Spatio-temporal patterns of key exploited marine species in the Northwestern Mediterranean Sea.

PubMed

Morfin, Marie; Fromentin, Jean-Marc; Jadaud, Angélique; Bez, Nicolas

2012-01-01

This study analyzes the temporal variability/stability of the spatial distributions of key exploited species in the Gulf of Lions (Northwestern Mediterranean Sea). To do so, we analyzed data from the MEDITS bottom-trawl scientific surveys from 1994 to 2010 at 66 fixed stations and selected 12 key exploited species. We proposed a geostatistical approach to handle zero-inflated and non-stationary distributions and to test for the temporal stability of the spatial structures. Empirical Orthogonal Functions and other descriptors were then applied to investigate the temporal persistence and the characteristics of the spatial patterns. The spatial structure of the distribution (i.e. the pattern of spatial autocorrelation) of the 12 key species studied remained highly stable over the time period sampled. The spatial distributions of all species obtained through kriging also appeared to be stable over time, while each species displayed a specific spatial distribution. Furthermore, adults were generally more densely concentrated than juveniles and occupied areas included in the distribution of juveniles. Despite the strong persistence of spatial distributions, we also observed that the area occupied by each species was correlated to its abundance: the more abundant the species, the larger the occupation area. Such a result tends to support MacCall's basin theory, according to which density-dependence responses would drive the expansion of those 12 key species in the Gulf of Lions. Further analyses showed that these species never saturated their habitats, suggesting that they are below their carrying capacity; an assumption in agreement with the overexploitation of several of these species. Finally, the stability of their spatial distributions over time and their potential ability to diffuse outside their main habitats give support to Marine Protected Areas as a potential pertinent management tool.

Spatial distribution, seasonality and trap preference of stable fly, Stomoxys calcitrans L. (Diptera: Muscidae), adults on a 12-hectare zoological park

USDA-ARS?s Scientific Manuscript database

Although this study was originally designed to compare the efficacy of 2 different stable fly traps within 10 sites at a 12-ha zoological park, seasonal and spatial population distribution data were simultaneously collected. The two traps included an Alsynite fiberglass cylindrical trap (AFT) and a...

Submillimeter-scale heterogeneity of labile phosphorus in sediments characterized by diffusive gradients in thin films and spatial analysis.

PubMed

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.

Alcohol beverage control, privatization and the geographic distribution of alcohol outlets

PubMed Central

2012-01-01

Background With Pennsylvania currently considering a move away from an Alcohol Beverage Control state to a privatized alcohol distribution system, this study uses a spatial analytical approach to examine potential impacts of privatization on the number and spatial distribution of alcohol outlets in the city of Philadelphia over a long time horizon. Methods A suite of geospatial data were acquired for Philadelphia, including 1,964 alcohol outlet locations, 569,928 land parcels, and school, church, hospital, park and playground locations. These data were used as inputs for exploratory spatial analysis to estimate the expected number of outlets that would eventually operate in Philadelphia. Constraints included proximity restrictions (based on current ordinances regulating outlet distribution) of at least 200 feet between alcohol outlets and at least 300 feet between outlets and schools, churches, hospitals, parks and playgrounds. Results Findings suggest that current state policies on alcohol outlet distributions in Philadelphia are loosely enforced, with many areas exhibiting extremely high spatial densities of outlets that violate existing proximity restrictions. The spatial model indicates that an additional 1,115 outlets could open in Philadelphia if privatization was to occur and current proximity ordinances were maintained. Conclusions The study reveals that spatial analytical approaches can function as an excellent tool for contingency-based “what-if” analysis, providing an objective snapshot of potential policy outcomes prior to implementation. In this case, the likely outcome is a tremendous increase in alcohol outlets in Philadelphia, with concomitant negative health, crime and quality of life outcomes that accompany such an increase. PMID:23170899

Proton Energy Optimization and Spatial Distribution Analysis from a Thickness Study Using Liquid Crystal Targets

NASA Astrophysics Data System (ADS)

Willis, Christopher; Poole, Patrick; Schumacher, Douglas; Freeman, Richard; van Woerkom, Linn

2016-10-01

Laser-accelerated ions from thin targets have been widely studied for applications including secondary radiation sources and cancer therapy, with recent studies trending towards thinner targets which can provide improved ion energies and yields. Here we discuss results from an experiment on the Scarlet laser at OSU using variable thickness liquid crystal targets. On this experiment, the spatial and spectral distributions of accelerated ions were measured along target normal and laser axes at varying thicknesses from 150nm to 2000nm at a laser intensity of 1 ×1020W /cm2 . Maximum ion energy was observed for targets in the 600 - 800nm thickness range, with proton energies reaching 24MeV . The ions were further characterized using radiochromic film, revealing an unusual spatial distribution on many laser shots. Here, the peak ion yield falls in an annular ring surrounding the target normal, with an increasing divergence angle as a function of ion energy. Details of these spatial and spectral ion distributions will be presented, including spectral deconvolution of the RCF data, revealing additional trends in the accelerated ion distributions. Supported by the DARPA PULSE program through a Grant from AMRDEC, and by the NNSA under contract DE-NA0001976.

Climate change, fisheries management and fishing aptitude affecting spatial and temporal distributions of the Barents Sea cod fishery.

PubMed

Eide, Arne

2017-12-01

Climate change is expected to influence spatial and temporal distributions of fish stocks. The aim of this paper is to compare climate change impact on a fishery with other factors impacting the performance of fishing fleets. The fishery in question is the Northeast Arctic cod fishery, a well-documented fishery where data on spatial and temporal distributions are available. A cellular automata model is developed for the purpose of mimicking possible distributional patterns and different management alternatives are studied under varying assumptions on the fleets' fishing aptitude. Fisheries management and fishing aptitude, also including technological development and local knowledge, turn out to have the greatest impact on the spatial distribution of the fishing effort, when comparing the IPCC's SRES A1B scenario with repeated sequences of the current environmental situation over a period of 45 years. In both cases, the highest profits in the simulation period of 45 years are obtained at low exploitation levels and moderate fishing aptitude.

Spatial Light Modulators as Optical Crossbar Switches

NASA Technical Reports Server (NTRS)

Juday, Richard

2003-01-01

A proposed method of implementing cross connections in an optical communication network is based on the use of a spatial light modulator (SLM) to form controlled diffraction patterns that connect inputs (light sources) and outputs (light sinks). Sources would typically include optical fibers and/or light-emitting diodes; sinks would typically include optical fibers and/or photodetectors. The sources and/or sinks could be distributed in two dimensions; that is, on planes. Alternatively or in addition, sources and/or sinks could be distributed in three dimensions -- for example, on curved surfaces or in more complex (including random) three-dimensional patterns.

Spatial and vertical distribution of soil physico-chemical properties and the content of heavy metals in the pedosphere in Poland

Treesearch

Marek Degorski

1998-01-01

The lithological and petrographical characteristics of soil pedogenesis was determined, and the spatial and vertical distribution of some soil physico-chemical properties (including heavy metal content) were studied along two transects in Poland. The genetic horizon for 22 soil profiles were described for particle size and petrographic composition, quartz grain...

40 CFR 194.42 - Monitoring.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., including porosity, permeability, and degree of compaction and reconsolidation; (2) Stresses and extent of..., composition, and spatial distribution; (6) Gas quantity and composition; and (7) Temperature distribution. (b...

40 CFR 194.42 - Monitoring.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., including porosity, permeability, and degree of compaction and reconsolidation; (2) Stresses and extent of..., composition, and spatial distribution; (6) Gas quantity and composition; and (7) Temperature distribution. (b...

40 CFR 194.42 - Monitoring.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., including porosity, permeability, and degree of compaction and reconsolidation; (2) Stresses and extent of..., composition, and spatial distribution; (6) Gas quantity and composition; and (7) Temperature distribution. (b...

40 CFR 194.42 - Monitoring.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., including porosity, permeability, and degree of compaction and reconsolidation; (2) Stresses and extent of..., composition, and spatial distribution; (6) Gas quantity and composition; and (7) Temperature distribution. (b...

40 CFR 194.42 - Monitoring.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., including porosity, permeability, and degree of compaction and reconsolidation; (2) Stresses and extent of..., composition, and spatial distribution; (6) Gas quantity and composition; and (7) Temperature distribution. (b...

