The leaf area index(LAI) is a critical biophysical variable that describes canopy geometric structures and growth conditions.It is also an important input parameter for climate,energy and carbon cycle models.The scali...The leaf area index(LAI) is a critical biophysical variable that describes canopy geometric structures and growth conditions.It is also an important input parameter for climate,energy and carbon cycle models.The scaling effect of the LAI has always been of concern.Considering the effects of the clumping indices on the BRDF models of discrete canopies,an effective LAI is defined.The effective LAI has the same function of describing the leaf density as does the traditional LAI.Therefore,our study was based on the effective LAI.The spatial scaling effect of discrete canopies significantly differed from that of continuous canopies.Based on the directional second-derivative method of effective LAI retrieval,the mechanism responsible for the spatial scaling effect of the discrete-canopy LAI is discussed and a scaling transformation formula for the effective LAI is suggested in this paper.Theoretical analysis shows that the mean values of effective LAIs retrieved from high-resolution pixels were always equal to or larger than the effective LAIs retrieved from corresponding coarse-resolution pixels.Both the conclusions and the scaling transformation formula were validated with airborne hyperspectral remote sensing imagery obtained in Huailai County,Zhangjiakou,Hebei Province,China.The scaling transformation formula agreed well with the effective LAI retrieved from hyperspectral remote sensing imagery.展开更多
Spatial scaling laws of velocity kinetic energy spectra for the compressible turbulence flow and the density-weighted counterparts are formulated in terms of the wavenumber, dissipation rate, and Mach number by using ...Spatial scaling laws of velocity kinetic energy spectra for the compressible turbulence flow and the density-weighted counterparts are formulated in terms of the wavenumber, dissipation rate, and Mach number by using a dimensional analysis. We apply the Barenblatt＇s incomplete similarity theory to both kinetic and density-weighted energy spectra. It shows that, within the initial subrange, both energy spectra approach the -5/3 and -2 power laws of the wavenumber when the Mach number tends to unity and infinity, respectively.展开更多
Landscape fragmentation is generally viewed as an indicator of environmental stresses or risks,but the fragmentation intensity assessment also depends on the scale of data and the definition of spatial unit.This study...Landscape fragmentation is generally viewed as an indicator of environmental stresses or risks,but the fragmentation intensity assessment also depends on the scale of data and the definition of spatial unit.This study aimed to explore the scale-dependence of forest fragmentation intensity along a moisture gradient in Yinshan Mountain of North China,and to estimate environmental sensitivity of forest fragmentation in this semi-arid landscape.We developed an automatic classification algorithm using simple linear iterative clustering(SLIC)and Gaussian mixture model(GMM),and extracted tree canopy patches from Google Earth images(GEI),with an accuracy of 89.2%in the study area.Then we convert the tree canopy patches to forest category according to definition of forest that tree density greater than 10%,and compared it with forest categories from global land use datasets,FROM-GLC10 and GlobeLand30,with spatial resolutions of 10 m and 30 m,respectively.We found that the FROM-GLC10 and GlobeLand30 datasets underestimated the forest area in Yinshan Mountain by 16.88%and 21.06%,respectively;and the ratio of open forest(OF,10%<tree coverage<40%)to closed forest(CF,tree coverage>40%)areas in the underestimated part was 2:1.The underestimations concentrated in warmer and drier areas occupied mostly by large coverage of OFs with severely fragmented canopies.Fragmentation intensity of canopies positively correlated with spring temperature while negatively correlated with summer precipitation and terrain slope.When summer precipitation was less than 300 mm or spring temperature higher than 4℃,canopy fragmentation intensity rose drastically,while the forest area percentage kept stable.Our study suggested that the spatial configuration,e.g.,sparseness,is more sensitive to drought stress than area percentage.This highlights the importance of data resolution and proper fragmentation measurements for forest patterns and environmental interpretation,which is the base of reliable ecosystem predictions with regard to the future climate scenarios.展开更多
This study aims to verify the concept of niches at multiple spatial scales in plant communities.To this end,we analyzed the niche characteristic of Rhododendron dauricum plant communities in Northeast China at three s...This study aims to verify the concept of niches at multiple spatial scales in plant communities.To this end,we analyzed the niche characteristic of Rhododendron dauricum plant communities in Northeast China at three spatial scales.At the local scale,we calculated the Importance Value(IV)of species in five communities in the north of the Da Hinggan Mountains.At the intermediate scale,we examined five communities in their entirety,calculated the niche breadth of the species,and integrated niche overlap and interspecific association to analyze interspecific relationships.Further,the generalized additive model(GAM)was used to analyze the impact of topography and soil factors on niche characteristics.At the regional scale,we analyzed the geographical distribution of dominant species of R.dauricum plant communities in Northeast China and used principal component analysis(PCA)to analyze the impact of geographical and climate factors on species distribution.The results show that at the local scale,the IV of the species in each community varies widely.At the intermediate scale,species with a wide niche breadth tend to have a high value for IV.Larix gmelinii,Betula platyphylla,R.dauricum,Ledum palustre,and Vaccinium vitis-idaea had a relatively wide niche breadth and a high niche overlap,and the interspecific associations were almost all positive.Elevation and soil nutrients were the most dominant environmental factors.At the regional scale,species with a wide niche breadth tend to have a wide range of distribution,and temperature and precipitation were the most dominant environmental factors.This study suggests that the niche characteristics at three scales are both related and different.Niche characteristics at the local scale were various and labile,and niche characteristics at the intermediate and regional scales were relatively regular.These results show some degree of consistency with previous studies from an evolutionary perspective.The action mechanisms of these communities are related to differences in the dominant environmental factors.In addition,the integration of niche overlap and interspecific association determine interspecific relationships more accurately.展开更多
The important role of spatial scale in exploring the geography of poverty as well as its policy implications has been noticed but with limited knowledge. To improve such limited understanding, we mainly investigated t...The important role of spatial scale in exploring the geography of poverty as well as its policy implications has been noticed but with limited knowledge. To improve such limited understanding, we mainly investigated the spatial patterns and influencing factors of rural poverty(indicated by poor population and poverty incidence) at three different administrative levels in the Liupan Mountain Region, one of the fourteen poorest regions in China. Our results show that from a global perspective, poor areas are clustered significantly at the county-, township-, and village-level, and more greatly at a lower level. Locally, there is spatial mismatch among poverty hotspots detected not only by the same indicator at different levels but also by different indicators at the same level. A scale effect can be found in the influencing factors of rural poverty. That is, the number of significant factors increases, but the degree of their association with poverty incidence decreases at a lower level. Such scale effect indicates that poverty incidence at lower levels may be affected by more complex factors, including not only the new local ones but also the already appeared non-local ones at higher levels. However, the natural conditions tend to play a scale-independent role to poverty incidence. In response to such scale-dependent patterns and factors, anti-poverty policies can be 1) a multilevel monitoring system to reduce incomplete or even misleading single-level information and understanding; 2) the village-based targeting strategy to increase the targeting efficiency and alleviate the mentioned spatial mismatch; 3) more flexible strategies responding to the local impoverishing factors, and 4) different task emphasises for multilevel policymakers to achieve the common goal of poverty reduction.展开更多
