Representation of vegetation by continental data sets derived from NOAA-AVHRR data
NASA Technical Reports Server (NTRS)
Justice, C. O.; Townshend, J. R. G.; Kalb, V. L.
1991-01-01
Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.
Landsat analysis of tropical forest succession employing a terrain model
NASA Technical Reports Server (NTRS)
Barringer, T. H.; Robinson, V. B.; Coiner, J. C.; Bruce, R. C.
1980-01-01
Landsat multispectral scanner (MSS) data have yielded a dual classification of rain forest and shadow in an analysis of a semi-deciduous forest on Mindonoro Island, Philippines. Both a spatial terrain model, using a fifth side polynomial trend surface analysis for quantitatively estimating the general spatial variation in the data set, and a spectral terrain model, based on the MSS data, have been set up. A discriminant analysis, using both sets of data, has suggested that shadowing effects may be due primarily to local variations in the spectral regions and can therefore be compensated for through the decomposition of the spatial variation in both elevation and MSS data.
Recent variations in seasonality of temperature and precipitation in Canada, 1976-95
NASA Astrophysics Data System (ADS)
Whitfield, Paul H.; Bodtker, Karin; Cannon, Alex J.
2002-11-01
A previously reported analysis of rehabilitated monthly temperature and precipitation time series for several hundred stations across Canada showed generally spatially coherent patterns of variation between two decades (1976-85 and 1986-95). The present work expands that analysis to finer time scales and a greater number of stations. We demonstrate how the finer temporal resolution, at 5 day or 11 day intervals, increases the separation between clusters of recent variations in seasonal patterns of temperature and precipitation. We also expand the analysis by increasing the number of stations from only rehabilitated monthly data sets to rehabilitated daily sets, then to approximately 1500 daily observation stations. This increases the spatial density of data and allows a finer spatial resolution of patterns between the two decades. We also examine the success of clustering partial records, i.e. sites where the data record is incomplete. The intent of this study was to be consistent with previous work and explore how greater temporal and spatial detail in the climate data affects the resolution of patterns of recent climate variations. The variations we report for temperature and precipitation are taking place at different temporal and spatial scales. Further, the spatial patterns are much broader than local climate regions and ecozones, indicating that the differences observed may be the result of variations in atmospheric circulation.
Li, Tianxin; Zhou, Xing Chen; Ikhumhen, Harrison Odion; Difei, An
2018-05-01
In recent years, with the significant increase in urban development, it has become necessary to optimize the current air monitoring stations to reflect the quality of air in the environment. Highlighting the spatial representation of some air monitoring stations using Beijing's regional air monitoring station data from 2012 to 2014, the monthly mean particulate matter concentration (PM10) in the region was calculated and through the IDW interpolation method and spatial grid statistical method using GIS, the spatial distribution of PM10 concentration in the whole region was deduced. The spatial distribution variation of districts in Beijing using the gridding model was performed, and through the 3-year spatial analysis, PM10 concentration data including the variation and spatial overlay (1.5 km × 1.5 km cell resolution grid), the spatial distribution result obtained showed that the total PM10 concentration frequency variation exceeded the standard. It is very important to optimize the layout of the existing air monitoring stations by combining the concentration distribution of air pollutants with the spatial region using GIS.
The relationship between observational scale and explained variance in benthic communities
Flood, Roger D.; Frisk, Michael G.; Garza, Corey D.; Lopez, Glenn R.; Maher, Nicole P.
2018-01-01
This study addresses the impact of spatial scale on explaining variance in benthic communities. In particular, the analysis estimated the fraction of community variation that occurred at a spatial scale smaller than the sampling interval (i.e., the geographic distance between samples). This estimate is important because it sets a limit on the amount of community variation that can be explained based on the spatial configuration of a study area and sampling design. Six benthic data sets were examined that consisted of faunal abundances, common environmental variables (water depth, grain size, and surficial percent cover), and sonar backscatter treated as a habitat proxy (categorical acoustic provinces). Redundancy analysis was coupled with spatial variograms generated by multiscale ordination to quantify the explained and residual variance at different spatial scales and within and between acoustic provinces. The amount of community variation below the sampling interval of the surveys (< 100 m) was estimated to be 36–59% of the total. Once adjusted for this small-scale variation, > 71% of the remaining variance was explained by the environmental and province variables. Furthermore, these variables effectively explained the spatial structure present in the infaunal community. Overall, no scale problems remained to compromise inferences, and unexplained infaunal community variation had no apparent spatial structure within the observational scale of the surveys (> 100 m), although small-scale gradients (< 100 m) below the observational scale may be present. PMID:29324746
Gallego, Sergi; Márquez, Andrés; Méndez, David; Ortuño, Manuel; Neipp, Cristian; Fernández, Elena; Pascual, Inmaculada; Beléndez, Augusto
2008-05-10
One of the problems associated with photopolymers as optical recording media is the thickness variation during the recording process. Different values of shrinkages or swelling are reported in the literature for photopolymers. Furthermore, these variations depend on the spatial frequencies of the gratings stored in the materials. Thickness variations can be measured using different methods: studying the deviation from the Bragg's angle for nonslanted gratings, using MicroXAM S/N 8038 interferometer, or by the thermomechanical analysis experiments. In a previous paper, we began the characterization of the properties of a polyvinyl alcohol/acrylamide based photopolymer at the lowest end of recorded spatial frequencies. In this work, we continue analyzing the thickness variations of these materials using a reflection interferometer. With this technique we are able to obtain the variations of the layers refractive index and, therefore, a direct estimation of the polymer refractive index.
NASA Astrophysics Data System (ADS)
Ye, Ran; Cai, Yanhong; Wei, Yongjie; Li, Xiaoming
2017-04-01
The spatial pattern of phytoplankton community can indicate potential environmental variation in different water bodies. In this context, spatial pattern of phytoplankton community and its response to environmental and spatial factors were studied in the coastal waters of northern Zhejiang, East China Sea using multivariate statistical techniques. Results showed that 94 species belonging to 40 genera, 5 phyla were recorded (the remaining 9 were identified to genus level) with diatoms being the most dominant followed by dinoflagellates. Hierarchical clustering analysis (HCA), nonmetric multidimentional scaling (NMDS), and analysis of similarity (ANOSIM) all demomstrated that the whole study area could be divided into 3 subareas with significant differences. Indicator species analysis (ISA) further confirmed that the indicator species of each subarea correlated significantly with specific environmental factors. Distance-based linear model (Distlm) and Mantel test revealed that silicate (SiO32-), phosphate (PO43-), pH, and dissolved oxygen (DO) were the most important environmental factors influencing phytoplankton community. Variation portioning (VP) finally concluded that the shared fractions of environmental and spatial factors were higher than either the pure environmental effects or the pure spatial effects, suggesting phytoplankton biogeography were mainly affected by both the environmental variability and dispersal limitation. Additionally, other factors (eg., trace metals, biological grazing, climate change, and time-scale variation) may also be the sources of the unexplained variation which need further study.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jin, Ling; Harley, Robert A.; Brown, Nancy J.
Cluster analysis was applied to daily 8 h ozone maxima modeled for a summer season to characterize meteorology-induced variations in the spatial distribution of ozone. Principal component analysis is employed to form a reduced dimension set to describe and interpret ozone spatial patterns. The first three principal components (PCs) capture {approx}85% of total variance, with PC1 describing a general spatial trend, and PC2 and PC3 each describing a spatial contrast. Six clusters were identified for California's San Joaquin Valley (SJV) with two low, three moderate, and one high-ozone cluster. The moderate ozone clusters are distinguished by elevated ozone levels inmore » different parts of the valley: northern, western, and eastern, respectively. The SJV ozone clusters have stronger coupling with the San Francisco Bay area (SFB) than with the Sacramento Valley (SV). Variations in ozone spatial distributions induced by anthropogenic emission changes are small relative to the overall variations in ozone amomalies observed for the whole summer. Ozone regimes identified here are mostly determined by the direct and indirect meteorological effects. Existing measurement sites are sufficiently representative to capture ozone spatial patterns in the SFB and SV, but the western side of the SJV is under-sampled.« less
A space-time multiscale modelling of Earth's gravity field variations
NASA Astrophysics Data System (ADS)
Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric
2017-04-01
The mass distribution within the Earth varies over a wide range of spatial and temporal scales, generating variations in the Earth's gravity field in space and time. These variations are monitored by satellites as the GRACE mission, with a 400 km spatial resolution and 10 days to 1 month temporal resolution. They are expressed in the form of gravity field models, often with a fixed spatial or temporal resolution. The analysis of these models allows us to study the mass transfers within the Earth system. Here, we have developed space-time multi-scale models of the gravity field, in order to optimize the estimation of gravity signals resulting from local processes at different spatial and temporal scales, and to adapt the time resolution of the model to its spatial resolution according to the satellites sampling. For that, we first build a 4D wavelet family combining spatial Poisson wavelets with temporal Haar wavelets. Then, we set-up a regularized inversion of inter-satellites gravity potential differences in a bayesian framework, to estimate the model parameters. To build the prior, we develop a spectral analysis, localized in time and space, of geophysical models of mass transport and associated gravity variations. Finally, we test our approach to the reconstruction of space-time variations of the gravity field due to hydrology. We first consider a global distribution of observations along the orbit, from a simplified synthetic hydrology signal comprising only annual variations at large spatial scales. Then, we consider a regional distribution of observations in Africa, and a larger number of spatial and temporal scales. We test the influence of an imperfect prior and discuss our results.
Spatial and temporal temperature distribution optimization for a geostationary antenna
NASA Technical Reports Server (NTRS)
Tsuyuki, G.; Miyake, R.
1992-01-01
The Geostationary Microwave Precipitation Radiometer antenna is considered and a thermal design analysis is performed to determine a design that would minimize on-orbit antenna temporal and spatial temperature gradients. The final design is based on an optically opaque radome which covered the antenna. The average orbital antenna temperature is found to be 9 C with maximum temporal and spatial variations of 34 C and 1 C, respectively. An independent thermal distortion analysis showed that this temporal variation would give an antenna figure error of 14 microns.
Schistosomiasis Breeding Environment Situation Analysis in Dongting Lake Area
NASA Astrophysics Data System (ADS)
Li, Chuanrong; Jia, Yuanyuan; Ma, Lingling; Liu, Zhaoyan; Qian, Yonggang
2013-01-01
Monitoring environmental characteristics, such as vegetation, soil moisture et al., of Oncomelania hupensis (O. hupensis)’ spatial/temporal distribution is of vital importance to the schistosomiasis prevention and control. In this study, the relationship between environmental factors derived from remotely sensed data and the density of O. hupensis was analyzed by a multiple linear regression model. Secondly, spatial analysis of the regression residual was investigated by the semi-variogram method. Thirdly, spatial analysis of the regression residual and the multiple linear regression model were both employed to estimate the spatial variation of O. hupensis density. Finally, the approach was used to monitor and predict the spatial and temporal variations of oncomelania of Dongting Lake region, China. And the areas of potential O. hupensis habitats were predicted and the influence of Three Gorges Dam (TGB)project on the density of O. hupensis was analyzed.
Analysis of field-scale spatial correlations and variations of soil nutrients using geostatistics.
Liu, Ruimin; Xu, Fei; Yu, Wenwen; Shi, Jianhan; Zhang, Peipei; Shen, Zhenyao
2016-02-01
Spatial correlations and soil nutrient variations are important for soil nutrient management. They help to reduce the negative impacts of agricultural nonpoint source pollution. Based on the sampled available nitrogen (AN), available phosphorus (AP), and available potassium (AK), soil nutrient data from 2010, the spatial correlation, was analyzed, and the probabilities of the nutrient's abundance or deficiency were discussed. This paper presents a statistical approach to spatial analysis, the spatial correlation analysis (SCA), which was originally developed for describing heterogeneity in the presence of correlated variation and based on ordinary kriging (OK) results. Indicator kriging (IK) was used to assess the susceptibility of excess of soil nutrients based on crop needs. The kriged results showed there was a distinct spatial variability in the concentration of all three soil nutrients. High concentrations of these three soil nutrients were found near Anzhou. As the distance from the center of town increased, the concentration of the soil nutrients gradually decreased. Spatially, the relationship between AN and AP was negative, and the relationship between AP and AK was not clear. The IK results showed that there were few areas with a risk of AN and AP overabundance. However, almost the entire study region was at risk of AK overabundance. Based on the soil nutrient distribution results, it is clear that the spatial variability of the soil nutrients differed throughout the study region. This spatial soil nutrient variability might be caused by different fertilizer types and different fertilizing practices.
NASA Technical Reports Server (NTRS)
Roth, Don J.; Hepp, Aloysius F.; Deguire, Mark R.; Dolhert, Leonard E.
1991-01-01
The spatial (within-sample) uniformity of superconducting behavior and microstructure in YBa2Cu30(7-x) specimens over the pore fraction range of 0.10 to 0.25 was examined. The viability of using a room-temperature, nondestructive characterization method (ultrasonic velocity imaging) to predict spatial variability was determined. Spatial variations in superconductor properties were observed for specimens containing 0.10 pore fraction. An ultrasonic velocity image constructed from measurements at 1 mm increments across one such specimen revealed microstructural variation between edge and center locations that correlated with variations in alternating-current shielding and loss behavior. Optical quantitative image analysis on sample cross-sections revealed pore fraction to be the varying microstructural feature.
NASA Technical Reports Server (NTRS)
Roth, Don J.; Deguire, Mark R.; Dolhert, Leonard E.; Hepp, Aloysius F.
1991-01-01
The spatial (within-sample) uniformity of superconducting behavior and microstructure in YBa2Cu3O(7-x) specimens over the pore fraction range of 0.10 to 0.25 was examined. The viability of using a room-temperature, nondestructive characterization method (ultrasonic velocity imaging) to predict spatial variability was determined. Spatial variations in superconductor properties were observed for specimens containing 0.10 pore fraction. An ultrasonic velocity image constructed from measurements at 1 mm increments across one such specimen revealed microstructural variation between edge and center locations that correlated with variations in alternating-current shielding and loss behavior. Optical quantitative image analysis on sample cross-sections revealed pore fraction to be the varying microstructural feature.
NASA Astrophysics Data System (ADS)
Manikandan, M.; Tamilmani, D.
2015-09-01
The present study aims to investigate the spatial and temporal variation of meteorological drought in the Parambikulam-Aliyar basin, Tamil Nadu using the Standardized Precipitation Index (SPI) as an indicator of drought severity. The basin was divided into 97 grid-cells of 5 × 5 km with each grid correspondence to approximately 1.03 % of total area. Monthly rainfall data for the period of 40 years (1972-2011) from 28 rain gauge stations in the basin was spatially interpolated and gridded monthly rainfall was created. Regional representative of SPI values calculated from mean areal rainfall were used to analyse the temporal variation of drought at multiple time scales. Spatial variation of drought was analysed based on highest drought severity derived from the monthly gridded SPI values. Frequency analyse was applied to assess the recurrence pattern of drought severity. The temporal analysis of SPI indicated that moderate, severe and extreme droughts are common in the basin and spatial analysis of drought severity identified the areas most frequently affected by drought. The results of this study can be used for developing drought preparedness plan and formulating mitigation strategies for sustainable water resource management within the basin.
Cordova-Kreylos, A. L.; Cao, Y.; Green, P.G.; Hwang, H.-M.; Kuivila, K.M.; LaMontagne, M.G.; Van De Werfhorst, L. C.; Holden, P.A.; Scow, K.M.
2006-01-01
The Pacific Estuarine Ecosystem Indicators Research Consortium seeks to develop bioindicators of toxicant-induced stress and bioavailability for wetland biota. Within this framework, the effects of environmental and pollutant variables on microbial communities were studied at different spatial scales over a 2-year period. Six salt marshes along the California coastline were characterized using phospholipid fatty acid (PLFA) analysis and terminal restriction fragment length polymorphism (TRFLP) analysis. Additionally, 27 metals, six currently used pesticides, total polychlorinated biphenyls and polycyclic aromatic hydrocarbons, chlordanes, nonachlors, dichlorodiphenyldichloroethane, and dichlorodiphenyldichloroethylene were analyzed. Sampling was performed over large (between salt marshes), medium (stations within a marsh), and small (different channel depths) spatial scales. Regression and ordination analysis suggested that the spatial variation in microbial communities exceeded the variation attributable to pollutants. PLFA analysis and TRFLP canonical correspondence analysis (CCA) explained 74 and 43% of the variation, respectively, and both methods attributed 34% of the variation to tidal cycles, marsh, year, and latitude. After accounting for spatial variation using partial CCA, we found that metals had a greater effect on microbial community composition than organic pollutants had. Organic carbon and nitrogen contents were positively correlated with PLFA biomass, whereas total metal concentrations were positively correlated with biomass and diversity. Higher concentrations of heavy metals were negatively correlated with branched PLFAs and positively correlated with methyl- and cyclo-substituted PLFAs. The strong relationships observed between pollutant concentrations and some of the microbial indicators indicated the potential for using microbial community analyses in assessments of the ecosystem health of salt marshes. Copyright ?? 2006, American Society for Microbiology. All Rights Reserved.
Córdova-Kreylos, Ana Lucía; Cao, Yiping; Green, Peter G.; Hwang, Hyun-Min; Kuivila, Kathryn M.; LaMontagne, Michael G.; Van De Werfhorst, Laurie C.; Holden, Patricia A.; Scow, Kate M.
2006-01-01
The Pacific Estuarine Ecosystem Indicators Research Consortium seeks to develop bioindicators of toxicant-induced stress and bioavailability for wetland biota. Within this framework, the effects of environmental and pollutant variables on microbial communities were studied at different spatial scales over a 2-year period. Six salt marshes along the California coastline were characterized using phospholipid fatty acid (PLFA) analysis and terminal restriction fragment length polymorphism (TRFLP) analysis. Additionally, 27 metals, six currently used pesticides, total polychlorinated biphenyls and polycyclic aromatic hydrocarbons, chlordanes, nonachlors, dichlorodiphenyldichloroethane, and dichlorodiphenyldichloroethylene were analyzed. Sampling was performed over large (between salt marshes), medium (stations within a marsh), and small (different channel depths) spatial scales. Regression and ordination analysis suggested that the spatial variation in microbial communities exceeded the variation attributable to pollutants. PLFA analysis and TRFLP canonical correspondence analysis (CCA) explained 74 and 43% of the variation, respectively, and both methods attributed 34% of the variation to tidal cycles, marsh, year, and latitude. After accounting for spatial variation using partial CCA, we found that metals had a greater effect on microbial community composition than organic pollutants had. Organic carbon and nitrogen contents were positively correlated with PLFA biomass, whereas total metal concentrations were positively correlated with biomass and diversity. Higher concentrations of heavy metals were negatively correlated with branched PLFAs and positively correlated with methyl- and cyclo-substituted PLFAs. The strong relationships observed between pollutant concentrations and some of the microbial indicators indicated the potential for using microbial community analyses in assessments of the ecosystem health of salt marshes. PMID:16672478
Xu, Henglong; Jiang, Yong; Xu, Guangjian
2016-11-15
Body-size spectra has proved to be a useful taxon-free resolution to summarize a community structure for bioassessment. The spatial variations in annual cycles of body-size spectra of planktonic ciliates and their environmental drivers were studied based on an annual dataset. Samples were biweekly collected at five stations in a bay of the Yellow Sea, northern China during a 1-year cycle. Based on a multivariate approach, the second-stage analysis, it was shown that the annual cycles of the body-size spectra were significantly different among five sampling stations. Correlation analysis demonstrated that the spatial variations in the body-size spectra were significantly related to changes of environmental conditions, especially dissolved nitrogen, alone or in combination with salinity and dissolve oxygen. Based on results, it is suggested that the nutrients may be the environmental drivers to shape the spatial variations in annual cycles of planktonic ciliates in terms of body-size spectra in marine ecosystems. Copyright © 2016 Elsevier Ltd. All rights reserved.
Chen, Zhi; Yu, Guirui; Ge, Jianping; Wang, Qiufeng; Zhu, Xianjin; Xu, Zhiwei
2015-01-01
Climate, vegetation, and soil characteristics play important roles in regulating the spatial variation in carbon dioxide fluxes, but their relative influence is still uncertain. In this study, we compiled data from 241 eddy covariance flux sites in the Northern Hemisphere and used Classification and Regression Trees and Redundancy Analysis to assess how climate, vegetation, and soil affect the spatial variations in three carbon dioxide fluxes (annual gross primary production (AGPP), annual ecosystem respiration (ARE), and annual net ecosystem production (ANEP)). Our results showed that the spatial variations in AGPP, ARE, and ANEP were significantly related to the climate and vegetation factors (correlation coefficients, R = 0.22 to 0.69, P < 0.01) while they were not related to the soil factors (R = -0.11 to 0.14, P > 0.05) in the Northern Hemisphere. The climate and vegetation together explained 60% and 58% of the spatial variations in AGPP and ARE, respectively. Climate factors (mean annual temperature and precipitation) could account for 45-47% of the spatial variations in AGPP and ARE, but the climate constraint on the vegetation index explained approximately 75%. Our findings suggest that climate factors affect the spatial variations in AGPP and ARE mainly by regulating vegetation properties, while soil factors exert a minor effect. To more accurately assess global carbon balance and predict ecosystem responses to climate change, these discrepant roles of climate, vegetation, and soil are required to be fully considered in the future land surface models. Moreover, our results showed that climate and vegetation factors failed to capture the spatial variation in ANEP and suggest that to reveal the underlying mechanism for variation in ANEP, taking into account the effects of other factors (such as climate change and disturbances) is necessary.
Jones, Mirkka M; Tuomisto, Hanna; Borcard, Daniel; Legendre, Pierre; Clark, David B; Olivas, Paulo C
2008-03-01
The degree to which variation in plant community composition (beta-diversity) is predictable from environmental variation, relative to other spatial processes, is of considerable current interest. We addressed this question in Costa Rican rain forest pteridophytes (1,045 plots, 127 species). We also tested the effect of data quality on the results, which has largely been overlooked in earlier studies. To do so, we compared two alternative spatial models [polynomial vs. principal coordinates of neighbour matrices (PCNM)] and ten alternative environmental models (all available environmental variables vs. four subsets, and including their polynomials vs. not). Of the environmental data types, soil chemistry contributed most to explaining pteridophyte community variation, followed in decreasing order of contribution by topography, soil type and forest structure. Environmentally explained variation increased moderately when polynomials of the environmental variables were included. Spatially explained variation increased substantially when the multi-scale PCNM spatial model was used instead of the traditional, broad-scale polynomial spatial model. The best model combination (PCNM spatial model and full environmental model including polynomials) explained 32% of pteridophyte community variation, after correcting for the number of sampling sites and explanatory variables. Overall evidence for environmental control of beta-diversity was strong, and the main floristic gradients detected were correlated with environmental variation at all scales encompassed by the study (c. 100-2,000 m). Depending on model choice, however, total explained variation differed more than fourfold, and the apparent relative importance of space and environment could be reversed. Therefore, we advocate a broader recognition of the impacts that data quality has on analysis results. A general understanding of the relative contributions of spatial and environmental processes to species distributions and beta-diversity requires that methodological artefacts are separated from real ecological differences.
Chen, Zhi; Yu, Guirui; Ge, Jianping; Wang, Qiufeng; Zhu, Xianjin; Xu, Zhiwei
2015-01-01
Climate, vegetation, and soil characteristics play important roles in regulating the spatial variation in carbon dioxide fluxes, but their relative influence is still uncertain. In this study, we compiled data from 241 eddy covariance flux sites in the Northern Hemisphere and used Classification and Regression Trees and Redundancy Analysis to assess how climate, vegetation, and soil affect the spatial variations in three carbon dioxide fluxes (annual gross primary production (AGPP), annual ecosystem respiration (ARE), and annual net ecosystem production (ANEP)). Our results showed that the spatial variations in AGPP, ARE, and ANEP were significantly related to the climate and vegetation factors (correlation coefficients, R = 0.22 to 0.69, P < 0.01) while they were not related to the soil factors (R = -0.11 to 0.14, P > 0.05) in the Northern Hemisphere. The climate and vegetation together explained 60 % and 58 % of the spatial variations in AGPP and ARE, respectively. Climate factors (mean annual temperature and precipitation) could account for 45 - 47 % of the spatial variations in AGPP and ARE, but the climate constraint on the vegetation index explained approximately 75 %. Our findings suggest that climate factors affect the spatial variations in AGPP and ARE mainly by regulating vegetation properties, while soil factors exert a minor effect. To more accurately assess global carbon balance and predict ecosystem responses to climate change, these discrepant roles of climate, vegetation, and soil are required to be fully considered in the future land surface models. Moreover, our results showed that climate and vegetation factors failed to capture the spatial variation in ANEP and suggest that to reveal the underlying mechanism for variation in ANEP, taking into account the effects of other factors (such as climate change and disturbances) is necessary. PMID:25928452
Huang, Jinliang; Huang, Yaling; Zhang, Zhenyu
2014-01-01
Surface water samples of baseflow were collected from 20 headwater sub-watersheds which were classified into three types of watersheds (natural, urban and agricultural) in the flood, dry and transition seasons during three consecutive years (2010–2012) within a coastal watershed of Southeast China. Integrating spatial statistics with multivariate statistical techniques, river water quality variations and their interactions with natural and anthropogenic controls were examined to identify the causal factors and underlying mechanisms governing spatiotemporal patterns of water quality. Anthropogenic input related to industrial effluents and domestic wastewater, agricultural activities associated with the precipitation-induced surface runoff, and natural weathering process were identified as the potential important factors to drive the seasonal variations in stream water quality for the transition, flood and dry seasons, respectively. All water quality indicators except SRP had the highest mean concentrations in the dry and transition seasons. Anthropogenic activities and watershed characteristics led to the spatial variations in stream water quality in three types of watersheds. Concentrations of NH4 +-N, SRP, K+, CODMn, and Cl− were generally highest in urban watersheds. NO3 –N Concentration was generally highest in agricultural watersheds. Mg2+ concentration in natural watersheds was significantly higher than that in agricultural watersheds. Spatial autocorrelations analysis showed similar levels of water pollution between the neighboring sub-watersheds exhibited in the dry and transition seasons while non-point source pollution contributed to the significant variations in water quality between neighboring sub-watersheds. Spatial regression analysis showed anthropogenic controls played critical roles in variations of water quality in the JRW. Management implications were further discussed for water resource management. This research demonstrates that the coupled effects of natural and anthropogenic controls involved in watershed processes, contribute to the seasonal and spatial variation of headwater stream water quality in a coastal watershed with high spatial variability and intensive anthropogenic activities. PMID:24618771
Using a spatially explicit analysis model to evaluate spatial variation of corn yield
USDA-ARS?s Scientific Manuscript database
Spatial irrigation of agricultural crops using site-specific variable-rate irrigation (VRI) systems is beginning to have wide-spread acceptance. However, optimizing the management of these VRI systems to conserve natural resources and increase profitability requires an understanding of the spatial ...
2007-09-30
secondary gap outflow that appeared in COAMPS simulations ( Cherrett 2006). Figure 3d shows similar SST spatial variations as in Fig. 3c with slight... Cherrett , R. C. 2006: Observed and Simulated temporal and spatial variations of the gap outflow region, M.S. Thesis, Meteorology Department, Naval
Spatial variability effects on precision and power of forage yield estimation
USDA-ARS?s Scientific Manuscript database
Spatial analyses of yield trials are important, as they adjust cultivar means for spatial variation and improve the statistical precision of yield estimation. While the relative efficiency of spatial analysis has been frequently reported in several yield trials, its application on long-term forage y...
Geographic variations of ecosystem service intensity in Fuzhou City, China.
Hu, Xisheng; Hong, Wei; Qiu, Rongzu; Hong, Tao; Chen, Can; Wu, Chengzhen
2015-04-15
Ecosystem services are strongly influenced by the landscape configuration of natural and human systems. So they are heterogeneous across landscapes. However lack of the knowledge of spatial variations of ecosystem services constrains the effective management and conservation of ecosystems. We presented a spatially explicit and quantitative assessment of the geographic variations in ecosystem services for the Fuzhou City in 2009 using exploratory spatial data analysis (ESDA) and semivariance analysis. Results confirmed a significant and positive spatial autocorrelation, and revealed several hot-spots and cold-spots for the spatial distribution of ecosystem service intensity (ESI) in the study area. Also the trend surface analysis indicated that the level of ESI tended to be reduced gradually from north to south and from west to east, with a trough in the urban central area, which was quite in accordance with land-use structure. A more precise cluster map was then developed using the range of lag distance, deriving from semivariance analysis, as neighborhood size instead of default value in the software of ESRI ArcGIS 10.0, and geographical clusters where population growth and land-use pressure varied significantly and positively with ESI across the city were also created by geographically weighted regression (GWR). This study has good policy implications applicable to prioritize areas for conservation or construction, and design ecological corridor to improve ecosystem service delivery to benefiting areas. Copyright © 2015 Elsevier B.V. All rights reserved.
A comparison of small-area hospitalisation rates, estimated morbidity and hospital access.
Shulman, H; Birkin, M; Clarke, G P
2015-11-01
Published data on hospitalisation rates tend to reveal marked spatial variations within a city or region. Such variations may simply reflect corresponding variations in need at the small-area level. However, they might also be a consequence of poorer accessibility to medical facilities for certain communities within the region. To help answer this question it is important to compare these variable hospitalisation rates with small-area estimates of need. This paper first maps hospitalisation rates at the small-area level across the region of Yorkshire in the UK to show the spatial variations present. Then the Health Survey of England is used to explore the characteristics of persons with heart disease, using chi-square and logistic regression analysis. Using the most significant variables from this analysis the authors build a spatial microsimulation model of morbidity for heart disease for the Yorkshire region. We then compare these estimates of need with the patterns of hospitalisation rates seen across the region. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.
Griffiths, Natalie A.; Hanson, Paul J.; Ricciuto, Daniel M.; ...
2017-11-22
Here, we are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO 2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determinemore » if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m –2 yr –1 to a sink of 67 g C m –2 yr –1. Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO 2 treatments.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Griffiths, Natalie A.; Hanson, Paul J.; Ricciuto, Daniel M.
Here, we are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO 2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determinemore » if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m –2 yr –1 to a sink of 67 g C m –2 yr –1. Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO 2 treatments.« less
Kuehnl, Andreas; Salvermoser, Michael; Erk, Alexander; Trenner, Matthias; Schmid, Volker; Eckstein, Hans-Henning
2018-06-01
This study aimed to analyze the spatial distribution and regional variation of the hospital incidence and in hospital mortality of abdominal aortic aneurysms (AAA) in Germany. German DRG statistics (2011-2014) were analysed. Patients with ruptured AAA (rAAA, I71.3, treated or not) and patients with non-ruptured AAA (nrAAA, I71.4, treated by open or endovascular aneurysm repair) were included. Age, sex, and risk standardisation was done using standard statistical procedures. Regional variation was quantified using systematic component of variation. To analyse spatial auto-correlation and spatial pattern, global Moran's I and Getis-Ord Gi* were calculated. A total of 50,702 cases were included. Raw hospital incidence of AAA was 15.7 per 100,000 inhabitants (nrAAA 13.1; all rAAA 2.7; treated rAAA 1.6). The standardised hospital incidence of AAA ranged from 6.3 to 30.3 per 100,000. Systematic component of variation proportion was 96% in nrAAA and 55% in treated rAAA. Incidence rates of all AAA were significantly clustered with above average values in the northwestern parts of Germany and below average values in the south and eastern regions. Standardised mortality of nrAAA ranged from 1.7% to 4.3%, with that of treated rAAA ranging from 28% to 52%. Regional variation and spatial distribution of standardised mortality was not different from random. There was significant regional variation and clustering of the hospital incidence of AAA in Germany, with higher rates in the northwest and lower rates in the southeast. There was no significant variation in standardised (age/sex/risk) mortality between counties. Copyright © 2018. Published by Elsevier B.V.
NASA Astrophysics Data System (ADS)
Barette, Florian; Poppe, Sam; Smets, Benoît; Benbakkar, Mhammed; Kervyn, Matthieu
2017-10-01
We present an integrated, spatially-explicit database of existing geochemical major-element analyses available from (post-) colonial scientific reports, PhD Theses and international publications for the Virunga Volcanic Province, located in the western branch of the East African Rift System. This volcanic province is characterised by alkaline volcanism, including silica-undersaturated, alkaline and potassic lavas. The database contains a total of 908 geochemical analyses of eruptive rocks for the entire volcanic province with a localisation for most samples. A preliminary analysis of the overall consistency of the database, using statistical techniques on sets of geochemical analyses with contrasted analytical methods or dates, demonstrates that the database is consistent. We applied a principal component analysis and cluster analysis on whole-rock major element compositions included in the database to study the spatial variation of the chemical composition of eruptive products in the Virunga Volcanic Province. These statistical analyses identify spatially distributed clusters of eruptive products. The known geochemical contrasts are highlighted by the spatial analysis, such as the unique geochemical signature of Nyiragongo lavas compared to other Virunga lavas, the geochemical heterogeneity of the Bulengo area, and the trachyte flows of Karisimbi volcano. Most importantly, we identified separate clusters of eruptive products which originate from primitive magmatic sources. These lavas of primitive composition are preferentially located along NE-SW inherited rift structures, often at distance from the central Virunga volcanoes. Our results illustrate the relevance of a spatial analysis on integrated geochemical data for a volcanic province, as a complement to classical petrological investigations. This approach indeed helps to characterise geochemical variations within a complex of magmatic systems and to identify specific petrologic and geochemical investigations that should be tackled within a study area.
Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep
2015-05-01
The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.
Zulu, Leo C; Kalipeni, Ezekiel; Johannes, Eliza
2014-05-23
Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi's estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across 'sub-epidemics' while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV "hotspots" clustered among eleven southern districts/cities while a "coldspot" captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale.
2014-01-01
Background Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi’s estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Methods Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Results Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across ‘sub-epidemics’ while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV “hotspots” clustered among eleven southern districts/cities while a “coldspot” captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Conclusions Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale. PMID:24886573
Huang, Ni; Wang, Li; Hu, Yongsen; Tian, Haifeng; Niu, Zheng
2016-01-01
Spatial variation of soil respiration (Rs) in cropland ecosystems must be assessed to evaluate the global terrestrial carbon budget. This study aims to explore the spatial characteristics and controlling factors of Rs in a cropland under winter wheat and summer maize rotation in the North China Plain. We collected Rs data from 23 sample plots in the cropland. At the late jointing stage, the daily mean Rs of summer maize (4.74 μmol CO2 m-2 s-1) was significantly higher than that of winter wheat (3.77μmol CO2 m-2 s-1). However, the spatial variation of Rs in summer maize (coefficient of variation, CV = 12.2%) was lower than that in winter wheat (CV = 18.5%). A similar trend in CV was also observed for environmental factors but not for biotic factors, such as leaf area index, aboveground biomass, and canopy chlorophyll content. Pearson's correlation analyses based on the sampling data revealed that the spatial variation of Rs was poorly explained by the spatial variations of biotic factors, environmental factors, or soil properties alone for winter wheat and summer maize. The similarly non-significant relationship was observed between Rs and the enhanced vegetation index (EVI), which was used as surrogate for plant photosynthesis. EVI was better correlated with field-measured leaf area index than the normalized difference vegetation index and red edge chlorophyll index. All the data from the 23 sample plots were categorized into three clusters based on the cluster analysis of soil carbon/nitrogen and soil organic carbon content. An apparent improvement was observed in the relationship between Rs and EVI in each cluster for both winter wheat and summer maize. The spatial variation of Rs in the cropland under winter wheat and summer maize rotation could be attributed to the differences in spatial variations of soil properties and biotic factors. The results indicate that applying cluster analysis to minimize differences in soil properties among different clusters can improve the role of remote sensing data as a proxy of plant photosynthesis in semi-empirical Rs models and benefit the acquisition of Rs in cropland ecosystems at large scales.
Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer.
Pacheco Castro, Roger; Pacheco Ávila, Julia; Ye, Ming; Cabrera Sansores, Armando
2018-01-01
This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box-plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously. © 2017, National Ground Water Association.
Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis
NASA Technical Reports Server (NTRS)
Guseman, L. F., Jr.
1985-01-01
Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.
NASA Astrophysics Data System (ADS)
Kodama, Taketoshi; Wagawa, Taku; Iguchi, Naoki; Takada, Yoshitake; Takahashi, Takashi; Fukudome, Ken-Ichi; Morimoto, Haruyuki; Goto, Tsuneo
2018-06-01
This study evaluates spatial variations in zooplankton community structure and potential controlling factors along the Japanese coast under the influence of the coastal branch of the Tsushima Warm Current (CBTWC). Variations in the density of morphologically identified zooplankton in the surface layer in May were investigated for a 15-year period. The density of zooplankton (individuals per cubic meter) varied between sampling stations, but there was no consistent west-east trend. Instead, there were different zooplankton community structures in the west and east, with that in Toyama Bay particularly distinct: Corycaeus affinis and Calanus sinicus were dominant in the west and Oithona atlantica was dominant in Toyama Bay. Distance-based redundancy analysis (db-RDA) was used to characterize the variation in zooplankton community structure, and four axes (RD1-4) provided significant explanation. RD2-4 only explained < 4.8 % of variation in the zooplankton community and did not show significant spatial difference; however, RD1, which explained 89.9 % of variation, did vary spatially. Positive and negative species scores on RD1 represent warm- and cold-water species, respectively, and their variation was mainly explained by water column mean temperature, and it is considered to vary spatially with the CBTWC. The CBTWC intrusion to the cold Toyama Bay is weak and occasional due to the submarine canyon structure of the bay. Therefore, the varying bathymetric characteristics along the Japanese coast of the Japan Sea generate the spatial variation in zooplankton community structure, and dominance of warm-water species can be considered an indicator of the CBTWC.
Terán-Hernández, Mónica; Ramis-Prieto, Rebeca; Calderón-Hernández, Jaqueline; Garrocho-Rangel, Carlos Félix; Campos-Alanís, Juan; Ávalos-Lozano, José Antonio; Aguilar-Robledo, Miguel
2016-09-29
Worldwide, Cervical Cancer (CC) is the fourth most common type of cancer and cause of death in women. It is a significant public health problem, especially in low and middle-income/Gross Domestic Product (GDP) countries. In the past decade, several studies of CC have been published, that identify the main modifiable and non-modifiable CC risk factors for Mexican women. However, there are no studies that attempt to explain the residual spatial variation in CC incidence In Mexico, i.e. spatial variation that cannot be ascribed to known, spatially varying risk factors. This paper uses a spatial statistical methodology that takes into account spatial variation in socio-economic factors and accessibility to health services, whilst allowing for residual, unexplained spatial variation in risk. To describe residual spatial variations in CC risk, we used generalised linear mixed models (GLMM) with both spatially structured and unstructured random effects, using a Bayesian approach to inference. The highest risk is concentrated in the southeast, where the Matlapa and Aquismón municipalities register excessive risk, with posterior probabilities greater than 0.8. The lack of coverage of Cervical Cancer-Screening Programme (CCSP) (RR 1.17, 95 % CI 1.12-1.22), Marginalisation Index (RR 1.05, 95 % CI 1.03-1.08), and lack of accessibility to health services (RR 1.01, 95 % CI 1.00-1.03) were significant covariates. There are substantial differences between municipalities, with high-risk areas mainly in low-resource areas lacking accessibility to health services for CC. Our results clearly indicate the presence of spatial patterns, and the relevance of the spatial analysis for public health intervention. Ignoring the spatial variability means to continue a public policy that does not tackle deficiencies in its national CCSP and to keep disadvantaging and disempowering Mexican women in regard to their health care.
Variability of Soil Temperature: A Spatial and Temporal Analysis.
ERIC Educational Resources Information Center
Walsh, Stephen J.; And Others
1991-01-01
Discusses an analysis of the relationship of soil temperatures at 3 depths to various climatic variables along a 200-kilometer transect in west-central Oklahoma. Reports that temperature readings increased from east to west. Concludes that temperature variations were explained by a combination of spatial, temporal, and biophysical factors. (SG)
Heino, Jani; Melo, Adriano S; Bini, Luis Mauricio; Altermatt, Florian; Al-Shami, Salman A; Angeler, David G; Bonada, Núria; Brand, Cecilia; Callisto, Marcos; Cottenie, Karl; Dangles, Olivier; Dudgeon, David; Encalada, Andrea; Göthe, Emma; Grönroos, Mira; Hamada, Neusa; Jacobsen, Dean; Landeiro, Victor L; Ligeiro, Raphael; Martins, Renato T; Miserendino, María Laura; Md Rawi, Che Salmah; Rodrigues, Marciel E; Roque, Fabio de Oliveira; Sandin, Leonard; Schmera, Denes; Sgarbi, Luciano F; Simaika, John P; Siqueira, Tadeu; Thompson, Ross M; Townsend, Colin R
2015-03-01
The hypotheses that beta diversity should increase with decreasing latitude and increase with spatial extent of a region have rarely been tested based on a comparative analysis of multiple datasets, and no such study has focused on stream insects. We first assessed how well variability in beta diversity of stream insect metacommunities is predicted by insect group, latitude, spatial extent, altitudinal range, and dataset properties across multiple drainage basins throughout the world. Second, we assessed the relative roles of environmental and spatial factors in driving variation in assemblage composition within each drainage basin. Our analyses were based on a dataset of 95 stream insect metacommunities from 31 drainage basins distributed around the world. We used dissimilarity-based indices to quantify beta diversity for each metacommunity and, subsequently, regressed beta diversity on insect group, latitude, spatial extent, altitudinal range, and dataset properties (e.g., number of sites and percentage of presences). Within each metacommunity, we used a combination of spatial eigenfunction analyses and partial redundancy analysis to partition variation in assemblage structure into environmental, shared, spatial, and unexplained fractions. We found that dataset properties were more important predictors of beta diversity than ecological and geographical factors across multiple drainage basins. In the within-basin analyses, environmental and spatial variables were generally poor predictors of variation in assemblage composition. Our results revealed deviation from general biodiversity patterns because beta diversity did not show the expected decreasing trend with latitude. Our results also call for reconsideration of just how predictable stream assemblages are along ecological gradients, with implications for environmental assessment and conservation decisions. Our findings may also be applicable to other dynamic systems where predictability is low.
Environment-dependent variation in selection on life history across small spatial scales.
Lange, Rolanda; Monro, Keyne; J Marshall, Dustin
2016-10-01
Variation in life-history traits is ubiquitous, even though genetic variation is thought to be depleted by selection. One potential mechanism for the maintenance of trait variation is spatially variable selection. We explored spatial variation in selection in the field for a colonial marine invertebrate that shows phenotypic differences across a depth gradient of only 3 m. Our analysis included life-history traits relating to module size, colony growth, and phenology. Directional selection on colony growth varied in strength across depths, while module size was under directional selection at one depth but not the other. Differences in selection may explain some of the observed phenotypic differentiation among depths for one trait but not another: instead, selection should actually erode the differences observed for this trait. Our results suggest selection is not acting alone to maintain trait variation within and across environments in this system. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.
Hoffman, Kate; Aschengrau, Ann; Webster, Thomas F; Bartell, Scott M; Vieira, Verónica M
2015-07-21
Mental health disorders impact approximately one in four US adults. While their causes are likely multifactorial, prior research has linked the risk of certain mental health disorders to prenatal and early childhood environmental exposures, motivating a spatial analysis to determine whether risk varies by birth location. We investigated the spatial associations between residence at birth and odds of depression, bipolar disorder, and post-traumatic stress disorder (PTSD) in a retrospective cohort (Cape Cod, Massachusetts, 1969-1983) using generalized additive models to simultaneously smooth location and adjust for confounders. Birth location served as a surrogate for prenatal exposure to the combination of social and environmental factors related to the development of mental illness. We predicted crude and adjusted odds ratios (aOR) for each outcome across the study area. The results were mapped to identify areas of increased risk. We observed spatial variation in the crude odds ratios of depression that was still present even after accounting for spatial confounding due to geographic differences in the distribution of known risk factors (aOR range: 0.61-3.07, P = 0.03). Similar geographic patterns were seen for the crude odds of PTSD; however, these patterns were no longer present in the adjusted analysis (aOR range: 0.49-1.36, P = 0.79), with family history of mental illness most notably influencing the geographic patterns. Analyses of the odds of bipolar disorder did not show any meaningful spatial variation (aOR range: 0.58-1.17, P = 0.82). Spatial associations exist between residence at birth and odds of PTSD and depression, but much of this variation can be explained by the geographic distributions of available risk factors. However, these risk factors did not account for all the variation observed with depression, suggesting that other social and environmental factors within our study area need further investigation.
The methane distribution on Titan: high resolution spectroscopy in the near-IR with Keck NIRSPEC/AO
NASA Astrophysics Data System (ADS)
Adamkovics, Mate; Mitchell, Jonathan L.
2014-11-01
The distribution of methane on Titan is a diagnostic of regional scale meteorology and large scale atmospheric circulation. The observed formation of clouds and the transport of heat through the atmosphere both depend on spatial and temporal variations in methane humidity. We have performed observations to measure the the distribution on methane Titan using high spectral resolution near-IR (H-band) observations made with NIRSPEC, with adaptive optics, at Keck Observatory in July 2014. This work builds on previous attempts at this measurement with improvement in the observing protocol and data reduction, together with increased integration times. Radiative transfer models using line-by-line calculation of methane opacities from the HITRAN2012 database are used to retrieve methane abundances. We will describe analysis of the reduced observations, which show latitudinal spatial variation in the region the spectrum that is thought to be sensitive to methane abundance. Quantifying the methane abundance variation requires models that include the spatial variation in surface albedo and meridional haze gradient; we will describe (currently preliminary) analysis of the the methane distribution and uncertainties in the retrieval.
Algorithm for Identifying Erroneous Rain-Gauge Readings
NASA Technical Reports Server (NTRS)
Rickman, Doug
2005-01-01
An algorithm analyzes rain-gauge data to identify statistical outliers that could be deemed to be erroneous readings. Heretofore, analyses of this type have been performed in burdensome manual procedures that have involved subjective judgements. Sometimes, the analyses have included computational assistance for detecting values falling outside of arbitrary limits. The analyses have been performed without statistically valid knowledge of the spatial and temporal variations of precipitation within rain events. In contrast, the present algorithm makes it possible to automate such an analysis, makes the analysis objective, takes account of the spatial distribution of rain gauges in conjunction with the statistical nature of spatial variations in rainfall readings, and minimizes the use of arbitrary criteria. The algorithm implements an iterative process that involves nonparametric statistics.
Modeling spatial variation in avian survival and residency probabilities
Saracco, James F.; Royle, J. Andrew; DeSante, David F.; Gardner, Beth
2010-01-01
The importance of understanding spatial variation in processes driving animal population dynamics is widely recognized. Yet little attention has been paid to spatial modeling of vital rates. Here we describe a hierarchical spatial autoregressive model to provide spatially explicit year-specific estimates of apparent survival (phi) and residency (pi) probabilities from capture-recapture data. We apply the model to data collected on a declining bird species, Wood Thrush (Hylocichla mustelina), as part of a broad-scale bird-banding network, the Monitoring Avian Productivity and Survivorship (MAPS) program. The Wood Thrush analysis showed variability in both phi and pi among years and across space. Spatial heterogeneity in residency probability was particularly striking, suggesting the importance of understanding the role of transients in local populations. We found broad-scale spatial patterning in Wood Thrush phi and pi that lend insight into population trends and can direct conservation and research. The spatial model developed here represents a significant advance over approaches to investigating spatial pattern in vital rates that aggregate data at coarse spatial scales and do not explicitly incorporate spatial information in the model. Further development and application of hierarchical capture-recapture models offers the opportunity to more fully investigate spatiotemporal variation in the processes that drive population changes.
Mapping the Risk of Soil-Transmitted Helminthic Infections in the Philippines
Leonardo, Lydia; Gray, Darren J.; Carabin, Hélène; Halton, Kate; McManus, Donald P.; Williams, Gail M.; Rivera, Pilarita; Saniel, Ofelia; Hernandez, Leda; Yakob, Laith; McGarvey, Stephen T.; Clements, Archie C. A.
2015-01-01
Background In order to increase the efficient allocation of soil-transmitted helminth (STH) disease control resources in the Philippines, we aimed to describe for the first time the spatial variation in the prevalence of A. lumbricoides, T. trichiura and hookworm across the country, quantify the association between the physical environment and spatial variation of STH infection and develop predictive risk maps for each infection. Methodology/Principal Findings Data on STH infection from 35,573 individuals across the country were geolocated at the barangay level and included in the analysis. The analysis was stratified geographically in two major regions: 1) Luzon and the Visayas and 2) Mindanao. Bayesian geostatistical models of STH prevalence were developed, including age and sex of individuals and environmental variables (rainfall, land surface temperature and distance to inland water bodies) as predictors, and diagnostic uncertainty was incorporated. The role of environmental variables was different between regions of the Philippines. This analysis revealed that while A. lumbricoides and T. trichiura infections were widespread and highly endemic, hookworm infections were more circumscribed to smaller foci in the Visayas and Mindanao. Conclusions/Significance This analysis revealed significant spatial variation in STH infection prevalence within provinces of the Philippines. This suggests that a spatially targeted approach to STH interventions, including mass drug administration, is warranted. When financially possible, additional STH surveys should be prioritized to high-risk areas identified by our study in Luzon. PMID:26368819
Sequential analysis of hydrochemical data for watershed characterization.
Thyne, Geoffrey; Güler, Cüneyt; Poeter, Eileen
2004-01-01
A methodology for characterizing the hydrogeology of watersheds using hydrochemical data that combine statistical, geochemical, and spatial techniques is presented. Surface water and ground water base flow and spring runoff samples (180 total) from a single watershed are first classified using hierarchical cluster analysis. The statistical clusters are analyzed for spatial coherence confirming that the clusters have a geological basis corresponding to topographic flowpaths and showing that the fractured rock aquifer behaves as an equivalent porous medium on the watershed scale. Then principal component analysis (PCA) is used to determine the sources of variation between parameters. PCA analysis shows that the variations within the dataset are related to variations in calcium, magnesium, SO4, and HCO3, which are derived from natural weathering reactions, and pH, NO3, and chlorine, which indicate anthropogenic impact. PHREEQC modeling is used to quantitatively describe the natural hydrochemical evolution for the watershed and aid in discrimination of samples that have an anthropogenic component. Finally, the seasonal changes in the water chemistry of individual sites were analyzed to better characterize the spatial variability of vertical hydraulic conductivity. The integrated result provides a method to characterize the hydrogeology of the watershed that fully utilizes traditional data.
Craniofacial plasticity in ancient Peru.
Stone, Jessica H; Chew, Kristen; Ross, Ann H; Verano, John W
2015-01-01
Numerous studies have utilized craniometric data to explore the roles of genetic diversity and environment in human cranial shape variation. Peru is a particularly interesting region to examine cranial variation due to the wide variety of high and low altitude ecological zones, which in combination with rugged terrain have created isolated populations with vastly different physiological adaptations. This study examines seven samples from throughout Peru in an effort to understand the contributions of environmental adaptation and genetic relatedness to craniofacial variation at a regional scale. Morphological variation was investigated using a canonical discriminant analysis and Mahalanobis D(2) analysis. Results indicate that all groups are significantly different from one another with the closest relationship between Yauyos and Jahuay, two sites that are located geographically close in central Peru but in very different ecozones. The relationship between latitude/longitude and face shape was also examined with a spatial autocorrelation analysis (Moran's I) using ArcMap and show that there is significant spatial patterning for facial measures and geographic location suggesting that there is an association between biological variation and geographic location.
NASA Astrophysics Data System (ADS)
Liu, Meixian; Xu, Xianli; Sun, Alex
2015-07-01
Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.
Analysis of Local Variations in Free Field Seismic Ground Motion.
1981-01-01
analysis) can conveniently account for material damping through the introduction of complex moduli into the equations of motion. This method can...determined, and the total response is obtained by superposition. This technique, however, can not properly account for the spatial variation of damping...2.9. Most available data only consider the variation of shear modulus and damping ratio with shear strain amplitude. In principle , two moduli and two
Gover, Bradford N; Ryan, James G; Stinson, Michael R
2002-11-01
A measurement system has been developed that is capable of analyzing the directional and spatial variations in a reverberant sound field. A spherical, 32-element array of microphones is used to generate a narrow beam that is steered in 60 directions. Using an omnidirectional loudspeaker as excitation, the sound pressure arriving from each steering direction is measured as a function of time, in the form of pressure impulse responses. By subsequent analysis of these responses, the variation of arriving energy with direction is studied. The directional diffusion and directivity index of the arriving sound can be computed, as can the energy decay rate in each direction. An analysis of the 32 microphone responses themselves allows computation of the point-to-point variation of reverberation time and of sound pressure level, as well as the spatial cross-correlation coefficient, over the extent of the array. The system has been validated in simple sound fields in an anechoic chamber and in a reverberation chamber. The system characterizes these sound fields as expected, both quantitatively from the measures and qualitatively from plots of the arriving energy versus direction. It is anticipated that the system will be of value in evaluating the directional distribution of arriving energy and the degree and diffuseness of sound fields in rooms.
Geostatistics for spatial genetic structures: study of wild populations of perennial ryegrass.
Monestiez, P; Goulard, M; Charmet, G
1994-04-01
Methods based on geostatistics were applied to quantitative traits of agricultural interest measured on a collection of 547 wild populations of perennial ryegrass in France. The mathematical background of these methods, which resembles spatial autocorrelation analysis, is briefly described. When a single variable is studied, the spatial structure analysis is similar to spatial autocorrelation analysis, and a spatial prediction method, called "kriging", gives a filtered map of the spatial pattern over all the sampled area. When complex interactions of agronomic traits with different evaluation sites define a multivariate structure for the spatial analysis, geostatistical methods allow the spatial variations to be broken down into two main spatial structures with ranges of 120 km and 300 km, respectively. The predicted maps that corresponded to each range were interpreted as a result of the isolation-by-distance model and as a consequence of selection by environmental factors. Practical collecting methodology for breeders may be derived from such spatial structures.
Monitoring tropical vegetation succession with LANDSAT data
NASA Technical Reports Server (NTRS)
Robinson, V. B. (Principal Investigator)
1983-01-01
The shadowing problem, which is endemic to the use of LANDSAT in tropical areas, and the ability to model changes over space and through time are problems to be addressed when monitoring tropical vegetation succession. Application of a trend surface analysis model to major land cover classes in a mountainous region of the Phillipines shows that the spatial modeling of radiance values can provide a useful approach to tropical rain forest succession monitoring. Results indicate shadowing effects may be due primarily to local variations in the spectral responses. These variations can be compensated for through the decomposition of the spatial variation in both elevation and MSS data. Using the model to estimate both elevation and spectral terrain surface as a posteriori inputs in the classification process leads to improved classification accuracy for vegetation of cover of this type. Spatial patterns depicted by the MSS data reflect the measurement of responses to spatial processes acting at several scales.
Chen, X.; Ashcroft, I. A.; Wildman, R. D.; Tuck, C. J.
2015-01-01
A method using experimental nanoindentation and inverse finite-element analysis (FEA) has been developed that enables the spatial variation of material constitutive properties to be accurately determined. The method was used to measure property variation in a three-dimensional printed (3DP) polymeric material. The accuracy of the method is dependent on the applicability of the constitutive model used in the inverse FEA, hence four potential material models: viscoelastic, viscoelastic–viscoplastic, nonlinear viscoelastic and nonlinear viscoelastic–viscoplastic were evaluated, with the latter enabling the best fit to experimental data. Significant changes in material properties were seen in the depth direction of the 3DP sample, which could be linked to the degree of cross-linking within the material, a feature inherent in a UV-cured layer-by-layer construction method. It is proposed that the method is a powerful tool in the analysis of manufacturing processes with potential spatial property variation that will also enable the accurate prediction of final manufactured part performance. PMID:26730216
Chen, X; Ashcroft, I A; Wildman, R D; Tuck, C J
2015-11-08
A method using experimental nanoindentation and inverse finite-element analysis (FEA) has been developed that enables the spatial variation of material constitutive properties to be accurately determined. The method was used to measure property variation in a three-dimensional printed (3DP) polymeric material. The accuracy of the method is dependent on the applicability of the constitutive model used in the inverse FEA, hence four potential material models: viscoelastic, viscoelastic-viscoplastic, nonlinear viscoelastic and nonlinear viscoelastic-viscoplastic were evaluated, with the latter enabling the best fit to experimental data. Significant changes in material properties were seen in the depth direction of the 3DP sample, which could be linked to the degree of cross-linking within the material, a feature inherent in a UV-cured layer-by-layer construction method. It is proposed that the method is a powerful tool in the analysis of manufacturing processes with potential spatial property variation that will also enable the accurate prediction of final manufactured part performance.
NASA Astrophysics Data System (ADS)
Zabolotnov, Yu. M.
2016-07-01
We analyze the spatial motion of a rigid body fixed to a cable about its center of mass when the orbital cable system is unrolling. The analysis is based on the integral manifold method, which permits separating the rigid body motion into the slow and fast components. The motion of the rigid body is studied in the case of slow variations in the cable tension force and under the action of various disturbances.We estimate the influence of the static and dynamic asymmetry of the rigid body on its spatial motion about the cable fixation point. An example of the analysis of the rigid body motion when the orbital cable system is unrolling is given for a special program of variations in the cable tension force. The conditions of applicability of the integral manifold method are analyzed.
Spatial and temporal stability of temperature in the first-level basins of China during 1951-2013
NASA Astrophysics Data System (ADS)
Cheng, Yuting; Li, Peng; Xu, Guoce; Li, Zhanbin; Cheng, Shengdong; Wang, Bin; Zhao, Binhua
2018-05-01
In recent years, global warming has attracted great attention around the world. Temperature change is not only involved in global climate change but also closely linked to economic development, the ecological environment, and agricultural production. In this study, based on temperature data recorded by 756 meteorological stations in China during 1951-2013, the spatial and temporal stability characteristics of annual temperature in China and its first-level basins were investigated using the rank correlation coefficient method, the relative difference method, rescaled range (R/S) analysis, and wavelet transforms. The results showed that during 1951-2013, the spatial variation of annual temperature belonged to moderate variability in the national level. Among the first-level basins, the largest variation coefficient was 114% in the Songhuajiang basin and the smallest variation coefficient was 10% in the Huaihe basin. During 1951-2013, the spatial distribution pattern of annual temperature presented extremely strong spatial and temporal stability characteristics in the national level. The variation range of Spearman's rank correlation coefficient was 0.97-0.99, and the spatial distribution pattern of annual temperature showed an increasing trend. In the national level, the Liaohe basin, the rivers in the southwestern region, the Haihe basin, the Yellow River basin, the Yangtze River basin, the Huaihe basin, the rivers in the southeastern region, and the Pearl River basin all had representative meteorological stations for annual temperature. In the Songhuajiang basin and the rivers in the northwestern region, there was no representative meteorological station. R/S analysis, the Mann-Kendall test, and the Morlet wavelet analysis of annual temperature showed that the best representative meteorological station could reflect the variation trend and the main periodic changes of annual temperature in the region. Therefore, strong temporal stability characteristics exist for annual temperature in China and its first-level basins. It was therefore feasible to estimate the annual average temperature by the annual temperature recorded by the representative meteorological station in the region. Moreover, it was of great significance to assess average temperature changes quickly and forecast future change tendencies in the region.
Nordey, Thibault; Léchaudel, Mathieu; Saudreau, Marc; Joas, Jacques; Génard, Michel
2014-01-01
Fruit physiology is strongly affected by both fruit temperature and water losses through transpiration. Fruit temperature and its transpiration vary with environmental factors and fruit characteristics. In line with previous studies, measurements of physical and thermal fruit properties were found to significantly vary between fruit tissues and maturity stages. To study the impact of these variations on fruit temperature and transpiration, a modelling approach was used. A physical model was developed to predict the spatial and temporal variations of fruit temperature and transpiration according to the spatial and temporal variations of environmental factors and thermal and physical fruit properties. Model predictions compared well to temperature measurements on mango fruits, making it possible to accurately simulate the daily temperature variations of the sunny and shaded sides of fruits. Model simulations indicated that fruit development induced an increase in both the temperature gradient within the fruit and fruit water losses, mainly due to fruit expansion. However, the evolution of fruit characteristics has only a very slight impact on the average temperature and the transpiration per surface unit. The importance of temperature and transpiration gradients highlighted in this study made it necessary to take spatial and temporal variations of environmental factors and fruit characteristics into account to model fruit physiology.
Barreto-Silva, Juan Sebastian; López, Dairon Cárdenas; Montoya, Alvaro Javier Duque
2014-03-01
The effect of environmental variation on the structure of tree communities in tropical forests is still under debate. There is evidence that in landscapes like Tierra Firme forest, where the environmental gradient decreases at a local level, the effect of soil on the distribution patterns of plant species is minimal, happens to be random or is due to biological processes. In contrast, in studies with different kinds of plants from tropical forests, a greater effect on floristic composition of varying soil and topography has been reported. To assess this, the current study was carried out in a permanent plot of ten hectares in the Amacayacu National Park, Colombian Amazonia. To run the analysis, floristic and environmental variations were obtained according to tree species abundance categories and growth forms. In order to quantify the role played by both environmental filtering and dispersal limitation, the variation of the spatial configuration was included. We used Detrended Correspondence Analysis and Canonical Correspondence Analysis, followed by a variation partitioning, to analyze the species distribution patterns. The spatial template was evaluated using the Principal Coordinates of Neighbor Matrix method. We recorded 14 074 individuals from 1 053 species and 80 families. The most abundant families were Myristicaceae, Moraceae, Meliaceae, Arecaceae and Lecythidaceae, coinciding with other studies from Northwest Amazonia. Beta diversity was relatively low within the plot. Soils were very poor, had high aluminum concentration and were predominantly clayey. The floristic differences explained along the ten hectares plot were mainly associated to biological processes, such as dispersal limitation. The largest proportion of community variation in our dataset was unexplained by either environmental or spatial data. In conclusion, these results support random processes as the major drivers of the spatial variation of tree species at a local scale on Tierra Firme forests of Amacayacu National Park, and suggest reserve's size as a key element to ensure the conservation of plant diversity at both regional and local levels.
Geographic information system-based spatial analysis of sawmill wood procurement
Nathaniel M. Anderson; Rene H. Germain; Eddie Bevilacqua
2011-01-01
In the sawmill sector of the forest products industry, the clustering of mills and wide variation in forest stocking and ownership result in sawlog markets that are complex and spatially differentiated. Despite the inherent spatial attributes of markets for stumpage and logs, few studies have used geospatial methods to examine wood procurement in detail across...
Buckley, Hannah L; Rafat, Arash; Ridden, Johnathon D; Cruickshank, Robert H; Ridgway, Hayley J; Paterson, Adrian M
2014-01-01
The role of species' interactions in structuring biological communities remains unclear. Mutualistic symbioses, involving close positive interactions between two distinct organismal lineages, provide an excellent means to explore the roles of both evolutionary and ecological processes in determining how positive interactions affect community structure. In this study, we investigate patterns of co-diversification between fungi and algae for a range of New Zealand lichens at the community, genus, and species levels and explore explanations for possible patterns related to spatial scale and pattern, taxonomic diversity of the lichens considered, and the level sampling replication. We assembled six independent datasets to compare patterns in phylogenetic congruence with varied spatial extent of sampling, taxonomic diversity and level of specimen replication. For each dataset, we used the DNA sequences from the ITS regions of both the fungal and algal genomes from lichen specimens to produce genetic distance matrices. Phylogenetic congruence between fungi and algae was quantified using distance-based redundancy analysis and we used geographic distance matrices in Moran's eigenvector mapping and variance partitioning to evaluate the effects of spatial variation on the quantification of phylogenetic congruence. Phylogenetic congruence was highly significant for all datasets and a large proportion of variance in both algal and fungal genetic distances was explained by partner genetic variation. Spatial variables, primarily at large and intermediate scales, were also important for explaining genetic diversity patterns in all datasets. Interestingly, spatial structuring was stronger for fungal than algal genetic variation. As the spatial extent of the samples increased, so too did the proportion of explained variation that was shared between the spatial variables and the partners' genetic variation. Different lichen taxa showed some variation in their phylogenetic congruence and spatial genetic patterns and where greater sample replication was used, the amount of variation explained by partner genetic variation increased. Our results suggest that the phylogenetic congruence pattern, at least at small spatial scales, is likely due to reciprocal co-adaptation or co-dispersal. However, the detection of these patterns varies among different lichen taxa, across spatial scales and with different levels of sample replication. This work provides insight into the complexities faced in determining how evolutionary and ecological processes may interact to generate diversity in symbiotic association patterns at the population and community levels. Further, it highlights the critical importance of considering sample replication, taxonomic diversity and spatial scale in designing studies of co-diversification.
Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques
NASA Astrophysics Data System (ADS)
Gulgundi, Mohammad Shahid; Shetty, Amba
2018-03-01
Groundwater quality deterioration due to anthropogenic activities has become a subject of prime concern. The objective of the study was to assess the spatial and temporal variations in groundwater quality and to identify the sources in the western half of the Bengaluru city using multivariate statistical techniques. Water quality index rating was calculated for pre and post monsoon seasons to quantify overall water quality for human consumption. The post-monsoon samples show signs of poor quality in drinking purpose compared to pre-monsoon. Cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA) were applied to the groundwater quality data measured on 14 parameters from 67 sites distributed across the city. Hierarchical cluster analysis (CA) grouped the 67 sampling stations into two groups, cluster 1 having high pollution and cluster 2 having lesser pollution. Discriminant analysis (DA) was applied to delineate the most meaningful parameters accounting for temporal and spatial variations in groundwater quality of the study area. Temporal DA identified pH as the most important parameter, which discriminates between water quality in the pre-monsoon and post-monsoon seasons and accounts for 72% seasonal assignation of cases. Spatial DA identified Mg, Cl and NO3 as the three most important parameters discriminating between two clusters and accounting for 89% spatial assignation of cases. Principal component analysis was applied to the dataset obtained from the two clusters, which evolved three factors in each cluster, explaining 85.4 and 84% of the total variance, respectively. Varifactors obtained from principal component analysis showed that groundwater quality variation is mainly explained by dissolution of minerals from rock water interactions in the aquifer, effect of anthropogenic activities and ion exchange processes in water.
SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering
DOE Office of Scientific and Technical Information (OSTI.GOV)
Iliopoulos, AS; Sun, X; Floros, D
Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well asmore » histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.« less
NASA Astrophysics Data System (ADS)
Gourdol, L.; Hissler, C.; Pfister, L.
2012-04-01
The Luxembourg sandstone aquifer is of major relevance for the national supply of drinking water in Luxembourg. The city of Luxembourg (20% of the country's population) gets almost 2/3 of its drinking water from this aquifer. As a consequence, the study of both the groundwater hydrochemistry, as well as its spatial and temporal variations, are considered as of highest priority. Since 2005, a monitoring network has been implemented by the Water Department of Luxembourg City, with a view to a more sustainable management of this strategic water resource. The data collected to date forms a large and complex dataset, describing spatial and temporal variations of many hydrochemical parameters. The data treatment issue is tightly connected to this kind of water monitoring programs and complex databases. Standard multivariate statistical techniques, such as principal components analysis and hierarchical cluster analysis, have been widely used as unbiased methods for extracting meaningful information from groundwater quality data and are now classically used in many hydrogeological studies, in particular to characterize temporal or spatial hydrochemical variations induced by natural and anthropogenic factors. But these classical multivariate methods deal with two-way matrices, usually parameters/sites or parameters/time, while often the dataset resulting from qualitative water monitoring programs should be seen as a datacube parameters/sites/time. Three-way matrices, such as the one we propose here, are difficult to handle and to analyse by classical multivariate statistical tools and thus should be treated with approaches dealing with three-way data structures. One possible analysis approach consists in the use of partial triadic analysis (PTA). The PTA was previously used with success in many ecological studies but never to date in the domain of hydrogeology. Applied to the dataset of the Luxembourg Sandstone aquifer, the PTA appears as a new promising statistical instrument for hydrogeologists, in particular to characterize temporal and spatial hydrochemical variations induced by natural and anthropogenic factors. This new approach for groundwater management offers potential for 1) identifying a common multivariate spatial structure, 2) untapping the different hydrochemical patterns and explaining their controlling factors and 3) analysing the temporal variability of this structure and grasping hydrochemical changes.
Cui, Lifang; Wang, Lunche; Singh, Ramesh P; Lai, Zhongping; Jiang, Liangliang; Yao, Rui
2018-05-23
The variation in vegetation greenness provides good understanding of the sustainable management and monitoring of land surface ecosystems. The present paper discusses the spatial-temporal changes in vegetation and controlling factors in the Yangtze River Basin (YRB) using Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) for the period 2001-2013. Theil-Sen Median trend analysis, Pearson correlation coefficients, and residual analysis have been used, which shows decreasing trend of the annual mean NDVI over the whole YRB. Spatially, the regions with significant decreasing trends were mainly located in parts of central YRB, and pronounced increasing trends were observed in parts of the eastern and western YRB. The mean NDVI during spring and summer seasons increased, while it decreased during autumn and winter seasons. The seasonal mean NDVI shows spatial heterogeneity due to the vegetation types. The correlation analysis shows a positive relation between NDVI and temperature over most of the YRB, whereas NDVI and precipitation show a negative correlation. The residual analysis shows an increase in NDVI in parts of eastern and western YRB and the decrease in NDVI in the small part of Yangtze River Delta (YRD) and the mid-western YRB due to human activities. In general, climate factors were the principal drivers of NDVI variation in YRB in recent years.
Zachery A. Holden; Michael A. Crimmins; Samuel A. Cushman; Jeremy S. Littell
2010-01-01
Accurate, fine spatial resolution predictions of surface air temperatures are critical for understanding many hydrologic and ecological processes. This study examines the spatial and temporal variability in nocturnal air temperatures across a mountainous region of Northern Idaho. Principal components analysis (PCA) was applied to a network of 70 Hobo temperature...
Spatio-temporal Analysis for New York State SPARCS Data
Chen, Xin; Wang, Yu; Schoenfeld, Elinor; Saltz, Mary; Saltz, Joel; Wang, Fusheng
2017-01-01
Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data. We analyzed spatial distribution patterns of typical diseases at ZIP code level. We performed temporal analysis of common diseases based on 12 years’ historical data. We then compared the spatial variations for diseases with different levels of clustering tendency, and studied the evolution history of such spatial patterns. Case studies based on asthma demonstrated that the discovered spatial clusters are consistent with prior studies. We visualized our spatial-temporal patterns as animations through videos. PMID:28815148
Temporal and spatial variations in fly ash quality
Hower, J.C.; Trimble, A.S.; Eble, C.F.
2001-01-01
Fly ash quality, both as the amount of petrographically distinguishable carbons and in chemistry, varies in both time and space. Temporal variations are a function of a number of variables. Variables can include variations in the coal blend organic petrography, mineralogy, and chemistry; variations in the pulverization of the coal, both as a function of the coal's Hardgrove grindability index and as a function of the maintenance and settings of the pulverizers; and variations in the operating conditions of the boiler, including changes in the pollution control system. Spatial variation, as an instantaneous measure of fly ash characteristics, should not involve changes in the first two sets of variables listed above. Spatial variations are a function of the gas flow within the boiler and ducts, certain flow conditions leading to a tendency for segregation of the less-dense carbons in one portion of the gas stream. Caution must be applied in sampling fly ash. Samples from a single bin, or series of bins, m ay not be representative of the whole fly ash, providing a biased view of the nature of the material. Further, it is generally not possible to be certain about variation until the analysis of the ash is complete. ?? 2001 Elsevier Science B.V. All rights reserved.
Impact of Spatial Scales on the Intercomparison of Climate Scenarios
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luo, Wei; Steptoe, Michael; Chang, Zheng
2017-01-01
Scenario analysis has been widely applied in climate science to understand the impact of climate change on the future human environment, but intercomparison and similarity analysis of different climate scenarios based on multiple simulation runs remain challenging. Although spatial heterogeneity plays a key role in modeling climate and human systems, little research has been performed to understand the impact of spatial variations and scales on similarity analysis of climate scenarios. To address this issue, the authors developed a geovisual analytics framework that lets users perform similarity analysis of climate scenarios from the Global Change Assessment Model (GCAM) using a hierarchicalmore » clustering approach.« less
Genome-scale modelling of microbial metabolism with temporal and spatial resolution.
Henson, Michael A
2015-12-01
Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.
Vaughan, Adam S; Kramer, Michael R; Cooper, Hannah L F; Rosenberg, Eli S; Sullivan, Patrick S
2017-02-01
Theory and research on HIV and among men who have sex with men (MSM) have long suggested the importance of non-residential locations in defining structural exposures. Despite this, most studies within these fields define place as a residential context, neglecting the potential influence of non-residential locations on HIV-related outcomes. The concept of activity spaces, defined as a set of locations to which an individual is routinely exposed, represents one theoretical basis for addressing this potential imbalance. Using a one-time online survey to collect demographic, behavioral, and spatial data from MSM, this paper describes activity spaces and examines correlates of this spatial variation. We used latent class analysis to identify categories of activity spaces using spatial data on home, routine, potential sexual risk, and HIV prevention locations. We then assessed individual and area-level covariates for their associations with these categories. Classes were distinguished by the degree of spatial variation in routine and prevention behaviors (which were the same within each class) and in sexual risk behaviors (i.e., sex locations and locations of meeting sex partners). Partner type (e.g. casual or main) represented a key correlate of the activity space. In this early examination of activity spaces in an online sample of MSM, patterns of spatial behavior represent further evidence of significant spatial variation in locations of routine, potential HIV sexual risk, and HIV prevention behaviors among MSM. Although prevention behaviors tend to have similar geographic variation as routine behaviors, locations where men engage in potentially high-risk behaviors may be more spatially focused for some MSM than for others. Copyright © 2016 Elsevier Ltd. All rights reserved.
