Automatic generalization of geographic information is the core of multi_scale representation of spatial data,but the scale_dependent generalization methods are far from abundant because of its extreme complicacy.This ...Automatic generalization of geographic information is the core of multi_scale representation of spatial data,but the scale_dependent generalization methods are far from abundant because of its extreme complicacy.This paper puts forward a new consistency model about scale_dependent representations of relief based on wavelet analysis,and discusses the thresholds in the model so as to acquire the continual representations of relief with different details between scales.The model not only meets the need of automatic generalization but also is scale-dependent completely.Some practical examples are given.展开更多
In this paper,the behavior of breakthrough curves(BTCs) for reactive solute transport through stratified porous media is investigated.A physical laboratory model for layered porous media was constructed,in which thin ...In this paper,the behavior of breakthrough curves(BTCs) for reactive solute transport through stratified porous media is investigated.A physical laboratory model for layered porous media was constructed,in which thin layer of gravel was sandwiched in between two thick layers of natural soil.Gravel layer and natural soil layers were hydraulically connected as single porous continuum.A constant source of tracer was connected through gravel layer and elucidated at different sampling points in the direction of flow.Flexible multiprocess non-equilibrium(MPNE) transport equation with scale-dependent dispersivity function was used to simulate experimental BTCs of reactive solute transport through layered porous media.The values of equilibrium sorption coefficient and other input parameters were obtained experimentally.The simulation of BTC was performed using MPNE model with scale-dependent dispersivity.The simulation of different scale-dependent dispersivities was then compared and it was found that for field scale of estimation of dispersivity,asymptotic and exponential dispersivity functions performed better.In continuation to the comparison of simulated BTCs obtained using different models,spatial moment analysis of each aforesaid scale-dependent dispersivity model was also done.Spatial moment analysis provides the information related to mean solute mass,rate of mass travel,and mean plume dispersion.Linear and constant dispersivities showed higher variance as compared to asymptotic and exponential dispersion functions.This supports the field applicability of asymptotic and exponential dispersivity functions.The BTCs were also found to elucidate a nonzero concentration with time,which was clearly affected by physical non-equilibrium.In natural condition,such information is required in effective aquifer remediation process.展开更多
To examine the effects of microtopography on the stoichiometry of carbon(C), nitrogen(N) and phosphorus(P) in mosses along the hummock-hollow gradient in boreal peatlands, we investigated species-level C?N, C?P and N?...To examine the effects of microtopography on the stoichiometry of carbon(C), nitrogen(N) and phosphorus(P) in mosses along the hummock-hollow gradient in boreal peatlands, we investigated species-level C?N, C?P and N?P ratios of five mosses(Sphagnum magellanicum, S. perichaetiale, S. palustre, S. girgensohnii and Aulacomnium palustre) in the hummocks, hollows and their intermediate zones, and then assessed community-level spatial patterns in a boreal ombrotrophic peatland of north of the Great Xing'an Mountain, Northeast China. The results show that at the species level, C?N, C?P and N?P ratios of the selected Sphagnum mosses remained stable in the hummock-hollow complexes due to unchanged C, N and P concentrations, whereas the non-Sphagnum moss(A. palustre) in the hummocks and intermediate zones had lower P concentrations and thus greater C?P ratios than that in the hollows. At the community level, moss N concentration and C?N ratio remained constant along the hummock-hollow gradient, whereas hummocks and intermediate zones had higher community-level moss C?P and N?P ratios than hollows because of greater C and lower P concentrations. These findings imply that the effects of microtopography on moss C?N?P stoichiometry are scale-dependent and reveal spatial heterogeneity in C and nutrient dynamics. These results provide a more comprehensive understanding of biogeochemical cycles in boreal peatlands.展开更多
Tree-ring based temperature reconstructions have successfully inferred the past inter-annual to millennium scales summer temperature variability. A clear relationship between annual and summer temperatures can provide...Tree-ring based temperature reconstructions have successfully inferred the past inter-annual to millennium scales summer temperature variability. A clear relationship between annual and summer temperatures can provide insights into tile variability of past annual mean tem- perature from the reconstructed summer temperature. However, how similar are summer and annual temperatures is to a large extent still unknown. This study aims at investigating the relationship between annual and summer temperatures at different timescales in central Sweden during the last millennium. The temperature variability in central Sweden can represent large parts of Scandinavia which has been a key region for dendroclimatological research. The observed annual and summer temperatures during 1901-2005 were firstly decomposed into different frequency bands using ensemble empirical mode decomposition （EEMD） method, and then the scale-dependent relationship was quantified using Pearson correlation coefficients. The relationship between the observed annual and summer temperatures determined by the instrumental data was subsequently used to evaluate 7 climate models. The model with the best performance was used to infer the relationship for the last millennium. The results show that the relationship between the observed annual and summer temperatures becomes stronger as the timescale increases, except for the 4--16 years timescales at which it does not show any relationship. The summer temperature variability at short timescales （2--4 years） shows much higher variance than the annual variability, while the annual temperature variability at long timescales （〉32 years） has a much higher variance than the summer one. During the last millennium, the simulated summer temperature also shows higher variance at the short timescales （2-4 years） and lower variance at the long timescales （〉1024 years） than those of the annual temperature. The relationship between the two temperatures is generally close at the long timescales, and weak at the short timescales. Overall the summer temperature variability cannot well reflect the annual mean temperature variability for the study region during both the 20th century and the last millennium. Furthermore, all the climate models examined overestimate the annual mean temperature variance at the 2--4 years timescales, which indicates that the overestimate could be one of reasons why the volcanic eruption induced cooling is larger in climate models than in proxy data.展开更多