Precipitation and associated cloud hydrometeors have large temporal and spatial variability, which makes accurate quantitative precipitation forecasting difficult. Thus, dependence of accurate precipitation and associ...Precipitation and associated cloud hydrometeors have large temporal and spatial variability, which makes accurate quantitative precipitation forecasting difficult. Thus, dependence of accurate precipitation and associated cloud simulation on temporal and spatial scales becomes an important issue. We report a cloud- resolving modeling analysis on this issue by comparing the control experiment with experiments perturbed by initial temperature, water vapor, and cloud conditions. The simulation is considered to be accurate only if the root-mean-squared difference between the perturbation experiments and the control experiment is smaller than the standard deviation. The analysis may suggest that accurate precipitation and cloud simulations cannot be obtained on both fine temporal and spatial scales simultaneously, which limits quanti- tative precipitation forecasting. The accurate simulation of water vapor convergence could lead to accurate precipitation and cloud simulations on daily time scales, but it may not be beneficial to precipitation and cloud simulations on hourly time scales due to the dominance of cloud processes.展开更多
Temporal and spatial scales play important roles in fishery ecology,and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution.The objective of this study is to evaluate the ro...Temporal and spatial scales play important roles in fishery ecology,and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution.The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling,with the western stock of winter-spring cohort of neon flying squid （Ornmastrephes bartramii） in the northwest Pacific Ocean as an example.In this study,the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature （SST） from remote sensing during August to October of 2003-2008 were used.We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales （0.5°,1 ° and 2°）,four longitude scales （0.5°,1°,2° and 4°）,and three temporal scales （week,fortnight,and month）.The coefficients of variation （CV） of the weekly,biweekly and monthly suitability index （SI） were compared to determine which temporal and spatial scales of SI model are more precise.This study shows that the optimal temporal and spatial scales with the lowest CV are month,and 0.5° latitude and 0.5° longitude for O.bartramii in the northwest Pacific Ocean.This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts.We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.展开更多
The drastic decline in groundwater table and many other detrimental effects in meeting irrigation demand, and the projected population growth have force to evaluate consumptive use or evapo-transpiration (ET), the rat...The drastic decline in groundwater table and many other detrimental effects in meeting irrigation demand, and the projected population growth have force to evaluate consumptive use or evapo-transpiration (ET), the rate of liquid water transformation to vapor from open water, bare soil, and vegetation, which determines the irrigation demand. As underscored in the literature, Pen-man-Monteith method which is based on aerodynamic and energy balance method is widely used and accepted as the method of estimation of ET. However, the estimation of ET is oftentimes carried out using meteorological data from climate stations. Therefore, such estimation of ET may vary spatially and thus there exists a need to estimate ET spatially at different spatial or grid scales/resolutions. Thus, in this paper, a spatial tool that can geographically encompass all the best available climate datasets to produce ET at different spatial scales is developed. The spatial tool is developed as a Python toolbox in ArcGIS using Python, an open source programming language, and the ArcPy site-package of ArcGIS. The developed spatial tool is demonstrated using the meteorological data from Automated Weather Data Network in Nebraska in 2010.展开更多
During the past two decades, the exhibition industry in China has been developing rapidly and has become an important part of the modern service industry, particularly the agglomeration characteristics of exhibition e...During the past two decades, the exhibition industry in China has been developing rapidly and has become an important part of the modern service industry, particularly the agglomeration characteristics of exhibition enterprises highlighted on the regional scale. Although the development of theoretical research on the western exhibition industry has taken place over time, the spatial perspective has not been at the centre of attention so far. This paper aims to fill this gap and report on the agglomeration characteristics of exhibition enterprises and their influential factors. Based on data about exhibition enterprises in the Pearl River Delta(PRD) during 1991–2013, using the Ripley K function analysis and kernel density estimation, this research identifies that: 1) the exhibition enterprise on the regional scale is significantly characterized by spatial agglomeration, and the agglomeration density and scale are continuously increasing; 2) the spatial pattern of agglomeration has developed from a single-center to multi-center form. Meanwhile, this paper profiles the factors influencing the spatial agglomeration of exhibition enterprises by selecting the panel data of nine cities in the PRD in 1999, 2002, 2006 and 2013. The results show that market capacity, urban informatization level and exhibition venues significantly influence the location choice of exhibition enterprises. Among them, the market capacity is a variable that exerts a far greater impact than other factors do.展开更多
Scale is the range or measurement unit of the characteristics of natural or human ontology in the temporal or spatial dimension and is widely used in daily life and the study of various disciplines.Scale effect pertai...Scale is the range or measurement unit of the characteristics of natural or human ontology in the temporal or spatial dimension and is widely used in daily life and the study of various disciplines.Scale effect pertains to certain laws and characteristics that can only be reflected on a specific scale,so choosing the appropriate scale remains the basic premise of scientific research.The concept of the urban spatial system is complex and has the characteristics of scale dependence,and the selection of an appropriate spatial scale is important for the accurate estimation and description of urban issues.In this paper,we discuss spatial scale in urban research using cases that primarily come from the Chinese experience,provide some examples that demonstrate the importance of appropriate scale in urban research,including urban shrinkage,and highlight problems in spatial research.Ultimately,we suggest that scale consciousness should be the basic consciousness required in empirical research.展开更多
Data from Goddard cumulus ensemble model experiment are used to study temporal and spatial scale dependence of tropical rainfall separation analysis based on cloud budget during Tropical Ocean Global Atmosphere Couple...Data from Goddard cumulus ensemble model experiment are used to study temporal and spatial scale dependence of tropical rainfall separation analysis based on cloud budget during Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment （TOGA COARE）. The analysis shows that the calculations of model domain mean or time-mean grid-scale mean simulation data overestimate the rain rates of the two rainfall types associated with net condensation but they severely underestimate the rain rate of the rainfall type associated with net evaporation and hydrometeor convergence.展开更多