The Non-Gaussian Nature of Prostate Motion Based on Real-Time Intrafraction Tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Yuting; Liu, Tian; Yang, Wells

2013-10-01

Purpose: The objective of this work is to test the validity of the Gaussian approximation for prostate motion through characterization of its spatial distribution. Methods and Materials: Real-time intrafraction prostate motion was observed using Calypso 4-dimensional (4D) nonradioactive electromagnetic tracking system. We report the results from a total of 1024 fractions from 31 prostate cancer patients. First, the correlation of prostate motion in right/left (RL), anteroposterior (AP), and superoinferior (SI) direction were determined using Pearson's correlation of coefficient. Then the spatial distribution of prostate motion was analyzed for individual fraction, individual patient including all fractions, and all patients including allmore » fractions. The displacement in RL, AP, SI, oblique, or total direction is fitted into a Gaussian distribution, and a Lilliefors test was used to evaluate the validity of the hypothesis that the displacement is normally distributed. Results: There is high correlation in AP/SI direction (61% of fractions with medium or strong correlation). This is consistent with the longitudinal oblique motion of the prostate, and likely the effect from respiration on an organ confined within the genitourinary diaphragm with the rectum sitting posteriorly and bladder sitting superiorly. In all directions, the non-Gaussian distribution is more common for individual fraction, individual patient including all fractions, and all patients including all fractions. The spatial distribution of prostate motion shows an elongated shape in oblique direction, indicating a higher range of motion in the AP and SI directions. Conclusions: Our results showed that the prostate motion is highly correlated in AP and SI direction, indicating an oblique motion preference. In addition, the spatial distribution of prostate motion is elongated in an oblique direction, indicating that the organ motion dosimetric modeling using Gaussian kernel may need to be modified to account for the particular organ motion character of prostate.« less

The non-Gaussian nature of prostate motion based on real-time intrafraction tracking.

PubMed

Lin, Yuting; Liu, Tian; Yang, Wells; Yang, Xiaofeng; Khan, Mohammad K

2013-10-01

The objective of this work is to test the validity of the Gaussian approximation for prostate motion through characterization of its spatial distribution. Real-time intrafraction prostate motion was observed using Calypso 4-dimensional (4D) nonradioactive electromagnetic tracking system. We report the results from a total of 1024 fractions from 31 prostate cancer patients. First, the correlation of prostate motion in right/left (RL), anteroposterior (AP), and superoinferior (SI) direction were determined using Pearson's correlation of coefficient. Then the spatial distribution of prostate motion was analyzed for individual fraction, individual patient including all fractions, and all patients including all fractions. The displacement in RL, AP, SI, oblique, or total direction is fitted into a Gaussian distribution, and a Lilliefors test was used to evaluate the validity of the hypothesis that the displacement is normally distributed. There is high correlation in AP/SI direction (61% of fractions with medium or strong correlation). This is consistent with the longitudinal oblique motion of the prostate, and likely the effect from respiration on an organ confined within the genitourinary diaphragm with the rectum sitting posteriorly and bladder sitting superiorly. In all directions, the non-Gaussian distribution is more common for individual fraction, individual patient including all fractions, and all patients including all fractions. The spatial distribution of prostate motion shows an elongated shape in oblique direction, indicating a higher range of motion in the AP and SI directions. Our results showed that the prostate motion is highly correlated in AP and SI direction, indicating an oblique motion preference. In addition, the spatial distribution of prostate motion is elongated in an oblique direction, indicating that the organ motion dosimetric modeling using Gaussian kernel may need to be modified to account for the particular organ motion character of prostate. Copyright © 2013 Elsevier Inc. All rights reserved.

Spatial Inference for Distributed Remote Sensing Data

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Katzfuss, M.; Nguyen, H.

2014-12-01

Remote sensing data are inherently spatial, and a substantial portion of their value for scientific analyses derives from the information they can provide about spatially dependent processes. Geophysical variables such as atmopsheric temperature, cloud properties, humidity, aerosols and carbon dioxide all exhibit spatial patterns, and satellite observations can help us learn about the physical mechanisms driving them. However, remote sensing observations are often noisy and incomplete, so inferring properties of true geophysical fields from them requires some care. These data can also be massive, which is both a blessing and a curse: using more data drives uncertainties down, but also drives costs up, particularly when data are stored on different computers or in different physical locations. In this talk I will discuss a methodology for spatial inference on massive, distributed data sets that does not require moving large volumes of data. The idea is based on a combination of ideas including modeling spatial covariance structures with low-rank covariance matrices, and distributed estimation in sensor or wireless networks.

Spatial and temporal statistical analysis of bycatch data: Patterns of sea turtle bycatch in the North Atlantic

USGS Publications Warehouse

Gardner, B.; Sullivan, P.J.; Morreale, S.J.; Epperly, S.P.

2008-01-01

Loggerhead (Caretta caretta) and leatherback (Dermochelys coriacea) sea turtle distributions and movements in offshore waters of the western North Atlantic are not well understood despite continued efforts to monitor, survey, and observe them. Loggerhead and leatherback sea turtles are listed as endangered by the World Conservation Union, and thus anthropogenic mortality of these species, including fishing, is of elevated interest. This study quantifies spatial and temporal patterns of sea turtle bycatch distributions to identify potential processes influencing their locations. A Ripley's K function analysis was employed on the NOAA Fisheries Atlantic Pelagic Longline Observer Program data to determine spatial, temporal, and spatio-temporal patterns of sea turtle bycatch distributions within the pattern of the pelagic fishery distribution. Results indicate that loggerhead and leatherback sea turtle catch distributions change seasonally, with patterns of spatial clustering appearing from July through October. The results from the space-time analysis indicate that sea turtle catch distributions are related on a relatively fine scale (30-200 km and 1-5 days). The use of spatial and temporal point pattern analysis, particularly K function analysis, is a novel way to examine bycatch data and can be used to inform fishing practices such that fishing could still occur while minimizing sea turtle bycatch. ?? 2008 NRC.

Relationship Study on Land Use Spatial Distribution Structure and Energy-Related Carbon Emission Intensity in Different Land Use Types of Guangdong, China, 1996–2008

PubMed Central

Huang, Yi; Yang, Lei

2013-01-01

This study attempts to discuss the relationship between land use spatial distribution structure and energy-related carbon emission intensity in Guangdong during 1996–2008. We quantized the spatial distribution structure of five land use types including agricultural land, industrial land, residential and commercial land, traffic land, and other land through applying spatial Lorenz curve and Gini coefficient. Then the corresponding energy-related carbon emissions in each type of land were calculated in the study period. Through building the reasonable regression models, we found that the concentration degree of industrial land is negatively correlated with carbon emission intensity in the long term, whereas the concentration degree is positively correlated with carbon emission intensity in agricultural land, residential and commercial land, traffic land, and other land. The results also indicate that land use spatial distribution structure affects carbon emission intensity more intensively than energy efficiency and production efficiency do. These conclusions provide valuable reference to develop comprehensive policies for energy conservation and carbon emission reduction in a new perspective. PMID:23476128

Relationship study on land use spatial distribution structure and energy-related carbon emission intensity in different land use types of Guangdong, China, 1996-2008.

PubMed

Huang, Yi; Xia, Bin; Yang, Lei

2013-01-01

This study attempts to discuss the relationship between land use spatial distribution structure and energy-related carbon emission intensity in Guangdong during 1996-2008. We quantized the spatial distribution structure of five land use types including agricultural land, industrial land, residential and commercial land, traffic land, and other land through applying spatial Lorenz curve and Gini coefficient. Then the corresponding energy-related carbon emissions in each type of land were calculated in the study period. Through building the reasonable regression models, we found that the concentration degree of industrial land is negatively correlated with carbon emission intensity in the long term, whereas the concentration degree is positively correlated with carbon emission intensity in agricultural land, residential and commercial land, traffic land, and other land. The results also indicate that land use spatial distribution structure affects carbon emission intensity more intensively than energy efficiency and production efficiency do. These conclusions provide valuable reference to develop comprehensive policies for energy conservation and carbon emission reduction in a new perspective.

Remote-sensing based approach to forecast habitat quality under climate change scenarios.

PubMed

Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.