Macroscopic Spatial Complexity of the Game of Life Cellular Automaton: A Simple Data Analysis
NASA Astrophysics Data System (ADS)
Hernández-Montoya, A. R.; Coronel-Brizio, H. F.; Rodríguez-Achach, M. E.
In this chapter we present a simple data analysis of an ensemble of 20 time series, generated by averaging the spatial positions of the living cells for each state of the Game of Life Cellular Automaton (GoL). We show that at the macroscopic level described by these time series, complexity properties of GoL are also presented and the following emergent properties, typical of data extracted complex systems such as financial or economical come out: variations of the generated time series following an asymptotic power law distribution, large fluctuations tending to be followed by large fluctuations, and small fluctuations tending to be followed by small ones, and fast decay of linear correlations, however, the correlations associated to their absolute variations exhibit a long range memory. Finally, a Detrended Fluctuation Analysis (DFA) of the generated time series, indicates that the GoL spatial macro states described by the time series are not either completely ordered or random, in a measurable and very interesting way.
Spatial Evolution of the Thickness Variations over a CFRP Laminated Structure
NASA Astrophysics Data System (ADS)
Davila, Yves; Crouzeix, Laurent; Douchin, Bernard; Collombet, Francis; Grunevald, Yves-Henri
2017-10-01
Ply thickness is one of the main drivers of the structural performance of a composite part. For stress analysis calculations (e.g., finite element analysis), composite plies are commonly considered to have a constant thickness compared to the reality (coefficients of variation up to 9% of the mean ply thickness). Unless this variability is taken into account reliable property predictions cannot be made. A modelling approach of such variations is proposed using parameters obtained from a 16-ply quasi-isotropic CFRP plate cured in an autoclave. A discrete Fourier transform algorithm is used to analyse the frequency response of the observed ply and plate thickness profiles. The model inputs, obtained by a mathematical representation of the ply thickness profiles, permit the generation of a representative stratification considering the spatial continuity of the thickness variations that are in good agreement with the real ply profiles spread over the composite part. A residual deformation FE model of the composite plate is used to illustrate the feasibility of the approach.
Contrasting patterns of fine-scale herb layer species composition in temperate forests
NASA Astrophysics Data System (ADS)
Chudomelová, Markéta; Zelený, David; Li, Ching-Feng
2017-04-01
Although being well described at the landscape level, patterns in species composition of forest herb layer are rarely studied at smaller scales. Here, we examined fine-scale environmental determinants and spatial structures of herb layer communities in thermophilous oak- and hornbeam dominated forests of the south-eastern part of the Czech Republic. Species composition of herb layer vegetation and environmental variables were recorded within a fixed grid of 2 × 2 m subplots regularly distributed within 1-ha quadrate plots in three forest stands. For each site, environmental models best explaining species composition were constructed using constrained ordination analysis. Spatial eigenvector mapping was used to model and account for spatial structures in community variation. Mean Ellenberg indicator values calculated for each subplot were used for ecological interpretation of spatially structured residual variation. The amount of variation explained by environmental and spatial models as well as the selection of variables with the best explanatory power differed among sites. As an important environmental factor, relative elevation was common to all three sites, while pH and canopy openness were shared by two sites. Both environmental and community variation was mostly coarse-scaled, as was the spatially structured portion of residual variation. When corrected for bias due to spatial autocorrelation, those environmental factors with already weak explanatory power lost their significance. Only a weak evidence of possibly omitted environmental predictor was found for autocorrelated residuals of site models using mean Ellenberg indicator values. Community structure was determined by different factors at different sites. The relative importance of environmental filtering vs. spatial processes was also site specific, implying that results of fine-scale studies tend to be shaped by local conditions. Contrary to expectations based on other studies, overall dominance of spatial processes at fine scale has not been detected. Ecologists should keep this in mind when making generalizations about community dynamics.
Van der Laan, Carina; Verweij, Pita A; Quiñones, Marcela J; Faaij, André Pc
2014-12-01
Land use and land cover change occurring in tropical forest landscapes contributes substantially to carbon emissions. Better insights into the spatial variation of aboveground biomass is therefore needed. By means of multiple statistical tests, including geographically weighted regression, we analysed the effects of eight variables on the regional spatial variation of aboveground biomass. North and East Kalimantan were selected as the case study region; the third largest carbon emitting Indonesian provinces. Strong positive relationships were found between aboveground biomass and the tested variables; altitude, slope, land allocation zoning, soil type, and distance to the nearest fire, road, river and city. Furthermore, the results suggest that the regional spatial variation of aboveground biomass can be largely attributed to altitude, distance to nearest fire and land allocation zoning. Our study showed that in this landscape, aboveground biomass could not be explained by one single variable; the variables were interrelated, with altitude as the dominant variable. Spatial analyses should therefore integrate a variety of biophysical and anthropogenic variables to provide a better understanding of spatial variation in aboveground biomass. Efforts to minimise carbon emissions should incorporate the identified factors, by 1) the maintenance of lands with high AGB or carbon stocks, namely in the identified zones at the higher altitudes; and 2) regeneration or sustainable utilisation of lands with low AGB or carbon stocks, dependent on the regeneration capacity of the vegetation. Low aboveground biomass densities can be found in the lowlands in burned areas, and in non-forest zones and production forests.
Spatiotemporal variation in reproductive parameters of yellow-bellied marmots.
Ozgul, Arpat; Oli, Madan K; Olson, Lucretia E; Blumstein, Daniel T; Armitage, Kenneth B
2007-11-01
Spatiotemporal variation in reproductive rates is a common phenomenon in many wildlife populations, but the population dynamic consequences of spatial and temporal variability in different components of reproduction remain poorly understood. We used 43 years (1962-2004) of data from 17 locations and a capture-mark-recapture (CMR) modeling framework to investigate the spatiotemporal variation in reproductive parameters of yellow-bellied marmots (Marmota flaviventris), and its influence on the realized population growth rate. Specifically, we estimated and modeled breeding probabilities of two-year-old females (earliest age of first reproduction), >2-year-old females that have not reproduced before (subadults), and >2-year-old females that have reproduced before (adults), as well as the litter sizes of two-year old and >2-year-old females. Most reproductive parameters exhibited spatial and/or temporal variation. However, reproductive parameters differed with respect to their relative influence on the realized population growth rate (lambda). Litter size had a stronger influence than did breeding probabilities on both spatial and temporal variations in lambda. Our analysis indicated that lambda was proportionately more sensitive to survival than recruitment. However, the annual fluctuation in litter size, abetted by the breeding probabilities, accounted for most of the temporal variation in lambda.
The calibration analysis of soil infiltration formula in farmland scale
NASA Astrophysics Data System (ADS)
Qian, Tao; Han, Na Na; Chang, Shuan Ling
2018-06-01
Soil infiltration characteristic is an important basis of farmland scale parameter estimation. Based on 12 groups of double-loop infiltration tests conducted in the test field of tianjin agricultural university west campus. Based on the calibration theory and the combination of statistics, the calibration analysis of phillips formula was carried out and the spatial variation characteristics of the calibration factor were analyzed. Results show that in study area based on the soil stability infiltration rate A calculate calibration factor αA calibration effect is best, that is suitable for the area formula of calibration infiltration and αA variation coefficient is 0.3234, with A certain degree of spatial variability.
NASA Astrophysics Data System (ADS)
Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig
2008-08-01
SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network.
Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Kvien, Craig
2008-01-01
This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.
NASA Astrophysics Data System (ADS)
Li, Yunkai; Zhang, Yuying; Xu, Jun; Zhang, Shuo
2018-03-01
Food web structures are well known to vary widely among ecosystems. Moreover, many food web studies of lakes have generally attempted to characterize the overall food web structure and have largely ignored internal spatial and environmental variations. In this study, we hypothesize that there is a high degree of spatial heterogeneity within an ecosystem and such heterogeneity may lead to strong variations in environmental conditions and resource availability, in turn resulting in different trophic pathways. Stable carbon and nitrogen isotopes were employed for the whole food web to describe the structure of the food web in different sub-basins within Taihu Lake. This lake is a large eutrophic freshwater lake that has been intensively managed and highly influenced by human activities for more than 50 years. The results show significant isotopic differences between basins with different environmental characteristics. Such differences likely result from isotopic baseline differences combining with a shift in food web structure. Both are related to local spatial heterogeneity in nutrient loading in waters. Such variation should be explicitly considered in future food web studies and ecosystem-based management in this lake ecosystem.
Meng, Yuting; Ding, Shiming; Gong, Mengdan; Chen, Musong; Wang, Yan; Fan, Xianfang; Shi, Lei; Zhang, Chaosheng
2018-03-01
Sediments have a heterogeneous distribution of labile redox-sensitive elements due to a drastic downward transition from oxic to anoxic condition as a result of organic matter degradation. Characterization of the heterogeneous nature of sediments is vital for understanding of small-scale biogeochemical processes. However, there are limited reports on the related specialized methodology. In this study, the monthly distributions of labile phosphorus (P), a redox-sensitive limiting nutrient, were measured in the eutrophic Lake Taihu by Zr-oxide diffusive gradients in thin films (Zr-oxide DGT) on a two-dimensional (2D) submillimeter level. Geographical information system (GIS) techniques were used to visualize the labile P distribution at such a micro-scale, showing that the DGT-labile P was low in winter and high in summer. Spatial analysis methods, including semivariogram and Moran's I, were used to quantify the spatial variation of DGT-labile P. The distribution of DGT-labile P had clear submillimeter-scale spatial patterns with significant spatial autocorrelation during the whole year and displayed seasonal changes. High values of labile P with strong spatial variation were observed in summer, while low values of labile P with relatively uniform spatial patterns were detected in winter, demonstrating the strong influences of temperature on the mobility and spatial distribution of P in sediment profiles. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Divíšek, Jan; Zelený, David; Culek, Martin; Št'astný, Karel
2014-08-01
Studies that explore species-environment relationships at a broad scale are usually limited by the availability of sufficient habitat description, which is often too coarse to differentiate natural habitat patches. Therefore, it is not well understood how the distribution of natural habitats affects broad-scale patterns in the distribution of animal species. In this study, we evaluate the role of field-mapped natural habitats, land-cover types derived from remote sensing and climate on the composition of assemblages of five distinct animal groups, namely non-volant mammals, birds, reptiles, amphibians and butterflies native to the Czech Republic. First, we used variation partitioning based on redundancy analysis to evaluate the extent to which the environmental variables and their spatial structure might underlie the observed spatial patterns in the composition of animal assemblages. Second, we partitioned variations explained by climate, natural habitats and land-cover to compare their relative importance. Finally, we tested the independent effects of each variable in order to evaluate the significance of their contributions to the environmental model. Our results showed that spatial patterns in the composition of assemblages of almost all the considered animal groups may be ascribed mostly to variations in the environment. Although the shared effects of climatic variables, natural habitats and land-cover types explained the largest proportion of variation in each animal group, the variation explained purely by natural habitats was always higher than the variation explained purely by climate or land-cover. We conclude that most spatial variation in the composition of assemblages of almost all animal groups probably arises from biological processes operating within a spatially structured environment and suggest that natural habitats are important to explain observed patterns because they often perform better than habitat descriptions based on remote sensing. This underlines the value of using appropriate habitat data, for which high-resolution and large-area field-mapping projects are necessary.
Muñoz, Cynthia C; Vermeiren, Peter
2018-04-01
Knowledge of spatial variation in pollutant profiles among sea turtle nesting locations is limited. This poses challenges in identifying processes shaping this variability and sets constraints to the conservation management of sea turtles and their use as biomonitoring tools for environmental pollutants. We aimed to increase understanding of the spatial variation in polycyclic aromatic hydrocarbon (PAH), organochlorine pesticide (OCP) and polychlorinated biphenyl (PCB) compounds among nesting beaches. We link the spatial variation to turtle migration patterns and the persistence of these pollutants. Specifically, using gas chromatography, we confirmed maternal transfer of a large number of compounds (n = 68 out of 69) among 104 eggs collected from 21 nests across three nesting beaches within the Yucatán Peninsula, one of the world's most important rookeries for hawksbill turtles (Eretmochelys imbricata). High variation in PAH profiles was observed among beaches, using multivariate correspondence analysis and univariate Peto-Prentice tests, reflecting local acquisition during recent migration movements. Diagnostic PAH ratios reflected petrogenic origins in Celestún, the beach closest to petroleum industries in the Gulf of Mexico. By contrast, pollution profiles of OCPs and PCBs showed high similarity among beaches, reflecting the long-term accumulation of these pollutants at regional scales. Therefore, spatial planning of protected areas and the use of turtle eggs in biomonitoring needs to account for the spatial variation in pollution profiles among nesting beaches. Copyright © 2018 Elsevier Ltd. All rights reserved.
Analysis of Co-spatial UV-Optical STIS Spectra of Planetary Nebulae From HST Cycle 19 GO 12600
NASA Astrophysics Data System (ADS)
Miller, Timothy R.; Henry, Richard B. C.; Dufour, Reginald J.; Kwitter, Karen B.; Shaw, Richard A.; Balick, Bruce; Corradi, Romano
2015-01-01
We present an analysis of five spatially resolved planetary nebulae (PNe), NGC 5315, NGC 5882, NGC 7662, IC 2165, and IC 3568, from observations in the Cycle 19 program GO 12600 using HST STIS. Details of the observations and data are presented in the poster by Dufour et al. in this session. These five observations cover the wavelength range 1150-10,270 Å with 0.2 and 0.5 arcsec wide slits, and are co-spatial to 0.1 arcsec along a 25 arcsec length across each nebula. This unprecedented resolution in both wavelength and spatial coverage enabled detailed studies of physical conditions and abundances from UV line ion emissions (compared to optical lines). We first analyzed the low- and moderate-resolution UV emission lines of carbon using the resolved lines of C III] 1906.68 and 1908.73, which yielded a direct measurement of the density within the volume occupied by doubly-ionized carbon and other similar co-spatial ions. Next, each PN spectrum was divided into spatial sub-regions in order to assess inferred density variations among the sub-regions along the entire slit. Variations in electron temperature and chemical abundances were also probed. Lastly, these nebulae were modeled in detail with the photoionization code CLOUDY. This modeling tested different density profiles in order to reproduce the observed density variations and temperature fluctuations, and constrain central star parameters. We gratefully acknowledge generous support from NASA through grants related to the Cycle 19 program GO 12600, as well as from the University of Oklahoma.
NASA Astrophysics Data System (ADS)
Wang, Z.; Gu, Z.; Chen, B.; Yuan, J.; Wang, C.
2016-12-01
The CHAOS-6 geomagnetic field model, presented in 2016 by the Denmark's national space institute (DTU Space), is a model of the near-Earth magnetic field. According the CHAOS-6 model, seven component data of geomagnetic filed at 30 observatories in China in 2015 and at 3 observatories in China spanning the time interval 2008.0-2016.5 were calculated. Also seven component data of geomagnetic filed from the geomagnetic data of practical observations in China was obtained. Based on the model calculated data and the practical data, we have compared and analyzed the spatial distribution and the secular variation of the geomagnetic field in China. There is obvious difference between the two type data. The CHAOS-6 model cannot describe the spatial distribution and the secular variation of the geomagnetic field in China with comparative precision because of the regional and local magnetic anomalies in China.
Variation of ecosystem services and human activities: A case study in the Yanhe Watershed of China
NASA Astrophysics Data System (ADS)
Su, Chang-hong; Fu, Bo-Jie; He, Chan-Sheng; Lü, Yi-He
2012-10-01
The concept of 'ecosystem service' provides cohesive views on mechanisms by which nature contributes to human well-being. Fast social and economic development calls for research on interactions between human and natural systems. We took the Yanhe Watershed as our study area, and valued the variation of ecosystem services and human activities of 2000 and 2008. Five ecosystem services were selected i.e. net primary production (NPP), carbon sequestration and oxygen production (CSOP), water conservation, soil conservation, and grain production. Human activity was represented by a composite human activity index (HAI) that integrates human population density, farmland ratio, influence of residential sites and road network. Analysis results of the five ecosystem services and human activity (HAI) are as follows: (i) NPP, CSOP, water conservation, and soil conservation increased from 2000 to 2008, while grain production declined. HAI decreased from 2000 to 2008. Spatially, NPP, CSOP, and water conservation in 2000 and 2008 roughly demonstrated a pattern of decline from south to north, while grain production shows an endocentric increasing spatial pattern. Soil conservation showed a spatial pattern of high in the south and low in the north in 2000 and a different pattern of high in the west and low in the east in 2008 respectively. HAI is proportional to the administrative level and economic development. Variation of NPP/CSOP between 2000 and 2008 show an increasing spatial pattern from northwest to southeast. In contrast, the variation of soil conservation shows an increasing pattern from southeast to northwest. Variation of water conservation shows a fanning out decreasing pattern. Variation of grain production doesn't show conspicuous spatial pattern. (ii) Variation of water conservation and of soil conservation is significantly positively correlated at 0.01 level. Both variations of water conservation and soil conservation are negatively correlated with variation of HAI at 0.01 level. Variations of NPP/CSOP are negatively correlated with variations of soil conservation and grain production at 0.05 level. (iii) Strong tradeoffs exist between regulation services and provision service, while synergies exist within regulation services. Driving effect of human activities on ecosystem services and tradeoffs and synergies among ecosystem service are also discussed.
Spatial pattern analysis of Cu, Zn and Ni and their interpretation in the Campania region (Italy)
NASA Astrophysics Data System (ADS)
Petrik, Attila; Albanese, Stefano; Jordan, Gyozo; Rolandi, Roberto; De Vivo, Benedetto
2017-04-01
The uniquely abundant Campanian topsoil dataset enabled us to perform a spatial pattern analysis on 3 potentially toxic elements of Cu, Zn and Ni. This study is focusing on revealing the spatial texture and distribution of these elements by spatial point pattern and image processing analysis such as lineament density and spatial variability index calculation. The application of these methods on geochemical data provides a new and efficient tool to understand the spatial variation of concentrations and their background/baseline values. The determination and quantification of spatial variability is crucial to understand how fast the change in concentration is in a certain area and what processes might govern the variation. The spatial variability index calculation and image processing analysis including lineament density enables us to delineate homogenous areas and analyse them with respect to lithology and land use. Identification of spatial outliers and their patterns were also investigated by local spatial autocorrelation and image processing analysis including the determination of local minima and maxima points and singularity index analysis. The spatial variability of Cu and Zn reveals the highest zone (Cu: 0.5 MAD, Zn: 0.8-0.9 MAD, Median Deviation Index) along the coast between Campi Flegrei and the Sorrento Peninsula with the vast majority of statistically identified outliers and high-high spatial clustered points. The background/baseline maps of Cu and Zn reveals a moderate to high variability (Cu: 0.3 MAD, Zn: 0.4-0.5 MAD) NW-SE oriented zone including disrupted patches from Bisaccia to Mignano following the alluvial plains of Appenine's rivers. This zone has high abundance of anomaly concentrations identified using singularity analysis and it also has a high density of lineaments. The spatial variability of Ni shows the highest variability zone (0.6-0.7 MAD) around Campi Flegrei where the majority of low outliers are concentrated. The variability of background/baseline map of Ni reveals a shift to the east in case of highest variability zones coinciding with limestone outcrops. The high segmented area between Mignano and Bisaccia partially follows the alluvial plains of Appenine's rivers which seem to be playing a crucial role in the distribution and redistribution pattern of Cu, Zn and Ni in Campania. The high spatial variability zones of the later elements are located in topsoils on volcanoclastic rocks and are mostly related to cultivation and urbanised areas.
Kounina, Anna; Margni, Manuele; Shaked, Shanna; Bulle, Cécile; Jolliet, Olivier
2014-08-01
This paper develops continent-specific factors for the USEtox model and analyses the accuracy of different model architectures, spatial scales and archetypes in evaluating toxic impacts, with a focus on freshwater pathways. Inter-continental variation is analysed by comparing chemical fate and intake fractions between sub-continental zones of two life cycle impact assessment models: (1) the nested USEtox model parameterized with sub-continental zones and (2) the spatially differentiated IMPACTWorld model with 17 interconnected sub-continental regions. Substance residence time in water varies by up to two orders of magnitude among the 17 zones assessed with IMPACTWorld and USEtox, and intake fraction varies by up to three orders of magnitude. Despite this variation, the nested USEtox model succeeds in mimicking the results of the spatially differentiated model, with the exception of very persistent volatile pollutants that can be transported to polar regions. Intra-continental variation is analysed by comparing fate and intake fractions modelled with the a-spatial (one box) IMPACT Europe continental model vs. the spatially differentiated version of the same model. Results show that the one box model might overestimate chemical fate and characterisation factors for freshwater eco-toxicity of persistent pollutants by up to three orders of magnitude for point source emissions. Subdividing Europe into three archetypes, based on freshwater residence time (how long it takes water to reach the sea), improves the prediction of fate and intake fractions for point source emissions, bringing them within a factor five compared to the spatial model. We demonstrated that a sub-continental nested model such as USEtox, with continent-specific parameterization complemented with freshwater archetypes, can thus represent inter- and intra-continental spatial variations, whilst minimizing model complexity. Copyright © 2014 Elsevier Ltd. All rights reserved.
Spatial variations in δ13C and δ15N values of primary consumers in a coastal lagoon
NASA Astrophysics Data System (ADS)
Como, S.; Magni, P.; Van Der Velde, G.; Blok, F. S.; Van De Steeg, M. F. M.
2012-12-01
The analysis of the contribution of a food source to a consumer's diet or the trophic position of a consumer is highly sensitive to the variability of the isotopic values used as input data. However, little is known in coastal lagoons about the spatial variations in the isotopic values of primary consumers considered 'end members' in the isotope mixing models for quantifying the diet of secondary consumers or as a baseline for estimating the trophic position of consumers higher up in the food web. We studied the spatial variations in the δ13C and δ15N values of primary consumers and sedimentary organic matter (SOM) within a selected area of the Cabras lagoon (Sardinia, Italy). Our aim was to assess how much of the spatial variation in isotopic values of primary consumers was due to the spatial variability between sites and how much was due to differences in short distances from the shore. Samples were collected at four stations (50-100 m apart) selected randomly at two sites (1.5-2 km apart) chosen randomly at two distances from the shore (i.e. in proximity of the shore -Nearshore - and about 200 m away from the shore -Offshore). The sampling was repeated in March, May and August 2006 using new sites at the two chosen distances from the shore on each date. The isotopic values of size-fractionated seston and macrophytes were also analyzed as a complementary characterization of the study area. While δ15N did not show any spatial variations, the δ13C values of deposit feeders, Alitta (=Neanthes) succinea, Lekanesphaera hookeri, Hydrobia acuta and Gammarus aequicauda, were more depleted Offshore than Nearshore. For these species, there were significant effects of distance or distance × dates in the mean δ13C values, irrespective of the intrinsic variation between sites. SOM showed similar spatial variations in δ13C values, with Nearshore-Offshore differences up to 6‰. This indicates that the spatial isotopic changes are transferred from the food sources to the deposit feeders studied. In contrast, δ13C and δ15N values of suspension feeders, Ficopomatus enigmaticus and Amphibalanus amphitrite, did not show major variations, either between sites, or between Nearshore and Offshore. These different patterns between deposit feeders and suspension feeders are probably due to a weaker trophic link of the latter with SOM. We suggest that the Nearshore-Offshore gradient might be an important source of isotopic variation that needs to be considered in future web studies in coastal lagoons.
Davey, Nicholas G; Fitzpatrick, Cole T E; Etzkorn, Jacob M; Martinsen, Morten; Crampton, Robert S; Onstad, Gretchen D; Larson, Timothy V; Yost, Michael G; Krogh, Erik T; Gilroy, Michael; Himes, Kathy H; Saganić, Erik T; Simpson, Christopher D; Gill, Christopher G
2014-09-19
The objective of this study was to use membrane introduction mass spectrometry (MIMS), implemented on a mobile platform, in order to provide real-time, fine-scale, temporally and spatially resolved measurements of several hazardous air pollutants. This work is important because there is now substantial evidence that fine-scale spatial and temporal variations of air pollutant concentrations are important determinants of exposure to air pollution and adverse health outcomes. The study took place in Tacoma, WA during periods of impaired air quality in the winter and summer of 2008 and 2009. Levels of fine particles were higher in winter compared to summer, and were spatially uniform across the study area. Concentrations of vapor phase pollutants measured by membrane introduction mass spectrometry (MIMS), notably benzene and toluene, had relatively uniform spatial distributions at night, but exhibited substantial spatial variation during the day-daytime levels were up to 3-fold higher at traffic-impacted locations compared to a reference site. Although no direct side-by-side comparison was made between the MIMS system and traditional fixed site monitors, the MIMS system typically reported higher concentrations of specific VOCs, particularly benzene, ethylbenzene and naphthalene, compared to annual average concentrations obtained from SUMA canisters and gas chromatographic analysis at the fixed sites.
Study on temporal variation and spatial distribution for rural poverty in China based on GIS
NASA Astrophysics Data System (ADS)
Feng, Xianfeng; Xu, Xiuli; Wang, Yingjie; Cui, Jing; Mo, Hongyuan; Liu, Ling; Yan, Hong; Zhang, Yan; Han, Jiafu
2009-07-01
Poverty is one of the most serious challenges all over the world, is an obstacle to hinder economics and agriculture in poverty area. Research on poverty alleviation in China is very useful and important. In this paper, we will explore the comprehensive poverty characteristics in China, analyze the current poverty status, spatial distribution and temporal variations about rural poverty in China, and to category the different poverty types and their spatial distribution. First, we achieved the gathering and processing the relevant data. These data contain investigation data, research reports, statistical yearbook, censuses, social-economic data, physical and anthrop geographical data, etc. After deeply analysis of these data, we will get the distribution of poverty areas by spatial-temporal data model according to different poverty given standard in different stages in China to see the poverty variation and the regional difference in County-level. Then, the current poverty status, spatial pattern about poverty area in villages-level will be lucubrated; the relationship among poverty, environment (including physical and anthrop geographical factors) and economic development, etc. will be expanded. We hope our research will enhance the people knowledge of poverty in China and contribute to the poverty alleviation in China.
On Electron-Positron Pair Production by a Spatially Inhomogeneous Electric Field
NASA Astrophysics Data System (ADS)
Chervyakov, A.; Kleinert, H.
2018-05-01
A detailed analysis of electron-positron pair creation induced by a spatially non-uniform and static electric field from vacuum is presented. A typical example is provided by the Sauter potential. For this potential, we derive the analytic expressions for vacuum decay and pair production rate accounted for the entire range of spatial variations. In the limit of a sharp step, we recover the divergent result due to the singular electric field at the origin. The limit of a constant field reproduces the classical result of Euler, Heisenberg and Schwinger, if the latter is properly averaged over the width of a spatial variation. The pair production by the Sauter potential is described for different regimes from weak to strong fields. For all these regimes, the locally constant-field rate is shown to be the upper limit.
Martinson, Holly M; Fagan, William F
2014-09-01
Habitat fragmentation is a complex process that affects ecological systems in diverse ways, altering everything from population persistence to ecosystem function. Despite widespread recognition that habitat fragmentation can influence food web interactions, consensus on the factors underlying variation in the impacts of fragmentation across systems remains elusive. In this study, we conduct a systematic review and meta-analysis to quantify the effects of habitat fragmentation and spatial habitat structure on resource consumption in terrestrial arthropod food webs. Across 419 studies, we found a negative overall effect of fragmentation on resource consumption. Variation in effect size was extensive but predictable. Specifically, resource consumption was reduced on small, isolated habitat fragments, higher at patch edges, and neutral with respect to landscape-scale spatial variables. In general, resource consumption increased in fragmented settings for habitat generalist consumers but decreased for specialist consumers. Our study demonstrates widespread disruption of trophic interactions in fragmented habitats and describes variation among studies that is largely predictable based on the ecological traits of the interacting species. We highlight future prospects for understanding how changes in spatial habitat structure may influence trophic modules and food webs. © 2014 John Wiley & Sons Ltd/CNRS.
Spatial variation of peat soil properties in the oil-producing region of northeastern Sakhalin
NASA Astrophysics Data System (ADS)
Lipatov, D. N.; Shcheglov, A. I.; Manakhov, D. V.; Zavgorodnyaya, Yu. A.; Rozanova, M. S.; Brekhov, P. T.
2017-07-01
Morphology and properties of medium-deep oligotrophic peat, oligotrophic peat gley, pyrogenic oligotrophic peat gley, and peat gley soils on subshrub-cotton grass-sphagnum bogs and in swampy larch forests of northeastern Sakhalin have been studied. Variation in the thickness and reserves of litters in the studied bog and forest biogeocenoses has been analyzed. The profile distribution and spatial variability of moisture, density, ash, and pHKCl in separate groups of peat soils have been described. The content and spatial variability of petroleum hydrocarbons have been considered in relation to the accumulation of natural bitumoids by peat soils and the technogenic pressing in the oil-producing region. Variation of each parameter at different distances (10, 50, and 1000 m) has been estimated using a hierarchical sampling scheme. The spatial conjugation of soil parameters has been studied by factor analysis using the principal components method and Spearman correlation coefficients. Regression equations have been proposed to describe relationships of ash content with soil density and content of petroleum hydrocarbons in peat horizons.
Magalhães, Ricardo J Soares; Salamat, Maria Sonia; Leonardo, Lydia; Gray, Darren J; Carabin, Hélène; Halton, Kate; McManus, Donald P; Williams, Gail M; Rivera, Pilarita; Saniel, Ofelia; Hernandez, Leda; Yakob, Laith; McGarvey, Stephen; Clements, Archie
2015-01-01
Schistosoma japonicum infection is believed to be endemic in 28 of the 80 provinces of The Philippines and the most recent data on schistosomiasis prevalence have shown considerable variability between provinces. In order to increase the efficient allocation of parasitic disease control resources in the country, we aimed to describe the small-scale spatial variation in S. japonicum prevalence across The Philippines, quantify the role of the physical environment in driving the spatial variation of S. japonicum, and develop a predictive risk map of S. japonicum infection. Data on S. japonicum infection from 35,754 individuals across the country were geolocated at the barangay level and included in the analysis. The analysis was then stratified geographically for the regions of Luzon, the Visayas and Mindanao. Zero-inflated binomial Bayesian geostatistical models of S. japonicum prevalence were developed and diagnostic uncertainty was incorporated. Results of the analysis show that in the three regions, males and individuals aged ≥ 20 years had significantly higher prevalence of S. japonicum compared with females and children < 5 years. The role of the environmental variables differed between regions of The Philippines. Schistosoma japonicum infection was widespread in the Visayas whereas it was much more focal in Luzon and Mindanao. This analysis revealed significant spatial variation in the prevalence of S. japonicum infection in The Philippines. This suggests that a spatially targeted approach to schistosomiasis interventions, including mass drug administration, is warranted. When financially possible, additional schistosomiasis surveys should be prioritized for areas identified to be at high risk but which were under-represented in our dataset. PMID:25128879
Soares Magalhães, Ricardo J; Salamat, Maria Sonia; Leonardo, Lydia; Gray, Darren J; Carabin, Hélène; Halton, Kate; McManus, Donald P; Williams, Gail M; Rivera, Pilarita; Saniel, Ofelia; Hernandez, Leda; Yakob, Laith; McGarvey, Stephen; Clements, Archie
2014-11-01
Schistosoma japonicum infection is believed to be endemic in 28 of the 80 provinces of The Philippines and the most recent data on schistosomiasis prevalence have shown considerable variability between provinces. In order to increase the efficient allocation of parasitic disease control resources in the country, we aimed to describe the small-scale spatial variation in S. japonicum prevalence across The Philippines, quantify the role of the physical environment in driving the spatial variation of S. japonicum, and develop a predictive risk map of S. japonicum infection. Data on S. japonicum infection from 35,754 individuals across the country were geo-located at the barangay level and included in the analysis. The analysis was then stratified geographically for the regions of Luzon, the Visayas and Mindanao. Zero-inflated binomial Bayesian geostatistical models of S. japonicum prevalence were developed and diagnostic uncertainty was incorporated. Results of the analysis show that in the three regions, males and individuals aged ⩾20years had significantly higher prevalence of S. japonicum compared with females and children <5years. The role of the environmental variables differed between regions of The Philippines. Schistosoma japonicum infection was widespread in the Visayas whereas it was much more focal in Luzon and Mindanao. This analysis revealed significant spatial variation in the prevalence of S. japonicum infection in The Philippines. This suggests that a spatially targeted approach to schistosomiasis interventions, including mass drug administration, is warranted. When financially possible, additional schistosomiasis surveys should be prioritised for areas identified to be at high risk but which were under-represented in our dataset. Copyright © 2014 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.
Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre
2014-12-05
Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.
2011-01-01
Background Geographic Information Systems (GIS) combined with spatial analytical methods could be helpful in examining patterns of drug use. Little attention has been paid to geographic variation of cardiovascular prescription use in Taiwan. The main objective was to use local spatial association statistics to test whether or not the cardiovascular medication-prescribing pattern is homogenous across 352 townships in Taiwan. Methods The statistical methods used were the global measures of Moran's I and Local Indicators of Spatial Association (LISA). While Moran's I provides information on the overall spatial distribution of the data, LISA provides information on types of spatial association at the local level. LISA statistics can also be used to identify influential locations in spatial association analysis. The major classes of prescription cardiovascular drugs were taken from Taiwan's National Health Insurance Research Database (NHIRD), which has a coverage rate of over 97%. The dosage of each prescription was converted into defined daily doses to measure the consumption of each class of drugs. Data were analyzed with ArcGIS and GeoDa at the township level. Results The LISA statistics showed an unusual use of cardiovascular medications in the southern townships with high local variation. Patterns of drug use also showed more low-low spatial clusters (cold spots) than high-high spatial clusters (hot spots), and those low-low associations were clustered in the rural areas. Conclusions The cardiovascular drug prescribing patterns were heterogeneous across Taiwan. In particular, a clear pattern of north-south disparity exists. Such spatial clustering helps prioritize the target areas that require better education concerning drug use. PMID:21609462
NASA Astrophysics Data System (ADS)
Zhang, Hui; Xue, Lianqing; Yang, Changbing; Chen, Xinfang; Zhang, Luochen; Wei, Guanghui
2018-01-01
The Tarim River (TR), as the longest inland river at an arid area in China, is a typical regions of vegetation variation research and plays a crucial role in the sustainable development of regional ecological environment. In this paper, the newest dataset of MODND1M NDVI, at a resolution of 500m, were applied to calculate vegetation index in growing season during the period 2000-2015. Using a vegetation coverage index, a trend line analysis, and the local spatial autocorrelation analysis, this paper investigated the landscape patterns and spatio-temporal variation of vegetation coverage at regional and pixel scales over mainstream of the Tarim River, Xinjiang. The results showed that (1) The bare land area on both sides of Tarim River appeared to have a fluctuated downward trend and there were two obvious valley values in 2005 and 2012. (2) Spatially, the vegetation coverage improved areas is mostly distributed in upstream and the degraded areas is mainly distributed in the left bank of midstream and the end of Tarim River during 2000-2005. (3) The local spatial auto-correlation analysis revealed that vegetation coverage was spatially positive autocorrelated and spatial concentrated. The high-high self-related areas are mainly distributed in upstream, where vegetation cover are relatively good, and the low-low self-related areas are mostly with lower vegetation cover in the lower reaches of Tarim River.
Onozuka, Daisuke; Hagihara, Akihito
2016-02-15
Several studies have reported the burden of climate change on extreme heat-related mortality or morbidity. However, few studies have investigated the spatial and temporal variation in emergency transport during periods of extreme heat on a national scale. Daily emergency ambulance dispatch data from 2007 to 2010 were acquired from all 47 prefectures of Japan. The temporal variability in the relationship between heat and morbidity in each prefecture was estimated using Poisson regression combined with a distributed lag non-linear model and adjusted for time trends. The spatial variability in the heat-morbidity relationships between prefectures was estimated using a multivariate meta-analysis. A total of 5,289,660 emergency transports were reported during the summer months (June through September) within the study period. The overall cumulative relative risk (RR) at the 99th percentile vs. the minimum morbidity percentile was 1.292 (95% CI: 1.251-1.333) for all causes, 1.039 (95% CI: 0.989-1.091) for cardiovascular diseases, and 1.287 (95% CI: 1.210-1.368) for respiratory diseases. Temporal variation in the estimated effects indicated a non-linear relationship, and there were differences in the temporal variations between heat and all-cause and cause-specific morbidity. Spatial variation between prefectures was observed for all causes (Cochran Q test, p<0.001; I(2)=45.8%); however, there was no significant spatial heterogeneity for cardiovascular (Cochran Q test, p=0.054; I(2)=15.1%) and respiratory (Cochran Q test, p=0.681; I(2)=1.0%) diseases. Our nationwide study demonstrated differences in the spatial and temporal variations in the relative risk for all-cause and cause-specific emergency transport during periods of extreme heat in Japan between 2007 and 2010. Our results suggest that public health strategies aimed at controlling heat-related morbidity should be tailored according to region-specific weather conditions. Copyright © 2015 Elsevier B.V. All rights reserved.
Species composition and morphologic variation of Porites in the Gulf of California
NASA Astrophysics Data System (ADS)
López-Pérez, R. A.
2013-09-01
Morphometric analysis of corallite calices confirmed that from the late Miocene to the Recent, four species of Porites have inhabited the Gulf of California: the extinct Porites carrizensis, the locally extirpated Porites lobata and the extant Porites sverdrupi and Porites panamensis. Furthermore, large-scale spatial and temporal phenotypic plasticity was observed in the dominant species P. panamensis. Canonical discriminant analysis and ANOVA demonstrated that the calice structures of P. panamensis experienced size reduction between the late Pleistocene and Recent. Similarly, PERMANOVA, regression and correlation analyses demonstrated that across the 800 km north to south in the gulf, P. panamensis populations displayed a similar reduction in calice structures. Based on correlation analysis with environmental data, these large spatial changes are likely related to changes in nutrient concentration and sea surface temperature. As such, the large-scale spatial and temporal phenotypic variation recorded in populations of P. panamensis in the Gulf of California is likely related to optimization of corallite performance (energy acquisition) within various environmental scenarios. These findings may have relevance to modern conservation efforts within this ecological dominant genus.
Broadband interferometric characterization of divergence and spatial chirp.
Meier, Amanda K; Iliev, Marin; Squier, Jeff A; Durfee, Charles G
2015-09-01
We demonstrate a spectral interferometric method to characterize lateral and angular spatial chirp to optimize intensity localization in spatio-temporally focused ultrafast beams. Interference between two spatially sheared beams in an interferometer will lead to straight fringes if the wavefronts are curved. To produce reference fringes, we delay one arm relative to another in order to measure fringe rotation in the spatially resolved spectral interferogram. With Fourier analysis, we can obtain frequency-resolved divergence. In another arrangement, we spatially flip one beam relative to the other, which allows the frequency-dependent beamlet direction (angular spatial chirp) to be measured. Blocking one beam shows the spatial variation of the beamlet position with frequency (i.e., the lateral spatial chirp).
NASA Astrophysics Data System (ADS)
Zhang, S.; Wang, Y.; Ju, H.
2017-12-01
The interprovincial terrestrial physical geographical entities are the key areas of regional integrated management. Based on toponomy dictionaries and different thematic maps, the attributes and the spatial extent of the interprovincial terrestrial physical geographical names (ITPGN, including terrain ITPGN and water ITPGN) were extracted. The coefficient of variation and Moran's I were combined together to measure the spatial variation and spatial association of ITPGN. The influencing factors of the distribution of ITPGN and the implications for the regional management were further discussed. The results showed that 11325 ITPGN were extracted, including 7082 terrain ITPGN and 4243 water ITPGN. Hunan Province had the largest number of ITPGN in China, and Shanghai had the smallest number. The spatial variance of the terrain ITPGN was larger than that of the water ITPGN, and the ITPGN showed a significant agglomeration phenomenon in the southern part of China. Further analysis showed that the number of ITPGN was positively related with the relative elevation and the population where the relative elevation was lower than 2000m and the population was less than 50 million. But the number of ITPGN showed a negative relationship with the two factors when their values became larger, indicating a large number of unnamed entities existed in complex terrain areas and a decreasing number of terrestrial physical geographical entities in densely populated area. Based on these analysis, we suggest the government take the ITPGN as management units to realize a balance development between different parts of the entities and strengthen the geographical names census and the nomination of unnamed interprovincial physical geographical entities. This study also demonstrated that the methods of literature survey, coefficient of variation and Moran's I can be combined to enhance the understanding of the spatial pattern of ITPGN.
Spatial variations of the Sr I 4607 Å scattering polarization peak
NASA Astrophysics Data System (ADS)
Bianda, M.; Berdyugina, S.; Gisler, D.; Ramelli, R.; Belluzzi, L.; Carlin, E. S.; Stenflo, J. O.; Berkefeld, T.
2018-06-01
Context. The scattering polarization signal observed in the photospheric Sr I 4607 Å line is expected to vary at granular spatial scales. This variation can be due to changes in the magnetic field intensity and orientation (Hanle effect), but also to spatial and temporal variations in the plasma properties. Measuring the spatial variation of such polarization signal would allow us to study the properties of the magnetic fields at subgranular scales, but observations are challenging since both high spatial resolution and high spectropolarimetric sensitivity are required. Aims: We aim to provide observational evidence of the polarization peak spatial variations, and to analyze the correlation they might have with granulation. Methods: Observations conjugating high spatial resolution and high spectropolarimetric precision were performed with the Zurich IMaging POLarimeter, ZIMPOL, at the GREGOR solar telescope, taking advantage of the adaptive optics system and the newly installed image derotator. Results: Spatial variations of the scattering polarization in the Sr I 4607 Å line are clearly observed. The spatial scale of these variations is comparable with the granular size. Small correlations between the polarization signal amplitude and the continuum intensity indicate that the polarization is higher at the center of granules than in the intergranular lanes.
Ye, Chen; Li, Siyue; Yang, Yuyi; Shu, Xiao; Zhang, Jiaquan; Zhang, Quanfa
2015-01-01
The ~350 km2 water level fluctuation zone (WLFZ) in the Three Gorges Reservoir (TGR) of China, situated at the intersection of terrestrial and aquatic ecosystems, experiences a great hydrological change with prolonged winter inundation. Soil samples were collected in 12 sites pre- (September 2008) and post submergence (June 2009) in the WLFZ and analyzed for soil nutrients. Self-organizing map (SOM) and statistical analysis including multi-way ANOVA, paired-T test, and stepwise least squares multiple regression were employed to determine the spatio-temporal variations of soil nutrients in relation to submergence, and their correlations with soil physical characteristics. Results showed significant spatial variability in nutrients along ~600 km long shoreline of the TGR before and after submergence. There were higher contents of organic matter, total nitrogen (TN), and nitrate (NO3-) in the lower reach and total phosphorus (TP) in the upper reach that were primarily due to the spatial variations in soil particle size composition and anthropogenic activities. Submergence enhanced soil available potassium (K), while significantly decreased soil N, possibly due to the alterations of soil particle size composition and increase in soil pH. In addition, SOM analysis determined important roles of soil pH value, bulk density, soil particle size (i.e., silt and sand) and nutrients (TP, TK, and AK) on the spatial and temporal variations in soil quality. Our results suggest that urban sewage and agricultural runoffs are primary pollutants that affect soil nutrients in the WLFZ of TGR. PMID:25789612
Classifying and mapping wetlands and peat resources using digital cartography
Cameron, Cornelia C.; Emery, David A.
1992-01-01
Digital cartography allows the portrayal of spatial associations among diverse data types and is ideally suited for land use and resource analysis. We have developed methodology that uses digital cartography for the classification of wetlands and their associated peat resources and applied it to a 1:24 000 scale map area in New Hampshire. Classifying and mapping wetlands involves integrating the spatial distribution of wetlands types with depth variations in associated peat quality and character. A hierarchically structured classification that integrates the spatial distribution of variations in (1) vegetation, (2) soil type, (3) hydrology, (4) geologic aspects, and (5) peat characteristics has been developed and can be used to build digital cartographic files for resource and land use analysis. The first three parameters are the bases used by the National Wetlands Inventory to classify wetlands and deepwater habitats of the United States. The fourth parameter, geological aspects, includes slope, relief, depth of wetland (from surface to underlying rock or substrate), wetland stratigraphy, and the type and structure of solid and unconsolidated rock surrounding and underlying the wetland. The fifth parameter, peat characteristics, includes the subsurface variation in ash, acidity, moisture, heating value (Btu), sulfur content, and other chemical properties as shown in specimens obtained from core holes. These parameters can be shown as a series of map data overlays with tables that can be integrated for resource or land use analysis.
Qing, Feng Ting; Peng, Yu
2016-05-01
Based on the remote sensing data in 1997, 2001, 2005, 2009 and 2013, this article classified the landscape types of Shunyi, and the ecological risk index was built based on landscape disturbance index and landscape fragility. The spatial auto-correlation and geostatistical analysis by GS + and ArcGIS was used to study temporal and spatial changes of ecological risk. The results showed that eco-risk degree in the study region had positive spatial correlation which decreased with the increasing grain size. Within a certain grain range (<12 km), the spatial auto-correlation had an obvious dependence on scale. The random variation of spatial heterogeneity was less than spatial auto-correlation variation from 1997 to 2013, which meant the auto-correlation had a dominant role in spatial heterogeneity. The ecological risk of Shunyi was mainly at moderate level during the study period. The area of the district with higher and lower ecological risk increased, while that of mode-rate ecological risk decreased. The area with low ecological risk was mainly located in the airport region and forest of southeast Shunyi, while that with high ecological risk was mainly concentrated in the water landscape, such as the banks of Chaobai River.
Effects of Topography-driven Micro-climatology on Evaporation
NASA Astrophysics Data System (ADS)
Adams, D. D.; Boll, J.; Wagenbrenner, N. S.
2017-12-01
The effects of spatial-temporal variation of climatic conditions on evaporation in micro-climates are not well defined. Current spatially-based remote sensing and modeling for evaporation is limited for high resolutions and complex topographies. We investigated the effect of topography-driven micro-climatology on evaporation supported by field measurements and modeling. Fourteen anemometers and thermometers were installed in intersecting transects over the complex topography of the Cook Agronomy Farm, Pullman, WA. WindNinja was used to create 2-D vector maps based on recorded observations for wind. Spatial analysis of vector maps using ArcGIS was performed for analysis of wind patterns and variation. Based on field measurements, wind speed and direction show consequential variability based on hill-slope location in this complex topography. Wind speed and wind direction varied up to threefold and more than 45 degrees, respectively for a given time interval. The use of existing wind models enables prediction of wind variability over the landscape and subsequently topography-driven evaporation patterns relative to wind. The magnitude of the spatial-temporal variability of wind therefore resulted in variable evaporation rates over the landscape. These variations may contribute to uneven crop development patterns observed during the late growth stages of the agricultural crops at the study location. Use of hill-slope location indexes and appropriate methods for estimating actual evaporation support development of methodologies to better define topography-driven heterogeneity in evaporation. The cumulative effects of spatially-variable climatic factors on evaporation are important to quantify the localized water balance and inform precision farming practices.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garten Jr, Charles T; Kang, S.; Brice, Deanne Jane
2007-01-01
The purpose of this research was to test the hypothesis that variability in 11 soil properties, related to soil texture and soil C and N, would increase from small (1 m) to large (1 km) spatial scales in a temperate, mixed-hardwood forest ecosystem in east Tennessee, USA. The results were somewhat surprising and indicated that a fundamental assumption in geospatial analysis, namely that variability increases with increasing spatial scale, did not apply for at least five of the 11 soil properties measured over a 0.5-km2 area. Composite mineral soil samples (15 cm deep) were collected at 1, 5, 10, 50,more » 250, and 500 m distances from a center point along transects in a north, south, east, and westerly direction. A null hypothesis of equal variance at different spatial scales was rejected (P{le}0.05) for mineral soil C concentration, silt content, and the C-to-N ratios in particulate organic matter (POM), mineral-associated organic matter (MOM), and whole surface soil. Results from different tests of spatial variation, based on coefficients of variation or a Mantel test, led to similar conclusions about measurement variability and geographic distance for eight of the 11 variables examined. Measurements of mineral soil C and N concentrations, C concentrations in MOM, extractable soil NH{sub 4}-N, and clay contents were just as variable at smaller scales (1-10 m) as they were at larger scales (50-500 m). On the other hand, measurement variation in mineral soil C-to-N ratios, MOM C-to-N ratios, and the fraction of soil C in POM clearly increased from smaller to larger spatial scales. With the exception of extractable soil NH4-N, measured soil properties in the forest ecosystem could be estimated (with 95% confidence) to within 15% of their true mean with a relatively modest number of sampling points (n{le}25). For some variables, scaling up variation from smaller to larger spatial domains within the ecosystem could be relatively easy because small-scale variation may be indicative of variation at larger scales.« less
NASA Astrophysics Data System (ADS)
Wang, Y. L.; Yeh, T. C. J.; Wen, J. C.
2017-12-01
This study is to investigate the ability of river stage tomography to estimate the spatial distribution of hydraulic transmissivity (T), storage coefficient (S), and diffusivity (D) in groundwater basins using information of groundwater level variations induced by periodic variations of stream stage, and infiltrated flux from the stream boundary. In order to accomplish this objective, the sensitivity and correlation of groundwater heads with respect to the hydraulic properties is first conducted to investigate the spatial characteristics of groundwater level in response to the stream variations at different frequencies. Results of the analysis show that the spatial distributions of the sensitivity of heads at an observation well in response to periodic river stage variations are highly correlated despite different frequencies. On the other hand, the spatial patterns of the sensitivity of the observed head to river flux boundaries at different frequencies are different. Specifically, the observed head is highly correlated with T at the region between the stream and observation well when the high-frequency periodic flux is considered. On the other hand, it is highly correlated with T at the region between monitoring well and the boundary opposite to the stream when the low-frequency periodic flux is prescribed to the stream. We also find that the spatial distributions of the sensitivity of observed head to S variation are highly correlated with all frequencies in spite of heads or fluxes stream boundary. Subsequently, the differences of the spatial correlations of the observed heads to the hydraulic properties under the head and flux boundary conditions are further investigated by an inverse model (i.e., successive stochastic linear estimator). This investigation uses noise-free groundwater and stream data of a synthetic aquifer, where aquifer heterogeneity is known exactly. The ability of river stage tomography is then tested with these synthetic data sets to estimate T, S, and D distribution. The results reveal that boundary flux variations with different frequencies contain different information about the aquifer characteristics while the head boundary does not.
Saha, Shubhayu; Brock, John W; Vaidyanathan, Ambarish; Easterling, David R; Luber, George
2015-03-04
Predictions of intense heat waves across the United States will lead to localized health impacts, most of which are preventable. There is a need to better understand the spatial variation in the morbidity impacts associated with extreme heat across the country to prevent such adverse health outcomes. Hyperthermia-related emergency department (ED) visits were obtained from the Truven Health MarketScan(®) Research dataset for 2000-2010. Three measures of daily ambient heat were constructed using meteorological observations from the National Climatic Data Center (maximum temperature, heat index) and the Spatial Synoptic Classification. Using a time-stratified case crossover approach, odds ratio of hyperthermia-related ED visit were estimated for the three different heat measures. Random effects meta-analysis was used to combine the odds ratios for 94 Metropolitan Statistical Areas (MSA) to examine the spatial variation by eight latitude categories and nine U.S. climate regions. Examination of lags for all three temperature measures showed that the odds ratio of ED visit was statistically significant and highest on the day of the ED visit. For heat waves lasting two or more days, additional statistically significant association was observed when heat index and synoptic classification was used as the temperature measure. These results were insensitive to the inclusion of air pollution measures. On average, the maximum temperature on the day of an ED visit was 93.4°F in 'South' and 81.9°F in the 'Northwest' climatic regions of United States. The meta-analysis showed higher odds ratios of hyperthermia ED visit in the central and the northern parts of the country compared to the south and southwest. The results showed spatial variation in average temperature on days of ED visit and odds ratio for hyperthermia ED visits associated with extreme heat across United States. This suggests that heat response plans need to be customized for different regions and the potential role of hyperthermia ED visits in syndromic surveillance for extreme heat.
Padial, André A.; Ceschin, Fernanda; Declerck, Steven A. J.; De Meester, Luc; Bonecker, Cláudia C.; Lansac-Tôha, Fabio A.; Rodrigues, Liliana; Rodrigues, Luzia C.; Train, Sueli; Velho, Luiz F. M.; Bini, Luis M.
2014-01-01
Recently, community ecologists are focusing on the relative importance of local environmental factors and proxies to dispersal limitation to explain spatial variation in community structure. Albeit less explored, temporal processes may also be important in explaining species composition variation in metacommunities occupying dynamic systems. We aimed to evaluate the relative role of environmental, spatial and temporal variables on the metacommunity structure of different organism groups in the Upper Paraná River floodplain (Brazil). We used data on macrophytes, fish, benthic macroinvertebrates, zooplankton, periphyton, and phytoplankton collected in up to 36 habitats during a total of eight sampling campaigns over two years. According to variation partitioning results, the importance of predictors varied among biological groups. Spatial predictors were particularly important for organisms with comparatively lower dispersal ability, such as aquatic macrophytes and fish. On the other hand, environmental predictors were particularly important for organisms with high dispersal ability, such as microalgae, indicating the importance of species sorting processes in shaping the community structure of these organisms. The importance of watercourse distances increased when spatial variables were the main predictors of metacommunity structure. The contribution of temporal predictors was low. Our results emphasize the strength of a trait-based analysis and of better defining spatial variables. More importantly, they supported the view that “all-or- nothing” interpretations on the mechanisms structuring metacommunities are rather the exception than the rule. PMID:25340577
Li, Li; Qian, Jun; Ou, Chun-Quan; Zhou, Ying-Xue; Guo, Cui; Guo, Yuming
2014-07-01
There is an increasing interest in spatial and temporal variation of air pollution and its association with weather conditions. We presented the spatial and temporal variation of Air Pollution Index (API) and examined the associations between API and meteorological factors during 2001-2011 in Guangzhou, China. A Seasonal-Trend Decomposition Procedure Based on Loess (STL) was used to decompose API. Wavelet analyses were performed to examine the relationships between API and several meteorological factors. Air quality has improved since 2005. APIs were highly correlated among five monitoring stations, and there were substantial temporal variations. Timescale-dependent relationships were found between API and a variety of meteorological factors. Temperature, relative humidity, precipitation and wind speed were negatively correlated with API, while diurnal temperature range and atmospheric pressure were positively correlated with API in the annual cycle. Our findings should be taken into account when determining air quality forecasts and pollution control measures. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Bliss, Donald; Franzoni, Linda; Rouse, Jerry; Manning, Ben
2005-09-01
An analysis method for time-dependent broadband diffuse sound fields in enclosures is described. Beginning with a formulation utilizing time-dependent broadband intensity boundary sources, the strength of these wall sources is expanded in a series in powers of an absorption parameter, thereby giving a separate boundary integral problem for each power. The temporal behavior is characterized by a Taylor expansion in the delay time for a source to influence an evaluation point. The lowest-order problem has a uniform interior field proportional to the reciprocal of the absorption parameter, as expected, and exhibits relatively slow exponential decay. The next-order problem gives a mean-square pressure distribution that is independent of the absorption parameter and is primarily responsible for the spatial variation of the reverberant field. This problem, which is driven by input sources and the lowest-order reverberant field, depends on source location and the spatial distribution of absorption. Additional problems proceed at integer powers of the absorption parameter, but are essentially higher-order corrections to the spatial variation. Temporal behavior is expressed in terms of an eigenvalue problem, with boundary source strength distributions expressed as eigenmodes. Solutions exhibit rapid short-time spatial redistribution followed by long-time decay of a predominant spatial mode.
NASA Astrophysics Data System (ADS)
Soczka Mandac, Rok; Žagar, Dušan; Faganeli, Jadran
2013-04-01
In this study influence of fresh water discharge on the spatial and temporal variability of thermohaline (TH) conditions is explored for the Bay of Koper (Bay). The Bay is subject to different driving agents: wind stress (bora, sirocco), tidal and seiches effect, buoyancy fluxes, general circulation of the Adriatic Sea and discharge of the Rizana and Badaševica rivers. These rivers have torrential characteristics that are hard to forecast in relation to meteorological events (precipitation). Therefore, during episodic events the spatial and temporal variability of TH properties in the Bay is difficult to determine [1]. Measurements of temperature, salinity and turbidity were conducted monthly on 35 sampling points in the period: June 2011 - December 2012. The data were processed and spatial interpolated with an objective analysis method. Furthermore, empirical orthogonal function analysis (EOF) [2] was applied to investigate spatial and temporal TH variations. Strong horizontal and vertical stratification was observed in the beginning of June 2011 due to high fresh water discharge of the Rizana (31 m3/s) and Badaševica (2 m3/s) rivers. The horizontal gradient (ΔT = 6°C) was noticed near the mouth of the Rizana river. Similar pattern was identified for salinity field on the boundary of the front where the gradient was ΔS = 20 PSU. Vertical temperature gradient was ΔT = 4°C while salinity gradient was ΔS = 18 PSU in the subsurface layer at depth of 3 m. Spatial analysis of the first principal component (86% of the total variance) shows uniform temperature distribution in the surface layer (1m) during the studied period. Furthermore, temporal variability of temperature shows seasonal variation with a minimum in February and maximum in August. This confirms that episodic events have a negligible effect on spatial and temporal variation of temperature in the subsurface layer. Further analysis will include application of EOF on the salinity, density and total suspended matter. Additionally, we will investigate the cross correlations between the above mentioned parameters with singular value decomposition method. Reference: 1. Faganeli, J., Planinc, R., Pezdic, J., Smodis, B., Stegnar, P., and Ogorelec, B. 1991. Marine geology of Gulf of Trieste (northern Adriatic): Geochemical aspects. Marine Geology, 99: 93-108. 2. Glover, M., Jenkins, J., and Doney, S. C. 2011. Modeling methods for marine science. Cambridge University Press, 571 p.
Kohyama, Tetsuo I; Omote, Keita; Nishida, Chizuko; Takenaka, Takeshi; Saito, Keisuke; Fujimoto, Satoshi; Masuda, Ryuichi
2015-01-01
Quantifying intraspecific genetic variation in functionally important genes, such as those of the major histocompatibility complex (MHC), is important in the establishment of conservation plans for endangered species. The MHC genes play a crucial role in the vertebrate immune system and generally show high levels of diversity, which is likely due to pathogen-driven balancing selection. The endangered Blakiston's fish owl (Bubo blakistoni) has suffered marked population declines on Hokkaido Island, Japan, during the past several decades due to human-induced habitat loss and fragmentation. We investigated the spatial and temporal patterns of genetic diversity in MHC class IIβ genes in Blakiston's fish owl, using massively parallel pyrosequencing. We found that the Blakiston's fish owl genome contains at least eight MHC class IIβ loci, indicating recent gene duplications. An analysis of sequence polymorphism provided evidence that balancing selection acted in the past. The level of MHC variation, however, was low in the current fish owl populations in Hokkaido: only 19 alleles were identified from 174 individuals. We detected considerable spatial differences in MHC diversity among the geographically isolated populations. We also detected a decline of MHC diversity in some local populations during the past decades. Our study demonstrated that the current spatial patterns of MHC variation in Blakiston's fish owl populations have been shaped by loss of variation due to the decline and fragmentation of populations, and that the short-term effects of genetic drift have counteracted the long-term effects of balancing selection.
Evidence for fish dispersal from spatial analysis of stream network topology
Hitt, N.P.; Angermeier, P.L.
2008-01-01
Developing spatially explicit conservation strategies for stream fishes requires an understanding of the spatial structure of dispersal within stream networks. We explored spatial patterns of stream fish dispersal by evaluating how the size and proximity of connected streams (i.e., stream network topology) explained variation in fish assemblage structure and how this relationship varied with local stream size. We used data from the US Environmental Protection Agency's Environmental Monitoring and Assessment Program in wadeable streams of the Mid-Atlantic Highlands region (n = 308 sites). We quantified stream network topology with a continuous analysis based on the rate of downstream flow accumulation from sites and with a discrete analysis based on the presence of mainstem river confluences (i.e., basin area >250 km2) within 20 fluvial km (fkm) from sites. Continuous variation in stream network topology was related to local species richness within a distance of ???10 fkm, suggesting an influence of fish dispersal within this spatial grain. This effect was explained largely by catostomid species, cyprinid species, and riverine species, but was not explained by zoogeographic regions, ecoregions, sampling period, or spatial autocorrelation. Sites near mainstem river confluences supported greater species richness and abundance of catostomid, cyprinid, and ictalurid fishes than did sites >20 fkm from such confluences. Assemblages at sites on the smallest streams were not related to stream network topology, consistent with the hypothesis that local stream size regulates the influence of regional dispersal. These results demonstrate that the size and proximity of connected streams influence the spatial distribution of fish and suggest that these influences can be incorporated into the designs of stream bioassessments and reserves to enhance management efficacy. ?? 2008 by The North American Benthological Society.
Determinants of single family residential water use across scales in four western US cities.
Chang, Heejun; Bonnette, Matthew Ryan; Stoker, Philip; Crow-Miller, Britt; Wentz, Elizabeth
2017-10-15
A growing body of literature examines urban water sustainability with increasing evidence that locally-based physical and social spatial interactions contribute to water use. These studies however are based on single-city analysis and often fail to consider whether these interactions occur more generally. We examine a multi-city comparison using a common set of spatially-explicit water, socioeconomic, and biophysical data. We investigate the relative importance of variables for explaining the variations of single family residential (SFR) water uses at Census Block Group (CBG) and Census Tract (CT) scales in four representative western US cities - Austin, Phoenix, Portland, and Salt Lake City, - which cover a wide range of climate and development density. We used both ordinary least squares regression and spatial error regression models to identify the influence of spatial dependence on water use patterns. Our results show that older downtown areas show lower water use than newer suburban areas in all four cities. Tax assessed value and building age are the main determinants of SFR water use across the four cities regardless of the scale. Impervious surface area becomes an important variable for summer water use in all cities, and it is important in all seasons for arid environments such as Phoenix. CT level analysis shows better model predictability than CBG analysis. In all cities, seasons, and spatial scales, spatial error regression models better explain the variations of SFR water use. Such a spatially-varying relationship of urban water consumption provides additional evidence for the need to integrate urban land use planning and municipal water planning. Copyright © 2017 Elsevier B.V. All rights reserved.
Spatio-temporal patterns of Barmah Forest virus disease in Queensland, Australia.
Naish, Suchithra; Hu, Wenbiao; Mengersen, Kerrie; Tong, Shilu
2011-01-01
Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ(2) = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.
Kiesler, James L.
2002-01-01
An analysis of the application indicates that the selected data layers to be combined should be at the greatest spatial resolution possible; however, all data layers do not have to be at the same spatial resolution. The spatial variation of the data layers should be adequately defined. The size of each grid cell should be small enough to maintain the spatial definition of smaller features within the data layers. The most accurate results are shown to occur when the values for the grid cells representing the individual data layers are summed and the mean of the summed grid-cell values is used to describe the watershed of interest.
Huang, Li-Nan; Zhou, Wen-Hua; Hallberg, Kevin B.; Wan, Cai-Yun; Li, Jie; Shu, Wen-Sheng
2011-01-01
Analysis of spatial and temporal variations in the microbial community in the abandoned tailings impoundment of a Pb-Zn mine revealed distinct microbial populations associated with the different oxidation stages of the tailings. Although Acidithiobacillus ferrooxidans and Leptospirillum spp. were consistently present in the acidic tailings, acidophilic archaea, mostly Ferroplasma acidiphilum, were predominant in the oxidized zones and the oxidation front, indicating their importance to generation of acid mine drainage. PMID:21705549
Araki, Kiwako S; Kubo, Takuya; Kudoh, Hiroshi
2017-01-01
In sessile organisms such as plants, spatial genetic structures of populations show long-lasting patterns. These structures have been analyzed across diverse taxa to understand the processes that determine the genetic makeup of organismal populations. For many sessile organisms that mainly propagate via clonal spread, epigenetic status can vary between clonal individuals in the absence of genetic changes. However, fewer previous studies have explored the epigenetic properties in comparison to the genetic properties of natural plant populations. Here, we report the simultaneous evaluation of the spatial structure of genetic and epigenetic variation in a natural population of the clonal plant Cardamine leucantha. We applied a hierarchical Bayesian model to evaluate the effects of membership of a genet (a group of individuals clonally derived from a single seed) and vegetation cover on the epigenetic variation between ramets (clonal plants that are physiologically independent individuals). We sampled 332 ramets in a 20 m × 20 m study plot that contained 137 genets (identified using eight SSR markers). We detected epigenetic variation in DNA methylation at 24 methylation-sensitive amplified fragment length polymorphism (MS-AFLP) loci. There were significant genet effects at all 24 MS-AFLP loci in the distribution of subepiloci. Vegetation cover had no statistically significant effect on variation in the majority of MS-AFLP loci. The spatial aggregation of epigenetic variation is therefore largely explained by the aggregation of ramets that belong to the same genets. By applying hierarchical Bayesian analyses, we successfully identified a number of genet-specific changes in epigenetic status within a natural plant population in a complex context, where genotypes and environmental factors are unevenly distributed. This finding suggests that it requires further studies on the spatial epigenetic structure of natural populations of diverse organisms, particularly for sessile clonal species.
Yude Pan; John Hom; Jennifer Jenkins; Richard Birdsey
2004-01-01
To assess what difference it might make to include spatially defined estimates of foliar nitrogen in the regional application of a forest ecosystem model (PnET-II), we composed model predictions of wood production from extensive ground-based forest inventory analysis data across the Mid-Atlantic region. Spatial variation in foliar N concentration was assigned based on...
Three-dimensional analysis of magnetometer array data
NASA Technical Reports Server (NTRS)
Richmond, A. D.; Baumjohann, W.
1984-01-01
A technique is developed for mapping magnetic variation fields in three dimensions using data from an array of magnetometers, based on the theory of optimal linear estimation. The technique is applied to data from the Scandinavian Magnetometer Array. Estimates of the spatial power spectra for the internal and external magnetic variations are derived, which in turn provide estimates of the spatial autocorrelation functions of the three magnetic variation components. Statistical errors involved in mapping the external and internal fields are quantified and displayed over the mapping region. Examples of field mapping and of separation into external and internal components are presented. A comparison between the three-dimensional field separation and a two-dimensional separation from a single chain of stations shows that significant differences can arise in the inferred internal component.
NASA Astrophysics Data System (ADS)
Marston, B. K.; Bishop, M. P.; Shroder, J. F.
2009-12-01
Digital terrain analysis of mountain topography is widely utilized for mapping landforms, assessing the role of surface processes in landscape evolution, and estimating the spatial variation of erosion. Numerous geomorphometry techniques exist to characterize terrain surface parameters, although their utility to characterize the spatial hierarchical structure of the topography and permit an assessment of the erosion/tectonic impact on the landscape is very limited due to scale and data integration issues. To address this problem, we apply scale-dependent geomorphometric and object-oriented analyses to characterize the hierarchical spatial structure of mountain topography. Specifically, we utilized a high resolution digital elevation model to characterize complex topography in the Shimshal Valley in the Western Himalaya of Pakistan. To accomplish this, we generate terrain objects (geomorphological features and landform) including valley floors and walls, drainage basins, drainage network, ridge network, slope facets, and elemental forms based upon curvature. Object-oriented analysis was used to characterize object properties accounting for object size, shape, and morphometry. The spatial overlay and integration of terrain objects at various scales defines the nature of the hierarchical organization. Our results indicate that variations in the spatial complexity of the terrain hierarchical organization is related to the spatio-temporal influence of surface processes and landscape evolution dynamics. Terrain segmentation and the integration of multi-scale terrain information permits further assessment of process domains and erosion, tectonic impact potential, and natural hazard potential. We demonstrate this with landform mapping and geomorphological assessment examples.
Scale-dependent variation in forest structures in naturally dynamic boreal forest landscapes
NASA Astrophysics Data System (ADS)
Kulha, Niko; Pasanen, Leena; De Grandpré, Louis; Kuuluvainen, Timo; Aakala, Tuomas
2017-04-01
Natural forest structures vary at multiple spatial scales. This variation reflects the occurrence of driving factors, such as disturbances and variation in soil or topography. To explore and understand the linkages of forest structural characteristics and factors driving their variation, we need to recognize how the structural characteristics vary in relation to spatial scale. This can be achieved by identifying scale-dependent features in forest structure within unmanaged forest landscapes. By identifying these features and examining their relationship with potential driving factors, we can better understand the dynamics of forest structural development. Here, we examine the spatial variation in forest structures at multiple spatial scales, utilizing data from old-growth boreal forests in two regions with contrasting disturbance regimes: northern Finland and north-eastern Québec, Canada ( 67° 45'N, 29° 36'E, 49° 39'N, 67° 55'W, respectively). The three landscapes (4 km2 each) in Finland are dominated by Pinus sylvestris and Picea abies, whereas the two landscapes in Québec are dominated by Abies balsamea and Picea mariana. Québec's forests are a subject to cyclic outbreaks of the eastern spruce budworm, causing extensive mortality especially in A. balsamea-dominated stands. In the Finnish landscapes, gap- to patch-scale disturbances due to tree senescence, fungi and wind, as well as infrequent surface fires in areas dominated by P. sylvestris, prevail. Owing to the differences in the species compositions and the disturbance regimes, we expect differing scales of variation between the landscapes. To quantify patterns of variation, we visually interpret stereopairs of recent aerial photographs. From the photographs, we collect information on forest canopy coverage, species composition and dead wood. For the interpretation, each 4 km2 plot is divided into 0.1ha square cells (4096 per plot). Interpretations are validated against field observations and compiled to raster maps. We analyze the raster maps with Bayesian scale space approach (iBSiZer), which aims in capturing credible variations at different spatial scales. As a result, we can detect structural entities (e.g. patches with higher canopy cover), which deviate credibly from their surroundings. The detected entities can further be linked to specific drivers. Our results show that the role of a particular driving factor varies in relation to spatial scale. For example, in the Finnish landscapes, topoedaphic factors exerted a stronger control on broad-scale forest structural characteristics, whereas recent disturbances (quantified as the amount of dead wood) appeared to play an important role in explaining the smaller scale variation of forest structures. Here, we showcase the methodology used in the detection of scale-dependent forest structural entities and present the results of our analysis of the spatial scales of variation in the natural boreal forest structures.
NASA Astrophysics Data System (ADS)
Zhang, Lulu; Liu, Jingling; Li, Yi
2015-03-01
The influence of spatial differences, which are caused by different anthropogenic disturbances, and temporal changes, which are caused by natural conditions, on macroinvertebrates with periphyton communities in Baiyangdian Lake was compared. Periphyton and macrobenthos assemblage samples were simultaneously collected on four occasions during 2009 and 2010. Based on the physical and chemical attributes in the water and sediment, the 8 sampling sites can be divided into 5 habitat types by using cluster analysis. According to coefficients variation analysis (CV), three primary conclusions can be drawn: (1) the metrics of Hilsenhoff Biotic Index (HBI), Percent Tolerant Taxa (PTT), Percent dominant taxon (PDT), and community loss index (CLI), based on macroinvertebrates, and the metrics of algal density (AD), the proportion of chlorophyta (CHL), and the proportion of cyanophyta (CYA), based on periphytons, were mostly constant throughout our study; (2) in terms of spatial variation, the CV values in the macroinvertebratebased metrics were lower than the CV values in the periphyton-based metrics, and these findings may be caused by the effects of changes in environmental factors; whereas, the CV values in the macroinvertebrate-based metrics were higher than those in the periphyton-based metrics, and these results may be linked to the influences of phenology and life history patterns of the macroinvertebrate individuals; and (3) the CV values for the functionalbased metrics were higher than those for the structuralbased metrics. Therefore, spatial and temporal variation for metrics should be considered when assessing applying the biometrics.
Spatial and Temporal Variation of Land Surface Temperature in Fujian Province from 2001 TO 2015
NASA Astrophysics Data System (ADS)
Li, Y.; Wang, X.; Ding, Z.
2018-04-01
Land surface temperature (LST) is an essential parameter in the physics of land surface processes. The spatiotemporal variations of LST on the Fujian province were studied using AQUA Moderate Resolution Imaging Spectroradiometer LST data. Considering the data gaps in remotely sensed LST products caused by cloud contamination, the Savitzky-Golay (S-G) filter method was used to eliminate the influence of cloud cover and to describe the periodical signals of LST. Observed air temperature data from 27 weather stations were employed to evaluate the fitting performance of the S-G filter method. Results indicate that S-G can effectively fit the LST time series and remove the influence of cloud cover. Based on the S-G-derived result, Spatial and temporal Variations of LST in Fujian province from 2001 to 2015 are analysed through slope analysis. The results show that: 1) the spatial distribution of annual mean LST generally exhibits consistency with altitude in the study area and the average of LST was much higher in the east than in the west. 2) The annual mean temperature of LST declines slightly among 15 years in Fujian. 3) Slope analysis reflects the spatial distribution characteristics of LST changing trend in Fujian.Improvement areas of LST are mainly concentrated in the urban areas of Fujian, especially in the eastern urban areas. Apparent descent areas are mainly distributed in the area of Zhangzhou and eastern mountain area.
Piana, Pitágoras A.; Cardoso, Bárbara F.; Dias, Joilson; Gomes, Luiz C.; Agostinho, Angelo A.; Miranda, Leandro E.