The need to allocate the existing water in a sustainable manner, even with the projected population growth, has made to assess the consumptive use or evapotranspiration (ET), which determines the irrigation demand. As...The need to allocate the existing water in a sustainable manner, even with the projected population growth, has made to assess the consumptive use or evapotranspiration (ET), which determines the irrigation demand. As underscored in the literature, Penman-Monteith method which is a combination of aerodynamic and energy balance method is widely used and accepted as the method of estimation of ET. However, the application of Penman-Monteith relies on many climate parameters such as relative humidity, solar radiation, temperature, and wind speed. Therefore, there exists a need to determine the parameters that are most sensitive and correlated with dependent variable (i.e., ET), to strengthen the knowledge base. However, the sensitivity of ET using Penman-Monteith is oftentimes estimated using meteorological data from climate stations. Such estimation of sensitivity may vary spatially and thus there exists a need to estimate sensitivity of ET spatially. Thus, in this paper, based on One-AT-A-Time (OAT) method, a spatial sensitivity tool that can geographically encompass all the best available climate datasets to produce ET and its sensitivity at different spatial scales is developed. The spatial tool is developed as a Python toolbox in ArcGIS using Python, an open source programming language, and the ArcPy site-package of ArcGIS. The developed spatial tool is demonstrated using the meteorological data from Automated Weather Data Network in Nebraska in 2010. To summarize the outcome of the sensitivity analysis using OAT method, sensitivity indices are developed for each raster cell. The demonstration of the tool shows that, among the considered parameters, the computed ET using Penman-Monteith is highly sensitive to solar radiation followed by temperature for the state of Nebraska, as depicted by the sensitivity index. The computed sensitivity index of wind speed and the relative humidity are not that significant compared to the sensitivity index of solar radiation and temperature.展开更多
Abstract The chlorophyll-a concentration data obtained through remote sensing are important for a wide range of scientific concerns.However,cloud cover and limitations of inversion algorithms of chlorophyll-a concentr...Abstract The chlorophyll-a concentration data obtained through remote sensing are important for a wide range of scientific concerns.However,cloud cover and limitations of inversion algorithms of chlorophyll-a concentration lead to data loss,which critically limits studying the mechanism of spatial-temporal patterns of chlorophyll-a concentration in response to marine environment changes.If the commonly used operational chlorophyll-a concentration products can offer the best data coverage frequency,highest accuracy,best applicability,and greatest robustness at different scales remains debatable to date.Therefore,in the present study,four commonly used operational multi-sensor multi-algorithm fusion products were compared and subjected to validation based on statistical analysis using the available data measured at multiple spatial and temporal scales.The experimental results revealed that in terms of spatial distribution,the chlorophyll-a concentration products generated by averaging method(Chl1-AV/AVW)and GSM model(Chl1-GSM)presented a relatively high data coverage frequency in Case Ⅰ water regions and extremely low or no data coverage frequency in the estuarine coastal zone regions and inland water regions,the chlorophyll-a concentration products generated by the Neural Network algorithm(Chl2)presented high data coverage frequency in the estuarine coastal zone Case 2 water regions.The chlorophyll-a concentration products generated by the OC5 algorithm(ChlOC5)presented high data coverage frequency in Case I water regions and the turbid Case Ⅱ water regions.In terms of absolute precision,the Chl1-AV/AVW and Chl1-GSM chlorophyll-a concentration products performed better in Class I water regions,and the Chl2 product performed well only in Case Ⅱ estuarine coastal zones,while presenting large errors in absolute precision in the Case Ⅰ water regions.The ChlOC5 product presented a higher precision in Case Ⅰ and Case Ⅱ water regions,with a better and more stable performance in both regions compared to the other products.展开更多
Understanding how spatial scale influences commonly-observed effects of climate and soil texture on soil organic carbon （SOC） storage is important for accurately estimating the SOC pool at different scales. The rela...Understanding how spatial scale influences commonly-observed effects of climate and soil texture on soil organic carbon （SOC） storage is important for accurately estimating the SOC pool at different scales. The relationships among climate factors, soil texture and SOC density at the regional, provincial, city, and county scales were evaluated at both the soil surface （0-20 cm） and throughout the soil profile （0-100 cm） in the Northeast China uplands. We examined 1 022 profiles obtained from the Second National Soil Survey of China. The results indicated that the relationships between climate factors and SOC density generally weakened with decreasing spatial scale. The provincial scale was optimal to assess the relationship between climate factors and SOC density because regional differences among provinces were covered up at the regional scale. However, the relationship between soil texture and SOC density had no obvious trend with increasing scale and changed with temperature. There were great differences in the impacts of climate factors and soil texture on SOC density at different scales. Climate factors had a larger effect on SOC density than soil texture at the regional scale. Similar trends were seen in Heilongjiang and eastern Inner Mongolia at the provincial scale. But, soil texture had a greater effect on SOC density compared with climate factors in Jilin and Liaoning. At the city and county scales, the influence of soil texture on SOC density was more important than climate factors.展开更多
Ecological patterns and processes in dune ecosystems have been a research focus in recent years, however the information on how dune stabilization influences the spatial scale dependence of plant diversity is still la...Ecological patterns and processes in dune ecosystems have been a research focus in recent years, however the information on how dune stabilization influences the spatial scale dependence of plant diversity is still lacking. In this study, we measured the plant species richness, soil properties and altitude across four spatial scales （1, 10, 100 and 1,000 m2） at three different dune stabilization stages （mobile dune, semi-fixed dune and fixed dune） in Horqin Sandy Land, Northern China. We also examined the relationships between plant species richness, community composition and environmental factors along the gradient of dune stabilization. Our results showed that plant species richness increased with the increase of spatial scales in each dune stabilization stage, as well as with the increase of dune stabilization degrees. Canonical correspondence analysis （CCA） showed that plant distribu- tions in the processes of dune stabilization were determined by the combined environmental gradient in relation to soil organic carbon （SOC）, total nitrogen （TN）, carbon/nitrogen （C/N）, pH, electrical conductivity （EC）, soil water content （SWC）, fine sand （FS）, very fine sand （VFS）, silt and clay （SC）, and altitude. Plant species richness was significantly and positively correlated to SOC and TN in mobile dune, and significantly and positively correlated to SOC, TN, C/N, VFS and SC in semi-fixed dune. However, no significant correlation between plant species richness and environmental factors was observed in fixed dune. In addition, plant species richness in different dune stabili- zation stages was also determined by the combined gradient of soil properties and altitude. These results suggest that plant species richness has obvious scale dependence along the gradient of dune stabilization. Soil resources depending on dune habitats and environmental gradients caused by dune stabilization are important factors to de- termine the scale dependence of species diversity in sand dune ecosystems.展开更多