Since 2005,dozens of geographical observational stations have been established in the Heihe River Basin(HRB),and by now a large amount of meteorological,hydrological,and ecological observations as well as data pertain...Since 2005,dozens of geographical observational stations have been established in the Heihe River Basin(HRB),and by now a large amount of meteorological,hydrological,and ecological observations as well as data pertaining to water resources,soil and vegetation have been collected.To adequately analyze these available data and data to be further collected in future,we present a perspective from complexity theory.The concrete materials covered include a presentation of adaptive multiscale filter,which can readily determine arbitrary trends,maximally reduce noise,and reliably perform fractal and multifractal analysis,and a presentation of scale-dependent Lyapunov exponent(SDLE),which can reliably distinguish deterministic chaos from random processes,determine the error doubling time for prediction,and obtain the defining parameters of the process examined.The adaptive filter is illustrated by applying it to obtain the global warming trend and the Atlantic multidecadal oscillation from sea surface temperature data,and by applying it to some variables collected at the HRB to determine diurnal cycle and fractal properties.The SDLE is illustrated to determine intermittent chaos from river flow data.展开更多
The ensemble technique has been widely used in numerical weather prediction and extended-range forecasting.Current approaches to evaluate the predictability using the ensemble technique can be divided into two major g...The ensemble technique has been widely used in numerical weather prediction and extended-range forecasting.Current approaches to evaluate the predictability using the ensemble technique can be divided into two major groups.One is dynamical,including generating Lyapunov vectors,bred vectors,and singular vectors,sampling the fastest error-growing directions of the phase space,and examining the dependence of prediction efficiency on ensemble size.The other is statistical,including distributional analysis and quantifying prediction utility by the Shannon entropy and the relative entropy.Currently,with simple models,one could choose as many ensembles as possible,with each ensemble containing a large number of members.When the forecast models become increasingly complicated,however,one would only be able to afford a small number of ensembles,each with limited number of members,thus sacrificing estimation accuracy of the forecast errors.To uncover connections between different information theoretic approaches and between dynamical and statistical approaches,we propose an (∈;T)-entropy and scale-dependent Lyapunov exponent——based general theoretical framework to quantify information loss in ensemble forecasting.More importantly,to tremendously expedite computations,reduce data storage,and improve forecasting accuracy,we propose a technique for constructing a large number of "pseudo" ensembles from one single solution or scalar dataset.This pseudo-ensemble technique appears to be applicable under rather general conditions,one important situation being that observational data are available but the exact dynamical model is unknown.展开更多
Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis （hereafter, beaver） has been studied at singular spatial scales, but ...Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis （hereafter, beaver） has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy （MaxEnt） models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system （GPS） relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse （study area） and fine （within home range） scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density （i.e., smaller non-forested wetlands or lodges closer to banks） for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection.展开更多
As one of the most well-documented biogeographic patterns,the distance-decay relation-ship provides insights into the underlying mechanisms driving biodiversity distribution.Al-though wastewater treatment plants(WWTPs...As one of the most well-documented biogeographic patterns,the distance-decay relation-ship provides insights into the underlying mechanisms driving biodiversity distribution.Al-though wastewater treatment plants(WWTPs)are well-controlled engineered ecosystems,this pattern has been seen among microbial communities in activated sludge(AS).However,little is known about the relative importance of environmental heterogeneity and dispersal limitation in shaping AS microbial community across China;especially they are related to spatial scale and organism types.Here,we assessed the distance-decay relationship based on different spatial scales and microbial phylogenetic groups by analyzing 132 activated sludge(AS)samples across China comprising 3,379,20016S rRNA sequences.Our results in-dicated that the drivers of distance-decay pattern in China were scale-dependent.Microbial biogeographic patterns in WWTPs were mainly driven by dispersal limitation at both local and national scales.In contrast,conductivity,SRT,and pH played dominant roles in shaping AS microbial community compositions at the regional scale.Turnover rates and the drivers of beta-diversity also varied with microorganism populations.Moreover,a quantitative re-lationship between dispersal limitation ratio and AS microbial turnover rate was generated.Collectively,these results highlighted the importance of considering multiple spatial scales and micro-organism types for understanding microbial biogeography in WWTPs and pro-vided new insights into predicting variations in AS community structure in response to environmental disturbance.展开更多
基金ProjectsupportedbytheNationalScienceFoundationofSurveyingandMappingofChina (No .990 1 3) .
