and delivery points are located near the exits of service areas;others are situated in the centre of the service areas.For the Cainiao Stations, 80% are located within 125 m of the exit;for the China Post stations, 80% are located within 175 m of the exit.4) The spatial distribution of the attended collection and delivery points in Changsha is unbalanced, with ‘more centre and fewer surrounding’.The centre is an ‘inverted triangle’, and the edge is an ‘orphan’, showing a northwest-southeast orientation and symmetrical along the axis.The layout of the attended collection and delivery points forms three core areas, and the number of sites decreases with the distance from the core.5) The number and distribution of the attended collection and delivery points are strongly consistent with the regional economic development level, population, and roadway system traffic convenience.Most attended collection and delivery points are on residential, scientific and educational, and commercial and financial land.展开更多
Traditional Chinese villages are precious historical and cultural heritage and special tourist attractions. This study took 646 traditional villages that announced by the government in 2012 as an example to analyze th...Traditional Chinese villages are precious historical and cultural heritage and special tourist attractions. This study took 646 traditional villages that announced by the government in 2012 as an example to analyze the spatial structure of the traditional villages in China by means of GIS spatial analysis tools and quantitative analysis methods, namely the nearest distance index, geographic concentration index, Gini coefficient and Lorenz curve. The results showed that:(1) in terms of the spatial distribution density, the average density of traditional villages in 29 provinces(cities, districts) was 0.70/10,000 km^2, showing a large provincial gap;(2) as for the type of spatial distribution, there was a cluster distribution; and(3) on the balance of spatial distribution, there were many differences between the east and west, and the distribution was extremely uneven. Based on the above, this study explored the reasons for the uneven spatial distribution, including the natural environment, population migration, the level of traffic accessibility, the degree of government attention, and the level of economic development.展开更多
Rift Valley Fever (RVF) is an emerging, mosquito-borne disease with serious economical and negative implications on human and animal health. This study was conducted to verify the factors which influenced the spatial ...Rift Valley Fever (RVF) is an emerging, mosquito-borne disease with serious economical and negative implications on human and animal health. This study was conducted to verify the factors which influenced the spatial pattern of Rift Valley Fever occurrence and identified the high risk areas for the occurrence of the disease at Sinner State, Sudan. The normalized difference vegetation index (NDVI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite and rainfall data in addition to the point data of RVF clinical cases in humans were used in this study. In order to identify the RVF high risk areas, remote sensing data and rainfall data were integrated in a GIS with other information including, soil type, water body, DEM (Digital Elevation Model), and animal routes and analyzed using Spatial Analysis tools. The information on clinical cases was used for verification. The Normalized Difference Vegetation Index (NDVI) was used to describe vegetation patterns of the study area by calculating the mean NDVI. The results of the study showed that, RVF risk increased with the increase in vegetation cover (high NDVI values), and increase in rainfall, which both provided suitable conditions for disease vectors breeding and a good indicator for RVF epizootics. The study concluded that, identification of high risk area for RVF disease improved the understanding of the spatial distribution of the disease and helped in locating the areas where disease was likely to be endemic and therefore preparedness measures should be taken. The identification represents the first step of prospective predictions of RVF outbreaks and provides a baseline for improved early warning, control, response planning, and mitigation. Further detailed studies are recommended in this domain.展开更多
The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions.Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet ...The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions.Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet Plateau as a case study.The present study firstly investigates the change of permafrost moisture in different slope positions and depths. Based on this investigation, this article attempts to investigate the spatial variability of permafrost moisture and identifies the key influence factors in different terrain conditions. The method of classification and regression tree(CART) is adopted to identify the main controlling factors influencing the soil moisture movement. The relationships between soil moisture and environmental factors are revealed by the use of the method of canonical correspondence analysis(CCA). The results show that: 1) Due to the terrain slope and the freezing-thawing process, the horizontal flow weakens in the freezing period. The vertical migration of the soil moisture movement strengthens. It will lead to that the soil-moisture content in the up-slope is higher than that in the down-slope. The conclusion is contrary during the melting period. 2) Elevation, soil texture, soil temperature and vegetation coverage are the main environmental factors which affect the slopepermafrost soil-moisture. 3) Slope, elevation and vegetation coverage are the main factors that affect the slope-permafrost soil-moisture at the shallow depth of 0-20 cm. It is complex at the middle and lower depth.展开更多
Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research h...Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research has been conducted on this subject. In this study, we used generalized additive models(GAMs) to explore the influence of spatial-temporal and environmental factors on CPUEs of species aggregated, small yellow croaker(Larimichthys polyactis), and octopus(Octopus variabilis) based on logbooks investigations conducted at 4 stations in an alongshore area of Haizhou Bay from 2011 to 2012. The results showed that all CPUEs exhibited significant spatial-temporal differences at various scales. Aggregated CPUE was high when the sea surface temperature(SST) was 15-18℃ and 20-23℃, which was mainly determined by life history traits of the octopus and small yellow croaker(optimal SSTs 14-17℃ and 19-24℃, respectively). Chlorophyll-a concentration had significant influences on the aggregated, small yellow croaker and octopus CPUEs at optimal ranges of 3.8-6.2 mg m^(-3), 4.2-4.8 mg m^(-3) and 4.5-5.5 mg m^(-3), respectively. Flow through the net had positive relationships with CPUEs. The approximate logarithmic trends in regression curves had a critical point of 2.5 Mm^3 d^(-1), which was the dividing point that differentiated whether the major factor affecting CPUEs was the flow velocity or the fishery resource. Our results from this study will help guide fishery production and improve catch rate of set-net fishing in Haizhou Bay.展开更多
Soil organic matter(SOM) is an important parameter related to soil nutrient and miscellaneous ecosystem services. This paper attempts to improve the performance of traditional partial least square regression(PLSR) mod...Soil organic matter(SOM) is an important parameter related to soil nutrient and miscellaneous ecosystem services. This paper attempts to improve the performance of traditional partial least square regression(PLSR) model by considering the spatial autocorrelation and soil forming factors. Surface soil samples(n = 180) were collected from Honghu City located in the middle of Jianghan Plain, China. The visible and near infrared(VNIR) spectra and six environmental factors(elevation, land use types, roughness, relief amplitude, enhanced vegetation index, and land surface water index) were used as the auxiliary variables to construct the multiple linear regression(MLR), PLSR and geographically weighted regression(GWR) models. Results showed that: 1) the VNIR spectra can increase about 39.62% prediction accuracy than the environmental factors in predicting SOM; 2) the comprehensive variables of VNIR spectra and the environmental factors can improve about 5.78% and 44.90% relative to soil spectral models and soil environmental models, respectively; 3) the spatial model(GWR) can improve about 3.28% accuracy than MLR and PLSR. Our results suggest that the combination of spectral reflectance and the environmental variables can be used as the suitable auxiliary variables in predicting SOM, and GWR is a promising model for predicting soil properties.展开更多
To develop and protect traditional villages reasonably, this paper applied Arc GIS Spatial Analyst Tools to analyze spatial distribution and infl uence factors of 101 traditional villages in Hunan Province. The resear...To develop and protect traditional villages reasonably, this paper applied Arc GIS Spatial Analyst Tools to analyze spatial distribution and infl uence factors of 101 traditional villages in Hunan Province. The research showed the agglomerate distribution of traditional villages in Hunan; from the city scale, distribution of traditional villages was concentrated mainly in West Hunan Tujia Nationality Autonomous Prefecture, Chenzhou, Yongzhou, Huaihua and Shaoyang; concentrated distribution of traditional villages in the fi ve major geographic regions showed poor equilibrium, West Hunan had the most concentrated traditional villages, and South Hunan has the second most; relatively closed regional environment, perilous hills, inconvenient transportation, and underdeveloped social economy contributed to the protection of traditional villages, and they were all signifi cant infl uence factors for the distribution of traditional villages in Hunan.展开更多
基金Ecological Restoration Cost Evaluation in Archipelago Ecosystems:A Case Study in Putuo,Zhoushan Archipelago,East China Sea.
文摘Understanding the relative roles of local environmental effects and spatial effects on phytoplankton community is of essential importance to study the biogeography of them at regional scale. However, the determinants that driving the biogeography of phytoplankton communities in the coastal area of northern Zhejiang still remained unclear. We surveyed phytoplankton community compositions in water columns associated with environmental and spatial influences across five subzones that geographically covering this region over four seasons. Diatoms and dinoflagellates were recorded as the main dominant groups and Coscinodiscus oculs-iridis, Coscinodiscus jonesianus, and Skeletonema costatum, were identified as the major abundant species existing in all seasons.Spatially structured environmental conditions, rather than pure spatial or environmental factors, substantially shaped the biogeography of phytoplankton community, with the former mainly comprised of water temperature,dissolved oxygen, phosphate, pH, and salinity, and the latter referring to a non-negligible factor. This study was the first integrated research that combining environmental filtering with spatial factors in structuring phytoplankton communities at a complete tempo-spatial scale. Our results may facilitate to the further study of harmful algal blooms early-warning in this region.