A new soil moisture dataset from direct gravimetric measurements within the top 50-cm soil layers at 178 soil moisture stations in China covering the period 1981 1998 are used to study the long-term and seasonal trend...A new soil moisture dataset from direct gravimetric measurements within the top 50-cm soil layers at 178 soil moisture stations in China covering the period 1981 1998 are used to study the long-term and seasonal trends of soil moisture variations, as well as estimate the temporal and spatial scales of soil moisture for different soil layers. Additional datasets of precipitation and temperature difference between land surface and air （TDSA） are analyzed to gain further insight into the changes of soil moisture. There are increasing trends for the top 10 cm, but decreasing trends for the top 50 cm of soil layers in most regions. Trends in precipitation appear to dominantly influence trends in soil moisture in both cases. Seasonal variation of soil moisture is mainly controlled by precipitation and evaporation, and in some regions can be affected by snow cover in winter. Timescales of soil moisture variation are roughly 1-3 months and increase with soil depth. Further influences of TDSA and precipitation on soil moisture in surface layers, rather than in deeper layers, cause this phenomenon. Seasonal variations of temporal scales for soil moisture are region-dependent and consistent in both layer depths. Spatial scales of soil moisture range from 200-600 km, with topography also having an affect on these. Spatial scales of soil moisture in plains are larger than in mountainous areas. In the former, the spatial scale of soil moisture follows the spatial patterns of precipitation and evaporation, whereas in the latter, the spatial scale is controlled by topography.展开更多
In order to better explore the maintenance mechanisms of biodiversity, data collected from a 40-ha undisturbed Pinus forest were applied to the Individual Species-Area Relationship model(ISAR) to determine distributio...In order to better explore the maintenance mechanisms of biodiversity, data collected from a 40-ha undisturbed Pinus forest were applied to the Individual Species-Area Relationship model(ISAR) to determine distribution patterns for species richness. The ecological processes influencing species abundance distribution patterns were assessed by applying the same data set to five models: a LogNormal Model(LNM), a Broken Stick Model(BSM), a Zipf Model(ZM), a Niche Preemption Model(NPM), and a Neutral Model(NM). Each of the five models was used at six different sampling scales(10 m×10 m, 20 m×20 m, 40 m×40 m, 60 m×60 m, 80 m×80 m, and 100 m×100 m). Model outputs showed that:(1) Accumulators and neutral species strongly influenced species diversity, but the relative importance of the two types of species varied across spatial scales.(2) Distribution patterns of species abundance were best explained by the NPM at small scales(10 m-20 m), whereas the NM was the best fit model at large spatial scales.(3) Species richness and abundance distribution patterns appeared to be driven by similar ecological processes. At small scales, the niche theory could be applied to describe species richness and abundance, while at larger scales the neutral theory was more applicable.展开更多
We examined the scale impacts on spatial hot and cold spots of CPUE for Ommastrephes bartramii in the northwest Pacific Ocean. The original fishery data were tessellated to 18 spatial scales from 5′×5′ to 90′&...We examined the scale impacts on spatial hot and cold spots of CPUE for Ommastrephes bartramii in the northwest Pacific Ocean. The original fishery data were tessellated to 18 spatial scales from 5′×5′ to 90′×90′ with a scale interval of 5′ to identify the local clusters. The changes in location, boundaries, and statistics regarding the Getis-Ord Gi＊ hot and cold spots in response to the spatial scales were analyzed in detail. Several statistics including Min, mean, Max, SD, CV, skewness, kurtosis, first quartile（Q1）, median, third quartile（Q3）, area and centroid were calculated for spatial hot and cold spots. Scaling impacts were examined for the selected statistics using linear, logarithmic, exponential, power law and polynomial functions. Clear scaling relations were identified for Max, SD and kurtosis for both hot and cold spots. For the remaining statistics, either a difference of scale impacts was found between the two clusters, or no clear scaling relation was identified. Spatial scales coarser than 30′ are not recommended to identify the local spatial patterns of fisheries because the boundary and locations of hot and cold spots at a coarser scale are significantly different from those at the original scale.展开更多
In order to examine the effect of spatial scale and building exposure distribution on the pure rate of earthquake catastrophe insurance,this study described three modules for rate determination,put forward the general...In order to examine the effect of spatial scale and building exposure distribution on the pure rate of earthquake catastrophe insurance,this study described three modules for rate determination,put forward the general assumptions and principles for calculating the pure insurance rate,and introduced three types of building distribution and their calculation.Taking Tangshan City of Hebei Province in China as an example,we analyzed the pure rate of regional earthquake insurance in terms of spatial scale and building exposure distribution by using the method of control variables.The results show that for districts(or counties)with large differences in seismic risk,the risk areas can be further divided to apply differential rates.In areas with a diverse distribution of potential earthquake source areas and large differences in building density,there is a risk of overestimating or underestimating the pure rate of earthquake insurance when buildings are distributed evenly or partially evenly.This violates the break-even principle of rate setting.This study also provides a reference for earthquake catastrophe insurance companies to choose the spatial scale and the detailed level of exposure distribution in rate determination.展开更多
There is a consensus that sediment delivery ratio in the Chinese Loess Plateau is close to 1at the inter-annual timescale. However, little information is available about the sediment delivery at finer timescales. We e...There is a consensus that sediment delivery ratio in the Chinese Loess Plateau is close to 1at the inter-annual timescale. However, little information is available about the sediment delivery at finer timescales. We evaluated the sediment delivery from plots to watersheds at the event or intra-annual, annual, and inter-annual timescales within the Wudinghe river basin, a 30,261 km2 basin in the Loess Plateau. We calculated the ratio of sediment output to sediment input and presented the temporal change of the channel morphology to determine whether sediment deposition occurs.Although a single flood event frequently has a sediment yield exceeding 10,000 t km-2, sediment deposition rarely occurs except during some small runoff events(sediment yield < 5000 t km-2) or dry years(sediment yield < 10,000 t km-2) when moving from slopes up to the main channels of the Wudinghe River. This observation suggests a sediment delivery ratio close to 1 even at the event or intra-annual and the annual timescales, but not necessarily at the interannual timescale. Such a high sediment delivery ratio can be related to hyper-concentrated flows, which have very strong sediment transport capacity even at low flow strength. Because hyper-concentrated flows are well-developed in the whole Loess Plateau, a sediment delivery ratio close to 1 below the interannual timescale possibly remains true for other rivers in the Loess Plateau.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.91025006,40871186,40730525)National Basic Research Program of China(Grant No.2007CB714402)National High Technology Research and Development Program of China(Grant Nos.2009AA12Z143,2009AA122103)
文摘The leaf area index(LAI) is a critical biophysical variable that describes canopy geometric structures and growth conditions.It is also an important input parameter for climate,energy and carbon cycle models.The scaling effect of the LAI has always been of concern.Considering the effects of the clumping indices on the BRDF models of discrete canopies,an effective LAI is defined.The effective LAI has the same function of describing the leaf density as does the traditional LAI.Therefore,our study was based on the effective LAI.The spatial scaling effect of discrete canopies significantly differed from that of continuous canopies.Based on the directional second-derivative method of effective LAI retrieval,the mechanism responsible for the spatial scaling effect of the discrete-canopy LAI is discussed and a scaling transformation formula for the effective LAI is suggested in this paper.Theoretical analysis shows that the mean values of effective LAIs retrieved from high-resolution pixels were always equal to or larger than the effective LAIs retrieved from corresponding coarse-resolution pixels.Both the conclusions and the scaling transformation formula were validated with airborne hyperspectral remote sensing imagery obtained in Huailai County,Zhangjiakou,Hebei Province,China.The scaling transformation formula agreed well with the effective LAI retrieved from hyperspectral remote sensing imagery.