2017-01-01
Populations show spatial-temporal fluctuations in abundance, partly due to random processes and partly due to self-regulatory processes. We evaluated the effects of various external factors on the population numerical abundance of curimba Prochilodus lineatus in the upper Paraná River floodplain, Brazil, over a 19-year period. Panel data analysis was applied to examine the structure of temporal and spatial abundance while controlling auto-regressive processes and spatial non-homogeneity variances that often obscure relationships. As sources of population variation, we considered predation, competition, selected abiotic variables, construction of a dam upstream of the study area, water level and flood intensity during the spawning period. We found that biological interactions (predation and competition) were not significantly related to variations in curimba abundance; specific conductance was a space indicator of abundance, apparently linked to the biology of the species; intensity of floods determined inter-annual variation in abundances; Porto Primavera Dam negatively impacted the abundances at sites in the floodplain directly affected by discharges from the dam. Panel data analysis was a powerful tool that identified the need for intense flooding to maintain high abundances of curimba in the upper Paraná River. We believe our results apply to other species with similar life strategy.
Spatial Variations of Spectral Properties of (21) Lutetia as Observed by OSIRIS/Rosetta
NASA Astrophysics Data System (ADS)
Leyrat, Cedric; Sierks, H.; Barbieri, C.; Barucci, A.; Da Deppo, V.; De Leon, J.; Fulchignoni, M.; Fornasier, S.; Groussin, O.; Hviid, S. F.; Jorda, L.; Keller, H. U.; La Forgia, F.; Lara, L.; Lazzarin, M.; Magrin, S.; Marchi, S.; Thomas, N.; Schroder, S. E.; OSIRIS Team
2010-10-01
On July 10, 2010, the Rosetta ESA/NASA spacecraft successfully flew by the asteroid (21) Lutetia, which becomes the largest asteroid observed by a space probe. The closest approach occurred at 15H45 UTC at a relative speed of 15km/s and a relative distance of 3160 km. The Narrow Angle Camera (NAC) and the Wide Angle Camera (WAC) of the OSIRIS instrument onboard Rosetta acquired images at different phase angles ranging from almost zero to more than 150 degrees. The best spatial resolution (60 m/pixel) allowed to reveal a very complex topography with several features and different crater's surface densities. Spectrophotometric analysis of the data could suggest spatial variations of the albedo and spectral properties at the surface of the asteroid, at least in the northern hemisphere. Numerous sets of data have been obtained at different wavelengths from 270nm to 980nm. We will first present a color-color analysis of data in order to locate landscapes where surface variegation is present. We will also present a more accurate study of spectral properties using the shape model and different statistical methods. Possible variations of the surface spectral properties with the slope of the ground and the gravity field orientation will be discussed as well.
Spatio-Temporal Analysis of Smear-Positive Tuberculosis in the Sidama Zone, Southern Ethiopia
Dangisso, Mesay Hailu; Datiko, Daniel Gemechu; Lindtjørn, Bernt
2015-01-01
Background Tuberculosis (TB) is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. Ethiopia is a country with a high burden of TB, with regional variations in TB case notification rates (CNRs). However, TB program reports are often compiled and reported at higher administrative units that do not show the burden at lower units, so there is limited information about the spatial distribution of the disease. We therefore aim to assess the spatial distribution and presence of the spatio-temporal clustering of the disease in different geographic settings over 10 years in the Sidama Zone in southern Ethiopia. Methods A retrospective space–time and spatial analysis were carried out at the kebele level (the lowest administrative unit within a district) to identify spatial and space-time clusters of smear-positive pulmonary TB (PTB). Scan statistics, Global Moran’s I, and Getis and Ordi (Gi*) statistics were all used to help analyze the spatial distribution and clusters of the disease across settings. Results A total of 22,545 smear-positive PTB cases notified over 10 years were used for spatial analysis. In a purely spatial analysis, we identified the most likely cluster of smear-positive PTB in 192 kebeles in eight districts (RR= 2, p<0.001), with 12,155 observed and 8,668 expected cases. The Gi* statistic also identified the clusters in the same areas, and the spatial clusters showed stability in most areas in each year during the study period. The space-time analysis also detected the most likely cluster in 193 kebeles in the same eight districts (RR= 1.92, p<0.001), with 7,584 observed and 4,738 expected cases in 2003-2012. Conclusion The study found variations in CNRs and significant spatio-temporal clusters of smear-positive PTB in the Sidama Zone. The findings can be used to guide TB control programs to devise effective TB control strategies for the geographic areas characterized by the highest CNRs. Further studies are required to understand the factors associated with clustering based on individual level locations and investigation of cases. PMID:26030162
A variational Bayes spatiotemporal model for electromagnetic brain mapping.
Nathoo, F S; Babul, A; Moiseev, A; Virji-Babul, N; Beg, M F
2014-03-01
In this article, we present a new variational Bayes approach for solving the neuroelectromagnetic inverse problem arising in studies involving electroencephalography (EEG) and magnetoencephalography (MEG). This high-dimensional spatiotemporal estimation problem involves the recovery of time-varying neural activity at a large number of locations within the brain, from electromagnetic signals recorded at a relatively small number of external locations on or near the scalp. Framing this problem within the context of spatial variable selection for an underdetermined functional linear model, we propose a spatial mixture formulation where the profile of electrical activity within the brain is represented through location-specific spike-and-slab priors based on a spatial logistic specification. The prior specification accommodates spatial clustering in brain activation, while also allowing for the inclusion of auxiliary information derived from alternative imaging modalities, such as functional magnetic resonance imaging (fMRI). We develop a variational Bayes approach for computing estimates of neural source activity, and incorporate a nonparametric bootstrap for interval estimation. The proposed methodology is compared with several alternative approaches through simulation studies, and is applied to the analysis of a multimodal neuroimaging study examining the neural response to face perception using EEG, MEG, and fMRI. © 2013, The International Biometric Society.
Spatial Variations of DOM Compositions in the River with Multi-functional Weir
NASA Astrophysics Data System (ADS)
Yoon, S. M.; Choi, J. H.
2017-12-01
With the global trend to construct artificial impoundments over the last decades, there was a Large River Restoration Project conducted in South Korea from 2010 to 2011. The project included enlargement of river channel capacity and construction of multi-functional weirs, which can alter the hydrological flow of the river and cause spatial variations of water quality indicators, especially DOM (Dissolved Organic Matter) compositions. In order to analyze the spatial variations of organic matter, water samples were collected longitudinally (5 points upstream from the weir), horizontally (left, center, right at each point) and vertically (1m interval at each point). The specific UV-visible absorbance (SUVA) and fluorescence excitation-emission matrices (EEMs) have been used as rapid and non-destructive analytical methods for DOM compositions. In addition, parallel factor analysis (PARAFAC) has adopted for extracting a set of representative fluorescence components from EEMs. It was assumed that autochthonous DOM would be dominant near the weir due to the stagnation of hydrological flow. However, the results showed that the values of fluorescence index (FI) were 1.29-1.47, less than 2, indicating DOM of allochthonous origin dominated in the water near the weir. PARAFAC analysis also showed the peak at 450 nm of emission and < 250 nm of excitation which represented the humic substances group with terrestrial origins. There was no significant difference in the values of Biological index (BIX), however, values of humification index (HIX) spatially increased toward the weir. From the results of the water sample analysis, the river with multi-functional weir is influenced by the allochthonous DOM instead of autochthonous DOM and seems to accumulate humic substances near the weir.
Parallel Evolution of Copy-Number Variation across Continents in Drosophila melanogaster
Schrider, Daniel R.; Hahn, Matthew W.; Begun, David J.
2016-01-01
Genetic differentiation across populations that is maintained in the presence of gene flow is a hallmark of spatially varying selection. In Drosophila melanogaster, the latitudinal clines across the eastern coasts of Australia and North America appear to be examples of this type of selection, with recent studies showing that a substantial portion of the D. melanogaster genome exhibits allele frequency differentiation with respect to latitude on both continents. As of yet there has been no genome-wide examination of differentiated copy-number variants (CNVs) in these geographic regions, despite their potential importance for phenotypic variation in Drosophila and other taxa. Here, we present an analysis of geographic variation in CNVs in D. melanogaster. We also present the first genomic analysis of geographic variation for copy-number variation in the sister species, D. simulans, in order to investigate patterns of parallel evolution in these close relatives. In D. melanogaster we find hundreds of CNVs, many of which show parallel patterns of geographic variation on both continents, lending support to the idea that they are influenced by spatially varying selection. These findings support the idea that polymorphic CNVs contribute to local adaptation in D. melanogaster. In contrast, we find very few CNVs in D. simulans that are geographically differentiated in parallel on both continents, consistent with earlier work suggesting that clinal patterns are weaker in this species. PMID:26809315
Spatial Variations of Chemical Abundances in Titan's Atmosphere as Revealed by ALMA
NASA Astrophysics Data System (ADS)
Thelen, Alexander E.; Nixon, Conor; Chanover, Nancy J.; Molter, Edward; Serigano, Joseph; Cordiner, Martin; Charnley, Steven B.; Teanby, Nicholas A.; Irwin, Patrick
2016-10-01
Complex organic molecules in Titan's atmosphere - formed through the dissociation of N2 and CH4 - exhibit latitudinal variations in abundance as observed by Cassini. Chemical species including hydrocarbons - such as CH3CCH - and nitriles - HCN, HC3N, CH3CN, and C2H5CN - may show spatial abundance variations as a result of atmospheric circulation, photochemical production and subsequent destruction throughout Titan's seasonal cycle. Recent calibration images of Titan taken by the Atacama Large Millimeter/Submillimeter Array (ALMA) with beam sizes of ~0.3'' allow for measurements of rotational transition lines of these species in spatially resolved regions of Titan's disk. We present abundance profiles obtained from public ALMA data taken in 2014, as Titan transitioned into northern summer. Abundance profiles in Titan's lower/middle atmosphere were retrieved by modeling high resolution ALMA spectra using the Non-linear Optimal Estimator for MultivariatE Spectral analySIS (NEMESIS) radiative transfer code. These retrievals were performed using spatial temperature profiles obtained by modeling strong CO lines from datasets taken in similar times with comparable resolution. We compare the abundance variations of chemical species to measurements made using Cassini data. Comparisons of chemical species with strong abundance enhancements over the poles will inform our knowledge of chemical lifetimes in Titan's atmosphere, and allow us to observe the important changes in production and circulation of numerous organic molecules which are attributed to Titan's seasons.
Atlas warping for brain morphometry
NASA Astrophysics Data System (ADS)
Machado, Alexei M. C.; Gee, James C.
1998-06-01
In this work, we describe an automated approach to morphometry based on spatial normalizations of the data, and demonstrate its application to the analysis of gender differences in the human corpus callosum. The purpose is to describe a population by a reduced and representative set of variables, from which a prior model can be constructed. Our approach is rooted in the assumption that individual anatomies can be considered as quantitative variations on a common underlying qualitative plane. We can therefore imagine that a given individual's anatomy is a warped version of some referential anatomy, also known as an atlas. The spatial warps which transform a labeled atlas into anatomic alignment with a population yield immediate knowledge about organ size and shape in the group. Furthermore, variation within the set of spatial warps is directly related to the anatomic variation among the subjects. Specifically, the shape statistics--mean and variance of the mappings--for the population can be calculated in a special basis, and an eigendecomposition of the variance performed to identify the most significant modes of shape variation. The results obtained with the corpus callosum study confirm the existence of substantial anatomical differences between males and females, as reported in previous experimental work.
Spatial and temporal variability of chorus and hiss
NASA Astrophysics Data System (ADS)
Santolik, O.; Hospodarsky, G. B.; Kurth, W. S.; Kletzing, C.
2017-12-01
Whistler-mode electromagnetic waves, especially natural emissions of chorus and hiss, have been shown to influence the dynamics of the Van Allen radiation belts via quasi-linear or nonlinear wave particle interactions, transferring energy between different electron populations. Average intensities of chorus and hiss emissions have been found to increase with increasing levels of geomagnetic activity but their stochastic variations in individual spacecraft measurements are usually larger these large-scale temporal effects. To separate temporal and spatial variations of wave characteristics, measurements need to be simultaneously carried out in different locations by identical and/or well calibrated instrumentation. We use two-point survey measurements of the Waves instruments of the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) onboard two Van Allen Probes to asses spatial and temporal variability of chorus and hiss. We take advantage of a systematic analysis of this large data set which has been collected during 2012-2017 over a range of separation vectors of the two spacecraft. We specifically address the question whether similar variations occur at different places at the same time. Our results indicate that power variations are dominated by separations in MLT at scales larger than 0.5h.
NASA Astrophysics Data System (ADS)
Rupa, Chandra; Mujumdar, Pradeep
2016-04-01
In urban areas, quantification of extreme precipitation is important in the design of storm water drains and other infrastructure. Intensity Duration Frequency (IDF) relationships are generally used to obtain design return level for a given duration and return period. Due to lack of availability of extreme precipitation data for sufficiently large number of years, estimating the probability of extreme events is difficult. Typically, a single station data is used to obtain the design return levels for various durations and return periods, which are used in the design of urban infrastructure for the entire city. In an urban setting, the spatial variation of precipitation can be high; the precipitation amounts and patterns often vary within short distances of less than 5 km. Therefore it is crucial to study the uncertainties in the spatial variation of return levels for various durations. In this work, the extreme precipitation is modeled spatially using the Bayesian hierarchical analysis and the spatial variation of return levels is studied. The analysis is carried out with Block Maxima approach for defining the extreme precipitation, using Generalized Extreme Value (GEV) distribution for Bangalore city, Karnataka state, India. Daily data for nineteen stations in and around Bangalore city is considered in the study. The analysis is carried out for summer maxima (March - May), monsoon maxima (June - September) and the annual maxima rainfall. In the hierarchical analysis, the statistical model is specified in three layers. The data layer models the block maxima, pooling the extreme precipitation from all the stations. In the process layer, the latent spatial process characterized by geographical and climatological covariates (lat-lon, elevation, mean temperature etc.) which drives the extreme precipitation is modeled and in the prior level, the prior distributions that govern the latent process are modeled. Markov Chain Monte Carlo (MCMC) algorithm (Metropolis Hastings algorithm within a Gibbs sampler) is used to obtain the samples of parameters from the posterior distribution of parameters. The spatial maps of return levels for specified return periods, along with the associated uncertainties, are obtained for the summer, monsoon and annual maxima rainfall. Considering various covariates, the best fit model is selected using Deviance Information Criteria. It is observed that the geographical covariates outweigh the climatological covariates for the monsoon maxima rainfall (latitude and longitude). The best covariates for summer maxima and annual maxima rainfall are mean summer precipitation and mean monsoon precipitation respectively, including elevation for both the cases. The scale invariance theory, which states that statistical properties of a process observed at various scales are governed by the same relationship, is used to disaggregate the daily rainfall to hourly scales. The spatial maps of the scale are obtained for the study area. The spatial maps of IDF relationships thus generated are useful in storm water designs, adequacy analysis and identifying the vulnerable flooding areas.
Spatial and Temporal Dynamics of Pacific Oyster Hemolymph Microbiota across Multiple Scales
Lokmer, Ana; Goedknegt, M. Anouk; Thieltges, David W.; Fiorentino, Dario; Kuenzel, Sven; Baines, John F.; Wegner, K. Mathias
2016-01-01
Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics. PMID:27630625
A general method for the layout of ailerons and elevators of gliders and motorplanes
NASA Technical Reports Server (NTRS)
Hiller, M. H.
1979-01-01
A method is described which allows the layout of the spatial driving mechanism of the aileron for a glider or a motorplane to be performed in a systematic manner. In particular, a prescribed input-output behavior of the mechanism can be realized by variation of individual parameters of the spatial four-bar mechanisms which constitute the entire driving mechanism. By means of a sensitivity analysis, a systematic choice of parameters is possible. At the same time the forces acting in the mechanism can be limited by imposing maximum values of the forces as secondary conditions during the variation process.
Regional-scale drivers of marine nematode distribution in Southern Ocean continental shelf sediments
NASA Astrophysics Data System (ADS)
Hauquier, Freija; Verleyen, Elie; Tytgat, Bjorn; Vanreusel, Ann
2018-07-01
Many marine meiofauna taxa seem to possess cosmopolitan species distributions, despite their endobenthic lifestyle and restricted long-distance dispersal capacities. In light of this paradox we used a metacommunity framework to study spatial turnover in free-living nematode distribution and assess the importance of local environmental conditions in explaining differences between communities in surface and subsurface sediments of the Southern Ocean continental shelf. We analysed nematode community structure in two sediment layers (0-3 cm and 3-5 cm) of locations maximum 2400 km apart. We first focused on a subset of locations to evaluate whether the genus level is sufficiently taxonomically fine-grained to study large-scale patterns in nematode community structure. We subsequently used redundancy and variation partitioning analyses to quantify the unique and combined effects of local environmental conditions and spatial descriptors on genus-level community composition. Macroecological patterns in community structure were highly congruent at the genus and species level. Nematode community composition was highly divergent between both depth strata, likely as a result of local abiotic conditions. Variation in community structure between the different regions largely stemmed from turnover (i.e. genus/species replacement) rather than nestedness (i.e. genus/species loss). The level of turnover among communities increased with geographic distance and was more pronounced in subsurface layers compared to surface sediments. Variation partitioning analysis revealed that both environmental and spatial predictors significantly explained variation in community structure. Moreover, the shared fraction of both sets of variables was high, which suggested a substantial amount of spatially structured environmental variation. Additionally, the effect of space independent of environment was much higher than the effect of environment independent of space, which shows the importance of including spatial descriptors in meiofauna and nematode community ecology. Large-scale assessment of free-living nematode diversity and abundance in the Southern Ocean shelf zone revealed strong horizontal and vertical spatial structuring in response to local environmental conditions, in combination with (most likely) dispersal limitation.
Cauvy-Fraunié, Sophie; Espinosa, Rodrigo; Andino, Patricio; Jacobsen, Dean; Dangles, Olivier
2015-01-01
Under the ongoing climate change, understanding the mechanisms structuring the spatial distribution of aquatic species in glacial stream networks is of critical importance to predict the response of aquatic biodiversity in the face of glacier melting. In this study, we propose to use metacommunity theory as a conceptual framework to better understand how river network structure influences the spatial organization of aquatic communities in glacierized catchments. At 51 stream sites in an Andean glacierized catchment (Ecuador), we sampled benthic macroinvertebrates, measured physico-chemical and food resource conditions, and calculated geographical, altitudinal and glaciality distances among all sites. Using partial redundancy analysis, we partitioned community variation to evaluate the relative strength of environmental conditions (e.g., glaciality, food resource) vs. spatial processes (e.g., overland, watercourse, and downstream directional dispersal) in organizing the aquatic metacommunity. Results revealed that both environmental and spatial variables significantly explained community variation among sites. Among all environmental variables, the glacial influence component best explained community variation. Overland spatial variables based on geographical and altitudinal distances significantly affected community variation. Watercourse spatial variables based on glaciality distances had a unique significant effect on community variation. Within alpine catchment, glacial meltwater affects macroinvertebrate metacommunity structure in many ways. Indeed, the harsh environmental conditions characterizing glacial influence not only constitute the primary environmental filter but also, limit water-borne macroinvertebrate dispersal. Therefore, glacier runoff acts as an aquatic dispersal barrier, isolating species in headwater streams, and preventing non-adapted species to colonize throughout the entire stream network. Under a scenario of glacier runoff decrease, we expect a reduction in both environmental filtering and dispersal limitation, inducing a taxonomic homogenization of the aquatic fauna in glacierized catchments as well as the extinction of specialized species in headwater groundwater and glacier-fed streams, and consequently an irreversible reduction in regional diversity. PMID:26308853
Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun
2014-01-01
Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.
Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun
2014-01-01
Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760
Yang, Qianqian; Li, Tongwen; Shen, Huanfeng; Zhang, Liangpei
2017-01-01
The interactions between PM2.5 and meteorological factors play a crucial role in air pollution analysis. However, previous studies that have researched the relationships between PM2.5 concentration and meteorological conditions have been mainly confined to a certain city or district, and the correlation over the whole of China remains unclear. Whether spatial and seasonal variations exist deserves further research. In this study, the relationships between PM2.5 concentration and meteorological factors were investigated in 68 major cities in China for a continuous period of 22 months from February 2013 to November 2014, at season, year, city, and regional scales, and the spatial and seasonal variations were analyzed. The meteorological factors were relative humidity (RH), temperature (TEM), wind speed (WS), and surface pressure (PS). We found that spatial and seasonal variations of their relationships with PM2.5 exist. Spatially, RH is positively correlated with PM2.5 concentration in north China and Urumqi, but the relationship turns to negative in other areas of China. WS is negatively correlated with PM2.5 everywhere except for Hainan Island. PS has a strong positive relationship with PM2.5 concentration in northeast China and mid-south China, and in other areas the correlation is weak. Seasonally, the positive correlation between PM2.5 concentration and RH is stronger in winter and spring. TEM has a negative relationship with PM2.5 in autumn and the opposite in winter. PS is more positively correlated with PM2.5 in autumn than in other seasons. Our study investigated the relationships between PM2.5 and meteorological factors in terms of spatial and seasonal variations, and the conclusions about the relationships between PM2.5 and meteorological factors are more comprehensive and precise than before. We suggest that the variations could be considered in PM2.5 concentration prediction and haze control to improve the prediction accuracy and policy efficiency. PMID:29206181
Spatial and temporal variations of aridity indices in Iraq
NASA Astrophysics Data System (ADS)
Şarlak, Nermin; Mahmood Agha, Omar M. A.
2017-06-01
This study investigates the spatial and temporal variations of the aridity indices to reveal the desertification vulnerability of Iraq region. Relying on temperature and precipitation data taken from 28 meteorological stations for 31 years, the study aims to determine (1) dry land types and their delineating boundaries and (2) temporal change in aridity conditions in Iraq. Lang's aridity (Im), De Martonne's aridity (Am), United Nations Environmental Program (UNEP) aridity (AIu), and Erinç aridity (IE) indices were selected in this study because of the scarcity of the observed data. The analysis of the spatial variation of aridity indices exhibited that the arid and semi-arid regions cover about 97% of the country's areas. As for temporal variations, it was observed that the aridity indices tend to decrease (statistically significant or not) for all stations. The cumulative sum charts (CUSUMs) were applied to detect the year on which the climate pattern of aridity indices had changed from one pattern to another. The abrupt change point was detected around year 1997 for the majority of the stations. Thus, the spatial and temporal aridity characteristics in Iraq were examined for the two periods 1980-1997 and 1998-2011 (before and after the change-point year) to observe the influence of abrupt change point on aridity phenomena. The spatial variation after 1997 was observed from semi-arid (dry sub humid) to arid (semi-arid) especially at the stations located in northern Iraq, while hyper-arid and arid climatic conditions were still dominant over southern and central Iraq. Besides, the negative temporal variations of the two periods 1980-1997 and 1998-2011 were obtained for almost every station. As a result, it was emphasized that Iraq region, like other Middle East regions, has become drier after 1997. The observed reduction in precipitation and increase in temperature for this region seem to make the situation worse in future.
Localized Hotspots Drive Continental Geography of Abnormal Amphibians on U.S. Wildlife Refuges
Reeves, Mari K.; Medley, Kimberly A.; Pinkney, Alfred E.; Holyoak, Marcel; Johnson, Pieter T. J.; Lannoo, Michael J.
2013-01-01
Amphibians with missing, misshapen, and extra limbs have garnered public and scientific attention for two decades, yet the extent of the phenomenon remains poorly understood. Despite progress in identifying the causes of abnormalities in some regions, a lack of knowledge about their broader spatial distribution and temporal dynamics has hindered efforts to understand their implications for amphibian population declines and environmental quality. To address this data gap, we conducted a nationwide, 10-year assessment of 62,947 amphibians on U.S. National Wildlife Refuges. Analysis of a core dataset of 48,081 individuals revealed that consistent with expected background frequencies, an average of 2% were abnormal, but abnormalities exhibited marked spatial variation with a maximum prevalence of 40%. Variance partitioning analysis demonstrated that factors associated with space (rather than species or year sampled) captured 97% of the variation in abnormalities, and the amount of partitioned variance decreased with increasing spatial scale (from site to refuge to region). Consistent with this, abnormalities occurred in local to regional hotspots, clustering at scales of tens to hundreds of kilometers. We detected such hotspot clusters of high-abnormality sites in the Mississippi River Valley, California, and Alaska. Abnormality frequency was more variable within than outside of hotspot clusters. This is consistent with dynamic phenomena such as disturbance or natural enemies (pathogens or predators), whereas similarity of abnormality frequencies at scales of tens to hundreds of kilometers suggests involvement of factors that are spatially consistent at a regional scale. Our characterization of the spatial and temporal variation inherent in continent-wide amphibian abnormalities demonstrates the disproportionate contribution of local factors in predicting hotspots, and the episodic nature of their occurrence. PMID:24260103
NASA Astrophysics Data System (ADS)
Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.
2013-12-01
In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.
NASA Astrophysics Data System (ADS)
Akin, S.; Winemiller, K. O.; Gelwick, F. P.
2003-05-01
Fish and macrocrustacean assemblage structure was analyzed along an estuarine gradient at Mad Island Marsh (MIM), Matagorda Bay, TX, during March 1998-August 1999. Eight estuarine-dependent fish species accounted for 94% of the individual fishes collected, and three species accounted for 96% of macrocrustacean abundance. Consistent with evidence from other Gulf of Mexico estuarine studies, species richness and abundance were highest during late spring and summer, and lowest during winter and early spring. Sites near the bay supported the most individuals and species. Associations between fish abundance and environmental variables were examined with canonical correspondence analysis. The dominant gradient was associated with water depth and distance from the bay. The secondary gradient reflected seasonal variation and was associated with temperature, salinity, dissolved oxygen, and vegetation cover. At the scales examined, estuarine biota responded to seasonal variation more than spatial variation. Estuarine-dependent species dominated the fauna and were common throughout the open waters of the shallow lake during winter-early spring when water temperature and salinity were low and dissolved oxygen high. During summer-early fall, sub-optimal environmental conditions (high temperature, low DO) in upper reaches accounted for strong spatial variation in assemblage composition. Small estuarine-resident fishes and the blue crab ( Callinectes sapidus) were common in warm, shallow, vegetated inland sites during summer-fall. Estuarine-dependent species were common at deeper, more saline locations near the bay during this period. During summer, freshwater species, such as gizzard shad ( Dorosoma cepedianum) and gars ( Lepisosteus spp.), were positively associated with water depth and proximity to the bay. The distribution and abundance of fishes in MIM appear to result from the combined effects of endogenous, seasonal patterns of reproduction and migration operating on large spatial scales, and species-specific response to local environmental variation.
NASA Astrophysics Data System (ADS)
Olson, E. J.; Dodd, J. P.; Rivera, M. A.
2016-12-01
Arid regions are extremely sensitive to variations hydroclimate. However, our understanding of past hydroclimate variations in these regions is often limited by a paucity of spatially resolved proxy data. The Atacama Desert of northern Chile is one of the driest regions on Earth, and hydroclimatic processes in the Atacama Desert may be a useful proxy for understanding the implications of expanding global aridity. In order to assess the ability of tree-ring isotope studies to record changes in hydrology and terrestrial climate in the Atacama Desert, oxygen (δ18O), carbon (δ13C) and hydrogen (δ2H) isotope values in tree rings of Prosopis tamarugo are analyzed for the modern period (1954-2014) when anthropogenic change to regional groundwater levels have been most notable. Samples of wood cellulose were collected throughout the Pampa del Tamarugal basin from 14 individuals and used to create an interpolated surface of isotope variations. The isotope data were then compared to groundwater depth from well monitoring data provided by the Dirección de General de Agua of Chile. There is a significant correlation between groundwater level and isotope values with best agreement occurring during the past two decades for δ18O (r = 0.58), δ13C (r = 0.55), and δ2H (r = 0.66) values. This spatial correlation analysis reveals that tree ring a-cellulose isotope values are a suitable proxy for reconstructing groundwater depth in the Pampa del Tamarugal Basin. A stepwise multiregression analysis between δ18O values of cellulose and several other environmental variables including groundwater level, relative humidity, and temperature suggest that groundwater depth is the dominate control of variation in the modern δ18O tree ring record. The response of tree cellulose to the hydroclimate in this region suggests that tree ring isotope variations may be used to reconstruct past hydroclimate conditions in arid regions throughout the globe.
Yurkowski, David J; Ferguson, Steven H; Semeniuk, Christina A D; Brown, Tanya M; Muir, Derek C G; Fisk, Aaron T
2016-03-01
Spatial and temporal variation can confound interpretations of relationships within and between species in terms of diet composition, niche size, and trophic position (TP). The cause of dietary variation within species is commonly an ontogenetic niche shift, which is a key dynamic influencing community structure. We quantified spatial and temporal variations in ringed seal (Pusa hispida) diet, niche size, and TP during ontogeny across the Arctic-a rapidly changing ecosystem. Stable carbon and nitrogen isotope analysis was performed on 558 liver and 630 muscle samples from ringed seals and on likely prey species from five locations ranging from the High to the Low Arctic. A modest ontogenetic diet shift occurred, with adult ringed seals consuming more forage fish (approximately 80 versus 60 %) and having a higher TP than subadults, which generally decreased with latitude. However, the degree of shift varied spatially, with adults in the High Arctic presenting a more restricted niche size and consuming more Arctic cod (Boreogadus saida) than subadults (87 versus 44 %) and adults at the lowest latitude (29 %). The TPs of adult and subadult ringed seals generally decreased with latitude (4.7-3.3), which was mainly driven by greater complexity in trophic structure within the zooplankton communities. Adult isotopic niche size increased over time, likely due to the recent circumpolar increases in subarctic forage fish distribution and abundance. Given the spatial and temporal variability in ringed seal foraging ecology, ringed seals exhibit dietary plasticity as a species, suggesting adaptability in terms of their diet to climate change.
Evaluation of Improved Engine Compartment Overheat Detection Techniques.
1986-08-01
radiation properties (emissivity and reflectivity) of the surface. The first task of the numerical procedure is to investigate the radiosity (radiative heat...and radiosity are spatially uniform within each zone. 0 Radiative properties are spatially uniform and independent of direction. 0 The enclosure is...variation in the radiosity will be nonuniform in distribution in that region. The zone analysis method assumes the : . ,. temperature and radiation
NASA Astrophysics Data System (ADS)
Gao, Zhenxun; Wang, Jingying; Jiang, Chongwen; Lee, Chunhian
2014-11-01
In the framework of Reynolds-averaged Navier-Stokes simulation, supersonic turbulent combustion flows at the German Aerospace Centre (DLR) combustor and Japan Aerospace Exploration Agency (JAXA) integrated scramjet engine are numerically simulated using the flamelet model. Based on the DLR combustor case, theoretical analysis and numerical experiments conclude that: the finite rate model only implicitly considers the large-scale turbulent effect and, due to the lack of the small-scale non-equilibrium effect, it would overshoot the peak temperature compared to the flamelet model in general. Furthermore, high-Mach-number compressibility affects the flamelet model mainly through two ways: the spatial pressure variation and the static enthalpy variation due to the kinetic energy. In the flamelet library, the mass fractions of the intermediate species, e.g. OH, are more sensible to the above two effects than the main species such as H2O. Additionally, in the combustion flowfield where the pressure is larger than the value adopted in the generation of the flamelet library or the conversion from the static enthalpy to the kinetic energy occurs, the temperature obtained by the flamelet model without taking compressibility effects into account would be undershot, and vice versa. The static enthalpy variation effect has only little influence on the temperature simulation of the flamelet model, while the effect of the spatial pressure variation may cause relatively large errors. From the JAXA case, it is found that the flamelet model cannot in general be used for an integrated scramjet engine. The existence of the inlet together with the transverse injection scheme could cause large spatial variations of pressure, so the pressure value adopted for the generation of a flamelet library should be fine-tuned according to a pre-simulation of pure mixing.
Schuurman, Nadine; Hameed, S. Morad; Fiedler, Robert; Bell, Nathaniel; Simons, Richard K.
2008-01-01
Despite important advances in the prevention and treatment of trauma, preventable injuries continue to impact the lives of millions of people. Motor vehicle collisions and violence claim close to 3 million lives each year worldwide. Public health agencies have promoted the need for systematic and ongoing surveillance as a foundation for successful injury control. Surveillance has been used to quantify the incidence of injury for the prioritization of further research, monitor trends over time, identify new injury patterns, and plan and evaluate prevention and intervention efforts. Advances in capability to handle spatial data and substantial increases in computing power have positioned geographic information science (GIS) as a potentially important tool for health surveillance and the spatial organization of health care, and for informing prevention and acute care interventions. Two themes emerge in the trauma literature with respect to GIS theory and techniques: identifying determinants associated with the risk of trauma to guide injury prevention efforts and evaluating the spatial organization and accessibility of acute trauma care systems. We review the current literature on trauma and GIS research and provide examples of the importance of accounting for spatial scale when using spatial analysis for surveillance. The examples illustrate the effect of scale on incident analysis, the geographic variation of major injury across British Columbia's health service delivery areas (HSDAs) and the rates of variation of injury within individual HSDAs. PMID:18841227
A Spatio-Temporal Approach for Global Validation and Analysis of MODIS Aerosol Products
NASA Technical Reports Server (NTRS)
Ichoku, Charles; Chu, D. Allen; Mattoo, Shana; Kaufman, Yoram J.; Remer, Lorraine A.; Tanre, Didier; Slutsker, Ilya; Holben, Brent N.; Lau, William K. M. (Technical Monitor)
2001-01-01
With the launch of the MODIS sensor on the Terra spacecraft, new data sets of the global distribution and properties of aerosol are being retrieved, and need to be validated and analyzed. A system has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of the MODIS aerosol parameters over more than 100 validation sites spread around the globe. Corresponding statistics are also computed from temporal subsets of AERONET-derived aerosol data. The means and standard deviations of identical parameters from MOMS and AERONET are compared. Although, their means compare favorably, their standard deviations reveal some influence of surface effects on the MODIS aerosol retrievals over land, especially at low aerosol loading. The direction and rate of spatial variation from MODIS are used to study the spatial distribution of aerosols at various locations either individually or comparatively. This paper introduces the methodology for generating and analyzing the data sets used by the two MODIS aerosol validation papers in this issue.
Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia
Naish, Suchithra; Hu, Wenbiao; Mengersen, Kerrie; Tong, Shilu
2011-01-01
Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland. PMID:22022430
NASA Astrophysics Data System (ADS)
Schirmer, Michael; Harder, Phillip; Pomeroy, John
2016-04-01
The spatial and temporal dynamics of mountain snowmelt are controlled by the spatial distribution of snow accumulation and redistribution and the pattern of melt energy applied to this snowcover. In order to better quantify the spatial variations of accumulation and ablation, Structure-from-Motion techniques were applied to sequential aerial photographs of an alpine ridge in the Canadian Rocky Mountains taken from an Unmanned Aerial Vehicle (UAV). Seven spatial maps of snow depth and changes to depth during late melt (May-July) were generated at very high resolutions covering an area of 800 x 600 m. The accuracy was assessed with over 100 GPS measurements and RMSE were found to be less than 10 cm. Low resolution manual measurements of density permitted calculation of snow water equivalent (SWE) and change in SWE (ablation rate). The results indicate a highly variable initial SWE distribution, which was five times more variable than the spatial variation in ablation rate. Spatial variation in ablation rate was still substantial, with a factor of two difference between north and south aspects and small scale variations due to local dust deposition. However, the impact of spatial variations in ablation rate on the snowcover depletion curve could not be discerned. The reason for this is that only a weak spatial correlation developed between SWE and ablation rate. These findings suggest that despite substantial variations in ablation rate, snowcover depletion curve calculations should emphasize the spatial variation of initial SWE rather than the variation in ablation rate. While there is scientific evidence from other field studies that support this, there are also studies that suggest that spatial variations in ablation rate can influence snowcover depletion curves in complex terrain, particularly in early melt. The development of UAV photogrammetry has provided an opportunity for further detailed measurement of ablation rates, SWE and snowcover depletion over complex terrain and UAV field studies are recommended to clarify the relative importance of SWE and melt variability on snowcover depletion in various environmental conditions.
Zhu, Xian-Jin; Zhang, Han-Qi; Zhao, Tian-Hong; Li, Jian-Dong; Yin, Hong
2017-10-12
Spatial and temporal variations are important points of focus in ecological research. Analysing their differences improves our understanding on the variations of ecological phenomena. Using data from the Liaoning Statistical Yearbook, we investigated the spatial and temporal variations of cropland carbon transfer (CCT), an important ecological phenomenon in quantifying the regional carbon budget, in particular, the influencing factors and difference. The results showed that, from 1992 to 2014, the average CCT in Liaoning province was 18.56 TgC yr -1 and decreased from northwest to southeast. CCT spatial variation was primarily affected by the ratio of planting area to regional area (RPR) via its effect on the magnitude of carbon transfer (MCT), which depended mainly on fertilizer usage per area (FUA). From 1992 to 2014, CCT exhibited a significantly increasing trend with a rate of 0.48 TgC yr -1 . The inter-annual variation of CCT was dominated by carbon transfer per planting area (CTP) through its effect on MCT, which significantly correlated with FUA but showed no significant correlation with climatic factors. Therefore, the factors affecting the spatial variation of CCT differed from those that affected its inter-annual variation, indicating that the spatial and temporal variations of ecological phenomena were affected by divergent factors.
Hanson, Jamie L.; Chung, Moo K.; Avants, Brian B.; Rudolph, Karen D.; Shirtcliff, Elizabeth A.; Gee, James C.; Davidson, Richard J.; Pollak, Seth D.
2012-01-01
A large corpus of research indicates exposure to stress impairs cognitive abilities, specifically executive functioning dependent on the prefrontal cortex (PFC). We collected structural MRI scans (n=61), well-validated assessments of executive functioning, and detailed interviews assessing stress exposure in humans, to examine whether cumulative life stress affected brain morphometry and one type of executive functioning, spatial working memory, during adolescence—a critical time of brain development and reorganization. Analysis of variations in brain structure revealed that cumulative life stress and spatial working memory were related to smaller volumes in the PFC, specifically prefrontal gray and white matter between the anterior cingulate and the frontal poles. Mediation analyses revealed that individual differences in prefrontal volumes accounted for the association between cumulative life stress and spatial working memory. These results suggest that structural changes in the PFC may serve as a mediating mechanism through which greater cumulative life stress engenders decrements in cognitive functioning. PMID:22674267
Siebeneck, Laura K; Cova, Thomas J
2012-09-01
Developing effective evacuation and return-entry plans requires understanding the spatial and temporal dimensions of risk perception experienced by evacuees throughout a disaster event. Using data gathered from the 2008 Cedar Rapids, Iowa Flood, this article explores how risk perception and location influence evacuee behavior during the evacuation and return-entry process. Three themes are discussed: (1) the spatial and temporal characteristics of risk perception throughout the evacuation and return-entry process, (2) the relationship between risk perception and household compliance with return-entry orders, and (3) the role social influences have on the timing of the return by households. The results indicate that geographic location and spatial variation of risk influenced household risk perception and compliance with return-entry plans. In addition, sociodemographic characteristics influenced the timing and characteristics of the return groups. The findings of this study advance knowledge of evacuee behavior throughout a disaster and can inform strategies used by emergency managers throughout the evacuation and return-entry process. © 2012 Society for Risk Analysis.
Liu, Yang; Lv, Jianshu; Zhang, Bing; Bi, Jun
2013-04-15
Identifying the sources of spatial variability and deficiency risk of soil nutrients is a crucial issue for soil and agriculture management. A total of 1247 topsoil samples (0-20 cm) were collected at the nodes of a 2×2 km grid in Rizhao City and the contents of soil organic carbon (OC), total nitrogen (TN), and total phosphorus (TP) were determined. Factorial kriging analysis (FKA), stepwise multiple regression, and indicator kriging (IK) were appled to investigate the scale dependent correlations among soil nutrients, identify the sources of spatial variability at each spatial scale, and delineate the potential risk of soil nutrient deficiency. Linear model of co-regionalization (LMC) fitting indicated that the presence of multi-scale variation was comprised of nugget effect, an exponential structure with a range of 12 km (local scale), and a spherical structure with a range of 84 km (regional scale). The short-range variation of OC and TN was mainly dominated by land use types, and TP was controlled by terrain. At long-range scale, spatial variation of OC, TN, and TP was dominated by parent material. Indicator kriging maps depicted the probability of soil nutrient deficiency compared with the background values in eastern Shandong province. The high deficiency risk area of all nutrient integration was mainly located in eastern and northwestern parts. Copyright © 2013 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Dheenan, P. S.; Jha, Dilip Kumar; Vinithkumar, N. V.; Ponmalar, A. Angelin; Venkateshwaran, P.; Kirubagaran, R.
2014-01-01
The purpose of this study was to determine the concentration, distribution of bacteria and physicochemical property of surface seawater in Rangat Bay, Middle Andaman, Andaman Islands (India). The bay experiences tidal variations. Perhaps physicochemical properties of seawater in Rangat Bay were found not to vary significantly. The concentration of faecal streptococci was high (2.2 × 103 CFU/100 mL) at creek and harbour area, whereas total coliforms were high (7.0 × 102 CFU/100 mL) at mangrove area. Similarly, total heterotrophic bacterial concentration was high (5.92 × 104 CFU/100 mL) in mangrove and harbour area. The Vibrio cholerae and Vibrio parahaemolyticus concentration was high (4.2 × 104 CFU/100 mL and 9 × 103 CFU/100 mL) at open sea. Cluster analysis showed grouping of stations in different tidal periods. The spatial maps clearly depicted the bacterial concentration pattern in the bay. The combined approach of multivariate analysis and spatial mapping techniques was proved to be useful in the current study.
Spatially resolved variations in reflectivity across iron oxide thin films
NASA Astrophysics Data System (ADS)
Kelley, Chris S.; Thompson, Sarah M.; Gilks, Daniel; Sizeland, James; Lari, Leonardo; Lazarov, Vlado K.; Matsuzaki, Kosuke; LeFrançois, Stéphane; Cinque, Gianfelice; Dumas, Paul
2017-11-01
The spin polarising properties of the iron oxide magnetite (Fe3O4) make it attractive for use in spintronic devices, but its sensitivity to compositional and structural variations make it challenging to prepare reliably. Infrared microspectroscopy and modelling are used to determine the spatial variation in the chemical composition of three thin films of iron oxide; one prepared by pulsed laser deposition (PLD), one by molecular beam epitaxy (MBE) deposition of iron whilst simultaneously flowing oxygen into the chamber and one by flowing oxygen only once deposition is complete. The technique is easily able to distinguish between films which contain metallic iron and different iron oxide phases as well as spatial variations in composition across the films. The film grown by post-oxidising iron is spatially uniform but not fully oxidised, the film grown by simultaneously oxidising iron showed spatial variation in oxide composition while the film grown by PLD was spatially uniform magnetite.
Baldissera, Ronei; Rodrigues, Everton N L; Hartz, Sandra M
2012-01-01
The distribution of beta diversity is shaped by factors linked to environmental and spatial control. The relative importance of both processes in structuring spider metacommunities has not yet been investigated in the Atlantic Forest. The variance explained by purely environmental, spatially structured environmental, and purely spatial components was compared for a metacommunity of web spiders. The study was carried out in 16 patches of Atlantic Forest in southern Brazil. Field work was done in one landscape mosaic representing a slight gradient of urbanization. Environmental variables encompassed plot- and patch-level measurements and a climatic matrix, while principal coordinates of neighbor matrices (PCNMs) acted as spatial variables. A forward selection procedure was carried out to select environmental and spatial variables influencing web-spider beta diversity. Variation partitioning was used to estimate the contribution of pure environmental and pure spatial effects and their shared influence on beta-diversity patterns, and to estimate the relative importance of selected environmental variables. Three environmental variables (bush density, land use in the surroundings of patches, and shape of patches) and two spatial variables were selected by forward selection procedures. Variation partitioning revealed that 15% of the variation of beta diversity was explained by a combination of environmental and PCNM variables. Most of this variation (12%) corresponded to pure environmental and spatially environmental structure. The data indicated that (1) spatial legacy was not important in explaining the web-spider beta diversity; (2) environmental predictors explained a significant portion of the variation in web-spider composition; (3) one-third of environmental variation was due to a spatial structure that jointly explains variation in species distributions. We were able to detect important factors related to matrix management influencing the web-spider beta-diversity patterns, which are probably linked to historical deforestation events.
Mentoring Temporal and Spatial Variations in Rainfall across Wadi Ar-Rumah, Saudi Arabia
NASA Astrophysics Data System (ADS)
Alharbi, T.; Ahmed, M.
2015-12-01
Across the Kingdom of Saudi Arabia (KSA), the fresh water resources are limited only to those found in aquifer systems. Those aquifers were believed to be recharged during the previous wet climatic period but still receiving modest local recharge in interleaving dry periods such as those prevailing at present. Quantifying temporal and spatial variabilities in rainfall patterns, magnitudes, durations, and frequencies is of prime importance when it comes to sustainable management of such aquifer systems. In this study, an integrated approach, using remote sensing and field data, was used to assess the past, the current, and the projected spatial and temporal variations in rainfall over one of the major watersheds in KSA, Wadi Ar-Rumah. This watershed was selected given its larger areal extent and population intensity. Rainfall data were extracted from (1) the Climate Prediction Centers (CPC) Merged Analysis of Precipitation (CMAP; spatial coverage: global; spatial resolution: 2.5° × 2.5°; temporal coverage: January 1979 to April 2015; temporal resolution: monthly), and (2) the Tropical Rainfall Measuring Mission (TRMM; spatial coverage: 50°N to 50°S; spatial resolution: 0.25° × 0.25°; temporal coverage: January 1998 to March 2015; temporal resolution: 3 hours) and calibrated against rainfall measurements extracted from rain gauges. Trends in rainfall patterns were examined over four main investigation periods: period I (01/1979 to 12/1985), period II (01/1986 to 12/1992), period III (01/1993 to 12/2002), and period IV (01/2003 to 12/2014). Our findings indicate: (1) a significant increase (+14.19 mm/yr) in rainfall rates were observed during period I, (2) a significant decrease in rainfall rates were observed during periods II (-5.80 mm/yr), III (-9.38 mm/yr), and IV (-2.46 mm/yr), and (3) the observed variations in rainfall rates are largely related to the temporal variations in the northerlies (also called northwesterlies) and the monsoonal wind regimes.
Horizontal Temperature Variability in the Stratosphere: Global Variations Inferred from CRISTA Data
NASA Technical Reports Server (NTRS)
Eidmann, G.; Offermann, D.; Jarisch, M.; Preusse, P.; Eckermann, S. D.; Schmidlin, F. J.
2001-01-01
In two separate orbital campaigns (November, 1994 and August, 1997), the Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere (CRISTA) instrument acquired global stratospheric data of high accuracy and high spatial resolution. The standard limb-scanned CRISTA measurements resolved atmospheric spatial structures with vertical dimensions greater than or equal to 1.5 - 2 km and horizontal dimensions is greater than or equal to 100 - 200 km. A fluctuation analysis of horizontal temperature distributions derived from these data is presented. This method is somewhat complementary to conventional power-spectral analysis techniques.
Drive by Soil Moisture Measurement: A Citizen Science Project
NASA Astrophysics Data System (ADS)
Senanayake, I. P.; Willgoose, G. R.; Yeo, I. Y.; Hancock, G. R.
2017-12-01
Two of the common attributes of soil moisture are that at any given time it varies quite markedly from point to point, and that there is a significant deterministic pattern that underlies this spatial variation and which is typically 50% of the spatial variability. The spatial variation makes it difficult to determine the time varying catchment average soil moisture using field measurements because any individual measurement is unlikely to be equal to the average for the catchment. The traditional solution to this is to make many measurements (e.g. with soil moisture probes) spread over the catchment, which is very costly and manpower intensive, particularly if we need a time series of soil moisture variation across a catchment. An alternative approach, explored in this poster is to use the deterministic spatial pattern of soil moisture to calibrate one site (e.g. a permanent soil moisture probe at a weather station) to the spatial pattern of soil moisture over the study area. The challenge is then to determine the spatial pattern of soil moisture. This poster will present results from a proof of concept project, where data was collected by a number of undergraduate engineering students, to estimate the spatial pattern. The approach was to drive along a series of roads in a catchment and collect soil moisture measurements at the roadside using field portable soil moisture probes. This drive was repeated a number of times over the semester, and the time variation and spatial persistence of the soil moisture pattern were examined. Provided that the students could return to exactly the same location on each collection day there was a strong persistent pattern in the soil moisture, even while the average soil moisture varied temporally as a result of preceding rainfall. The poster will present results and analysis of the student data, and compare these results with several field sites where we have spatially distributed permanently installed soil moisture probes. The poster will also outline an experimental design, based on our experience, that will underpin a proposed citizen science project involving community environment and farming groups, and high school students.
Temporal-Spatial Variation of Global GPS-Derived Total Electron Content, 1999–2013
Guo, Jinyun; Li, Wang; Liu, Xin; Kong, Qiaoli; Zhao, Chunmei; Guo, Bin
2015-01-01
To investigate the temporal-spatial distribution and evolutions of global Total Electron Content (TEC), we estimate the global TEC data from 1999 to 2013 by processing the GPS data collected by the International Global Navigation Satellite System (GNSS) Service (IGS) stations, and robustly constructed the TEC time series at each of the global 5°×2.5° grids. We found that the spatial distribution of the global TEC has a pattern where the number of TECs diminishes gradually from a low-latitude region to high-latitude region, and anomalies appear in the equatorial crest and Greenland. Temporal variations show that the peak TEC appears in equinoctial months, and this corresponds to the semiannual variation of TEC. Furthermore, the winter anomaly is also observed in the equatorial area of the northern hemisphere and high latitudes of the southern hemisphere. Morlet wavelet analysis is used to determine periods of TEC variations and results indicate that the 1-day, 26.5-day, semi-annual and annual cycles are the major significant periods. The fitting results of a quadratic polynomial show that the effect of solar activity on TEC is stronger in low latitudes than in mid-high latitudes, and stronger in the southern hemisphere than in the northern hemisphere. But the effect in low latitudes in the northern hemisphere is stronger than that in low latitudes in the southern hemisphere. The effect of solar activity on TECs was analyzed with the cross wavelet analysis and the wavelet coherence transformation, and we found that there appears to be a strong coherence in the period of about 27 days. So the sunspot as one index of solar activity seriously affects the TEC variations with the sun’s rotation. We fit the TEC data with the least squares spectral analysis to study the periodic variations of TEC. The changing trend of TEC is generally -0.08 TECu per year from 1999 to 2013. So TECs decrease over most areas year by year, but TECs over the Arctic around Greenland maintained a rising trend during these 15 years. PMID:26193101
NASA Astrophysics Data System (ADS)
Bisht, Mahesh Singh; Rajput, Archana; Srivastava, Kumar Vaibhav
2018-04-01
A cloak based on gradient index metamaterial (GIM) is proposed. Here, the GIM is used, for conversion of propagating waves into surface waves and vice versa, to get the cloaking effect. The cloak is made of metamaterial consisting of four supercells with each supercell possessing the linear spatial variation of permittivity and permeability. The spatial variation of material parameters in supercells allows the conversion of propagating waves into surface waves and vice versa, hence results in reduction of electromagnetic signature of the object. To facilitate the practical implementation of the cloak, continuous spatial variation of permittivity and/or permeability, in each supercell, is discretized into seven segments and it is shown that there is not much deviation in cloaking performance of discretized cloak as compared to its continuous counterpart. The crucial advantage, of the proposed cloaks, is that the material parameters are isotropic and in physically realizable range. Furthermore, the proposed cloaks have been shown to possess bandwidth of the order of 190% which is a significantly improved performance compared to the recently published literature.
Gabriel, Mark; Kolka, Randy; Wickman, Trent; Woodruff, Laurel; Nater, Ed
2012-01-01
The focus of this study is to investigate processes causing the observed spatial variation of total mercury (THg) in the soil O horizon of watersheds within the Superior National Forest (Minnesota) and to determine if results have implications toward understanding long-term changes in THg concentrations for resident fish. Principal component analysis was used to evaluate the spatial relationships of 42 chemical elements in three soil horizons over 10 watersheds. Results indicate that soil organic carbon is the primary factor controlling the spatial variation of certain metals (Hg, Tl, Pb, Bi, Cd, Sn, Sb, Cu, and As) in the O and A soil horizons. In the B/E horizon, organic carbon appeared to play a minor role in metal spatial variation. These characteristics are consistent with the concentration of soil organic matter and carbon decreasing from the O to the B/E horizons. We also investigated the relationship between percent change in upland soil organic content and fish THg concentrations across all watersheds. Statistical regression analysis indicates that a 50% reduction in age-one and age-two fish THg concentration could result from an average 10% decrease in upland soil organic content. Disturbances that decrease the content of THg and organic matter in the O and A horizons (e.g., fire) may cause a short-term increase in atmospherically deposited mercury but, over the long term, may lead to decreased fish THg concentrations in affected watersheds. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
OSPAR standard method and software for statistical analysis of beach litter data.
Schulz, Marcus; van Loon, Willem; Fleet, David M; Baggelaar, Paul; van der Meulen, Eit
2017-09-15
The aim of this study is to develop standard statistical methods and software for the analysis of beach litter data. The optimal ensemble of statistical methods comprises the Mann-Kendall trend test, the Theil-Sen slope estimation, the Wilcoxon step trend test and basic descriptive statistics. The application of Litter Analyst, a tailor-made software for analysing the results of beach litter surveys, to OSPAR beach litter data from seven beaches bordering on the south-eastern North Sea, revealed 23 significant trends in the abundances of beach litter types for the period 2009-2014. Litter Analyst revealed a large variation in the abundance of litter types between beaches. To reduce the effects of spatial variation, trend analysis of beach litter data can most effectively be performed at the beach or national level. Spatial aggregation of beach litter data within a region is possible, but resulted in a considerable reduction in the number of significant trends. Copyright © 2017 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Xiaoma; Zhou, Yuyu; Asrar, Ghassem R.
Abstract: Urban heat island (UHI), a major concern worldwide, affects human health and energy use. With current and anticipated rapid urbanization, improved understanding of the response of UHI to urbanization is important for impact analysis and developing effective adaptation measures and mitigation strategies. Current studies mainly focus on a single or a few big cities and knowledge on the response of UHI to urbanization for large areas is very limited. Modelling UHI caused by urbanization for large areas that encompass multiple metropolitans remains a major scientific challenge/opportunity. As a major indicator of urbanization, urban area size lends itself well formore » representation in prognostic models to investigate the impacts of urbanization on UHI and the related socioeconomic and environmental effects. However, we have little knowledge on how UHI responds to the increase of urban area size, namely urban expansion, and its spatial and temporal variation over large areas. In this study, we investigated the relationship between surface UHI (SUHI) and urban area size in the climate and ecological context, and its spatial and temporal variations, based on a panel analysis of about 5000 urban areas of 10 km2 or larger, in the conterminous U.S. We found statistically significant positive relationship between SUHI and urban area size, and doubling the urban area size led to a SUHI increase of higher than 0.7 °C. The response of SUHI to the increase of urban area size shows spatial and temporal variations, with stronger SUHI increase in the Northern region of U.S., and during daytime and summer. Urban area size alone can explain as much as 87% of the variance of SUHI among cities studied, but with large spatial and temporal variations. Urban area size shows higher association with SUHI in regions where the thermal characteristics of land cover surrounding the urban are more homogeneous, such as in Eastern U.S., and in the summer months. This study provides a practical approach for large-scale assessment and modeling of the impact of urbanization on SUHI, both spatially and temporally, for developing mitigation/adaptation measures, especially in anticipated warmer climate conditions for the rest of this century.« less
NASA Astrophysics Data System (ADS)
Souza, V. M. C. E. S.; Jauer, P. R.; Alves, L. R.; Padilha, A. L.; Padua, M. B.; Vitorello, I.; Alves, M. V.; Da Silva, L. A.
2017-12-01
Interplanetary structures such as Coronal Mass Ejections (CME), Shocks, Corotating Interaction Regions (CIR) and Magnetic Clouds (MC) interfere directly on Space Weather conditions and can cause severe and intense disturbances in the Earth's magnetic field as measured in space and on the ground. During magnetically disturbed periods characterized by world-wide, abrupt variations of the geomagnetic field, large and intense current systems can be induced and amplified within the Earth even at low latitudes. Such current systems are known as geomagnetically induced currents (GIC) and can cause damage to power transmission lines, transformers and the degradation of pipelines. As part of an effort to estimate GIC intensities throughout the low to equatorial latitudes of the Brazilian territory, we used the 3-D MHD SWMF/BATSRUS code to estimate spatial variations of the geomagnetic field during periods when the magnetosphere is under the influence of CME and MC structures. Specifically, we used the CalcDeltaB tool (Rastatter et al., Space Weather, 2014) to provide a proxy for the spatial variations of the geomagnetic field, with a 1 minute cadence, at 31 virtual magnetometer stations located in the proposed study region. The stations are spatially arranged in a two-dimensional network with each station being 5 degrees apart in latitude and longitude. In a preliminary analysis, we found that prior to the arrival of each interplanetary structure, there is no appreciable variation in the components of the geomagnetic field between the virtual stations. However, when the interplanetary structures reach the magnetosphere, each station perceives the magnetic field variation differently, so that it is not possible to use a single station to represent the magnetic field perturbation throughout the Brazilian region. We discuss the minimum number and spacing between stations to adequately detail the geomagnetic field variations in this region.
The spatial patterns of directional phenotypic selection.
Siepielski, Adam M; Gotanda, Kiyoko M; Morrissey, Michael B; Diamond, Sarah E; DiBattista, Joseph D; Carlson, Stephanie M
2013-11-01
Local adaptation, adaptive population divergence and speciation are often expected to result from populations evolving in response to spatial variation in selection. Yet, we lack a comprehensive understanding of the major features that characterise the spatial patterns of selection, namely the extent of variation among populations in the strength and direction of selection. Here, we analyse a data set of spatially replicated studies of directional phenotypic selection from natural populations. The data set includes 60 studies, consisting of 3937 estimates of selection across an average of five populations. We performed meta-analyses to explore features characterising spatial variation in directional selection. We found that selection tends to vary mainly in strength and less in direction among populations. Although differences in the direction of selection occur among populations they do so where selection is often weakest, which may limit the potential for ongoing adaptive population divergence. Overall, we also found that spatial variation in selection appears comparable to temporal (annual) variation in selection within populations; however, several deficiencies in available data currently complicate this comparison. We discuss future research needs to further advance our understanding of spatial variation in selection. © 2013 John Wiley & Sons Ltd/CNRS.
Spatial variation of natural radiation and childhood leukaemia incidence in Great Britain.
Richardson, S; Monfort, C; Green, M; Draper, G; Muirhead, C
This paper describes an analysis of the geographical variation of childhood leukaemia incidence in Great Britain over a 15 year period in relation to natural radiation (gamma and radon). Data at the level of the 459 district level local authorities in England, Wales and regional districts in Scotland are analysed in two complementary ways: first, by Poisson regressions with the inclusion of environmental covariates and a smooth spatial structure; secondly, by a hierarchical Bayesian model in which extra-Poisson variability is modelled explicitly in terms of spatial and non-spatial components. From this analysis, we deduce a strong indication that a main part of the variability is accounted for by a local neighbourhood 'clustering' structure. This structure is furthermore relatively stable over the 15 year period for the lymphocytic leukaemias which make up the majority of observed cases. We found no evidence of a positive association of childhood leukaemia incidence with outdoor or indoor gamma radiation levels. There is no consistent evidence of any association with radon levels. Indeed, in the Poisson regressions, a significant positive association was only observed for one 5-year period, a result which is not compatible with a stable environmental effect. Moreover, this positive association became clearly non-significant when over-dispersion relative to the Poisson distribution was taken into account.
Relationship between sugarcane rust severity and soil properties in louisiana.
Johnson, Richard M; Grisham, Michael P; Richard, Edward P
2007-06-01
ABSTRACT The extent of spatial and temporal variability of sugarcane rust (Puccinia melanocephala) infestation was related to variation in soil properties in five commercial fields of sugarcane (interspecific hybrids of Saccharum spp., cv. LCP 85-384) in southern Louisiana. Sugarcane fields were grid-soil sampled at several intensities and rust ratings were collected at each point over 6 to 7 weeks. Soil properties exhibited significant variability (coefficients of variation = 9 to 70.1%) and were spatially correlated in 39 of 40 cases with a range of spatial correlation varying from 39 to 201 m. Rust ratings were spatially correlated in 32 of 33 cases, with a range varying from 29 to 241 m. Rust ratings were correlated with several soil properties, most notably soil phosphorus (r = 0.40 to 0.81) and soil sulfur (r = 0.36 to 0.68). Multiple linear regression analysis resulted in coefficients of determination that ranged from 0.22 to 0.73, and discriminant analysis further improved the overall predictive ability of rust models. Finally, contour plots of soil properties and rust levels clearly suggested a link between these two parameters. These combined data suggest that sugarcane growers that apply fertilizer in excess of plant requirements will increase the incidence and severity of rust infestations in their fields.
Jesse, Stephen; Kalinin, Sergei V
2009-02-25
An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.
Yergeau, Etienne; Bezemer, T Martijn; Hedlund, Katarina; Mortimer, Simon R; Kowalchuk, George A; Van Der Putten, Wim H
2010-08-01
Microbial communities respond to a variety of environmental factors related to resources (e.g. plant and soil organic matter), habitat (e.g. soil characteristics) and predation (e.g. nematodes, protozoa and viruses). However, the relative contribution of these factors on microbial community composition is poorly understood. Here, we sampled soils from 30 chalk grassland fields located in three different chalk hill ridges of Southern England, using a spatially explicit sampling scheme. We assessed microbial communities via phospholipid fatty acid (PLFA) analyses and PCR-denaturing gradient gel electrophoresis (DGGE) and measured soil characteristics, as well as nematode and plant community composition. The relative influences of space, soil, vegetation and nematodes on soil microorganisms were contrasted using variation partitioning and path analysis. Results indicate that soil characteristics and plant community composition, representing habitat and resources, shape soil microbial community composition, whereas the influence of nematodes, a potential predation factor, appears to be relatively small. Spatial variation in microbial community structure was detected at broad (between fields) and fine (within fields) scales, suggesting that microbial communities exhibit biogeographic patterns at different scales. Although our analysis included several relevant explanatory data sets, a large part of the variation in microbial communities remained unexplained (up to 92% in some analyses). However, in several analyses, significant parts of the variation in microbial community structure could be explained. The results of this study contribute to our understanding of the relative importance of different environmental and spatial factors in driving the composition of soil-borne microbial communities. © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd.
NASA Astrophysics Data System (ADS)
Arakaki, Takemitsu; Azechi, Sotaro; Somada, Yuka; Ijyu, Moriaki; Nakaema, Fumiya; Hitomi, Yuya; Handa, Daishi; Oshiro, Yoshito; Miyagi, Youichi; Tsuhako, Ai; Murayama, Hitomi; Higaonna, Yumi; Tanahara, Akira; Itoh, Akihide; Fukushima, Soko; Higashi, Kazuaki; Henza, Yui; Nishikawa, Rin; Shinjo, Hibiki; Wang, Hongyan
2014-11-01
East Asia's rapid economic growth has led to concerns about the emission of air pollutants. We collected total suspended particle (TSP) aerosol samples simultaneously at three islands in Okinawa, Japan, which are downwind of East Asia, during the Asian dust season, to examine the spatial and temporal variations and chemical transformations of major chemicals in the aerosols. Weekly samples were collected from July 2008 to June 2010, and the concentrations of water-soluble cations, anions, and organic carbon (WSOC) were determined (n = 303). Spatial distribution analysis showed that monthly mean concentrations of non-sea-salt (nss)-SO42- in the spring (Asian dust season) decreased with increasing distance from Asia, while the trend for NO3- was less evident, suggesting that chemical transformation affected the long-range transport of certain chemicals. Temporal variation analysis showed that concentrations of nss-SO42-, NO3-, and WSOC during the spring were about 2.0, 2.4, and 1.8 times those in the summer (cleaner air mass from the Pacific Ocean), respectively. This study demonstrated that air pollutants were transported from the Asian continent to the Okinawa islands and affected the air quality in the region. There may also be impacts on ecosystems, because increased concentrations of particulate NO3- could increase nutrient levels around the Okinawa islands.
Hamilton, Scott L.; Caselle, Jennifer E.; Lantz, Coulson A.; Egloff, Tiana L.; Kondo, Emi; Newsome, Seth D.; Loke-Smith, Kerri; Pondella, Daniel J.; Young, Kelly A.; Lowe, Christopher G.
2015-01-01
Interactions between predator and prey act to shape the structure of ecological communities, and these interactions can differ across space. California sheephead Semicossyphus pulcher are common predators of benthic invertebrates in kelp beds and rocky reefs in southern California, USA. Through gut content and stable isotope (δ13C and †15N) analyses, we investigated geographic and ontogenetic variation in trophic ecology across 9 populations located at island and mainland sites throughout southern California. We found extensive geographic variation in California sheephead diet composition over small spatial scales. Populations differed in the proportion of sessile filter/suspension feeders or mobile invertebrates in the diet. Spatial variation in diet was highly correlated with other life history and demographic traits (e.g. growth, survivorship, reproductive condition, and energy storage), in addition to proxies of prey availability from community surveys. Multivariate descriptions of the diet from gut contents roughly agreed with the spatial groupings of sites based on stable isotope analysis of both California sheephead and their prey. Ontogenetic changes in diet occurred consistently across populations, despite spatial differences in size structure. As California sheephead increase in size, diets shift from small filter feeders, like bivalves, to larger mobile invertebrates, such as sea urchins. Our results indicate that locations with large California sheephead present, such as many marine reserves, may experience increased predation pressure on sea urchins, which could ultimately affect kelp persistence. PMID:26246648
Spatial Normalization of Reverse Phase Protein Array Data
Kaushik, Poorvi; Molinelli, Evan J.; Miller, Martin L.; Wang, Weiqing; Korkut, Anil; Liu, Wenbin; Ju, Zhenlin; Lu, Yiling; Mills, Gordon; Sander, Chris
2014-01-01
Reverse phase protein arrays (RPPA) are an efficient, high-throughput, cost-effective method for the quantification of specific proteins in complex biological samples. The quality of RPPA data may be affected by various sources of error. One of these, spatial variation, is caused by uneven exposure of different parts of an RPPA slide to the reagents used in protein detection. We present a method for the determination and correction of systematic spatial variation in RPPA slides using positive control spots printed on each slide. The method uses a simple bi-linear interpolation technique to obtain a surface representing the spatial variation occurring across the dimensions of a slide. This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide. The adoption of the method results in increased agreement between technical and biological replicates of various tumor and cell-line derived samples. Further, in data from a study of the melanoma cell-line SKMEL-133, several slides that had previously been rejected because they had a coefficient of variation (CV) greater than 15%, are rescued by reduction of CV below this threshold in each case. The method is implemented in the R statistical programing language. It is compatible with MicroVigene and SuperCurve, packages commonly used in RPPA data analysis. The method is made available, along with suggestions for implementation, at http://bitbucket.org/rppa_preprocess/rppa_preprocess/src. PMID:25501559
NASA Astrophysics Data System (ADS)
Cholemari, Murali R.; Arakeri, Jaywant H.
2005-08-01
We study the stability of surface waves on the radial film flow created by a vertical cylindrical water jet striking a horizontal plate. In such flows, surface waves have been found to be unstable and can cause transition to turbulence. This surface-wave-induced transition is different from the well-known Tollmien-Schlichting wave-induced transition. The present study aims at understanding the instability and the transition process. We do a temporal stability analysis by assuming the flow to be locally two-dimensional but including spatial variations to first order in the basic flow. The waves are found to be dispersive, mostly unstable, and faster than the mean flow. Spatial variation is the major destabilizing factor. Experiments are done to test the results of the linear stability analysis and to document the wave breakup and transition. Comparison between theory and experiments is fairly good and indicates the adequacy of the model.
Mayne, Darren J; Morgan, Geoffrey G; Jalaludin, Bin B; Bauman, Adrian E
2017-10-03
Individual-level studies support a positive relation between walkable built environments and participation in moderate-intensity walking. However, the utility of this evidence for population-level planning is less clear as it is derived at much finer spatial scales than those used for regional programming. The aims of this study were to: evaluate if individual-level relations between walkability and walking to improve health manifest at population-level spatial scales; assess the specificity of area-level walkability for walking relative to other moderate and vigorous physical activity (MVPA); describe geographic variation in walking and other MVPA; and quantify the contribution of walkability to this variation. Data on sufficient walking, sufficient MVPA, and high MVPA to improve health were analyzed for 95,837 Sydney respondents to the baseline survey of the 45 and Up Study between January 2006 and April 2010. We used conditional autoregressive models to create smoothed MVPA "disease maps" and assess relations between sufficient MVPA to improve health and area-level walkability adjusted for individual-level demographic, socioeconomic, and health factors, and area-level relative socioeconomic disadvantage. Within-cohort prevalence of meeting recommendations for sufficient walking, sufficient MVPA, and high MVPA were 31.7 (95% CI 31.4-32.0), 69.4 (95% CI 69.1-69.7), and 56.1 (95% CI 55.8-56.4) percent. Prevalence of sufficient walking was increased by 1.20 (95% CrI 1.12-1.29) and 1.07 (95% CrI 1.01-1.13) for high and medium-high versus low walkability postal areas, and for sufficient MVPA by 1.05 (95% CrI 1.01-1.08) for high versus low walkability postal areas. Walkability was not related to high MVPA. Postal area walkability explained 65.8 and 47.4 percent of residual geographic variation in sufficient walking and sufficient MVPA not attributable to individual-level factors. Walkability is associated with area-level prevalence and geographic variation in sufficient walking and sufficient MVPA to improve health in Sydney, Australia. Our study supports the use of walkability indexes at multiple spatial scales for informing population-level action to increase physical activity and the utility of spatial analysis for walkability research and planning.
Laque, Thaís; Farjalla, Vinicius F; Rosado, Alexandre S; Esteves, Francisco A
2010-05-01
Bacterial community composition (BCC) has been extensively related to specific environmental conditions. Tropical coastal lagoons present great temporal and spatial variation in their limnological conditions, which, in turn, should influence the BCC. Here, we sought for the limnological factors that influence, in space and time, the BCC in tropical coastal lagoons (Rio de Janeiro State, Brazil). The Visgueiro lagoon was sampled monthly for 1 year and eight lagoons were sampled once for temporal and spatial analysis, respectively. BCC was evaluated by bacteria-specific PCR-DGGE methods. Great variations were observed in limnological conditions and BCC on both temporal and spatial scales. Changes in the BCC of Visgueiro lagoon throughout the year were best related to salinity and concentrations of NO (3) (-) , dissolved phosphorus and chlorophyll-a, while changes in BCC between lagoons were best related to salinity and dissolved phosphorus concentration. Salinity has a direct impact on the integrity of the bacterial cell, and it was previously observed that phosphorus is the main limiting nutrient to bacterial growth in these lagoons. Therefore, we conclude that great variations in limnological conditions of coastal lagoons throughout time and space resulted in different BCCs and salinity and nutrient concentration, particularly dissolved phosphorus, are the main limnological factors influencing BCC in these tropical coastal lagoons.
Qin, Hua-Peng; Khu, Soon-Thiam; Yu, Xiang-Ying
2010-09-15
The composition of land use for a rapidly urbanizing catchment is usually heterogeneous, and this may result in significant spatial variations of storm runoff pollution and increase the difficulties of water quality management. The Shiyan Reservoir catchment, a typical rapidly urbanizing area in China, is chosen as a study area, and temporary monitoring sites were set at the downstream of its 6 sub-catchments to synchronously measure rainfall, runoff and water quality during 4 storm events in 2007 and 2009. Due to relatively low frequency monitoring, the IHACRES and exponential pollutant wash-off simulation models are used to interpolate the measured data to compensate for data insufficiency. Three indicators, event pollutant loads per unit area (EPL), event mean concentration (EMC) and pollutant loads transported by the first 50% of runoff volume (FF50), were used to describe the runoff pollution for different pollutants in each sub-catchment during the storm events, and the correlations between runoff pollution spatial variations and land-use patterns were tested by Spearman's rank correlation analysis. The results indicated that similar spatial variation trends were found for different pollutants (EPL or EMC) in light storm events, which strongly correlate with the proportion of residential land use; however, they have different trends in heavy storm events, which correlate with not only the residential land use, but also agricultural and bare land use. And some pairs of pollutants (such as COD/BOD, NH(3)-N/TN) might have the similar source because they have strong or moderate positive spatial correlation. Moreover, the first flush intensity (FF50) varies with impervious land areas and different interception ratio of initial storm runoff volume should be adopted in different sub-catchments. Copyright 2010 Elsevier B.V. All rights reserved.