文摘Objective: In this study, the influence and response relationship between the seasonal freezing-thawing process of soil and the spatial factor changes in the management and utilization of water resource processes were explored. Methods: The monitoring equipment in this study was arranged at different altitudes, gradients, and slope directions, such as the typical forest sample area in the Dayekou Basin of the Qilian Mountains. The spatial variation characteristics of the seasonal freezing-thawing process of the soil were analyzed, and a regression model was established. Results: 1) The results of this study determined that the rate of the soil’s freezing increased with the altitude in a trend of volatility. However, the rate of the thawing of the frozen soil was found to have an opposite trend. The variation degree of the freezing-thawing process increased with the altitude in a trend of volatility. The end time of the approximate soil freezing with altitude increased in a volatility trend ahead of schedule. However, the opposite was observed in the thawing rate of the frozen soil;2) The rate of the soil’s freezing under the mosses of the spruce forest at an altitude of 3028 m was found to be the lowest. However, in the sub-alpine scrub forest at an altitude of 3300 m, a maximum in the spatial ordering was observed, with an average of 1.9 cm·d-1. The thawing rate of the frozen soil in scrub-spruce forest at an altitude of 3300 m was found to be minimal. However, in the sunny slope grassland at an altitude of 2946 m, a maximum in the spatial ordering was observed, with an average of 1.5 cm·d-1. In the spatial ordering of the variation degree of the process of freezing-thawing with an average of 1.2, the scrub-grassland at an altitude of 2518 m was found to be the lowest, and the scrub-spruce forest at an altitude of 3195 m was also low;3) The soil freezing began on approximately October 20th, and the rate of soil freezing gradually became reduced. The arrival time of the frozen soil of up to 150 cm in depth in sub-alpine scrub forest was first observed at an altitude of 3028 m. However, the scrub-spruce forest at an altitude of 3100 m did not become frozen until approximately January 12th on average. Then, the thawing rate of the frozen soil increased gradually. The end time of the thawing was earliest observed in the sunny slope grassland at an altitude of 2946 m. However, the scrub-spruce forest at an altitude of 3100 m was found to be the last to thaw, and averaged approximately July 27th. The average durations of the freezing and thawing of the soil were 77 and 121 days, respectively, and the average duration of the entire process of freezing-thawing was 199 days;4) This study’s established regression models of the duration time of frozen soil’s thaw, and the rate of frozen soil’s thaw, all passed the R test of goodness of fit, F test of variance, and t test. Conclusions: The characteristics of the seasonal freezing-thawing process of the soil with the spatial changes were seasonal. However, the characteristics under the different spatial factor influences were not the same.
文摘Past studies on the adoption of integrated pest management (IPM), analyzed the significance of non-spatial factors (social, economic, institutional and management factors etc.) in influencing farmers’ decision to adopt IPM while the present study analyzed spatial factors in addition to these non-spatial factors to address the questions-i. Do the spatial factors significantly influence the farmers to adopt IPM? If yes, then to what extent they do affect IPM adoption? The data were collected from 331 vegetable farmers of Narsingdi district, Bangladesh, by conducting a household survey. Farmers’ nineteen characteristics under five broad groups, namely social, economic, institutional, management and spatial factors were analyzed. The result of the binary logistic regression model revealed that two spatial factors namely the distance of farmers’ house from the nearest market and the distance from agriculture office, along with some specific social, economic, institutional and management factors, significantly influenced the farmers’ to use IPM. It is also observed from the model that the role of spatial factors was important in influencing IPM adoption. However, with regard to the level of importance, their contribution was less than those of economic and institutional factors but more than those of social and management factors. The influences of these factors in practicing IPM are discussed individually as well as group based. The findings show significance in domestic policy making.
基金financially supported by the National Natural Science Foundation of China(91025018)the Action Plan for West Development Project of Chinese Academy of Sciences(KZCX2-XB3-13)
文摘Understanding the spatial pattern of plant species diversity and the influencing factors has important implications for the conservation and management of ecosystem biodiversity. The transitional zone between biomes in desert ecosystems, however, has received little attention in that regard. In this study, we conducted a quantitative field survey （including 187 sampling plots） in a 40-km2 study area to determine the spatial pattern of plant species diversity and analyze the influencing factors in a Gobi Desert within the Heihe River Basin, Northwest China. A total of 42 plant species belonging to 16 families and 39 genera were recorded. Shrub and semi-shrub species generally represented the major part of the plant communities （covering 90% of the land surface）, while annual and perennial herbaceous species occupied a large proportion of the total recorded species （71%）. Patrick richness index （R）, Shannon-Wiener diversity index （H）, Simpson＇s dominance index （D）, and Pielou＇s evenness index （I） were all moderately spadaUy variable, and the variability increased with increasing sampling area. The semivariograms for R and H＇ were best fitted with Gaussian models while the semivariograms for D andJ were best fitted with exponential models. Nugget-to-still ratios indicated a moderate spatial autocorrelation for R, H＇, and D while a strong spatial autocorrelation was observed for J. The spatial patterns of R and H＇ were closely related to the geographic location within the study area, with lower values near the oasis and higher values near the mountains. However, there was an opposite trend for D. R, H＇, and D were significantly correlated with elevation, soil texture, bulk density, saturated hydraulic conductivity, and total porosity （P〈0.05）. Generally speaking, locations at higher elevations tended to have higher species richness and diversity and the higher elevations were characterized by higher values in sand and gravel contents, bulk density, and saturated hydraulic conductivity and also by lower values in total porosity. Furthermore, spatial variability of plant species diversity was dependent on the sampling area.