文摘Automatic generalization of geographic information is the core of multi_scale representation of spatial data,but the scale_dependent generalization methods are far from abundant because of its extreme complicacy.This paper puts forward a new consistency model about scale_dependent representations of relief based on wavelet analysis,and discusses the thresholds in the model so as to acquire the continual representations of relief with different details between scales.The model not only meets the need of automatic generalization but also is scale-dependent completely.Some practical examples are given.
文摘In this paper,the behavior of breakthrough curves(BTCs) for reactive solute transport through stratified porous media is investigated.A physical laboratory model for layered porous media was constructed,in which thin layer of gravel was sandwiched in between two thick layers of natural soil.Gravel layer and natural soil layers were hydraulically connected as single porous continuum.A constant source of tracer was connected through gravel layer and elucidated at different sampling points in the direction of flow.Flexible multiprocess non-equilibrium(MPNE) transport equation with scale-dependent dispersivity function was used to simulate experimental BTCs of reactive solute transport through layered porous media.The values of equilibrium sorption coefficient and other input parameters were obtained experimentally.The simulation of BTC was performed using MPNE model with scale-dependent dispersivity.The simulation of different scale-dependent dispersivities was then compared and it was found that for field scale of estimation of dispersivity,asymptotic and exponential dispersivity functions performed better.In continuation to the comparison of simulated BTCs obtained using different models,spatial moment analysis of each aforesaid scale-dependent dispersivity model was also done.Spatial moment analysis provides the information related to mean solute mass,rate of mass travel,and mean plume dispersion.Linear and constant dispersivities showed higher variance as compared to asymptotic and exponential dispersion functions.This supports the field applicability of asymptotic and exponential dispersivity functions.The BTCs were also found to elucidate a nonzero concentration with time,which was clearly affected by physical non-equilibrium.In natural condition,such information is required in effective aquifer remediation process.
基金Under the auspices of National Natural Science Foundation of China(No.31570479,41671091,41730643,41471056)
文摘To examine the effects of microtopography on the stoichiometry of carbon(C), nitrogen(N) and phosphorus(P) in mosses along the hummock-hollow gradient in boreal peatlands, we investigated species-level C?N, C?P and N?P ratios of five mosses(Sphagnum magellanicum, S. perichaetiale, S. palustre, S. girgensohnii and Aulacomnium palustre) in the hummocks, hollows and their intermediate zones, and then assessed community-level spatial patterns in a boreal ombrotrophic peatland of north of the Great Xing'an Mountain, Northeast China. The results show that at the species level, C?N, C?P and N?P ratios of the selected Sphagnum mosses remained stable in the hummock-hollow complexes due to unchanged C, N and P concentrations, whereas the non-Sphagnum moss(A. palustre) in the hummocks and intermediate zones had lower P concentrations and thus greater C?P ratios than that in the hollows. At the community level, moss N concentration and C?N ratio remained constant along the hummock-hollow gradient, whereas hummocks and intermediate zones had higher community-level moss C?P and N?P ratios than hollows because of greater C and lower P concentrations. These findings imply that the effects of microtopography on moss C?N?P stoichiometry are scale-dependent and reveal spatial heterogeneity in C and nutrient dynamics. These results provide a more comprehensive understanding of biogeochemical cycles in boreal peatlands.
文摘Tree-ring based temperature reconstructions have successfully inferred the past inter-annual to millennium scales summer temperature variability. A clear relationship between annual and summer temperatures can provide insights into tile variability of past annual mean tem- perature from the reconstructed summer temperature. However, how similar are summer and annual temperatures is to a large extent still unknown. This study aims at investigating the relationship between annual and summer temperatures at different timescales in central Sweden during the last millennium. The temperature variability in central Sweden can represent large parts of Scandinavia which has been a key region for dendroclimatological research. The observed annual and summer temperatures during 1901-2005 were firstly decomposed into different frequency bands using ensemble empirical mode decomposition （EEMD） method, and then the scale-dependent relationship was quantified using Pearson correlation coefficients. The relationship between the observed annual and summer temperatures determined by the instrumental data was subsequently used to evaluate 7 climate models. The model with the best performance was used to infer the relationship for the last millennium. The results show that the relationship between the observed annual and summer temperatures becomes stronger as the timescale increases, except for the 4--16 years timescales at which it does not show any relationship. The summer temperature variability at short timescales （2--4 years） shows much higher variance than the annual variability, while the annual temperature variability at long timescales （〉32 years） has a much higher variance than the summer one. During the last millennium, the simulated summer temperature also shows higher variance at the short timescales （2-4 years） and lower variance at the long timescales （〉1024 years） than those of the annual temperature. The relationship between the two temperatures is generally close at the long timescales, and weak at the short timescales. Overall the summer temperature variability cannot well reflect the annual mean temperature variability for the study region during both the 20th century and the last millennium. Furthermore, all the climate models examined overestimate the annual mean temperature variance at the 2--4 years timescales, which indicates that the overestimate could be one of reasons why the volcanic eruption induced cooling is larger in climate models than in proxy data.