Lee, Hyeongyu; Choi, Yosoon; Suh, Jangwon; Lee, Seung-Ho
2016-01-01
Understanding spatial variation of potentially toxic trace elements (PTEs) in soil is necessary to identify the proper measures for preventing soil contamination at both operating and abandoned mining areas. Many studies have been conducted worldwide to explore the spatial variation of PTEs and to create soil contamination maps using geostatistical methods. However, they generally depend only on inductively coupled plasma atomic emission spectrometry (ICP–AES) analysis data, therefore such studies are limited by insufficient input data owing to the disadvantages of ICP–AES analysis such as its costly operation and lengthy period required for analysis. To overcome this limitation, this study used both ICP–AES and portable X-ray fluorescence (PXRF) analysis data, with relatively low accuracy, for mapping copper and lead concentrations at a section of the Busan abandoned mine in Korea and compared the prediction performances of four different approaches: the application of ordinary kriging to ICP–AES analysis data, PXRF analysis data, both ICP–AES and transformed PXRF analysis data by considering the correlation between the ICP–AES and PXRF analysis data, and co-kriging to both the ICP–AES (primary variable) and PXRF analysis data (secondary variable). Their results were compared using an independent validation data set. The results obtained in this case study showed that the application of ordinary kriging to both ICP–AES and transformed PXRF analysis data is the most accurate approach when considers the spatial distribution of copper and lead contaminants in the soil and the estimation errors at 11 sampling points for validation. Therefore, when generating soil contamination maps for an abandoned mine, it is beneficial to use the proposed approach that incorporates the advantageous aspects of both ICP–AES and PXRF analysis data. PMID:27043594
Lee, Hyeongyu; Choi, Yosoon; Suh, Jangwon; Lee, Seung-Ho
2016-03-30
Understanding spatial variation of potentially toxic trace elements (PTEs) in soil is necessary to identify the proper measures for preventing soil contamination at both operating and abandoned mining areas. Many studies have been conducted worldwide to explore the spatial variation of PTEs and to create soil contamination maps using geostatistical methods. However, they generally depend only on inductively coupled plasma atomic emission spectrometry (ICP-AES) analysis data, therefore such studies are limited by insufficient input data owing to the disadvantages of ICP-AES analysis such as its costly operation and lengthy period required for analysis. To overcome this limitation, this study used both ICP-AES and portable X-ray fluorescence (PXRF) analysis data, with relatively low accuracy, for mapping copper and lead concentrations at a section of the Busan abandoned mine in Korea and compared the prediction performances of four different approaches: the application of ordinary kriging to ICP-AES analysis data, PXRF analysis data, both ICP-AES and transformed PXRF analysis data by considering the correlation between the ICP-AES and PXRF analysis data, and co-kriging to both the ICP-AES (primary variable) and PXRF analysis data (secondary variable). Their results were compared using an independent validation data set. The results obtained in this case study showed that the application of ordinary kriging to both ICP-AES and transformed PXRF analysis data is the most accurate approach when considers the spatial distribution of copper and lead contaminants in the soil and the estimation errors at 11 sampling points for validation. Therefore, when generating soil contamination maps for an abandoned mine, it is beneficial to use the proposed approach that incorporates the advantageous aspects of both ICP-AES and PXRF analysis data.
Seattle to Spokane: Mapping Perceptions of English in Washington State
Evans, Betsy E.
2015-01-01
This research explores perceptions of linguistic variation in English in Washington state (WA). Respondents marked on a map of WA the places where they believe people’s English sounds “different” and provided a label for that type of English. The analysis of the results used digital tools to create composite maps consisting of (1) respondents’ spatial perceptions of English in WA, (2) spatial perceptions of English in WA according to different demographic groups, and (3) affective values associated with regions identified by respondents. The results suggest that Washingtonians perceive that urban areas and eastern WA are places where English is different. The results also demonstrate that when respondents are surveyed about variation within their own state rather than variation across the country, local types of organizational categories, such as an urban/rural dichotomy or belief in a regional standard, can emerge. PMID:25892828
NASA Astrophysics Data System (ADS)
Xu, Yong; Li, Xinzheng; Ma, Lin; Dong, Dong; Kou, Qi; Sui, Jixing; Gan, Zhibin; Wang, Hongfa
2017-09-01
In spring and summer 2011, the macro- and megabenthic fauna in two sections of the East China Sea were investigated using an Agassiz net trawl to detect the seasonal and spatial variations of benthic community characteristics and the relation to environmental variables. The total number of species increased slightly from spring (131 species) to summer (133) whereas the percentage of Mollusca decreased significantly. The index of relative importance (IRI) indicated that the top five important species changed completely from spring to summer. Species number, abundance and biomass in summer were significantly higher than in spring, but no significant difference was observed among areas (coastal, transitional and oceanic areas, divided basically from inshore to offshore). Species richness ( d), diversity ( H') and evenness ( J') showed no significant seasonal or spatial variations. Cluster analysis and nMDS ordination identified three benthic communities from inshore to offshore, corresponding to the three areas. Analysis of Similarity (ANOSIM) indicated the overall significant difference in community structure between seasons and among areas. K-dominance curves revealed the high intrinsic diversity in the offshore area. Canonical correspondence analysis showed that the coastal community was positively correlated to total nitrogen and total organic carbon in spring, but negatively in summer; oceanic community was positively correlated to total nitrogen and total organic carbon in both seasons. Species such as Coelorhynchus multispinulosus, Neobythites sivicola, Lepidotrigla alata, Solenocera melantho, Parapenaeus fissuroides, Oratosquilla gonypetes and Spiropagurus spiriger occurred exclusively in the offshore oceanic area and their presence may reflect the influence of the offshore Kuroshio Current.
Spatiotemporal analysis of the agricultural drought risk in Heilongjiang Province, China
NASA Astrophysics Data System (ADS)
Pei, Wei; Fu, Qiang; Liu, Dong; Li, Tian-xiao; Cheng, Kun; Cui, Song
2017-06-01
Droughts are natural disasters that pose significant threats to agricultural production as well as living conditions, and a spatial-temporal difference analysis of agricultural drought risk can help determine the spatial distribution and temporal variation of the drought risk within a region. Moreover, this type of analysis can provide a theoretical basis for the identification, prevention, and mitigation of drought disasters. In this study, the overall dispersion and local aggregation of projection points were based on research by Friedman and Tukey (IEEE Trans on Computer 23:881-890, 1974). In this work, high-dimensional samples were clustered by cluster analysis. The clustering results were represented by the clustering matrix, which determined the local density in the projection index. This method avoids the problem of determining a cutoff radius. An improved projection pursuit model is proposed that combines cluster analysis and the projection pursuit model, which offer advantages for classification and assessment, respectively. The improved model was applied to analyze the agricultural drought risk of 13 cities in Heilongjiang Province over 6 years (2004, 2006, 2008, 2010, 2012, and 2014). The risk of an agricultural drought disaster was characterized by 14 indicators and the following four aspects: hazard, exposure, sensitivity, and resistance capacity. The spatial distribution and temporal variation characteristics of the agricultural drought risk in Heilongjiang Province were analyzed. The spatial distribution results indicated that Suihua, Qigihar, Daqing, Harbin, and Jiamusi are located in high-risk areas, Daxing'anling and Yichun are located in low-risk areas, and the differences among the regions were primarily caused by the aspects exposure and resistance capacity. The temporal variation results indicated that the risk of agricultural drought in most areas presented an initially increasing and then decreasing trend. A higher value for the exposure aspect increased the risk of drought, whereas a higher value for the resistance capacity aspect reduced the risk of drought. Over the long term, the exposure level of the region presented limited increases, whereas the resistance capacity presented considerable increases. Therefore, the risk of agricultural drought in Heilongjiang Province will continue to exhibit a decreasing trend.
Boieiro, Mário; Carvalho, José C.; Cardoso, Pedro; Aguiar, Carlos A. S.; Rego, Carla; de Faria e Silva, Israel; Amorim, Isabel R.; Pereira, Fernando; Azevedo, Eduardo B.; Borges, Paulo A. V.; Serrano, Artur R. M.
2013-01-01
The development in recent years of new beta diversity analytical approaches highlighted valuable information on the different processes structuring ecological communities. A crucial development for the understanding of beta diversity patterns was also its differentiation in two components: species turnover and richness differences. In this study, we evaluate beta diversity patterns of ground beetles from 26 sites in Madeira Island distributed throughout Laurisilva – a relict forest restricted to the Macaronesian archipelagos. We assess how the two components of ground beetle beta diversity (βrepl – species turnover and βrich - species richness differences) relate with differences in climate, geography, landscape composition matrix, woody plant species richness and soil characteristics and the relative importance of the effects of these variables at different spatial scales. We sampled 1025 specimens from 31 species, most of which are endemic to Madeira Island. A spatially explicit analysis was used to evaluate the contribution of pure environmental, pure spatial and environmental spatially structured effects on variation in ground beetle species richness and composition. Variation partitioning showed that 31.9% of species turnover (βrepl) and 40.7% of species richness variation (βrich) could be explained by the environmental and spatial variables. However, different environmental variables controlled the two types of beta diversity: βrepl was influenced by climate, disturbance and soil organic matter content whilst βrich was controlled by altitude and slope. Furthermore, spatial variables, represented through Moran’s eigenvector maps, played a significant role in explaining both βrepl and βrich, suggesting that both dispersal ability and Madeira Island complex orography are crucial for the understanding of beta diversity patterns in this group of beetles. PMID:23724065
NASA Astrophysics Data System (ADS)
Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio
2018-02-01
Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently correlated to a climate indicator such as the aridity index.
Bruce, James F.
2002-01-01
The Fountain Creek Basin in and around Colorado Springs, Colorado, is affected by various land- and water-use activities. Biological, hydrological, water-quality, and land-use data were collected at 10 sites in the Fountain Creek Basin from April 1998 through April 2001 to provide a baseline characterization of macroinvertebrate communities and habitat conditions for comparison in subsequent studies; and to assess variation in macroinvertebrate community structure relative to habitat quality. Analysis of variance results indicated that instream and riparian variables were not affected by season, but significant differences were found among sites. Nine metrics were used to describe and evaluate macroinvertebrate community structure. Statistical analysis indicated that for six of the nine metrics, significant variability occurred between spring and fall seasons for 60 percent of the sites. Cluster analysis (unweighted pair group method average) using macroinvertebrate presence-absence data showed a well-defined separation between spring and fall samples. Six of the nine metrics had significant spatial variation. Cluster analysis using Sorenson?s Coefficient of Community values computed from macroinvertebrate density (number of organisms per square meter) data showed that macroinvertebrate community structure was more similar among tributary sites than main-stem sites. Canonical correspondence analysis identified a substrate particle-size gradient from site-specific species-abundance data and environmental correlates that decreased the 10 sites to 5 site clusters and their associated taxa.
Growns, Ivor; Astles, Karen; Gehrke, Peter
2006-03-01
We studied the multiscale (sites, river reaches and rivers) and short-term temporal (monthly) variability in a freshwater fish assemblage. We found that small-scale spatial variation and short-term temporal variability significantly influenced fish community structure in the Macquarie and Namoi Rivers. However, larger scale spatial differences between rivers were the largest source of variation in the data. The interaction between temporal change and spatial variation in fish community structure, whilst statistically significant, was smaller than the variation between rivers. This suggests that although the fish communities within each river changed between sampling occasions, the underlying differences between rivers were maintained. In contrast, the strongest interaction between temporal and spatial effects occurred at the smallest spatial scale, at the level of individual sites. This means whilst the composition of the fish assemblage at a given site may fluctuate, the magnitude of these changes is unlikely to affect larger scale differences between reaches within rivers or between rivers. These results suggest that sampling at any time within a single season will be sufficient to show spatial differences that occur over large spatial scales, such as comparisons between rivers or between biogeographical regions.
Advancing the detection of steady-state visual evoked potentials in brain-computer interfaces.
Abu-Alqumsan, Mohammad; Peer, Angelika
2016-06-01
Spatial filtering has proved to be a powerful pre-processing step in detection of steady-state visual evoked potentials and boosted typical detection rates both in offline analysis and online SSVEP-based brain-computer interface applications. State-of-the-art detection methods and the spatial filters used thereby share many common foundations as they all build upon the second order statistics of the acquired Electroencephalographic (EEG) data, that is, its spatial autocovariance and cross-covariance with what is assumed to be a pure SSVEP response. The present study aims at highlighting the similarities and differences between these methods. We consider the canonical correlation analysis (CCA) method as a basis for the theoretical and empirical (with real EEG data) analysis of the state-of-the-art detection methods and the spatial filters used thereby. We build upon the findings of this analysis and prior research and propose a new detection method (CVARS) that combines the power of the canonical variates and that of the autoregressive spectral analysis in estimating the signal and noise power levels. We found that the multivariate synchronization index method and the maximum contrast combination method are variations of the CCA method. All three methods were found to provide relatively unreliable detections in low signal-to-noise ratio (SNR) regimes. CVARS and the minimum energy combination methods were found to provide better estimates for different SNR levels. Our theoretical and empirical results demonstrate that the proposed CVARS method outperforms other state-of-the-art detection methods when used in an unsupervised fashion. Furthermore, when used in a supervised fashion, a linear classifier learned from a short training session is able to estimate the hidden user intention, including the idle state (when the user is not attending to any stimulus), rapidly, accurately and reliably.
Peukert, S; Griffith, B A; Murray, P J; Macleod, C J A; Brazier, R E
2016-07-01
One of the major challenges for agriculture is to understand the effects of agricultural practices on soil properties and diffuse pollution, to support practical farm-scale land management. Three conventionally managed grassland fields with similar short-term management, but different ploughing histories, were studied on a long-term research platform: the North Wyke Farm Platform. The aims were to (i) quantify the between-field and within-field spatial variation in soil properties by geostatistical analysis, (ii) understand the effects of soil condition (in terms of nitrogen, phosphorus and carbon contents) on the quality of discharge water and (iii) establish robust baseline data before the implementation of various grassland management scenarios. Although the fields sampled had experienced the same land use and similar management for at least 6 years, there were differences in their mean soil properties. They showed different patterns of soil spatial variation and different rates of diffuse nutrient losses to water. The oldest permanent pasture field had the largest soil macronutrient concentrations and the greatest diffuse nutrient losses. We show that management histories affect soil properties and diffuse losses. Potential gains in herbage yield or benefits in water quality might be achieved by characterizing every field or by area-specific management within fields (a form of precision agriculture for grasslands). Permanent pasture per se cannot be considered a mitigation measure for diffuse pollution. The between- and within-field soil spatial variation emphasizes the importance of baseline characterization and will enable the reliable identification of any effects of future management change on the Farm Platform. Quantification of soil and water quality in grassland fields with contrasting management histories.Considerable spatial variation in soil properties and diffuse losses between and within fields.Contrasting management histories within and between fields strongly affected soil and water quality.Careful pasture management needed: the oldest pasture transferred the most nutrients from soil to water.
Application of Remote Sensing for Generation of Groundwater Prospect Map
NASA Astrophysics Data System (ADS)
Inayathulla, Masool
2016-07-01
In developing accurate hydrogeomorphological analysis, monitoring, ability to generate information in spatial and temporal domain and delineation of land features are crucial for successful analysis and prediction of groundwater resources. However, the use of RS and GIS in handling large amount of spatial data provides to gain accurate information for delineating the geological and geomorphological characteristics and allied significance, which are considered as a controlling factor for the occurrence and movement of groundwater used IRS LISS II data on 1: 50000 scale along with topographic maps in various parts of India to develop integrated groundwater potential zones. The present work is an attempt to integrate RS and GIS based analysis and methodology in groundwater potential zone identification in the Arkavathi Basin, Bangalore, study area. The information on geology, geomorphology, soil, slope, rainfall, water level and land use/land cover was gathered, in addition, GIS platform was used for the integration of various themes. The composite map generated was further classified according to the spatial variation of the groundwater potential. Five categories of groundwater potential zones namely poor, moderate to poor, moderate, good and very good were identified and delineated. The hydrogeomorphological units like valley fills and alluvial plain and are potential zones for groundwater exploration and development and valley fills associated with lineaments is highly promising area for ground water recharging. The spatial variation of the potential indicates that groundwater occurrence is controlled by geology, land use / land cover, slope and landforms.
Root, Elisabeth Dowling; Thomas, Deborah S K; Campagna, Elizabeth J; Morrato, Elaine H
2014-08-27
Area-level variation in treatment and outcomes may be a potential source of confounding bias in observational comparative effectiveness studies. This paper demonstrates how to use exploratory spatial data analysis (ESDA) and spatial statistical methods to investigate and control for these potential biases. The case presented compares the effectiveness of two antipsychotic treatment strategies: oral second-generation antipsychotics (SGAs) vs. long-acting paliperiodone palmitate (PP). A new-start cohort study was conducted analyzing patient-level administrative claims data (8/1/2008-4/30/2011) from Missouri Medicaid. ESDA techniques were used to examine spatial patterns of antipsychotic prescriptions and outcomes (hospitalization and emergency department (ED) visits). Likelihood of mental health-related outcomes were compared between patients starting PP (N = 295) and oral SGAs (N = 8,626) using multilevel logistic regression models adjusting for patient composition (demographic and clinical factors) and geographic region. ESDA indicated significant spatial variation in antipsychotic prescription patterns and moderate variation in hospitalization and ED visits thereby indicating possible confounding by geography. In the multilevel models for this antipsychotic case example, patient composition represented a stronger source of confounding than geographic context. Because geographic variation in health care delivery is ubiquitous, it could be a comparative effectiveness research (CER) best practice to test for possible geographic confounding in observational data. Though the magnitude of the area-level geography effects were small in this case, they were still statistically significant and should therefore be examined as part of this observational CER study. More research is needed to better estimate the range of confounding due to geography across different types of observational comparative effectiveness studies and healthcare utilization outcomes.
NASA Astrophysics Data System (ADS)
Saramul, Suriyan; Ezer, Tal
2014-11-01
The study addresses two important issues associated with sea level along the coasts of Thailand: first, the fast sea level rise and its spatial variation, and second, the monsoonal-driven seasonal variations in sea level. Tide gauge data that are more extensive than in past studies were obtained from several different local and global sources, and relative sea level rise (RSLR) rates were obtained from two different methods, linear regressions and non-linear Empirical Mode Decomposition/Hilbert-Huang Transform (EMD/HHT) analysis. The results show extremely large spatial variations in RSLR, with rates varying from ~ 1 mm y-1 to ~ 20 mm y-1; the maximum RSLR is found in the upper Gulf of Thailand (GOT) near Bangkok, where local land subsidence due to groundwater extraction dominates the trend. Furthermore, there are indications that RSLR rates increased significantly in all locations after the 2004 Sumatra-Andaman Earthquake and the Indian Ocean tsunami that followed, so that recent RSLR rates seem to have less spatial differences than in the past, but with high rates of ~ 20-30 mm y-1 almost everywhere. The seasonal sea level cycle was found to be very different between stations in the GOT, which have minimum sea level in June-July, and stations in the Andaman Sea, which have minimum sea level in February. The seasonal sea-level variations in the GOT are driven mostly by large-scale wind-driven set-up/set-down processes associated with the seasonal monsoon and have amplitudes about ten times larger than either typical steric changes at those latitudes or astronomical annual tides.
Short term variations in Jupiter's synchrotron radiation derived from VLA data analysis
NASA Astrophysics Data System (ADS)
Kita, H.; Misawa, H.; Tsuchiya, F.; Morioka, A.
2011-12-01
Jupiter's synchrotron radiation (JSR) is the emission from relativistic electrons in the strong magnetic field of the inner magnetosphere, and it is the most effective prove for remote sensing of Jupiter's radiation belt from the Earth. Although JSR has been thought to be stable for a long time, intensive observations for JSR have made after the collisions of comet P/SL9 to Jupiter in 1994, and these observations revealed short term variations of JSR on time scale of days to weeks. However, the mechanisms which cause the short term variations of total flux density and brightness distribution have not been revealed well. In order to reveal the mechanism of short term variations of JSR more precisely, we have made radio image analysis using the NRAO (National Radio Astronomy Observatory) archived data of the VLA [*]. Brice and McDonough [1973, Icarus] proposed a scenario for the short term variations: i.e, the solar UV/EUV heating for Jupiter's upper atmosphere drives neutral wind perturbations and then the induced dynamo electric field leads to enhancement of radial diffusion. It is also suggested that induced dynamo electric field produce dawn-dusk electric potential difference, which cause dawn-dusk asymmetry in electron spatial distribution and emission distribution. So far the following results have been indicated for the short term variations. Miyoshi et al. [1999, GRL] showed that a short term variation event at 2.3GHz is well correlate to solar UV/EUV flux variations. Tsuchiya et al. [2010, Adv. Geosci.] showed that JSR at 325MHz and 785MHz have short term variations. These JSR observations confirmed the existence of the short term variation which is caused by solar UV/EUV. However, the effect of solar UV/EUV heating on the spatial distribution of JSR has never been confirmed, so this study is the first attempt to confirm the solar UV/EUV effect on spatial distribution of JSR. We have selected the data observed from 28th Jan. to 5th Feb. 2000 at 327MHz. During the period, solar UV/EUV flux expected on Jupiter showed almost monotonic increase. It is expected from the analysis for the period that the enhancement of radial diffusion caused by solar UV/EUV heating produces total flux enhancement and dawn-dusk asymmetry of the emission distribution of the JSR. We can therefore examine the scenario by measuring total flux density and dawn-dusk peak emission ratio of JSR, and their relationships to the variation of solar UV/EUV activity. A preliminary result shows that total flux density variations occurred corresponding to the solar UV/EUV variations, but we couldn't find variations in the dawn-dusk asymmetry above the one rms level calculated from the background image. *The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc.
Short and long periodic atmospheric variations between 25 and 200 km
NASA Technical Reports Server (NTRS)
Justus, C. G.; Woodrum, A.
1973-01-01
Previously collected data on atmospheric pressure, density, temperature and winds between 25 and 200 km from sources including Meteorological Rocket Network data, ROBIN falling sphere data, grenade release and pitot tube data, meteor winds, chemical release winds, satellite data, and others were analyzed by a daily difference method and results on the distribution statistics, magnitude, and spatial structure of gravity wave and planetary wave atmospheric variations are presented. Time structure of the gravity wave variations were determined by the analysis of residuals from harmonic analysis of time series data. Planetary wave contributions in the 25-85 km range were discovered and found to have significant height and latitudinal variation. Long period planetary waves, and seasonal variations were also computed by harmonic analysis. Revised height variations of the gravity wave contributions in the 25 to 85 km height range were computed. An engineering method and design values for gravity wave magnitudes and wave lengths are given to be used for such tasks as evaluating the effects on the dynamical heating, stability and control of spacecraft such as the space shuttle vehicle in launch or reentry trajectories.
NASA Astrophysics Data System (ADS)
Xiao, Jianyong; Bai, Xiaoyong; Zhou, Dequan; Qian, Qinghuan; Zeng, Cheng; Chen, Fei
2018-01-01
Vegetation coverage dynamics is affected by climatic, topography and human activities, which is an important indicator reflecting the regional ecological environment. Revealing the spatial-temporal characteristics of vegetation coverage is of great significance to the protection and management of ecological environment. Based on MODIS NDVI data and the Maximum Value Composites (MVC), we excluded soil spectrum interference to calculate Fractional Vegetation Coverage (FVC). Then the long-term FVC was used to calculate the spatial pattern and temporal variation of vegetation in Wujiang River Basin from 2000 to 2016 by using Trend analysis and Hurst index. The relationship between topography and spatial distribution of FVC was analyzed. The main conclusions are as follows: (1) The multi-annual mean vegetation coverage reveals a spatial distribution variation characteristic of low value in midstream and high level in other parts of the basin, owing a mean value of 0.6567. (2) From 2000 to 2016, the FVC of the Wujiang River Basin fluctuated between 0.6110 and 0.7380, and the overall growth rate of FVC was 0.0074/a. (3) The area of vegetation coverage tending to improve is more than that going to degrade in the future. Grass land, Arable land and Others improved significantly; karst rocky desertification comprehensive management project lead to persistent vegetation coverage improvement of Grass land, Arable land and Others. Residential land is covered with obviously degraded vegetation, resulting of urban sprawl; (4) The spatial distribution of FVC is positively correlated with TNI. Researches of spatial-temporal evolution of vegetation coverage have significant meaning for the ecological environment protection and management of the Wujiang River Basin.
Temporal and spatial distribution of Microcystis biomass and genotype in bloom areas of Lake Taihu.
Guan, Dong-Xing; Wang, Xingyu; Xu, Huacheng; Chen, Li; Li, Pengfu; Ma, Lena Q
2018-06-26
Cyanobacterial blooms as a global environmental issue are of public health concern. In this study, we investigated the spatial (10 sites) and temporal (June, August and October) variations in: 1) their biomass based on chlorophyll-a (chl-a) concentration, 2) their toxic genotype based on gene copy ratio of mcyJ to cpcBA, and 3) their cpcBA genotype composition of Microcystis during cyanobacterial bloom in Lake Taihu. While spatial-temporal variations were found in chl-a and mcyJ/cpcBA ratio, only spatial variation was observed in cpcBA genotype composition. Samples from northwestern part had a higher chl-a, but mcyJ/cpcBA ratio didn't vary among the sites. High chl-a was observed in August, while mcyJ/cpcBA ratio and genotypic richness increased with time. The spatial variations in chl-a and mcyJ/cpcBA ratio and temporal variation in cpcBA genotype were correlated negatively with dissolved N and positively with dissolved P. Spatial distribution of Microcystis biomass was positively correlated with nitrite and P excluding October, but no correlation was found for spatial distribution of mcyJ/cpcBA ratio and cpcBA genotype. Spatial distribution of toxic and cpcBA genotypes may result from horizontal transport of Microcystis colonies, while spatial variation in Microcystis biomass was probably controlled by both nutrient-mediated growth and horizontal transport of Microcystis. The temporal variation in Microcystis biomass, toxic genotype and cpcBA genotype composition were related to nutrient levels, but cause-and-effect relationships require further study. Copyright © 2018 Elsevier Ltd. All rights reserved.
Luan, Hui; Law, Jane; Lysy, Martin
2018-02-01
Neighborhood restaurant environment (NRE) plays a vital role in shaping residents' eating behaviors. While NRE 'healthfulness' is a multi-facet concept, most studies evaluate it based only on restaurant type, thus largely ignoring variations of in-restaurant features. In the few studies that do account for such features, healthfulness scores are simply averaged over accessible restaurants, thereby concealing any uncertainty that attributed to neighborhoods' size or spatial correlation. To address these limitations, this paper presents a Bayesian Spatial Factor Analysis for assessing NRE healthfulness in the city of Kitchener, Canada. Several in-restaurant characteristics are included. By treating NRE healthfulness as a spatially correlated latent variable, the adopted modeling approach can: (i) identify specific indicators most relevant to NRE healthfulness, (ii) provide healthfulness estimates for neighborhoods without accessible restaurants, and (iii) readily quantify uncertainties in the healthfulness index. Implications of the analysis for intervention program development and community food planning are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.
Bertazzon, Stefania; Shahid, Rizwan
2017-07-25
An exploratory spatial analysis investigates the location of schools in Calgary (Canada) in relation to air pollution and active transportation options. Air pollution exhibits marked spatial variation throughout the city, along with distinct spatial patterns in summer and winter; however, all school locations lie within low to moderate pollution levels. Conversely, the study shows that almost half of the schools lie in low walkability locations; likewise, transitability is low for 60% of schools, and only bikability is widespread, with 93% of schools in very bikable locations. School locations are subsequently categorized by pollution exposure and active transportation options. This analysis identifies and maps schools according to two levels of concern: schools in car-dependent locations and relatively high pollution; and schools in locations conducive of active transportation, yet exposed to relatively high pollution. The findings can be mapped and effectively communicated to the public, health practitioners, and school boards. The study contributes with an explicitly spatial approach to the intra-urban public health literature. Developed for a moderately polluted city, the methods can be extended to more severely polluted environments, to assist in developing spatial public health policies to improve respiratory outcomes, neurodevelopment, and metabolic and attention disorders in school-aged children.
Shaul, Oren; Fanrazi-Kahana, Michal; Meitav, Omri; Pinhasi, Gad A; Abookasis, David
2017-11-10
Heat stress (HS) is a medical emergency defined by abnormally elevated body temperature that causes biochemical, physiological, and hematological changes. The goal of the present research was to detect variations in optical properties (absorption, reduced scattering, and refractive index coefficients) of mouse brain tissue during HS by using near-infrared (NIR) spatial light modulation. NIR spatial patterns with different spatial phases were used to differentiate the effects of tissue scattering from those of absorption. Decoupling optical scattering from absorption enabled the quantification of a tissue's chemical constituents (related to light absorption) and structural properties (related to light scattering). Technically, structured light patterns at low and high spatial frequencies of six wavelengths ranging between 690 and 970 nm were projected onto the mouse scalp surface while diffuse reflected light was recorded by a CCD camera positioned perpendicular to the mouse scalp. Concurrently to pattern projection, brain temperature was measured with a thermal camera positioned slightly off angle from the mouse head while core body temperature was monitored by thermocouple probe. Data analysis demonstrated variations from baseline measurements in a battery of intrinsic brain properties following HS.
Spatio-temporal variation of methane over Indian region: Seasonal and inter-annual variation .
NASA Astrophysics Data System (ADS)
M, K.; Nair, P. R.
2015-12-01
Methane (CH4) has an important role in the radiation budget and chemistry in the lower and middle atmosphere as a greenhouse and reactive trace gas. The rapid developments in the agriculture and industry over India have lead to the emission of many pollutants like CO, O3, CH4, CO2, SO2 etc into the atmosphere. However, their sources, sinks and concentration levels are poorly understood because of the lack of systematic sampling and monitoring. The advent of satellite remote sensing has helped to analyze the chemical composition of atmosphere with good spatial coverage especially over tropical region which was poorly sampled with the existing surface network. This work attempts an analysis of spatial distribution, seasonal cycle and inter annual variation of CH4 over Indian region during 2003-2009 using SCIAMACHY data onboard ENVISAT. Column CH4 varies from 1740-1890 ppbv over Indian region with distinct spatial and temporal features. We observed a dependence of seasonal CH4 variation on rice cultivation, convective activities and changes in boundary layer characteristics. The comparative study using satellite, aircraft and surface measurement shown CH4 has non-homogeneity in its distribution and seasonal variation in different layers of atmosphere. A comparative study of CH4 at different hot spot regions over the globe was carried out which showed prominent hemispherical variations. Large spread in column CH4 was observed at India and Chinese region compared to other regions with a significant seasonal variability. This study points to the blending of satellite, aircraft and surface measurements for the realization of regional distribution of CH4.
Helm, Fabian; Munzert, Jörn; Troje, Nikolaus F
2017-08-01
This study examined the kinematic characteristics of disguised movements by applying linear discriminant (LDA) and dissimilarity analyses to the motion data from 788 disguised and 792 non-disguised 7-m penalty throws performed by novice and expert handball field players. Results of the LDA showed that discrimination between type of throws (disguised vs. non-disguised) was more error-prone when throws were performed by experts (spatial: 4.6%; temporal: 29.6%) compared to novices (spatial: 1.0%; temporal: 20.2%). The dissimilarity analysis revealed significantly smaller spatial dissimilarities and variations between type of throws in experts compared to novices (p<0.001), but also showed that these spatial dissimilarities and variations increased significantly in both groups the closer the throws came to the moment of (predicted) ball release. In contrast, temporal dissimilarities did not differ significantly between groups. Thus, our data clearly demonstrate that expertise in disguising one's own action intentions results in an ability to perform disguised penalty throws that are highly similar to genuine throws. We suggest that this expertise depends mainly on keeping spatial dissimilarities small. However, the attempt to disguise becomes a challenge the closer one gets to the action outcome (i.e., ball release) becoming visible. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Itoh, M.; Kosugi, Y.; Takanashi, S.; Hayashi, Y.; Kanemitsu, S.; Osaka, K.; Tani, M.; Nik, A. R.
2010-09-01
To clarify the factors controlling temporal and spatial variations of soil carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes, we investigated these gas fluxes and environmental factors in a tropical rainforest in Peninsular Malaysia. Temporal variation of CO2 flux in a 2-ha plot was positively related to soil water condition and rainfall history. Spatially, CO2 flux was negatively related to soil water condition. When CO2 flux hotspots were included, no other environmental factors such as soil C or N concentrations showed any significant correlation. Although the larger area sampled in the present study complicates explanations of spatial variation of CO2 flux, our results support a previously reported bipolar relationship between the temporal and spatial patterns of CO2 flux and soil water condition observed at the study site in a smaller study plot. Flux of CH4 was usually negative with little variation, resulting in the soil at our study site functioning as a CH4 sink. Both temporal and spatial variations of CH4 flux were positively related to the soil water condition. Soil N concentration was also related to the spatial distribution of CH4 flux. Some hotspots were observed, probably due to CH4 production by termites, and these hotspots obscured the relationship between both temporal and spatial variations of CH4 flux and environmental factors. Temporal variation of N2O flux and soil N2O concentration was large and significantly related to the soil water condition, or in a strict sense, to rainfall history. Thus, the rainfall pattern controlled wet season N2O production in soil and its soil surface flux. Spatially, large N2O emissions were detected in wet periods at wetter and anaerobic locations, and were thus determined by soil physical properties. Our results showed that, even in Southeast Asian rainforests where distinct dry and wet seasons do not exist, variation in the soil water condition related to rainfall history controlled the temporal variations of soil CO2 flux, CH4 uptake, and N2O emission. The soil water condition associated with soil hydraulic properties was also the important controlling factor of the spatial distributions of these gas fluxes.
Predictive and postdictive analysis of forage yield trials
USDA-ARS?s Scientific Manuscript database
Classical experimental design theory, the predominant treatment in most textbooks, promotes the use of blocking designs for control of spatial variability in field studies and other situations in which there is significant variation among heterogeneity among experimental units. Many blocking design...
Alvarenga, Júlio Miguel; Vieira, Cecília Rodrigues; Godinho, Leandro Braga; Campelo, Pedro Henrique; Pitts, James Purser; Colli, Guarino Rinaldi
2017-01-01
Understanding how and why biological communities are organized over space and time is a major challenge and can aid biodiversity conservation in times of global changes. Herein, spatial-temporal variation in the structure of velvet ant communities was examined along a forest-savanna gradient in the Brazilian Cerrado to assess the roles of environmental filters and interspecific interactions upon community assembly. Velvet ants were sampled using 25 arrays of Y-shaped pitfall traps with drift fences for one year along an environmental gradient from cerrado sensu stricto (open canopy, warmer, drier) to cerradão (closed canopy, cooler, moister). Dataloggers installed on each trap recorded microclimate parameters throughout the study period. The effects of spatial distances, microclimate parameters and shared ancestry on species abundances and turnover were assessed with canonical correspondence analysis, generalized dissimilarity modelling and variance components analysis. Velvet ant diversity and abundance were higher in the cerrado sensu stricto and early in the wet season. There was pronounced compositional turnover along the environmental gradient, and temporal variation in richness and abundance was stronger than spatial variation. The dry season blooming of woody plant species fosters host abundance and, subsequently, velvet ant captures. Species were taxonomically clustered along the gradient with Sphaeropthalmina (especially Traumatomutilla spp.) and Pseudomethocina more associated, respectively, with cerrado sensu stricto and cerradão. This suggests a predominant role of environmental filters on community assemble, with physiological tolerances and host preferences being shared among members of the same lineages. Induced environmental changes in Cerrado can impact communities of wasps and their hosts with unpredictable consequences upon ecosystem functioning and services.
Godinho, Leandro Braga; Campelo, Pedro Henrique; Pitts, James Purser; Colli, Guarino Rinaldi
2017-01-01
Understanding how and why biological communities are organized over space and time is a major challenge and can aid biodiversity conservation in times of global changes. Herein, spatial-temporal variation in the structure of velvet ant communities was examined along a forest-savanna gradient in the Brazilian Cerrado to assess the roles of environmental filters and interspecific interactions upon community assembly. Velvet ants were sampled using 25 arrays of Y-shaped pitfall traps with drift fences for one year along an environmental gradient from cerrado sensu stricto (open canopy, warmer, drier) to cerradão (closed canopy, cooler, moister). Dataloggers installed on each trap recorded microclimate parameters throughout the study period. The effects of spatial distances, microclimate parameters and shared ancestry on species abundances and turnover were assessed with canonical correspondence analysis, generalized dissimilarity modelling and variance components analysis. Velvet ant diversity and abundance were higher in the cerrado sensu stricto and early in the wet season. There was pronounced compositional turnover along the environmental gradient, and temporal variation in richness and abundance was stronger than spatial variation. The dry season blooming of woody plant species fosters host abundance and, subsequently, velvet ant captures. Species were taxonomically clustered along the gradient with Sphaeropthalmina (especially Traumatomutilla spp.) and Pseudomethocina more associated, respectively, with cerrado sensu stricto and cerradão. This suggests a predominant role of environmental filters on community assemble, with physiological tolerances and host preferences being shared among members of the same lineages. Induced environmental changes in Cerrado can impact communities of wasps and their hosts with unpredictable consequences upon ecosystem functioning and services. PMID:29077763
Soil analysis based on sa,ples withdrawn from different volumes: correlation versus calibration
Lucian Weilopolski; Kurt Johnsen; Yuen Zhang
2010-01-01
Soil, particularly in forests, is replete with spatial variation with respect to soil C. Th e present standard chemical method for soil analysis by dry combustion (DC) is destructive, and comprehensive sampling is labor intensive and time consuming. Th ese, among other factors, are contributing to the development of new methods for soil analysis. Th ese include a near...
USDA-ARS?s Scientific Manuscript database
Climate gradients shape spatial variation in the richness and composition of plant communities. Given future predicted changes in climate means and variability, and likely regional variation in the magnitudes of these changes, it is important to determine how temporal variation in climate influences...
Steve J. Petty; Billy L. Fawkes
1997-01-01
Research on Tawny Owls (Strix aluco) in Kielder Forest, northern England, since 1981 demonstrated that field voles (Microtus agrestis) were their most important food. Here, field voles exhibited a 3-4 year cycle of abundance, and mean clutch size in Tawny Owls was significantly related to vole abundance in March. In this analysis...
Ismail, Azimah; Toriman, Mohd Ekhwan; Juahir, Hafizan; Zain, Sharifuddin Md; Habir, Nur Liyana Abdul; Retnam, Ananthy; Kamaruddin, Mohd Khairul Amri; Umar, Roslan; Azid, Azman
2016-05-15
This study presents the determination of the spatial variation and source identification of heavy metal pollution in surface water along the Straits of Malacca using several chemometric techniques. Clustering and discrimination of heavy metal compounds in surface water into two groups (northern and southern regions) are observed according to level of concentrations via the application of chemometric techniques. Principal component analysis (PCA) demonstrates that Cu and Cr dominate the source apportionment in northern region with a total variance of 57.62% and is identified with mining and shipping activities. These are the major contamination contributors in the Straits. Land-based pollution originating from vehicular emission with a total variance of 59.43% is attributed to the high level of Pb concentration in the southern region. The results revealed that one state representing each cluster (northern and southern regions) is significant as the main location for investigating heavy metal concentration in the Straits of Malacca which would save monitoring cost and time. The monitoring of spatial variation and source of heavy metals pollution at the northern and southern regions of the Straits of Malacca, Malaysia, using chemometric analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.
Object-based vegetation classification with high resolution remote sensing imagery
NASA Astrophysics Data System (ADS)
Yu, Qian
Vegetation species are valuable indicators to understand the earth system. Information from mapping of vegetation species and community distribution at large scales provides important insight for studying the phenological (growth) cycles of vegetation and plant physiology. Such information plays an important role in land process modeling including climate, ecosystem and hydrological models. The rapidly growing remote sensing technology has increased its potential in vegetation species mapping. However, extracting information at a species level is still a challenging research topic. I proposed an effective method for extracting vegetation species distribution from remotely sensed data and investigated some ways for accuracy improvement. The study consists of three phases. Firstly, a statistical analysis was conducted to explore the spatial variation and class separability of vegetation as a function of image scale. This analysis aimed to confirm that high resolution imagery contains the information on spatial vegetation variation and these species classes can be potentially separable. The second phase was a major effort in advancing classification by proposing a method for extracting vegetation species from high spatial resolution remote sensing data. The proposed classification employs an object-based approach that integrates GIS and remote sensing data and explores the usefulness of ancillary information. The whole process includes image segmentation, feature generation and selection, and nearest neighbor classification. The third phase introduces a spatial regression model for evaluating the mapping quality from the above vegetation classification results. The effects of six categories of sample characteristics on the classification uncertainty are examined: topography, sample membership, sample density, spatial composition characteristics, training reliability and sample object features. This evaluation analysis answered several interesting scientific questions such as (1) whether the sample characteristics affect the classification accuracy and how significant if it does; (2) how much variance of classification uncertainty can be explained by above factors. This research is carried out on a hilly peninsular area in Mediterranean climate, Point Reyes National Seashore (PRNS) in Northern California. The area mainly consists of a heterogeneous, semi-natural broadleaf and conifer woodland, shrub land, and annual grassland. A detailed list of vegetation alliances is used in this study. Research results from the first phase indicates that vegetation spatial variation as reflected by the average local variance (ALV) keeps a high level of magnitude between 1 m and 4 m resolution. (Abstract shortened by UMI.)
Spatial pattern characteristics of water footprint for maize production in Northeast China.
Duan, Peili; Qin, Lijie; Wang, Yeqiao; He, Hongshi
2016-01-30
Water footprint (WF) methodology is essential for quantifying total water consumption of crop production and making efficient water management policies. This study calculated the green, blue, grey and total WFs of maize production in Northeast China from 1998 to 2012 and compared the values of the provinces. This study also analyzed the spatial variation and structure characteristics of the WFs at the prefecture level. The annual average WF of maize production was 1029 m(3) per ton, which was 51% green, 21% blue and 28% grey. The WF of maize production was highest in Liaoning Province, moderate in Heilongjiang Province and lowest in Jilin Province. The spatial differences of the WFs calculated for the 36 major maize production prefectures were significant in Northeast China. There was a moderate positive spatial autocorrelation among prefectures that had similar WFs. Local indicator of spatial autocorrelation index (LISA) analysis identified prefectures with higher WFs in the southeast region of Liaoning Province and the southwest region of Heilongjiang Province and prefectures with lower WFs in the middle of Jilin Province. Spatial differences in the WF of maize production were caused mainly by variations in climate conditions, soil quality, irrigation facilities and maize yield. The spatial distribution of WFs can help provide a scientific basis for optimizing maize production distribution and then formulate strategies to reduce the WF of maize production. © 2015 Society of Chemical Industry.
NASA Astrophysics Data System (ADS)
Park, K.; Hahm, D.; Lee, D. G.; Rhee, T. S.; Kim, H. C.
2014-12-01
The Amundsen Sea, Antarctica, has been known for one of the most susceptible region to the current climate change such as sea ice melting and sea surface temperature change. In the Southern Ocean, a predominant amount of primary production is occurring in the continental shelf region. Phytoplankton blooms take place during the austral summer due to the limited sunlit and sea ice cover. Thus, quantifying the variation of summer season net community production (NCP) in the Amundsen Sea is essential to analyze the influence of climate change to the variation of biogeochemical cycle in the Southern Ocean. During the past three years of 2011, 2012 and 2014 in austral summer, we have conducted underway observations of ΔO2/Ar and derived NCP of the Amundsen Sea. Despite the importance of NCP for understanding biological carbon cycle of the ocean, the observations are rather limited to see the spatio-temporal variation in the Amundsen Sea. Therefore, we applied self-organizing map (SOM) analysis to expand our observed data sets and estimate the NCP during the summer season. SOM analysis, a type of artificial neural network, has been proved to be a useful method for extracting and classifying features in geoscience. In oceanography, SOM has applied for the analysis of various properties of the seawater such as sea surface temperature, chlorophyll concentration, pCO2, and NCP. Especially it is useful to expand a spatial coverage of direct measurements or to estimate properties whose satellite observations are technically or spatially limited. In this study, we estimate summer season NCP and find a variables set which optimally delineates the NCP variation in the Amundsen Sea as well. Moreover, we attempt to analyze the interannual variation of the Amundsen Sea NCP by taking climatological factors into account for the SOM analysis.
Regionalization of precipitation characteristics in Iran's Lake Urmia basin
NASA Astrophysics Data System (ADS)
Fazel, Nasim; Berndtsson, Ronny; Uvo, Cintia Bertacchi; Madani, Kaveh; Kløve, Bjørn
2018-04-01
Lake Urmia in northwest Iran, once one of the largest hypersaline lakes in the world, has shrunk by almost 90% in area and 80% in volume during the last four decades. To improve the understanding of regional differences in water availability throughout the region and to refine the existing information on precipitation variability, this study investigated the spatial pattern of precipitation for the Lake Urmia basin. Daily rainfall time series from 122 precipitation stations with different record lengths were used to extract 15 statistical descriptors comprising 25th percentile, 75th percentile, and coefficient of variation for annual and seasonal total precipitation. Principal component analysis in association with cluster analysis identified three main homogeneous precipitation groups in the lake basin. The first sub-region (group 1) includes stations located in the center and southeast; the second sub-region (group 2) covers mostly northern and northeastern part of the basin, and the third sub-region (group 3) covers the western and southern edges of the basin. Results of principal component (PC) and clustering analyses showed that seasonal precipitation variation is the most important feature controlling the spatial pattern of precipitation in the lake basin. The 25th and 75th percentiles of winter and autumn are the most important variables controlling the spatial pattern of the first rotated principal component explaining about 32% of the total variance. Summer and spring precipitation variations are the most important variables in the second and third rotated principal components, respectively. Seasonal variation in precipitation amount and seasonality are explained by topography and influenced by the lake and westerly winds that are related to the strength of the North Atlantic Oscillation. Despite using incomplete time series with different lengths, the identified sub-regions are physically meaningful.
Spatial and Temporal Comparison of DNRA Communities in New River Estuary, USA
NASA Astrophysics Data System (ADS)
Song, B.; Lisa, J.; Tobias, C. R.
2016-02-01
Dissimilatory nitrate reduction to ammonium (DNRA) is an important nitrate respiring pathway, competing with denitrification, in various ecosystems. Studies examining the diversity and composition of DNRA communities are limited and their link to DNRA activity is unknown. We conducted a multidisciplinary investigation of sediment communities in the upper reaches of a eutrophic estuary to examine spatial and temporal variation of DNRA community structures and determine their linkage to activities. Sediment samples were collected seasonally from two study sites (AA2 and JAX) in the New River Estuary, North Carolina, USA. 15N-nitrate tracer experiments were conducted to measure potential DNRA rates while abundance of DNRA communities was measured using quantitative PCR of cytochrome C nitrite reductase genes (nrfA). Composition and diversity of DNRA communities were also examined based on next generation sequencing (NGS) of nrfA genes using an Ion Torrent PGM. Bioinformatic analysis was conducted using the FunGene pipeline and Mothur program. Higher DNRA activities were measured at JAX and associated with higher abundance of nrfA genes. Seasonal variation in DNRA rates and nrfA gene abundance was more evident at JAX than AA2. Nitrate concentration and dissolved oxygen in bottom water were significantly and positively correlated with activities and abundance of DNRA communities. The nrfA NGS analysis revealed that spatial variation of DNRA communities was much greater than temporal variation with salinity, dissolved organic carbon, and nitrate as the most important environmental variables affecting these communities. Diversity of DNRA communities was negative correlated with the DNRA rates and nrfA gene abundance, which suggests that dominant members of the DNRA community are responsible for higher rates. Thus, our multidisciplinary study clearly demonstrates the linkage between structure and activities of DNRA communities in the upper reaches of New River Estuary.
Application of spatial Poisson process models to air mass thunderstorm rainfall
NASA Technical Reports Server (NTRS)
Eagleson, P. S.; Fennessy, N. M.; Wang, Qinliang; Rodriguez-Iturbe, I.
1987-01-01
Eight years of summer storm rainfall observations from 93 stations in and around the 154 sq km Walnut Gulch catchment of the Agricultural Research Service, U.S. Department of Agriculture, in Arizona are processed to yield the total station depths of 428 storms. Statistical analysis of these random fields yields the first two moments, the spatial correlation and variance functions, and the spatial distribution of total rainfall for each storm. The absolute and relative worth of three Poisson models are evaluated by comparing their prediction of the spatial distribution of storm rainfall with observations from the second half of the sample. The effect of interstorm parameter variation is examined.
NASA Astrophysics Data System (ADS)
Ryu, D.; Liu, S.; Western, A. W.; Webb, J. A.; Lintern, A.; Leahy, P.; Wilson, P.; Watson, M.; Waters, D.; Bende-Michl, U.
2016-12-01
The Great Barrier Reef (GBR) lagoon has been experiencing significant water quality deterioration due in part to agricultural intensification and urban settlement in adjacent catchments. The degradation of water quality in rivers is caused by land-derived pollutants (i.e. sediment, nutrient and pesticide). A better understanding of dynamics of water quality is essential for land management to improve the GBR ecosystem. However, water quality is also greatly influenced by natural hydrological processes. To assess influencing factors and predict the water quality accurately, selection of the most important predictors of water quality is necessary. In this work, multivariate statistical techniques - cluster analysis (CA), principal component analysis (PCA) and factor analysis (FA) - are used to reduce the complexity derived from the multidimensional water quality monitoring data. Seventeen stations are selected across the GBR catchments, and the event-based measurements of 12 variables monitored during 9 years (2006 - 2014) were analysed by means of CA and PCA/FA. The key findings are: (1) 17 stations can be grouped into two clusters according to the hierarchical CA, and the spatial dissimilarity between these sites is characterised by the different climatic and land use in the GBR catchments. (2) PCA results indicate that the first 3 PCs explain 85% of the total variance, and FA on the entire data set shows that the varifactor (VF) loadings can be used to interpret the sources of spatial variation in water quality on the GBR catchments level. The impact of soil erosion and non-point source of pollutants from agriculture contribution to VF1 and the variability in hydrological conditions and biogeochemical processes can explain the loadings in VF2. (3) FA is also performed on two groups of sites identified in CA individually, to evaluate the underlying sources that are responsible for spatial variability in water quality in the two groups. For the Cluster 1 sites, spatial variations in water quality are likely from the agricultural inputs (fertilises) and for the Cluster 2 sites, the differences in hydrological transport is responsible for large spatial variations in water quality. These findings can be applied to water quality assessment along with establish effective water and land management in the future.
Parallel Evolution of Copy-Number Variation across Continents in Drosophila melanogaster.
Schrider, Daniel R; Hahn, Matthew W; Begun, David J
2016-05-01
Genetic differentiation across populations that is maintained in the presence of gene flow is a hallmark of spatially varying selection. In Drosophila melanogaster, the latitudinal clines across the eastern coasts of Australia and North America appear to be examples of this type of selection, with recent studies showing that a substantial portion of the D. melanogaster genome exhibits allele frequency differentiation with respect to latitude on both continents. As of yet there has been no genome-wide examination of differentiated copy-number variants (CNVs) in these geographic regions, despite their potential importance for phenotypic variation in Drosophila and other taxa. Here, we present an analysis of geographic variation in CNVs in D. melanogaster. We also present the first genomic analysis of geographic variation for copy-number variation in the sister species, D. simulans, in order to investigate patterns of parallel evolution in these close relatives. In D. melanogaster we find hundreds of CNVs, many of which show parallel patterns of geographic variation on both continents, lending support to the idea that they are influenced by spatially varying selection. These findings support the idea that polymorphic CNVs contribute to local adaptation in D. melanogaster In contrast, we find very few CNVs in D. simulans that are geographically differentiated in parallel on both continents, consistent with earlier work suggesting that clinal patterns are weaker in this species. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
[Temporal and spatial variation of MODIS vegetation indices in Hunan Province].
Lin, Hui; Xiong, Yu-Jiu; Wan, Ling-Feng; Mo, Deng-Kui; Sun, Hua
2007-03-01
Based on MODIS images and by using the algorithm of maximum value composite (MVC), the monthly vegetation indices (VIs) in 2005 in Hunan Province were obtained. Through the analysis of the MODIS VIs, Hunan Province was divided into six districts to describe the spatial distribution of the VIs, and by using the monthly mean temperature and rainfall data collected from 5 climatic monitoring stations in this province, the temporal variation of the VIs was analyzed. The results showed that the spatial distribution of MODIS VIs was positively correlated with vegetation cover, and appeared regional characteristics. The MODIS VIs varied with season, and the curves of their monthly mean values were downwards opening quadratic parabolas, with the maximum appeared in July. The value of MODIS EVI was smaller than that of MODIS NDVI. MODIS VI was mainly affected by monthly mean temperature, but this effect was decreased with decreasing latitude. The variation pattern of MODIS EVI was more apparent than that of MODIS NDVI, i. e. , the quadratic parabola of MODIS EVI was smoother, going gradually from minimum to maximum and then going down, while that of MODIS NDVI had tiny fluctuations on both sides of the maximum point.
NASA Astrophysics Data System (ADS)
Fan, Linfeng; Lehmann, Peter; Or, Dani
2015-04-01
Naturally-occurring spatial variations in soil properties (e.g., soil depth, moisture, and texture) affect key hydrological processes and potentially the mechanical response of soil to hydromechanical loading (relative to the commonly-assumed uniform soil mantle). We quantified the effects of soil spatial variability on the triggering of rainfall-induced shallow landslides at the hillslope- and catchment-scales, using a physically-based landslide triggering model that considers interacting soil columns with mechanical strength thresholds (represented by the Fiber Bundle Model). The spatial variations in soil properties are represented as Gaussian random distributions and the level of variation is characterized by the coefficient of variation and correlation lengths of soil properties (i.e., soil depth, soil texture and initial water content in this study). The impacts of these spatial variations on landslide triggering characteristics were measured by comparing the times to triggering and landslide volumes for heterogeneous soil properties and homogeneous cases. Results at hillslope scale indicate that for spatial variations of an individual property (without cross correlation), the increasing of coefficient of variation introduces weak spots where mechanical damage is accelerated and leads to earlier onset of landslide triggering and smaller volumes. Increasing spatial correlation length of soil texture and initial water content also induces early landslide triggering and small released volumes due to the transition of failure mode from brittle to ductile failure. In contrast, increasing spatial correlation length of soil depth "reduces" local steepness and postpones landslide triggering. Cross-correlated soil properties generally promote landslide initiation, but depending on the internal structure of spatial distribution of each soil property, landslide triggering may be reduced. The effects of cross-correlation between initial water content and soil texture were investigated in detail at the catchment scale by incorporating correlations of both variables with topography. Results indicate that the internal structure of the spatial distribution of each soil property together with their interplays determine the overall performance of the coupled spatial variability. This study emphasizes the importance of both the randomness and spatial structure of soil properties on landslide triggering and characteristics.
NASA Astrophysics Data System (ADS)
Kathiravan, K.; Natesan, Usha; Vishnunath, R.
2017-03-01
The intention of this study was to appraise the spatial and temporal variations in the physico-chemical parameters of coastal waters of Rameswaram Island, Gulf of Mannar Marine Biosphere Reserve, south India, using multivariate statistical techniques, such as cluster analysis, factor analysis and principal component analysis. Spatio-temporal variations among the physico-chemical parameters are observed in the coastal waters of Gulf of Mannar, especially during northeast and post monsoon seasons. It is inferred that the high loadings of pH, temperature, suspended particulate matter, salinity, dissolved oxygen, biochemical oxygen demand, chlorophyll a, nutrient species of nitrogen and phosphorus strongly determine the discrimination of coastal water quality. Results highlight the important role of monsoonal variations to determine the coastal water quality around Rameswaram Island.
NASA Astrophysics Data System (ADS)
Labbardi, Hanane; Ettahiri, Omar; Lazar, Said; Massik, Zakia; El Antri, Said
2005-04-01
Our interest is related to the hydrological characteristics of the Moulay Bousselham lagoon. Water samples were taken monthly from July 2001 to June 2002 in 15 stations distributed along the lagoon. The various measured hydrological parameters (temperature, salinity, suspended matter, chlorophyll a) showed significant monthly variations ( p<0.001), whereas spatially among all sampled stations, only the salinity showed significant variations. The variability analysis approached by the analysis of the normalized principal components combined with discriminate analysis showed very small inter-stations variability. Its percentage is 11% and 9% of the total variance during high and low tide, respectively. To cite this article: H. Labbardi et al., C. R. Geoscience 337 (2005).
Area variations in multiple morbidity using a life table methodology.
Congdon, Peter
Analysis of healthy life expectancy is typically based on a binary distinction between health and ill-health. By contrast, this paper considers spatial modelling of disease free life expectancy taking account of the number of chronic conditions. Thus the analysis is based on population sub-groups with no disease, those with one disease only, and those with two or more diseases (multiple morbidity). Data on health status is accordingly modelled using a multinomial likelihood. The analysis uses data for 258 small areas in north London, and shows wide differences in the disease burden related to multiple morbidity. Strong associations between area socioeconomic deprivation and multiple morbidity are demonstrated, as well as strong spatial clustering.
Spatial variation and density-dependent dispersal in competitive coexistence.
Amarasekare, Priyanga
2004-01-01
It is well known that dispersal from localities favourable to a species' growth and reproduction (sources) can prevent competitive exclusion in unfavourable localities (sinks). What is perhaps less well known is that too much emigration can undermine the viability of sources and cause regional competitive exclusion. Here, I investigate two biological mechanisms that reduce the cost of dispersal to source communities. The first involves increasing the spatial variation in the strength of competition such that sources can withstand high rates of emigration; the second involves reducing emigration from sources via density-dependent dispersal. I compare how different forms of spatial variation and modes of dispersal influence source viability, and hence source-sink coexistence, under dominance and pre-emptive competition. A key finding is that, while spatial variation substantially reduces dispersal costs under both types of competition, density-dependent dispersal does so only under dominance competition. For instance, when spatial variation in the strength of competition is high, coexistence is possible (regardless of the type of competition) even when sources experience high emigration rates; when spatial variation is low, coexistence is restricted even under low emigration rates. Under dominance competition, density-dependent dispersal has a strong effect on coexistence. For instance, when the emigration rate increases with density at an accelerating rate (Type III density-dependent dispersal), coexistence is possible even when spatial variation is quite low; when the emigration rate increases with density at a decelerating rate (Type II density-dependent dispersal), coexistence is restricted even when spatial variation is quite high. Under pre-emptive competition, density-dependent dispersal has only a marginal effect on coexistence. Thus, the diversity-reducing effects of high dispersal rates persist under pre-emptive competition even when dispersal is density dependent, but can be significantly mitigated under dominance competition if density-dependent dispersal is Type III rather than Type II. These results lead to testable predictions about source-sink coexistence under different regimes of competition, spatial variation and dispersal. They identify situations in which density-independent dispersal provides a reasonable approximation to species' dispersal patterns, and those under which consideration of density-dependent dispersal is crucial to predicting long-term coexistence. PMID:15306322
Imaging spectroscopy links aspen genotype with below-ground processes at landscape scales
Madritch, Michael D.; Kingdon, Clayton C.; Singh, Aditya; Mock, Karen E.; Lindroth, Richard L.; Townsend, Philip A.
2014-01-01
Fine-scale biodiversity is increasingly recognized as important to ecosystem-level processes. Remote sensing technologies have great potential to estimate both biodiversity and ecosystem function over large spatial scales. Here, we demonstrate the capacity of imaging spectroscopy to discriminate among genotypes of Populus tremuloides (trembling aspen), one of the most genetically diverse and widespread forest species in North America. We combine imaging spectroscopy (AVIRIS) data with genetic, phytochemical, microbial and biogeochemical data to determine how intraspecific plant genetic variation influences below-ground processes at landscape scales. We demonstrate that both canopy chemistry and below-ground processes vary over large spatial scales (continental) according to aspen genotype. Imaging spectrometer data distinguish aspen genotypes through variation in canopy spectral signature. In addition, foliar spectral variation correlates well with variation in canopy chemistry, especially condensed tannins. Variation in aspen canopy chemistry, in turn, is correlated with variation in below-ground processes. Variation in spectra also correlates well with variation in soil traits. These findings indicate that forest tree species can create spatial mosaics of ecosystem functioning across large spatial scales and that these patterns can be quantified via remote sensing techniques. Moreover, they demonstrate the utility of using optical properties as proxies for fine-scale measurements of biodiversity over large spatial scales. PMID:24733949
1984-09-01
10). Barratt (1953) also found variation in strategies in a number of spatial tests, particularly for more difficult items. Thus, there is likely to...J. R. Arguments concerning representations for mental imagery. Psychological Review, 1978, §5, 249-277. Barratt , E. S. An analysis of verbal reports...Naval Education and Training Liason Office I Dr. NiIliaa L. Malay t21 Air Force Human Resource Laboratory Chief of Naval Education and Traininc
Distribution of Chironomidae in a semiarid intermittent river of Brazil.
Farias, R L; Carvalho, L K; Medeiros, E S F
2012-12-01
The effects of the intermittency of water flow on habitat structure and substrate composition have been reported to create a patch dynamics for the aquatic fauna, mostly for that associated with the substrate. This study aims to describe the spatial distribution of Chironomidae in an intermittent river of semiarid Brazil and to associate assemblage composition with environmental variables. Benthic invertebrates were sampled during the wet and dry seasons using a D-shaped net (40 cm wide and 250 μm mesh), and the Chironomidae were identified to genus level. The most abundant genera were Tanytarsus, Polypedilum, and Saetheria with important contributions of the genera Procladius, Aedokritus, and Dicrotendipes. Richness and density were not significantly different between the study sites, and multiple regression showed that the variation in richness and density explained by the environmental variables was significant only for substrate composition. The composition of genera showed significant spatial segregation across the study sites. Canonical Correspondence Analysis showed significant correspondence between Chironomidae composition and the environmental variables, with submerged vegetation, elevation, and leaf litter being important predictors of the Chironomidae fauna. This study showed that Chironomidae presented important spatial variation along the river and that this variation was substantially explained by environmental variables associated with the habitat structure and river hierarchy. We suggest that the observed spatial segregation in the fauna results in the high diversity of this group of organisms in intermittent streams.
NASA Astrophysics Data System (ADS)
Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.
2017-09-01
Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.
Hundessa, Samuel H; Williams, Gail; Li, Shanshan; Guo, Jinpeng; Chen, Linping; Zhang, Wenyi; Guo, Yuming
2016-12-19
Despite the declining burden of malaria in China, the disease remains a significant public health problem with periodic outbreaks and spatial variation across the country. A better understanding of the spatial and temporal characteristics of malaria is essential for consolidating the disease control and elimination programme. This study aims to understand the spatial and spatiotemporal distribution of Plasmodium vivax and Plasmodium falciparum malaria in China during 2005-2009. Global Moran's I statistics was used to detect a spatial distribution of local P. falciparum and P. vivax malaria at the county level. Spatial and space-time scan statistics were applied to detect spatial and spatiotemporal clusters, respectively. Both P. vivax and P. falciparum malaria showed spatial autocorrelation. The most likely spatial cluster of P. vivax was detected in northern Anhui province between 2005 and 2009, and western Yunnan province between 2010 and 2014. For P. falciparum, the clusters included several counties of western Yunnan province from 2005 to 2011, Guangxi from 2012 to 2013, and Anhui in 2014. The most likely space-time clusters of P. vivax malaria and P. falciparum malaria were detected in northern Anhui province and western Yunnan province, respectively, during 2005-2009. The spatial and space-time cluster analysis identified high-risk areas and periods for both P. vivax and P. falciparum malaria. Both malaria types showed significant spatial and spatiotemporal variations. Contrary to P. vivax, the high-risk areas for P. falciparum malaria shifted from the west to the east of China. Further studies are required to examine the spatial changes in risk of malaria transmission and identify the underlying causes of elevated risk in the high-risk areas.
Garza-Gisholt, Eduardo; Hemmi, Jan M; Hart, Nathan S; Collin, Shaun P
2014-01-01
Topographic maps that illustrate variations in the density of different neuronal sub-types across the retina are valuable tools for understanding the adaptive significance of retinal specialisations in different species of vertebrates. To date, such maps have been created from raw count data that have been subjected to only limited analysis (linear interpolation) and, in many cases, have been presented as iso-density contour maps with contour lines that have been smoothed 'by eye'. With the use of stereological approach to count neuronal distribution, a more rigorous approach to analysing the count data is warranted and potentially provides a more accurate representation of the neuron distribution pattern. Moreover, a formal spatial analysis of retinal topography permits a more robust comparison of topographic maps within and between species. In this paper, we present a new R-script for analysing the topography of retinal neurons and compare methods of interpolating and smoothing count data for the construction of topographic maps. We compare four methods for spatial analysis of cell count data: Akima interpolation, thin plate spline interpolation, thin plate spline smoothing and Gaussian kernel smoothing. The use of interpolation 'respects' the observed data and simply calculates the intermediate values required to create iso-density contour maps. Interpolation preserves more of the data but, consequently includes outliers, sampling errors and/or other experimental artefacts. In contrast, smoothing the data reduces the 'noise' caused by artefacts and permits a clearer representation of the dominant, 'real' distribution. This is particularly useful where cell density gradients are shallow and small variations in local density may dramatically influence the perceived spatial pattern of neuronal topography. The thin plate spline and the Gaussian kernel methods both produce similar retinal topography maps but the smoothing parameters used may affect the outcome.
NASA Astrophysics Data System (ADS)
Lu, Bing; He, Yuhong
2017-06-01
Investigating spatio-temporal variations of species composition in grassland is an essential step in evaluating grassland health conditions, understanding the evolutionary processes of the local ecosystem, and developing grassland management strategies. Space-borne remote sensing images (e.g., MODIS, Landsat, and Quickbird) with spatial resolutions varying from less than 1 m to 500 m have been widely applied for vegetation species classification at spatial scales from community to regional levels. However, the spatial resolutions of these images are not fine enough to investigate grassland species composition, since grass species are generally small in size and highly mixed, and vegetation cover is greatly heterogeneous. Unmanned Aerial Vehicle (UAV) as an emerging remote sensing platform offers a unique ability to acquire imagery at very high spatial resolution (centimetres). Compared to satellites or airplanes, UAVs can be deployed quickly and repeatedly, and are less limited by weather conditions, facilitating advantageous temporal studies. In this study, we utilize an octocopter, on which we mounted a modified digital camera (with near-infrared (NIR), green, and blue bands), to investigate species composition in a tall grassland in Ontario, Canada. Seven flight missions were conducted during the growing season (April to December) in 2015 to detect seasonal variations, and four of them were selected in this study to investigate the spatio-temporal variations of species composition. To quantitatively compare images acquired at different times, we establish a processing flow of UAV-acquired imagery, focusing on imagery quality evaluation and radiometric correction. The corrected imagery is then applied to an object-based species classification. Maps of species distribution are subsequently used for a spatio-temporal change analysis. Results indicate that UAV-acquired imagery is an incomparable data source for studying fine-scale grassland species composition, owing to its high spatial resolution. The overall accuracy is around 85% for images acquired at different times. Species composition is spatially attributed by topographical features and soil moisture conditions. Spatio-temporal variation of species composition implies the growing process and succession of different species, which is critical for understanding the evolutionary features of grassland ecosystems. Strengths and challenges of applying UAV-acquired imagery for vegetation studies are summarized at the end.
Nordey, Thibault; Léchaudel, Mathieu; Génard, Michel; Joas, Jacques
2014-11-01
Managing fruit quality is complex because many different attributes have to be taken into account, which are themselves subjected to spatial and temporal variations. Heterogeneous fruit quality has been assumed to be partly related to temperature and maturity gradients within the fruit. To test this assumption, we measured the spatial variability of certain mango fruit quality traits: colour of the peel and of the flesh, and sourness and sweetness, at different stages of fruit maturity using destructive methods as well as vis-NIR reflectance. The spatial variability of mango quality traits was compared to internal variations in thermal time, simulated by a physical model, and to internal variations in maturity, using ethylene content as an indicator. All the fruit quality indicators analysed showed significant spatial and temporal variations, regardless of the measurement method used. The heterogeneity of internal fruit quality traits was not correlated with the marked internal temperature gradient we modelled. However, variations in ethylene content revealed a strong internal maturity gradient which was correlated with the spatial variations in measured mango quality traits. Nonetheless, alone, the internal maturity gradient did not explain the variability of fruit quality traits, suggesting that other factors, such as gas, abscisic acid and water gradients, are also involved. Copyright © 2014 Elsevier GmbH. All rights reserved.
Lindley, Lisa C.; Oyana, Tonny J.
2017-01-01
Cancer is one of the leading causes of death among children in the United States. Previous research has examined geographic variation in cancer incidence and survival, but the geographic variation in mortality among children and adolescents is not as well understood. The purpose of this study was to investigate geographic variation by race in mortality among children and adolescents diagnosed with cancer in Tennessee. Using an innovative combination of spatial and non-spatial analysis techniques with data from the 2004–2011 Tennessee Cancer Registry, pediatric deaths were mapped and the affect of race on the proximity to rural areas and clusters of mortality were explored with multivariate regressions. The findings revealed that African American children and adolescents in Tennessee were more likely than their counterparts of other races to reside in rural areas with close proximity to mortality clusters of children and adolescents with a cancer. Findings have clinical implications for pediatric oncology nurses regarding the delivery of supportive care at end of life for rural African American children and adolescents. PMID:26458417
Spatial and temporal variation in evapotranspiration
USDA-ARS?s Scientific Manuscript database
Spatial and temporal variation in evapotranspiration occurs at multiple scales as the result of several different spatial and temporal patterns in precipitation, soil water holding capacity, cloudiness (available energy), types of crops, and residue and tillage management practices. We have often as...
Quantitative Imaging in Cancer Evolution and Ecology
Grove, Olya; Gillies, Robert J.
2013-01-01
Cancer therapy, even when highly targeted, typically fails because of the remarkable capacity of malignant cells to evolve effective adaptations. These evolutionary dynamics are both a cause and a consequence of cancer system heterogeneity at many scales, ranging from genetic properties of individual cells to large-scale imaging features. Tumors of the same organ and cell type can have remarkably diverse appearances in different patients. Furthermore, even within a single tumor, marked variations in imaging features, such as necrosis or contrast enhancement, are common. Similar spatial variations recently have been reported in genetic profiles. Radiologic heterogeneity within tumors is usually governed by variations in blood flow, whereas genetic heterogeneity is typically ascribed to random mutations. However, evolution within tumors, as in all living systems, is subject to Darwinian principles; thus, it is governed by predictable and reproducible interactions between environmental selection forces and cell phenotype (not genotype). This link between regional variations in environmental properties and cellular adaptive strategies may permit clinical imaging to be used to assess and monitor intratumoral evolution in individual patients. This approach is enabled by new methods that extract, report, and analyze quantitative, reproducible, and mineable clinical imaging data. However, most current quantitative metrics lack spatialness, expressing quantitative radiologic features as a single value for a region of interest encompassing the whole tumor. In contrast, spatially explicit image analysis recognizes that tumors are heterogeneous but not well mixed and defines regionally distinct habitats, some of which appear to harbor tumor populations that are more aggressive and less treatable than others. By identifying regional variations in key environmental selection forces and evidence of cellular adaptation, clinical imaging can enable us to define intratumoral Darwinian dynamics before and during therapy. Advances in image analysis will place clinical imaging in an increasingly central role in the development of evolution-based patient-specific cancer therapy. © RSNA, 2013 PMID:24062559
Łopata, Michał; Popielarczyk, Dariusz; Templin, Tomasz; Dunalska, Julita; Wiśniewski, Grzegorz; Bigaj, Izabela; Szymański, Daniel
2014-01-01
We investigated changes in the spatial distribution of phosphorus (P) and nitrogen (N) in the deep, mesotrophic Lake Hańcza. The raw data collection, supported by global navigation satellite system (GNSS) positioning, was conducted on 79 sampling points. A geostatistical method (kriging) was applied in spatial interpolation. Despite the relatively small area of the lake (3.04 km(2)), compact shape (shore development index of 2.04) and low horizontal exchange of water (retention time 11.4 years), chemical gradients in the surface waters were found. The largest variation concerns the main biogenic element - phosphorus. The average value was 0.032 at the extreme values of 0.019 to 0.265 mg L(-1) (coefficient of variation 87%). Smaller differences are related to nitrogen compounds (0.452-1.424 mg L(-1) with an average value of 0.583 mg L(-1), the coefficient of variation 20%). The parts of the lake which are fed with tributaries are the richest in phosphorus. The water quality of the oligo-mesotrophic Lake Hańcza has been deteriorating in recent years. Our results indicate that inferences about trends in the evolution of examined lake trophic status should be based on an analysis of the data, taking into account the local variation in water chemistry.
Poster 12: Nitrile and Hydrocarbon Spatial Abundance Variations in Titan's Atmosphere
NASA Astrophysics Data System (ADS)
Thelen, Alexander E.; Nixon, Conor A.; Molter, Edward; Serigano, Joseph; Cordiner, Martin A.; Charnley, Steven B.; Teanby, Nick; Chanover, Nancy
2016-06-01
Many minor constituents of Titan's atmosphere exhibit latitudinal variations in abundance as a result of atmospheric circulation, photochemical production and subsequent destruction throughout Titan's seasonal cycle [1,2]. Species with observed spatial abundance variations include hydrocarbons - such as CH3CCH - and nitriles - HCN, HC3N, CH3CN, and C2H5CN - as found by Cassini [3,4]. Recent calibration images of Titan taken by the Atacama Large Millimeter/Submillimeter Array (ALMA) allow for measurements of rotational transition lines of these species in spatially resolved regions of Titan's disk [5]. Abundance profiles in Titan's lower/middle atmosphere are retrieved by modeling high resolution ALMA spectra using the Non-linear Optimal Estimator for MultivariatE Spectral analySIS (NEMESIS) radiative transfer code [6]. We present continuous abundance profiles for various species in Titan's atmosphere obtained from ALMA data in 2014. These species show polar abundance enhancements which can be compared to studies using Cassini data [7]. Measurements in the mesosphere will constrain molecular photochemical and dynamical models, while temporal variations inform our knowledge of chemical lifetimes for the large inventory of organic species produced in Titan's atmosphere. The synthesis of the ALMA and Cassini datasets thus allow us to observe the important changes in production and circulation of numerous trace components of Titan's atmosphere, which are attributed to Titan's seasons.