基金supported by the National Natural Science Foundation of China (4120124)the Science Fund of the Education Department of Sichuan Province, China (16ZB0048)
文摘Soil bulk density is a basic but important physic soil property related to soil porosity,soil moisture and hydraulic conductivity,which is crucial to soil quality assessment and land use management.In this study,we evaluated the spatial variability of soil bulk density in the 0–20,20–40,40–60 and 60–100 cm layers as well as its affecting factors in Southwest China’s agricultural intensive area.Results indicated the mean value of surface soil bulk density(0–20 cm)was 1.26 g cm^(–3),significantly lower than that of subsoil(20–100 cm).No statistical difference existed among the subsoil with a mean soil bulk density of 1.54 g cm^(–3).Spatially,soil bulk density played a similar spatial pattern in soil profile,whereas obvious differences were found in details.The nugget effects for soil bulk density in the 0–20 and 20–40 cm layers were 27.22 and27.02%while 12.06 and 3.46%in the 40–60 and 60–100 cm layers,respectively,gradually decreasing in the soil profile,indicating that the spatial variability of soil bulk density above 40 cm was affected by structural and random factors while dominated by structural factors under 40 cm.Soil organic matter was the controlling factor on the spatial variability of soil bulk density in each layer.Land use and elevation were another two dominated factor controlling the spatial variability of soil bulk density in the 0–20 and 40–60 cm layers,respectively.Soil genus was one of the dominated factors controlling the spatial variability of soil bulk below 40 cm.
基金Knowledge Innovation Project of the Chinese Academy of Sciences National Natural Science Foundation of China, No.40571059
文摘Based on the case study of peripheral urban areas in Beijing, this paper aims to identify the factors which will influence the spatial distribution of peri-urban recreation areas, by analyzing the collected data from questionnaires, online survey, documentation and field investigations （2007）. In order to achieve sound information, relevant data from different management departments, owners and land-use types involved in the case study area are collected. A sampling database for peri-urban recreation areas in Beijing is established, and GIS spatial analyses as well as statistic analyses are applied. The result indicates that spatial distribution of recreation areas is majorly influenced by four factors, e.g. tourism attractions and environmental conditions, policy and spatial governance, consumption demand and preference, land price and availability. Tourism attractions and environmental conditions are dominant factors for public recreation areas. Commercial recreation areas are highly related with accessibility. Agricultural recreation areas are usually attached to special farmlands near large-scaled scenic areas. Meanwhile, recreational business clusters have appeared in sub- urbs influenced by mass recreation market growth. Controlled by the land price, commercial recreation areas are differentiated on their scales and developing intensity. Policy and spatial governance have made arrangements of recreation areas more balancing and more hu- man-oriented. A peri-urban recreation area model is therefore established on the basis of this analysis, which can guide urban planning and designing, land-use planning and recreation resource development.
基金Supported by the National Special Fund for Basic Science and Technology of China(No.2012FY112500)the Public Science and Technology Research Funds Projects of Ocean in China(Nos.201305009,201505012)the Special Fund of Chinese Central Government for Basic Scientific Research Operations in Commonweal Research Institutes(No.FIO2015G13)
文摘Herbaceous plants are widely distributed on islands and where they exhibit spatial heterogeneity.Accurately identifying the impact factors that drive spatial heterogeneity can reveal typical island biodiversity patterns.Five southern islands in the Miaodao Archipelago,North China were studied herein.The spatial distribution of herbaceous plant diversity on these islands was analyzed,and the impact factors and their degree of impact on spatial heterogeneity were identified using CCA ordination and ANOVA.The results reveal 114 herbaceous plant species,belonging to 94 genera from 34 families in the50 plots sampled.The total species numbers on different islands were significantly positively correlated with island area,and the average a diversity was correlated with human activities,while the(3 diversity among islands was more affected by island area than mutual distances.Spatial heterogeneity within islands indicated that the diversities were generally high in areas with higher altitude,slope,total nitrogen,total carbon,and canopy density,and lower moisture content,pH,total phosphorus,total potassium,and aspect.Among the environmental factors,pH,canopy density,total K,total P,moisture content,altitude,and slope had significant gross effects,but only canopy density exhibited a significant net effect.Terrain affected diversity by restricting plantation,plantation in turn influenced soil properties and the two together affected diversity.Therefore,plantation was ultimately the fundamental driving factor for spatial heterogeneity in herbaceous plant diversity on the five islands.