基金Project supported by the National Research Foundation of South Africa(No.93918)
文摘Spatial scaling laws of velocity kinetic energy spectra for the compressible turbulence flow and the density-weighted counterparts are formulated in terms of the wavenumber, dissipation rate, and Mach number by using a dimensional analysis. We apply the Barenblatt＇s incomplete similarity theory to both kinetic and density-weighted energy spectra. It shows that, within the initial subrange, both energy spectra approach the -5/3 and -2 power laws of the wavenumber when the Mach number tends to unity and infinity, respectively.
基金the Natural Science Foundation of China(Grant No.41790425).
文摘Landscape fragmentation is generally viewed as an indicator of environmental stresses or risks,but the fragmentation intensity assessment also depends on the scale of data and the definition of spatial unit.This study aimed to explore the scale-dependence of forest fragmentation intensity along a moisture gradient in Yinshan Mountain of North China,and to estimate environmental sensitivity of forest fragmentation in this semi-arid landscape.We developed an automatic classification algorithm using simple linear iterative clustering(SLIC)and Gaussian mixture model(GMM),and extracted tree canopy patches from Google Earth images(GEI),with an accuracy of 89.2%in the study area.Then we convert the tree canopy patches to forest category according to definition of forest that tree density greater than 10%,and compared it with forest categories from global land use datasets,FROM-GLC10 and GlobeLand30,with spatial resolutions of 10 m and 30 m,respectively.We found that the FROM-GLC10 and GlobeLand30 datasets underestimated the forest area in Yinshan Mountain by 16.88%and 21.06%,respectively;and the ratio of open forest(OF,10%<tree coverage<40%)to closed forest(CF,tree coverage>40%)areas in the underestimated part was 2:1.The underestimations concentrated in warmer and drier areas occupied mostly by large coverage of OFs with severely fragmented canopies.Fragmentation intensity of canopies positively correlated with spring temperature while negatively correlated with summer precipitation and terrain slope.When summer precipitation was less than 300 mm or spring temperature higher than 4℃,canopy fragmentation intensity rose drastically,while the forest area percentage kept stable.Our study suggested that the spatial configuration,e.g.,sparseness,is more sensitive to drought stress than area percentage.This highlights the importance of data resolution and proper fragmentation measurements for forest patterns and environmental interpretation,which is the base of reliable ecosystem predictions with regard to the future climate scenarios.
基金Under the auspices of National Key Research and Development Program of China(No.2016YFC0500306)。
文摘This study aims to verify the concept of niches at multiple spatial scales in plant communities.To this end,we analyzed the niche characteristic of Rhododendron dauricum plant communities in Northeast China at three spatial scales.At the local scale,we calculated the Importance Value(IV)of species in five communities in the north of the Da Hinggan Mountains.At the intermediate scale,we examined five communities in their entirety,calculated the niche breadth of the species,and integrated niche overlap and interspecific association to analyze interspecific relationships.Further,the generalized additive model(GAM)was used to analyze the impact of topography and soil factors on niche characteristics.At the regional scale,we analyzed the geographical distribution of dominant species of R.dauricum plant communities in Northeast China and used principal component analysis(PCA)to analyze the impact of geographical and climate factors on species distribution.The results show that at the local scale,the IV of the species in each community varies widely.At the intermediate scale,species with a wide niche breadth tend to have a high value for IV.Larix gmelinii,Betula platyphylla,R.dauricum,Ledum palustre,and Vaccinium vitis-idaea had a relatively wide niche breadth and a high niche overlap,and the interspecific associations were almost all positive.Elevation and soil nutrients were the most dominant environmental factors.At the regional scale,species with a wide niche breadth tend to have a wide range of distribution,and temperature and precipitation were the most dominant environmental factors.This study suggests that the niche characteristics at three scales are both related and different.Niche characteristics at the local scale were various and labile,and niche characteristics at the intermediate and regional scales were relatively regular.These results show some degree of consistency with previous studies from an evolutionary perspective.The action mechanisms of these communities are related to differences in the dominant environmental factors.In addition,the integration of niche overlap and interspecific association determine interspecific relationships more accurately.
基金Under the auspices of National Natural Science Foundation of China(No.41401204,41471462)Fundamental Research Funds for the Central Universities(No.lzujbky-2013-128)
文摘The important role of spatial scale in exploring the geography of poverty as well as its policy implications has been noticed but with limited knowledge. To improve such limited understanding, we mainly investigated the spatial patterns and influencing factors of rural poverty(indicated by poor population and poverty incidence) at three different administrative levels in the Liupan Mountain Region, one of the fourteen poorest regions in China. Our results show that from a global perspective, poor areas are clustered significantly at the county-, township-, and village-level, and more greatly at a lower level. Locally, there is spatial mismatch among poverty hotspots detected not only by the same indicator at different levels but also by different indicators at the same level. A scale effect can be found in the influencing factors of rural poverty. That is, the number of significant factors increases, but the degree of their association with poverty incidence decreases at a lower level. Such scale effect indicates that poverty incidence at lower levels may be affected by more complex factors, including not only the new local ones but also the already appeared non-local ones at higher levels. However, the natural conditions tend to play a scale-independent role to poverty incidence. In response to such scale-dependent patterns and factors, anti-poverty policies can be 1) a multilevel monitoring system to reduce incomplete or even misleading single-level information and understanding; 2) the village-based targeting strategy to increase the targeting efficiency and alleviate the mentioned spatial mismatch; 3) more flexible strategies responding to the local impoverishing factors, and 4) different task emphasises for multilevel policymakers to achieve the common goal of poverty reduction.