Liu, Yu; Gao, Peng; Zhang, Liyong; Niu, Xiang; Wang, Bing
2016-10-01
Soil total nitrogen (STN) and total phosphorus (STP) are important indicators of soil nutrients and the important indexes of soil fertility and soil quality evaluation. Using geographic information system (GIS) and geostatistics, the spatial heterogeneity distribution of STN and STP in the Yaoxiang watershed in a hilly area of northern China was studied. The results showed that: (1) The STN and STP contents showed a declining trend with the increase in soil depth; the variation coefficients ( C v ) of STN and STP in the 0- to 10-cm soil layer (42.25% and 14.77%, respectively) were higher than in the 10- to 30-cm soil layer (28.77% and 11.60%, respectively). Moreover, the C v of STN was higher than that of STP. (2) The maximum C 0 /( C 0 + C 1 ) of STN and STP in the soil layers was less than 25%, this indicated that a strong spatial distribution autocorrelation existed for STN and STP; and the STP showed higher intensity and more stable variation than the STN. (3) From the correlation analysis, we concluded that the topographic indexes such as elevation and slope direction all influenced the spatial distribution of STN and STP (correlation coefficients were 0.688 and 0.518, respectively). (4) The overall distribution of STN and STP in the Yaoxiang watershed decreased from the northwest to the southeast. This variation trend was similar to the watershed DEM trend and was significantly influenced by vegetation and topographic factors. These results revealed the spatial heterogeneity distribution of STN and STP, and addressed the influences of forest vegetation coverage, elevation, and other topographic factors on the spatial distribution of STN and STP at the watershed scale.
Hassan, M Manzurul; Atkins, Peter J
2011-01-01
This article seeks to explore the spatial variability of groundwater arsenic (As) concentrations in Southwestern Bangladesh. Facts about spatial pattern of As are important to understand the complex processes of As concentrations and its spatial predictions in the unsampled areas of the study site. The relevant As data for this study were collected from Southwest Bangladesh and were analyzed with Flow Injection Hydride Generation Atomic Absorption Spectrometry (FI-HG-AAS). A geostatistical analysis with Indicator Kriging (IK) was employed to investigate the regionalized variation of As concentration. The IK prediction map shows a highly uneven spatial pattern of arsenic concentrations. The safe zones are mainly concentrated in the north, central and south part of the study area in a scattered manner, while the contamination zones are found to be concentrated in the west and northeast parts of the study area. The southwest part of the study area is contaminated with a highly irregular pattern. A Generalized Linear Model (GLM) was also used to investigate the relationship between As concentrations and aquifer depths. A negligible negative correlation between aquifer depth and arsenic concentrations was found in the study area. The fitted value with 95 % confidence interval shows a decreasing tendency of arsenic concentrations with the increase of aquifer depth. The adjusted mean smoothed lowess curve with a bandwidth of 0.8 shows an increasing trend of arsenic concentration up to a depth of 75 m, with some erratic fluctuations and regional variations at the depth between 30 m and 60 m. The borehole lithology was considered to analyze and map the pattern of As variability with aquifer depths. The study has performed an investigation of spatial pattern and variation of As concentrations.
Naish, Suchithra; Dale, Pat; Mackenzie, John S; McBride, John; Mengersen, Kerrie; Tong, Shilu
2014-01-01
Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. We explored spatio-temporal characteristics of locally-acquired dengue cases in northern tropical Queensland, Australia during the period 1993-2012. Locally-acquired notified cases of dengue were collected for northern tropical Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. 2,398 locally-acquired dengue cases were recorded in northern tropical Queensland during the study period. The areas affected by the dengue cases exhibited spatial and temporal variation over the study period. Notified cases of dengue occurred more frequently in autumn. Mapping of dengue by statistical local areas (census units) reveals the presence of substantial spatio-temporal variation over time and place. Statistically significant differences in dengue incidence rates among males and females (with more cases in females) (χ(2) = 15.17, d.f. = 1, p<0.01). Differences were observed among age groups, but these were not statistically significant. There was a significant positive spatial autocorrelation of dengue incidence for the four sub-periods, with the Moran's I statistic ranging from 0.011 to 0.463 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the northern Queensland. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in northern tropical Queensland, Australia. Therefore, this study provides an impetus for further investigation of clusters and risk factors in these high-risk areas.
Naish, Suchithra; Dale, Pat; Mackenzie, John S.; McBride, John; Mengersen, Kerrie; Tong, Shilu
2014-01-01
Background Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992–1993. We explored spatio-temporal characteristics of locally-acquired dengue cases in northern tropical Queensland, Australia during the period 1993–2012. Methods Locally-acquired notified cases of dengue were collected for northern tropical Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Results 2,398 locally-acquired dengue cases were recorded in northern tropical Queensland during the study period. The areas affected by the dengue cases exhibited spatial and temporal variation over the study period. Notified cases of dengue occurred more frequently in autumn. Mapping of dengue by statistical local areas (census units) reveals the presence of substantial spatio-temporal variation over time and place. Statistically significant differences in dengue incidence rates among males and females (with more cases in females) (χ2 = 15.17, d.f. = 1, p<0.01). Differences were observed among age groups, but these were not statistically significant. There was a significant positive spatial autocorrelation of dengue incidence for the four sub-periods, with the Moran's I statistic ranging from 0.011 to 0.463 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the northern Queensland. Conclusions Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in northern tropical Queensland, Australia. Therefore, this study provides an impetus for further investigation of clusters and risk factors in these high-risk areas. PMID:24691549
Temperature induced distortions in space telescope mirrors
NASA Technical Reports Server (NTRS)
Nied, H. F.; Rudmann, A. A.
1993-01-01
In this paper, it is illustrated how measured instantaneous coefficients of thermal expansion (CTE) can be accurately taken into account when modeling the structural behavior of space based optical systems. In particular, the importance of including CTE spatial variations in the analysis of optical elements is emphasized. A comparison is made between the CTE's of three optical materials commonly used in the construction of space mirrors (ULE, Zerodur, and beryllium). The overall impact that selection of any one of these materials has on thermal distortions is briefly discussed. As an example of how temperature dependent spatial variations in thermal strain can be accurately incorporated in the thermo-structural analysis of a precision optical system, a finite element model is developed, which is used to estimate the thermally induced distortions in the Hubble Space Telescope's (HST) primary mirror. In addition to the structural analysis, the optical aberrations due to thermally induced distortions are also examined. These calculations indicate that thermal distortions in HST's primary mirror contribute mainly to defocus error with a relatively small contribution to spherical aberration.
Zhao, Xuan; Hao, Qi Li; Sun, Ying Ying
2017-06-18
Studies on the spatial heterogeneity of saline soil in the Mu Us Desert-Loess Plateau transition zone are meaningful for understanding the mechanisms of land desertification. Taking the Mu Us Desert-Loess Plateau transition zone as the study subject, its spatial heterogeneity of pH, electrical conductivity (EC) and total salt content were analyzed by using on-site sampling followed with indoor analysis, classical statistical and geostatistical analysis. The results indicated that: 1) The average values of pH, EC and total salt content were 8.44, 5.13 mS·cm -1 and 21.66 g·kg -1 , respectively, and the coefficient of variation ranged from 6.9% to 73.3%. The pH was weakly variable, while EC and total salt content were moderately variable. 2) Results of semivariogram analysis showed that the most fitting model for spatial variability of all three indexes was spherical model. The C 0 /(C 0 +C) ratios of three indexes ranged from 8.6% to 14.3%, which suggested the spatial variability of all indexes had a strong spatial autocorrelation, and the structural factors played a more important role. The variation range decreased in order of pH
Modeling vertebrate diversity in Oregon using satellite imagery
NASA Astrophysics Data System (ADS)
Cablk, Mary Elizabeth
Vertebrate diversity was modeled for the state of Oregon using a parametric approach to regression tree analysis. This exploratory data analysis effectively modeled the non-linear relationships between vertebrate richness and phenology, terrain, and climate. Phenology was derived from time-series NOAA-AVHRR satellite imagery for the year 1992 using two methods: principal component analysis and derivation of EROS data center greenness metrics. These two measures of spatial and temporal vegetation condition incorporated the critical temporal element in this analysis. The first three principal components were shown to contain spatial and temporal information about the landscape and discriminated phenologically distinct regions in Oregon. Principal components 2 and 3, 6 greenness metrics, elevation, slope, aspect, annual precipitation, and annual seasonal temperature difference were investigated as correlates to amphibians, birds, all vertebrates, reptiles, and mammals. Variation explained for each regression tree by taxa were: amphibians (91%), birds (67%), all vertebrates (66%), reptiles (57%), and mammals (55%). Spatial statistics were used to quantify the pattern of each taxa and assess validity of resulting predictions from regression tree models. Regression tree analysis was relatively robust against spatial autocorrelation in the response data and graphical results indicated models were well fit to the data.
NASA Astrophysics Data System (ADS)
Sun, Cheng; Li, Jianping; Kucharski, Fred; Xue, Jiaqing; Li, Xiang
2018-04-01
The spatial structure of Atlantic multidecadal oscillation (AMO) is analyzed and compared between the observations and simulations from slab ocean models (SOMs) and fully coupled models. The observed sea surface temperature (SST) pattern of AMO is characterized by a basin-wide monopole structure, and there is a significantly high degree of spatial coherence of decadal SST variations across the entire North Atlantic basin. The observed SST anomalies share a common decadal-scale signal, corresponding to the basin-wide average (i. e., the AMO). In contrast, the simulated AMO in SOMs (AMOs) exhibits a tripole-like structure, with the mid-latitude North Atlantic SST showing an inverse relationship with other parts of the basin, and the SOMs fail to reproduce the observed strong spatial coherence of decadal SST variations associated with the AMO. The observed spatial coherence of AMO SST anomalies is identified as a key feature that can be used to distinguish the AMO mechanism. The tripole-like SST pattern of AMOs in SOMs can be largely explained by the atmosphere-forced thermodynamics mechanism due to the surface heat flux changes associated with the North Atlantic Oscillation (NAO). The thermodynamic forcing of AMOs by the NAO gives rise to a simultaneous inverse NAO-AMOs relationship at both interannual and decadal timescales and a seasonal phase locking of the AMOs variability to the cold season. However, the NAO-forced thermodynamics mechanism cannot explain the observed NAO-AMO relationship and the seasonal phase locking of observed AMO variability to the warm season. At decadal timescales, a strong lagged relationship between NAO and AMO is observed, with the NAO leading by up to two decades, while the simultaneous correlation of NAO with AMO is weak. This lagged relationship and the spatial coherence of AMO can be well understood from the view point of ocean dynamics. A time-integrated NAO index, which reflects the variations in Atlantic meridional overturning circulation (AMOC) and northward ocean heat transport caused by the accumulated effect of NAO forcing, reasonably well captures the observed multidecadal fluctuations in the AMO. Further analysis using the fully coupled model simulations provides direct modeling evidence that the observed spatial coherence of decadal SST variations across North Atlantic basin can be reproduced only by including the AMOC-related ocean dynamics, and the AMOC acts as a common forcing signal that results in a spatially coherent variation of North Atlantic SST.
NASA Astrophysics Data System (ADS)
Ward, John; Kaczan, David
2014-11-01
Water poverty in the Niger River Basin is a function of physical constraints affecting access and supply, and institutional arrangements affecting the ability to utilise the water resource. This distinction reflects the complexity of water poverty and points to the need to look beyond technical and financial means alone to reduce its prevalence and severity. Policy decisions affecting water resources are generally made at a state or national level. Hydrological and socio-economic evaluations at these levels, or at the basin level, cannot be presumed to be concordant with the differentiation of poverty or livelihood vulnerability at more local levels. We focus on three objectives: first, the initial mapping of observed poverty, using two health metrics and a household assets metric; second, the estimation of factors which potentially influence the observed poverty patterns; and third, a consideration of spatial non-stationarity, which identifies spatial correlates of poverty in the places where their effects appear most severe. We quantify the extent to which different levels of analysis influence these results. Comparative analysis of correlates of poverty at basin, national and local levels shows limited congruence. Variation in water quantity, and the presence of irrigation and dams had either limited or no significant correlation with observed variation in poverty measures across levels. Education and access to improved water quality were the only variables consistently significant and spatially stable across the entire basin. At all levels, education is the most consistent non-water correlate of poverty while access to protected water sources is the strongest water related correlate. The analysis indicates that landscape and scale matter for understanding water-poverty linkages and for devising policy concerned with alleviating water poverty. Interactions between environmental, social and institutional factors are complex and consequently a comprehensive understanding of poverty and its causes requires analysis at multiple spatial resolutions.
Wang, Quan; Wu, Xianhua; Zhao, Bin; Qin, Jie; Peng, Tingchun
2015-01-01
Understanding spatial and temporal variations in river water quality and quantitatively evaluating the trend of changes are important in order to study and efficiently manage water resources. In this study, an analysis of Water Pollution Index (WPI), Daniel Trend Test, Cluster Analysis and Discriminant Analysis are applied as an integrated approach to quantitatively explore the spatial and temporal variations and the latent sources of water pollution in the Shanchong River basin, Northwest Basin of Lake Fuxian, China. We group all field surveys into 2 clusters (dry season and rainy season). Moreover, 14 sampling sites have been grouped into 3 clusters for the rainy season (highly polluted, moderately polluted and less polluted sites) and 2 clusters for the dry season (highly polluted and less polluted sites) based on their similarities and the level of pollution during the two seasons. The results show that the main trend of pollution was aggravated during the transition from the dry to the rainy season. The Water Pollution Index of Total Nitrogen is the highest of all pollution parameters, whereas the Chemical Oxygen Demand (Chromium) is the lowest. Our results also show that the main sources of pollution are farming activities alongside the Shanchong River, soil erosion and fish culture at Shanchong River reservoir area and domestic sewage from scattered rural residential area. Our results suggest that strategies to prevent water pollutionat the Shanchong River basin need to focus on non-point pollution control by employing appropriate fertilizer formulas in farming, and take the measures of soil and water conservation at Shanchong reservoir area, and purifying sewage from scattered villages.
Wang, Quan; Wu, Xianhua; Zhao, Bin; Qin, Jie; Peng, Tingchun
2015-01-01
Understanding spatial and temporal variations in river water quality and quantitatively evaluating the trend of changes are important in order to study and efficiently manage water resources. In this study, an analysis of Water Pollution Index (WPI), Daniel Trend Test, Cluster Analysis and Discriminant Analysis are applied as an integrated approach to quantitatively explore the spatial and temporal variations and the latent sources of water pollution in the Shanchong River basin, Northwest Basin of Lake Fuxian, China. We group all field surveys into 2 clusters (dry season and rainy season). Moreover, 14 sampling sites have been grouped into 3 clusters for the rainy season (highly polluted, moderately polluted and less polluted sites) and 2 clusters for the dry season (highly polluted and less polluted sites) based on their similarities and the level of pollution during the two seasons. The results show that the main trend of pollution was aggravated during the transition from the dry to the rainy season. The Water Pollution Index of Total Nitrogen is the highest of all pollution parameters, whereas the Chemical Oxygen Demand (Chromium) is the lowest. Our results also show that the main sources of pollution are farming activities alongside the Shanchong River, soil erosion and fish culture at Shanchong River reservoir area and domestic sewage from scattered rural residential area. Our results suggest that strategies to prevent water pollutionat the Shanchong River basin need to focus on non-point pollution control by employing appropriate fertilizer formulas in farming, and take the measures of soil and water conservation at Shanchong reservoir area, and purifying sewage from scattered villages. PMID:25837673
Spatio-temporal analysis of annual rainfall in Crete, Greece
NASA Astrophysics Data System (ADS)
Varouchakis, Emmanouil A.; Corzo, Gerald A.; Karatzas, George P.; Kotsopoulou, Anastasia
2018-03-01
Analysis of rainfall data from the island of Crete, Greece was performed to identify key hydrological years and return periods as well as to analyze the inter-annual behavior of the rainfall variability during the period 1981-2014. The rainfall spatial distribution was also examined in detail to identify vulnerable areas of the island. Data analysis using statistical tools and spectral analysis were applied to investigate and interpret the temporal course of the available rainfall data set. In addition, spatial analysis techniques were applied and compared to determine the rainfall spatial distribution on the island of Crete. The analysis presented that in contrast to Regional Climate Model estimations, rainfall rates have not decreased, while return periods vary depending on seasonality and geographic location. A small but statistical significant increasing trend was detected in the inter-annual rainfall variations as well as a significant rainfall cycle almost every 8 years. In addition, statistically significant correlation of the island's rainfall variability with the North Atlantic Oscillation is identified for the examined period. On the other hand, regression kriging method combining surface elevation as secondary information improved the estimation of the annual rainfall spatial variability on the island of Crete by 70% compared to ordinary kriging. The rainfall spatial and temporal trends on the island of Crete have variable characteristics that depend on the geographical area and on the hydrological period.
Analysis of Co-spatial UV-Optical STIS Spectra of Seven Planetary Nebulae From HST Cycle 19 GO 12600
NASA Astrophysics Data System (ADS)
Miller, Timothy R.; Henry, Richard B. C.; Dufour, Reginald J.; Kwitter, Karen B.; Shaw, Richard A.; Balick, Bruce; Corradi, Romano
2016-01-01
We present an analysis of seven spatially resolved planetary nebulae (PNe), NGC 2440, NGC 3242, NGC 5315, NGC 5882, NGC 7662, IC 2165, and IC 3568, from observations in the Cycle 19 program GO 12600 using HST STIS. These seven observations cover the wavelength range 1150-10,270 Å with 0.2 and 0.5 arcsec wide slits, and are co-spatial to within 0.1 arcsec along a 25 arcsec length across each nebula. The wavelength and spatial coverage enabled a detailed study of physical conditions and abundances from UV and optical line emissions (compared to only optical lines) for these seven PNe. The first UV lines of interest are those of carbon. The resolved lines of C III] 1906.68 and 1908.73 yielded a direct measurement of the density within the volume occupied by doubly-ionized carbon and other similar co-spatial ions as well as contributed to an accurate measurement of the carbon abundance. Each PN spectrum was divided into smaller spatial regions or segments in order to assess inferred density variations among the regions along the entire slit. There is a clear difference in the inferred density for several regions of each PNe. Variations in electron temperature and chemical abundances were also probed and shown to be completely homogeneous within the errors. Lastly, these nebulae were modeled in detail with the photoionization code CLOUDY. This modeling constrained the central star parameters of temperature and luminosity and tested the effects different density profiles have on these parameters. We gratefully acknowledge generous support from NASA through grants related to the Cycle 19 program GO 12600, as well as from the University of Oklahoma.
Bauerle, William L.; Bowden, Joseph D.
2011-01-01
A spatially explicit mechanistic model, MAESTRA, was used to separate key parameters affecting transpiration to provide insights into the most influential parameters for accurate predictions of within-crown and within-canopy transpiration. Once validated among Acer rubrum L. genotypes, model responses to different parameterization scenarios were scaled up to stand transpiration (expressed per unit leaf area) to assess how transpiration might be affected by the spatial distribution of foliage properties. For example, when physiological differences were accounted for, differences in leaf width among A. rubrum L. genotypes resulted in a 25% difference in transpiration. An in silico within-canopy sensitivity analysis was conducted over the range of genotype parameter variation observed and under different climate forcing conditions. The analysis revealed that seven of 16 leaf traits had a ≥5% impact on transpiration predictions. Under sparse foliage conditions, comparisons of the present findings with previous studies were in agreement that parameters such as the maximum Rubisco-limited rate of photosynthesis can explain ∼20% of the variability in predicted transpiration. However, the spatial analysis shows how such parameters can decrease or change in importance below the uppermost canopy layer. Alternatively, model sensitivity to leaf width and minimum stomatal conductance was continuous along a vertical canopy depth profile. Foremost, transpiration sensitivity to an observed range of morphological and physiological parameters is examined and the spatial sensitivity of transpiration model predictions to vertical variations in microclimate and foliage density is identified to reduce the uncertainty of current transpiration predictions. PMID:21617246
Tunno, Brett J; Dalton, Rebecca; Michanowicz, Drew R; Shmool, Jessie L C; Kinnee, Ellen; Tripathy, Sheila; Cambal, Leah; Clougherty, Jane E
2016-01-01
Health effects of fine particulate matter (PM2.5) vary by chemical composition, and composition can help to identify key PM2.5 sources across urban areas. Further, this intra-urban spatial variation in concentrations and composition may vary with meteorological conditions (e.g., mixing height). Accordingly, we hypothesized that spatial sampling during atmospheric inversions would help to better identify localized source effects, and reveal more distinct spatial patterns in key constituents. We designed a 2-year monitoring campaign to capture fine-scale intra-urban variability in PM2.5 composition across Pittsburgh, PA, and compared both spatial patterns and source effects during “frequent inversion” hours vs 24-h weeklong averages. Using spatially distributed programmable monitors, and a geographic information systems (GIS)-based design, we collected PM2.5 samples across 37 sampling locations per year to capture variation in local pollution sources (e.g., proximity to industry, traffic density) and terrain (e.g., elevation). We used inductively coupled plasma mass spectrometry (ICP-MS) to determine elemental composition, and unconstrained factor analysis to identify source suites by sampling scheme and season. We examined spatial patterning in source factors using land use regression (LUR), wherein GIS-based source indicators served to corroborate factor interpretations. Under both summer sampling regimes, and for winter inversion-focused sampling, we identified six source factors, characterized by tracers associated with brake and tire wear, steel-making, soil and road dust, coal, diesel exhaust, and vehicular emissions. For winter 24-h samples, four factors suggested traffic/fuel oil, traffic emissions, coal/industry, and steel-making sources. In LURs, as hypothesized, GIS-based source terms better explained spatial variability in inversion-focused samples, including a greater contribution from roadway, steel, and coal-related sources. Factor analysis produced source-related constituent suites under both sampling designs, though factors were more distinct under inversion-focused sampling. PMID:26507005
NASA Astrophysics Data System (ADS)
Wang, Yang; Zhao, Chuanfeng
2016-04-01
Clouds play essential roles in the Earth's energy and water cycle, and Cloud Fraction (CF) is one of the most important cloud parameters. The CF from Moderate Resolution Imaging Spectroradiometer (MODIS) has been widely used, whereas the time representation of these instantaneous CF values is not clear. In this study, we evaluate MODIS-derived CF by using continuous, day-and-night radar/lidar CF from the Atmospheric Radiation Measurement (ARM) program Active Remote Sensing of CLouds (ARSCL) product and the total sky cover (TSC) day-time CF datasets. Inter-comparisons between MODIS and surface CFs for time period from 2000 to 2011 are performed for three climate regimes as represented by the ARM sites of Southern Great Plains (SGP), Manus, Papua New Guinea (PNG) and North Slope of Alaska (NSA). We first choose both the TSC and ARSCL CFs averaged over 1 hour around the two passing time of satellite, which are around 10:30 AM and 1:30 PM local time. Then two kind of analyses have been done. One is the spatial variation analysis and the other is temporal variation analysis. For the spatial variation analysis, we compare the 1-hour averaged cloud fractions from TSC and ARSCL around 10:30 AM and 1:30 PM with the instantaneous cloud fractions from MODIS but with different spatial resolution. By obtaining the RMS errors and ratio of average values of CFs for these inter-comparisons, the optimal CF-matching spatial resolutions for MODIS regarding to TSC and ARSCL are obtained which are both 30 km radius of circle. We also find that the optimal matching spatial resolution increases when the ground observation average time increases. For the temporal analysis, we first analyze the diurnal variation of the cloud fraction based on the surface CFs from TSC and ARSCL from which we can see the daily representation of cloud fraction observed at 10:30 AM and 1:30 PM. Then we make a statistical comparison of daily and monthly cloud fraction between using all time observation and using the 1-hour averaged observations at both 10:30 AM and 1:30 PM. Comparison results will be shown in our paper. It shows a high correlation coefficient of 0.95 (0.93) for observations from TSC (ARSCL). The ratios of daily (monthly) averaged cloud fraction between using all time and using the time satellite passes are 0.87(0.92) and 0.86(0.97) for TSC and ARSCL, respectively. This suggests that considerable errors could be introduced while using the cloud fraction at two fixed time points (10:30 AM and 1:30 PM) to represent the daily cloud fraction.
NASA Astrophysics Data System (ADS)
Smith, K.; Tape, C.; Bruton, C. P.; West, M. E.
2016-12-01
Continuous seismic recordings-or ambient noise-provide means for time-dependent monitoring of site conditions. Frequency-domain amplitude spectra of seismic recordings can be used to characterize time-dependent variations as a function of period (or frequency). Spatial variations can be characterized by using a set of stations across a large region. We analyze time-dependent ambient noise spectra from stations across central Alaska with three purposes. First, we are interested in monitoring the station performance and quality of a new array (FLATS) of 13 posthole seismometers near the Tanana River in Minto Flats. Second, we want to understand time-dependent threshold levels for earthquake detection: when noise is high, earthquake detections are low. Third, we are interested in identifying the effects of nature and Earth structure on seismic stations at different spatial-temporal scales. Our results show that seismic stations are sensitive to variations in wind speed and river flow. Correlations between wind speed and long-period (>10 seconds) seismic noise variations are probably due to tilt effects that have been previously documented. We identify a seismic signal at 10 Hz that is present only on stations close (<100 m) to the main channel of the Tanana river. The 10-Hz signal is strongly correlated with river gage height during summer and weakly correlated during the winter, when the river surface is covered in 1 m of ice. Spatial correlations among stations reveal large variations at shorter time scales (days); these could be due to weather anomalies. The amplitude of seismic noise at periods 2-10 s is strongly influenced by the thickness of sediment, which ranges from 0 m at bedrock sites to 6000 m at sites in the deepest part of Nenana basin. Our analysis allows us to better monitor the performance of temporary and permanent seismic stations, and to understand the physical causes of time-dependent noise variations in Alaska. Our findings show that seismic stations near rivers can potentially be used to monitor the flow of the river during summer and during ice-covered winter, raising the possibility for monitoring river ice break-up during April.
NASA Astrophysics Data System (ADS)
Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan
2018-05-01
Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.
Geostatistics and spatial analysis in biological anthropology.
Relethford, John H
2008-05-01
A variety of methods have been used to make evolutionary inferences based on the spatial distribution of biological data, including reconstructing population history and detection of the geographic pattern of natural selection. This article provides an examination of geostatistical analysis, a method used widely in geology but which has not often been applied in biological anthropology. Geostatistical analysis begins with the examination of a variogram, a plot showing the relationship between a biological distance measure and the geographic distance between data points and which provides information on the extent and pattern of spatial correlation. The results of variogram analysis are used for interpolating values of unknown data points in order to construct a contour map, a process known as kriging. The methods of geostatistical analysis and discussion of potential problems are applied to a large data set of anthropometric measures for 197 populations in Ireland. The geostatistical analysis reveals two major sources of spatial variation. One pattern, seen for overall body and craniofacial size, shows an east-west cline most likely reflecting the combined effects of past population dispersal and settlement. The second pattern is seen for craniofacial height and shows an isolation by distance pattern reflecting rapid spatial changes in the midlands region of Ireland, perhaps attributable to the genetic impact of the Vikings. The correspondence of these results with other analyses of these data and the additional insights generated from variogram analysis and kriging illustrate the potential utility of geostatistical analysis in biological anthropology. (c) 2008 Wiley-Liss, Inc.
Spatial-temporal analysis of building surface temperatures in Hung Hom
NASA Astrophysics Data System (ADS)
Zeng, Ying; Shen, Yueqian
2015-12-01
This thesis presents a study on spatial-temporal analysis of building surface temperatures in Hung Hom. Observations were collected from Aug 2013 to Oct 2013 at a 30-min interval, using iButton sensors (N=20) covering twelve locations in Hung Hom. And thermal images were captured in PolyU from 05 Aug 2013 to 06 Aug 2013. A linear regression model of iButton and thermal records is established to calibrate temperature data. A 3D modeling system is developed based on Visual Studio 2010 development platform, using ArcEngine10.0 component, Microsoft Access 2010 database and C# programming language. The system realizes processing data, spatial analysis, compound query and 3D face temperature rendering and so on. After statistical analyses, building face azimuths are found to have a statistically significant relationship with sun azimuths at peak time. And seasonal building temperature changing also corresponds to the sun angle and sun azimuth variations. Building materials are found to have a significant effect on building surface temperatures. Buildings with lower albedo materials tend to have higher temperatures and larger thermal conductivity material have significant diurnal variations. For the geographical locations, the peripheral faces of campus have higher temperatures than the inner faces during day time and buildings located at the southeast are cooler than the western. Furthermore, human activity is found to have a strong relationship with building surface temperatures through weekday and weekend comparison.
Influence of land use on water quality in a tropical landscape: a multi-scale analysis
Yackulic, Charles B.; Lim, Yili; Arce-Nazario, Javier A.
2015-01-01
There is a pressing need to understand the consequences of human activities, such as land transformations, on watershed ecosystem services. This is a challenging task because different indicators of water quality and yield are expected to vary in their responsiveness to large versus local-scale heterogeneity in land use and land cover (LUC). Here we rely on water quality data collected between 1977 and 2000 from dozens of gauge stations in Puerto Rico together with precipitation data and land cover maps to (1) quantify impacts of spatial heterogeneity in LUC on several water quality indicators; (2) determine the spatial scale at which this heterogeneity influences water quality; and (3) examine how antecedent precipitation modulates these impacts. Our models explained 30–58% of observed variance in water quality metrics. Temporal variation in antecedent precipitation and changes in LUC between measurements periods rather than spatial variation in LUC accounted for the majority of variation in water quality. Urbanization and pasture development generally degraded water quality while agriculture and secondary forest re-growth had mixed impacts. The spatial scale over which LUC influenced water quality differed across indicators. Turbidity and dissolved oxygen (DO) responded to LUC in large-scale watersheds, in-stream nitrogen concentrations to LUC in riparian buffers of large watersheds, and fecal matter content and in-stream phosphorus concentration to LUC at the sub-watershed scale. Stream discharge modulated impacts of LUC on water quality for most of the metrics. Our findings highlight the importance of considering multiple spatial scales for understanding the impacts of human activities on watershed ecosystem services. PMID:26146455
Manzano-León, Natalia; Quintana, Raúl; Sánchez, Brisa; Serrano, Jesús; Vega, Elizabeth; Vázquez-López, Inés; Rojas-Bracho, Leonora; López-Villegas, Tania; O’Neill, Marie S.; Vadillo-Ortega, Felipe; De Vizcaya-Ruiz, Andrea; Rosas, Irma
2015-01-01
Spatial variation in particulate matter–related health and toxicological outcomes is partly due to its composition. We studied spatial variability in particle composition and induced cellular responses in Mexico City to complement an ongoing epidemiologic study. We measured elements, endotoxins, and polycyclic aromatic hydrocarbons in two particle size fractions collected in five sites. We compared the in vitro proinflammatory response of J774A.1 and THP-1 cells after exposure to particles, measuring subsequent TNFα and IL-6 secretion. Particle composition varied by site and size. Particle constituents were subjected to principal component analysis, identifying three components: C1 (Si, Sr, Mg, Ca, Al, Fe, Mn, endotoxin), C2 (polycyclic aromatic hydrocarbons), and C3 (Zn, S, Sb, Ni, Cu, Pb). Induced TNFα levels were higher and more heterogeneous than IL-6 levels. Cytokines produced by both cell lines only correlated with C1, suggesting that constituents associated with soil induced the inflammatory response and explain observed spatial differences. PMID:23335408
Spatial and temporal characterizations of water quality in Kuwait Bay.
Al-Mutairi, N; Abahussain, A; El-Battay, A
2014-06-15
The spatial and temporal patterns of water quality in Kuwait Bay have been investigated using data from six stations between 2009 and 2011. The results showed that most of water quality parameters such as phosphorus (PO4), nitrate (NO3), dissolved oxygen (DO), and Total Suspended Solids (TSS) fluctuated over time and space. Based on Water Quality Index (WQI) data, six stations were significantly clustered into two main classes using cluster analysis, one group located in western side of the Bay, and other in eastern side. Three principal components are responsible for water quality variations in the Bay. The first component included DO and pH. The second included PO4, TSS and NO3, and the last component contained seawater temperature and turbidity. The spatial and temporal patterns of water quality in Kuwait Bay are mainly controlled by seasonal variations and discharges from point sources of pollution along Kuwait Bay's coast as well as from Shatt Al-Arab River. Copyright © 2014 Elsevier Ltd. All rights reserved.
Kihal-Talantikite, Wahida; Deguen, Séverine; Padilla, Cindy; Siebert, Muriel; Couchoud, Cécile; Vigneau, Cécile; Bayat, Sahar
2015-02-01
Several studies have investigated the implication of biological and environmental factors on geographic variations of end-stage renal disease (ESRD) incidence at large area scales, but none of them assessed the implication of neighbourhood characteristics (healthcare supply, socio-economic level and urbanization degree) on spatial repartition of ESRD. We evaluated the spatial implications of adjustment for neighbourhood characteristics on the spatial distribution of ESRD incidence at the smallest geographic unit in France. All adult patients living in Bretagne and beginning renal replacement therapy during the 2004-09 period were included. Their residential address was geocoded at the census block level. Each census block was characterized by socio-economic deprivation index, healthcare supply and rural/urban typology. Using a spatial scan statistic, we examined whether there were significant clusters of high risk of ESRD incidence. The ESRD incidence was non-randomly spatially distributed, with a cluster of high risk in the western Bretagne region (relative risk, RR = 1.28, P-value = 0.0003). Adjustment for sex, age and neighbourhood characteristics induced cluster shifts. After these adjustments, a significant cluster (P = 0.013) persisted. Our spatial analysis of ESRD incidence at a fine scale, across a mixed rural/urban area, indicated that, beyond age and sex, neighbourhood characteristics explained a great part of spatial distribution of ESRD incidence. However, to better understand spatial variation of ESRD incidence, it would be necessary to research and adjust for other determinants of ESRD.
Khan, Diba; Rossen, Lauren M; Hamilton, Brady E; He, Yulei; Wei, Rong; Dienes, Erin
2017-06-01
Teen birth rates have evidenced a significant decline in the United States over the past few decades. Most of the states in the US have mirrored this national decline, though some reports have illustrated substantial variation in the magnitude of these decreases across the U.S. Importantly, geographic variation at the county level has largely not been explored. We used National Vital Statistics Births data and Hierarchical Bayesian space-time interaction models to produce smoothed estimates of teen birth rates at the county level from 2003-2012. Results indicate that teen birth rates show evidence of clustering, where hot and cold spots occur, and identify spatial outliers. Findings from this analysis may help inform efforts targeting the prevention efforts by illustrating how geographic patterns of teen birth rates have changed over the past decade and where clusters of high or low teen birth rates are evident. Published by Elsevier Ltd.
Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003–2012
Khan, Diba; Rossen, Lauren M.; Hamilton, Brady E.; He, Yulei; Wei, Rong; Dienes, Erin
2017-01-01
Teen birth rates have evidenced a significant decline in the United States over the past few decades. Most of the states in the US have mirrored this national decline, though some reports have illustrated substantial variation in the magnitude of these decreases across the U.S. Importantly, geographic variation at the county level has largely not been explored. We used National Vital Statistics Births data and Hierarchical Bayesian space-time interaction models to produce smoothed estimates of teen birth rates at the county level from 2003–2012. Results indicate that teen birth rates show evidence of clustering, where hot and cold spots occur, and identify spatial outliers. Findings from this analysis may help inform efforts targeting the prevention efforts by illustrating how geographic patterns of teen birth rates have changed over the past decade and where clusters of high or low teen birth rates are evident. PMID:28552189
Strecker, Angela L; Casselman, John M; Fortin, Marie-Josée; Jackson, Donald A; Ridgway, Mark S; Abrams, Peter A; Shuter, Brian J
2011-07-01
Species present in communities are affected by the prevailing environmental conditions, and the traits that these species display may be sensitive indicators of community responses to environmental change. However, interpretation of community responses may be confounded by environmental variation at different spatial scales. Using a hierarchical approach, we assessed the spatial and temporal variation of traits in coastal fish communities in Lake Huron over a 5-year time period (2001-2005) in response to biotic and abiotic environmental factors. The association of environmental and spatial variables with trophic, life-history, and thermal traits at two spatial scales (regional basin-scale, local site-scale) was quantified using multivariate statistics and variation partitioning. We defined these two scales (regional, local) on which to measure variation and then applied this measurement framework identically in all 5 study years. With this framework, we found that there was no change in the spatial scales of fish community traits over the course of the study, although there were small inter-annual shifts in the importance of regional basin- and local site-scale variables in determining community trait composition (e.g., life-history, trophic, and thermal). The overriding effects of regional-scale variables may be related to inter-annual variation in average summer temperature. Additionally, drivers of fish community traits were highly variable among study years, with some years dominated by environmental variation and others dominated by spatially structured variation. The influence of spatial factors on trait composition was dynamic, which suggests that spatial patterns in fish communities over large landscapes are transient. Air temperature and vegetation were significant variables in most years, underscoring the importance of future climate change and shoreline development as drivers of fish community structure. Overall, a trait-based hierarchical framework may be a useful conservation tool, as it highlights the multi-scaled interactive effect of variables over a large landscape.
Andrus, J Malia; Porter, Matthew D; Rodríguez, Luis F; Kuehlhorn, Timothy; Cooke, Richard A C; Zhang, Yuanhui; Kent, Angela D; Zilles, Julie L
2014-02-01
Denitrifying biofilters can remove agricultural nitrates from subsurface drainage, reducing nitrate pollution that contributes to coastal hypoxic zones. The performance and reliability of natural and engineered systems dependent upon microbially mediated processes, such as the denitrifying biofilters, can be affected by the spatial structure of their microbial communities. Furthermore, our understanding of the relationship between microbial community composition and function is influenced by the spatial distribution of samples.In this study we characterized the spatial structure of bacterial communities in a denitrifying biofilter in central Illinois. Bacterial communities were assessed using automated ribosomal intergenic spacer analysis for bacteria and terminal restriction fragment length polymorphism of nosZ for denitrifying bacteria.Non-metric multidimensional scaling and analysis of similarity (ANOSIM) analyses indicated that bacteria showed statistically significant spatial structure by depth and transect,while denitrifying bacteria did not exhibit significant spatial structure. For determination of spatial patterns, we developed a package of automated functions for the R statistical environment that allows directional analysis of microbial community composition data using either ANOSIM or Mantel statistics.Applying this package to the biofilter data, the flow path correlation range for the bacterial community was 6.4 m at the shallower, periodically in undated depth and 10.7 m at the deeper, continually submerged depth. These spatial structures suggest a strong influence of hydrology on the microbial community composition in these denitrifying biofilters. Understanding such spatial structure can also guide optimal sample collection strategies for microbial community analyses.
Blankena, Roos; Kleinloog, Rachel; Verweij, Bon H.; van Ooij, Pim; ten Haken, Bennie; Luijten, Peter R.; Rinkel, Gabriel J.E.; Zwanenburg, Jaco J.M.
2016-01-01
Purpose To develop a method for semi-quantitative wall thickness assessment on in vivo 7.0 tesla (7T) MRI images of intracranial aneurysms for studying the relation between apparent aneurysm wall thickness and wall shear stress. Materials and Methods Wall thickness was analyzed in 11 unruptured aneurysms in 9 patients, who underwent 7T MRI with a TSE based vessel wall sequence (0.8 mm isotropic resolution). A custom analysis program determined the in vivo aneurysm wall intensities, which were normalized to signal of nearby brain tissue and were used as measure for apparent wall thickness (AWT). Spatial wall thickness variation was determined as the interquartile range in AWT (the middle 50% of the AWT range). Wall shear stress was determined using phase contrast MRI (0.5 mm isotropic resolution). We performed visual and statistical comparisons (Pearson’s correlation) to study the relation between wall thickness and wall shear stress. Results 3D colored AWT maps of the aneurysms showed spatial AWT variation, which ranged from 0.07 to 0.53, with a mean variation of 0.22 (a variation of 1.0 roughly means a wall thickness variation of one voxel (0.8mm)). In all aneurysms, AWT was inversely related to WSS (mean correlation coefficient −0.35, P<0.05). Conclusions A method was developed to measure the wall thickness semi-quantitatively, using 7T MRI. An inverse correlation between wall shear stress and AWT was determined. In future studies, this non-invasive method can be used to assess spatial wall thickness variation in relation to pathophysiologic processes such as aneurysm growth and –rupture. PMID:26892986
Menéndez, Lumila Paula
2016-11-01
The spatial variation of dental caries in late Holocene southern South American populations will be analyzed using geostatistical methods. The existence of a continuous geographical pattern of dental caries variation will be tested. The author recorded dental caries in 400 individuals, collated this information with published caries data from 666 additional individuals, and calculated a Caries Index. The caries spatial distribution was evaluated by means of 2D maps and scatterplots. Geostatistical analyses were performed by calculating Moran's I, correlograms and a Procrustes analysis. There is a relatively strong latitudinal continuous gradient of dental caries variation, especially in the extremes of the distribution. Moreover, the association between dental caries and geography was relatively high (m 12 = 0.6). Although northern and southern samples had the highest and lowest frequencies of dental caries, respectively, the central ones had the largest variation and had lower rates of caries than expected. The large variation in frequencies of dental caries in populations located in the center of the distribution could be explained by their subsistence strategies, characterized either by the consumption of wild cariogenic plants or cultigens (obtained locally or by exchange), a reliance on fishing, or the incorporation of plants rich in starch rather than carbohydrates. It is suggested that dental caries must be considered a multifactorial disease which results from the interaction of cultural practices and environmental factors. This can change how we understand subsistence strategies as well as how we interpret dental caries rates. Am. J. Hum. Biol., 2016. © 2016 Wiley Periodicals, Inc. Am. J. Hum. Biol. 28:825-836, 2016. © 2016Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Spatially explicit spectral analysis of point clouds and geospatial data
Buscombe, Daniel D.
2015-01-01
The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.
Sparse modeling of spatial environmental variables associated with asthma
Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.
2014-01-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437
Sparse modeling of spatial environmental variables associated with asthma.
Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W
2015-02-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.
Analysis of Co-spatial UV-Optical STIS Spectra of Six Planetary Nebulae From HST Cycle 19 GO 12600
NASA Astrophysics Data System (ADS)
Reid Miller, Timothy; Henry, Richard B. C.; Dufour, Reginald J.; Kwitter, Karen; Shaw, Richard A.; Balick, Bruce; Corradi, Romano
2015-08-01
We present an analysis of six spatially resolved planetary nebulae (PNe), NGC 3242, NGC 5315, NGC5882, NGC 7662, IC 2165, and IC 3568, from observations in the Cycle 19 program GO 12600 using HSTSTIS. These six observations cover the wavelength range 1150-10,270 Å with 0.2 and 0.5 arcsec wideslits, and are co-spatial to 0.1 arcsec along a 25 arcsec length across each nebula. The wavelength andspatial coverage enabled this detailed study of physical conditions and abundances from UV and opticalline emissions (compared to only optical lines) for these six PNe. The first UV lines of interest are thoseof carbon. The resolved lines of C III] 1906.68 and 1908.73 yielded a direct measurement of the densitywithin the volume occupied by doubly-ionized carbon and other similar co-spatial ions as well ascontributed to an accurate measurement of the carbon abundance. Each PN spectrum was divided intosmaller spatial regions in order to assess inferred density variations among the regions along the entireslit. There is a clear difference in the inferred density for several regions of each PNe. Variations inelectron temperature and chemical abundances were also probed and shown to be nearly completelyhomogeneous within the errors. Lastly, these nebulae were modeled in detail with the photoionizationcode CLOUDY. This modeling tested different density profiles in order to reproduce the observed densityvariations and temperature fluctuations, and constrain central star parameters. We gratefullyacknowledge generous support from NASA through grants related to the Cycle 19 program GO 12600, aswell as from the University of Oklahoma.
Power quality analysis based on spatial correlation
NASA Astrophysics Data System (ADS)
Li, Jiangtao; Zhao, Gang; Liu, Haibo; Li, Fenghou; Liu, Xiaoli
2018-03-01
With the industrialization and urbanization, the status of electricity in the production and life is getting higher and higher. So the prediction of power quality is the more potential significance. Traditional power quality analysis methods include: power quality data compression, disturbance event pattern classification, disturbance parameter calculation. Under certain conditions, these methods can predict power quality. This paper analyses the temporal variation of power quality of one provincial power grid in China from time angle. The distribution of power quality was analyzed based on spatial autocorrelation. This paper tries to prove that the research idea of geography is effective for mining the potential information of power quality.
Belley, Rénald; Snelgrove, Paul V R; Archambault, Philippe; Juniper, S Kim
2016-01-01
The upwelling of deep waters from the oxygen minimum zone in the Northeast Pacific from the continental slope to the shelf and into the Salish Sea during spring and summer offers a unique opportunity to study ecosystem functioning in the form of benthic fluxes along natural gradients. Using the ROV ROPOS we collected sediment cores from 10 sites in May and July 2011, and September 2013 to perform shipboard incubations and flux measurements. Specifically, we measured benthic fluxes of oxygen and nutrients to evaluate potential environmental drivers of benthic flux variation and ecosystem functioning along natural gradients of temperature and bottom water dissolved oxygen concentrations. The range of temperature and dissolved oxygen encountered across our study sites allowed us to apply a suite of multivariate analyses rarely used in flux studies to identify bottom water temperature as the primary environmental driver of benthic flux variation and organic matter remineralization. Redundancy analysis revealed that bottom water characteristics (temperature and dissolved oxygen), quality of organic matter (chl a:phaeo and C:N ratios) and sediment characteristics (mean grain size and porosity) explained 51.5% of benthic flux variation. Multivariate analyses identified significant spatial and temporal variation in benthic fluxes, demonstrating key differences between the Northeast Pacific and Salish Sea. Moreover, Northeast Pacific slope fluxes were generally lower than shelf fluxes. Spatial and temporal variation in benthic fluxes in the Salish Sea were driven primarily by differences in temperature and quality of organic matter on the seafloor following phytoplankton blooms. These results demonstrate the utility of multivariate approaches in differentiating among potential drivers of seafloor ecosystem functioning, and indicate that current and future predictive models of organic matter remineralization and ecosystem functioning of soft-muddy shelf and slope seafloor habitats should consider bottom water temperature variation. Bottom temperature has important implications for estimates of seasonal and spatial benthic flux variation, benthic-pelagic coupling, and impacts of predicted ocean warming at high latitudes.
Spatio-temporal analysis of small-area intestinal parasites infections in Ghana.
Osei, F B; Stein, A
2017-09-22
Intestinal parasites infection is a major public health burden in low and middle-income countries. In Ghana, it is amongst the top five morbidities. In order to optimize scarce resources, reliable information on its geographical distribution is needed to guide periodic mass drug administration to populations of high risk. We analyzed district level morbidities of intestinal parasites between 2010 and 2014 using exploratory spatial analysis and geostatistics. We found a significantly positive Moran's Index of spatial autocorrelation for each year, suggesting that adjoining districts have similar risk levels. Using local Moran's Index, we found high-high clusters extending towards the Guinea and Sudan Savannah ecological zones, whereas low-low clusters extended within the semi-deciduous forest and transitional ecological zones. Variograms indicated that local and regional scale risk factors modulate the variation of intestinal parasites. Poisson kriging maps showed smoothed spatially varied distribution of intestinal parasites risk. These emphasize the need for a follow-up investigation into the exact determining factors modulating the observed patterns. The findings also underscored the potential of exploratory spatial analysis and geostatistics as tools for visualizing the spatial distribution of small area intestinal worms infections.
Ownership reform and the changing manufacturing landscape in Chinese cities: The case of Wuxi.
Zhou, Lei; Yang, Shan; Wang, Shuguang; Xiong, Liyang
2017-01-01
Since the economic transition, manufacturing in China has undergone profound changes not only in number of enterprises, but also in ownership structure and intra-urban spatial distribution. Investigating the changing manufacturing landscape from the perspective of ownership structure is critical to a deep understanding of the changing role of market and government in re-shaping manufacturing location behavior. Through a case study of Wuxi, a city experiencing comprehensive ownership reform, this paper presents a detailed analysis of the intra-urban spatial shift of manufacturing, identifies the location discrepancies, and examines the underlying forces responsible for the geographical differentiations. Through zone- and district-based analysis, a distinctive trend of decentralization and suburbanization, as well as an uneven distribution of manufacturing, is unveiled. The results of Location Quotient analysis show that the distribution of manufacturing by ownership exhibits distinctive spatial patterns, which is characterized by a historically-based, market-led, and institutionally-created spatial variation. By employing Hot Spot analysis, the role of development zones in attracting manufacturing enterprises of different ownerships is established. Overall, the location behavior of the diversified manufacturing has been increasingly based on the forces of market since the land marketization began. A proactive role played by local governments has also guided the enterprise location decision through spatial planning and regulatory policies.
Ownership reform and the changing manufacturing landscape in Chinese cities: The case of Wuxi
Zhou, Lei; Yang, Shan; Wang, Shuguang
2017-01-01
Since the economic transition, manufacturing in China has undergone profound changes not only in number of enterprises, but also in ownership structure and intra-urban spatial distribution. Investigating the changing manufacturing landscape from the perspective of ownership structure is critical to a deep understanding of the changing role of market and government in re-shaping manufacturing location behavior. Through a case study of Wuxi, a city experiencing comprehensive ownership reform, this paper presents a detailed analysis of the intra-urban spatial shift of manufacturing, identifies the location discrepancies, and examines the underlying forces responsible for the geographical differentiations. Through zone- and district-based analysis, a distinctive trend of decentralization and suburbanization, as well as an uneven distribution of manufacturing, is unveiled. The results of Location Quotient analysis show that the distribution of manufacturing by ownership exhibits distinctive spatial patterns, which is characterized by a historically-based, market-led, and institutionally-created spatial variation. By employing Hot Spot analysis, the role of development zones in attracting manufacturing enterprises of different ownerships is established. Overall, the location behavior of the diversified manufacturing has been increasingly based on the forces of market since the land marketization began. A proactive role played by local governments has also guided the enterprise location decision through spatial planning and regulatory policies. PMID:28278284
NASA Astrophysics Data System (ADS)
Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan
2018-03-01
GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.
Spatial analysis to identify hotspots of prevalence of schizophrenia.
Moreno, Berta; García-Alonso, Carlos R; Negrín Hernández, Miguel A; Torres-González, Francisco; Salvador-Carulla, Luis
2008-10-01
The geographical distribution of mental health disorders is useful information for epidemiological research and health services planning. To determine the existence of geographical hotspots with a high prevalence of schizophrenia in a mental health area in Spain. The study included 774 patients with schizophrenia who were users of the community mental health care service in the area of South Granada. Spatial analysis (Kernel estimation) and Bayesian relative risks were used to locate potential hotspots. Availability and accessibility were both rated in each zone and spatial algebra was applied to identify hotspots in a particular zone. The age-corrected prevalence rate of schizophrenia was 2.86 per 1,000 population in the South Granada area. Bayesian analysis showed a relative risk varying from 0.43 to 2.33. The area analysed had a non-uniform spatial distribution of schizophrenia, with one main hotspot (zone S2). This zone had poor accessibility to and availability of mental health services. A municipality-based variation exists in the prevalence of schizophrenia and related disorders in the study area. Spatial analysis techniques are useful tools to analyse the heterogeneous distribution of a variable and to explain genetic/environmental factors in hotspots related with a lack of easy availability of and accessibility to adequate health care services.
NASA Astrophysics Data System (ADS)
Ambekar Ramachandra Rao, Raghu; Mehta, Monal R.; Toussaint, Kimani C., Jr.
2010-02-01
We demonstrate the use of Fourier transform-second-harmonic generation (FT-SHG) imaging of collagen fibers as a means of performing quantitative analysis of obtained images of selected spatial regions in porcine trachea, ear, and cornea. Two quantitative markers, preferred orientation and maximum spatial frequency are proposed for differentiating structural information between various spatial regions of interest in the specimens. The ear shows consistent maximum spatial frequency and orientation as also observed in its real-space image. However, there are observable changes in the orientation and minimum feature size of fibers in the trachea indicating a more random organization. Finally, the analysis is applied to a 3D image stack of the cornea. It is shown that the standard deviation of the orientation is sensitive to the randomness in fiber orientation. Regions with variations in the maximum spatial frequency, but with relatively constant orientation, suggest that maximum spatial frequency is useful as an independent quantitative marker. We emphasize that FT-SHG is a simple, yet powerful, tool for extracting information from images that is not obvious in real space. This technique can be used as a quantitative biomarker to assess the structure of collagen fibers that may change due to damage from disease or physical injury.
Bertazzon, Stefania; Shahid, Rizwan
2017-01-01
An exploratory spatial analysis investigates the location of schools in Calgary (Canada) in relation to air pollution and active transportation options. Air pollution exhibits marked spatial variation throughout the city, along with distinct spatial patterns in summer and winter; however, all school locations lie within low to moderate pollution levels. Conversely, the study shows that almost half of the schools lie in low walkability locations; likewise, transitability is low for 60% of schools, and only bikability is widespread, with 93% of schools in very bikable locations. School locations are subsequently categorized by pollution exposure and active transportation options. This analysis identifies and maps schools according to two levels of concern: schools in car-dependent locations and relatively high pollution; and schools in locations conducive of active transportation, yet exposed to relatively high pollution. The findings can be mapped and effectively communicated to the public, health practitioners, and school boards. The study contributes with an explicitly spatial approach to the intra-urban public health literature. Developed for a moderately polluted city, the methods can be extended to more severely polluted environments, to assist in developing spatial public health policies to improve respiratory outcomes, neurodevelopment, and metabolic and attention disorders in school-aged children. PMID:28757577
Malvisi, Lucio; Troisi, Catherine L; Selwyn, Beatrice J
2018-06-23
The risk of malaria infection displays spatial and temporal variability that is likely due to interaction between the physical environment and the human population. In this study, we performed a spatial analysis at three different time points, corresponding to three cross-sectional surveys conducted as part of an insecticide-treated bed nets efficacy study, to reveal patterns of malaria incidence distribution in an area of Northern Guatemala characterized by low malaria endemicity. A thorough understanding of the spatial and temporal patterns of malaria distribution is essential for targeted malaria control programs. Two methods, the local Moran's I and the Getis-Ord G * (d), were used for the analysis, providing two different statistical approaches and allowing for a comparison of results. A distance band of 3.5 km was considered to be the most appropriate distance for the analysis of data based on epidemiological and entomological factors. Incidence rates were higher at the first cross-sectional survey conducted prior to the intervention compared to the following two surveys. Clusters or hot spots of malaria incidence exhibited high spatial and temporal variations. Findings from the two statistics were similar, though the G * (d) detected cold spots using a higher distance band (5.5 km). The high spatial and temporal variability in the distribution of clusters of high malaria incidence seems to be consistent with an area of unstable malaria transmission. In such a context, a strong surveillance system and the use of spatial analysis may be crucial for targeted malaria control activities.
Results from OSO-IV - The long term behavior of X-ray emitting regions.
NASA Technical Reports Server (NTRS)
Krieger, A.; Paolini, F.; Vaiana, G. S.; Webb, D.
1972-01-01
Analysis of images of the sun obtained with the aid of a grazing incidence X-ray telescope on board the OSO IV spacecraft in the 2.5 to 12-A waveband nearly continuously from Oct. 27, 1967, to May 12, 1968. The instrument had sufficient spatial resolution (one and four arc minutes) and temporal resolution (5 to 20 min) to estimate the spatial characteristics of X-ray emitting regions and to monitor the temporal behavior of individual active regions. Variations in the absence of flares of as much as a factor of 10 in the X-ray output of individual regions were observed, with typical durations ranging from several hours to several days. The X-ray time variations are related to observations at optical and radio wavelengths. The results are interpreted under the assumption that the X-ray time variations are caused by temperature changes in the coronal portions of active regions. The contribution of radiative losses to the energy budget of the coronal active region is estimated.
Long, J.M.; Fisher, W.L.
2006-01-01
We present a method for spatial interpretation of environmental variation in a reservoir that integrates principal components analysis (PCA) of environmental data with geographic information systems (GIS). To illustrate our method, we used data from a Great Plains reservoir (Skiatook Lake, Oklahoma) with longitudinal variation in physicochemical conditions. We measured 18 physicochemical features, mapped them using GIS, and then calculated and interpreted four principal components. Principal component 1 (PC1) was readily interpreted as longitudinal variation in water chemistry, but the other principal components (PC2-4) were difficult to interpret. Site scores for PC1-4 were calculated in GIS by summing weighted overlays of the 18 measured environmental variables, with the factor loadings from the PCA as the weights. PC1-4 were then ordered into a landscape hierarchy, an emergent property of this technique, which enabled their interpretation. PC1 was interpreted as a reservoir scale change in water chemistry, PC2 was a microhabitat variable of rip-rap substrate, PC3 identified coves/embayments and PC4 consisted of shoreline microhabitats related to slope. The use of GIS improved our ability to interpret the more obscure principal components (PC2-4), which made the spatial variability of the reservoir environment more apparent. This method is applicable to a variety of aquatic systems, can be accomplished using commercially available software programs, and allows for improved interpretation of the geographic environmental variability of a system compared to using typical PCA plots. ?? Copyright by the North American Lake Management Society 2006.
Spatial Characteristics of Tree Diameter Distributions in a Temperate Old-Growth Forest
Zhao, Xiuhai; von Gadow, Klaus
2013-01-01
This contribution identifies spatial characteristics of tree diameter in a temperate forest in north-eastern China, based on a fully censused observational study area covering 500×600 m. Mark correlation analysis with three null hypothesis models was used to determine departure from expectations at different neighborhood distances. Tree positions are clumped at all investigated scales in all 37 studied species, while the diameters of most species are spatially negatively correlated, especially at short distances. Interestingly, all three cases showing short-distance attraction of dbh marks are associated with light-demanding shrub species. The short-distance attraction of dbh marks indicates spatially aggregated cohorts of stems of similar size. The percentage of species showing significant dbh suppression peaked at a 4 m distance under the heterogeneous Poisson model. At scales exceeding the peak distance, the percentage of species showing significant dbh suppression decreases sharply with increasing distances. The evidence from this large observational study shows that some of the variation of the spatial characteristics of tree diameters is related variations of topography and soil chemistry. However, an obvious interpretation of this result is still lacking. Thus, removing competitors surrounding the target trees is an effective way to avoid neighboring competition effects reducing the growth of valuable target trees in forest management practice. PMID:23527066
Spatial characteristics of tree diameter distributions in a temperate old-growth forest.
Zhang, Chunyu; Wei, Yanbo; Zhao, Xiuhai; von Gadow, Klaus
2013-01-01
This contribution identifies spatial characteristics of tree diameter in a temperate forest in north-eastern China, based on a fully censused observational study area covering 500×600 m. Mark correlation analysis with three null hypothesis models was used to determine departure from expectations at different neighborhood distances. Tree positions are clumped at all investigated scales in all 37 studied species, while the diameters of most species are spatially negatively correlated, especially at short distances. Interestingly, all three cases showing short-distance attraction of dbh marks are associated with light-demanding shrub species. The short-distance attraction of dbh marks indicates spatially aggregated cohorts of stems of similar size. The percentage of species showing significant dbh suppression peaked at a 4 m distance under the heterogeneous Poisson model. At scales exceeding the peak distance, the percentage of species showing significant dbh suppression decreases sharply with increasing distances. The evidence from this large observational study shows that some of the variation of the spatial characteristics of tree diameters is related variations of topography and soil chemistry. However, an obvious interpretation of this result is still lacking. Thus, removing competitors surrounding the target trees is an effective way to avoid neighboring competition effects reducing the growth of valuable target trees in forest management practice.
Stewart, Barclay T.; Gyedu, Adam; Boakye, Godfred; Lewis, Daniel; Hoogerboord, Marius; Mock, Charles
2017-01-01
Background Surgical disease burden falls disproportionately on individuals in low- and middle-income countries. These populations are also the least likely to have access to surgical care. Understanding the barriers to access in these populations is therefore necessary to meet the global surgical need. Methods Using geospatial methods, this study explores the district-level variation of two access barriers in Ghana: poverty and spatial access to care. National survey data were used to estimate the average total household expenditure (THE) in each district. Estimates of the spatial access to essential surgical care were generated from a cost-distance model based on a recent surgical capacity assessment. Correlations were analyzed using regression and displayed cartographically. Results Both THE and spatial access to surgical care were found to have statistically significant regional variation in Ghana (p < 0.001). An inverse relationship was identified between THE and spatial access to essential surgical care (β −5.15 USD, p < 0.001). Poverty and poor spatial access to surgical care were found to co-localize in the northwest of the country. Conclusions Multiple barriers to accessing surgical care can coexist within populations. A careful understanding of all access barriers is necessary to identify and target strategies to address unmet surgical need within a given population. PMID:27766400
Russell, Ashley R; Valin, Lukas C; Bucsela, Eric J; Wenig, Mark O; Cohen, Ronald C
2010-05-01
We describe ground and space-based measurements of spatial and temporal variation of NO(2) in four California metropolitan regions. The measurements of weekly cycles and trends over the years 2005-2008 observed both from the surface and from space are nearly identical to each other. Observed decreases in Los Angeles and the surrounding cities are 46% on weekends and 9%/year from 2005-2008. Similar decreases are observed in the San Francisco Bay area and in Sacramento. In the San Joaquin Valley cities of Fresno and Bakersfield weekend decreases are much smaller, only 27%, and the decreasing trend is only 4%/year. We describe evidence that the satellite observations provide a uniquely complete view of changes in spatial patterns over time. For example, we observe variations in the spatial pattern of weekday-weekend concentrations in the Los Angeles basin with much steeper weekend decreases at the eastern edge of the basin. We also observe that the spatial extent of high NO(2) in the San Joaquin Valley has not receded as much as it has for other regions in the state. Analysis of these measurements is used to describe observational constraints on temporal trends in emission sources in the different regions.
Pu, Haixia; Luo, Kunli; Wang, Pin; Wang, Shaobin; Kang, Shun
2017-02-01
Daily air quality index (AQI) of 161 Chinese cities obtained from the Ministry of Environmental Protection of China in 2015 is conducted. In this study, to better explore spatial distribution and regional characteristic of AQI, global and local spatial autocorrelation is utilized. Pearson's correlation is introduced to determine the influence of single urban indicator on AQI value. Meanwhile, multiple linear stepwise regression is chosen to estimate quantitatively the most influential urban indicators on AQI. The spatial autocorrelation analysis indicates that the AQI value of Chinese 161 cities shows a spatial dependency. Higher AQI is mainly located in north and northwest regions, whereas low AQI is concentrated in the south and the Qinghai-Tibet regions. The low AQI and high AQI values in China both exhibit relative immobility through seasonal variation. The influence degree of three adverse urban driving factors on AQI value is ranked from high to low: coal consumption of manufacturing > building area > coal consumption of the power industry. It is worth noting that the risk of exposed population to poor quality is greater in the northern region than in other regions. The results of the study provide a reference for the formulation of urban policy and improvement of air quality in China.
Spatial-temporal and cancer risk assessment of selected hazardous air pollutants in Seattle.
Wu, Chang-fu; Liu, L-J Sally; Cullen, Alison; Westberg, Hal; Williamson, John
2011-01-01
In the Seattle Air Toxics Monitoring Pilot Program, we measured 15 hazardous air pollutants (HAPs) at 6 sites for more than a year between 2000 and 2002. Spatial-temporal variations were evaluated with random-effects models and principal component analyses. The potential health risks were further estimated based on the monitored data, with the incorporation of the bootstrapping technique for the uncertainty analysis. It is found that the temporal variability was generally higher than the spatial variability for most air toxics. The highest temporal variability was observed for tetrachloroethylene (70% temporal vs. 34% spatial variability). Nevertheless, most air toxics still exhibited significant spatial variations, even after accounting for the temporal effects. These results suggest that it would require operating multiple air toxics monitoring sites over a significant period of time with proper monitoring frequency to better evaluate population exposure to HAPs. The median values of the estimated inhalation cancer risks ranged between 4.3 × 10⁻⁵ and 6.0 × 10⁻⁵, with the 5th and 95th percentile levels exceeding the 1 in a million level. VOCs as a whole contributed over 80% of the risk among the HAPs measured and arsenic contributed most substantially to the overall risk associated with metals. Copyright © 2010 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Xu, Yong; Sui, Jixing; Yang, Mei; Sun, Yue; Li, Xinzheng; Wang, Hongfa; Zhang, Baolin
2017-09-01
To detect large, temporal- and spatial-scale variations in the macrofaunal community in the southern Yellow Sea, data collected along the western, middle and eastern regions of the southern Yellow Sea from 1958 to 2014 were organized and analyzed. Statistical methods such as cluster analysis, non-metric multidimensional scaling ordination (nMDS), permutational multivariate analysis of variance (PERMANOVA), redundancy analysis (RDA) and canonical correspondence analysis (CCA) were applied. The abundance of polychaetes increased in the western region but decreased in the eastern region from 1958 to 2014, whereas the abundance of echinoderms showed an opposite trend. For the entire macrofaunal community, Margalef's richness (d), the Shannon-Wiener index (H‧) and Pielou's evenness (J‧) were significantly lower in the eastern region when compared with the other two regions. No significant temporal differences were found for d and H‧, but there were significantly lower values of J‧ in 2014. Considerable variation in the macrofaunal community structure over the past several decades and among the geographical regions at the species, genus and family levels were observed. The species, genera and families that contributed to the temporal variation in each region were also identified. The most conspicuous pattern was the increase in the species Ophiura sarsii vadicola in the eastern region. In the western region, five polychaetes (Ninoe palmata, Notomastus latericeus, Paralacydonia paradoxa, Paraprionospio pinnata and Sternaspis scutata) increased consistently from 1958 to 2014. The dominance curves showed that both the species diversity and the dominance patterns were relatively stable in the western and middle regions. Environmental parameters such as depth, temperature and salinity could only partially explain the observed biological variation in the southern Yellow Sea. Anthropogenic activities such as demersal fishing and other unmeasured environmental variables may be more responsible for the long-term changes in the macrofaunal community.
Spatial luminescence imaging of dopant incorporation in CdTe Films
Guthrey, Harvey; Moseley, John; Colegrove, Eric; ...
2017-01-25
State-of-the-art cathodoluminescence (CL) spectrum imaging with spectrum-per-pixel CL emission mapping is applied to spatially profile how dopant elements are incorporated into Cadmium telluride (CdTe). Emission spectra and intensity monitor the spatial distribution of additional charge carriers through characteristic variations in the CL emission based on computational modeling. Our results show that grain boundaries play a role in incorporating dopants in CdTe exposed to copper, phosphorus, and intrinsic point defects in CdTe. Furthermore, the image analysis provides critical, unique feedback to understand dopant incorporation and activation in the inhomogeneous CdTe material, which has struggled to reach high levels of hole density.
Pan, Jay; Zhao, Hanqing; Wang, Xiuli; Shi, Xun
2016-12-01
In 2009, the Chinese government launched a new round of healthcare reform, which encourages development of private hospitals. Meanwhile, many public hospitals in China also became increasingly profit-oriented. These trends have led to concerns about social justice and regional disparity. However, there is a lack of empirical scientific analysis to support the debate. We started to fill this gap by conducting a regional-level analysis of spatial variation in spatial access to hospitals in the Sichuan Province. Such variation is an important indication of (in) equity in healthcare resource allocation. Using data of 2012, we intended to provide a snapshot of the situation that was a few years later since the new policies had set out. We employed two methods to quantify the spatial access: the nearest-neighbor method and the enhanced two-step floating catchment area (E2SFCA) method. We recognized two sub-regions of Sichuan: the rural West Sichuan and the well-developed East Sichuan. We classified the hospitals using both ownership and level. We applied the analysis to the resulting groups of hospitals and their combinations in the two sub-regions. The two sub-regions have a high contrast in the spatial access to hospitals, in terms of both quantity and spatial pattern. Public hospitals still dominated the service in the province, especially in the West Sichuan, which had been solely relying on public hospitals. Private hospitals only occurred in the East Sichuan, and at the primary level, they had surpassed public hospitals in terms of spatial accessibility. However, the governmental health expenditures seemed to be disconnected with the actual situation of the spatial access to hospitals. The government should continue carrying on its responsibility in allocating healthcare resources, be cautious about marketizing public hospitals, and encourage private hospitals to expand into rural areas. Methodologically, the results from the two methods are concurring but not identical. The E2SFCA method calculates population-adjusted density of hospitals, which measures deviation from the expected pattern, and therefore is more meaningful in assessing associations of the spatial access to hospitals with other factors (e.g., population density and investment). Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Bailey, S. W.
2016-12-01
Nine catchments are gaged at Hubbard Brook Experimental Forest, Woodstock, NH, USA, with weirs installed on adjacent first-order streams. These catchments have been used as unit ecosystems for analysis of chemical budgets, including evaluation of long term trends and response to disturbance. This study examines uncertainty in the representativeness of these budgets to other nearby catchments, or as representatives of the broader northern hardwood ecosystem, depending on choice of location of the stream gaging station. Within forested northern hardwood catchments across the Hubbard Brook region, there is relatively little spatial variation in amount or chemistry of precipitation inputs or in amount of streamwater outputs. For example, runoff per unit catchment area varies by less than 10% at gaging stations on first to sixth order streams. In contrast, concentrations of major solutes vary by an order of magnitude or more across stream sampling sites, with a similar range in concentrations seen within individual first order catchments as seen across the third order Hubbard Brook valley or across the White Mountain region. These spatial variations in stream chemistry are temporally persistent across a range of flow conditions. Thus first order catchment budgets vary greatly depending on very local variations in stream chemistry driven by choice of the site to develop a stream gage. For example, carbon output in dissolved organic matter varies by a factor of five depending on where the catchment output is defined at Watershed 3. I hypothesize that catchment outputs from first order streams are driven by spatially variable chemistry of shallow groundwater, reflecting local variations in the distribution of soils and vegetation. In contrast, spatial variability in stream chemistry decreases with stream order, hypothesized to reflect deeper groundwater inputs on larger streams, which are more regionally uniform. Thus, choice of a gaging site and definition of an ecosystem as a unit of analysis at a larger scale, such as the Hubbard Brook valley, would have less impact on calculated budgets than at the headwater scale. Monitoring of a larger catchment is more likely to be representative of other similar sized catchments. However, particular research questions may be better studied at the smaller headwater scale.
Turelli, Michael; Barton, N H
2004-01-01
We investigate three alternative selection-based scenarios proposed to maintain polygenic variation: pleiotropic balancing selection, G x E interactions (with spatial or temporal variation in allelic effects), and sex-dependent allelic effects. Each analysis assumes an additive polygenic trait with n diallelic loci under stabilizing selection. We allow loci to have different effects and consider equilibria at which the population mean departs from the stabilizing-selection optimum. Under weak selection, each model produces essentially identical, approximate allele-frequency dynamics. Variation is maintained under pleiotropic balancing selection only at loci for which the strength of balancing selection exceeds the effective strength of stabilizing selection. In addition, for all models, polymorphism requires that the population mean be close enough to the optimum that directional selection does not overwhelm balancing selection. This balance allows many simultaneously stable equilibria, and we explore their properties numerically. Both spatial and temporal G x E can maintain variation at loci for which the coefficient of variation (across environments) of the effect of a substitution exceeds a critical value greater than one. The critical value depends on the correlation between substitution effects at different loci. For large positive correlations (e.g., rho(ij)2>3/4), even extreme fluctuations in allelic effects cannot maintain variation. Surprisingly, this constraint on correlations implies that sex-dependent allelic effects cannot maintain polygenic variation. We present numerical results that support our analytical approximations and discuss our results in connection to relevant data and alternative variance-maintaining mechanisms. PMID:15020487
NASA Astrophysics Data System (ADS)
Kwon, O.; Kim, W.; Kim, J.
2017-12-01
Recently construction of subsea tunnel has been increased globally. For safe construction of subsea tunnel, identifying the geological structure including fault at design and construction stage is more than important. Then unlike the tunnel in land, it's very difficult to obtain the data on geological structure because of the limit in geological survey. This study is intended to challenge such difficulties in a way of developing the technology to identify the geological structure of seabed automatically by using echo sounding data. When investigation a potential site for a deep subsea tunnel, there is the technical and economical limit with borehole of geophysical investigation. On the contrary, echo sounding data is easily obtainable while information reliability is higher comparing to above approaches. This study is aimed at developing the algorithm that identifies the large scale of geological structure of seabed using geostatic approach. This study is based on theory of structural geology that topographic features indicate geological structure. Basic concept of algorithm is outlined as follows; (1) convert the seabed topography to the grid data using echo sounding data, (2) apply the moving window in optimal size to the grid data, (3) estimate the spatial statistics of the grid data in the window area, (4) set the percentile standard of spatial statistics, (5) display the values satisfying the standard on the map, (6) visualize the geological structure on the map. The important elements in this study include optimal size of moving window, kinds of optimal spatial statistics and determination of optimal percentile standard. To determine such optimal elements, a numerous simulations were implemented. Eventually, user program based on R was developed using optimal analysis algorithm. The user program was designed to identify the variations of various spatial statistics. It leads to easy analysis of geological structure depending on variation of spatial statistics by arranging to easily designate the type of spatial statistics and percentile standard. This research was supported by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport of the Korean government. (Project Number: 13 Construction Research T01)
DiLeo, Michelle F; Siu, Jenna C; Rhodes, Matthew K; López-Villalobos, Adriana; Redwine, Angela; Ksiazek, Kelly; Dyer, Rodney J
2014-08-01
Pollen-mediated gene flow is a major driver of spatial genetic structure in plant populations. Both individual plant characteristics and site-specific features of the landscape can modify the perceived attractiveness of plants to their pollinators and thus play an important role in shaping spatial genetic variation. Most studies of landscape-level genetic connectivity in plants have focused on the effects of interindividual distance using spatial and increasingly ecological separation, yet have not incorporated individual plant characteristics or other at-site ecological variables. Using spatially explicit simulations, we first tested the extent to which the inclusion of at-site variables influencing local pollination success improved the statistical characterization of genetic connectivity based upon examination of pollen pool genetic structure. The addition of at-site characteristics provided better models than those that only considered interindividual spatial distance (e.g. IBD). Models parameterized using conditional genetic covariance (e.g. population graphs) also outperformed those assuming panmixia. In a natural population of Cornus florida L. (Cornaceae), we showed that the addition of at-site characteristics (clumping of primary canopy opening above each maternal tree and maternal tree floral output) provided significantly better models describing gene flow than models including only between-site spatial (IBD) and ecological (isolation by resistance) variables. Overall, our results show that including interindividual and local ecological variation greatly aids in characterizing landscape-level measures of contemporary gene flow. © 2014 John Wiley & Sons Ltd.