基金National Natural Science Foundation of China, No.41361081 High-level Innovative Talents Cultivation Program of Guizhou Province （Qian Ke He SY [201615674） Project of Innovation Program for Postgraduate Education of Guizhou Province, No.[2016]04
文摘This research examines the distribution features of 4960 caves across Guizhou Province, while probing the relationship between the caves＇ spatial patterns and geographic elements. This study is based on hydrogeological and topographic maps of Guizhou. ArcGIS software was used to process the adjacent index, spatial analysis, and coupling analysis of the caves altitude and longitude, as well as the rock properties, lithology, drainage and tec- tonic division of almost 5000 caves. Based on a point pattern analysis of Guizhou caves, the adjacent index is 0.53, and the coefficient of variation verified by Tyson polygon reached 72.469%. This figure reflects the clustered distribution pattern of the caves. Across the entire province, caves are divided into four concentrated areas and one weakly affected area. The four concentrated areas are Zunyi-Tongren, Bijie, Qianxinan-Liupanshui, and Gui- yang-Anshun-Qinan. The one weakly affected zone is Qiandongnan. The most concentrated among them is the Guiyang-Anshun-Qiannan area, which covers 24.67% of the total province area, and accounts for 36.63% of the total province＇s caves. Cave distribution in Guizhou is characterized as dense in the western part and sparse in the eastern part. Under this study background, the natural elements of formation, including lithology, structure, climate, hydrol- ogy, and altitude, and their effects on the distribution, number, and spatial pattern of cave development is analyzed.
基金supported by the National Natural Science Foundation of China (71273105)the Fundamental Research Funds for the Central Universities,China (2013YB12)
文摘Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China’s agricultural carbon emissions. Based on 23 kinds of major carbon emission sources including agricultural materials inputs, paddy ifeld, soil and livestock breeding, this paper ifrstly calculated agricultural carbon emissions from 1995 to 2010, as well as 31 provinces and cities in 2010 in China. We then made a decomposed analysis to the driving factors of carbon emissions with logarithmic mean Divisia index （LMDI） model. The results show：（1） The amount of agricultural carbon emissions is 291.1691 million t in 2010. Compared with 249.5239 million t in 1995, it increased by 16.69%, in which, agricultural materials inputs, paddy ifeld, soil, enteric fermentation, and manure management accounted for 33.59, 22.03, 7.46, 17.53 and 19.39%of total agricultural carbon emissions, respectively. Although the amount exist ups and downs, it shows an overall trend of cyclical rise; （2） There is an obvious difference among regions：the amount of agricultural carbon emissions from top ten zones account for 56.68%, while 9.84%from last 10 zones. The traditional agricultural provinces, especially the major crop production areas are the main source regions. Based on the differences of carbon emission rations, 31 provinces and cities are divided into ifve types, namely agricultural materials dominant type, paddy ifeld dominant type, enteric fermentation dominant type, composite factors dominant type and balanced type. The agricultural carbon emissions intensity in west of China is the highest, followed by the central region, and the east zone is the lowest; （3） Compared with 1995, efifciency, labor and structure factors cut down carbon emissions by 65.78, 27.51 and 3.19%, respectively;while economy factor increase carbon emissions by 113.16%.
文摘Aim: To investigate the spatial and temporal expression of germ cell nuclear factor (GCNF) in mouse and rat epididymis during postnatal period. Methods: The epididymal sections from different postnatal days were stained for GCNF by the indirect immunofluorescence technique and digital photographs were taken by a Carl Zeiss confocal microscope. Results: GCNF was first detected on day 12 in mouse epididymis and day 14 in rat epididymis. The highest expression of GCNF was observed on day 35 in both mouse and rat epididymis. In adults, GCNF exhibited a region-specific expression pattern, i.e., it was expressed predominantly in the initial segment, caput and proximal corpus of rat epididymis and was abundant in the proximal corpus of mouse epididymis. GCNF could be found in the nuclei of the principal, apical, narrow, clear and halo cells. Conclusion: GCNF may play an important role in epididymal differentiation and development and in sperm maturation.