Remote-sensing based approach to forecast habitat quality under climate change scenarios

PubMed Central

Requena-Mullor, Juan M.; López, Enrique; Castro, Antonio J.; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios. PMID:28257501

Spatial Dependence and Heterogeneity in Bayesian Factor Analysis: A Cross-National Investigation of Schwartz Values

ERIC Educational Resources Information Center

Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

2012-01-01

In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the model parameters and demonstrates the consequences…

Research on reconstructing spatial distribution of historical cropland over 300 years in traditional cultivated regions of China

NASA Astrophysics Data System (ADS)

Yang, Xuhong; Jin, Xiaobin; Guo, Beibei; Long, Ying; Zhou, Yinkang

2015-05-01

Constructing a spatially explicit time series of historical cultivated land is of upmost importance for climatic and ecological studies that make use of Land Use and Cover Change (LUCC) data. Some scholars have made efforts to simulate and reconstruct the quantitative information on historical land use at the global or regional level based on "top-down" decision-making behaviors to match overall cropland area to land parcels using land arability and universal parameters. Considering the concentrated distribution of cultivated land and various factors influencing cropland distribution, including environmental and human factors, this study developed a "bottom-up" model of historical cropland based on constrained Cellular Automaton (CA). Our model takes a historical cropland area as an external variable and the cropland distribution in 1980 as the maximum potential scope of historical cropland. We selected elevation, slope, water availability, average annual precipitation, and distance to the nearest rural settlement as the main influencing factors of land use suitability. Then, an available labor force index is used as a proxy for the amount of cropland to inspect and calibrate these spatial patterns. This paper applies the model to a traditional cultivated region in China and reconstructs its spatial distribution of cropland during 6 periods. The results are shown as follows: (1) a constrained CA is well suited for simulating and reconstructing the spatial distribution of cropland in China's traditional cultivated region. (2) Taking the different factors affecting spatial pattern of cropland into consideration, the partitioning of the research area effectively reflected the spatial differences in cropland evolution rules and rates. (3) Compared with "HYDE datasets", this research has formed higher-resolution Boolean spatial distribution datasets of historical cropland with a more definitive concept of spatial pattern in terms of fractional format. We conclude that our reconstruction is closer to the actual change pattern of the traditional cultivated region in China.

A Spatial Analysis and Game Theoretical Approach Over the Disputed Islands in the Aegean Sea

DTIC Science & Technology

2016-06-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release; distribution is unlimited A SPATIAL ANALYSIS ...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE A SPATIAL ANALYSIS AND GAME THEORETICAL APPROACH OVER THE DISPUTED ISLANDS...including perimeter, area, population, distance to Greece, distance to Turkey, and territorial water area. After applying spatial analysis to two

Proceedings of the Workshop on Applications of Distributed System Theory to the Control of Large Space Structures

NASA Technical Reports Server (NTRS)

Rodriguez, G. (Editor)

1983-01-01

Two general themes in the control of large space structures are addressed: control theory for distributed parameter systems and distributed control for systems requiring spatially-distributed multipoint sensing and actuation. Topics include modeling and control, stabilization, and estimation and identification.

Relevance of anisotropy and spatial variability of gas diffusivity for soil-gas transport

NASA Astrophysics Data System (ADS)

Schack-Kirchner, Helmer; Kühne, Anke; Lang, Friederike

2017-04-01

Models of soil gas transport generally do not consider neither direction dependence of gas diffusivity, nor its small-scale variability. However, in a recent study, we could provide evidence for anisotropy favouring vertical gas diffusion in natural soils. We hypothesize that gas transport models based on gas diffusion data measured with soil rings are strongly influenced by both, anisotropy and spatial variability and the use of averaged diffusivities could be misleading. To test this we used a 2-dimensional model of soil gas transport to under compacted wheel tracks to model the soil-air oxygen distribution in the soil. The model was parametrized with data obtained from soil-ring measurements with its central tendency and variability. The model includes vertical parameter variability as well as variation perpendicular to the elongated wheel track. Different parametrization types have been tested: [i)]Averaged values for wheel track and undisturbed. em [ii)]Random distribution of soil cells with normally distributed variability within the strata. em [iii)]Random distributed soil cells with uniformly distributed variability within the strata. All three types of small-scale variability has been tested for [j)] isotropic gas diffusivity and em [jj)]reduced horizontal gas diffusivity (constant factor), yielding in total six models. As expected the different parametrizations had an important influence to the aeration state under wheel tracks with the strongest oxygen depletion in case of uniformly distributed variability and anisotropy towards higher vertical diffusivity. The simple simulation approach clearly showed the relevance of anisotropy and spatial variability in case of identical central tendency measures of gas diffusivity. However, until now it did not consider spatial dependency of variability, that could even aggravate effects. To consider anisotropy and spatial variability in gas transport models we recommend a) to measure soil-gas transport parameters spatially explicit including different directions and b) to use random-field stochastic models to assess the possible effects for gas-exchange models.

Habitat influences distribution of chronic wasting disease in white-tailed deer

USGS Publications Warehouse

Evans, Tyler S.; Kirchgessner, Megan S.; Eyler, B.; Ryan, Christopher W.; Walter, W. David

2015-01-01

Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy that was first detected in 1967 in a captive research facility in Colorado. In the northeastern United States, CWD was first confirmed in white-tailed deer (Odocoileus virginianus) in 2005. Because CWD is a new and emerging disease with a spatial distribution that had yet to be assessed in the Northeast, we examined demographic, environmental, and spatial effects to determine how each related to this spatial distribution. The objectives of our study were to identify environmental and spatial effects that best described the spatial distribution of CWD in free-ranging white-tailed deer and identify areas that support deer that are at risk for CWD infection in the Northeast. We used Bayesian hierarchical modeling that incorporated demographic covariates, such as sex and age, along with environmental covariates, which included elevation, slope, riparian corridor, percent clay, and 3 landscapes (i.e., developed, forested, open). The model with the most support contained landscape covariates and spatial effects that represented clustering of CWD in adjacent grid cells. Forested landscapes had the strongest relationship with the distribution of CWD, with increased risk of CWD occurring in areas that had lesser amounts of forest. Our results will assist resource managers in understanding the spatial distribution of CWD within the study area, and in surrounding areas where CWD has yet to be found. Efficiency of disease surveillance and containment efforts can be improved by allocating resources used for surveillance in areas with deer populations that are at greatest risk for infection.

Location of Road Emergency Stations in Fars Province, Using Spatial Multi-Criteria Decision Making.

PubMed

Goli, Ali; Ansarizade, Najmeh; Barati, Omid; Kavosi, Zahra

2015-01-01

To locate the road emergency stations in Fars province based on using spatial multi-criteria decision making (Delphi method). In this study, the criteria affecting the location of road emergency stations have been identified through Delphi method and their importance was determined using Analytical Hierarchical Process (AHP). With regard to the importance of the criteria and by using Geographical Information System (GIS), the appropriateness of the existing stations with the criteria and the way of their distribution has been explored, and the appropriate arenas for creating new emergency stations were determined. In order to investigate the spatial distribution pattern of the stations, Moran's Index was used. The accidents (0.318), placement position (0.235), time (0.198), roads (0.160), and population (0.079) were introduced as the main criteria in location road emergency stations. The findings showed that the distribution of the existing stations was clustering (Moran's I=0.3). Three priorities were introduced for establishing new stations. Some arenas including Abade, north of Eghlid and Khoram bid, and small parts of Shiraz, Farashband, Bavanat, and Kazeroon were suggested as the first priority. GIS is a useful and applicable tool in investigating spatial distribution and geographical accessibility to the setting that provide health care, including emergency stations.

Generating Within-Plant Spatial Distributions of an Insect Herbivore Based on Aggregation Patterns and Per-Node Infestation Probabilities.

PubMed

Rincon, Diego F; Hoy, Casey W; Cañas, Luis A

2015-04-01

Most predator-prey models extrapolate functional responses from small-scale experiments assuming spatially uniform within-plant predator-prey interactions. However, some predators focus their search in certain plant regions, and herbivores tend to select leaves to balance their nutrient uptake and exposure to plant defenses. Individual-based models that account for heterogeneous within-plant predator-prey interactions can be used to scale-up functional responses, but they would require the generation of explicit prey spatial distributions within-plant architecture models. The silverleaf whitefly, Bemisia tabaci biotype B (Gennadius) (Hemiptera: Aleyrodidae), is a significant pest of tomato crops worldwide that exhibits highly aggregated populations at several spatial scales, including within the plant. As part of an analytical framework to understand predator-silverleaf whitefly interactions, the objective of this research was to develop an algorithm to generate explicit spatial counts of silverleaf whitefly nymphs within tomato plants. The algorithm requires the plant size and the number of silverleaf whitefly individuals to distribute as inputs, and includes models that describe infestation probabilities per leaf nodal position and the aggregation pattern of the silverleaf whitefly within tomato plants and leaves. The output is a simulated number of silverleaf whitefly individuals for each leaf and leaflet on one or more plants. Parameter estimation was performed using nymph counts per leaflet censused from 30 artificially infested tomato plants. Validation revealed a substantial agreement between algorithm outputs and independent data that included the distribution of counts of both eggs and nymphs. This algorithm can be used in simulation models that explore the effect of local heterogeneity on whitefly-predator dynamics. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Denitrification potential of riparian soils in relation to multiscale spatial environmental factors: a case study of a typical watershed, China.