基金supported from the National Key Basic Research and Development Projectof China(2009CB421505)the National Natural Sciences Foundation of China(40775031)the Project(No.2008LASW-A01)
文摘Precipitation and associated cloud hydrometeors have large temporal and spatial variability, which makes accurate quantitative precipitation forecasting difficult. Thus, dependence of accurate precipitation and associated cloud simulation on temporal and spatial scales becomes an important issue. We report a cloud- resolving modeling analysis on this issue by comparing the control experiment with experiments perturbed by initial temperature, water vapor, and cloud conditions. The simulation is considered to be accurate only if the root-mean-squared difference between the perturbation experiments and the control experiment is smaller than the standard deviation. The analysis may suggest that accurate precipitation and cloud simulations cannot be obtained on both fine temporal and spatial scales simultaneously, which limits quanti- tative precipitation forecasting. The accurate simulation of water vapor convergence could lead to accurate precipitation and cloud simulations on daily time scales, but it may not be beneficial to precipitation and cloud simulations on hourly time scales due to the dominance of cloud processes.
基金funded by National High Technology Research and Development Program of China (863 Program,2012AA092303)Project of Shanghai Science and Technology Innovation (12231203900)+2 种基金Industrialization Program of National Development and Reform Commission (2159999)National Science and Technology Support Program (2013BAD13B01)Shanghai Leading Academic Discipline Project
文摘Temporal and spatial scales play important roles in fishery ecology,and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution.The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling,with the western stock of winter-spring cohort of neon flying squid （Ornmastrephes bartramii） in the northwest Pacific Ocean as an example.In this study,the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature （SST） from remote sensing during August to October of 2003-2008 were used.We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales （0.5°,1 ° and 2°）,four longitude scales （0.5°,1°,2° and 4°）,and three temporal scales （week,fortnight,and month）.The coefficients of variation （CV） of the weekly,biweekly and monthly suitability index （SI） were compared to determine which temporal and spatial scales of SI model are more precise.This study shows that the optimal temporal and spatial scales with the lowest CV are month,and 0.5° latitude and 0.5° longitude for O.bartramii in the northwest Pacific Ocean.This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts.We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.
文摘The drastic decline in groundwater table and many other detrimental effects in meeting irrigation demand, and the projected population growth have force to evaluate consumptive use or evapo-transpiration (ET), the rate of liquid water transformation to vapor from open water, bare soil, and vegetation, which determines the irrigation demand. As underscored in the literature, Pen-man-Monteith method which is based on aerodynamic and energy balance method is widely used and accepted as the method of estimation of ET. However, the estimation of ET is oftentimes carried out using meteorological data from climate stations. Therefore, such estimation of ET may vary spatially and thus there exists a need to estimate ET spatially at different spatial or grid scales/resolutions. Thus, in this paper, a spatial tool that can geographically encompass all the best available climate datasets to produce ET at different spatial scales is developed. The spatial tool is developed as a Python toolbox in ArcGIS using Python, an open source programming language, and the ArcPy site-package of ArcGIS. The developed spatial tool is demonstrated using the meteorological data from Automated Weather Data Network in Nebraska in 2010.
基金Under the auspices of Humanities and Social Science Foundation of Ministry of Education of China(No.10YJA790047)Funding Project for Academic Human Resources Development in Beijing Union University
文摘During the past two decades, the exhibition industry in China has been developing rapidly and has become an important part of the modern service industry, particularly the agglomeration characteristics of exhibition enterprises highlighted on the regional scale. Although the development of theoretical research on the western exhibition industry has taken place over time, the spatial perspective has not been at the centre of attention so far. This paper aims to fill this gap and report on the agglomeration characteristics of exhibition enterprises and their influential factors. Based on data about exhibition enterprises in the Pearl River Delta(PRD) during 1991–2013, using the Ripley K function analysis and kernel density estimation, this research identifies that: 1) the exhibition enterprise on the regional scale is significantly characterized by spatial agglomeration, and the agglomeration density and scale are continuously increasing; 2) the spatial pattern of agglomeration has developed from a single-center to multi-center form. Meanwhile, this paper profiles the factors influencing the spatial agglomeration of exhibition enterprises by selecting the panel data of nine cities in the PRD in 1999, 2002, 2006 and 2013. The results show that market capacity, urban informatization level and exhibition venues significantly influence the location choice of exhibition enterprises. Among them, the market capacity is a variable that exerts a far greater impact than other factors do.
基金Under the auspices of National Natural Science Foundation of China(No.41871162)。
文摘Scale is the range or measurement unit of the characteristics of natural or human ontology in the temporal or spatial dimension and is widely used in daily life and the study of various disciplines.Scale effect pertains to certain laws and characteristics that can only be reflected on a specific scale,so choosing the appropriate scale remains the basic premise of scientific research.The concept of the urban spatial system is complex and has the characteristics of scale dependence,and the selection of an appropriate spatial scale is important for the accurate estimation and description of urban issues.In this paper,we discuss spatial scale in urban research using cases that primarily come from the Chinese experience,provide some examples that demonstrate the importance of appropriate scale in urban research,including urban shrinkage,and highlight problems in spatial research.Ultimately,we suggest that scale consciousness should be the basic consciousness required in empirical research.
基金supported by the National Key Basic Research and Development Project of China under Grant No.2011CB403405the National Natural Science Foundation of China under Grant Nos.41075039 and 41175065the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘Data from Goddard cumulus ensemble model experiment are used to study temporal and spatial scale dependence of tropical rainfall separation analysis based on cloud budget during Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment （TOGA COARE）. The analysis shows that the calculations of model domain mean or time-mean grid-scale mean simulation data overestimate the rain rates of the two rainfall types associated with net condensation but they severely underestimate the rain rate of the rainfall type associated with net evaporation and hydrometeor convergence.