基金National Basic Research Program of China,No.2015CB452702National Natural Science Foundation of China,No.41671098,No.41530749+1 种基金"Strategic Priority Research Program" of the Chinese Academy of Sciences,No.XDA20020202Open Foundation of Laboratory for Earth Surface Processes(LESP)Ministry of Education
文摘Runoff generation is an important part of water retention service, and also plays an important role on soil and water retention. Under the background of the ecosystem degradation, which was caused by the vulnerable karst ecosystem combined with human activity, it is necessary to understand the spatial pattern and impact factors of runoff generation in the karst region. The typical karst peak-cluster depression basin was selected as the study area. And the calibrated and verified Soil and Water Assessment Tool (SWAT) was the main techniques to simulate the runoff generation in the typical karst basin. Further, the spatial variability of total/surface/groundwater runoff was analyzed along with the methods of gradient analysis and local regression. Results indicated that the law of spatial difference was obvious, and the total runoff coefficients were 70.0%. The groundwater runoff was rich, about 2–3 times the surface runoff. Terrain is a significant factor contributing to macroscopic control effect on the runoff service, where the total and groundwater runoff increased significantly with the rising elevation and slope. The distribution characteristics of vegetation have great effects on surface runoff. There were spatial differences between the forest land in the upstream and orchard land in the downstream, in turn the surface runoff presented a turning point due to the influence of vegetation. Moreover, the results of spatial overlay analysis showed that the highest value of total and groundwater runoff was distributed in the forest land. It is not only owing to the stronger soil water retention capacity of forest ecosystem, and geologic feature of rapid infiltration in this region, but also reflected the combining effects on the land cover types and topographical features. Overall, this study will promote the development and innovation of ecosystem services fields in the karst region, and further provide a theoretical foundation for ecosystem restoration and reconstruction.
基金National Key Research and Development Program Project,No.2017YFC1502505,No.2016YFA0602403National Natural Science Foundation of China,No.41271544
文摘Analysis of casualties due to landslides from 2000 to 2012 revealed that their spa- tial pattern was affected by terrain and other natural environmental factors, which resulted in a higher distribution of landslide casualty events in southern China than in northern China. Hotspots of landslide-generated casualties were in the western Sichuan mountainous area and Yunnan-Guizhou Plateau region, southeast hilly area, northern part of the loess hilly area and Tianshan and Qilian Mountains. However, local distribution patterns indicated that land- slide casualty events were also influenced by economic activity factors. To quantitatively analyse the influence of natural environment and human-economic activity factors, the Probability Model for Landslide Casualty Events in China （LCEC） was built based on logistic regression analysis. The results showed that relative relief, GDP growth rate, mean annual precipitation, fault zones, and population density were positively correlated with casualties caused by landslides. Notably, GDP growth rate ranked only second to relative relief as the primary factors in the probability of casualties due to landslides. The occurrence probability of a landslide casualty event increased 2.706 times with a GDP growth rate increase of 2.72%. In contrast, vegetation coverage was negatively correlated with casualties caused by land- slides. The LCEC model was then applied to calculate the occurrence probability of landslide casualty events for each county in China. The results showed that there are 27 counties with high occurrence probability but zero casualty events. The 27 counties were divided into three categories： poverty-stricken counties, mineral-rich counties, and real-estate overexploited counties; these are key areas that should be emphasized in reducing landslide risk.
基金the National Key Research and Development Program of China(Grant No.2022YFF1302405)the Yunnan Province Key Research and Development Program(Grant No.202203AC100005)+1 种基金the National Natural Science Foundation of China(Grant No.42061005,42067033)Applied Basic Research Programs of Yunnan Province(Grant No.202101AT070110,202001BB050073).
文摘Flood disasters pose serious threats to human life and property worldwide.Exploring the spatial drivers of flood disasters on a macroscopic scale is of great significance for mitigating their impacts.This study proposes a comprehensive framework for integrating driving-factor optimization and interpretability,while considering spatial heterogeneity.In this framework,the Optimal Parameter-based Geographic Detector(OPGD),Recursive Feature Estimation(RFE),and Light Gradient Boosting Machine(LGBM)models were utilized to construct the OPGD–RFE–LGBM coupled model to identify the essential driving factors and simulate the spatial distribution of flood disasters.The SHapley Additive ExPlanation(SHAP)interpreter was employed to quantitatively explain the driving mechanisms behind the spatial distribution of flood disasters.Yunnan Province,a typical mountainous and plateau area in Southwest China,was selected to implement the proposed framework and conduct a case study.For this purpose,a flood disaster inventory of 7332 historical events was prepared,and 22 potential driving factors related to precipitation,surface environment,and human activity were initially selected.Results revealed that flood disasters in Yunnan Province exhibit high spatial heterogeneity,with geomorphic zoning accounting for 66.1%of the spatial variation in historical flood disasters.The OPGD–RFE–LGBM coupled model offers clear advantages over a single LGBM in identifying essential driving factors and quantitatively analyzing their impacts.Moreover,the simulation performance shows a slight improvement(a 6%average decrease in RMSE and an average increase of 1%in R2)even with reduced factor data.Factor explanatory analysis indicated that the combination of the essential driving factor sets varied across different subregions;nevertheless,precipitation-related factors,such as precipitation intensity index(SDII),wet days(R10MM),and 5-day maximum precipitation(RX5day),were the main driving factors controlling flood disasters.This study provides a quantitative analytical framework for the spatial drivers of flood disasters at large scales with significant heterogeneity,offering a reference for disaster management authorities in developing macro-strategies for disaster prevention.