PubMed

Wei, Jianbing; Feng, Hao; Cheng, Quanguo; Gao, Shiqian; Liu, Haiyan

2017-02-01

The objective of this study was to test the hypothesis that environmental regulators of riparian zone soil denitrification potential differ according to spatial scale within a watershed; consequently, a second objective was to provide spatial strategies for conserving and restoring the purification function of runoff in riparian ecosystems. The results show that soil denitrification in riparian zones was more heterogeneous at the profile scale than at the cross-section and landscape scales. At the profile scale, biogeochemical factors (including soil total organic carbon, total nitrogen, and nitrate-nitrogen) were the major direct regulators of the spatial distribution of soil denitrification enzyme activity (DEA). At the cross-section scale, factors included distance from river bank and vegetation density, while landscape-scale factors, including topographic index, elevation, and land use types, indirectly regulated the spatial distribution of DEA. At the profile scale, soil DEA was greatest in the upper soil layers. At the cross-section scale, maximum soil DEA occurred in the mid-part of the riparian zone. At the landscape scale, soil DEA showed an increasing trend towards downstream sites, except for those in urbanized areas.

Hyperspectral imaging spectro radiometer improves radiometric accuracy

NASA Astrophysics Data System (ADS)

Prel, Florent; Moreau, Louis; Bouchard, Robert; Bullis, Ritchie D.; Roy, Claude; Vallières, Christian; Levesque, Luc

2013-06-01

Reliable and accurate infrared characterization is necessary to measure the specific spectral signatures of aircrafts and associated infrared counter-measures protections (i.e. flares). Infrared characterization is essential to improve counter measures efficiency, improve friend-foe identification and reduce the risk of friendly fire. Typical infrared characterization measurement setups include a variety of panchromatic cameras and spectroradiometers. Each instrument brings essential information; cameras measure the spatial distribution of targets and spectroradiometers provide the spectral distribution of the emitted energy. However, the combination of separate instruments brings out possible radiometric errors and uncertainties that can be reduced with Hyperspectral imagers. These instruments combine both spectral and spatial information into the same data. These instruments measure both the spectral and spatial distribution of the energy at the same time ensuring the temporal and spatial cohesion of collected information. This paper presents a quantitative analysis of the main contributors of radiometric uncertainties and shows how a hyperspectral imager can reduce these uncertainties.

Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; He, Y.; Davis, K. J.

2017-12-01

Most current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve topographically driven land surface heterogeneity (e.g., lateral water flow, soil moisture, soil temperature, solar radiation) or the spatial pattern of nutrient availability. A spatially distributed forest biogeochemical model with nitrogen transport, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM, and adding an advection dominated nitrogen transport module. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model, and is augmented by adding a topographic solar radiation module. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while nitrogen is transported among model grids via surface and subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation, while BBGC provides Flux-PIHM with spatially-distributed leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills Critical Zone Observatory. The model-predicted aboveground vegetation carbon and soil carbon distributions generally agree with the macro patterns observed within the watershed. The importance of abiotic variables (including soil moisture, soil temperature, solar radiation, and soil mineral nitrogen) in predicting aboveground carbon distribution is calculated using a random forest. The result suggests that the spatial pattern of aboveground carbon is controlled by the distribution of soil mineral nitrogen. A Flux-PIHM-BGC simulation without the nitrogen transport module is also executed. The model without nitrogen transport fails in predicting the spatial patterns of vegetation carbon, which indicates the importance of having a nitrogen transport module in spatially distributed ecohydrologic modeling.

Regional Management Units for Marine Turtles: A Novel Framework for Prioritizing Conservation and Research across Multiple Scales

PubMed Central

Wallace, Bryan P.; DiMatteo, Andrew D.; Hurley, Brendan J.; Finkbeiner, Elena M.; Bolten, Alan B.; Chaloupka, Milani Y.; Hutchinson, Brian J.; Abreu-Grobois, F. Alberto; Amorocho, Diego; Bjorndal, Karen A.; Bourjea, Jerome; Bowen, Brian W.; Dueñas, Raquel Briseño; Casale, Paolo; Choudhury, B. C.; Costa, Alice; Dutton, Peter H.; Fallabrino, Alejandro; Girard, Alexandre; Girondot, Marc; Godfrey, Matthew H.; Hamann, Mark; López-Mendilaharsu, Milagros; Marcovaldi, Maria Angela; Mortimer, Jeanne A.; Musick, John A.; Nel, Ronel; Pilcher, Nicolas J.; Seminoff, Jeffrey A.; Troëng, Sebastian; Witherington, Blair; Mast, Roderic B.

2010-01-01

Background Resolving threats to widely distributed marine megafauna requires definition of the geographic distributions of both the threats as well as the population unit(s) of interest. In turn, because individual threats can operate on varying spatial scales, their impacts can affect different segments of a population of the same species. Therefore, integration of multiple tools and techniques — including site-based monitoring, genetic analyses, mark-recapture studies and telemetry — can facilitate robust definitions of population segments at multiple biological and spatial scales to address different management and research challenges. Methodology/Principal Findings To address these issues for marine turtles, we collated all available studies on marine turtle biogeography, including nesting sites, population abundances and trends, population genetics, and satellite telemetry. We georeferenced this information to generate separate layers for nesting sites, genetic stocks, and core distributions of population segments of all marine turtle species. We then spatially integrated this information from fine- to coarse-spatial scales to develop nested envelope models, or Regional Management Units (RMUs), for marine turtles globally. Conclusions/Significance The RMU framework is a solution to the challenge of how to organize marine turtles into units of protection above the level of nesting populations, but below the level of species, within regional entities that might be on independent evolutionary trajectories. Among many potential applications, RMUs provide a framework for identifying data gaps, assessing high diversity areas for multiple species and genetic stocks, and evaluating conservation status of marine turtles. Furthermore, RMUs allow for identification of geographic barriers to gene flow, and can provide valuable guidance to marine spatial planning initiatives that integrate spatial distributions of protected species and human activities. In addition, the RMU framework — including maps and supporting metadata — will be an iterative, user-driven tool made publicly available in an online application for comments, improvements, download and analysis. PMID:21253007

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.

Spatial Variability of CCN Sized Aerosol Particles

NASA Astrophysics Data System (ADS)

Asmi, A.; Väänänen, R.

2014-12-01

The computational limitations restrict the grid size used in GCM models, and for many cloud types they are too large when compared to the scale of the cloud formation processes. Several parameterizations for e.g. convective cloud formation exist, but information on spatial subgrid variation of the cloud condensation nuclei (CCNs) sized aerosol concentration is not known. We quantify this variation as a function of the spatial scale by using datasets from airborne aerosol measurement campaigns around the world including EUCAARI LONGREX, ATAR, INCA, INDOEX, CLAIRE, PEGASOS and several regional airborne campaigns in Finland. The typical shapes of the distributions are analyzed. When possible, we use information obtained by CCN counters. In some other cases, we use particle size distribution measured by for example SMPS to get approximated CCN concentration. Other instruments used include optical particle counters or condensational particle counters. When using the GCM models, the CCN concentration used for each the grid-box is often considered to be either flat, or as an arithmetic mean of the concentration inside the grid-box. However, the aircraft data shows that the concentration values are often lognormal distributed. This, combined with the subgrid variations in the land use and atmospheric properties, might cause that the aerosol-cloud interactions calculated by using mean values to vary significantly from the true effects both temporary and spatially. This, in turn, can cause non-linear bias into the GCMs. We calculate the CCN aerosol concentration distribution as a function of different spatial scales. The measurements allow us to study the variation of these distributions within from hundreds of meters up to hundreds of kilometers. This is used to quantify the potential error when mean values are used in GCMs.