文摘The need to allocate the existing water in a sustainable manner, even with the projected population growth, has made to assess the consumptive use or evapotranspiration (ET), which determines the irrigation demand. As underscored in the literature, Penman-Monteith method which is a combination of aerodynamic and energy balance method is widely used and accepted as the method of estimation of ET. However, the application of Penman-Monteith relies on many climate parameters such as relative humidity, solar radiation, temperature, and wind speed. Therefore, there exists a need to determine the parameters that are most sensitive and correlated with dependent variable (i.e., ET), to strengthen the knowledge base. However, the sensitivity of ET using Penman-Monteith is oftentimes estimated using meteorological data from climate stations. Such estimation of sensitivity may vary spatially and thus there exists a need to estimate sensitivity of ET spatially. Thus, in this paper, based on One-AT-A-Time (OAT) method, a spatial sensitivity tool that can geographically encompass all the best available climate datasets to produce ET and its sensitivity at different spatial scales is developed. The spatial tool is developed as a Python toolbox in ArcGIS using Python, an open source programming language, and the ArcPy site-package of ArcGIS. The developed spatial tool is demonstrated using the meteorological data from Automated Weather Data Network in Nebraska in 2010. To summarize the outcome of the sensitivity analysis using OAT method, sensitivity indices are developed for each raster cell. The demonstration of the tool shows that, among the considered parameters, the computed ET using Penman-Monteith is highly sensitive to solar radiation followed by temperature for the state of Nebraska, as depicted by the sensitivity index. The computed sensitivity index of wind speed and the relative humidity are not that significant compared to the sensitivity index of solar radiation and temperature.
基金funded by the Project for Fostering Outstanding Young talents of Henan Academy of Sciences(No.210401001)Special Project for Team Building of Henan Academy of Sciences(No.200501007)+1 种基金Science and Technology Research Project of Henan Province(Nos.212102310424,222102320467,and 212102310024)Major Scientific Research Focus Project of Henan Academy of Sciences(No.210101007).
文摘Abstract The chlorophyll-a concentration data obtained through remote sensing are important for a wide range of scientific concerns.However,cloud cover and limitations of inversion algorithms of chlorophyll-a concentration lead to data loss,which critically limits studying the mechanism of spatial-temporal patterns of chlorophyll-a concentration in response to marine environment changes.If the commonly used operational chlorophyll-a concentration products can offer the best data coverage frequency,highest accuracy,best applicability,and greatest robustness at different scales remains debatable to date.Therefore,in the present study,four commonly used operational multi-sensor multi-algorithm fusion products were compared and subjected to validation based on statistical analysis using the available data measured at multiple spatial and temporal scales.The experimental results revealed that in terms of spatial distribution,the chlorophyll-a concentration products generated by averaging method(Chl1-AV/AVW)and GSM model(Chl1-GSM)presented a relatively high data coverage frequency in Case Ⅰ water regions and extremely low or no data coverage frequency in the estuarine coastal zone regions and inland water regions,the chlorophyll-a concentration products generated by the Neural Network algorithm(Chl2)presented high data coverage frequency in the estuarine coastal zone Case 2 water regions.The chlorophyll-a concentration products generated by the OC5 algorithm(ChlOC5)presented high data coverage frequency in Case I water regions and the turbid Case Ⅱ water regions.In terms of absolute precision,the Chl1-AV/AVW and Chl1-GSM chlorophyll-a concentration products performed better in Class I water regions,and the Chl2 product performed well only in Case Ⅱ estuarine coastal zones,while presenting large errors in absolute precision in the Case Ⅰ water regions.The ChlOC5 product presented a higher precision in Case Ⅰ and Case Ⅱ water regions,with a better and more stable performance in both regions compared to the other products.
基金Supported by the National Natural Science Foundation of China (No.40921061)the National Basic Research Program (973 Program) of China (No.2007CB407206)the Frontier Project of the Chinese Academy of Sciences(No.ISSASIP0715)
文摘Understanding how spatial scale influences commonly-observed effects of climate and soil texture on soil organic carbon （SOC） storage is important for accurately estimating the SOC pool at different scales. The relationships among climate factors, soil texture and SOC density at the regional, provincial, city, and county scales were evaluated at both the soil surface （0-20 cm） and throughout the soil profile （0-100 cm） in the Northeast China uplands. We examined 1 022 profiles obtained from the Second National Soil Survey of China. The results indicated that the relationships between climate factors and SOC density generally weakened with decreasing spatial scale. The provincial scale was optimal to assess the relationship between climate factors and SOC density because regional differences among provinces were covered up at the regional scale. However, the relationship between soil texture and SOC density had no obvious trend with increasing scale and changed with temperature. There were great differences in the impacts of climate factors and soil texture on SOC density at different scales. Climate factors had a larger effect on SOC density than soil texture at the regional scale. Similar trends were seen in Heilongjiang and eastern Inner Mongolia at the provincial scale. But, soil texture had a greater effect on SOC density compared with climate factors in Jilin and Liaoning. At the city and county scales, the influence of soil texture on SOC density was more important than climate factors.
基金financially supported by the National Natural Science Foundation of China (41171414)the Knowledge Innovation Program of the Chinese Academy of Sciences (KZCX2-EW-QN313)+1 种基金the Chinese Academy of Sciences Visiting Professorships for Senior International Scientists (2011T2Z36)the Key Project of Scientific and Technical Supporting Programs (2011BAC07B02-09), and the National Basic Research Program of China (2009CB421303)
文摘Ecological patterns and processes in dune ecosystems have been a research focus in recent years, however the information on how dune stabilization influences the spatial scale dependence of plant diversity is still lacking. In this study, we measured the plant species richness, soil properties and altitude across four spatial scales （1, 10, 100 and 1,000 m2） at three different dune stabilization stages （mobile dune, semi-fixed dune and fixed dune） in Horqin Sandy Land, Northern China. We also examined the relationships between plant species richness, community composition and environmental factors along the gradient of dune stabilization. Our results showed that plant species richness increased with the increase of spatial scales in each dune stabilization stage, as well as with the increase of dune stabilization degrees. Canonical correspondence analysis （CCA） showed that plant distribu- tions in the processes of dune stabilization were determined by the combined environmental gradient in relation to soil organic carbon （SOC）, total nitrogen （TN）, carbon/nitrogen （C/N）, pH, electrical conductivity （EC）, soil water content （SWC）, fine sand （FS）, very fine sand （VFS）, silt and clay （SC）, and altitude. Plant species richness was significantly and positively correlated to SOC and TN in mobile dune, and significantly and positively correlated to SOC, TN, C/N, VFS and SC in semi-fixed dune. However, no significant correlation between plant species richness and environmental factors was observed in fixed dune. In addition, plant species richness in different dune stabili- zation stages was also determined by the combined gradient of soil properties and altitude. These results suggest that plant species richness has obvious scale dependence along the gradient of dune stabilization. Soil resources depending on dune habitats and environmental gradients caused by dune stabilization are important factors to de- termine the scale dependence of species diversity in sand dune ecosystems.