Fine scale variations of surface water chemistry in an ephemeral to perennial drainage network
Margaret A. Zimmer; Scott W. Bailey; Kevin J. McGuire; Thomas D. Bullen
2013-01-01
Although temporal variation in headwater stream chemistry has long been used to document baseline conditions and response to environmental drivers, less attention is paid to fine scale spatial variations that could yield clues to processes controlling stream water sources. We documented spatial and temporal variation in water composition in a headwater catchment (41 ha...
NASA Astrophysics Data System (ADS)
Shoko, Cletah; Clark, David; Mengistu, Michael; Dube, Timothy; Bulcock, Hartley
2015-01-01
This study evaluated the effect of two readily available multispectral sensors: the newly launched 30 m spatial resolution Landsat 8 and the long-serving 1000 m moderate resolution imaging spectroradiometer (MODIS) datasets in the spatial representation of total evaporation in the heterogeneous uMngeni catchment, South Africa, using the surface energy balance system model. The results showed that sensor spatial resolution plays a critical role in the accurate estimation of energy fluxes and total evaporation across a heterogeneous catchment. Landsat 8 estimates showed better spatial representation of the biophysical parameters and total evaporation for different land cover types, due to the relatively higher spatial resolution compared to the coarse spatial resolution MODIS sensor. Moreover, MODIS failed to capture the spatial variations of total evaporation estimates across the catchment. Analysis of variance (ANOVA) results showed that MODIS-based total evaporation estimates did not show any significant differences across different land cover types (one-way ANOVA; F1.924=1.412, p=0.186). However, Landsat 8 images yielded significantly different estimates between different land cover types (one-way ANOVA; F1.993=5.185, p<0.001). The validation results showed that Landsat 8 estimates were more comparable to eddy covariance (EC) measurements than the MODIS-based total evaporation estimates. EC measurement on May 23, 2013, was 3.8 mm/day, whereas the Landsat 8 estimate on the same day was 3.6 mm/day, with MODIS showing significantly lower estimates of 2.3 mm/day. The findings of this study underscore the importance of spatial resolution in estimating spatial variations of total evaporation at the catchment scale, thus, they provide critical information on the relevance of the readily available remote sensing products in water resources management in data-scarce environments.
Hierarchical spatial models of abundance and occurrence from imperfect survey data
Royle, J. Andrew; Kery, M.; Gautier, R.; Schmid, Hans
2007-01-01
Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate ('census') all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the Population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.
Le Pichon, Céline; Tales, Évelyne; Belliard, Jérôme; Torgersen, Christian E.
2017-01-01
Spatially intensive sampling by electrofishing is proposed as a method for quantifying spatial variation in fish assemblages at multiple scales along extensive stream sections in headwater catchments. We used this method to sample fish species at 10-m2 points spaced every 20 m throughout 5 km of a headwater stream in France. The spatially intensive sampling design provided information at a spatial resolution and extent that enabled exploration of spatial heterogeneity in fish assemblage structure and aquatic habitat at multiple scales with empirical variograms and wavelet analysis. These analyses were effective for detecting scales of periodicity, trends, and discontinuities in the distribution of species in relation to tributary junctions and obstacles to fish movement. This approach to sampling riverine fishes may be useful in fisheries research and management for evaluating stream fish responses to natural and altered habitats and for identifying sites for potential restoration.
NASA Astrophysics Data System (ADS)
Zhong, Lingmin; Xu, Mo; Yang, Yanna; Wang, Xingbing
2018-02-01
Neotectonics has changed the coupled process of endogenic and exogenic geological dynamics, which mold the modern landform. Geomorphologic analysis is essential for identifying and understanding the tectonic activity and indicates the responsive mechanism of the landform to tectonic activity. At first, this research reconstructed the twisted Shanpen period planation surface, computed the valley floor width-to-height ratio of Sancha river and extracted the cross sections marking the river terraces to analyze the characteristics of the neotectonics. And then, the relation between neotectonic movement and landform development was analyzed by dividing the landform types. At last, the spatial variation of landform evolution was analyzed by extracting the Hypsometric Integral of sub-catchments. The Sancha river catchment's neotectonic movement presents the tilt-lift of earth's crust from NW to SE, which is characterized by the posthumous activity of Yanshan tectonic deformation. The spatial distribution of river terraces indicates that Sancha river catchment has experienced at least four intermittent uplifts and the fault blocks at both the sides of Liuzhi-Zhijin basement fault have differentially uplifted since the late Pleistocene. As the resurgence of Liuzhi-Zhijin basement fault, the Sancha river catchment was broken into two relative independent landform units. The spatial variations of the landform types near the Sancha river and the sub-catchments' landform evolution are characterized by periodic replacement. The styles of geological structure have controlled the development of landform far away from the Sancha River and influenced the landform evolution. The posthumous activities of the secondary structure have resulted in the spatial variation of sub-catchments' landform evolution, which presents periodic replacement with local exceptions. The present study suggests that spatial variations of the development and evolution of modern landform of Sancha River catchment owe their genesis to the interplay between the hydrodynamic force and tectonic activity in the neotectonic period. Likewise, the application of geomorphic indicators also provides a new way to assess the regional crustal stability.
Spatial variation in disease resistance: from molecules to metapopulations
Laine, Anna-Liisa; Burdon, Jeremy J.; Dodds, Peter N.; Thrall, Peter H.
2010-01-01
Summary Variation in disease resistance is a widespread phenomenon in wild plant-pathogen associations. Here, we review current literature on natural plant-pathogen associations to determine how diversity in disease resistance is distributed at different hierarchical levels – within host individuals, within host populations, among host populations at the metapopulation scale and at larger regional scales. We find diversity in resistance across all spatial scales examined. Furthermore, variability seems to be the best counter-defence of plants against their rapidly evolving pathogens. We find that higher diversity of resistance phenotypes also results in higher levels of resistance at the population level. Overall, we find that wild plant populations are more likely to be susceptible than resistant to their pathogens. However, the degree of resistance differs strikingly depending on the origin of the pathogen strains used in experimental inoculation studies. Plant populations are on average 16% more resistant to allopatric pathogen strains than they are to strains that occur within the same population (48 % vs. 32 % respectively). Pathogen dispersal mode affects levels of resistance in natural plant populations with lowest levels detected for hosts of airborne pathogens and highest for waterborne pathogens. Detailed analysis of two model systems, Linum marginale infected by Melampsora lini, and Plantago lanceolata infected by Podosphaera plantaginis, show that the amount of variation in disease resistance declines towards higher spatial scales as we move from individual hosts to metapopulations, but evaluation of multiple spatial scales is needed to fully capture the structure of disease resistance. Synthesis: Variation in disease resistance is ubiquitous in wild plant-pathogen associations. While the debate over whether the resistance structure of plant populations is determined by pathogen-imposed selection versus non-adaptive processes remains unresolved, we do report examples of pathogen-imposed selection on host resistance. Here we highlight the importance of measuring resistance across multiple spatial scales, and of using sympatric strains when looking for signs of coevolution in wild plant-pathogen interactions. PMID:21243068
Analysis of Terrestrial Water Storage Changes from GRACE and GLDAS
NASA Technical Reports Server (NTRS)
Syed, Tajdarul H.; Famiglietti, James S.; Rodell, Matthew; Chen, Jianli; Wilson, Clark R.
2008-01-01
Since March 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided first estimates of land water storage variations by monitoring the time-variable component of Earth's gravity field. Here we characterize spatial-temporal variations in terrestrial water storage changes (TWSC) from GRACE and compare them to those simulated with the Global Land Data Assimilation System (GLDAS). Additionally, we use GLDAS simulations to infer how TWSC is partitioned into snow, canopy water and soil water components, and to understand how variations in the hydrologic fluxes act to enhance or dissipate the stores. Results quantify the range of GRACE-derived storage changes during the studied period and place them in the context of seasonal variations in global climate and hydrologic extremes including drought and flood, by impacting land memory processes. The role of the largest continental river basins as major locations for freshwater redistribution is highlighted. GRACE-based storage changes are in good agreement with those obtained from GLDAS simulations. Analysis of GLDAS-simulated TWSC illustrates several key characteristics of spatial and temporal land water storage variations. Global averages of TWSC were partitioned nearly equally between soil moisture and snow water equivalent, while zonal averages of TWSC revealed the importance of soil moisture storage at low latitudes and snow storage at high latitudes. Evapotranspiration plays a key role in dissipating globally averaged terrestrial water storage. Latitudinal averages showed how precipitation dominates TWSC variations in the tropics, evapotranspiration is most effective in the midlatitudes, and snowmelt runoff is a key dissipating flux at high latitudes. Results have implications for monitoring water storage response to climate variability and change, and for constraining land model hydrology simulations.
NASA Astrophysics Data System (ADS)
Ansari, Kutubuddin; Panda, Sampad Kumar; Corumluoglu, Ozsen
2018-03-01
The present study examines the ionospheric Total Electron Content (TEC) variations in the lower mid-latitude Turkish region from the Turkish permanent GNSS network (TPGN) and International GNSS Services (IGS) observations during the years 2009 to 2017. The corresponding vertical TEC (VTEC) predicted by Kriging and NeQuick-2 models are evaluated to realize their efficacy over the country. We studied the diurnal, seasonal and spatial pattern of VTEC variation and tried to estimate by a new mathematical model using the long term of 9 years VTEC data. The diurnal variation of VTEC demonstrates a normal trend with its gradual enhancement from dawn to attain a peak around 09:00-14.00 UT and reaching the minimum level after 22.00 UT. The seasonal behavior of VTEC indicates a strong semi-annual variation of VTEC with maxima in September equinox followed by March equinox and minima in June solstice followed by December solstice. Also, the spatial variation in VTEC depicts a meaningful longitudinal/latitudinal pattern altering with seasons. It decreases longitudinally from the west to the east during March equinox and June solstice increases with latitude. The comparative analysis among the GNSS-VTEC, Kriging, NeQuick and the proposed mathematical model are evaluated with the help one way ANOVA test. The analysis shows that the null hypothesis of the models during storm and quiet days are accepted and suggesting that all models are statistically significantly equivalent from each other. We believe the outcomes from this study would complement towards a relatively better understanding of the lower mid-latitude VTEC variation over the Turkish region and analogous latitudes over the globe.
Adaptations to Climate in Candidate Genes for Common Metabolic Disorders
Hancock, Angela M; Witonsky, David B; Gordon, Adam S; Eshel, Gidon; Pritchard, Jonathan K; Coop, Graham; Di Rienzo, Anna
2008-01-01
Evolutionary pressures due to variation in climate play an important role in shaping phenotypic variation among and within species and have been shown to influence variation in phenotypes such as body shape and size among humans. Genes involved in energy metabolism are likely to be central to heat and cold tolerance. To test the hypothesis that climate shaped variation in metabolism genes in humans, we used a bioinformatics approach based on network theory to select 82 candidate genes for common metabolic disorders. We genotyped 873 tag SNPs in these genes in 54 worldwide populations (including the 52 in the Human Genome Diversity Project panel) and found correlations with climate variables using rank correlation analysis and a newly developed method termed Bayesian geographic analysis. In addition, we genotyped 210 carefully matched control SNPs to provide an empirical null distribution for spatial patterns of allele frequency due to population history alone. For nearly all climate variables, we found an excess of genic SNPs in the tail of the distributions of the test statistics compared to the control SNPs, implying that metabolic genes as a group show signals of spatially varying selection. Among our strongest signals were several SNPs (e.g., LEPR R109K, FABP2 A54T) that had previously been associated with phenotypes directly related to cold tolerance. Since variation in climate may be correlated with other aspects of environmental variation, it is possible that some of the signals that we detected reflect selective pressures other than climate. Nevertheless, our results are consistent with the idea that climate has been an important selective pressure acting on candidate genes for common metabolic disorders. PMID:18282109
NASA Astrophysics Data System (ADS)
Wang, Hao; Wei, Ming; Li, Guoping; Zhou, Shenghui; Zeng, Qingfeng
2013-08-01
The rainfall process of Chengdu region in autumn has obvious regional features. Especially, the night-time rain rate of this region in this season is very high in China. Studying the spatial distribution and temporal variation of regional atmospheric precipitable water vapor (PWV) is important for our understanding of water vapor related processes, such as rainfall, evaporation, convective activity, among others in this area. Since GPS detection technology has the unique characteristics, such as all-weather, high accuracy, high spatial and temporal resolution as well as low cost, tracking and monitoring techniques on water vapor has achieved rapid developments in recent years. With GPS-PWV data at 30-min interval gathered from six GPS observational stations in Chengdu region in two autumns (September 2007-December 2007 and September 2008-December 2008), it is revealed that negative correlations exist between seasonally averaged value of GPS-PWV as well as its variation amplitude and local terrain altitude. The variation of PWV in the upper atmosphere of this region results from the water vapor variation from surface to 850 hPa. With the help of Fast Fourier Transform (FFT), it is found that the autumn PWV in Chengdu region has a multi-scale feature, which includes a seasonal cycle, 22.5 days period (quasi-tri-weekly oscillation). The variation of the GPS-PWV is related to periodical change in the transmitting of the water vapor caused by zonal and meridional wind strengths’ change and to the East Asian monsoon system. According to seasonal variation characteristics, we concluded that the middle October is the critical turning point in PWV content. On a shorter time scale, the relationship between autumn PWV and ground meteorological elements was obtained using the composite analysis approach.
NASA Astrophysics Data System (ADS)
Venäläinen, Ari; Laapas, Mikko; Pirinen, Pentti; Horttanainen, Matti; Hyvönen, Reijo; Lehtonen, Ilari; Junila, Päivi; Hou, Meiting; Peltola, Heli M.
2017-07-01
The bioeconomy has an increasing role to play in climate change mitigation and the sustainable development of national economies. In Finland, a forested country, over 50 % of the current bioeconomy relies on the sustainable management and utilization of forest resources. Wind storms are a major risk that forests are exposed to and high-spatial-resolution analysis of the most vulnerable locations can produce risk assessment of forest management planning. In this paper, we examine the feasibility of the wind multiplier approach for downscaling of maximum wind speed, using 20 m spatial resolution CORINE land-use dataset and high-resolution digital elevation data. A coarse spatial resolution estimate of the 10-year return level of maximum wind speed was obtained from the ERA-Interim reanalyzed data. Using a geospatial re-mapping technique the data were downscaled to 26 meteorological station locations to represent very diverse environments. Applying a comparison, we find that the downscaled 10-year return levels represent 66 % of the observed variation among the stations examined. In addition, the spatial variation in wind-multiplier-downscaled 10-year return level wind was compared with the WAsP model-simulated wind. The heterogeneous test area was situated in northern Finland, and it was found that the major features of the spatial variation were similar, but in some locations, there were relatively large differences. The results indicate that the wind multiplier method offers a pragmatic and computationally feasible tool for identifying at a high spatial resolution those locations with the highest forest wind damage risks. It can also be used to provide the necessary wind climate information for wind damage risk model calculations, thus making it possible to estimate the probability of predicted threshold wind speeds for wind damage and consequently the probability (and amount) of wind damage for certain forest stand configurations.
NASA Technical Reports Server (NTRS)
Davis, Frank W.; Quattrochi, Dale A.; Ridd, Merrill K.; Lam, Nina S.-N.; Walsh, Stephen J.
1991-01-01
This paper discusses some basic scientific issues and research needs in the joint processing of remotely sensed and GIS data for environmental analysis. Two general topics are treated in detail: (1) scale dependence of geographic data and the analysis of multiscale remotely sensed and GIS data, and (2) data transformations and information flow during data processing. The discussion of scale dependence focuses on the theory and applications of spatial autocorrelation, geostatistics, and fractals for characterizing and modeling spatial variation. Data transformations during processing are described within the larger framework of geographical analysis, encompassing sampling, cartography, remote sensing, and GIS. Development of better user interfaces between image processing, GIS, database management, and statistical software is needed to expedite research on these and other impediments to integrated analysis of remotely sensed and GIS data.
Large-Scale Circulation and Climate Variability. Chapter 5
NASA Technical Reports Server (NTRS)
Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.
2017-01-01
The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.
Evaluation of a spatially-distributed Thornthwaite water-balance model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lough, J.A.
1993-03-01
A small watershed of low relief in coastal New Hampshire was divided into hydrologic sub-areas in a geographic information system on the basis of soils, sub-basins and remotely-sensed landcover. Three variables were spatially modeled for input to 49 individual water-balances: available water content of the root zone, water input and potential evapotranspiration (PET). The individual balances were weight-summed to generate the aggregate watershed-balance, which saw 9% (48--50 mm) less annual actual-evapotranspiration (AET) compared to a lumped approach. Analysis of streamflow coefficients suggests that the spatially-distributed approach is more representative of the basin dynamics. Variation of PET by landcover accounted formore » the majority of the 9% AET reduction. Variation of soils played a near-negligible role. As a consequence of the above points, estimates of landcover proportions and annual PET by landcover are sufficient to correct a lumped water-balance in the Northeast. If remote sensing is used to estimate the landcover area, a sensor with a high spatial resolution is required. Finally, while the lower Thornthwaite model has conceptual limitations for distributed application, the upper Thornthwaite model is highly adaptable to distributed problems and may prove useful in many earth-system models.« less
Spatial/Temporal Variations of Crime: A Routine Activity Theory Perspective.
de Melo, Silas Nogueira; Pereira, Débora V S; Andresen, Martin A; Matias, Lindon Fonseca
2018-05-01
Temporal and spatial patterns of crime in Campinas, Brazil, are analyzed considering the relevance of routine activity theory in a Latin American context. We use geo-referenced criminal event data, 2010-2013, analyzing spatial patterns using census tracts and temporal patterns considering seasons, months, days, and hours. Our analyses include difference in means tests, count-based regression models, and Kulldorff's scan test. We find that crime in Campinas, Brazil, exhibits both temporal and spatial-temporal patterns. However, the presence of these patterns at the different temporal scales varies by crime type. Specifically, not all crime types have statistically significant temporal patterns at all scales of analysis. As such, routine activity theory works well to explain temporal and spatial-temporal patterns of crime in Campinas, Brazil. However, local knowledge of Brazilian culture is necessary for understanding a portion of these crime patterns.
SPATIAL VARIATION OF THE EVOLUTION AND STRUCTURE OF THE URBAN BOUNDARY LAYER
The spatial variation of the nocturnal urban boundary layer structure and the time variation of the mixing height, the nocturnal inversion top and strength after sunrise are presented for urban sites located upwind, downwind, and near the center of the heat island and for upwind ...
Advancing the detection of steady-state visual evoked potentials in brain-computer interfaces
NASA Astrophysics Data System (ADS)
Abu-Alqumsan, Mohammad; Peer, Angelika
2016-06-01
Objective. Spatial filtering has proved to be a powerful pre-processing step in detection of steady-state visual evoked potentials and boosted typical detection rates both in offline analysis and online SSVEP-based brain-computer interface applications. State-of-the-art detection methods and the spatial filters used thereby share many common foundations as they all build upon the second order statistics of the acquired Electroencephalographic (EEG) data, that is, its spatial autocovariance and cross-covariance with what is assumed to be a pure SSVEP response. The present study aims at highlighting the similarities and differences between these methods. Approach. We consider the canonical correlation analysis (CCA) method as a basis for the theoretical and empirical (with real EEG data) analysis of the state-of-the-art detection methods and the spatial filters used thereby. We build upon the findings of this analysis and prior research and propose a new detection method (CVARS) that combines the power of the canonical variates and that of the autoregressive spectral analysis in estimating the signal and noise power levels. Main results. We found that the multivariate synchronization index method and the maximum contrast combination method are variations of the CCA method. All three methods were found to provide relatively unreliable detections in low signal-to-noise ratio (SNR) regimes. CVARS and the minimum energy combination methods were found to provide better estimates for different SNR levels. Significance. Our theoretical and empirical results demonstrate that the proposed CVARS method outperforms other state-of-the-art detection methods when used in an unsupervised fashion. Furthermore, when used in a supervised fashion, a linear classifier learned from a short training session is able to estimate the hidden user intention, including the idle state (when the user is not attending to any stimulus), rapidly, accurately and reliably.
Chen, Zhangxing; Huang, Tianyu; Shao, Yimin; ...
2018-03-15
Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Zhangxing; Huang, Tianyu; Shao, Yimin
Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less
Spatiotemporal analysis of Quaternary normal faults in the Northern Rocky Mountains, USA
NASA Astrophysics Data System (ADS)
Davarpanah, A.; Babaie, H. A.; Reed, P.
2010-12-01
The mid-Tertiary Basin-and-Range extensional tectonic event developed most of the normal faults that bound the ranges in the northern Rocky Mountains within Montana, Wyoming, and Idaho. The interaction of the thermally induced stress field of the Yellowstone hot spot with the existing Basin-and-Range fault blocks, during the last 15 my, has produced a new, spatially and temporally variable system of normal faults in these areas. The orientation and spatial distribution of the trace of these hot-spot induced normal faults, relative to earlier Basin-and-Range faults, have significant implications for the effect of the temporally varying and spatially propagating thermal dome on the growth of new hot spot related normal faults and reactivation of existing Basin-and-Range faults. Digitally enhanced LANDSAT 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 4 and 5 Thematic Mapper (TM) bands, with spatial resolution of 30 m, combined with analytical GIS and geological techniques helped in determining and analyzing the lineaments and traces of the Quaternary, thermally-induced normal faults in the study area. Applying the color composite (CC) image enhancement technique, the combination of bands 3, 2 and 1 of the ETM+ and TM images was chosen as the best statistical choice to create a color composite for lineament identification. The spatiotemporal analysis of the Quaternary normal faults produces significant information on the structural style, timing, spatial variation, spatial density, and frequency of the faults. The seismic Quaternary normal faults, in the whole study area, are divided, based on their age, into four specific sets, which from oldest to youngest include: Quaternary (>1.6 Ma), middle and late Quaternary (>750 ka), latest Quaternary (>15 ka), and the last 150 years. A density map for the Quaternary faults reveals that most active faults are near the current Yellowstone National Park area (YNP), where most seismically active faults, in the past 1.6 my, are located. The GIS based autocorrelation method, applied to the trace orientation, length, frequency, and spatial distribution for each age-defined fault set, revealed spatial homogeneity for each specific set. The results of the method of Moran`sI and Geary`s C show no spatial autocorrelation among the trend of the fault traces and their location. Our results suggest that while lineaments of similar age define a clustered pattern in each domain, the overall distribution pattern of lineaments with different ages seems to be non-uniform (random). The directional distribution analysis reveals a distinct range of variation for fault traces of different ages (i.e., some displaying ellipsis behavior). Among the Quaternary normal fault sets, the youngest lineament set (i.e., last 150 years) defines the greatest ellipticity (eccentricity) and the least lineaments distribution variation. The frequency rose diagram for the entire Quaternary normal faults, shows four major modes (around 360o, 330o, 300o, and 270o), and two minor modes (around 235 and 205).
Luo, Ji; Chen, Youchao; Wu, Yanhong; Shi, Peili; She, Jia; Zhou, Peng
2012-01-01
Soil respiration (SR) is an important process in the global carbon cycle. It is difficult to estimate SR emission accurately because of its temporal and spatial variability. Primary forest succession on Glacier forehead provides the ideal environment for examining the temporal-spatial variation and controlling factors of SR. However, relevant studies on SR are relatively scarce, and variations, as well as controlling factors, remain uncertain in this kind of region. In this study, we used a static chamber system to measure SR in six sites which represent different stages of forest succession on forehead of a temperate glacier in Gongga Mountain, China. Our results showed that there was substantial temporal (coefficient of variation (CV) ranged from 39.3% to 73.9%) and spatial (CV ranged from 12.3% to 88.6%) variation in SR. Soil temperature (ST) at 5 cm depth was the major controlling factor of temporal variation in all six sites. Spatial variation in SR was mainly caused by differences in plant biomass and Total N among the six sites. Moreover, soil moisture (SM), microbial biomass carbon (MBC), soil organic carbon (SOC), pH and bulk density could influence SR by directly or indirectly affecting plant biomass and Total N. Q10 values (ranged from 2.1 to 4.7) increased along the forest succession, and the mean value (3.3) was larger than that of temperate ecosystems, which indicated a general tendency towards higher-Q10 in colder ecosystems than in warmer ecosystems. Our findings provided valuable information for understanding temporal-spatial variation and controlling factors of SR. PMID:22879950
Andrade-Silva, A C R; Nemésio, A; de Oliveira, F F; Nascimento, F S
2012-08-01
The spatial and temporal distribution of organisms is a fundamental aspect of biological communities. The present study focused on three remnants of arboreal Caatinga in northeastern Brazil between May, 2009 and April, 2010. A total of 627 euglossine males were captured in traps baited with artificial aromatic compounds. The specimens belonged to 14 species and four genera: Euglossa Latreille, Eulaema Lepeletier, Eufriesea Cockerell, and Exaerete Hoffmannsegg. Eulaema nigrita Lepeletier (41.6), Euglossa carolina Nemésio (15.3%), Eulaema marcii Nemésio (13.6%), and Euglossa melanotricha Moure (12.8%) were the most common species sampled. The distribution of collected specimens per fragment was as follows: Braúna (280 ha)--259 individuals belonging to 14 species; Cambuí (179 ha)--161 individuals from eight species; and Pindoba (100 ha)--207 individuals represented by seven species. Braúna had the highest diversity (H' = 1.91) and estimated species richness. The largest fragment was the main source of the observed variation in species richness and abundance, indicating a non-random pattern of spatial distribution. The analysis of environmental factors indicated that seasonal variation in these factors was the principal determinant of species occurrence and abundance.
Determination of mean pressure from PIV in compressible flows using the Reynolds-averaging approach
NASA Astrophysics Data System (ADS)
van Gent, Paul L.; van Oudheusden, Bas W.; Schrijer, Ferry F. J.
2018-03-01
The feasibility of computing the flow pressure on the basis of PIV velocity data has been demonstrated abundantly for low-speed conditions. The added complications occurring for high-speed compressible flows have, however, so far proved to be largely inhibitive for the accurate experimental determination of instantaneous pressure. Obtaining mean pressure may remain a worthwhile and realistic goal to pursue. In a previous study, a Reynolds-averaging procedure was developed for this, under the moderate-Mach-number assumption that density fluctuations can be neglected. The present communication addresses the accuracy of this assumption, and the consistency of its implementation, by evaluating of the relevance of the different contributions resulting from the Reynolds-averaging. The methodology involves a theoretical order-of-magnitude analysis, complemented with a quantitative assessment based on a simulated and a real PIV experiment. The assessments show that it is sufficient to account for spatial variations in the mean velocity and the Reynolds-stresses and that temporal and spatial density variations (fluctuations and gradients) are of secondary importance and comparable order-of-magnitude. This result permits to simplify the calculation of mean pressure from PIV velocity data and to validate the approximation of neglecting temporal and spatial density variations without having access to reference pressure data.
Investigation of priorities in water quality management based on correlations and variations.
Boyacıoğlu, Hülya; Gündogdu, Vildan; Boyacıoğlu, Hayal
2013-04-15
The development of water quality assessment strategies investigating spatial and temporal changes caused by natural and anthropogenic phenomena is an important tool in management practices. This paper used cluster analysis, water quality index method, sensitivity analysis and canonical correlation analysis to investigate priorities in pollution control activities. Data sets representing 22 surface water quality parameters were subject to analysis. Results revealed that organic pollution was serious threat for overall water quality in the region. Besides, oil and grease, lead and mercury were the critical variables violating the standard. In contrast to inorganic variables, organic and physical-inorganic chemical parameters were influenced by variations in physical conditions (discharge, temperature). This study showed that information produced based on the variations and correlations in water quality data sets can be helpful to investigate priorities in water management activities. Moreover statistical techniques and index methods are useful tools in data - information transformation process. Copyright © 2013 Elsevier Ltd. All rights reserved.
de Rooij, Myrna M T; Heederik, Dick J J; Borlée, Floor; Hoek, Gerard; Wouters, Inge M
2017-02-01
Several studies have reported associations between farming and respiratory health in neighboring residents. Health effects are possibly linked to fine dust and endotoxin emissions from livestock farms. Little is known about levels of these air pollutants in ambient air in livestock dense areas. We aimed to explore temporal and spatial variation of PM10 and endotoxin concentrations, and the association with livestock-related spatial and meteorological temporal determinants. From March till September 2011, one week average PM10 samples were collected using Harvard Impactors at eight sites (residential gardens) representing a variety of nearby livestock-related characteristics. A background site was included in the study area, situated at least 500m away from the nearest farm. PM10 mass was determined by gravimetric analysis and endotoxin level by means of Limulus-Amebocyte-Lysate assay. Data were analyzed using mixed models. The range between sites of geometric mean concentrations was for PM10 19.8-22.3µg/m 3 and for endotoxin 0.46-0.66EU/m 3 . PM10 concentrations and spatial variation were very similar for all sites, while endotoxin concentrations displayed a more variable pattern over time with larger differences between sites. Nonetheless, the temporal pattern at the background location was highly comparable to the sites mean temporal pattern both for PM10 and endotoxin (Pearson correlation: 0.92, 0.62). Spatial variation was larger for endotoxin than for PM10 (within/between site variance ratio: 0.63, 2.03). Spatial livestock-related characteristics of the surroundings were more strongly related to endotoxin concentrations, while temporal determinants were more strongly related to PM10 concentrations. The effect of local livestock-related sources on PM10 concentration was limited in this study carried out in a livestock dense area. The effect on endotoxin concentrations was more profound. To gain more insight in the effect of livestock-related sources on ambient levels of PM10 and endotoxin, measurements should be based on a broader set of locations. Copyright © 2016. Published by Elsevier Inc.
Covariate selection with iterative principal component analysis for predicting physical
USDA-ARS?s Scientific Manuscript database
Local and regional soil data can be improved by coupling new digital soil mapping techniques with high resolution remote sensing products to quantify both spatial and absolute variation of soil properties. The objective of this research was to advance data-driven digital soil mapping techniques for ...
Betty Petersen Memorial Library - NCWCP Publications - NWS
Filters to Variational Statistical Analysis with Spatially Inhomogeneous Covariances (.PDF file) 432 2001 file) 456 2008 Purser, R. James Normalization Of The Diffusive Filters That Represent The Inhomogeneous file) 457 2008 Purser, R. James Normalization Of The Diffusive Filters That Represent The Inhomogeneous
Quantifying uncertainty in forest nutrient budgets
Ruth D. Yanai; Carrie R. Levine; Mark B. Green; John L. Campbell
2012-01-01
Nutrient budgets for forested ecosystems have rarely included error analysis, in spite of the importance of uncertainty to interpretation and extrapolation of the results. Uncertainty derives from natural spatial and temporal variation and also from knowledge uncertainty in measurement and models. For example, when estimating forest biomass, researchers commonly report...
USDA-ARS?s Scientific Manuscript database
This study explores the spatial relationship between Russian wheat aphid population density and variation in edaphic or topographic factors within wheat fields. Multiple regression analysis was applied to data collected from six wheat fields located in three States, Colorado, Wyoming, and Nebraska....
Evidence for subsurface water ice in Korolev crater, Mars
Armstrong, J.C.; Titus, T.N.; Kieffer, H.H.
2005-01-01
Following the work of Kieffer and Titus (2001, Icarus 154, 162-180), we present results of thermal IR observations of Korolev crater, located at ???73?? latitude in the martian northern polar region. Similar to techniques employed by Titus et al. (2003, Science 299, 1048-1050), we use infrared images from the Thermal Emission Imaging System (THEMIS) aboard Mars Odyssey to identify several regions within the crater basin with distinct thermal properties that correlate with topography. The THEMIS results show these regions exhibit temperature variations, spatially within the crater and throughout the martian year. In addition to the variations identified in the THEMIS observations, Mars Global Surveyor Thermal Emission Spectrometer (TES) observations show differences in albedo and temperature of these regions on both daily and seasonal cycles. Modeling annual temperature variations of the surface, we use TES observations to examine the thermal properties of these regions. This analysis reveals the crater interior deposits are likely thick layers (several meters) of high thermal inertia material (water ice, or extremely ice-rich regolith). Spatial variations of the physical properties of these regions are likely due to topography and possibly variations in the subsurface material itself. The nature of these deposits may help constrain polar processes, as well as provide context for the polar lander mission, Phoenix. ?? 2004 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Wang, Dengfeng; Wei, Zhiyuan; Qi, Zhiping
Research on the temporal and spatial distribution of soil nutrients in tropical arable land is very important to promote the tropical sustainable agriculture development. Take the Eastern part of Hainan as research area, applying GIS spatial analysis technique, analyzing the temporal and spatial variation of soil N, P and K contents in arable land. The results indicate that the contents of soil N, P and K were 0.28%, 0.20% and 1.75% respectively in 2005. The concentrations of total N and P in arable land soil increased significantly from 1980s to 2005. The variances in contents of soil nutrients were closely related to the application of chemical fertilizers in recent years, and the uneven distribution of soil nutrient contents was a reflection of fertilizer application in research area. Fertilization can be planned based on the distribution of soil nutrients and the spatial analysis techniques, so as to sustain balance of soil nutrients contents.
Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach.
Xu, Pengpeng; Huang, Helai; Dong, Ni; Wong, S C
2017-01-01
This study was performed to investigate the spatially varying relationships between crash frequency and related risk factors. A Bayesian spatially varying coefficients model was elaborately introduced as a methodological alternative to simultaneously account for the unstructured and spatially structured heterogeneity of the regression coefficients in predicting crash frequencies. The proposed method was appealing in that the parameters were modeled via a conditional autoregressive prior distribution, which involved a single set of random effects and a spatial correlation parameter with extreme values corresponding to pure unstructured or pure spatially correlated random effects. A case study using a three-year crash dataset from the Hillsborough County, Florida, was conducted to illustrate the proposed model. Empirical analysis confirmed the presence of both unstructured and spatially correlated variations in the effects of contributory factors on severe crash occurrences. The findings also suggested that ignoring spatially structured heterogeneity may result in biased parameter estimates and incorrect inferences, while assuming the regression coefficients to be spatially clustered only is probably subject to the issue of over-smoothness. Copyright © 2016 Elsevier Ltd. All rights reserved.
Jones, R Christian; Kelso, Donald P; Schaeffer, Elaine
2008-12-01
Spatial and temporal patterns in water quality were studied for seven years within an embayment-river mainstem area of the tidal freshwater Potomac River. The purpose of this paper is to determine the important components of spatial and temporal variation in water quality in this study area to facilitate an understanding of management impacts and allow the most effective use of future monitoring resources. The study area received treated sewage effluent and freshwater inflow from direct tributary inputs into the shallow embayment as well as upriver sources in the mainstem. Depth variations were determined to be detectable, but minimal due mainly to the influence of tidal mixing. Results of principal component analysis of two independent water quality datasets revealed clear spatial and seasonal patterns. Interannual variation was generally minimal despite substantial variations in tributary and mainstem discharge among years. Since both spatial and seasonal components were important, data were segmented by season to best determine the spatial pattern. A clear difference was found between a set of stations located within one embayment (Gunston Cove) and a second set in the nearby Potomac mainstem. Parameters most highly correlated with differences were those typically associated with higher densities of phytoplankton: chlorophyll a, photosynthetic rate, pH, dissolved oxygen, BOD, total phosphorus and Secchi depth. These differences and their consistency indicated two distinct water masses: one in the cove harboring higher algal density and activity and a second in the river with lower phytoplankton activity. A second embayment not receiving sewage effluent generally had an intermediate position. While this was the most consistent spatial pattern, there were two others of a secondary nature. Stations closer to the effluent inputs in the embayment sometimes grouped separately due to elevated ammonia and chloride. Stations closer to tributary inflows into the embayment sometimes grouped separately due to dilution with freshwater runoff. Segmenting the datasets by spatial region resulted in a clarification of seasonal patterns with similar factors relating to algal activity being the major correlates of the seasonal pattern. A basic seasonal pattern of lower scores in the spring increasing steadily to a peak in July and August followed by a steady decline through the fall was observed in the cove. In the river, the pattern of increases tended to be delayed slightly in the spring. Results indicate that the study area can be effectively monitored with fewer study sites provided that at least one is located in each of the spatial regions.
Grundel, R.; Pavlovic, N.B.
2007-01-01
Determination of which aspects of habitat quality and habitat spatial arrangement best account for variation in a species’ distribution can guide management for organisms such as the Karner blue butterfly (Lycaeides melissa samuelis), a federally endangered subspecies inhabiting savannas of Midwest and Eastern United States. We examined the extent to which three sets of predictors, (1) larval host plant (Lupinus perennis, wild lupine) availability, (2) characteristics of the matrix surrounding host plant patches, and (3) factors affecting a patch’s thermal environment, accounted for variation in lupine patch use by Karner blues at Indiana Dunes National Lakeshore, Indiana and Fort McCoy, Wisconsin, USA. Each predictor set accounted for 7–13% of variation in patch occupancy by Karner blues at both sites and in larval feeding activity among patches at Indiana Dunes. Patch area, an indicator of host plant availability, was an exception, accounting for 30% of variation in patch occupancy at Indiana Dunes. Spatially structured patterns of patch use across the landscape accounted for 9–16% of variation in patch use and explained more variation in larval feeding activity than did spatial autocorrelation between neighboring patches. Because of this broader spatial trend across sites, a given management action may be more effective in promoting patch use in some portions of the landscape than in others. Spatial trend, resource availability, matrix quality, and microclimate, in general, accounted for similar amounts of variation in patch use and each should be incorporated into habitat management planning for the Karner blue butterfly.
NASA Astrophysics Data System (ADS)
Fisher, Jon; Zhao, Bo; Lin, Cuikun; Berry, Mary; May, P. Stanley; Smith, Steve
2015-03-01
We use spectroscopic imaging to assess the spatial variations in upconversion luminescence from NaYF4:Er3+,Yb3+ nanoparticles embedded in PMMA on Au nano-cavity arrays. The nano-cavity arrays support a surface plasmon (SP) resonance at 980nm, coincident with the peak absorption of the Yb3+ sensitizer. Spatially-resolved upconversion spectra show a 30X to 3X luminescence intensity enhancement on the nano-cavity array compared to the nearby smooth Au surface, corresponding to excitation intensities from 1 W/cm2 to 300kW/cm2. Our analysis shows the power dependent enhancement in upconversion luminescence can be almost entirely accounted for by a constant shift in the effective excitation intensity, which is maintained over five orders of magnitude variation in excitation intensity. The variations in upconversion luminescence enhancement with power are modeled by a 3-level-system near the saturation limit, and by simultaneous solution of a system of coupled nonlinear differential equations, both analyses agree well with the experiments. Analysis of the statistical distribution of emission intensities in the spectroscopic images on and off the nano-cavity arrays provides an estimate of the average enhancement factor independent of fluctuations in nano-particle density. Funding provided by NSF Award # 0903685 (IGERT).
Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination
Ha, Hoehun; Rogerson, Peter A.; Olson, James R.; Han, Daikwon; Bian, Ling; Shao, Wanyun
2016-01-01
Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations. PMID:27649221
Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination.
Ha, Hoehun; Rogerson, Peter A; Olson, James R; Han, Daikwon; Bian, Ling; Shao, Wanyun
2016-09-14
Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations.
NASA Technical Reports Server (NTRS)
Sadowski, F. E.; Sarno, J. E.
1976-01-01
First, an analysis of forest feature signatures was used to help explain the large variation in classification accuracy that can occur among individual forest features for any one case of spatial resolution and the inconsistent changes in classification accuracy that were demonstrated among features as spatial resolution was degraded. Second, the classification rejection threshold was varied in an effort to reduce the large proportion of unclassified resolution elements that previously appeared in the processing of coarse resolution data when a constant rejection threshold was used for all cases of spatial resolution. For the signature analysis, two-channel ellipse plots showing the feature signature distributions for several cases of spatial resolution indicated that the capability of signatures to correctly identify their respective features is dependent on the amount of statistical overlap among signatures. Reductions in signature variance that occur in data of degraded spatial resolution may not necessarily decrease the amount of statistical overlap among signatures having large variance and small mean separations. Features classified by such signatures may thus continue to have similar amounts of misclassified elements in coarser resolution data, and thus, not necessarily improve in classification accuracy.
The underlying processes of a soil mite metacommunity on a small scale.
Dong, Chengxu; Gao, Meixiang; Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin
2017-01-01
Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran's eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale.
The underlying processes of a soil mite metacommunity on a small scale
Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin
2017-01-01
Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran’s eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale. PMID:28481906
Influence of Aerosols And Surface Reflectance On NO2 Retrieval Over China From 2005 to 2015
NASA Astrophysics Data System (ADS)
Liu, M.; Lin, J.
2016-12-01
Satellite observation is a powerful way to analysis annual and seasonal variations of nitrogen dioxide (NO2). However, much retrieval of vertical column densities (VCDs) of normally do not explicitly account for aerosol optical effects and surface reflectance anisotropy that vary with space and time. In traditional retrieval, aerosols' effects are often considered as cloud. However, China has complicated aerosols type and aerosol loading. Their optical properties may be very different from the cloud. Furthermore, China has undergone big changes in land use type in recent 10 years. Traditional climatology surface reflectance data may not have representation. In order to study spatial-temporal variation of and influences of these two factors on variations and trends, we use an improved retrieval method of VCDs over China, called the POMINO, based on measurements from the Ozone Monitoring Instrument (OMI), and we compare the results of without aerosol, without surface reflectance treatments and without both to the original POMINO product from 2005 to 2015. Furthermore, we will study correspondent spatial-temporal variations of aerosols, represented by MODIS aerosol optical depth (AOD) data and CALIOP extinction data; surface reflectance, represented by MODIS bidirectional reflectance distribution function (BRDF) data.
Perlman, Christopher
2018-01-01
Mental Health has been known to vary geographically. Different rates of utilization of mental health services in local areas reflect geographic variation of mental health and complexity of health care. Variations and inequalities in how the health care system addresses risks are two critical issues for addressing population mental health. This study examines these issues by analyzing the utilization of mental health services in Toronto at the neighbourhood level. We adopted a shared component spatial modeling approach that allows simultaneous analysis of two main health service utilizations: doctor visits and hospitalizations related to mental health conditions. Our results reflect a geographic variation of both types of mental health service utilization across neighbourhoods in Toronto. We identified hot and cold spots of mental health risks that are common to both or specific to only one type of health service utilization. Based on the evidence found, we discuss intervention strategies, focusing on the hotspots and provision of health services about doctors and hospitals, to improve mental health for the neighbourhoods. Limitations of the study and further research directions are also discussed. PMID:29587426
Volis, Sergei; Ormanbekova, Danara; Yermekbayev, Kanat; Song, Minshu; Shulgina, Irina
2015-01-01
Detecting local adaptation and its spatial scale is one of the most important questions of evolutionary biology. However, recognition of the effect of local selection can be challenging when there is considerable environmental variation across the distance at the whole species range. We analyzed patterns of local adaptation in emmer wheat, Triticum dicoccoides, at two spatial scales, small (inter-population distance less than one km) and large (inter-population distance more than 50 km) using several approaches. Plants originating from four distinct habitats at two geographic scales (cold edge, arid edge and two topographically dissimilar core locations) were reciprocally transplanted and their success over time was measured as 1) lifetime fitness in a year of planting, and 2) population growth four years after planting. In addition, we analyzed molecular (SSR) and quantitative trait variation and calculated the QST/FST ratio. No home advantage was detected at the small spatial scale. At the large spatial scale, home advantage was detected for the core population and the cold edge population in the year of introduction via measuring life-time plant performance. However, superior performance of the arid edge population in its own environment was evident only after several generations via measuring experimental population growth rate through genotyping with SSRs allowing counting the number of plants and seeds per introduced genotype per site. These results highlight the importance of multi-generation surveys of population growth rate in local adaptation testing. Despite predominant self-fertilization of T. dicoccoides and the associated high degree of structuring of genetic variation, the results of the QST - FST comparison were in general agreement with the pattern of local adaptation at the two spatial scales detected by reciprocal transplanting.
Detto, Matteo; Muller-Landau, Helene C; Mascaro, Joseph; Asner, Gregory P
2013-01-01
An understanding of the spatial variability in tropical forest structure and biomass, and the mechanisms that underpin this variability, is critical for designing, interpreting, and upscaling field studies for regional carbon inventories. We investigated the spatial structure of tropical forest vegetation and its relationship to the hydrological network and associated topographic structure across spatial scales of 10-1000 m using high-resolution maps of LiDAR-derived mean canopy profile height (MCH) and elevation for 4930 ha of tropical forest in central Panama. MCH was strongly associated with the hydrological network: canopy height was highest in areas of positive convexity (valleys, depressions) close to channels draining 1 ha or more. Average MCH declined strongly with decreasing convexity (transition to ridges, hilltops) and increasing distance from the nearest channel. Spectral analysis, performed with wavelet decomposition, showed that the variance in MCH had fractal similarity at scales of ∼30-600 m, and was strongly associated with variation in elevation, with peak correlations at scales of ∼250 m. Whereas previous studies of topographic correlates of tropical forest structure conducted analyses at just one or a few spatial grains, our study found that correlations were strongly scale-dependent. Multi-scale analyses of correlations of MCH with slope, aspect, curvature, and Laplacian convexity found that MCH was most strongly related to convexity measured at scales of 20-300 m, a topographic variable that is a good proxy for position with respect to the hydrological network. Overall, our results support the idea that, even in these mesic forests, hydrological networks and associated topographical variation serve as templates upon which vegetation is organized over specific ranges of scales. These findings constitute an important step towards a mechanistic understanding of these patterns, and can guide upscaling and downscaling.
Hjort, Jan; Hugg, Timo T; Antikainen, Harri; Rusanen, Jarmo; Sofiev, Mikhail; Kukkonen, Jaakko; Jaakkola, Maritta S; Jaakkola, Jouni J K
2016-05-01
Despite the recent developments in physically and chemically based analysis of atmospheric particles, no models exist for resolving the spatial variability of pollen concentration at urban scale. We developed a land use regression (LUR) approach for predicting spatial fine-scale allergenic pollen concentrations in the Helsinki metropolitan area, Finland, and evaluated the performance of the models against available empirical data. We used grass pollen data monitored at 16 sites in an urban area during the peak pollen season and geospatial environmental data. The main statistical method was generalized linear model (GLM). GLM-based LURs explained 79% of the spatial variation in the grass pollen data based on all samples, and 47% of the variation when samples from two sites with very high concentrations were excluded. In model evaluation, prediction errors ranged from 6% to 26% of the observed range of grass pollen concentrations. Our findings support the use of geospatial data-based statistical models to predict the spatial variation of allergenic grass pollen concentrations at intra-urban scales. A remote sensing-based vegetation index was the strongest predictor of pollen concentrations for exposure assessments at local scales. The LUR approach provides new opportunities to estimate the relations between environmental determinants and allergenic pollen concentration in human-modified environments at fine spatial scales. This approach could potentially be applied to estimate retrospectively pollen concentrations to be used for long-term exposure assessments. Hjort J, Hugg TT, Antikainen H, Rusanen J, Sofiev M, Kukkonen J, Jaakkola MS, Jaakkola JJ. 2016. Fine-scale exposure to allergenic pollen in the urban environment: evaluation of land use regression approach. Environ Health Perspect 124:619-626; http://dx.doi.org/10.1289/ehp.1509761.
Hou, Ying; Li, Bo; Müller, Felix; Chen, Weiping
2016-11-01
Watersheds provide multiple ecosystem services. Ecosystem service assessment is a promising approach to investigate human-environment interaction at the watershed scale. The spatial characteristics of ecosystem services are closely related to land use statuses in human-dominated watersheds. This study aims to investigate the effects of land use on the spatial variations of ecosystem services at the Dianchi Lake watershed in Southwest China. We investigated the spatial variations of six ecosystem services-food supply, net primary productivity (NPP), habitat quality, evapotranspiration, water yield, and nitrogen retention. These services were selected based on their significance at the Dianchi Lake watershed and the availability of their data. The quantification of these services was based on modeling, value transference, and spatial analysis in combination with biophysical and socioeconomic data. Furthermore, we calculated the values of ecosystem services provided by different land use types and quantified the correlations between ecosystem service values and land use area proportions. The results show considerable spatial variations in the six ecosystem services associated with land use influences in the Dianchi Lake watershed. The cropland and forest land use types had predominantly positive influences on food productivity and NPP, respectively. The rural residential area and forest land use types reduced and enhanced habitat quality, respectively; these influences were identical to those of evapotranspiration. Urban area and rural residential area exerted significantly positive influences on water yield. In contrast, water yield was negatively correlated with forest area proportion. Finally, cropland and forest had significantly positive and negative influences, respectively, on nitrogen retention. Our study emphasizes the importance of consideration of the influences from land use composition and distribution on ecosystem services for managing the ecosystems of human-dominated watersheds.
Force Balance at the Magnetopause Determined with MMS: Application to Flux Transfer Events
NASA Technical Reports Server (NTRS)
Zhao, C.; Russell, C. T.; Strangeway, R. J.; Petrinec, S. M.; Paterson, W. R.; Zhou, M.; Anderson, B. J.; Baumjohann, W.; Bromund, K. R.; Chutter, M.;
2016-01-01
The Magnetospheric Multiscale mission (MMS) consists of four identical spacecraft forming a closely separated (less than or equal to 10 km) and nearly regular tetrahedron. This configuration enables the decoupling of spatial and temporal variations and allows the calculation of the spatial gradients of plasma and electromagnetic field quantities. We make full use of the well cross-calibrated MMS magnetometers and fast plasma instruments measurements to calculate both the magnetic and plasma forces in flux transfer events (FTEs) and evaluate the relative contributions of different forces to the magnetopause momentum variation. This analysis demonstrates that some but not all FTEs, consistent with previous studies, are indeed force-free structures in which the magnetic pressure force balances the magnetic curvature force. Furthermore, we contrast these events with FTE events that have non-force-free signatures.
NASA Technical Reports Server (NTRS)
Braun, M. J.; Mullen, R. L.; Hendricks, R. C.
1984-01-01
The analysis presented herein deals with the evaluation of the pressure, velocity, and temperature profiles in a finite-length plane journal bearing. The geometry of the case under study consists of a spatially tilted shaft. The two-dimensional Reynolds equation accounts for the variation of the clearance gap h with x and z and is used to model the pressure field. The latter is solved for a variety of shaft tilt angles and then used to calculate the two-dimensional flow field. Finally, the flow field is used in the energy equation to solve for the film temperature profile, when the effect of viscous dissipation is taken into account.
Spatial and seasonal variations of polycyclic aromatic hydrocarbons in Haihe Plain, China.
Wang, Rong; Cao, Hongying; Li, Wei; Wang, Wei; Wang, Wentao; Zhang, Liwen; Liu, Jiumeng; Ouyang, Huiling; Tao, Shu
2011-05-01
A dynamic fugacity model was developed to simulate the spatial and seasonal variations of PAHs in Haihe Plain, China. The calculated and measured concentrations exhibited good consistency in magnitude with deviations within a factor of 4 in air and 2 in soil. The spatial distributions of PAHs in air were mainly controlled by emission while the seasonal variations were dominated by emission and gas-particle partition. In soil, the spatial distributions of PAHs were controlled by the soil organic carbon content while the seasonal variations were insignificant. The severest soil contamination was observed in Shanxi and followed by the southwest of Hebei province. Transfer fluxes of total PAHs between air and soil were calculated. The spatial distribution of air-to-soil flux was closely related to the landcover while the soil-to-air flux changed with soil organic matter content. Monte Carlo simulation was done to evaluate the uncertainty of the estimated results in air. Copyright © 2011 Elsevier Ltd. All rights reserved.
The effects of oil spills on marine fish: Implications of spatial variation in natural mortality.
Langangen, Ø; Olsen, E; Stige, L C; Ohlberger, J; Yaragina, N A; Vikebø, F B; Bogstad, B; Stenseth, N C; Hjermann, D Ø
2017-06-15
The effects of oil spills on marine biological systems are of great concern, especially in regions with high biological production of harvested resources such as in the Northeastern Atlantic. The scientific studies of the impact of oil spills on fish stocks tend to ignore that spatial patterns of natural mortality may influence the magnitude of the impact over time. Here, we first illustrate how spatial variation in natural mortality may affect the population impact by considering a thought experiment. Second, we consider an empirically based example of Northeast Arctic cod to extend the concept to a realistic setting. Finally, we present a scenario-based investigation of how the degree of spatial variation in natural mortality affects the impact over a gradient of oil spill sizes. Including the effects of spatial variations in natural mortality tends to widen the impact distribution, hence increasing the probability of both high and low impact events. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Change of spatial information under rescaling: A case study using multi-resolution image series
NASA Astrophysics Data System (ADS)
Chen, Weirong; Henebry, Geoffrey M.
Spatial structure in imagery depends on a complicated interaction between the observational regime and the types and arrangements of entities within the scene that the image portrays. Although block averaging of pixels has commonly been used to simulate coarser resolution imagery, relatively little attention has been focused on the effects of simple rescaling on spatial structure and the explanation and a possible solution to the problem. Yet, if there are significant differences in spatial variance between rescaled and observed images, it may affect the reliability of retrieved biogeophysical quantities. To investigate these issues, a nested series of high spatial resolution digital imagery was collected at a research site in eastern Nebraska in 2001. An airborne Kodak DCS420IR camera acquired imagery at three altitudes, yielding nominal spatial resolutions ranging from 0.187 m to 1 m. The red and near infrared (NIR) bands of the co-registered image series were normalized using pseudo-invariant features, and the normalized difference vegetation index (NDVI) was calculated. Plots of grain sorghum planted in orthogonal crop row orientations were extracted from the image series. The finest spatial resolution data were then rescaled by averaging blocks of pixels to produce a rescaled image series that closely matched the spatial resolution of the observed image series. Spatial structures of the observed and rescaled image series were characterized using semivariogram analysis. Results for NDVI and its component bands show, as expected, that decreasing spatial resolution leads to decreasing spatial variability and increasing spatial dependence. However, compared to the observed data, the rescaled images contain more persistent spatial structure that exhibits limited variation in both spatial dependence and spatial heterogeneity. Rescaling via simple block averaging fails to consider the effect of scene object shape and extent on spatial information. As the features portrayed by pixels are equally weighted regardless of the shape and extent of the underlying scene objects, the rescaled image retains more of the original spatial information than would occur through direct observation at a coarser sensor spatial resolution. In contrast, for the observed images, due to the effect of the modulation transfer function (MTF) of the imaging system, high frequency features like edges are blurred or lost as the pixel size increases, resulting in greater variation in spatial structure. Successive applications of a low-pass spatial convolution filter are shown to mimic a MTF. Accordingly, it is recommended that such a procedure be applied prior to rescaling by simple block averaging, if insufficient image metadata exist to replicate the net MTF of the imaging system, as might be expected in land cover change analysis studies using historical imagery.
Liu, Haiwei; Wang, Haiyun; Zhang, Yan; Yuan, Jumin; Peng, Yaodong; Li, Xiuchun; Shi, Yi; He, Kuanxin; Zhang, Qiming
2018-06-01
The heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in the surface soils of tobacco (Nicotiana tabacum L.) fields in Jiangxi Province were analyzed, and the mean heavy metal concentrations were 3.55, 0.19, 25.89, 14.96, 0.25, 10.89, 27.80, and 44.00 mg/kg, respectively. Spatial distribution analysis showed that the highest concentrations were recorded in the north-western, south-western, and mid-eastern parts of the study area. The index of geo-accumulation and pollution index indicated modest enrichment with Cd and Hg, which were the only two metals posing a potentially high ecological risk to the local agricultural environment. The health risk assessment showed no considerable non-carcinogenic or carcinogenic risks for children and adults from these elements. The principal component analysis (PCA) and cluster analysis (CA) found that the variations in the Cr and Ni concentrations were largely on account of the soil parent rocks, but the As, Cd, Cu, and Hg variations in the soil were largely owing to agricultural practices of years. However, the main factor influencing Pb and Zn was atmospheric deposition.
[Design and implementation of Geographical Information System on prevention and control of cholera].
Li, Xiu-jun; Fang, Li-qun; Wang, Duo-chun; Wang, Lu-xi; Li, Ya-pin; Li, Yan-li; Yang, Hong; Kan, Biao; Cao, Wu-chun
2012-04-01
To build the Geographical Information System (GIS) database for prevention and control of cholera programs as well as using management analysis and function demonstration to show the spatial attribute of cholera. Data from case reporting system regarding diarrhoea, vibrio cholerae, serotypes of vibrio cholerae at the surveillance spots and seafoods, as well as surveillance data on ambient environment and climate were collected. All the data were imported to system database to show the incidence of vibrio cholerae in different provinces, regions and counties to support the spatial analysis through the spatial analysis of GIS. The epidemic trends of cholera, seasonal characteristics of the cholera and the variation of the vibrio cholerae with times were better understood. Information on hotspots, regions and time of epidemics was collected, and helpful in providing risk prediction on the incidence of vibrio cholerae. The exploitation of the software can predict and simulate the spatio-temporal risks, so as to provide guidance for the prevention and control of the disease.
NASA Technical Reports Server (NTRS)
Franklin, Rima B.; Blum, Linda K.; McComb, Alison C.; Mills, Aaron L.
2002-01-01
Small-scale variations in bacterial abundance and community structure were examined in salt marsh sediments from Virginia's eastern shore. Samples were collected at 5 cm intervals (horizontally) along a 50 cm elevation gradient, over a 215 cm horizontal transect. For each sample, bacterial abundance was determined using acridine orange direct counts and community structure was analyzed using randomly amplified polymorphic DNA fingerprinting of whole-community DNA extracts. A geostatistical analysis was used to determine the degree of spatial autocorrelation among the samples, for each variable and each direction (horizontal and vertical). The proportion of variance in bacterial abundance that could be accounted for by the spatial model was quite high (vertical: 60%, horizontal: 73%); significant autocorrelation was found among samples separated by 25 cm in the vertical direction and up to 115 cm horizontally. In contrast, most of the variability in community structure was not accounted for by simply considering the spatial separation of samples (vertical: 11%, horizontal: 22%), and must reflect variability from other parameters (e.g., variation at other spatial scales, experimental error, or environmental heterogeneity). Microbial community patch size based upon overall similarity in community structure varied between 17 cm (vertical) and 35 cm (horizontal). Overall, variability due to horizontal position (distance from the creek bank) was much smaller than that due to vertical position (elevation) for both community properties assayed. This suggests that processes more correlated with elevation (e.g., drainage and redox potential) vary at a smaller scale (therefore producing smaller patch sizes) than processes controlled by distance from the creek bank. c2002 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.
Fine-Scale Analysis Reveals Cryptic Landscape Genetic Structure in Desert Tortoises
Latch, Emily K.; Boarman, William I.; Walde, Andrew; Fleischer, Robert C.
2011-01-01
Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately. PMID:22132143
Fine-scale analysis reveals cryptic landscape genetic structure in desert tortoises.
Latch, Emily K; Boarman, William I; Walde, Andrew; Fleischer, Robert C
2011-01-01
Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately.
NASA Astrophysics Data System (ADS)
Jiang, H.; Lin, T.
2017-12-01
Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.
Robust geostatistical analysis of spatial data
NASA Astrophysics Data System (ADS)
Papritz, A.; Künsch, H. R.; Schwierz, C.; Stahel, W. A.
2012-04-01
Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outlying observations may results from errors (e.g. in data transcription) or from local perturbations in the processes that are responsible for a given pattern of spatial variation. As an example, the spatial distribution of some trace metal in the soils of a region may be distorted by emissions of local anthropogenic sources. Outliers affect the modelling of the large-scale spatial variation, the so-called external drift or trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) [2] proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) [1] for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation. Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and unsampled locations and kriging variances. The method has been implemented in an R package. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis of the Tarrawarra soil moisture data set [3].
NASA Astrophysics Data System (ADS)
Manson, F. J.; Loneragan, N. R.; Phinn, S. R.
2003-07-01
An assessment of the changes in the distribution and extent of mangroves within Moreton Bay, southeast Queensland, Australia, was carried out. Two assessment methods were evaluated: spatial and temporal pattern metrics analysis, and change detection analysis. Currently, about 15,000 ha of mangroves are present in Moreton Bay. These mangroves are important ecosystems, but are subject to disturbance from a number of sources. Over the past 25 years, there has been a loss of more than 3800 ha, as a result of natural losses and mangrove clearing (e.g. for urban and industrial development, agriculture and aquaculture). However, areas of new mangroves have become established over the same time period, offsetting these losses to create a net loss of about 200 ha. These new mangroves have mainly appeared in the southern bay region and the bay islands, particularly on the landward edge of existing mangroves. In addition, spatial patterns and species composition of mangrove patches have changed. The pattern metrics analysis provided an overview of mangrove distribution and change in the form of single metric values, while the change detection analysis gave a more detailed and spatially explicit description of change. An analysis of the effects of spatial scales on the pattern metrics indicated that they were relatively insensitive to scale at spatial resolutions less than 50 m, but that most metrics became sensitive at coarser resolutions, a finding which has implications for mapping of mangroves based on remotely sensed data.
Ma, Qi Yun; Zhang, Ji Quan; Lai, Quan; Zhang, Feng; Dong, Zhen Hua; A, Lu Si
2017-06-18
Fourteen extreme climatic indices related with main regional meteorological disasters and vegetation growth were calculated based on daily data from 13 meteorological stations during 1960-2014 in Songnen Grassland, Northeast China. Then, the variation trend and the spatial and temporal patterns of climatic extreme events were analyzed by using regression analysis, break trend analy-sis, Mann-Kendall test, Sen's slope estimator and moving t-test method. The results indicated that summer days (SU25), warm days (TX90P), warm nights (TN90P) and warm spell duration (WSDI) representing extremely high temperatures showed significant increasing trends (P<0.05). Meanwhile, frost days (FD0), cold days (TX10P), cold nights (TN10P) and cold spell duration indicator (CSDI) representing extremely low temperatures showed obviously decreasing trends. The magnitudes of changes in cold indices (FD0, TX10P, TN10P and CSDI) were clearly greater than those of warm indices (SU25, TX90P, TN90P and WSDI), and that changes in night indices were larger than those of day indices. Regional climate warming trend was obvious from 1970 to 2009, and the most occurrences of the abrupt changes in these indices were identified in this period. The extreme precipitation indices did not show obvious trend, in general, SDII and CDD experienced a slightly decreasing trend while RX5D, R95P, PRCPTOT and CWD witnessed a mildly increasing trend. It may be concluded that regional climate changed towards warming and slightly wetting in Songnen Grassland. The most sensitive region for extreme temperature was distributed in the south and north region. Additionally, the extreme temperature indices showed clearly spatial difference between the south and the north. As for the spatial variations of extreme precipitation indices, the climate could be characterized by becoming wetter in northern region, and getting drier in southern region, especially in southwestern region with a high drought risk.
Spatial evolutionary epidemiology of spreading epidemics
2016-01-01
Most spatial models of host–parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. PMID:27798295
Spatial evolutionary epidemiology of spreading epidemics.
Lion, S; Gandon, S
2016-10-26
Most spatial models of host-parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. © 2016 The Author(s).
NASA Astrophysics Data System (ADS)
Yue, H.; Liu, Y.
2018-04-01
As a key factor affecting the biogeochemical cycle of human existence, terrestrial vegetation is vulnerable to natural environment and human activities, with obvious temporal and spatial characteristics. The change of vegetation cover will affect the ecological balance and environmental quality to a great extent. Therefore, the research on the causes and influencing factors of vegetation cover has become the focus of attention of scholars at home and abroad. In the evolution of human activities and natural environment, the vegetation coverage in Shaanxi has changed accordingly. Using MODIS/NDVI 2000-2014 time series data, using the method of raster pixel trend analysis, stability evaluation, rescaled range analysis and correlation analysis, the climatic factors in Shaanxi province were studied in the near 15 years vegetation spatial and temporal variation and influence of vegetation NDVI changes. The results show that NDVI in Shaanxi province in the near 15 years increased by 0.081, the increase of NDVI in Northern Shaanxi was obvious, and negative growth was found in some areas of Guanzhong, southern Shaanxi NDVI overall still maintained at a high level; the trend of vegetation change in Shaanxi province has obvious spatial differences, most of the province is a slight tendency to improve vegetation, there are many obvious improvement areas in Northern Shaanxi Province. Guanzhong area vegetation area decreased, the small range of variation of vegetation in Shaanxi province; the most stable areas are mainly concentrated in the southern, southern Yanan, Yulin, Xi'an area of Weinan changed greatly; Shaanxi Province in recent 15 a, the temperature and precipitation have shown an increasing trend, and the vegetation NDVI is more closely related to the average annual rainfall, with increase of 0.48 °C/10 years and 69.5 mm per year.
Smith, Amanda L.; Benazzi, Stefano; Ledogar, Justin A.; Tamvada, Kelli; Smith, Leslie C. Pryor; Weber, Gerhard W.; Spencer, Mark A.; Dechow, Paul C.; Grosse, Ian R.; Ross, Callum F.; Richmond, Brian G.; Wright, Barth W.; Wang, Qian; Byron, Craig; Slice, Dennis E.; Strait, David S.
2014-01-01
In a broad range of evolutionary studies, an understanding of intraspecific variation is needed in order to contextualize and interpret the meaning of variation between species. However, mechanical analyses of primate crania using experimental or modeling methods typically encounter logistical constraints that force them to rely on data gathered from only one or a few individuals. This results in a lack of knowledge concerning the mechanical significance of intraspecific shape variation that limits our ability to infer the significance of interspecific differences. This study uses geometric morphometric methods (GM) and finite element analysis (FEA) to examine the biomechanical implications of shape variation in chimpanzee crania, thereby providing a comparative context in which to interpret shape-related mechanical variation between hominin species. Six finite element models (FEMs) of chimpanzee crania were constructed from CT scans following shape-space Principal Component Analysis (PCA) of a matrix of 709 Procrustes coordinates (digitized onto 21 specimens) to identify the individuals at the extremes of the first three principal components. The FEMs were assigned the material properties of bone and were loaded and constrained to simulate maximal bites on the P3 and M2. Resulting strains indicate that intraspecific cranial variation in morphology is associated with quantitatively high levels of variation in strain magnitudes, but qualitatively little variation in the distribution of strain concentrations. Thus, interspecific comparisons should include considerations of the spatial patterning of strains rather than focus only their magnitude. PMID:25529239
Spatial correlation of auroral zone geomagnetic variations
NASA Astrophysics Data System (ADS)
Jackel, B. J.; Davalos, A.
2016-12-01
Magnetic field perturbations in the auroral zone are produced by a combination of distant ionospheric and local ground induced currents. Spatial and temporal structure of these currents is scientifically interesting and can also have a significant influence on critical infrastructure.Ground-based magnetometer networks are an essential tool for studying these phenomena, with the existing complement of instruments in Canada providing extended local time coverage. In this study we examine the spatial correlation between magnetic field observations over a range of scale lengths. Principal component and canonical correlation analysis are used to quantify relationships between multiple sites. Results could be used to optimize network configurations, validate computational models, and improve methods for empirical interpolation.
NASA Astrophysics Data System (ADS)
Follum, Michael L.; Niemann, Jeffrey D.; Parno, Julie T.; Downer, Charles W.
2018-05-01
Frozen ground can be important to flood production and is often heterogeneous within a watershed due to spatial variations in the available energy, insulation by snowpack and ground cover, and the thermal and moisture properties of the soil. The widely used continuous frozen ground index (CFGI) model is a degree-day approach and identifies frozen ground using a simple frost index, which varies mainly with elevation through an elevation-temperature relationship. Similarly, snow depth and its insulating effect are also estimated based on elevation. The objective of this paper is to develop a model for frozen ground that (1) captures the spatial variations of frozen ground within a watershed, (2) allows the frozen ground model to be incorporated into a variety of watershed models, and (3) allows application in data sparse environments. To do this, we modify the existing CFGI method within the gridded surface subsurface hydrologic analysis watershed model. Among the modifications, the snowpack and frost indices are simulated by replacing air temperature (a surrogate for the available energy) with a radiation-derived temperature that aims to better represent spatial variations in available energy. Ground cover is also included as an additional insulator of the soil. Furthermore, the modified Berggren equation, which accounts for soil thermal conductivity and soil moisture, is used to convert the frost index into frost depth. The modified CFGI model is tested by application at six test sites within the Sleepers River experimental watershed in Vermont. Compared to the CFGI model, the modified CFGI model more accurately captures the variations in frozen ground between the sites, inter-annual variations in frozen ground depths at a given site, and the occurrence of frozen ground.
Spatial trends in S and Cl in ash leachates of the May 18th, 1980 eruption of Mt. St Helens
NASA Astrophysics Data System (ADS)
Ayris, Paul M.; Delmelle, Pierre; Durant, Adam J.; Damby, David E.; Maters, Elena C.
2014-05-01
It has long been known that surficial deposits of salts and acids on volcanic ash particles derive from interactions of ash with sulphur and halide species within the eruption plume and volcanic cloud. These compounds are mobilised as ash particles are wetted, and beneficial or detrimental environmental and health impacts may be induced where the most concentrated solutions are produced. However, limited mechanistic understanding of gas-ash interactions currently precludes prediction of the spatial distribution or variation in leachate chemistry and concentration following an eruption. Sampling and leachate analysis of freshly-fallen ash therefore offers the sole method by which such variations can be observed. Previous ash leachate studies often involve a limited number of ash samples, and utilise a 'one-dimensional' analysis that considers variation in terms of absolute distance from the source volcano. Here, we demonstrate that extensive sampling and a 'two-dimensional' analysis can uncover more complex spatial trends. We compiled over 358 leachate compositions from the May 18th 1980 eruption of Mt. St. Helens. Of the water-extracted leachates, only 95 compositions from ash sampled at 45 localities between 35 and 1129 km from the volcano are sufficiently documented to be retrospectively comparable. To consider the effects of intra-deposit variability, we calculated average concentrations of leachate data within 11×22 km grid cells across the region, and defined a data quality parameter to reflect confidence in the derived values. To investigate any dependence of leachate composition on the grain size distribution, we generated an interpolated map of geometric specific surface area variation across the deposit, normalising ash leachate data to the calculated specific surface area at the corresponding sampling location. The data treatment identifies S and Cl enrichments in proximal blast deposits; relatively constant Cl concentrations across the ashfall deposits; and a core region of depleted S concentrations in ashfall deposits between 240 and 400 km from the volcano, coinciding with the distal thickening of the deposit attributed to particle aggregation and enhanced fallout. Blast deposit enrichments can be attributed to pre-eruptive uptake of SO2 and HCl gases within the cryptodome, while ashfall deposit trends could reflect differences in the rates of HCl and SO2 uptake by ash, modified by in-plume aggregation processes. However, to validate and interpret such trends with greater confidence would have required a greater spatial density and temporal resolution of sampling, with comprehensive characterisation of the recovered ash and the surrounding deposit. In the future, rigorous study and sampling of equivalent extent to that in the aftermath of the historic Mt. St. Helens eruption is likely required to extend insight into processes affecting the spatial distribution of leachate chemistry.
Using demography and movement behavior to predict range expansion of the southern sea otter.
Tinker, M.T.; Doak, D.F.; Estes, J.A.
2008-01-01
In addition to forecasting population growth, basic demographic data combined with movement data provide a means for predicting rates of range expansion. Quantitative models of range expansion have rarely been applied to large vertebrates, although such tools could be useful for restoration and management of many threatened but recovering populations. Using the southern sea otter (Enhydra lutris nereis) as a case study, we utilized integro-difference equations in combination with a stage-structured projection matrix that incorporated spatial variation in dispersal and demography to make forecasts of population recovery and range recolonization. In addition to these basic predictions, we emphasize how to make these modeling predictions useful in a management context through the inclusion of parameter uncertainty and sensitivity analysis. Our models resulted in hind-cast (1989–2003) predictions of net population growth and range expansion that closely matched observed patterns. We next made projections of future range expansion and population growth, incorporating uncertainty in all model parameters, and explored the sensitivity of model predictions to variation in spatially explicit survival and dispersal rates. The predicted rate of southward range expansion (median = 5.2 km/yr) was sensitive to both dispersal and survival rates; elasticity analysis indicated that changes in adult survival would have the greatest potential effect on the rate of range expansion, while perturbation analysis showed that variation in subadult dispersal contributed most to variance in model predictions. Variation in survival and dispersal of females at the south end of the range contributed most of the variance in predicted southward range expansion. Our approach provides guidance for the acquisition of further data and a means of forecasting the consequence of specific management actions. Similar methods could aid in the management of other recovering populations.