Inputs and spatial distribution patterns of Cr in Jiaozhou Bay

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Miao, Zhenqing; Huang, Xinmin; Wei, Linzhen; Feng, Ming

2018-03-01

Cr pollution in marine bays has been one of the critical environmental issues, and understanding the input and spatial distribution patterns is essential to pollution control. In according to the source strengths of the major pollution sources, the input patterns of pollutants to marine bay include slight, moderate and heavy, and the spatial distribution are corresponding to three block models respectively. This paper analyzed input patterns and distributions of Cr in Jiaozhou Bay, eastern China based on investigation on Cr in surface waters during 1979-1983. Results showed that the input strengths of Cr in Jiaozhou Bay could be classified as moderate input and slight input, and the input strengths were 32.32-112.30 μg L-1 and 4.17-19.76 μg L-1, respectively. The input patterns of Cr included two patterns of moderate input and slight input, and the horizontal distributions could be defined by means of Block Model 2 and Block Model 3, respectively. In case of moderate input pattern via overland runoff, Cr contents were decreasing from the estuaries to the bay mouth, and the distribution pattern was parallel. In case of moderate input pattern via marine current, Cr contents were decreasing from the bay mouth to the bay, and the distribution pattern was parallel to circular. The Block Models were able to reveal the transferring process of various pollutants, and were helpful to understand the distributions of pollutants in marine bay.

Analyzing Protein Clusters on the Plasma Membrane: Application of Spatial Statistical Analysis Methods on Super-Resolution Microscopy Images.

PubMed

Paparelli, Laura; Corthout, Nikky; Pavie, Benjamin; Annaert, Wim; Munck, Sebastian

2016-01-01

The spatial distribution of proteins within the cell affects their capability to interact with other molecules and directly influences cellular processes and signaling. At the plasma membrane, multiple factors drive protein compartmentalization into specialized functional domains, leading to the formation of clusters in which intermolecule interactions are facilitated. Therefore, quantifying protein distributions is a necessity for understanding their regulation and function. The recent advent of super-resolution microscopy has opened up the possibility of imaging protein distributions at the nanometer scale. In parallel, new spatial analysis methods have been developed to quantify distribution patterns in super-resolution images. In this chapter, we provide an overview of super-resolution microscopy and summarize the factors influencing protein arrangements on the plasma membrane. Finally, we highlight methods for analyzing clusterization of plasma membrane proteins, including examples of their applications.

Spatial distribution of end-stage renal disease (ESRD) and social inequalities in mixed urban and rural areas: a study in the Bretagne administrative region of France.

PubMed

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.

Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

USGS Publications Warehouse

Torgersen, Christian E.; Gresswell, Robert E.; Bateman, Douglas S.

2004-01-01

Biological and physical properties of rivers and streams are inherently difficult to sample and visualize at the resolution and extent necessary to detect fine-scale distributional patterns over large areas. Satellite imagery and broad-scale fish survey methods are effective for quantifying spatial variability in biological and physical variables over a range of scales in marine environments but are often too coarse in resolution to address conservation needs in inland fisheries management. We present methods for sampling and analyzing multiscale, spatially continuous patterns of stream fishes and physical habitat in small- to medium-size watersheds (500–1000 hectares). Geospatial tools, including geographic information system (GIS) software such as ArcInfo dynamic segmentation and ArcScene 3D analyst modules, were used to display complex biological and physical datasets. These tools also provided spatial referencing information (e.g. Cartesian and route-measure coordinates) necessary for conducting geostatistical analyses of spatial patterns (empirical semivariograms and wavelet analysis) in linear stream networks. Graphical depiction of fish distribution along a one-dimensional longitudinal profile and throughout the stream network (superimposed on a 10-metre digital elevation model) provided the spatial context necessary for describing and interpreting the relationship between landscape pattern and the distribution of coastal cutthroat trout (Oncorhynchus clarki clarki) in western Oregon, U.S.A. The distribution of coastal cutthroat trout was highly autocorrelated and exhibited a spherical semivariogram with a defined nugget, sill, and range. Wavelet analysis of the main-stem longitudinal profile revealed periodicity in trout distribution at three nested spatial scales corresponding ostensibly to landscape disturbances and the spacing of tributary junctions.

Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.

Distributed Optical Fiber Sensors Based on Optical Frequency Domain Reflectometry: A review

PubMed Central

Wang, Chenhuan; Liu, Kun; Jiang, Junfeng; Yang, Di; Pan, Guanyi; Pu, Zelin; Liu, Tiegen

2018-01-01

Distributed optical fiber sensors (DOFS) offer unprecedented features, the most unique one of which is the ability of monitoring variations of the physical and chemical parameters with spatial continuity along the fiber. Among all these distributed sensing techniques, optical frequency domain reflectometry (OFDR) has been given tremendous attention because of its high spatial resolution and large dynamic range. In addition, DOFS based on OFDR have been used to sense many parameters. In this review, we will survey the key technologies for improving sensing range, spatial resolution and sensing performance in DOFS based on OFDR. We also introduce the sensing mechanisms and the applications of DOFS based on OFDR including strain, stress, vibration, temperature, 3D shape, flow, refractive index, magnetic field, radiation, gas and so on. PMID:29614024

Distributed Optical Fiber Sensors Based on Optical Frequency Domain Reflectometry: A review.

PubMed

Ding, Zhenyang; Wang, Chenhuan; Liu, Kun; Jiang, Junfeng; Yang, Di; Pan, Guanyi; Pu, Zelin; Liu, Tiegen

2018-04-03

Distributed optical fiber sensors (DOFS) offer unprecedented features, the most unique one of which is the ability of monitoring variations of the physical and chemical parameters with spatial continuity along the fiber. Among all these distributed sensing techniques, optical frequency domain reflectometry (OFDR) has been given tremendous attention because of its high spatial resolution and large dynamic range. In addition, DOFS based on OFDR have been used to sense many parameters. In this review, we will survey the key technologies for improving sensing range, spatial resolution and sensing performance in DOFS based on OFDR. We also introduce the sensing mechanisms and the applications of DOFS based on OFDR including strain, stress, vibration, temperature, 3D shape, flow, refractive index, magnetic field, radiation, gas and so on.

Surface plasmon enhanced cell microscopy with blocked random spatial activation

NASA Astrophysics Data System (ADS)

Son, Taehwang; Oh, Youngjin; Lee, Wonju; Yang, Heejin; Kim, Donghyun

2016-03-01

We present surface plasmon enhanced fluorescence microscopy with random spatial sampling using patterned block of silver nanoislands. Rigorous coupled wave analysis was performed to confirm near-field localization on nanoislands. Random nanoislands were fabricated in silver by temperature annealing. By analyzing random near-field distribution, average size of localized fields was found to be on the order of 135 nm. Randomly localized near-fields were used to spatially sample F-actin of J774 cells (mouse macrophage cell-line). Image deconvolution algorithm based on linear imaging theory was established for stochastic estimation of fluorescent molecular distribution. The alignment between near-field distribution and raw image was performed by the patterned block. The achieved resolution is dependent upon factors including the size of localized fields and estimated to be 100-150 nm.

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage

USGS Publications Warehouse

Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

PubMed

Mattsson, Brady J; Zipkin, Elise F; Gardner, Beth; Blank, Peter J; Sauer, John R; Royle, J Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Explaining Local-Scale Species Distributions: Relative Contributions of Spatial Autocorrelation and Landscape Heterogeneity for an Avian Assemblage

PubMed Central

Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition. PMID:23393564

Quantification of spatial distribution and spread of bacteria in soil at microscale

NASA Astrophysics Data System (ADS)

Juyal, Archana; Eickhorst, Thilo; Falconer, Ruth; Baveye, Philippe; Otten, Wilfred

2015-04-01

Soil bacteria play an essential role in functioning of ecosystems and maintaining of biogeochemical cycles. Soil is a complex heterogeneous environment comprising of highly variable and dynamic micro-habitats that have significant impacts on the growth and activity of resident microbiota including bacteria and fungi. Bacteria occupy a very small portion of available pore space in soil which demonstrates that their spatial arrangement in soil has a huge impact on the contact to their target and on the way they interact to carry out their functions. Due to limitation of techniques, there is scant information on spatial distribution of indigenous or introduced bacteria at microhabitat scale. There is a need to understand the interaction between soil structure and microorganisms including fungi for ecosystem-level processes such as carbon sequestration and improving the predictive models for soil management. In this work, a combination of techniques was used including X-ray CT to characterize the soil structure and in-situ detection via fluorescence microscopy to visualize and quantify bacteria in soil thin sections. Pseudomonas fluorescens bacteria were introduced in sterilized soil of aggregate size 1-2 mm and packed at bulk-densities 1.3 g cm-3 and 1.5 g cm-3. A subset of samples was fixed with paraformaldehyde and subsequently impregnated with resin. DAPI and fluorescence in situ hybridization (FISH) were used to visualize bacteria in thin sections of soil cores by epifluorescence microscopy to enumerate spatial distribution of bacteria in soil. The pore geometry of soil was quantified after X-ray microtomography scanning. The distribution of bacteria introduced locally reduced significantly (P