文摘A new soil moisture dataset from direct gravimetric measurements within the top 50-cm soil layers at 178 soil moisture stations in China covering the period 1981 1998 are used to study the long-term and seasonal trends of soil moisture variations, as well as estimate the temporal and spatial scales of soil moisture for different soil layers. Additional datasets of precipitation and temperature difference between land surface and air （TDSA） are analyzed to gain further insight into the changes of soil moisture. There are increasing trends for the top 10 cm, but decreasing trends for the top 50 cm of soil layers in most regions. Trends in precipitation appear to dominantly influence trends in soil moisture in both cases. Seasonal variation of soil moisture is mainly controlled by precipitation and evaporation, and in some regions can be affected by snow cover in winter. Timescales of soil moisture variation are roughly 1-3 months and increase with soil depth. Further influences of TDSA and precipitation on soil moisture in surface layers, rather than in deeper layers, cause this phenomenon. Seasonal variations of temporal scales for soil moisture are region-dependent and consistent in both layer depths. Spatial scales of soil moisture range from 200-600 km, with topography also having an affect on these. Spatial scales of soil moisture in plains are larger than in mountainous areas. In the former, the spatial scale of soil moisture follows the spatial patterns of precipitation and evaporation, whereas in the latter, the spatial scale is controlled by topography.
基金supported by the Beijing Common Construction Project Research and demonstration on the regression technique of the minimum population of wild plants (2016YFC0503106)
文摘In order to better explore the maintenance mechanisms of biodiversity, data collected from a 40-ha undisturbed Pinus forest were applied to the Individual Species-Area Relationship model(ISAR) to determine distribution patterns for species richness. The ecological processes influencing species abundance distribution patterns were assessed by applying the same data set to five models: a LogNormal Model(LNM), a Broken Stick Model(BSM), a Zipf Model(ZM), a Niche Preemption Model(NPM), and a Neutral Model(NM). Each of the five models was used at six different sampling scales(10 m×10 m, 20 m×20 m, 40 m×40 m, 60 m×60 m, 80 m×80 m, and 100 m×100 m). Model outputs showed that:(1) Accumulators and neutral species strongly influenced species diversity, but the relative importance of the two types of species varied across spatial scales.(2) Distribution patterns of species abundance were best explained by the NPM at small scales(10 m-20 m), whereas the NM was the best fit model at large spatial scales.(3) Species richness and abundance distribution patterns appeared to be driven by similar ecological processes. At small scales, the niche theory could be applied to describe species richness and abundance, while at larger scales the neutral theory was more applicable.
基金The National Natural Science Foundation of China under contract No.41406146the Open Fund from Laboratory for Marine Fisheries Science and Food Production Processes at Qingdao National Laboratory for Marine Science and Technology of China under contract No.2017-1A02Shanghai Universities First-class Disciplines Project-Fisheries(A)
文摘We examined the scale impacts on spatial hot and cold spots of CPUE for Ommastrephes bartramii in the northwest Pacific Ocean. The original fishery data were tessellated to 18 spatial scales from 5′×5′ to 90′×90′ with a scale interval of 5′ to identify the local clusters. The changes in location, boundaries, and statistics regarding the Getis-Ord Gi＊ hot and cold spots in response to the spatial scales were analyzed in detail. Several statistics including Min, mean, Max, SD, CV, skewness, kurtosis, first quartile（Q1）, median, third quartile（Q3）, area and centroid were calculated for spatial hot and cold spots. Scaling impacts were examined for the selected statistics using linear, logarithmic, exponential, power law and polynomial functions. Clear scaling relations were identified for Max, SD and kurtosis for both hot and cold spots. For the remaining statistics, either a difference of scale impacts was found between the two clusters, or no clear scaling relation was identified. Spatial scales coarser than 30′ are not recommended to identify the local spatial patterns of fisheries because the boundary and locations of hot and cold spots at a coarser scale are significantly different from those at the original scale.
基金funded by the National Key Research and Development Program(2022YFC3003500)the 111 Project(D21001).
文摘In order to examine the effect of spatial scale and building exposure distribution on the pure rate of earthquake catastrophe insurance,this study described three modules for rate determination,put forward the general assumptions and principles for calculating the pure insurance rate,and introduced three types of building distribution and their calculation.Taking Tangshan City of Hebei Province in China as an example,we analyzed the pure rate of regional earthquake insurance in terms of spatial scale and building exposure distribution by using the method of control variables.The results show that for districts(or counties)with large differences in seismic risk,the risk areas can be further divided to apply differential rates.In areas with a diverse distribution of potential earthquake source areas and large differences in building density,there is a risk of overestimating or underestimating the pure rate of earthquake insurance when buildings are distributed evenly or partially evenly.This violates the break-even principle of rate setting.This study also provides a reference for earthquake catastrophe insurance companies to choose the spatial scale and the detailed level of exposure distribution in rate determination.
基金funded by National Natural Science Foundation of China (Grant Nos. 41230746, 41271306)the National Key Technology Research and Development Program (Grant No. 2012BAC09B03)the Open-fund Project of Jiangxi Provincial Key Laboratory of Soil Erosion and Prevention (Grant No. JXSB201301)
文摘There is a consensus that sediment delivery ratio in the Chinese Loess Plateau is close to 1at the inter-annual timescale. However, little information is available about the sediment delivery at finer timescales. We evaluated the sediment delivery from plots to watersheds at the event or intra-annual, annual, and inter-annual timescales within the Wudinghe river basin, a 30,261 km2 basin in the Loess Plateau. We calculated the ratio of sediment output to sediment input and presented the temporal change of the channel morphology to determine whether sediment deposition occurs.Although a single flood event frequently has a sediment yield exceeding 10,000 t km-2, sediment deposition rarely occurs except during some small runoff events(sediment yield < 5000 t km-2) or dry years(sediment yield < 10,000 t km-2) when moving from slopes up to the main channels of the Wudinghe River. This observation suggests a sediment delivery ratio close to 1 even at the event or intra-annual and the annual timescales, but not necessarily at the interannual timescale. Such a high sediment delivery ratio can be related to hyper-concentrated flows, which have very strong sediment transport capacity even at low flow strength. Because hyper-concentrated flows are well-developed in the whole Loess Plateau, a sediment delivery ratio close to 1 below the interannual timescale possibly remains true for other rivers in the Loess Plateau.