Modeling α- and β-diversity in a tropical forest from remotely sensed and spatial data
NASA Astrophysics Data System (ADS)
Hernández-Stefanoni, J. Luis; Gallardo-Cruz, J. Alberto; Meave, Jorge A.; Rocchini, Duccio; Bello-Pineda, Javier; López-Martínez, J. Omar
2012-10-01
Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and can therefore be extremely useful for estimating both species richness and spatial variation of species composition (α- and β-diversity). An essential step to map such attributes is to identify and understand their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining α- and β-diversity, and evaluated the relative roles of productivity-habitat structure and spatial variables in explaining observed patterns of α- and β-diversity by using a Principal Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed and field data, in order to map α- and β-diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure. These two procedures integrate the relationship of species richness and spatial species turnover both with remotely sensed data and spatial structure. The empirical models so obtained can be used to predict species richness and variation in species composition, and they can be regarded as valuable tools not only for identifying areas with high local species richness (α-diversity), but also areas with high species turnover (β-diversity). Ultimately, information obtained in this way can help maximize the number of species preserved in a landscape.
Variation in mineral content of red maple sap across an atmospheric deposition gradient
DOE Office of Scientific and Technical Information (OSTI.GOV)
McCormick, L.H.
1997-11-01
Xylem sap was collected from red maple (Acer rubrum L.) trees during the spring of 1988 and 1989 at seven forest sites along an atmospheric deposition gradient in north central Pennsylvania and analyzed for pH and twelve mineral constituents. The objectives of the study were to examine the sources and patterns of variation in red maple sap chemistry across an atmospheric deposition gradient and to assess the feasibility of using sap analysis as an indicator of nutrient bioavailability. For most sap constituents, there was considerable spatial and temporal variation in concentration. Sources of variation included within and between site variation,more » date, and year of collection. The nature and extent of variation varied for different constituents. Site differences were similar in 1988 and 1989 for most sap constituents and for some constituents corresponded with differences in soil levels.« less
Jia, Xiaoxu; Xie, Baoni; Shao, Ming’an; Zhao, Chunlei
2015-01-01
Clarifying spatial variations in aboveground net primary productivity (ANPP) and precipitation-use efficiency (PUE) of grasslands is critical for effective prediction of the response of terrestrial ecosystem carbon and water cycle to future climate change. Though the combination use of remote sensing products and in situ ANPP measurements, we quantified the effects of climatic [mean annual precipitation (MAP) and precipitation seasonal distribution (PSD)], biotic [leaf area index (LAI)] and abiotic [slope gradient, aspect, soil water storage (SWS) and other soil physical properties] factors on the spatial variations in ANPP and PUE across different grassland types (i.e., meadow steppe, typical steppe and desert steppe) in the Loess Plateau. Based on the study, ANPP increased exponentially with MAP for the entire temperate grassland; suggesting that PUE increased with increasing MAP. Also PSD had a significant effect on ANPP and PUE; where more even PSD favored higher ANPP and PUE. Then MAP, more than PSD, explained spatial variations in typical steppe and desert steppe. However, PSD was the dominant driving factor of spatial variations in ANPP of meadow steppe. This suggested that in terms of spatial variations in ANPP of meadow steppe, change in PSD due to climate change was more important than that in total annual precipitation. LAI explained 78% of spatial PUE in the entire Loess Plateau temperate grassland. As such, LAI was the primary driving factor of spatial variations in PUE. Although the effect of SWS on ANPP and PUE was significant, it was nonetheless less than that of precipitation and vegetation. We therefore concluded that changes in vegetation structure and consequently in LAI and/or altered pattern of seasonal distribution of rainfall due to global climate change could significantly influence ecosystem carbon and water cycle in temperate grasslands. PMID:26295954
Jia, Xiaoxu; Xie, Baoni; Shao, Ming'an; Zhao, Chunlei
2015-01-01
Clarifying spatial variations in aboveground net primary productivity (ANPP) and precipitation-use efficiency (PUE) of grasslands is critical for effective prediction of the response of terrestrial ecosystem carbon and water cycle to future climate change. Though the combination use of remote sensing products and in situ ANPP measurements, we quantified the effects of climatic [mean annual precipitation (MAP) and precipitation seasonal distribution (PSD)], biotic [leaf area index (LAI)] and abiotic [slope gradient, aspect, soil water storage (SWS) and other soil physical properties] factors on the spatial variations in ANPP and PUE across different grassland types (i.e., meadow steppe, typical steppe and desert steppe) in the Loess Plateau. Based on the study, ANPP increased exponentially with MAP for the entire temperate grassland; suggesting that PUE increased with increasing MAP. Also PSD had a significant effect on ANPP and PUE; where more even PSD favored higher ANPP and PUE. Then MAP, more than PSD, explained spatial variations in typical steppe and desert steppe. However, PSD was the dominant driving factor of spatial variations in ANPP of meadow steppe. This suggested that in terms of spatial variations in ANPP of meadow steppe, change in PSD due to climate change was more important than that in total annual precipitation. LAI explained 78% of spatial PUE in the entire Loess Plateau temperate grassland. As such, LAI was the primary driving factor of spatial variations in PUE. Although the effect of SWS on ANPP and PUE was significant, it was nonetheless less than that of precipitation and vegetation. We therefore concluded that changes in vegetation structure and consequently in LAI and/or altered pattern of seasonal distribution of rainfall due to global climate change could significantly influence ecosystem carbon and water cycle in temperate grasslands.
Satellite-based studies of maize yield spatial variations and their causes in China
NASA Astrophysics Data System (ADS)
Zhao, Y.
2013-12-01
Maize production in China has been expanding significantly in the past two decades, but yield has become relatively stagnant in the past few years, and needs to be improved to meet increasing demand. Multiple studies found that the gap between potential and actual yield of maize is as large as 40% to 60% of yield potential. Although a few major causes of yield gap have been qualitatively identified with surveys, there has not been spatial analysis aimed at quantifying relative importance of specific biophysical and socio-economic causes, information which would be useful for targeting interventions. This study analyzes the causes of yield variation at field and village level in Quzhou county of North China Plain (NCP). We combine remote sensing and crop modeling to estimate yields in 2009-2012, and identify fields that are consistently high or low yielding. To establish the relationship between yield and potential factors, we gather data on those factors through a household survey. We select targeted survey fields such that not only both extremes of yield distribution but also all soil texture categories in the county is covered. Our survey assesses management and biophysical factors as well as social factors such as farmers' access to agronomic knowledge, which is approximated by distance to the closest demonstration plot or 'Science and technology backyard'. Our survey covers 10 townships, 53 villages and 180 fields. Three to ten farmers are surveyed depending on the amount of variation present among sub pixels of each field. According to survey results, we extract the amount of variation within as well as between villages and or soil type. The higher within village or within field variation, the higher importance of management factors. Factors such as soil type and access to knowledge are more represented by between village variation. Through regression and analysis of variance, we gain more quantitative and thorough understanding of causes to yield variation at village scale, which further explains the gap between average and highest achieved yield.
Subramanian, Dharaneedharan; Ramalingam, Rajkumar; Karuppasamy, Radhakrishnan; Subramanian, Thanga Leela; Chellam, Balasundaram; Rajan, Koilmani Emmanuvel
2012-10-03
In the present study, we observed variations in the expression pattern of proteins isolated from the telencephalon of goldfish (Carassius auratus). The expression of a 28 kDa protein was elevated in the individuals trained in a spatial task when compared with the untrained individuals. The ∼28 kDa protein was analyzed using liquid chromatography and mass spectrometry; further, the data were analyzed using the MASCOT search engine. The analysis showed that the ∼28 kDa protein is a β form of 14-3-3 protein with 35.1% identity. In addition, the semiquantitative PCR confirmed the variation in the expression of 14-3-3 between the trained and the untrained groups. Subsequently, we examined the effect of upregulation of 14-3-3 (β) in the neurotransmitters; that is, serotonin (5-hydroxytryptamine, 5-HT) and dopamine (DA). Notably, the level of 5-HT and DA was found to be significantly elevated in the telencephalon of individuals trained in the spatial task than in the untrained individuals. Our results suggest that the spatial learning increases the expression of 14-3-3 (β), which in turn leads to an increase in the level of 5-HT and DA. The upregulated 5-HT and DA may facilitate synapse formation during spatial learning in a novel environment.
Temporal and spatial variations of the Chesapeake Bay plume
NASA Technical Reports Server (NTRS)
Ruzecki, E. P.
1981-01-01
Historical records and data obtained during the Superflux experiments are used to describe the temporal and spatial variations of the effluent waters of Chesapeake Bay. The alongshore extent of the plume resulting from variations of freshwater discharge into the Bay and the effects of wind are illustrated. Variations of the cross sectional configuration of the plume over portions of a tidal cycle and results of a rapid underway water sampling system are discussed.
Spatial and temporal variations of evapotranspiration, groundwater and precipitation in Amazonia
NASA Astrophysics Data System (ADS)
Niu, J.; Riley, W. J.; Shen, C.; Melack, J. M.; Qiu, H.
2017-12-01
We used wavelet coherence analysis to investigate the effects of precipitation (P) and groundwater dynamics (total water storage anomaly, TWSA) on evapotranspiration (ET) at kilometer, sub-basin, and whole basin scales in the Amazon basin. The Amazon-scale averaged ET, P, and TWSA have about the same annual periodicity. The phase lag between ET and P (ΦET-P) is 1 to 3 months, and between ET and TWSA (ΦET-TWSA) is 3 to 7 months. The phase patterns have a south-north divide due to significant variation in climatic conditions. The correlation between ΦET-P and ΦET-TWSA is affected by the aridity index (the ratio between potential ET (PET) and P, PET / P), of each sub-basin, as determined using the Budyko framework at the sub-basin level. The spatial structure of ΦET-P is negatively correlated with the spatial structure of annual ET. At Amazon-scale during a drought year (e.g., 2010), both phases decreased, while in the subsequent years, ΦET-TWSA increased, indicating strong groundwater effects on ET immediately following dry years Amazon-wide.
NASA Astrophysics Data System (ADS)
Hsieh, Cheng-Ta; Huang, Kae-Horng; Lee, Chang-Hsing; Han, Chin-Chuan; Fan, Kuo-Chin
2017-12-01
Robust face recognition under illumination variations is an important and challenging task in a face recognition system, particularly for face recognition in the wild. In this paper, a face image preprocessing approach, called spatial adaptive shadow compensation (SASC), is proposed to eliminate shadows in the face image due to different lighting directions. First, spatial adaptive histogram equalization (SAHE), which uses face intensity prior model, is proposed to enhance the contrast of each local face region without generating visible noises in smooth face areas. Adaptive shadow compensation (ASC), which performs shadow compensation in each local image block, is then used to produce a wellcompensated face image appropriate for face feature extraction and recognition. Finally, null-space linear discriminant analysis (NLDA) is employed to extract discriminant features from SASC compensated images. Experiments performed on the Yale B, Yale B extended, and CMU PIE face databases have shown that the proposed SASC always yields the best face recognition accuracy. That is, SASC is more robust to face recognition under illumination variations than other shadow compensation approaches.
A systematic temporal and spatial analysis is being conducted at the U.S. EPA on historical precipitation and stream flow over the continental U.S. and their relationships with Atlantic hurricanes and lower Mississippi river basin flooding. The objective is to decipher the period...
A systematic temporal and spatial analysis is being conducted at the U.S. EPA on historical precipitation and stream flow over the continental U.S. and their relationships with Atlantic hurricanes and lower Mississippi river basin flooding. The objective is to decipher the perio...
Water quality modeling based on landscape analysis: Importance of riparian hydrology
Thomas Grabs
2010-01-01
Several studies in high-latitude catchments have demonstrated the importance of near-stream riparian zones as hydrogeochemical hotspots with a substantial influence on stream chemistry. An adequate representation of the spatial variability of riparian-zone processes and characteristics is the key for modeling spatiotemporal variations of stream-water quality. This...
Contact line motion over substrates with spatially non-uniform properties
NASA Astrophysics Data System (ADS)
Ajaev, Vladimir; Gatapova, Elizaveta; Kabov, Oleg
2017-11-01
We develop mathematical models of moving contact lines over flat solid surfaces with spatial variation of temperature and wetting properties under the conditions when evaporation is significant. The gas phase is assumed to be pure vapor and a lubrication-type framework is employed for describing viscous flow in the liquid. Marangoni stresses at the liquid surface arise as a result of temperature variation in the vapor phase, non-equilibrium effects during evaporation at the interface, and Kelvin effect. The relative importance of these three factors is determined. Variation of wetting properties is modeled through a two-component disjoining pressure, with the main focus on spatially periodic patterns leading to time-periodic variation of the contact line speed.
Rico-Sánchez, Axel Eduardo; Rodríguez-Romero, Alexis Joseph; López-López, Eugenia; Sedeño-Díaz, Jacinto Elías
2014-04-01
Lake Tecocomulco, Hidalgo, is a relic of the ancient lakes ofAnahuac, important for the conservation of resident and migratory birds. However, the composition of aquatic macroinvertebrates is unknown; this is an important gap in conservation as they play an important role in the food web. This study analyzed the spatial and temporal variations in macroinvertebrate assemblages and their relationship with habitat characteristics. We carried out four monitoring campaigns covering the rainy and dry seasons. The monitoring was conducted at six study sites (four in the littoral zone and two in the middle part of the lake), environmental factors were recorded at each study site, water samples were collected for their physical and chemical analysis and aquatic macroinvertebrates were collected. A principal component analysis (PCA) was used to group study sites based on physical and chemical characteristics. Richness of taxa was analysed with rarefaction. We assessed the importance value index of each taxon (considering their frequency of occurrence and abundance). Similarity analyzes were performed between study sites and similarity of taxa with indices of Jaccard and Bray-Curtis, respectively. We performed a canonical correspondence analysis (CCA) between environmental factors and macroinvertebrate taxa. The PCA showed a marked seasonal variation represented by warm periods, with high values of conductivity, alkalinity, hardness, sulfates, and macronutrients (N and P) and the cold period with low values. We found a total of 26 taxa of aquatic macroinvertebrates and the highest richness was found in August. The Jaccard similarity analysis found differences between the littoral area and the limnetic zone, which differ also in the composition of macrophytes. The littoral zone had the highest taxa richness of macroinvertebrates and macrophytes, while the lowest diversity was found in the offshore zone. The CCA related physicochemical characteristics of the water body with macroinvertebrate taxa showing the influence of both physicochemical characteristics and the composition of macrophytes in the spatio-temporal patterns of aquatic macroinvertebrates in the lake. The dominance of Corixidae highlights a strong grazing activity in the lake and in turn suggests an important amount of food available for higher trophic levels. Our study shows that the macroinvertebrates of Tecocomulco Lake have spatial and seasonal variations that are related to both environmental and biotic factors with groups being dominant.
Root, Elisabeth Dowling; Gonzales, Louis; Persse, David E.; Hinchey, Paul R.; McNally, Bryan; Sasson, Comilla
2013-01-01
Background Despite evidence to suggest significant spatial variation in out-of-hospital cardiac arrest (OHCA) and bystander cardiopulmonary resuscitation (BCPR) rates, geographic information systems (GIS) and spatial analysis have not been widely used to understand the reasons behind this variation. This study employs spatial statistics to identify the location and extent of clusters of bystander CPR in Houston and Travis County, TX. Methods Data were extracted from the Cardiac Arrest Registry to Enhance Survival for two U.S. sites –Austin-Travis County EMS and the Houston Fire Department – between October 1, 2006 and December 31, 2009. Hierarchical logistic regression models were used to assess the relationship between income and racial/ethnic composition of a neighborhood and BCPR for OHCA and to adjust expected counts of BCPR for spatial cluster analysis. The spatial scan statistic was used to find the geographic extent of clusters of high and low BCPR. Results Results indicate spatial clusters of lower than expected BCPR rates in Houston. Compared to BCPR rates in the rest of the community, there was a circular area of 4.2 km radius where BCPR rates were lower than expected (RR = 0.62; p < 0.0001 and RR = 0.55; p = 0.037) which persist when adjusted for individual-level patient characteristics (RR = 0.34; p = 0.027) and neighborhood-level race (RR = 0.34; p = 0.034) and household income (RR = 0.34; p = 0.046). We also find a spatial cluster of higher than expected BCPR in Austin. Compared to the rest of the community, there was a 23.8 km radius area where BCPR rates were higher than expected (RR = 1.75; p = 0.07) which disappears after controlling for individual-level characteristics. Conclusions A geographically targeted CPR training strategy which is tailored to individual and neighborhood population characteristics may be effective in reducing existing disparities in the provision of bystander CPR for out-of-hospital cardiac arrest. PMID:23318916
Garza-Gisholt, Eduardo; Hemmi, Jan M.; Hart, Nathan S.; Collin, Shaun P.
2014-01-01
Topographic maps that illustrate variations in the density of different neuronal sub-types across the retina are valuable tools for understanding the adaptive significance of retinal specialisations in different species of vertebrates. To date, such maps have been created from raw count data that have been subjected to only limited analysis (linear interpolation) and, in many cases, have been presented as iso-density contour maps with contour lines that have been smoothed ‘by eye’. With the use of stereological approach to count neuronal distribution, a more rigorous approach to analysing the count data is warranted and potentially provides a more accurate representation of the neuron distribution pattern. Moreover, a formal spatial analysis of retinal topography permits a more robust comparison of topographic maps within and between species. In this paper, we present a new R-script for analysing the topography of retinal neurons and compare methods of interpolating and smoothing count data for the construction of topographic maps. We compare four methods for spatial analysis of cell count data: Akima interpolation, thin plate spline interpolation, thin plate spline smoothing and Gaussian kernel smoothing. The use of interpolation ‘respects’ the observed data and simply calculates the intermediate values required to create iso-density contour maps. Interpolation preserves more of the data but, consequently includes outliers, sampling errors and/or other experimental artefacts. In contrast, smoothing the data reduces the ‘noise’ caused by artefacts and permits a clearer representation of the dominant, ‘real’ distribution. This is particularly useful where cell density gradients are shallow and small variations in local density may dramatically influence the perceived spatial pattern of neuronal topography. The thin plate spline and the Gaussian kernel methods both produce similar retinal topography maps but the smoothing parameters used may affect the outcome. PMID:24747568
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dolly, S; University of Missouri, Columbia, MO; Chen, H
Purpose: Local noise power spectrum (NPS) properties are significantly affected by calculation variables and CT acquisition and reconstruction parameters, but a thoughtful analysis of these effects is absent. In this study, we performed a complete analysis of the effects of calculation and imaging parameters on the NPS. Methods: The uniformity module of a Catphan phantom was scanned with a Philips Brilliance 64-slice CT simulator using various scanning protocols. Images were reconstructed using both FBP and iDose4 reconstruction algorithms. From these images, local NPS were calculated for regions of interest (ROI) of varying locations and sizes, using four image background removalmore » methods. Additionally, using a predetermined ground truth, NPS calculation accuracy for various calculation parameters was compared for computer simulated ROIs. A complete analysis of the effects of calculation, acquisition, and reconstruction parameters on the NPS was conducted. Results: The local NPS varied with ROI size and image background removal method, particularly at low spatial frequencies. The image subtraction method was the most accurate according to the computer simulation study, and was also the most effective at removing low frequency background components in the acquired data. However, first-order polynomial fitting using residual sum of squares and principle component analysis provided comparable accuracy under certain situations. Similar general trends were observed when comparing the NPS for FBP to that of iDose4 while varying other calculation and scanning parameters. However, while iDose4 reduces the noise magnitude compared to FBP, this reduction is spatial-frequency dependent, further affecting NPS variations at low spatial frequencies. Conclusion: The local NPS varies significantly depending on calculation parameters, image acquisition parameters, and reconstruction techniques. Appropriate local NPS calculation should be performed to capture spatial variations of noise; calculation methodology should be selected with consideration of image reconstruction effects and the desired purpose of CT simulation for radiotherapy tasks.« less
Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region.
Li, Tianyu; Meng, Qingmin
2017-05-01
The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.
Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region
NASA Astrophysics Data System (ADS)
Li, Tianyu; Meng, Qingmin
2017-05-01
The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.
Analysis of tropospheric ozone concentration on a Western Mediterranean site: Castellon (Spain).
Castell, Nuria; Mantilla, Enrique; Millan, Millan M
2008-01-01
Ozone dynamics in our study area (Castellon, Spain) is both strongly bound to the mesoscale circulations that develop under the effect of high insolation (especially in summer) and conditioned by the morphological characteristics of the Western Mediterranean Basin. In this work we present a preliminary analysis of ozone time series on five locations in Castellon for the period 1997-2003. We study their temporal and spatial variations at different scales: daily, weekly, seasonally and interannually. Because both the O3 concentration and its temporal variation depend on the topographic location of the observing station, they can show large differences within tens of kilometer. We also contrast the variation in the ozone concentration with the variations found for meteorological variables such as radiation, temperature, relative humidity and recirculation of the air mass. The link between elevated ozone concentrations and high values of the recirculation factor (r=0.7-0.9) shown the importance of recirculating flows on the local air pollution episodes.
ERIC Educational Resources Information Center
Collin, Charles A.; Liu, Chang Hong; Troje, Nikolaus F.; McMullen, Patricia A.; Chaudhuri, Avi
2004-01-01
Previous studies have suggested that face identification is more sensitive to variations in spatial frequency content than object recognition, but none have compared how sensitive the 2 processes are to variations in spatial frequency overlap (SFO). The authors tested face and object matching accuracy under varying SFO conditions. Their results…
Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel
2014-01-01
Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes
Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel
2014-01-01
Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes
Moreno-Pino, Mario; De la Iglesia, Rodrigo; Valdivia, Nelson; Henríquez-Castilo, Carlos; Galán, Alexander; Díez, Beatriz; Trefault, Nicole
2016-07-01
Spatial environmental heterogeneity influences diversity of organisms at different scales. Environmental filtering suggests that local environmental conditions provide habitat-specific scenarios for niche requirements, ultimately determining the composition of local communities. In this work, we analyze the spatial variation of microbial communities across environmental gradients of sea surface temperature, salinity and photosynthetically active radiation and spatial distance in Fildes Bay, King George Island, Antarctica. We hypothesize that environmental filters are the main control of the spatial variation of these communities. Thus, strong relationships between community composition and environmental variation and weak relationships between community composition and spatial distance are expected. Combining physical characterization of the water column, cell counts by flow cytometry, small ribosomal subunit genes fingerprinting and next generation sequencing, we contrast the abundance and composition of photosynthetic eukaryotes and heterotrophic bacterial local communities at a submesoscale. Our results indicate that the strength of the environmental controls differed markedly between eukaryotes and bacterial communities. Whereas eukaryotic photosynthetic assemblages responded weakly to environmental variability, bacteria respond promptly to fine-scale environmental changes in this polar marine system. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
NASA Astrophysics Data System (ADS)
Bayat, Bardia; Zahraie, Banafsheh; Taghavi, Farahnaz; Nasseri, Mohsen
2013-08-01
Identification of spatial and spatiotemporal precipitation variations plays an important role in different hydrological applications such as missing data estimation. In this paper, the results of Bayesian maximum entropy (BME) and ordinary kriging (OK) are compared for modeling spatial and spatiotemporal variations of annual precipitation with and without incorporating elevation variations. The study area of this research is Namak Lake watershed located in the central part of Iran with an area of approximately 90,000 km2. The BME and OK methods have been used to model the spatial and spatiotemporal variations of precipitation in this watershed, and their performances have been evaluated using cross-validation statistics. The results of the case study have shown the superiority of BME over OK in both spatial and spatiotemporal modes. The results have shown that BME estimates are less biased and more accurate than OK. The improvements in the BME estimates are mostly related to incorporating hard and soft data in the estimation process, which resulted in more detailed and reliable results. Estimation error variance for BME results is less than OK estimations in the study area in both spatial and spatiotemporal modes.
NASA Astrophysics Data System (ADS)
Benitez Buelga, Javier; Rodriguez-Sinobas, Leonor; Sanchez, Raul; Gil, Maria; Tarquis, Ana M.
2014-05-01
Soils can be seen as the result of spatial variation operating over several scales. This observation points to 'variability' as a key soil attribute that should be studied. Soil variability has often been considered to be composed of 'functional' (explained) variations plus random fluctuations or noise. However, the distinction between these two components is scale dependent because increasing the scale of observation almost always reveals structure in the noise. Geostatistical methods and, more recently, multifractal/wavelet techniques have been used to characterize scaling and heterogeneity of soil properties among others coming from complexity science. Multifractal formalism, first proposed by Mandelbrot (1982), is suitable for variables with self-similar distribution on a spatial domain (Kravchenko et al., 2002). Multifractal analysis can provide insight into spatial variability of crop or soil parameters (Vereecken et al., 2007). This technique has been used to characterize the scaling property of a variable measured along a transect as a mass distribution of a statistical measure on a spatial domain of the studied field (Zeleke and Si, 2004). To do this, it divides the transect into a number of self-similar segments. It identifies the differences among the subsets by using a wide range of statistical moments. Wavelets were developed in the 1980s for signal processing, and later introduced to soil science by Lark and Webster (1999). The wavelet transform decomposes a series; whether this be a time series (Whitcher, 1998; Percival and Walden, 2000), or as in our case a series of measurements made along a transect; into components (wavelet coefficients) which describe local variation in the series at different scale (or frequency) intervals, giving up only some resolution in space (Lark et al., 2003, 2004). Wavelet coefficients can be used to estimate scale specific components of variation and correlation. This allows us to see which scales contribute most to signal variation, or to see at which scales signals are most correlated. This can give us an insight into the dominant processes An alternative to both of the above methods has been described recently. Relative entropy and increments in relative entropy has been applied in soil images (Bird et al., 2006) and in soil transect data (Tarquis et al., 2008) to study scale effects localized in scale and provide the information that is complementary to the information about scale dependencies found across a range of scales. We will use them in this work to describe the spatial scaling properties of a set of field water content data measured in an extension of a corn field, in a plot of 500 m2 and an spatial resolution of 25 cm. These measurements are based on an optics cable (BruggSteal) buried on a ziz-zag deployment at 30cm depth. References Bird, N., M.C. Díaz, A. Saa, and A.M. Tarquis. 2006. A review of fractal and multifractal analysis of soil pore-scale images. J. Hydrol. 322:211-219. Kravchenko, A.N., R. Omonode, G.A. Bollero, and D.G. Bullock. 2002. Quantitative mapping of soil drainage classes using topographical data and soil electrical conductivity. Soil Sci. Soc. Am. J. 66:235-243. Lark, R.M., A.E. Milne, T.M. Addiscott, K.W.T. Goulding, C.P. Webster, and S. O'Flaherty. 2004. Scale- and location-dependent correlation of nitrous oxide emissions with soil properties: An analysis using wavelets. Eur. J. Soil Sci. 55:611-627. Lark, R.M., S.R. Kaffka, and D.L. Corwin. 2003. Multiresolution analysis of data on electrical conductivity of soil using wavelets. J. Hydrol. 272:276-290. Lark, R. M. and Webster, R. 1999. Analysis and elucidation of soil variation using wavelets. European J. of Soil Science, 50(2): 185-206. Mandelbrot, B.B. 1982. The fractal geometry of nature. W.H. Freeman, New York. Percival, D.B., and A.T. Walden. 2000. Wavelet methods for time series analysis. Cambridge Univ. Press, Cambridge, UK. Tarquis, A.M., N.R. Bird, A.P. Whitmore, M.C. Cartagena, and Y. Pachepsky. 2008. Multiscale analysis of soil transect data. Vadose Zone J. 7: 563-569. Vereecken, H., R. Kasteel, J. Vanderborght, and T. Harter. 2007. Upscaling hydraulic properties and soil water flow processes in heterogeneous soils: A review. Vadose Zone J. 6:1-28. Whitcher, B.J. 1998. Assessing nonstationary time series using wavelets. Ph.D. diss. Univ. of Washington, Seattle (Diss. Abstr. 9907961). Zeleke, T.B., and B.C. Si. 2004. Scaling properties of topographic indices and crop yield: Multifractal and joint multifractal approaches. Agron J., 96:1082-1090.
NASA Astrophysics Data System (ADS)
Guozhuang, Shen; Jingjuan, Liao; Huadong, Guo; Yingkui, Li
2014-03-01
Qinghai-Tibetan Plateau is the largest lake area in China, with a total area of existing lakes of 36,900km2, accounting for 52% of the total lake area of China. Lakes on the Tibetan Plateau play critical roles in the water cycle and ecological and environment systems of the Plateau. The global trend of warming up is increasing obviously, which has led to major changes in the climate conditions in China, even in the world. Whereas, when they analyse the relationship they just use the weather station's recording data, without any spatial analysis of the climate data. Here, we will do some researches on the relationship between the 10 selected lakes' area variation and the corresponding climate change in their drainage basin and discuss how the lakes changes in recent 40 years using the climate data processed using the spatial kriging. Thus, the drainage area can be taken into account and a real relationship can be pointed out. In order to study the relationship, Landsat MSS data, Landsat TM, Landsat ETM images, the topographic map have been collected to extract the variation of lake area. The 131 weather stations climate data, including precipitation, temperature, sun shine duration, evaporation are chosen to study the relationship. After extraction of the area of the lakes, a multivariate statistical analysis method was used to test the relationship between the area of the lakes and the global climate change, including the change of the temperature, the precipitation, and other factors. The variation of lakes in Qinghai-Tibetan Plateau is related to the mean temperature, the precipitation and saturation vapour pressure. But the frozen soil may affect the lake area variation to some extent.
NASA Technical Reports Server (NTRS)
Donahue, T. M.; Wasser, B.
1977-01-01
Analysis of OGO-6 OI green line photometer results was carried out for 8 cases when the alignment of the spacecraft was such that local emission rates could be determined below the altitude of maximum emission and down to about 80 km. Results show a variation on a scale of 6 deg to 8 deg in latitude between regions where the emission rate increases rapidly between 90 and 95 km and regions where it increases slowly from 80 km to 95 km. Latitude-altitude maps of iso-emissivity contours and iso-density contours for oxygen concentration are presented. The latter are computed under 3 assumptions concerning excitation mechanisms. Comparisons of the spatial variations of oxygen density with the results of a time dependent theory suggest the regions of strong downward transport alternate on a scale of about 1000 km with regions of weak transport near 90 km. In the first case conversion of O to O3 at night appears to be overwhelmed by downward transport of O.
Place, Sean P.; Menge, Bruce A.; Hofmann, Gretchen E.
2011-01-01
Summary The marine intertidal zone is characterized by large variation in temperature, pH, dissolved oxygen and the supply of nutrients and food on seasonal and daily time scales. These oceanic fluctuations drive of ecological processes such as recruitment, competition and consumer-prey interactions largely via physiological mehcanisms. Thus, to understand coastal ecosystem dynamics and responses to climate change, it is crucial to understand these mechanisms. Here we utilize transcriptome analysis of the physiological response of the mussel Mytilus californianus at different spatial scales to gain insight into these mechanisms. We used mussels inhabiting different vertical locations within Strawberry Hill on Cape Perpetua, OR and Boiler Bay on Cape Foulweather, OR to study inter- and intra-site variation of gene expression. The results highlight two distinct gene expression signatures related to the cycling of metabolic activity and perturbations to cellular homeostasis. Intermediate spatial scales show a strong influence of oceanographic differences in food and stress environments between sites separated by ~65 km. Together, these new insights into environmental control of gene expression may allow understanding of important physiological drivers within and across populations. PMID:22563136
Divergent and nonuniform gene expression patterns in mouse brain
Morris, John A.; Royall, Joshua J.; Bertagnolli, Darren; Boe, Andrew F.; Burnell, Josh J.; Byrnes, Emi J.; Copeland, Cathy; Desta, Tsega; Fischer, Shanna R.; Goldy, Jeff; Glattfelder, Katie J.; Kidney, Jolene M.; Lemon, Tracy; Orta, Geralyn J.; Parry, Sheana E.; Pathak, Sayan D.; Pearson, Owen C.; Reding, Melissa; Shapouri, Sheila; Smith, Kimberly A.; Soden, Chad; Solan, Beth M.; Weller, John; Takahashi, Joseph S.; Overly, Caroline C.; Lein, Ed S.; Hawrylycz, Michael J.; Hohmann, John G.; Jones, Allan R.
2010-01-01
Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs. PMID:20956311
Gastmans, Didier; Santos, Vinícius; Galhardi, Juliana Aparecida; Gromboni, João Felipe; Batista, Ludmila Vianna; Miotlinski, Konrad; Chang, Hung Kiang; Govone, José Silvio
2017-10-01
Based on Global Network Isotopes in Precipitation (GNIP) isotopic data set, a review of the spatial and temporal variability of δ 18 O and δ 2 H in precipitation was conducted throughout central and eastern Brazil, indicating that dynamic interactions between Intertropical and South Atlantic Convergence Zones, Amazon rainforest, and Atlantic Ocean determine the variations on the isotopic composition of precipitation over this area. Despite the seasonality and latitude effects observed, a fair correlation with precipitation amount was found. In addition, Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) air mass back trajectories were used to quantify the factors controlling daily variability in stable isotopes in precipitation. Through a linear multiple regression analysis, it was observed that temporal variations were consistent with the meteorological parameters derived from HYSPLIT, particularly precipitation amount along the trajectory and mix depth, but are not dependent on vapour residence time in the atmosphere. These findings also indicate the importance of convective systems to control the isotopic composition of precipitation in tropical and subtropical regions.
Liu, Yunbo; Wear, Keith A; Harris, Gerald R
2017-10-01
Reliable acoustic characterization is fundamental for patient safety and clinical efficacy during high-intensity therapeutic ultrasound (HITU) treatment. Technical challenges, such as measurement variation and signal analysis, still exist for HITU exposimetry using ultrasound hydrophones. In this work, four hydrophones were compared for pressure measurement: a robust needle hydrophone, a small polyvinylidene fluoride capsule hydrophone and two fiberoptic hydrophones. The focal waveform and beam distribution of a single-element HITU transducer (1.05 MHz and 3.3 MHz) were evaluated. Complex deconvolution between the hydrophone voltage signal and frequency-dependent complex sensitivity was performed to obtain pressure waveforms. Compressional pressure (p + ), rarefactional pressure (p - ) and focal beam distribution were compared up to 10.6/-6.0 MPa (p + /p - ) (1.05 MHz) and 20.65/-7.20 MPa (3.3 MHz). The effects of spatial averaging, local non-linear distortion, complex deconvolution and hydrophone damage thresholds were investigated. This study showed a variation of no better than 10%-15% among hydrophones during HITU pressure characterization. Published by Elsevier Inc.
Temporal and spatial patterns of suicides in Stockholm's subway stations.
Uittenbogaard, Adriaan; Ceccato, Vania
2015-08-01
This paper investigates the potential temporal and spatial variations of suicides in subway stations in Stockholm, Sweden. The study also assesses whether the variation in suicide rates is related to the station environments by controlling for each station's location and a number of contextual factors using regression models and geographical information systems (GIS). Data on accidents are used as references for the analysis of suicides. Findings show that suicides tend to occur during the day and in the spring. They are concentrated in the main transportation hubs but, interestingly, during off-peak hours. However, the highest rates of suicides per passenger are found in Stockholm's subway stations located in the Southern outskirts. More than half of the variation in suicide rates is associated with stations that have walls between the two sides of the platform but still allow some visibility from passers-by. The surrounding environment and socioeconomic context show little effect on suicide rates, but stations embedded in areas with high drug-related crime rates tend to show higher suicide rates. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Messaoudi, Akila; Laouami, Nasser; Mezouar, Nourredine
2017-07-01
During the May 21, 2003 M w 6.8 Boumerdes earthquake, in the "Cité des 102 Logements" built on a hilltop, in Corso, heavy damages were observed: near the crest, a four-story RC building collapsed while others experienced severe structural damage and far from the crest, slight damage was observed. In the present paper, we perform a 2D slope topography seismic analysis and investigate its effects on the response at the plateau as well as the correlation with the observed damage distribution. A site-specific seismic scenario is used involving seismological, geological, and geotechnical data. 2D finite element numerical seismic study of the idealized Corso site subjected to vertical SV wave propagation is carried out by the universal code FLUSH. The results highlighted the main factors that explain the causes of block collapse, located 8-26 m far from the crest. These are as follows: (i) a significant spatial variation of ground response along the plateau due to the topographic effect, (ii) this spatial variation presents high loss of coherence, (iii) the seismic ground responses (PGA and response spectra) reach their maxima, and (iv) the fundamental frequency of the collapsed blocks coincides with the frequency content of the topographic component. For distances far from the crest where slight damages were observed, the topographic contribution is found negligible. On the basis of these results, it is important to take into account the topographic effect and the induced spatial variability in the seismic design of structures sited near the crest of slope.
Temple, Andrew J; Tregenza, Nick; Amir, Omar A; Jiddawi, Narriman; Berggren, Per
2016-01-01
Understanding temporal patterns in distribution, occurrence and behaviour is vital for the effective conservation of cetaceans. This study used cetacean click detectors (C-PODs) to investigate spatial and temporal variation in occurrence and foraging activity of the Indo-Pacific bottlenose (Tursiops aduncus) and Indian Ocean humpback (Sousa plumbea) dolphins resident in the Menai Bay Conservation Area (MBCA), Zanzibar, Tanzania. Occurrence was measured using detection positive minutes. Inter-click intervals were used to identify terminal buzz vocalisations, allowing for analysis of foraging activity. Data were analysed in relation to spatial (location) and temporal (monsoon season, diel phase and tidal phase) variables. Results showed significantly increased occurrence and foraging activity of dolphins in southern areas and during hours of darkness. Higher occurrence at night was not explained by diel variation in echolocation rate and so were considered representative of occurrence patterns. Both tidal phase and monsoon season influenced occurrence but results varied among sites, with no general patterns found. Foraging activity was greatest during hours of darkness, High water and Flood tidal phases. Comparisons of echolocation data among sites suggested differences in the broadband click spectra of MBCA dolphins, possibly indicative of species differences. These dolphin populations are threatened by unsustainable fisheries bycatch and tourism activities. The spatial and temporal patterns identified in this study have implications for future conservation and management actions with regards to these two threats. Further, the results indicate future potential for using passive acoustics to identify and monitor the occurrence of these two species in areas where they co-exist.
NASA Astrophysics Data System (ADS)
Mortuza, M.; Demissie, D.
2013-12-01
According to the U.S. Department of Energy's annual wind technologies market report, the wind power capacity in the country grew from 2.5 gigawatts in early 2000 to 60 gigawatts in 2012, making it one of the largest new sources of electric capacity additions in the U.S. in recent years. With over 2.8 gigawatts of current capacity (eighth largest in the nation), Washington State plays a significant role in this rapidly increasing energy resource. To further expand and/or optimize these capacities, assessment of wind resource and its spatial and temporal variations are important. However, since at-site frequency analysis using meteorological data is not adequate for extending wind frequency to locations with no data, longer return period, and heterogeneous topography and surface, a regional frequency analysis based on L-moment method is adopted in this study to estimate regional wind speed patterns and return periods in Washington State using hourly mean wind speed data from 1979 - 2010. The analysis applies the k-means, hierarchical and self-organizing map clustering techniques to explore potential clusters or regions; statistical tests are then applied to identify homogeneous regions and appropriate probability distribution models. The result from the analysis is expected to provide essential knowledge about the areas with potential capacity of constructing wind power plants, which can also be readily extended to assist decisions on their daily operations.
Computer-based video analysis identifies infants with absence of fidgety movements.
Støen, Ragnhild; Songstad, Nils Thomas; Silberg, Inger Elisabeth; Fjørtoft, Toril; Jensenius, Alexander Refsum; Adde, Lars
2017-10-01
BackgroundAbsence of fidgety movements (FMs) at 3 months' corrected age is a strong predictor of cerebral palsy (CP) in high-risk infants. This study evaluates the association between computer-based video analysis and the temporal organization of FMs assessed with the General Movement Assessment (GMA).MethodsInfants were eligible for this prospective cohort study if referred to a high-risk follow-up program in a participating hospital. Video recordings taken at 10-15 weeks post term age were used for GMA and computer-based analysis. The variation of the spatial center of motion, derived from differences between subsequent video frames, was used for quantitative analysis.ResultsOf 241 recordings from 150 infants, 48 (24.1%) were classified with absence of FMs or sporadic FMs using the GMA. The variation of the spatial center of motion (C SD ) during a recording was significantly lower in infants with normal (0.320; 95% confidence interval (CI) 0.309, 0.330) vs. absence of or sporadic (0.380; 95% CI 0.361, 0.398) FMs (P<0.001). A triage model with C SD thresholds chosen for sensitivity of 90% and specificity of 80% gave a 40% referral rate for GMA.ConclusionQuantitative video analysis during the FMs' period can be used to triage infants at high risk of CP to early intervention or observational GMA.
NASA Astrophysics Data System (ADS)
Feng, Yongjiu; Chen, Xinjun; Liu, Yan
2017-07-01
With the increasing effects of global climate change and fishing activities, the spatial distribution of the neon flying squid ( Ommastrephes bartramii) is changing in the traditional fishing ground of 150°-160°E and 38°-45°N in the northwest Pacific Ocean. This research aims to identify the spatial hot and cold spots (i.e. spatial clusters) of O. bartramii to reveal its spatial structure using commercial fishery data from 2007 to 2010 collected by Chinese mainland squid-jigging fleets. A relatively strongly-clustered distribution for O. bartramii was observed using an exploratory spatial data analysis (ESDA) method. The results show two hot spots and one cold spot in 2007 while only one hot and one cold spots were identified each year from 2008 to 2010. The hot and cold spots in 2007 occupied 8.2% and 5.6% of the study area, respectively; these percentages for hot and cold spot areas were 5.8% and 3.1% in 2008, 10.2% and 2.9% in 2009, and 16.4% and 11.9% in 2010, respectively. Nearly half (>45%) of the squid from 2007 to 2009 reported by Chinese fleets were caught in hot spot areas while this percentage reached its peak at 68.8% in 2010, indicating that the hot spot areas are central fishing grounds. A further change analysis shows the area centered at 156°E/43.5°N was persistent as a hot spot over the whole period from 2007 to 2010. Furthermore, the hot spots were mainly identified in areas with sea surface temperature (SST) in the range of 15-20°C around warm Kuroshio Currents as well as with the chlorophyll- a (chl- a) concentration above 0.3 mg/m3. The outcome of this research improves our understanding of spatiotemporal hotspots and its variation for O. bartramii and is useful for sustainable exploitation, assessment, and management of this squid.
Warren, Victoria E; Marques, Tiago A; Harris, Danielle; Thomas, Len; Tyack, Peter L; Aguilar de Soto, Natacha; Hickmott, Leigh S; Johnson, Mark P
2017-03-01
Passive acoustic monitoring has become an increasingly prevalent tool for estimating density of marine mammals, such as beaked whales, which vocalize often but are difficult to survey visually. Counts of acoustic cues (e.g., vocalizations), when corrected for detection probability, can be translated into animal density estimates by applying an individual cue production rate multiplier. It is essential to understand variation in these rates to avoid biased estimates. The most direct way to measure cue production rate is with animal-mounted acoustic recorders. This study utilized data from sound recording tags deployed on Blainville's (Mesoplodon densirostris, 19 deployments) and Cuvier's (Ziphius cavirostris, 16 deployments) beaked whales, in two locations per species, to explore spatial and temporal variation in click production rates. No spatial or temporal variation was detected within the average click production rate of Blainville's beaked whales when calculated over dive cycles (including silent periods between dives); however, spatial variation was detected when averaged only over vocal periods. Cuvier's beaked whales exhibited significant spatial and temporal variation in click production rates within vocal periods and when silent periods were included. This evidence of variation emphasizes the need to utilize appropriate cue production rates when estimating density from passive acoustic data.
Cheng, Linjun; Wang, Shuai; Gong, Zhengyu; Li, Hong; Yang, Qi; Wang, Yeyao
2018-05-01
Owing to the vast territory of China and strong regional characteristic of ozone pollution, it's desirable for policy makers to have a targeted and prioritized regulation and ozone pollution control strategy in China based on scientific evidences. It's important to assess its current pollution status as well as spatial and temporal variation patterns across China. Recent advances of national monitoring networks provide an opportunity to insight the actions of ozone pollution. Here, we present rotated empirical orthogonal function (REOF) analysis that was used on studying the spatiotemporal characteristics of daily ozone concentrations. Based on results of REOF analysis in pollution seasons for 3years' observations, twelve regions with clear patterns were identified in China. The patterns of temporal variation of ozone in each region were separated well and different from each other, reflecting local meteorological, photochemical or pollution features. A rising trend in annual averaged Eight-hour Average Ozone Concentrations (O 3 -8hr) from 2014 to 2016 was observed for all regions, except for the Tibetan Plateau. The mean values of annual and 90 percentile concentrations for all 338 cities were 82.6±14.6 and 133.9±25.8μg/m 3 , respectively, in 2015. The regionalization results of ozone were found to be influenced greatly by terrain features, indicating significant terrain and landform effects on ozone spatial correlations. Among 12 regions, North China Plain, Huanghuai Plain, Central Yangtze River Plain, Pearl River Delta and Sichuan Basin were realized as priority regions for mitigation strategies, due to their higher ozone concentrations and dense population. Copyright © 2017. Published by Elsevier B.V.
Krasnov, Helena; Kloog, Itai; Friger, Michael; Katra, Itzhak
2016-01-01
Dust storms are a common phenomenon in arid and semi-arid areas, and their impacts on both physical and human environments are of great interest. Number of studies have associated atmospheric PM pollution in urban environments with origin in natural soil/dust, but less evaluated the dust spatial patterns over a city. We aimed to analyze the spatial-temporal behavior of PM concentrations over the city of Beer Sheva, in southern Israel, where dust storms are quite frequent. PM data were recorded during the peak of each dust episode simultaneously in 23 predetermined fixed points around the city. Data were analyzed for both dust days and non-dust days (background). The database was constructed using Geographic Information System and includes distributions of PM that were derived using inverse distance weighted (IDW) interpolation. The results show that the daily averages of atmospheric PM10 concentrations during the background period are within a narrow range of 31 to 48 μg m-3 with low variations. During dust days however, the temporal variations are significant and can range from an hourly PM10 concentration of 100 μg m-3 to more than 1280 μg m-3 during strong storms. IDW analysis demonstrates that during the peak time of the storm the spatial variations in PM between locations in the city can reach 400 μg m-3. An analysis of site and storm contribution to total PM concentration revealed that higher concentrations are found in parts of the city that are proximal to dust sources. The results improve the understanding of the dynamics of natural PM and the dependence on wind direction. This may have implications for environmental and health outcomes. PMID:27513479
NASA Astrophysics Data System (ADS)
Chaudhury, Baishali; Zhou, Mu; Farhidzadeh, Hamidreza; Goldgof, Dmitry B.; Hall, Lawrence O.; Gatenby, Robert A.; Gillies, Robert J.; Weinfurtner, Robert J.; Drukteinis, Jennifer S.
2016-03-01
The use of Ki67% expression, a cell proliferation marker, as a predictive and prognostic factor has been widely studied in the literature. Yet its usefulness is limited due to inconsistent cut off scores for Ki67% expression, subjective differences in its assessment in various studies, and spatial variation in expression, which makes it difficult to reproduce as a reliable independent prognostic factor. Previous studies have shown that there are significant spatial variations in Ki67% expression, which may limit its clinical prognostic utility after core biopsy. These variations are most evident when examining the periphery of the tumor vs. the core. To date, prediction of Ki67% expression from quantitative image analysis of DCE-MRI is very limited. This work presents a novel computer aided diagnosis framework to use textural kinetics to (i) predict the ratio of periphery Ki67% expression to core Ki67% expression, and (ii) predict Ki67% expression from individual tumor habitats. The pilot cohort consists of T1 weighted fat saturated DCE-MR images from 17 patients. Support vector regression with a radial basis function was used for predicting the Ki67% expression and ratios. The initial results show that texture features from individual tumor habitats are more predictive of the Ki67% expression ratio and spatial Ki67% expression than features from the whole tumor. The Ki67% expression ratio could be predicted with a root mean square error (RMSE) of 1.67%. Quantitative image analysis of DCE-MRI using textural kinetic habitats, has the potential to be used as a non-invasive method for predicting Ki67 percentage and ratio, thus more accurately reporting high KI-67 expression for patient prognosis.
NASA Astrophysics Data System (ADS)
Lillis, Ashlee; Mooney, T. Aran
2018-06-01
The rich acoustic environment of coral reefs, including the sounds of a variety of fish and invertebrates, is a reflection of the structural complexity and biological diversity of these habitats. Emerging interest in applying passive acoustic monitoring and soundscape analysis to measure coral reef habitat characteristics and track ecological patterns is hindered by a poor understanding of the most common and abundant sound producers on reefs—the snapping shrimp. Here, we sought to address several basic biophysical drivers of reef sound by investigating acoustic activity patterns of snapping shrimp populations on two adjacent coral reefs using a detailed snap detection analysis routine to a high-resolution 2.5-month acoustic dataset from the US Virgin Islands. The reefs exhibited strong diel and lunar periodicity in snap rates and clear spatial differences in snapping levels. Snap rates peaked at dawn and dusk and were higher overall during daytime versus nighttime, a seldom-reported pattern in earlier descriptions of diel snapping shrimp acoustic activity. Small differences between the sites in snap rate rhythms were detected and illustrate how analyses of specific soundscape elements might reveal subtle between-reef variation. Snap rates were highly correlated with environmental variables, including water temperature and light, and were found to be sensitive to changes in oceanographic forcing. This study further establishes snapping shrimp as key players in the coral reef chorus and provides evidence that their acoustic output reflects a combination of environmental conditions, celestial influences, and spatial habitat variation. Effective application of passive acoustic monitoring in coral reef habitats using snap rates or snapping-influenced acoustic metrics will require a mechanistic understanding of the underlying spatial and temporal variation in snapping shrimp sound production across multiple scales.
NASA Astrophysics Data System (ADS)
Liu, J.; Tarasick, D. W.; Mao, H.; Li, Y., , Dr; Osman, M.; Zhao, T.; Jung, J.; Fioletov, V.; Moeini, O.
2017-12-01
Ozone trends and spatial variations in the North American free troposphere from the 1970s to the 2000s are characterized, based on the newly developed Trajectory-mapped Ozonesonde dataset for the Stratosphere and Troposphere (TOST). TOST uses a special domain-filling technique with forward and backward trajectory calculations to fill in spatial gaps in ozonesonde data. TOST is resolved in latitude, longitude, and altitude so it can provide new information on the long-term variations of troposheric ozone in three dimensions. . Global trend calculations with sparse and irregularly-spaced ozonesonde data must contend with the problem of how to properly weight the data in a zonal or regional average. As TOST spreads the data according to dynamic meteorological information, in a zonal or regional average it will therefore weight the data according to the meteorologically-determined area that each site samples. Through four decades, the highest ozone concentrations in the lower and middle troposphere generally appeared over the central midlatitudes of North America. Longitudinally, ozone was lowest over the southern Pacific Ocean, intermediate over the North American continent, and highest in the outflow along the east coast. The overall ozone trends in the four decades averaged over North America are positive. In particular, there has been an increasing trend at high latitudes between 50-90°N in the North American middle troposphere. Our analysis suggests that this may be caused by influences from the stratosphere and from lower latitudes during the period. The trends from TOST are compared with the original ozonesonde data at selected stations and both datasets correlate closely.
Ling, Juan; Zhang, Yan-Ying; Dong, Jun-De; Wang, You-Shao; Feng, Jing-Bing; Zhou, Wei-Hua
2015-10-01
Bacteria play important roles in the structure and function of marine food webs by utilizing nutrients and degrading the pollutants, and their distribution are determined by surrounding water chemistry to a certain extent. It is vital to investigate the bacterial community's structure and identifying the significant factors by controlling the bacterial distribution in the paper. Flow cytometry showed that the total bacterial abundance ranged from 5.27 × 10(5) to 3.77 × 10(6) cells/mL. Molecular fingerprinting technique, denaturing gradient gel electrophoresis (DGGE) followed by DNA sequencing has been employed to investigate the bacterial community composition. The results were then interpreted through multivariate statistical analysis and tended to explain its relationship to the environmental factors. A total of 270 bands at 83 different positions were detected in DGGE profiles and 29 distinct DGGE bands were sequenced. The predominant bacteria were related to Phyla Protebacteria species (31 %, nine sequences), Cyanobacteria (37.9 %, eleven sequences) and Actinobacteria (17.2 %, five sequences). Other phylogenetic groups identified including Firmicutes (6.9 %, two sequences), Bacteroidetes (3.5 %, one sequences) and Verrucomicrobia (3.5 %, one sequences). Conical correspondence analysis was used to elucidate the relationships between the bacterial community compositions and environmental factors. The results showed that the spatial variations in the bacterial community composition was significantly related to phosphate (P = 0.002, P < 0.01), dissolved organic carbon (P = 0.004, P < 0.01), chemical oxygen demand (P = 0.010, P < 0.05) and nitrite (P = 0.016, P < 0.05). This study revealed the spatial variations of bacterial community and significant environmental factors driving the bacterial composition shift. These results may be valuable for further investigation on the functional microbial structure and expression quantitatively under the polluted environments in the world.
Li, Tao; Hao, Xinmei; Kang, Shaozhong
2016-01-01
There is a growing interest in precision viticulture with the development of global positioning system and geographical information system technologies. Limited information is available on spatial variation of bud behavior and its possible association with soil properties. The objective of this study was to investigate spatial variability of bud burst percentage and its association with soil properties based on 2-year experiments at a vineyard of arid northwest China. Geostatistical approach was used to describe the spatial variation in bud burst percentage within the vineyard. Partial least square regressions (PLSRs) of bud burst percentage with soil properties were used to evaluate the contribution of soil properties to overall spatial variability in bud burst percentage for the high, medium and low bud burst percentage groups. Within the vineyard, the coefficient of variation (CV) of bud burst percentage was 20% and 15% for 2012 and 2013 respectively. Bud burst percentage within the vineyard showed moderate spatial variability, and the overall spatial pattern of bud burst percentage was similar between the two years. Soil properties alone explained 31% and 37% of the total spatial variation respectively for the low group of 2012 and 2013, and 16% and 24% for the high group of 2012 and 2013 respectively. For the low group, the fraction of variations explained by soil properties was found similar between the two years, while there was substantial difference for the high group. The findings are expected to lay a good foundation for developing remedy measures in the areas with low bud burst percentage, thus in turn improving the overall grape yield and quality. PMID:27798692
NASA Astrophysics Data System (ADS)
Girotto, M.; De Lannoy, G. J. M.; Reichle, R. H.; Rodell, M.
2015-12-01
The Gravity Recovery And Climate Experiment (GRACE) mission is unique because it provides highly accurate column integrated estimates of terrestrial water storage (TWS) variations. Major limitations of GRACE-based TWS observations are related to their monthly temporal and coarse spatial resolution (around 330 km at the equator), and to the vertical integration of the water storage components. These challenges can be addressed through data assimilation. To date, it is still not obvious how best to assimilate GRACE-TWS observations into a land surface model, in order to improve hydrological variables, and many details have yet to be worked out. This presentation discusses specific recent features of the assimilation of gridded GRACE-TWS data into the NASA Goddard Earth Observing System (GEOS-5) Catchment land surface model to improve soil moisture and shallow groundwater estimates at the continental scale. The major recent advancements introduced by the presented work with respect to earlier systems include: 1) the assimilation of gridded GRACE-TWS data product with scaling factors that are specifically derived for data assimilation purposes only; 2) the assimilation is performed through a 3D assimilation scheme, in which reasonable spatial and temporal error standard deviations and correlations are exploited; 3) the analysis step uses an optimized calculation and application of the analysis increments; 4) a poor-man's adaptive estimation of a spatially variable measurement error. This work shows that even if they are characterized by a coarse spatial and temporal resolution, the observed column integrated GRACE-TWS data have potential for improving our understanding of soil moisture and shallow groundwater variations.
Spreading speeds for plant populations in landscapes with low environmental variation.
Gilbert, Mark A; Gaffney, Eamonn A; Bullock, James M; White, Steven M
2014-12-21
Characterising the spread of biological populations is crucial in responding to both biological invasions and the shifting of habitat under climate change. Spreading speeds can be studied through mathematical models such as the discrete-time integro-difference equation (IDE) framework. The usual approach in implementing IDE models has been to ignore spatial variation in the demographic and dispersal parameters and to assume that these are spatially homogeneous. On the other hand, real landscapes are rarely spatially uniform with environmental variation being very important in determining biological spread. This raises the question of under what circumstances spatial structure need not be modelled explicitly. Recent work has shown that spatial variation can be ignored for the specific case where the scale of landscape variation is much smaller than the spreading population׳s dispersal scale. We consider more general types of landscape, where the spatial scales of environmental variation are arbitrarily large, but the maximum change in environmental parameters is relatively small. We find that the difference between the wave-speeds of populations spreading in a spatially structured periodic landscape and its homogenisation is, in general, proportional to ϵ(2), where ϵ governs the degree of environmental variation. For stochastically generated landscapes we numerically demonstrate that the error decays faster than ϵ. In both cases, this means that for sufficiently small ϵ, the homogeneous approximation is better than might be expected. Hence, in many situations, the precise details of the landscape can be ignored in favour of spatially homogeneous parameters. This means that field ecologists can use the homogeneous IDE as a relatively simple modelling tool--in terms of both measuring parameter values and doing the modelling itself. However, as ϵ increases, this homogeneous approximation loses its accuracy. The change in wave-speed due to the extrinsic (landscape) variation can be positive or negative, which is in contrast to the reduction in wave-speed caused by intrinsic stochasticity. To deal with the loss of accuracy as ϵ increases, we formulate a second-order approximation to the wave-speed for periodic landscapes and compare both approximations against the results of numerical simulation and show that they are both accurate for the range of landscapes considered. Copyright © 2014 Elsevier Ltd. All rights reserved.
Efficient dynamic events discrimination technique for fiber distributed Brillouin sensors.
Galindez, Carlos A; Madruga, Francisco J; Lopez-Higuera, Jose M
2011-09-26
A technique to detect real time variations of temperature or strain in Brillouin based distributed fiber sensors is proposed and is investigated in this paper. The technique is based on anomaly detection methods such as the RX-algorithm. Detection and isolation of dynamic events from the static ones are demonstrated by a proper processing of the Brillouin gain values obtained by using a standard BOTDA system. Results also suggest that better signal to noise ratio, dynamic range and spatial resolution can be obtained. For a pump pulse of 5 ns the spatial resolution is enhanced, (from 0.541 m obtained by direct gain measurement, to 0.418 m obtained with the technique here exposed) since the analysis is concentrated in the variation of the Brillouin gain and not only on the averaging of the signal along the time. © 2011 Optical Society of America
Spatial and layer-controlled variability in fracture networks
NASA Astrophysics Data System (ADS)
Procter, Andrew; Sanderson, David J.
2018-03-01
Topological sampling, based on 1) node counting and 2) circular sampling areas, is used to measure fracture intensity in surface exposures of a layered limestone/shale sequence in north Somerset, UK. This method provides similar levels of precision as more traditional line samples, but is about 10 times quicker and allows characterization of the network topology. Georeferencing of photographs of the sample sites allows later analysis of trace lengths and orientations, and identification of joint set development. ANOVA tests support a complex interaction of within-layer, between-layer and between-location variability in fracture intensity, with the different layers showing anomalous intensity at different locations. This variation is not simply due to bed thickness, nor can it be related to any obvious compositional or textural variation between the limestone beds. These results are used to assess approaches to the spatial mapping of fracture intensity.
Study on temporal and spatial variations of urban land use based on land change data
NASA Astrophysics Data System (ADS)
Jiang, Ping; Liu, Yanfang; Fan, Min; Zhang, Yang
2009-10-01
With the rapid development of urbanization, demands of urban land increase in succession, hence, to analyze temporal and spatial variations of urban land use becomes more and more important. In this paper, the principle of trend surface analysis and formula of urban land sprawl index ( ULSI) are expatiated at first, and then based on land change data of Jiayu county, the author fits quadratic trend surface by choosing urban land area as dependent variable and urbanization and GDP as independent variables from 1996 to 2006, draws isoline of trend surface and residual values; and then urban land sprawl indexes of towns are calculated on the basis of urban land area of 1996 and 2006 and distribution map of ULSI is plotted. After analyzing those results, we can conclude that there is consanguineous relationship between urban land area and urbanization, economic level etc.
NASA Technical Reports Server (NTRS)
Talpe, Matthieu J.; Nerem, R. Steven; Forootan, Ehsan; Schmidt, Michael; Lemoine, Frank G.; Enderlin, Ellyn M.; Landerer, Felix W.
2017-01-01
We construct long-term time series of Greenland and Antarctic ice sheet mass change from satellite gravity measurements. A statistical reconstruction approach is developed based on a principal component analysis (PCA) to combine high-resolution spatial modes from the Gravity Recovery and Climate Experiment (GRACE) mission with the gravity information from conventional satellite tracking data. Uncertainties of this reconstruction are rigorously assessed; they include temporal limitations for short GRACE measurements, spatial limitations for the low-resolution conventional tracking data measurements, and limitations of the estimated statistical relationships between low- and high-degree potential coefficients reflected in the PCA modes. Trends of mass variations in Greenland and Antarctica are assessed against a number of previous studies. The resulting time series for Greenland show a higher rate of mass loss than other methods before 2000, while the Antarctic ice sheet appears heavily influenced by interannual variations.
Spatial heterogeneity and the distribution of bromeliad pollinators in the Atlantic Forest
NASA Astrophysics Data System (ADS)
Varassin, Isabela Galarda; Sazima, Marlies
2012-08-01
Interactions between plants and their pollinators are influenced by environmental heterogeneity, resulting in small-scale variations in interactions. This may influence pollinator co-existence and plant reproductive success. This study, conducted at the Estação Biológica de Santa Lúcia (EBSL), a remnant of the Atlantic Forest in southeastern Brazil, investigated the effect of small-scale spatial variations on the interactions between bromeliads and their pollinators. Overall, hummingbirds pollinated 19 of 23 bromeliad species, of which 11 were also pollinated by bees and/or butterflies. However, spatial heterogeneity unrelated to the spatial location of plots or bromeliad species abundance influenced the presence of pollinators. Hummingbirds were the most ubiquitous pollinators at the high-elevation transect, with insect participation clearly declining as transect elevation increased. In the redundancy analysis, the presence of the hummingbird species Phaethornis eurynome, Phaethornis squalidus, Ramphodon naevius, and Thalurania glaucopis, and the butterfly species Heliconius erato and Heliconius nattereri in each plot was correlated with environmental factors such as bromeliad and tree abundance, and was also correlated with horizontal diversity. Since plant-pollinator interactions varied within the environmental mosaics at the study site, this small-scale environmental heterogeneity may relax competition among pollinators, and may explain the high diversity of bromeliads and pollinators generally found in the Atlantic Forest.
Spherical Cap Harmonic Modelling of 400 Years of Secular Variation in the South-west Pacific
NASA Astrophysics Data System (ADS)
Ingham, M.; Alfheid, M.; Ingham, E. M.; Turner, G. M.
2014-12-01
Historical magnetic data recorded in ship's logs on voyages of exploration and trade in the south-west Pacific have been used as a basis for constructing a model of secular variation in the region using spherical cap harmonic (SCH) analysis. The spherical cap used is centred on colatitude 115° and longitude 160° and has a radius of 50°, thus covering New Zealand, Australia and parts of Antarctica. Gaps in the observational data have been filled by an iterative procedure started by using IGRF field values to obtain SCH models for 2000, 1950 and 1900 and assuming that the spherical cap coefficients have a linear variation in time over the 400 year time period of the model, as is observed to a first approximation for Gauss coefficients calculated from a global spherical harmonic analysis. The resulting field models have generally smooth spatial and temporal variations in declination, inclination and intensity which show some differences from the variations calculated using the global spherical harmonic model gufm1. The technique clearly shows promise for producing more refined models of secular variation in the south-west Pacific when the historical data are supplemented by archeomagnetic and paleomagnetic data.
Population and allelic variation of A-to-I RNA editing in human transcriptomes.
Park, Eddie; Guo, Jiguang; Shen, Shihao; Demirdjian, Levon; Wu, Ying Nian; Lin, Lan; Xing, Yi
2017-07-28
A-to-I RNA editing is an important step in RNA processing in which specific adenosines in some RNA molecules are post-transcriptionally modified to inosines. RNA editing has emerged as a widespread mechanism for generating transcriptome diversity. However, there remain significant knowledge gaps about the variation and function of RNA editing. In order to determine the influence of genetic variation on A-to-I RNA editing, we integrate genomic and transcriptomic data from 445 human lymphoblastoid cell lines by combining an RNA editing QTL (edQTL) analysis with an allele-specific RNA editing (ASED) analysis. We identify 1054 RNA editing events associated with cis genetic polymorphisms. Additionally, we find that a subset of these polymorphisms is linked to genome-wide association study signals of complex traits or diseases. Finally, compared to random cis polymorphisms, polymorphisms associated with RNA editing variation are located closer spatially to their respective editing sites and have a more pronounced impact on RNA secondary structure. Our study reveals widespread cis variation in RNA editing among genetically distinct individuals and sheds light on possible phenotypic consequences of such variation on complex traits and diseases.
Reproduction of a higher-order circular harmonic field using a linear array of loudspeakers.
Lee, Jung-Min; Choi, Jung-Woo; Kim, Yang-Hann
2015-03-01
This paper presents a direct formula for reproducing a sound field consisting of higher-order circular harmonics with polar phase variation. Sound fields with phase variation can be used for synthesizing various spatial attributes, such as the perceived width or the location of a virtual sound source. To reproduce such a sound field using a linear loudspeaker array, the driving function of the array is derived in the format of an integral formula. The proposed function shows fewer reproduction errors than a conventional formula focused on magnitude variations. In addition, analysis of the sweet spot reveals that its shape can be asymmetric, depending on the order of harmonics.
Surfzone alongshore advective accelerations: observations and modeling
NASA Astrophysics Data System (ADS)
Hansen, J.; Raubenheimer, B.; Elgar, S.
2014-12-01
The sources, magnitudes, and impacts of non-linear advective accelerations on alongshore surfzone currents are investigated with observations and a numerical model. Previous numerical modeling results have indicated that advective accelerations are an important contribution to the alongshore force balance, and are required to understand spatial variations in alongshore currents (which may result in spatially variable morphological change). However, most prior observational studies have neglected advective accelerations in the alongshore force balance. Using a numerical model (Delft3D) to predict optimal sensor locations, a dense array of 26 colocated current meters and pressure sensors was deployed between the shoreline and 3-m water depth over a 200 by 115 m region near Duck, NC in fall 2013. The array included 7 cross- and 3 alongshore transects. Here, observational and numerical estimates of the dominant forcing terms in the alongshore balance (pressure and radiation-stress gradients) and the advective acceleration terms will be compared with each other. In addition, the numerical model will be used to examine the force balance, including sources of velocity gradients, at a higher spatial resolution than possible with the instrument array. Preliminary numerical results indicate that at O(10-100 m) alongshore scales, bathymetric variations and the ensuing alongshore variations in the wave field and subsequent forcing are the dominant sources of the modeled velocity gradients and advective accelerations. Additional simulations and analysis of the observations will be presented. Funded by NSF and ASDR&E.
Quantifying Diurnal and Seasonal Variation in On-road CO2 Emissions Across the Northeastern U.S.
NASA Astrophysics Data System (ADS)
Gately, C.; Hutyra, L.
2014-12-01
On-road emissions comprised 29% of U.S. fossil fuel carbon dioxide emissions in 2012, with 64% of those emissions occurring in urban areas. Understanding the social, economic and technological factors that influence urban emissions requires the development of emissions inventories that are resolved at fine spatial and temporal scales. As city governments are increasingly at the forefront of developing policies to mitigate greenhouse gas emissions from vehicles, high-resolution, bottom-up inventories will support local and regional emissions benchmarking, as well as the monitoring, reporting, and verification of trends in emissions across time and space. To that end, we combine a large regional dataset of hourly traffic counts with the 1km gridded estimates of on-road CO2 emissions from the Database of Road Transportation Emissions (DARTE) to develop hourly CO2 emissions estimates for the year 2012 that cover 12 northeastern states. The inventory scope covers several large metropolitan regions as well as many small- and medium-sized urban, suburban and exurban population centers, altogether representing 20% of urban and 17% of total U.S. on-road CO2 emissions in 2012. We identify significant variation in the time structure of vehicle emissions across the urban-suburban gradients of the Boston, New York, and Washington, D.C. metropolitan areas. In particular we note considerable spatial variation between morning and evening peak periods, both within and between cities, as well as variations in the duration of peak periods, depending on time of year and spatial location. We also examine the relationship between the temporal and spatial structure of morning and evening peak period emissions and the spatial distribution of population and employment density across urban to rural gradients. Finally we utilize data on minute-by-minute vehicle speeds to quantify the effect of traffic congestion on vehicle CO2 emission rates across the Boston metro area, and we highlight the sensitivity of congestion to small sub-hourly variations in traffic flows at key periods of the morning and evening rush hours. Results from our analysis demonstrate the potential for reducing vehicle emissions through time-sensitive toll pricing or commuter incentive schemes targeting peak period vehicle use on urban freeways.
On the Character and Mitigation of Atmospheric Noise in InSAR Time Series Analysis (Invited)
NASA Astrophysics Data System (ADS)
Barnhart, W. D.; Fielding, E. J.; Fishbein, E.
2013-12-01
Time series analysis of interferometric synthetic aperture radar (InSAR) data, with its broad spatial coverage and ability to image regions that are sometimes very difficult to access, is a powerful tool for characterizing continental surface deformation and its temporal variations. With the impending launch of dedicated SAR missions such as Sentinel-1, ALOS-2, and the planned NASA L-band SAR mission, large volume data sets will allow researchers to further probe ground displacement processes with increased fidelity. Unfortunately, the precision of measurements in individual interferograms is impacted by several sources of noise, notably spatially correlated signals caused by path delays through the stratified and turbulent atmosphere and ionosphere. Spatial and temporal variations in atmospheric water vapor often introduce several to tens of centimeters of apparent deformation in the radar line-of-sight, correlated over short spatial scales (<10 km). Signals resulting from atmospheric path delays are particularly problematic because, like the subsidence and uplift signals associated with tectonic deformation, they are often spatially correlated with topography. In this talk, we provide an overview of the effects of spatially correlated tropospheric noise in individual interferograms and InSAR time series analysis, and we highlight where common assumptions of the temporal and spatial characteristics of tropospheric noise fail. Next, we discuss two classes of methods for mitigating the effects of tropospheric water vapor noise in InSAR time series analysis and single interferograms: noise estimation and characterization with independent observations from multispectral sensors such as MODIS and MERIS; and noise estimation and removal with weather models, multispectral sensor observations, and GPS. Each of these techniques can provide independent assessments of the contribution of water vapor in interferograms, but each technique also suffers from several pitfalls that we outline. The multispectral near-infrared (NIR) sensors provide high spatial resolution (~1 km) estimates of total column tropospheric water vapor by measuring the absorption of reflected solar illumination and provide may excellent estimates of wet delay. The Online Services for Correcting Atmosphere in Radar (OSCAR) project currently provides water vapor products through web services (http://oscar.jpl.nasa.gov). Unfortunately, such sensors require daytime and cloudless observations. Global and regional numerical weather models can provide an additional estimate of both the dry and atmospheric delays with spatial resolution of (3-100 km) and time scales of 1-3 hours, though these models are of lower accuracy than imaging observations and are benefited by independent observations from independent observations of atmospheric water vapor. Despite these issues, the integration of these techniques for InSAR correction and uncertainty estimation may contribute substantially to the reduction and rigorous characterization of uncertainty in InSAR time series analysis - helping to expand the range of tectonic displacements imaged with InSAR, to robustly constrain geophysical models, and to generate a-priori assessments of satellite acquisitions goals.
Brooker, Simon; Clarke, Siân; Njagi, Joseph Kiambo; Polack, Sarah; Mugo, Benbolt; Estambale, Benson; Muchiri, Eric; Magnussen, Pascal; Cox, Jonathan
2004-07-01
The epidemiology of malaria over small areas remains poorly understood, and this is particularly true for malaria during epidemics in highland areas of Africa, where transmission intensity is low and characterized by acute within and between year variations. We report an analysis of the spatial distribution of clinical malaria during an epidemic and investigate putative risk factors. Active case surveillance was undertaken in three schools in Nandi District, Western Kenya for 10 weeks during a malaria outbreak in May-July 2002. Household surveys of cases and age-matched controls were conducted to collect information on household construction, exposure factors and socio-economic status. Household geographical location and altitude were determined using a hand-held geographical positioning system and landcover types were determined using high spatial resolution satellite sensor data. Among 129 cases identified during the surveillance, which were matched to 155 controls, we identified significant spatial clusters of malaria cases as determined using the spatial scan statistic. Conditional multiple logistic regression analysis showed that the risk of malaria was higher in children who were underweight, who lived at lower altitudes, and who lived in households where drugs were not kept at home. Copyright 2004 Blackwell Publishing Ltd
Nguyen, Ngan; Mulla, Ali; Nelson, Andrew J; Wilson, Timothy D
2014-01-01
The present study explored the problem-solving strategies of high- and low-spatial visualization ability learners on a novel spatial anatomy task to determine whether differences in strategies contribute to differences in task performance. The results of this study provide further insights into the processing commonalities and differences among learners beyond the classification of spatial visualization ability alone, and help elucidate what, if anything, high- and low-spatial visualization ability learners do differently while solving spatial anatomy task problems. Forty-two students completed a standardized measure of spatial visualization ability, a novel spatial anatomy task, and a questionnaire involving personal self-analysis of the processes and strategies used while performing the spatial anatomy task. Strategy reports revealed that there were different ways students approached answering the spatial anatomy task problems. However, chi-square test analyses established that differences in problem-solving strategies did not contribute to differences in task performance. Therefore, underlying spatial visualization ability is the main source of variation in spatial anatomy task performance, irrespective of strategy. In addition to scoring higher and spending less time on the anatomy task, participants with high spatial visualization ability were also more accurate when solving the task problems. © 2013 American Association of Anatomists.