Implementing an SIG based platform of application and service for city spatial information in Shanghai

NASA Astrophysics Data System (ADS)

Yu, Bailang; Wu, Jianping

2006-10-01

Spatial Information Grid (SIG) is an infrastructure that has the ability to provide the services for spatial information according to users' needs by means of collecting, sharing, organizing and processing the massive distributed spatial information resources. This paper presents the architecture, technologies and implementation of the Shanghai City Spatial Information Application and Service System, a SIG based platform, which is an integrated platform that serves for administration, planning, construction and development of the city. In the System, there are ten categories of spatial information resources, including city planning, land-use, real estate, river system, transportation, municipal facility construction, environment protection, sanitation, urban afforestation and basic geographic information data. In addition, spatial information processing services are offered as a means of GIS Web Services. The resources and services are all distributed in different web-based nodes. A single database is created to store the metadata of all the spatial information. A portal site is published as the main user interface of the System. There are three main functions in the portal site. First, users can search the metadata and consequently acquire the distributed data by using the searching results. Second, some spatial processing web applications that developed with GIS Web Services, such as file format conversion, spatial coordinate transfer, cartographic generalization and spatial analysis etc, are offered to use. Third, GIS Web Services currently available in the System can be searched and new ones can be registered. The System has been working efficiently in Shanghai Government Network since 2005.

Spatially Explicit Modeling Reveals Cephalopod Distributions Match Contrasting Trophic Pathways in the Western Mediterranean Sea

PubMed Central

Puerta, Patricia; Hunsicker, Mary E.; Quetglas, Antoni; Álvarez-Berastegui, Diego; Esteban, Antonio; González, María; Hidalgo, Manuel

2015-01-01

Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla) and sea surface temperature (SST), and trophic (prey density) conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid) across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents a valuable approach for understanding the spatially variant ecology of cephalopod populations, which is important for fisheries and ecosystem management. PMID:26201075

Long-Term Changes in the Distributions of Larval and Adult Fish in the Northeast U.S. Shelf Ecosystem.

PubMed

Walsh, Harvey J; Richardson, David E; Marancik, Katrin E; Hare, Jonathan A

2015-01-01

Many studies have documented long-term changes in adult marine fish distributions and linked these changes to climate change and multi-decadal climate variability. Most marine fish, however, have complex life histories with morphologically distinct stages, which use different habitats. Shifts in distribution of one stage may affect the connectivity between life stages and thereby impact population processes including spawning and recruitment. Specifically, many marine fish species have a planktonic larval stage, which lasts from weeks to months. We compared the spatial distribution and seasonal occurrence of larval fish in the Northeast U.S. Shelf Ecosystem to test whether spatial and temporal distributions changed between two decades. Two large-scale ichthyoplankton programs sampled using similar methods and spatial domain each decade. Adult distributions from a long-term bottom trawl survey over the same time period and spatial area were also analyzed using the same analytical framework to compare changes in larval and adult distributions between the two decades. Changes in spatial distribution of larvae occurred for 43% of taxa, with shifts predominately northward (i.e., along-shelf). Timing of larval occurrence shifted for 49% of the larval taxa, with shifts evenly split between occurring earlier and later in the season. Where both larvae and adults of the same species were analyzed, 48% exhibited different shifts between larval and adult stages. Overall, these results demonstrate that larval fish distributions are changing in the ecosystem. The spatial changes are largely consistent with expectations from a changing climate. The temporal changes are more complex, indicating we need a better understanding of reproductive timing of fishes in the ecosystem. These changes may impact population productivity through changes in life history connectivity and recruitment, and add to the accumulating evidence for changes in the Northeast U.S. Shelf Ecosystem with potential to impact fisheries and other ecosystem services.

Long-Term Changes in the Distributions of Larval and Adult Fish in the Northeast U.S. Shelf Ecosystem

PubMed Central

2015-01-01

Many studies have documented long-term changes in adult marine fish distributions and linked these changes to climate change and multi-decadal climate variability. Most marine fish, however, have complex life histories with morphologically distinct stages, which use different habitats. Shifts in distribution of one stage may affect the connectivity between life stages and thereby impact population processes including spawning and recruitment. Specifically, many marine fish species have a planktonic larval stage, which lasts from weeks to months. We compared the spatial distribution and seasonal occurrence of larval fish in the Northeast U.S. Shelf Ecosystem to test whether spatial and temporal distributions changed between two decades. Two large-scale ichthyoplankton programs sampled using similar methods and spatial domain each decade. Adult distributions from a long-term bottom trawl survey over the same time period and spatial area were also analyzed using the same analytical framework to compare changes in larval and adult distributions between the two decades. Changes in spatial distribution of larvae occurred for 43% of taxa, with shifts predominately northward (i.e., along-shelf). Timing of larval occurrence shifted for 49% of the larval taxa, with shifts evenly split between occurring earlier and later in the season. Where both larvae and adults of the same species were analyzed, 48% exhibited different shifts between larval and adult stages. Overall, these results demonstrate that larval fish distributions are changing in the ecosystem. The spatial changes are largely consistent with expectations from a changing climate. The temporal changes are more complex, indicating we need a better understanding of reproductive timing of fishes in the ecosystem. These changes may impact population productivity through changes in life history connectivity and recruitment, and add to the accumulating evidence for changes in the Northeast U.S. Shelf Ecosystem with potential to impact fisheries and other ecosystem services. PMID:26398900

Spatial intensity distribution of controlled-NOT gate carrying orbital angular momentum via photonic band gap structure

NASA Astrophysics Data System (ADS)

Zhang, Yan; Wang, Xiaorui; Zhe Zhang, Yun

2018-07-01

By employing the different topological charges of a Laguerre–Gaussian beam as a qubit, we experimentally demonstrate a controlled-NOT (CNOT) gate with light beams carrying orbital angular momentum via a photonic band gap structure in a hot atomic ensemble. Through a degenerate four-wave mixing process, the spatial distribution of the CNOT gate including splitting and spatial shift can be affected by the Kerr nonlinear effect in multilevel atomic systems. Moreover, the intensity variations of the CNOT gate can be controlled by the relative phase modulation. This research can be useful for applications in quantum information processing.

Inverse modelling of fluvial sediment connectivity identifies characteristics and spatial distribution of sediment sources in a large river network.

NASA Astrophysics Data System (ADS)

Schmitt, R. J. P.; Bizzi, S.; Kondolf, G. M.; Rubin, Z.; Castelletti, A.

2016-12-01

Field and laboratory evidence indicates that the spatial distribution of transport in both alluvial and bedrock rivers is an adaptation to sediment supply. Sediment supply, in turn, depends on spatial distribution and properties (e.g., grain sizes and supply rates) of individual sediment sources. Analyzing the distribution of transport capacity in a river network could hence clarify the spatial distribution and properties of sediment sources. Yet, challenges include a) identifying magnitude and spatial distribution of transport capacity for each of multiple grain sizes being simultaneously transported, and b) estimating source grain sizes and supply rates, both at network scales. Herein, we approach the problem of identifying the spatial distribution of sediment sources and the resulting network sediment fluxes in a major, poorly monitored tributary (80,000 km2) of the Mekong. Therefore, we apply the CASCADE modeling framework (Schmitt et al. (2016)). CASCADE calculates transport capacities and sediment fluxes for multiple grainsizes on the network scale based on remotely-sensed morphology and modelled hydrology. CASCADE is run in an inverse Monte Carlo approach for 7500 random initializations of source grain sizes. In all runs, supply of each source is inferred from the minimum downstream transport capacity for the source grain size. Results for each realization are compared to sparse available sedimentary records. Only 1 % of initializations reproduced the sedimentary record. Results for these realizations revealed a spatial pattern in source supply rates, grain sizes, and network sediment fluxes that correlated well with map-derived patterns in lithology and river-morphology. Hence, we propose that observable river hydro-morphology contains information on upstream source properties that can be back-calculated using an inverse modeling approach. Such an approach could be coupled to more detailed models of hillslope processes in future to derive integrated models of hillslope production and fluvial transport processes, which is particularly useful to identify sediment provenance in poorly monitored river basins.

Large-watershed flood simulation and forecasting based on different-resolution distributed hydrological model

NASA Astrophysics Data System (ADS)

Li, J.