基金Under the auspices of the Tang Scholar Program of Northwest University(No.2016)
文摘Attended collection and delivery points are vital components of ‘last-mile logistics’.Based on point of interest(POI) data for Cainiao Stations and China Post stations in Changsha City, China, this paper provides a detailed exploration of the basic features, spatial distribution, and location influencing factors of attended collection and delivery points.Specifically, analyses of the types, service objects and location distributions of the attended collection and delivery points alongside a discussion of their spatial pattern and influencing factors provides a reference for their general geographic layout and characteristics.The findings of this study indicate that: 1) The main mode of operation of attended collection and delivery points is franchises, with other modes of operation rely on supermarkets and other individual shop types.2) The main service targets of attended collection and delivery points are communities, schools, and businesses, followed by townships, enterprises, scenic spots, and administrative units.3) Approximately 77.44% of the attended collection and delivery points are located near the exits of service areas;others are situated in the centre of the service areas.For the Cainiao Stations, 80% are located within 125 m of the exit;for the China Post stations, 80% are located within 175 m of the exit.4) The spatial distribution of the attended collection and delivery points in Changsha is unbalanced, with ‘more centre and fewer surrounding’.The centre is an ‘inverted triangle’, and the edge is an ‘orphan’, showing a northwest-southeast orientation and symmetrical along the axis.The layout of the attended collection and delivery points forms three core areas, and the number of sites decreases with the distance from the core.5) The number and distribution of the attended collection and delivery points are strongly consistent with the regional economic development level, population, and roadway system traffic convenience.Most attended collection and delivery points are on residential, scientific and educational, and commercial and financial land.
文摘Traditional Chinese villages are precious historical and cultural heritage and special tourist attractions. This study took 646 traditional villages that announced by the government in 2012 as an example to analyze the spatial structure of the traditional villages in China by means of GIS spatial analysis tools and quantitative analysis methods, namely the nearest distance index, geographic concentration index, Gini coefficient and Lorenz curve. The results showed that:(1) in terms of the spatial distribution density, the average density of traditional villages in 29 provinces(cities, districts) was 0.70/10,000 km^2, showing a large provincial gap;(2) as for the type of spatial distribution, there was a cluster distribution; and(3) on the balance of spatial distribution, there were many differences between the east and west, and the distribution was extremely uneven. Based on the above, this study explored the reasons for the uneven spatial distribution, including the natural environment, population migration, the level of traffic accessibility, the degree of government attention, and the level of economic development.
文摘Rift Valley Fever (RVF) is an emerging, mosquito-borne disease with serious economical and negative implications on human and animal health. This study was conducted to verify the factors which influenced the spatial pattern of Rift Valley Fever occurrence and identified the high risk areas for the occurrence of the disease at Sinner State, Sudan. The normalized difference vegetation index (NDVI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite and rainfall data in addition to the point data of RVF clinical cases in humans were used in this study. In order to identify the RVF high risk areas, remote sensing data and rainfall data were integrated in a GIS with other information including, soil type, water body, DEM (Digital Elevation Model), and animal routes and analyzed using Spatial Analysis tools. The information on clinical cases was used for verification. The Normalized Difference Vegetation Index (NDVI) was used to describe vegetation patterns of the study area by calculating the mean NDVI. The results of the study showed that, RVF risk increased with the increase in vegetation cover (high NDVI values), and increase in rainfall, which both provided suitable conditions for disease vectors breeding and a good indicator for RVF epizootics. The study concluded that, identification of high risk area for RVF disease improved the understanding of the spatial distribution of the disease and helped in locating the areas where disease was likely to be endemic and therefore preparedness measures should be taken. The identification represents the first step of prospective predictions of RVF outbreaks and provides a baseline for improved early warning, control, response planning, and mitigation. Further detailed studies are recommended in this domain.
基金supported by the National Natural Science Foundation of China(Grant No.41501079 and 91647103)Funded by State Key Laboratory of Frozen Soil Engineering(Grant No.SKLFSE-ZQ-43)+1 种基金the Chinese Academy of Sciences(CAS)Key Research Program(Grant No.KZZD-EW-13)the Foundation for Excellent Youth Scholars of NIEER,CAS
文摘The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions.Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet Plateau as a case study.The present study firstly investigates the change of permafrost moisture in different slope positions and depths. Based on this investigation, this article attempts to investigate the spatial variability of permafrost moisture and identifies the key influence factors in different terrain conditions. The method of classification and regression tree(CART) is adopted to identify the main controlling factors influencing the soil moisture movement. The relationships between soil moisture and environmental factors are revealed by the use of the method of canonical correspondence analysis(CCA). The results show that: 1) Due to the terrain slope and the freezing-thawing process, the horizontal flow weakens in the freezing period. The vertical migration of the soil moisture movement strengthens. It will lead to that the soil-moisture content in the up-slope is higher than that in the down-slope. The conclusion is contrary during the melting period. 2) Elevation, soil texture, soil temperature and vegetation coverage are the main environmental factors which affect the slopepermafrost soil-moisture. 3) Slope, elevation and vegetation coverage are the main factors that affect the slope-permafrost soil-moisture at the shallow depth of 0-20 cm. It is complex at the middle and lower depth.