Hurricane Directional Wave Spectrum Spatial Variation at Landfall
NASA Technical Reports Server (NTRS)
Walsh, Edward J.; Wright, C. Wayne; Vandemark, Douglas C.; Krabill, William B.; Garcia, Andrew W.; Houston, Samuel H.; Powell, Mark D.; Black, Peter G.; Marke, Frank D.; Busalacchi, Antonio J. (Technical Monitor)
2000-01-01
On 26 August 1998, hurricane Bonnie was making landfall near Wilmington, NC. The NASA airborne scanning radar altimeter (SRA) carried aboard one of the NOAA WP-3D hurricane hunter aircraft at 2.2 km height documented the sea surface directional wave spectrum in the region between Charleston, SC and Cape Hatteras, NC. The aircraft ground track included both segments along the shoreline and Pamlico Sound as well as far offshore. An animation of the directional wave spectrum spatial variation at landfall will be presented and contrasted with the spatial variation when Bonnie was in the open ocean on 24 August 1998.
Hurricane Directional Wave Spectrum Spatial Variation at Landfall
NASA Technical Reports Server (NTRS)
Walsh, E. J.; Wright, C. W.; Vandemark, D.; Krabill, W. B.; Garcia, A. W.
1999-01-01
On 26 August 1998, hurricane Bonnie was making landfall near Wilmington, NC. The NASA airborne scanning radar altimeter (SRA) carried aboard one of the NOAA WP-3D hurricane hunter aircraft at 2.2 km height documented the sea surface directional wave spectrum in the region between Charleston, SC and Cape Hatteras, NC. The aircraft ground track included both segments along the shoreline and Pamlico Sound as well as far offshore. An animation of the directional wave spectrum spatial variation at landfall will be presented and contrasted with the spatial variation when Bonnie was in the open ocean on 24 August 1998.
Wodschow, Kirstine; Hansen, Birgitte; Schullehner, Jörg; Ersbøll, Annette Kjær
2018-06-08
Concentrations and spatial variations of the four cations Na, K, Mg and Ca are known to some extent for groundwater and to a lesser extent for drinking water. Using Denmark as case, the purpose of this study was to analyze the spatial and temporal variations in the major cations in drinking water. The results will contribute to a better exposure estimation in future studies of the association between cations and diseases. Spatial and temporal variations and the association with aquifer types, were analyzed with spatial scan statistics, linear regression and a multilevel mixed-effects linear regression model. About 65,000 water samples of each cation (1980⁻2017) were included in the study. Results of mean concentrations were 31.4 mg/L, 3.5 mg/L, 12.1 mg/L and 84.5 mg/L for 1980⁻2017 for Na, K, Mg and Ca, respectively. An expected west-east trend in concentrations were confirmed, mainly explained by variations in aquifer types. The trend in concentration was stable for about 31⁻45% of the public water supply areas. It is therefore recommended that the exposure estimate in future health related studies not only be based on a single mean value, but that temporal and spatial variations should also be included.
Wang, Ying; Jiang, Hong; Jin, Jiaxin; Zhang, Xiuying; Lu, Xuehe; Wang, Yueqi
2015-05-20
Carrying abundant nutrition, terrigenous freshwater has a great impact on the spatial and temporal heterogeneity of phytoplankton in coastal waters. The present study analyzed the spatial-temporal variations of Chlorophyll-a (Chl-a) concentration under the influence of discharge from the Yangtze River, based on remotely sensed Chl-a concentrations. The study area was initially zoned to quantitatively investigate the spatial variation patterns of Chl-a. Then, the temporal variation of Chl-a in each zone was simulated by a sinusoidal curve model. The results showed that in the inshore waters, the terrigenous discharge was the predominant driving force determining the pattern of Chl-a, which brings the risk of red tide disasters; while in the open sea areas, Chl-a was mainly affected by meteorological factors. Furthermore, a diversity of spatial and temporal variations of Chl-a existed based on the degree of influences from discharge. The diluted water extended from inshore to the east of Jeju Island. This process affected the Chl-a concentration flowing through the area, and had a potential impact on the marine environment. The Chl-a from September to November showed an obvious response to the discharge from July to September with a lag of 1 to 2 months.
Wang, Ying; Jiang, Hong; Jin, Jiaxin; Zhang, Xiuying; Lu, Xuehe; Wang, Yueqi
2015-01-01
Carrying abundant nutrition, terrigenous freshwater has a great impact on the spatial and temporal heterogeneity of phytoplankton in coastal waters. The present study analyzed the spatial-temporal variations of Chlorophyll-a (Chl-a) concentration under the influence of discharge from the Yangtze River, based on remotely sensed Chl-a concentrations. The study area was initially zoned to quantitatively investigate the spatial variation patterns of Chl-a. Then, the temporal variation of Chl-a in each zone was simulated by a sinusoidal curve model. The results showed that in the inshore waters, the terrigenous discharge was the predominant driving force determining the pattern of Chl-a, which brings the risk of red tide disasters; while in the open sea areas, Chl-a was mainly affected by meteorological factors. Furthermore, a diversity of spatial and temporal variations of Chl-a existed based on the degree of influences from discharge. The diluted water extended from inshore to the east of Jeju Island. This process affected the Chl-a concentration flowing through the area, and had a potential impact on the marine environment. The Chl-a from September to November showed an obvious response to the discharge from July to September with a lag of 1 to 2 months. PMID:26006121
Dalecky, Ambroise; Renucci, Marielle; Tirard, Alain; Debout, Gabriel; Roux, Maurice; Kjellberg, Finn; Provost, Erick
2007-09-01
In social insects, biochemicals found at the surface of the cuticle are involved in the recognition process and in protection against desiccation and pathogens. However, the relative contribution of evolutionary forces in shaping diversity of these biochemicals remains largely unresolved in ants. We determined the composition of epicuticular biochemicals for workers sampled in 12 populations of the ant Petalomyrmex phylax from Cameroon. Genetic variation at 12 microsatellite markers was used to infer population history and to provide null expectations under the neutrality hypothesis. Genetic data suggest a recent southward range expansion of this ant species. Furthermore, there is a decline southward in the numbers of queens present in mature colonies. Here, we contrast the pattern of biochemical variation against genetic, social and spatial parameters. We thus provide the first estimates of the relative contribution of neutral and selective processes on variation of ant cuticular profile. Populations in migration-drift disequilibrium showed reduction of within-population variation for genetic markers as well as for cuticular profiles. In these populations, the cuticular profile became biased towards a limited number of high molecular weight molecules. Within- and among-population biochemical variation was explained by both genetic and social variation and by the spatial distribution of populations. We therefore propose that during range expansion of P. phylax, the composition of epicuticular compounds has been affected by a combination of neutral processes - genetic drift and spatially limited dispersal - and spatially varying selection, social organization and environmental effects.
Unraveling Cell Processes: Interference Imaging Interwoven with Data Analysis
Brazhe, A. R.; Pavlov, A. N.; Erokhova, L. A.; Yusipovich, A. I.; Maksimov, G. V.; Mosekilde, E.; Sosnovtseva, O. V.
2006-01-01
The paper presents results on the application of interference microscopy and wavelet-analysis for cell visualization and studies of cell dynamics. We demonstrate that interference imaging of erythrocytes can reveal reorganization of the cytoskeleton and inhomogenity in the distribution of hemoglobin, and that interference imaging of neurons can show intracellular compartmentalization and submembrane structures. We investigate temporal and spatial variations of the refractive index for different cell types: isolated neurons, mast cells and erythrocytes. We show that the refractive dynamical properties differ from cell type to cell type and depend on the cellular compartment. Our results suggest that low frequency variations (0.1–0.6 Hz) result from plasma membrane processes and that higher frequency variations (20–26 Hz) are related to the movement of vesicles. Using double-wavelet analysis, we study the modulation of the 1 Hz rhythm in neurons and reveal its changes under depolarization and hyperpolarization of the plasma membrane. We conclude that interference microscopy combined with wavelet analysis is a useful technique for non-invasive cell studies, cell visualization, and investigation of plasma membrane properties. PMID:19669463
Modeling Chinese ionospheric layer parameters based on EOF analysis
NASA Astrophysics Data System (ADS)
Yu, You; Wan, Weixing; Xiong, Bo; Ren, Zhipeng; Zhao, Biqiang; Zhang, Yun; Ning, Baiqi; Liu, Libo
2015-05-01
Using 24-ionosonde observations in and around China during the 20th solar cycle, an assimilative model is constructed to map the ionospheric layer parameters (foF2, hmF2, M(3000)F2, and foE) over China based on empirical orthogonal function (EOF) analysis. First, we decompose the background maps from the International Reference Ionosphere model 2007 (IRI-07) into different EOF modes. The obtained EOF modes consist of two factors: the EOF patterns and the corresponding EOF amplitudes. These two factors individually reflect the spatial distributions (e.g., the latitudinal dependence such as the equatorial ionization anomaly structure and the longitude structure with east-west difference) and temporal variations on different time scales (e.g., solar cycle, annual, semiannual, and diurnal variations) of the layer parameters. Then, the EOF patterns and long-term observations of ionosondes are assimilated to get the observed EOF amplitudes, which are further used to construct the Chinese Ionospheric Maps (CIMs) of the layer parameters. In contrast with the IRI-07 model, the mapped CIMs successfully capture the inherent temporal and spatial variations of the ionospheric layer parameters. Finally, comparison of the modeled (EOF and IRI-07 model) and observed values reveals that the EOF model reproduces the observation with smaller root-mean-square errors and higher linear correlation coefficients. In addition, IRI discrepancy at the low latitude especially for foF2 is effectively removed by EOF model.
Modeling Chinese ionospheric layer parameters based on EOF analysis
NASA Astrophysics Data System (ADS)
Yu, You; Wan, Weixing
2016-04-01
Using 24-ionosonde observations in and around China during the 20th solar cycle, an assimilative model is constructed to map the ionospheric layer parameters (foF2, hmF2, M(3000)F2, and foE) over China based on empirical orthogonal function (EOF) analysis. First, we decompose the background maps from the International Reference Ionosphere model 2007 (IRI-07) into different EOF modes. The obtained EOF modes consist of two factors: the EOF patterns and the corresponding EOF amplitudes. These two factors individually reflect the spatial distributions (e.g., the latitudinal dependence such as the equatorial ionization anomaly structure and the longitude structure with east-west difference) and temporal variations on different time scales (e.g., solar cycle, annual, semiannual, and diurnal variations) of the layer parameters. Then, the EOF patterns and long-term observations of ionosondes are assimilated to get the observed EOF amplitudes, which are further used to construct the Chinese Ionospheric Maps (CIMs) of the layer parameters. In contrast with the IRI-07 model, the mapped CIMs successfully capture the inherent temporal and spatial variations of the ionospheric layer parameters. Finally, comparison of the modeled (EOF and IRI-07 model) and observed values reveals that the EOF model reproduces the observation with smaller root-mean-square errors and higher linear correlation co- efficients. In addition, IRI discrepancy at the low latitude especially for foF2 is effectively removed by EOF model.
Spatial and temporal analysis of the total electron content over China during 2011-2014
NASA Astrophysics Data System (ADS)
Zheng, Jianchang; Zhao, Biqiang; Xiong, Bo; Wan, Weixing
2016-06-01
In the present work we investigate variations of ionospheric total electron content (TEC) with empirical orthogonal function (EOF) analysis, the four-year TEC data are derived from ∼250 GPS observations of the crustal movement observation network of China (CMONOC) over East Asian area (30-55°N, 70-140°E) during the period from 2011, January to 2014, December. The first two EOF components together account for ∼93.78% of total variance of the original TEC data set, and it is found that the first EOF component represents a spatial variability of semi-annual variation and the second EOF component exhibits pronounced east-west longitudinal difference with respect to zero valued geomagnetic declination line. In addition, climatology of the vertical plasma drift velocity vdz induced by HWM zonal wind field (∼300 km) are studied in the paper. Results shows vdz displays significant east-west longitudinal difference at 10:00 LT and 20:00 LT, and its daytime temporal variation is consistent with the second EOF principal component, which suggests that the east-west longitudinal variability is partly caused by the thermospheric zonal wind and geomagnetic declination. It is expected that with this dense GPS network, local ionospheric variability can be described more accurately and a more realistic ionospheric model can be constructed and used for the satellite navigation and radio propagation.
Soil respiration across a permafrost transition zone: spatial structure and environmental correlates
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stegen, James C.; Anderson, Carolyn G.; Bond-Lamberty, Ben
Soil respiration is a key ecosystem function whereby shifts in respiration rates can shift systems from carbon sinks to sources. Soil respiration in permafrost-associated systems is particularly important given climate change driven permafrost thaw that leads to significant uncertainty in resulting ecosystem carbon dynamics. Here we characterize the spatial structure and environmental drivers of soil respiration across a permafrost transition zone. We find that soil respiration is characterized by a non-linear threshold that occurs at active-layer depths greater than 140 cm. We also find that within each season, tree basal area is a dominant driver of soil respiration regardless of spatial scale, but onlymore » in spatial domains with significant spatial variability in basal area. Our analyses further show that spatial variation (the coefficient of variation) and mean-variance power-law scaling of soil respiration in our boreal system are consistent with previous work in other ecosystems (e.g., tropical forests) and in population ecology, respectively. Comparing our results to those in other ecosystems suggests that temporally stable features such as tree-stand structure are often primary drivers of spatial variation in soil respiration. If so, this provides an opportunity to better estimate the magnitude and spatial variation in soil respiration through remote sensing. Finally, combining such an approach with broader knowledge of thresholding behavior – here related to active layer depth – would provide empirical constraints on models aimed at predicting ecosystem responses to ongoing permafrost thaw.« less
Soil respiration across a permafrost transition zone: spatial structure and environmental correlates
Stegen, James C.; Anderson, Carolyn G.; Bond-Lamberty, Ben; ...
2017-09-28
Soil respiration is a key ecosystem function whereby shifts in respiration rates can shift systems from carbon sinks to sources. Soil respiration in permafrost-associated systems is particularly important given climate change driven permafrost thaw that leads to significant uncertainty in resulting ecosystem carbon dynamics. Here we characterize the spatial structure and environmental drivers of soil respiration across a permafrost transition zone. We find that soil respiration is characterized by a non-linear threshold that occurs at active-layer depths greater than 140 cm. We also find that within each season, tree basal area is a dominant driver of soil respiration regardless of spatial scale, but onlymore » in spatial domains with significant spatial variability in basal area. Our analyses further show that spatial variation (the coefficient of variation) and mean-variance power-law scaling of soil respiration in our boreal system are consistent with previous work in other ecosystems (e.g., tropical forests) and in population ecology, respectively. Comparing our results to those in other ecosystems suggests that temporally stable features such as tree-stand structure are often primary drivers of spatial variation in soil respiration. If so, this provides an opportunity to better estimate the magnitude and spatial variation in soil respiration through remote sensing. Finally, combining such an approach with broader knowledge of thresholding behavior – here related to active layer depth – would provide empirical constraints on models aimed at predicting ecosystem responses to ongoing permafrost thaw.« less
Soil respiration across a permafrost transition zone: spatial structure and environmental correlates
NASA Astrophysics Data System (ADS)
Stegen, James C.; Anderson, Carolyn G.; Bond-Lamberty, Ben; Crump, Alex R.; Chen, Xingyuan; Hess, Nancy
2017-09-01
Soil respiration is a key ecosystem function whereby shifts in respiration rates can shift systems from carbon sinks to sources. Soil respiration in permafrost-associated systems is particularly important given climate change driven permafrost thaw that leads to significant uncertainty in resulting ecosystem carbon dynamics. Here we characterize the spatial structure and environmental drivers of soil respiration across a permafrost transition zone. We find that soil respiration is characterized by a non-linear threshold that occurs at active-layer depths greater than 140 cm. We also find that within each season, tree basal area is a dominant driver of soil respiration regardless of spatial scale, but only in spatial domains with significant spatial variability in basal area. Our analyses further show that spatial variation (the coefficient of variation) and mean-variance power-law scaling of soil respiration in our boreal system are consistent with previous work in other ecosystems (e.g., tropical forests) and in population ecology, respectively. Comparing our results to those in other ecosystems suggests that temporally stable features such as tree-stand structure are often primary drivers of spatial variation in soil respiration. If so, this provides an opportunity to better estimate the magnitude and spatial variation in soil respiration through remote sensing. Combining such an approach with broader knowledge of thresholding behavior - here related to active layer depth - would provide empirical constraints on models aimed at predicting ecosystem responses to ongoing permafrost thaw.
Tello, J. Sebastián; Myers, Jonathan A.; Macía, Manuel J.; Fuentes, Alfredo F.; Cayola, Leslie; Arellano, Gabriel; Loza, M. Isabel; Torrez, Vania; Cornejo, Maritza; Miranda, Tatiana B.; Jørgensen, Peter M.
2015-01-01
Despite long-standing interest in elevational-diversity gradients, little is known about the processes that cause changes in the compositional variation of communities (β-diversity) across elevations. Recent studies have suggested that β-diversity gradients are driven by variation in species pools, rather than by variation in the strength of local community assembly mechanisms such as dispersal limitation, environmental filtering, or local biotic interactions. However, tests of this hypothesis have been limited to very small spatial scales that limit inferences about how the relative importance of assembly mechanisms may change across spatial scales. Here, we test the hypothesis that scale-dependent community assembly mechanisms shape biogeographic β-diversity gradients using one of the most well-characterized elevational gradients of tropical plant diversity. Using an extensive dataset on woody plant distributions along a 4,000-m elevational gradient in the Bolivian Andes, we compared observed patterns of β-diversity to null-model expectations. β-deviations (standardized differences from null values) were used to measure the relative effects of local community assembly mechanisms after removing sampling effects caused by variation in species pools. To test for scale-dependency, we compared elevational gradients at two contrasting spatial scales that differed in the size of local assemblages and regions by at least an order of magnitude. Elevational gradients in β-diversity persisted after accounting for regional variation in species pools. Moreover, the elevational gradient in β-deviations changed with spatial scale. At small scales, local assembly mechanisms were detectable, but variation in species pools accounted for most of the elevational gradient in β-diversity. At large spatial scales, in contrast, local assembly mechanisms were a dominant force driving changes in β-diversity. In contrast to the hypothesis that variation in species pools alone drives β-diversity gradients, we show that local community assembly mechanisms contribute strongly to systematic changes in β-diversity across elevations. We conclude that scale-dependent variation in community assembly mechanisms underlies these iconic gradients in global biodiversity. PMID:25803846
Forest Fires and Post - Fire Regeneration in Algeria Analysis with Satellite Data
NASA Astrophysics Data System (ADS)
Zegrar, Ahmed
2016-07-01
The Algerian forests are characterized by a particularly flammable material and fuel. The wind, the relief and the slope facilitates the propagation of fire. The use of remote sensing data multi-dates, combined with other types of data of various kinds on the environment and forest burned, opens up interesting perspectives for the management of post-fire regeneration. In this study the use of multi-temporal remote sensing image Alsat-1 and Landsat combined with other types of data concerning both background and burned down forest appears to be promising in evaluating and spatial and temporal effects of post fire regeneration. A spatial analysis taking into consideration the characteristics of the burned down site in the North West of Algeria, allowed to better account new factors to explain the regeneration and its temporal and spatial variation. We intended to show the potential use of remote sensing data from satellite ALSAT-1, of spatial resolution of 32 m. . This approach allows showing the contribution of the data of Algerian satellite ALSAT in the detection and the well attended some forest fires in Algeria.
Zhang, Houxi; Zhuang, Shunyao; Qian, Haiyan; Wang, Feng; Ji, Haibao
2015-01-01
Understanding the spatial variability of soil organic carbon (SOC) must be enhanced to improve sampling design and to develop soil management strategies in terrestrial ecosystems. Moso bamboo (Phyllostachys pubescens Mazel ex Houz.) forests have a high SOC storage potential; however, they also vary significantly spatially. This study investigated the spatial variability of SOC (0-20 cm) in association with other soil properties and with spatial variables in the Moso bamboo forests of Jian’ou City, which is a typical bamboo hometown in China. 209 soil samples were collected from Moso bamboo stands and then analyzed for SOC, bulk density (BD), pH, cation exchange capacity (CEC), and gravel content (GC) based on spatial distribution. The spatial variability of SOC was then examined using geostatistics. A Kriging map was produced through ordinary interpolation and required sample numbers were calculated by classical and Kriging methods. An aggregated boosted tree (ABT) analysis was also conducted. A semivariogram analysis indicated that ln(SOC) was best fitted with an exponential model and that it exhibited moderate spatial dependence, with a nugget/sill ratio of 0.462. SOC was significantly and linearly correlated with BD (r = −0.373**), pH (r = −0.429**), GC (r = −0.163*), CEC (r = 0.263**), and elevation (r = 0.192**). Moreover, the Kriging method requires fewer samples than the classical method given an expected standard error level as per a variance analysis. ABT analysis indicated that the physicochemical variables of soil affected SOC variation more significantly than spatial variables did, thus suggesting that the SOC in Moso bamboo forests can be strongly influenced by management practices. Thus, this study provides valuable information in relation to sampling strategy and insight into the potential of adjustments in agronomic measure, such as in fertilization for Moso bamboo production. PMID:25789615
The water column diffuse attenuation coefficient (Kd) of the Louisiana Continental Shelf (LCS) was examined during ten years to characterize the spatial and temporal variations on monthly scales from 1998 to 2007. This region is well-known for summer hypoxia (dissolved oxygen < 2...
Regional gradient analysis and spatial pattern of woody plant communities in Oregon forests.
J.L. Ohmann; T.A. Spies
1998-01-01
Knowledge of regional-scale patterns of ecological community structure, and of factors that control them, is largely conceptual. Regional- and local-scale factors associated with regional variation in community composition have not been quantified. We analyzed data on woody plant species abundance from 2443 field plots across natural and seminatural forests and...
Genetic Variance in Processing Speed Drives Variation in Aging of Spatial and Memory Abilities
ERIC Educational Resources Information Center
Finkel, Deborah; Reynolds, Chandra A.; McArdle, John J.; Hamagami, Fumiaki; Pedersen, Nancy L.
2009-01-01
Previous analyses have identified a genetic contribution to the correlation between declines with age in processing speed and higher cognitive abilities. The goal of the current analysis was to apply the biometric dual change score model to consider the possibility of temporal dynamics underlying the genetic covariance between aging trajectories…
Kelsey, Katharine C.; Wickland, Kimberly P.; Striegl, Robert G.; Neff, Jason C.
2012-01-01
Carbon dynamics of high-latitude regions are an important and highly uncertain component of global carbon budgets, and efforts to constrain estimates of soil-atmosphere carbon exchange in these regions are contingent on accurate representations of spatial and temporal variability in carbon fluxes. This study explores spatial and temporal variability in soilatmosphere carbon dynamics at both fine and coarse spatial scales in a high-elevation, permafrost-dominated boreal black spruce forest. We evaluate the importance of landscape-level investigations of soil-atmosphere carbon dynamics by characterizing seasonal trends in soil-atmosphere carbon exchange, describing soil temperature-moisture-respiration relations, and quantifying temporal and spatial variability at two spatial scales: the plot scale (0–5 m) and the landscape scale (500–1000 m). Plot-scale spatial variability (average variation on a given measurement day) in soil CO2 efflux ranged from a coefficient of variation (CV) of 0.25 to 0.69, and plot-scale temporal variability (average variation of plots across measurement days) in efflux ranged from a CV of 0.19 to 0.36. Landscape-scale spatial and temporal variability in efflux was represented by a CV of 0.40 and 0.31, respectively, indicating that plot-scale spatial variability in soil respiration is as great as landscape-scale spatial variability at this site. While soil respiration was related to soil temperature at both the plot- and landscape scale, landscape-level descriptions of soil moisture were necessary to define soil respiration-moisture relations. Soil moisture variability was also integral to explaining temporal variability in soil respiration. Our results have important implications for research efforts in high-latitude regions where remote study sites make landscape-scale field campaigns challenging.
Levels and patterns of internal migration in Europe: A cohort perspective.
Bernard, Aude
2017-11-01
Europe displays important variations in the level of internal migration, with a clear spatial gradient of high mobility in northern and western Europe but lower mobility in the south and east. However, cross-national variation in levels of internal migration remains poorly understood, because it is analysed almost exclusively using cross-sectional data and period measures. This paper seeks to advance understanding of cross-national variation in migration levels in 14 European countries by drawing on a recently proposed suite of migration cohort measures, coupled with internationally comparable retrospective residential histories. It shows that differences in migration levels are mainly attributable to variation in the extent of repeat movement, which is underpinned by the differences in mean ages at first and last move that together delineate the average length of migration careers. Cohort analysis provides a robust foundation for exploring the demographic mechanisms underpinning variation in migration levels across countries and over time.
Temporal variation of meandering intensity and domain-wide lateral oscillations of the Gulf Stream
NASA Technical Reports Server (NTRS)
Lee, Tong; Cornillon, Peter
1995-01-01
The path of the Gulf Stream exhibits two modes of variability: wavelike spatial meanders associated with instability processes and large-sale lateral shifts of the path presumably due to atmospheric forcing. The objectives of this study are to examine the temporal variation of the intensity of spatial meandering in the stream, to characterize large-scale lateral oscillations in the stream's path, and to study the correlation betwen these two dynamically distinct modes of variability. The data used for this analysis are path displacemets ofthe Gulf Stream between 75 deg and 60 deg W obtained from AVHRR-derived (Advanced Very High Resolution Radiometer) infrared images for the period April 1982 through December 1989. Meandering intensity, measured by the spatial root-mean-sqaure displacement of the stream path, displays a 9-month dominant periodicity which is persistent through the study period. The 9-month fluctuation in meandering intensity may be related to the interaction of Rosseby waves with the stream. Interannual variation of meandering intensity is also found to be significant, with meandering being mich more intense during 1985 than it was in 1987. Annual variation, however,is weak and not well-defined.The spatially averaged position of the stream, which reflects nonmeandering large-scale lateral oscillations of the stream path, is dominated by an annual cycle. On average, the mean position is farthest north in November and farthest south in April. The first empirical orthogonal function mode of the space-time path displacements represents lateral oscillatins that are in-phase over the space-time domain. Interannual oscillations are also observed and are found to be weaker than the annual oscillation. The eigenvalue of the first mode indicates that about 21.5% of the total space-time variability of the stream path can be attibuted to domain-wide lateral oscillation. The correlation between meandering intensity and domain-wide lateral oscillations is very weak.
NASA Astrophysics Data System (ADS)
Hopkinson, C.; Brisco, B.; Chasmer, L.; Devito, K.; Montgomery, J. S.; Patterson, S.; Petrone, R. M.
2017-12-01
The dense forest cover of the Western Boreal Plains of northern Alberta is underlain by a mix of glacial moraines, sandy outwash sediments and clay plains possessing spatially variable hydraulic conductivities. The region is also characterised by a large number of post-glacial surface depression wetlands that have seasonally and topographically limited surface connectivity. Consequently, drainage along shallow regional hydraulic gradients may be dominated either by variations in surface geology or local variations in Et. Long-term government lake level monitoring is sparse in this region, but over a decade of hydrometeorological monitoring has taken place around the Utikuma Regional Study Area (URSA), a research site led by the University of Alberta. In situ lake and ground water level data are here combined with time series of airborne lidar and RadarSat II synthetic aperture radar (SAR) data to assess the spatial variability of water levels during late summer period characterised by flow recession. Long term Lidar data were collected or obtained by the authors in August of 2002, 2008, 2011 and 2016, while seasonal SAR data were captured approximately every 24 days during the summers of 2015, 2016 and 2017. Water levels for wetlands exceeding 100m2 in area across a north-trending 20km x 5km topographic gradient north of Utikuma Lake were extracted directly from the lidar and indirectly from the SAR. The recent seasonal variability in spatial water levels was extracted from SAR, while the lidar data illustrated more long term trends associated with land use and riparian vegetation succession. All water level data collected in August were combined and averaged at multiple scales using a raster focal statistics function to generate a long term spatial map of the regional hydraulic gradient and scale-dependent variations. Areas of indicated high and low drainage efficiency were overlain onto layers of landcover and surface geology to ascertain causal relationships. Areas associated with high spatial variability in water level illustrate reduced drainage connectivity, while areas of reduced variability indicate high surface connectivity and/or hydraulic conductivity. The hypothesis of surface geology controls on local wetland connectivity and landscape drainage efficiency is supported through this analysis.
NASA Astrophysics Data System (ADS)
Selvakumar, R.; Ramasamy, SM.
2014-12-01
Flooding is a naturally recurrent phenomenon that causes severe damage to lives and property. Predictions on flood-prone zones are made based on intensity-duration of rainfall, carrying capacity of drainage, and natural or man-made obstructions. Particularly, the lower part of the drainage system and its adjacent geomorphic landforms like floodplains and deltaic plains are considered for analysis, but stagnation in parts of basins that are far away from major riverine systems is less unveiled. Similarly, uncharacteristic flooding in the upper and middle parts of drainage, especially in zones of an anomalous drainage pattern, is also least understood. Even though topographic differences are attributed for such anomalous spatial occurrence of floods, its genetic cause has to be identified for effective management practice. Added to structural and lithological variations, tectonic movements too impart micro-scale terrain undulations. Because active tectonic movements are slow-occurring, long-term geological processes, its resultant topographical variations and drainage anomalies are least correlated with floods. The recent floods of Tamil Nadu also exhibit a unique distribution pattern emphasizing the role of tectonics over it. Hence a detailed geoinformatics-based analysis was carried out to envisage the relationship between spatial distribution of flood and active tectonic elements such as regional arches and deeps, block faults, and graben and drainage anomalies such as deflected drainage, compressed meander, and eyed drainages. The analysis reveals that micro-scale topographic highs and lows imparted by active tectonic movements and its further induced drainage anomalies have substantially controlled the distribution pattern of flood.
NASA Astrophysics Data System (ADS)
Lu, Xiaoguang; Xue, Hui; Jolly, Marie-Pierre; Guetter, Christoph; Kellman, Peter; Hsu, Li-Yueh; Arai, Andrew; Zuehlsdorff, Sven; Littmann, Arne; Georgescu, Bogdan; Guehring, Jens
2011-03-01
Cardiac perfusion magnetic resonance imaging (MRI) has proven clinical significance in diagnosis of heart diseases. However, analysis of perfusion data is time-consuming, where automatic detection of anatomic landmarks and key-frames from perfusion MR sequences is helpful for anchoring structures and functional analysis of the heart, leading toward fully automated perfusion analysis. Learning-based object detection methods have demonstrated their capabilities to handle large variations of the object by exploring a local region, i.e., context. Conventional 2D approaches take into account spatial context only. Temporal signals in perfusion data present a strong cue for anchoring. We propose a joint context model to encode both spatial and temporal evidence. In addition, our spatial context is constructed not only based on the landmark of interest, but also the landmarks that are correlated in the neighboring anatomies. A discriminative model is learned through a probabilistic boosting tree. A marginal space learning strategy is applied to efficiently learn and search in a high dimensional parameter space. A fully automatic system is developed to simultaneously detect anatomic landmarks and key frames in both RV and LV from perfusion sequences. The proposed approach was evaluated on a database of 373 cardiac perfusion MRI sequences from 77 patients. Experimental results of a 4-fold cross validation show superior landmark detection accuracies of the proposed joint spatial-temporal approach to the 2D approach that is based on spatial context only. The key-frame identification results are promising.
Demographic controls of aboveground forest biomass across North America.
Vanderwel, Mark C; Zeng, Hongcheng; Caspersen, John P; Kunstler, Georges; Lichstein, Jeremy W
2016-04-01
Ecologists have limited understanding of how geographic variation in forest biomass arises from differences in growth and mortality at continental to global scales. Using forest inventories from across North America, we partitioned continental-scale variation in biomass growth and mortality rates of 49 tree species groups into (1) species-independent spatial effects and (2) inherent differences in demographic performance among species. Spatial factors that were separable from species composition explained 83% and 51% of the respective variation in growth and mortality. Moderate additional variation in mortality (26%) was attributable to differences in species composition. Age-dependent biomass models showed that variation in forest biomass can be explained primarily by spatial gradients in growth that were unrelated to species composition. Species-dependent patterns of mortality explained additional variation in biomass, with forests supporting less biomass when dominated by species that are highly susceptible to competition (e.g. Populus spp.) or to biotic disturbances (e.g. Abies balsamea). © 2016 John Wiley & Sons Ltd/CNRS.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garcia-Lechuga, M.; Laser Processing Group, Instituto de Óptica “Daza de Valdés,” CSIC, 28006-Madrid; Fuentes, L. M.
2014-10-07
We report a detailed characterization of the spatial resolution provided by two-photon absorption spectroscopy suited for plasma diagnosis via the 1S-2S transition of atomic hydrogen for optogalvanic detection and laser induced fluorescence (LIF). A precise knowledge of the spatial resolution is crucial for a correct interpretation of measurements, if the plasma parameters to be analysed undergo strong spatial variations. The present study is based on a novel approach which provides a reliable and realistic determination of the spatial resolution. Measured irradiance distribution of laser beam waists in the overlap volume, provided by a high resolution UV camera, are employed tomore » resolve coupled rate equations accounting for two-photon excitation, fluorescence decay and ionization. The resulting three-dimensional yield distributions reveal in detail the spatial resolution for optogalvanic and LIF detection and related saturation due to depletion. Two-photon absorption profiles broader than the Fourier transform-limited laser bandwidth are also incorporated in the calculations. The approach allows an accurate analysis of the spatial resolution present in recent and future measurements.« less
NASA Astrophysics Data System (ADS)
Van Oost, Kristof; Nadeu, Elisabet; Wiaux, François; Wang, Zhengang; Stevens, François; Vanclooster, Marnik; Tran, Anh; Bogaert, Patrick; Doetterl, Sebastian; Lambot, Sébastien; Van wesemael, Bas
2014-05-01
In this paper, we synthesize the main outcomes of a collaborative project (2009-2014) initiated at the UCL (Belgium). The main objective of the project was to increase our understanding of soil organic matter dynamics in complex landscapes and use this to improve predictions of regional scale soil carbon balances. In a first phase, the project characterized the emergent spatial variability in soil organic matter storage and key soil properties at the regional scale. Based on the integration of remote sensing, geomorphological and soil analysis techniques, we quantified the temporal and spatial variability of soil carbon stock and pool distribution at the local and regional scales. This work showed a linkage between lateral fluxes of C in relation with sediment transport and the spatial variation in carbon storage at multiple spatial scales. In a second phase, the project focused on characterizing key controlling factors and process interactions at the catena scale. In-situ experiments of soil CO2 respiration showed that the soil carbon response at the catena scale was spatially heterogeneous and was mainly controlled by the catenary variation of soil physical attributes (soil moisture, temperature, C quality). The hillslope scale characterization relied on advanced hydrogeophysical techniques such as GPR (Ground Penetrating Radar), EMI (Electromagnetic induction), ERT (Electrical Resistivity Tomography), and geophysical inversion and data mining tools. Finally, we report on the integration of these insights into a coupled and spatially explicit model and its application. Simulations showed that C stocks and redistribution of mass and energy fluxes are closely coupled, they induce structured spatial and temporal patterns with non negligible attached uncertainties. We discuss the main outcomes of these activities in relation to sink-source behavior and relevance of erosion processes for larger-scale C budgets.
Lin, Guojun; Stralberg, Diana; Gong, Guiquan; Huang, Zhongliang; Ye, Wanhui; Wu, Linfang
2013-01-01
Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.
Geostatistical modelling of household malaria in Malawi
NASA Astrophysics Data System (ADS)
Chirombo, J.; Lowe, R.; Kazembe, L.
2012-04-01
Malaria is one of the most important diseases in the world today, common in tropical and subtropical areas with sub-Saharan Africa being the region most burdened, including Malawi. This region has the right combination of biotic and abiotic components, including socioeconomic, climatic and environmental factors that sustain transmission of the disease. Differences in these conditions across the country consequently lead to spatial variation in risk of the disease. Analysis of nationwide survey data that takes into account this spatial variation is crucial in a resource constrained country like Malawi for targeted allocation of scare resources in the fight against malaria. Previous efforts to map malaria risk in Malawi have been based on limited data collected from small surveys. The Malaria Indicator Survey conducted in 2010 is the most comprehensive malaria survey carried out in Malawi and provides point referenced data for the study. The data has been shown to be spatially correlated. We use Bayesian logistic regression models with spatial correlation to model the relationship between malaria presence in children and covariates such as socioeconomic status of households and meteorological conditions. This spatial model is then used to assess how malaria varies spatially and a malaria risk map for Malawi is produced. By taking intervention measures into account, the developed model is used to assess whether they have an effect on the spatial distribution of the disease and Bayesian kriging is used to predict areas where malaria risk is more likely to increase. It is hoped that this study can help reveal areas that require more attention from the authorities in the continuing fight against malaria, particularly in children under the age of five.
Snowpack spatial and temporal variability assessment using SMP high-resolution penetrometer
NASA Astrophysics Data System (ADS)
Komarov, Anton; Seliverstov, Yuriy; Sokratov, Sergey; Grebennikov, Pavel
2017-04-01
This research is focused on study of spatial and temporal variability of structure and characteristics of snowpack, quick identification of layers based on hardness and dispersion values received from snow micro penetrometer (SMP). We also discuss the detection of weak layers and definition of their parameters in non-alpine terrain. As long as it is the first SMP tool available in Russia, our intent is to test it in different climate and weather conditions. During two separate snowpack studies in plain and mountain landscapes, we derived density and grain size profiles by comparing snow density and grain size from snowpits and SMP measurements. The first case study was MSU meteorological observatory test site in Moscow. SMP data was obtained by 6 consecutive measurements along 10 m transects with a horizontal resolution of approximately 50 cm. The detailed description of snowpack structure, density, grain size, air and snow temperature was also performed. By comparing this information, the detailed scheme of snowpack evolution was created. The second case study was in Khibiny mountains. One 10-meter-long transect was made. SMP, density, grain size and snow temperature data was obtained with horizontal resolution of approximately 50 cm. The high-definition profile of snowpack density variation was acquired using received data. The analysis of data reveals high spatial and temporal variability in snow density and layer structure in both horizontal and vertical dimensions. It indicates that the spatial variability is exhibiting similar spatial patterns as surface topology. This suggests a strong influence from such factors as wind and liquid water pressure on the temporal and spatial evolution of snow structure. It was also defined, that spatial variation of snowpack characteristics is substantial even within homogeneous plain landscape, while in high-latitude mountain regions it grows significantly.
NASA Astrophysics Data System (ADS)
Bailey, Bernard Charles
Increasing the optical range of target detection and recognition continues to be an area of great interest in the ocean environment. Light attenuation limits radiative and information transfer for image formation in water. These limitations are difficult to surmount in conventional underwater imaging system design. Methods for the formation of images in scattering media generally rely upon temporal or spatial methodologies. Some interesting designs have been developed in an attempt to circumvent or overcome the scattering problem. This document describes a variation of the spatial interferometric technique that relies upon projected spatial gratings with subsequent detection against a coherent return signal for the purpose of noise reduction and image enhancement. A model is developed that simulates the projected structured illumination through turbid water to a target and its return to a detector. The model shows an unstructured backscatter superimposed on a structured return signal. The model can predict the effect on received signal to noise of variations in the projected spatial frequency and turbidity. The model has been extended to predict what a camera would actually see so that various noise reduction schemes can be modeled. Finally, some water tank tests are presented validating original hypothesis and model predictions. The method is advantageous in not requiring temporal synchronization between reference and signal beams and may use a continuous illumination source. Spatial coherency of the beam allows detection of the direct return, while scattered light appears as a noncoherent noise term. Both model and illumination method should prove to be valuable tools in ocean research.
A Land System representation for global assessments and land-use modeling.
van Asselen, Sanneke; Verburg, Peter H
2012-10-01
Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.
Zhaohua Dai; Carl Trettin; Changsheng Li; Harbin Li; Ge Sun; Devendra Amatya
2011-01-01
Emissions of methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) from a forested watershed (160 ha) in South Carolina, USA, were estimated with a spatially explicit watershed-scale modeling framework that utilizes the spatial variations in physical and biogeochemical characteristics across watersheds. The target watershed (WS80) consisting of wetland (23%) and...
Abou Nader, Christelle; Loutfi, Hadi; Pellen, Fabrice; Le Jeune, Bernard; Le Brun, Guy; Lteif, Roger; Abboud, Marie
2017-01-01
In this paper, we report measurements of wine viscosity, correlated to polarized laser speckle results. Experiments were performed on white wine samples produced with a single grape variety. Effects of the wine making cellar, the grape variety, and the vintage on wine Brix degree, alcohol content, viscosity, and speckle parameters are considered. We show that speckle parameters, namely, spatial contrast and speckle decorrelation time, as well as the inertia moment extracted from the temporal history speckle pattern, are mainly affected by the alcohol and sugar content and hence the wine viscosity. Principal component analysis revealed a high correlation between laser speckle results on the one hand and viscosity and Brix degree values on the other. As speckle analysis proved to be an efficient method of measuring the variation of the viscosity of white mono-variety wine, one can therefore consider it as an alternative method to wine sensory analysis. PMID:29027936
Nader, Christelle Abou; Loutfi, Hadi; Pellen, Fabrice; Jeune, Bernard Le; Le Brun, Guy; Lteif, Roger; Abboud, Marie
2017-10-13
In this paper, we report measurements of wine viscosity, correlated to polarized laser speckle results. Experiments were performed on white wine samples produced with a single grape variety. Effects of the wine making cellar, the grape variety, and the vintage on wine Brix degree, alcohol content, viscosity, and speckle parameters are considered. We show that speckle parameters, namely, spatial contrast and speckle decorrelation time, as well as the inertia moment extracted from the temporal history speckle pattern, are mainly affected by the alcohol and sugar content and hence the wine viscosity. Principal component analysis revealed a high correlation between laser speckle results on the one hand and viscosity and Brix degree values on the other. As speckle analysis proved to be an efficient method of measuring the variation of the viscosity of white mono-variety wine, one can therefore consider it as an alternative method to wine sensory analysis.
NASA Astrophysics Data System (ADS)
Hirota, N.; Takayabu, Y. N.; Watanabe, M.; Kimoto, M.; Chikira, M.
2013-12-01
This study shows that a proper treatment of convective entrainment is essential in determining spatial distributions and temporal variations of precipitation by numerical experiments. They have performed and compared four experiments with different entrainment characteristics: a control (Ctl), no entrainment (NoEnt), original Arakawa Schubert (AS), and AS with simple empirical suppression of convection (ASRH). The fractional entrainment rate of AS and ASRH are constant for each cloud type and are very small near cloud base compared to Ctl, in which half of buoyancy-generated energy is consumed by the entrainment. Ctl well reproduces the spatial and temporal variations, whereas NoEnt and AS, which are very similar to each other, significantly underestimated the variations with the so-called the double ITCZ problem. The enhanced variations in Ctl are due to the larger entrainment that strengthens the coupling of convection and free tropospheric humidity. Time variations are also more realistic in Ctl; mid-height convection moistens mid-troposphere and large precipitation events occur after sufficient moisture is available. In contrast, deep convection is more frequent but with smaller precipitation amount in NoEnt and AS. ASRH shows smaller spatial but excessive temporal variations suggesting that its empirical suppression condition is too simple and a more sophisticated formulation is required for more realistic precipitation variations. This study was supported by the Ministry of Education, Culture, Sports, Science and Technology (GRENE), and by the Ministry of the Environment (2A-1201), Japan.
Sedda, Luigi; Tatem, Andrew J.; Morley, David W.; Atkinson, Peter M.; Wardrop, Nicola A.; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J.
2015-01-01
Background Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. Methods In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. Results This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. Conclusions These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. PMID:25733559
Chen, Yu; Berrocal, Veronica J; Bingham, C Raymond; Song, Peter X K
2014-04-01
Injury resulting from motor vehicle crashes is the leading cause of death among teenagers in the US. Few programs or policies have been found to be effective in reducing the risk of fatal car crashes for young novice drivers. One effective policy that has been widely implemented is Graduated Driver Licensing (GDL). Published articles have mostly reported on the temporal effectiveness of GDL in the US. This article reports on the development of spatial statistical modeling approaches to evaluate and compare the effectiveness of GDL policy across eighty-three counties in the state of Michigan. Data were gathered from several publicly available databases, including the US Fatality Analysis Reporting System (FARS), US Census Bureau, US Bureau of Labor Statistics, and US Department of Agriculture. To account for spatial dependence among crash counts from adjacent counties we invoke spatial random effects, which we provide with a Conditionally AutoRegressive (CAR) prior. Our analysis confirms previous findings that GDL in Michigan is an effective policy that significantly reduces the risk of fatal car crashes among novice teenage drivers. In addition, it indicates that rurality is an important contextual variable associated with spatial differences in GDL effectiveness across the state of Michigan. Finally, our findings provide information that can be used to strengthen GDL policy and its implementation to further enhance teenage-driver safety. Copyright © 2013 Elsevier Ltd. All rights reserved.
How does spatial extent of fMRI datasets affect independent component analysis decomposition?
Aragri, Adriana; Scarabino, Tommaso; Seifritz, Erich; Comani, Silvia; Cirillo, Sossio; Tedeschi, Gioacchino; Esposito, Fabrizio; Di Salle, Francesco
2006-09-01
Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity. (c) 2006 Wiley-Liss, Inc.
Spatiotemporal variations of severe haze episodes in China
NASA Astrophysics Data System (ADS)
Li, J.; Liao, H.
2017-12-01
Rapid economic growth and associated emissions increase in China have led to severe air pollution in recent decades. This study presents the spatial and temporal variations of severe haze episodes in China obtained from monitoring sites and the global chemical transport model GEOS-Chem. Cities in the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions suffered from severe haze, with highest numbers of severe haze episodes in winter and the lowest numbers of episodes in summer. Backward trajectory analysis by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicated the origins of air mass during severe haze episodes for BTH and YRD. The principal component analysis was applied for different regions to classify synoptic conditions associated with the severe haze episodes.
NASA Astrophysics Data System (ADS)
Muehlbauer, J. D.; Doyle, M. W.; Tockner, K.
2011-12-01
This presentation will present the results of a meta-analysis on river-floodplain carbon/energy subsidies. This analysis combines data from the existing body of literature (ca. 100 studies) to determine a "stream signature:" a regression equation that fits the decline in aquatic-derived energy in terrestrial predator food webs as a function of distance from the river. The nature of this decay curve and its implications for river/riparian ecological dynamics will be desrcibed. Variation in this metric due to the influence of stream order, river bank characteristics, and channel geomorphology will be assessed. In addition, the implications of variation in the stream signature for terrestrial aquatic food webs under different geomorphic and anthropogenic scenarios will be discussed.
NASA Astrophysics Data System (ADS)
Dobek, Mateusz; Demczuk, Piotr; Nowosad, Marek
2013-06-01
Due to the diversified land relief and presence of numerous gorge dissections intensively used by man largely for recreational purposes, Lublin is a valuable study area in terms of bioclimatology. The results of modelling of the variation of the bioclimatic conditions of Lublin provide information useful e.g. in the economy and spatial planning. The determined features of the city's bioclimate can be a significant element in the selection of locations for new residential and recreational investments. Knowledge on the spatial variation of biometeorological situations positively and negatively influencing the human organism can also find application in activities concerning the improvement of life quality and health protection, as well as in tourism and recreation. The objective of the paper is to present the spatial variation of biometeorological conditions in Lublin based on the example of specified weather scenarios.
Classification of Farmland Landscape Structure in Multiple Scales
NASA Astrophysics Data System (ADS)
Jiang, P.; Cheng, Q.; Li, M.
2017-12-01
Farmland is one of the basic terrestrial resources that support the development and survival of human beings and thus plays a crucial role in the national security of every country. Pattern change is the intuitively spatial representation of the scale and quality variation of farmland. Through the characteristic development of spatial shapes as well as through changes in system structures, functions and so on, farmland landscape patterns may indicate the landscape health level. Currently, it is still difficult to perform positioning analyses of landscape pattern changes that reflect the landscape structure variations of farmland with an index model. Depending on a number of spatial properties such as locations and adjacency relations, distance decay, fringe effect, and on the model of patch-corridor-matrix that is applied, this study defines a type system of farmland landscape structure on the national, provincial, and city levels. According to such a definition, the classification model of farmland landscape-structure type at the pixel scale is developed and validated based on mathematical-morphology concepts and on spatial-analysis methods. Then, the laws that govern farmland landscape-pattern change in multiple scales are analyzed from the perspectives of spatial heterogeneity, spatio-temporal evolution, and function transformation. The result shows that the classification model of farmland landscape-structure type can reflect farmland landscape-pattern change and its effects on farmland production function. Moreover, farmland landscape change in different scales displayed significant disparity in zonality, both within specific regions and in urban-rural areas.
Sedinger, James S.; Chelgren, Nathan; Lindberg, Mark S.; Obritchkewitch, Tim; Kirk, Morgan T.; Martin, Philip D.; Anderson, Betty A.; Ward, David H.
2002-01-01
We used capture-recapture methods to estimate adult survival rates for adult female Black Brant (Branta bernicla nigricans; hereafter “brant”) from three colonies in Alaska, two on the Yukon-Kuskokwim Delta, and one on Alaska's Arctic coast. Costs of migration and reproductive effort varied among those colonies, enabling us to examine variation in survival in relation to variation in these other variables. We used the Barker model in program MARK to estimate true annual survival for brant from the three colonies. Models allowing for spatial variation in survival were among the most parsimonious models but were indistinguishable from a model with no spatial variation. Point estimates of annual survival were slightly higher for brant from the Arctic (0.90 ± 0.036) than for brant from either Tutakoke River (0.85 ± 0.004) or Kokechik Bay (0.86 ± 0.011). Thus, our survival estimates do not support a hypothesis that the cost of longer migrations or harvest experienced by brant from the Arctic reduced their annual survival relative to brant from the Yukon-Kuskokwim Delta. Spatial variation in survival provides weak support for life-history theory because brant from the region with lower reproductive investment had slightly higher survival.
Probabilistic Common Spatial Patterns for Multichannel EEG Analysis
Chen, Zhe; Gao, Xiaorong; Li, Yuanqing; Brown, Emery N.; Gao, Shangkai
2015-01-01
Common spatial patterns (CSP) is a well-known spatial filtering algorithm for multichannel electroencephalogram (EEG) analysis. In this paper, we cast the CSP algorithm in a probabilistic modeling setting. Specifically, probabilistic CSP (P-CSP) is proposed as a generic EEG spatio-temporal modeling framework that subsumes the CSP and regularized CSP algorithms. The proposed framework enables us to resolve the overfitting issue of CSP in a principled manner. We derive statistical inference algorithms that can alleviate the issue of local optima. In particular, an efficient algorithm based on eigendecomposition is developed for maximum a posteriori (MAP) estimation in the case of isotropic noise. For more general cases, a variational algorithm is developed for group-wise sparse Bayesian learning for the P-CSP model and for automatically determining the model size. The two proposed algorithms are validated on a simulated data set. Their practical efficacy is also demonstrated by successful applications to single-trial classifications of three motor imagery EEG data sets and by the spatio-temporal pattern analysis of one EEG data set recorded in a Stroop color naming task. PMID:26005228
NASA Astrophysics Data System (ADS)
Joevivek, V.; Chandrasekar, N.; Saravanan, S.; Anandakumar, H.; Thanushkodi, K.; Suguna, N.; Jaya, J.
2018-06-01
Investigation of a beach and its wave conditions is highly requisite for understanding the physical processes in a coast. This study composes spatial and temporal correlation between beach and nearshore processes along the extensive sandy beach of Nagapattinam coast, southeast peninsular India. The data collection includes beach profile, wave data, and intertidal sediment samples for 2 years from January 2011 to January 2013. The field data revealed significant variability in beach and wave morphology during the northeast (NE) and southwest (SW) monsoon. However, the beach has been stabilized by the reworking of sediment distribution during the calm period. The changes in grain sorting and longshore sediment transport serve as a clear evidence of the sediment migration that persevered between foreshore and nearshore regions. The Empirical Orthogonal Function (EOF) analysis and Canonical Correlation Analysis (CCA) were utilized to investigate the spatial and temporal linkages between beach and nearshore criterions. The outcome of the multivariate analysis unveiled that the seasonal variations in the wave climate tends to influence the bar-berm sediment transition that is discerned in the coast.
NASA Astrophysics Data System (ADS)
Zhu, Wenjuan; Xiang, Wenhua; Pan, Qiong; Zeng, Yelin; Ouyang, Shuai; Lei, Pifeng; Deng, Xiangwen; Fang, Xi; Peng, Changhui
2016-07-01
Leaf area index (LAI) is an important parameter related to carbon, water, and energy exchange between canopy and atmosphere and is widely applied in process models that simulate production and hydrological cycles in forest ecosystems. However, fine-scale spatial heterogeneity of LAI and its controlling factors have yet to be fully understood in Chinese subtropical forests. We used hemispherical photography to measure LAI values in three subtropical forests (Pinus massoniana-Lithocarpus glaber coniferous and evergreen broadleaved mixed forests, Choerospondias axillaris deciduous broadleaved forests, and L. glaber-Cyclobalanopsis glauca evergreen broadleaved forests) from April 2014 to January 2015. Spatial heterogeneity of LAI and its controlling factors were analysed using geostatistical methods and the generalised additive models (GAMs) respectively. Our results showed that LAI values differed greatly in the three forests and their seasonal variations were consistent with plant phenology. LAI values exhibited strong spatial autocorrelation for the three forests measured in January and for the L. glaber-C. glauca forest in April, July, and October. Obvious patch distribution pattern of LAI values occurred in three forests during the non-growing period and this pattern gradually dwindled in the growing season. Stem number, crown coverage, proportion of evergreen conifer species on basal area basis, proportion of deciduous species on basal area basis, and forest types affected the spatial variations in LAI values in January, while stem number and proportion of deciduous species on basal area basis affected the spatial variations in LAI values in July. Floristic composition, spatial heterogeneity, and seasonal variations should be considered for sampling strategy in indirect LAI measurement and application of LAI to simulate functional processes in subtropical forests.
Analysis of a 7 year tropospheric ozone vertical distribution at the Observatoire de Haute Provence
NASA Technical Reports Server (NTRS)
Beekmann, Matthias; Ancellet, Gerard; Megie, Gerard
1994-01-01
A seven year (1984-90) climatology of tropospheric vertical ozone soundings, performed by electrochemical sondes at the OHP (44 deg N, 6 deg E, 700 m ASL) in Southern France, is presented. Its seasonal variation shows a broad spring/summer maximum in the troposphere. The contribution of photochemical ozone production and transport from the stratosphere to this seasonal variation are studied by a correlative analysis of ozone concentrations and meteorological variables, with emphasis on potential vorticity. This analysis shows the impact of dynamical and photochemical processes on the spatial and temporal ozone variability. In particular, a positive correlation (r = 04.0, significance greater than 99.9 percent) of ozone with potential vorticity is observed in the middle troposphere, reflecting the impact of stratosphere-troposphere exchange on the vertical ozone distribution.
NASA Astrophysics Data System (ADS)
Verma, S.; Gupta, R. D.
2014-11-01
In recent times, Japanese Encephalitis (JE) has emerged as a serious public health problem. In India, JE outbreaks were recently reported in Uttar Pradesh, Gorakhpur. The present study presents an approach to use GIS for analyzing the reported cases of JE in the Gorakhpur district based on spatial analysis to bring out the spatial and temporal dynamics of the JE epidemic. The study investigates spatiotemporal pattern of the occurrence of disease and detection of the JE hotspot. Spatial patterns of the JE disease can provide an understanding of geographical changes. Geospatial distribution of the JE disease outbreak is being investigated since 2005 in this study. The JE incidence data for the years 2005 to 2010 is used. The data is then geo-coded at block level. Spatial analysis is used to evaluate autocorrelation in JE distribution and to test the cases that are clustered or dispersed in space. The Inverse Distance Weighting interpolation technique is used to predict the pattern of JE incidence distribution prevalent across the study area. Moran's I Index (Moran's I) statistics is used to evaluate autocorrelation in spatial distribution. The Getis-Ord Gi*(d) is used to identify the disease areas. The results represent spatial disease patterns from 2005 to 2010, depicting spatially clustered patterns with significant differences between the blocks. It is observed that the blocks on the built up areas reported higher incidences.
Cross, Paul C.; Caillaud, Damien; Heisey, Dennis M.
2013-01-01
Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.
Circulation controls of the spatial structure of maximum daily precipitation over Poland
NASA Astrophysics Data System (ADS)
Stach, Alfred
2015-04-01
Among forecasts made on the basis of global and regional climatic models is one of a high probability of an increase in the frequency and intensity of extreme precipitation events. Learning the regularities underlying the recurrence and spatial extent of extreme precipitation is obviously of great importance, both economic and social. The main goal of the study was to analyse regularities underlying spatial and temporal variations in monthly Maximum Daily Precipitation Totals (MDPTs) observed in Poland over the years 1956-1980. These data are specific because apart from being spatially discontinuous, which is typical of precipitation, they are also non-synchronic. The main aim of the study was accomplished via several detailed goals: • identification and typology of the spatial structure of monthly MDPTs, • determination of the character and probable origin of events generating MDPTs, and • quantitative assessment of the contribution of the particular events to the overall MDPT figures. The analysis of the spatial structure of MDPTs was based on 300 models of spatial structure, one for each of the analysed sets of monthly MDPTs. The models were built on the basis of empirical anisotropic semivariograms of normalised data. In spite of their spatial discontinuity and asynchronicity, the MDPT data from Poland display marked regularities in their spatial pattern that yield readily to mathematical modelling. The MDPT field in Poland is usually the sum of the outcomes of three types of processes operating at various spatial scales: local (<10-20 km), regional (50-150 km), and supra-regional (>200 km). The spatial scales are probably connected with a convective/ orographic, a frontal and a 'planetary waves' genesis of high precipitation. Their contributions are highly variable. Generally predominant, however, are high daily precipitation totals with a spatial extent of 50 to 150 km connected with mesoscale phenomena and the migration of atmospheric fronts (35-38%). The spatial extent of areas of high local-scale precipitation usually varies at random, especially in the warm season. At supra-local scales, structures of repetitive size predominate. Eight types of anisotropic structures of monthly MDPTs were distinguished. To identify them, an analysis was made of semivariance surface similarities. The types differ not only in the level and direction of anisotropy, but also in the number and type of elementary components, which is evidence of genetic differences in precipitation. Their appearance shows a significant seasonal variability, so the most probable supposition was that temporal variations in the MDPT pattern were connected with circulation conditions: the type and direction of inflow of air masses. This hypothesis was validated by testing differences in the frequency of occurrence of Grosswetterlagen circulation situations in the months belonging to the distinguished types of the spatial MDPT pattern.
Soil nutrient-landscape relationships in a lowland tropical rainforest in Panama
Barthold, F.K.; Stallard, R.F.; Elsenbeer, H.
2008-01-01
Soils play a crucial role in biogeochemical cycles as spatially distributed sources and sinks of nutrients. Any spatial patterns depend on soil forming processes, our understanding of which is still limited, especially in regards to tropical rainforests. The objective of our study was to investigate the effects of landscape properties, with an emphasis on the geometry of the land surface, on the spatial heterogeneity of soil chemical properties, and to test the suitability of soil-landscape modeling as an appropriate technique to predict the spatial variability of exchangeable K and Mg in a humid tropical forest in Panama. We used a design-based, stratified sampling scheme to collect soil samples at 108 sites on Barro Colorado Island, Panama. Stratifying variables are lithology, vegetation and topography. Topographic variables were generated from high-resolution digital elevation models with a grid size of 5 m. We took samples from five depths down to 1 m, and analyzed for total and exchangeable K and Mg. We used simple explorative data analysis techniques to elucidate the importance of lithology for soil total and exchangeable K and Mg. Classification and Regression Trees (CART) were adopted to investigate importance of topography, lithology and vegetation for the spatial distribution of exchangeable K and Mg and with the intention to develop models that regionalize the point observations using digital terrain data as explanatory variables. Our results suggest that topography and vegetation do not control the spatial distribution of the selected soil chemical properties at a landscape scale and lithology is important to some degree. Exchangeable K is distributed equally across the study area indicating that other than landscape processes, e.g. biogeochemical processes, are responsible for its spatial distribution. Lithology contributes to the spatial variation of exchangeable Mg but controlling variables could not be detected. The spatial variation of soil total K and Mg is mainly influenced by lithology. ?? 2007 Elsevier B.V. All rights reserved.
This study analyzes variations in the model-projected changes in catchment runoff response after urbanization that stem from variations in the spatial distribution of impervious areas, interevent differences in temporal rainfall structure, and antecedent soil moisture (ASM). In t...
Congdon, Peter
2017-09-07
There is much ongoing research about the effect of the urban environment as compared with individual behaviour on growing obesity levels, including food environment, settlement patterns (e.g., sprawl, walkability, commuting patterns), and activity access. This paper considers obesity variations between US counties, and delineates the main dimensions of geographic variation in obesity between counties: by urban-rural status, by region, by area poverty status, and by majority ethnic group. Available measures of activity access, food environment, and settlement patterns are then assessed in terms of how far they can account for geographic variation. A county level regression analysis uses a Bayesian methodology that controls for spatial correlation in unmeasured area risk factors. It is found that environmental measures do play a significant role in explaining geographic contrasts in obesity.
2017-01-01
There is much ongoing research about the effect of the urban environment as compared with individual behaviour on growing obesity levels, including food environment, settlement patterns (e.g., sprawl, walkability, commuting patterns), and activity access. This paper considers obesity variations between US counties, and delineates the main dimensions of geographic variation in obesity between counties: by urban-rural status, by region, by area poverty status, and by majority ethnic group. Available measures of activity access, food environment, and settlement patterns are then assessed in terms of how far they can account for geographic variation. A county level regression analysis uses a Bayesian methodology that controls for spatial correlation in unmeasured area risk factors. It is found that environmental measures do play a significant role in explaining geographic contrasts in obesity. PMID:28880209
Siordia, Carlos; Saenz, Joseph; Tom, Sarah E.
2014-01-01
Type II diabetes is a growing health problem in the United States. Understanding geographic variation in diabetes prevalence will inform where resources for management and prevention should be allocated. Investigations of the correlates of diabetes prevalence have largely ignored how spatial nonstationarity might play a role in the macro-level distribution of diabetes. This paper introduces the reader to the concept of spatial nonstationarity—variance in statistical relationships as a function of geographical location. Since spatial nonstationarity means different predictors can have varying effects on model outcomes, we make use of a geographically weighed regression to calculate correlates of diabetes as a function of geographic location. By doing so, we demonstrate an exploratory example in which the diabetes-poverty macro-level statistical relationship varies as a function of location. In particular, we provide evidence that when predicting macro-level diabetes prevalence, poverty is not always positively associated with diabetes PMID:25414731
Statistical and Spatial Analysis of Bathymetric Data for the St. Clair River, 1971-2007
Bennion, David
2009-01-01
To address questions concerning ongoing geomorphic processes in the St. Clair River, selected bathymetric datasets spanning 36 years were analyzed. Comparisons of recent high-resolution datasets covering the upper river indicate a highly variable, active environment. Although statistical and spatial comparisons of the datasets show that some changes to the channel size and shape have taken place during the study period, uncertainty associated with various survey methods and interpolation processes limit the statistically certain results. The methods used to spatially compare the datasets are sensitive to small variations in position and depth that are within the range of uncertainty associated with the datasets. Characteristics of the data, such as the density of measured points and the range of values surveyed, can also influence the results of spatial comparison. With due consideration of these limitations, apparently active and ongoing areas of elevation change in the river are mapped and discussed.
Siordia, Carlos; Saenz, Joseph; Tom, Sarah E
2012-01-01
Type II diabetes is a growing health problem in the United States. Understanding geographic variation in diabetes prevalence will inform where resources for management and prevention should be allocated. Investigations of the correlates of diabetes prevalence have largely ignored how spatial nonstationarity might play a role in the macro-level distribution of diabetes. This paper introduces the reader to the concept of spatial nonstationarity-variance in statistical relationships as a function of geographical location. Since spatial nonstationarity means different predictors can have varying effects on model outcomes, we make use of a geographically weighed regression to calculate correlates of diabetes as a function of geographic location. By doing so, we demonstrate an exploratory example in which the diabetes-poverty macro-level statistical relationship varies as a function of location. In particular, we provide evidence that when predicting macro-level diabetes prevalence, poverty is not always positively associated with diabetes.
Spatial and Temporal Temperature trends on Iraq during 1980-2015
NASA Astrophysics Data System (ADS)
Al-Timimi, Yassen K.; Al-Khudhairy, Aws A.
2018-05-01
Monthly Mean surface air temperature at 23 stations in Iraq were analyzed for temporal trends and spatial variation during 1980-2015. Seasonal and annual temperature was analyzed using Mann-Kendall test to detect the significant trend. The results of temporal analysis showed that during winter, spring, summer and Autumn have a positive trend in all the parts of Iraq. A tendency has also been observed towards warmer years, with significantly warmer summer and spring periods and slightly warmer autumn and winter, the highest increase is (3.5)°C in Basrah during the summer. The results of spatial analyze using the ArcGIS showed that the seasonal temperature can be divided into two or three distinct areas with high temperature in the south and decreasing towards north, where the trend of spatial temperature were decreasing from south to the north in all the four seasons.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xiao, Kai; Ma, Ying -Zhong; Simpson, Mary Jane
Charge carrier trapping degrades the performance of organometallic halide perovskite solar cells. To characterize the locations of electronic trap states in a heterogeneous photoactive layer, a spatially resolved approach is essential. Here, we report a comparative study on methylammonium lead tri-iodide perovskite thin films subject to different thermal annealing times using a combined photoluminescence (PL) and femtosecond transient absorption microscopy (TAM) approach to spatially map trap states. This approach coregisters the initially populated electronic excited states with the regions that recombine radiatively. Although the TAM images are relatively homogeneous for both samples, the corresponding PL images are highly structured. Themore » remarkable variation in the PL intensities as compared to transient absorption signal amplitude suggests spatially dependent PL quantum efficiency, indicative of trapping events. Furthermore, detailed analysis enables identification of two trapping regimes: a densely packed trapping region and a sparse trapping area that appear as unique spatial features in scaled PL maps.« less
Gao, Yongnian; Gao, Junfeng; Chen, Jiongfeng
2011-01-01
The study presented in this paper attempts to evaluate the spatial pattern of soil available phosphorus, as well as the relation between soil available phosphorus and environment factors including elevation, slope, precipitation, percentage of cultivated land, percentage of forest land, percentage of construction land and NDVI using statistical methods and GIS spatial analysis techniques. The results showed that the Spline Tension method performed the best in the prediction of soil available phosphorus in the Chaohu Lake watershed. The spatial variation of surface soil available phosphorus was high in Chaohu Lake watershed and the upstream regions around Chaohu Lake, including the west of Chaohu lake (e.g., southwest of Feixi county, east of Shucheng county and north of Lujiang county) and to the north of Chaohu Lake (e.g., south of Hefei city, south of Feidong county, southwest of Juchao district), had the highest soil available phosphorus content. The mean and standard deviation of soil available phosphorus content gradually decreased as the elevation or slope increased. The cultivated land comprised 60.11% of the watershed and of that land 65.63% belonged to the medium to very high SAP level classes, and it played a major role in SAP availability within the watershed and a potential source of phosphorus to Chaohu Lake resulting in eutrophication. Among the land use types, paddy fields have some of the highest maximum values and variation of coefficients. Subwatershed scale soil available phosphorus was significantly affected by elevation, slope, precipitation, percentage of cultivated land and percentage of forest land and was decided by not only these environmental factors but also some other factors such as artificial phosphorus fertilizer application. PMID:21909308
Shen, Qiu; Liang, Liang; Luo, Xiang; Li, Yanjun; Zhang, Lianpeng
2017-08-25
Drought is a complex natural phenomenon that can cause reduced water supplies and can consequently have substantial effects on agriculture and socioeconomic activities. The objective of this study was to gain a better understanding of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China. The Vegetation Condition Index (VCI) dataset calculated from NOAA/AVHRR images from 1982 to 2010 was used to analyse the spatial-temporal variation characteristics of vegetative drought in China. This study also examined the trends in meteorological factors and their influences on drought using monitoring data collected from 686 national ground meteorological stations. The results showed that the VCI appeared to slowly rise in China from 1982 to 2010. From 1982 to 1999, the VCI rose slowly. Then, around 2000, the VCI exhibited a severe fluctuation before it entered into a relatively stable stage. Drought frequencies in China were higher, showing a spatial distribution feature of "higher in the north and lower in the south". Based on the different levels of drought, the frequencies of mild and moderate drought in four geographical areas were higher, and the frequency of severe drought was higher only in ecologically vulnerable areas, such as the Tarim Basin and the Qaidam Basin. Drought was mainly influenced by meteorological factors, which differed regionally. In the northern region, the main influential factor was sunshine duration, while the other factors showed minimal effects. In the southern region and Tibetan Plateau, the main influential factors were sunshine duration and temperature. In the northwestern region, the main influential factors were wind velocity and station atmospheric pressure.
Mark C. Gabriel; Randy Kolka; Trent Wickman; Ed Nater; Laurel. Woodruff
2009-01-01
The primary objective of this research is to investigate relationships between mercury in upland soil, lake water and fish tissue and explore the cause for the observed spatial variation of THg in age one yellow perch (Perca flavescens) for ten lakes within the Superior National Forest. Spatial relationships between yellow perch THg tissue...
NASA Technical Reports Server (NTRS)
Blount, Grady; Greeley, Ronald; Christensen, Phillip R.; Smith, Milton O.; Adams, John B.
1990-01-01
Mesoscale mapping of spatial variations in sand composition of the Gran Desierto (Sonora, Mexico) was carried out on multispectral Landsat TM images of this region, making it possible to examine the dynamic development of sand sheets and dunes. Compositions determined from remote imagery were found to agree well with samples from selected areas. The sand populations delineated were used to describe the sediment source areas, transport paths, and deposition sites. The image analysis revealed important compositional variations aver large areas that were not readily apparent in the field data.
NASA Astrophysics Data System (ADS)
Longuevergne, Laurent; Scanlon, Bridget R.; Wilson, Clark R.
2010-11-01
The Gravity Recovery and Climate Experiment (GRACE) satellites provide observations of water storage variation at regional scales. However, when focusing on a region of interest, limited spatial resolution and noise contamination can cause estimation bias and spatial leakage, problems that are exacerbated as the region of interest approaches the GRACE resolution limit of a few hundred km. Reliable estimates of water storage variations in small basins require compromises between competing needs for noise suppression and spatial resolution. The objective of this study was to quantitatively investigate processing methods and their impacts on bias, leakage, GRACE noise reduction, and estimated total error, allowing solution of the trade-offs. Among the methods tested is a recently developed concentration algorithm called spatiospectral localization, which optimizes the basin shape description, taking into account limited spatial resolution. This method is particularly suited to retrieval of basin-scale water storage variations and is effective for small basins. To increase confidence in derived methods, water storage variations were calculated for both CSR (Center for Space Research) and GRGS (Groupe de Recherche de Géodésie Spatiale) GRACE products, which employ different processing strategies. The processing techniques were tested on the intensively monitored High Plains Aquifer (450,000 km2 area), where application of the appropriate optimal processing method allowed retrieval of water storage variations over a portion of the aquifer as small as ˜200,000 km2.
Cyclic precipitation variation on the western Loess Plateau of China during the past four centuries
Tan, Liangcheng; An, Zhisheng; Huh, Chih-An; Cai, Yanjun; Shen, Chuan-Chou; Shiau, Liang-Jian; Yan, Libin; Cheng, Hai; Edwards, R. Lawrence
2014-01-01
Precipitation variation on the Loess Plateau (LP) of China is not only important for rain-fed agriculture in this environmentally sensitive region, but also critical for the water and life securities over the whole Yellow River basin. Here we reconstruct high resolution precipitation variation on the western LP during the past 370 years by using two replicated, annually-laminated stalagmites. Spatial analysis suggests that the reconstruction can be also representative for the whole LP region. The precipitation variations show a significant quasi-50 year periodicity during the last 370 years, and have an important role in determining the runoff of the middle Yellow River. The main factor controlling the decadal scale variations and long-term trend in precipitation over this region is southerly water vapour transport associated with the Asian summer monsoon. The Pacific Decadal Oscillation is also an important influence on precipitation variation in this region, as it can affect the East Asian summer monsoon and the West Pacific Subtropical High. PMID:25223372
Regional variation in diets of breeding Red-shouldered hawks
Strobel, Bradley N.; Boal, Clint W.
2010-01-01
We collected data on breeding season diet composition of Red-shouldered Hawks (Buteo lineatus) in south Texas and compared these data, and those reported from studies elsewhere to examine large scale spatial variation in prey use in eastern North America. Red-shouldered Hawk diets aligned into two significantly different groups, which appear to correlate with latitude. The diets of Red-shouldered Hawks in group 1, which are of more northern latitudes, had significantly more mammalian prey and significantly less amphibian prey than those in group 2, which are at more southerly latitudes. Our meta-analysis demonstrated the dietary flexibility of Red-shouldered Hawks, which likely accounts for their broad distribution by exploiting regional variations in taxon-specific prey availability.