基金National Natural Science Foundation of China,No.71661002,No.41671532National Key R&D Program of China,No.2017YFB0504102The Fundamental Research Funds for the Central Universities
文摘Since 2005,dozens of geographical observational stations have been established in the Heihe River Basin(HRB),and by now a large amount of meteorological,hydrological,and ecological observations as well as data pertaining to water resources,soil and vegetation have been collected.To adequately analyze these available data and data to be further collected in future,we present a perspective from complexity theory.The concrete materials covered include a presentation of adaptive multiscale filter,which can readily determine arbitrary trends,maximally reduce noise,and reliably perform fractal and multifractal analysis,and a presentation of scale-dependent Lyapunov exponent(SDLE),which can reliably distinguish deterministic chaos from random processes,determine the error doubling time for prediction,and obtain the defining parameters of the process examined.The adaptive filter is illustrated by applying it to obtain the global warming trend and the Atlantic multidecadal oscillation from sea surface temperature data,and by applying it to some variables collected at the HRB to determine diurnal cycle and fractal properties.The SDLE is illustrated to determine intermittent chaos from river flow data.
基金Project supported by the National Science Foundation (Nos.CMMI-0825311,CMMI-0826119)
文摘The ensemble technique has been widely used in numerical weather prediction and extended-range forecasting.Current approaches to evaluate the predictability using the ensemble technique can be divided into two major groups.One is dynamical,including generating Lyapunov vectors,bred vectors,and singular vectors,sampling the fastest error-growing directions of the phase space,and examining the dependence of prediction efficiency on ensemble size.The other is statistical,including distributional analysis and quantifying prediction utility by the Shannon entropy and the relative entropy.Currently,with simple models,one could choose as many ensembles as possible,with each ensemble containing a large number of members.When the forecast models become increasingly complicated,however,one would only be able to afford a small number of ensembles,each with limited number of members,thus sacrificing estimation accuracy of the forecast errors.To uncover connections between different information theoretic approaches and between dynamical and statistical approaches,we propose an (∈;T)-entropy and scale-dependent Lyapunov exponent——based general theoretical framework to quantify information loss in ensemble forecasting.More importantly,to tremendously expedite computations,reduce data storage,and improve forecasting accuracy,we propose a technique for constructing a large number of "pseudo" ensembles from one single solution or scalar dataset.This pseudo-ensemble technique appears to be applicable under rather general conditions,one important situation being that observational data are available but the exact dynamical model is unknown.
文摘Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis （hereafter, beaver） has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy （MaxEnt） models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system （GPS） relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse （study area） and fine （within home range） scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density （i.e., smaller non-forested wetlands or lodges closer to banks） for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection.
基金This work was supported by the Fundamental Research Funds for the Central Universities(No.2021QNPY84)the National Natural Science Foundation of China(No.52070109).
文摘As one of the most well-documented biogeographic patterns,the distance-decay relation-ship provides insights into the underlying mechanisms driving biodiversity distribution.Al-though wastewater treatment plants(WWTPs)are well-controlled engineered ecosystems,this pattern has been seen among microbial communities in activated sludge(AS).However,little is known about the relative importance of environmental heterogeneity and dispersal limitation in shaping AS microbial community across China;especially they are related to spatial scale and organism types.Here,we assessed the distance-decay relationship based on different spatial scales and microbial phylogenetic groups by analyzing 132 activated sludge(AS)samples across China comprising 3,379,20016S rRNA sequences.Our results in-dicated that the drivers of distance-decay pattern in China were scale-dependent.Microbial biogeographic patterns in WWTPs were mainly driven by dispersal limitation at both local and national scales.In contrast,conductivity,SRT,and pH played dominant roles in shaping AS microbial community compositions at the regional scale.Turnover rates and the drivers of beta-diversity also varied with microorganism populations.Moreover,a quantitative re-lationship between dispersal limitation ratio and AS microbial turnover rate was generated.Collectively,these results highlighted the importance of considering multiple spatial scales and micro-organism types for understanding microbial biogeography in WWTPs and pro-vided new insights into predicting variations in AS community structure in response to environmental disturbance.