基金funded through the Special Fund for Agro-Scientific Research in the Public Interestthe Special Public Welfare Industry (agriculture) Research-Research and Demonstration of Fisheries Fishing Technology and Fishing Gear (No. 201203018)the National Natural Science Foundation of China (No. 31402350)
文摘Set-nets are common alongshore fishing gear used in Haizhou Bay, which rely on flow to catch fish. The catch per unit effort(CPUE) of set-net is affected by spatial-temporal and environmental factors but no research has been conducted on this subject. In this study, we used generalized additive models(GAMs) to explore the influence of spatial-temporal and environmental factors on CPUEs of species aggregated, small yellow croaker(Larimichthys polyactis), and octopus(Octopus variabilis) based on logbooks investigations conducted at 4 stations in an alongshore area of Haizhou Bay from 2011 to 2012. The results showed that all CPUEs exhibited significant spatial-temporal differences at various scales. Aggregated CPUE was high when the sea surface temperature(SST) was 15-18℃ and 20-23℃, which was mainly determined by life history traits of the octopus and small yellow croaker(optimal SSTs 14-17℃ and 19-24℃, respectively). Chlorophyll-a concentration had significant influences on the aggregated, small yellow croaker and octopus CPUEs at optimal ranges of 3.8-6.2 mg m^(-3), 4.2-4.8 mg m^(-3) and 4.5-5.5 mg m^(-3), respectively. Flow through the net had positive relationships with CPUEs. The approximate logarithmic trends in regression curves had a critical point of 2.5 Mm^3 d^(-1), which was the dividing point that differentiated whether the major factor affecting CPUEs was the flow velocity or the fishery resource. Our results from this study will help guide fishery production and improve catch rate of set-net fishing in Haizhou Bay.
基金Under the auspices of the Natural Science Foundation of Hubei(No.2018CFB372)the Fundamental Research Funds for the Central Universities(No.2662016QD032)+2 种基金the Key Laboratory of Aquatic Plants and Watershed Ecology of Chinese Academy of Sciences(No.Y852721s04)the Chinese National Natural Science Foundation(No.41371227)the National Undergraduate Innovation and Entrepreneurship Training Program(No.201810504023,201810504030)
文摘Soil organic matter(SOM) is an important parameter related to soil nutrient and miscellaneous ecosystem services. This paper attempts to improve the performance of traditional partial least square regression(PLSR) model by considering the spatial autocorrelation and soil forming factors. Surface soil samples(n = 180) were collected from Honghu City located in the middle of Jianghan Plain, China. The visible and near infrared(VNIR) spectra and six environmental factors(elevation, land use types, roughness, relief amplitude, enhanced vegetation index, and land surface water index) were used as the auxiliary variables to construct the multiple linear regression(MLR), PLSR and geographically weighted regression(GWR) models. Results showed that: 1) the VNIR spectra can increase about 39.62% prediction accuracy than the environmental factors in predicting SOM; 2) the comprehensive variables of VNIR spectra and the environmental factors can improve about 5.78% and 44.90% relative to soil spectral models and soil environmental models, respectively; 3) the spatial model(GWR) can improve about 3.28% accuracy than MLR and PLSR. Our results suggest that the combination of spectral reflectance and the environmental variables can be used as the suitable auxiliary variables in predicting SOM, and GWR is a promising model for predicting soil properties.
基金Sponsored by National Science Foundation of China(41571161,41271167)Innovative Research Group Fund of Hunan Provincial Natural Science Foundation(12JJ7003)China Postdoctoral Fund Project(2014M560611)
文摘To develop and protect traditional villages reasonably, this paper applied Arc GIS Spatial Analyst Tools to analyze spatial distribution and infl uence factors of 101 traditional villages in Hunan Province. The research showed the agglomerate distribution of traditional villages in Hunan; from the city scale, distribution of traditional villages was concentrated mainly in West Hunan Tujia Nationality Autonomous Prefecture, Chenzhou, Yongzhou, Huaihua and Shaoyang; concentrated distribution of traditional villages in the fi ve major geographic regions showed poor equilibrium, West Hunan had the most concentrated traditional villages, and South Hunan has the second most; relatively closed regional environment, perilous hills, inconvenient transportation, and underdeveloped social economy contributed to the protection of traditional villages, and they were all signifi cant infl uence factors for the distribution of traditional villages in Hunan.