2017-12-01

Large-watershed flood simulation and forecasting is very important for a distributed hydrological model in the application. There are some challenges including the model's spatial resolution effect, model performance and accuracy and so on. To cope with the challenge of the model's spatial resolution effect, different model resolution including 1000m*1000m, 600m*600m, 500m*500m, 400m*400m, 200m*200m were used to build the distributed hydrological model—Liuxihe model respectively. The purpose is to find which one is the best resolution for Liuxihe model in Large-watershed flood simulation and forecasting. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil type and land use type are downloaded from the website freely. The model parameters are optimized by using an improved Particle Swarm Optimization(PSO) algorithm; And parameter optimization could reduce the parameter uncertainty that exists for physically deriving model parameters. The different model resolution (200m*200m—1000m*1000m ) are proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. The best model's spatial resolution effect for flood simulation and forecasting is 200m*200m.And with the model's spatial resolution reduction, the model performance and accuracy also become worse and worse. When the model resolution is 1000m*1000m, the flood simulation and forecasting result is the worst, also the river channel divided based on this resolution is differs from the actual one. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500m*500m grid cell, but the model spatial resolution with a 200m*200m grid cell is recommended in this study to keep the model at a best performance.

Spatial Distribution of Lactococcus lactis Colonies Modulates the Production of Major Metabolites during the Ripening of a Model Cheese.

PubMed

Le Boucher, Clémentine; Gagnaire, Valérie; Briard-Bion, Valérie; Jardin, Julien; Maillard, Marie-Bernadette; Dervilly-Pinel, Gaud; Le Bizec, Bruno; Lortal, Sylvie; Jeanson, Sophie; Thierry, Anne

2016-01-01

In cheese, lactic acid bacteria are immobilized at the coagulation step and grow as colonies. The spatial distribution of bacterial colonies is characterized by the size and number of colonies for a given bacterial population within cheese. Our objective was to demonstrate that different spatial distributions, which lead to differences in the exchange surface between the colonies and the cheese matrix, can influence the ripening process. The strategy was to generate cheeses with the same growth and acidification of a Lactococcus lactis strain with two different spatial distributions, big and small colonies, to monitor the production of the major ripening metabolites, including sugars, organic acids, peptides, free amino acids, and volatile metabolites, over 1 month of ripening. The monitored metabolites were qualitatively the same for both cheeses, but many of them were more abundant in the small-colony cheeses than in the big-colony cheeses over 1 month of ripening. Therefore, the results obtained showed that two different spatial distributions of L. lactis modulated the ripening time course by generating moderate but significant differences in the rates of production or consumption for many of the metabolites commonly monitored throughout ripening. The present work further explores the immobilization of bacteria as colonies within cheese and highlights the consequences of this immobilization on cheese ripening. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Preliminary surficial geologic map database of the Amboy 30 x 60 minute quadrangle, California

USGS Publications Warehouse

Bedford, David R.; Miller, David M.; Phelps, Geoffrey A.

2006-01-01

The surficial geologic map database of the Amboy 30x60 minute quadrangle presents characteristics of surficial materials for an area approximately 5,000 km2 in the eastern Mojave Desert of California. This map consists of new surficial mapping conducted between 2000 and 2005, as well as compilations of previous surficial mapping. Surficial geology units are mapped and described based on depositional process and age categories that reflect the mode of deposition, pedogenic effects occurring post-deposition, and, where appropriate, the lithologic nature of the material. The physical properties recorded in the database focus on those that drive hydrologic, biologic, and physical processes such as particle size distribution (PSD) and bulk density. This version of the database is distributed with point data representing locations of samples for both laboratory determined physical properties and semi-quantitative field-based information. Future publications will include the field and laboratory data as well as maps of distributed physical properties across the landscape tied to physical process models where appropriate. The database is distributed in three parts: documentation, spatial map-based data, and printable map graphics of the database. Documentation includes this file, which provides a discussion of the surficial geology and describes the format and content of the map data, a database 'readme' file, which describes the database contents, and FGDC metadata for the spatial map information. Spatial data are distributed as Arc/Info coverage in ESRI interchange (e00) format, or as tabular data in the form of DBF3-file (.DBF) file formats. Map graphics files are distributed as Postscript and Adobe Portable Document Format (PDF) files, and are appropriate for representing a view of the spatial database at the mapped scale.

Method and system for spatial data input, manipulation and distribution via an adaptive wireless transceiver

NASA Technical Reports Server (NTRS)

Wang, Ray (Inventor)

2009-01-01

A method and system for spatial data manipulation input and distribution via an adaptive wireless transceiver. The method and system include a wireless transceiver for automatically and adaptively controlling wireless transmissions using a Waveform-DNA method. The wireless transceiver can operate simultaneously over both the short and long distances. The wireless transceiver is automatically adaptive and wireless devices can send and receive wireless digital and analog data from various sources rapidly in real-time via available networks and network services.

Determinants of the geographic distribution of Puumala virus and Lyme borreliosis infections in Belgium.

PubMed

Linard, Catherine; Lamarque, Pénélope; Heyman, Paul; Ducoffre, Geneviève; Luyasu, Victor; Tersago, Katrien; Vanwambeke, Sophie O; Lambin, Eric F

2007-05-02

Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover and land use influence disease transmission by controlling both the spatial distribution of vectors or hosts, and the probability of contact with susceptible human populations. The objective of this study was to combine environmental and socio-economic factors to explain the spatial distribution of two emerging human diseases in Belgium, Puumala virus (PUUV) and Lyme borreliosis. Municipalities were taken as units of analysis. Negative binomial regressions including a correction for spatial endogeneity show that the spatial distribution of PUUV and Lyme borreliosis infections are associated with a combination of factors linked to the vector and host populations, to human behaviours, and to landscape attributes. Both diseases are associated with the presence of forests, which are the preferred habitat for vector or host populations. The PUUV infection risk is higher in remote forest areas, where the level of urbanisation is low, and among low-income populations. The Lyme borreliosis transmission risk is higher in mixed landscapes with forests and spatially dispersed houses, mostly in wealthy peri-urban areas. The spatial dependence resulting from a combination of endogenous and exogenous processes could be accounted for in the model on PUUV but not for Lyme borreliosis. A large part of the spatial variation in disease risk can be explained by environmental and socio-economic factors. The two diseases not only are most prevalent in different regions but also affect different groups of people. Combining these two criteria may increase the efficiency of information campaigns through appropriate targeting.

Hierarchical analysis of species distributions and abundance across environmental gradients

Treesearch

Jeffery Diez; Ronald H. Pulliam

2007-01-01

Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes...

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions.

PubMed

Wilson, Adam M; Jetz, Walter

2016-03-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

MULTIMEDIA ENVIRONMENTAL DISTRIBUTION OF TOXICS (MEND-TOX): PART II, SOFTWARE IMPLEMENTATION AND CASE STUDIES

EPA Science Inventory

An integrated hybrid spatial-compartmental simulator is presented for analyzing the dynamic distribution of chemicals in the multimedia environment. Information obtained from such analysis, which includes temporal chemical concentration profiles in various media, mass distribu...

Spatial surplus production modeling of Atlantic tunas and billfish.

PubMed

Carruthers, Thomas R; McAllister, Murdoch K; Taylor, Nathan G

2011-10-01

We formulate and simulation-test a spatial surplus production model that provides a basis with which to undertake multispecies, multi-area, stock assessment. Movement between areas is parameterized using a simple gravity model that includes a "residency" parameter that determines the degree of stock mixing among areas. The model is deliberately simple in order to (1) accommodate nontarget species that typically have fewer available data and (2) minimize computational demand to enable simulation evaluation of spatial management strategies. Using this model, we demonstrate that careful consideration of spatial catch and effort data can provide the basis for simple yet reliable spatial stock assessments. If simple spatial dynamics can be assumed, tagging data are not required to reliably estimate spatial distribution and movement. When applied to eight stocks of Atlantic tuna and billfish, the model tracks regional catch data relatively well by approximating local depletions and exchange among high-abundance areas. We use these results to investigate and discuss the implications of using spatially aggregated stock assessment for fisheries in which the distribution of both the population and fishing vary over time.

Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.

PubMed

Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J

2010-12-01

Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies conservation planning. Journal compilation © 2010 Society for Conservation Biology. No claim to original US government works.

Multistage Spatial Property Based Segmentation for Quantification of Fluorescence Distribution in Cells

NASA Astrophysics Data System (ADS)

Zhang, Guangyun; Jia, Xiuping; Pham, Tuan D.; Crane, Denis I.

2010-01-01

The interpretation of the distribution of fluorescence in cells is often by simple visualization of microscope-derived images for qualitative studies. In other cases, however, it is desirable to be able to quantify the distribution of fluorescence using digital image processing techniques. In this paper, the challenges of fluorescence segmentation due to the noise present in the data are addressed. We report that intensity measurements alone do not allow separation of overlapping data between target and background. Consequently, spatial properties derived from neighborhood profile were included. Mathematical Morphological operations were implemented for cell boundary extraction and a window based contrast measure was developed for fluorescence puncta identification. All of these operations were applied in the proposed multistage processing scheme. The testing results show that the spatial measures effectively enhance the target separability.

Estimating the Spatial Distribution of Groundwater Age Using Synoptic Surveys of Environmental Tracers in Streams

NASA Astrophysics Data System (ADS)

Gardner, W. P.

2017-12-01

A model which simulates tracer concentration in surface water as a function the age distribution of groundwater discharge is used to characterize groundwater flow systems at a variety of spatial scales. We develop the theory behind the model and demonstrate its application in several groundwater systems of local to regional scale. A 1-D stream transport model, which includes: advection, dispersion, gas exchange, first-order decay and groundwater inflow is coupled a lumped parameter model that calculates the concentration of environmental tracers in discharging groundwater as a function of the groundwater residence time distribution. The lumped parameters, which describe the residence time distribution, are allowed to vary spatially, and multiple environmental tracers can be simulated. This model allows us to calculate the longitudinal profile of tracer concentration in streams as a function of the spatially variable groundwater age distribution. By fitting model results to observations of stream chemistry and discharge, we can then estimate the spatial distribution of groundwater age. The volume of groundwater discharge to streams can be estimated using a subset of environmental tracers, applied tracers, synoptic stream gauging or other methods, and the age of groundwater then estimated using the previously calculated groundwater discharge and observed environmental tracer concentrations. Synoptic surveys of SF6, CFC's, 3H and 222Rn, along with measured stream discharge are used to estimate the groundwater inflow distribution and mean age for regional scale surveys of the Berland River in west-central Alberta. We find that groundwater entering the Berland has observable age, and that the age estimated using our stream survey is of similar order to limited samples from groundwater wells in the region. Our results show that the stream can be used as an easily accessible location to constrain the regional scale spatial distribution of groundwater age.

Spatial distribution and longitudinal development of deep cortical sulcal landmarks in infants.

PubMed

Meng, Yu; Li, Gang; Lin, Weili; Gilmore, John H; Shen, Dinggang

2014-10-15

Sulcal pits, the locally deepest points in sulci of the highly convoluted and variable cerebral cortex, are found to be spatially consistent across human adult individuals. It is suggested that sulcal pits are genetically controlled and have close relationships with functional areas. To date, the existing imaging studies of sulcal pits are mainly focused on adult brains, yet little is known about the spatial distribution and temporal development of sulcal pits in the first 2 years of life, which is the most dynamic and critical period of postnatal brain development. Studying sulcal pits during this period would greatly enrich our limited understandings of the origins and developmental trajectories of sulcal pits, and would also provide important insights into many neurodevelopmental disorders associated with abnormal cortical foldings. In this paper, by using surface-based morphometry, for the first time, we systemically investigated the spatial distribution and temporal development of sulcal pits in major cortical sulci from 73 healthy infants, each with three longitudinal 3T MR scans at term birth, 1 year, and 2 years of age. Our results suggest that the spatially consistent distributions of sulcal pits in major sulci across individuals have already existed at term birth and this spatial distribution pattern keeps relatively stable in the first 2 years of life, despite that the cerebral cortex expands dramatically and the sulcal depth increases considerably during this period. Specially, the depth of sulcal pits increases regionally heterogeneously, with more rapid growth in the high-order association cortex, including the prefrontal and temporal cortices, than the sensorimotor cortex in the first 2 years of life. Meanwhile, our results also suggest that there exist hemispheric asymmetries of the spatial distributions of sulcal pits in several cortical regions, such as the central, superior temporal and postcentral sulci, consistently from birth to 2 years of age, which likely has close relationships with the lateralization of brain functions of these regions. This study provides detailed insights into the spatial distribution and temporal development of deep sulcal landmarks in infants. Copyright © 2014 Elsevier Inc. All rights reserved.

Making Temporal Search More Central in Spatial Data Infrastructures

NASA Astrophysics Data System (ADS)

Corti, P.; Lewis, B.

2017-10-01

A temporally enabled Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users, and tools intended to provide an efficient and flexible way to use spatial information which includes the historical dimension. One of the key software components of an SDI is the catalogue service which is needed to discover, query, and manage the metadata. A search engine is a software system capable of supporting fast and reliable search, which may use any means necessary to get users to the resources they need quickly and efficiently. These techniques may include features such as full text search, natural language processing, weighted results, temporal search based on enrichment, visualization of patterns in distributions of results in time and space using temporal and spatial faceting, and many others. In this paper we will focus on the temporal aspects of search which include temporal enrichment using a time miner - a software engine able to search for date components within a larger block of text, the storage of time ranges in the search engine, handling historical dates, and the use of temporal histograms in the user interface to display the temporal distribution of search results.

Mercury's Exosphere During MESSENGER's Second Flyby: Detection of Magnesium and Distinct Distributions of Neutral Species

NASA Technical Reports Server (NTRS)

McClintock, William E.; Vervack, Ronald J., Jr.; Bradley, E. Todd; Killen, Rosemary M.; Mouawad, Nelly; Sprague, Ann L.; Burger, Matthew H.; Solomon, Sean C.; Izenberg, Noam R.

2009-01-01

During MESSENGER's second Mercury flyby, the Mercury Atmospheric and Surface Composition Spectrometer observed emission from Mercury's neutral exosphere. These observations include the first detection of emission from magnesium. Differing spatial distributions for sodium, calcium, and magnesium were revealed by observations beginning in Mercury's tail region, approximately 8 Mercury radii anti-sunward of the planet, continuing past the nightside, and ending near the dawn terminator. Analysis of these observations, supplemented by observations during the first Mercury flyby as well as those by other MESSENGER instruments, suggests that the distinct spatial distributions arise from a combination of differences in source, transfer, and loss processes.

Method for spatially distributing a population

DOEpatents

Bright, Edward A [Knoxville, TN; Bhaduri, Budhendra L [Knoxville, TN; Coleman, Phillip R [Knoxville, TN; Dobson, Jerome E [Lawrence, KS

2007-07-24

A process for spatially distributing a population count within a geographically defined area can include the steps of logically correlating land usages apparent from a geographically defined area to geospatial features in the geographically defined area and allocating portions of the population count to regions of the geographically defined area having the land usages, according to the logical correlation. The process can also include weighing the logical correlation for determining the allocation of portions of the population count and storing the allocated portions within a searchable data store. The logically correlating step can include the step of logically correlating time-based land usages to geospatial features of the geographically defined area. The process can also include obtaining a population count for the geographically defined area, organizing the geographically defined area into a plurality of sectors, and verifying the allocated portions according to direct observation.

mizuRoute version 1: A river network routing tool for a continental domain water resources applications

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Sampson, Kevin; Nijssen, Bart; Mao, Yixin; McMillan, Hilary; Viger, Roland; Markstrom, Steven; Hay, Lauren E.; Woods, Ross; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1) a kinematic wave tracking (KWT) routing procedure; and (2) an impulse response function – unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.

Distribution of ULF energy (f is less than 80 mHz) in the inner magnetosphere - A statistical analysis of AMPTE CCE magnetic field data

NASA Technical Reports Server (NTRS)

Takahashi, Kazue; Anderson, Brian J.

1992-01-01

Magnetic field measurements made with the AMPTE CCE spacecraft are used to investigate the distribution of ULF energy in the inner magnetosphere. The data base is employed to examine the spatial distribution of ULF energy. The spatial distribution of wave power and spectral structures are used to identify several pulsation types, including multiharmonic toroidal oscillations; equatorial compressional Pc 3 oscillations; second harmonic poloidal oscillations; and nightside compressional oscillations. The frequencies of the toroidal oscillations are applied to determine the statistical radial profile of the plasma mass density and Alfven velocity. A clear signature of the plasma pause in the profiles of these average parameters is found.

Temporal and Spatial Analysis of Monogenetic Volcanic Fields

NASA Astrophysics Data System (ADS)

Kiyosugi, Koji

Achieving an understanding of the nature of monogenetic volcanic fields depends on identification of the spatial and temporal patterns of volcanism in these fields, and their relationships to structures mapped in the shallow crust and inferred in the deep crust and mantle through interpretation of geochemical, radiometric and geophysical data. We investigate the spatial and temporal distributions of volcanism in the Abu Monogenetic Volcano Group, Southwest Japan. E-W elongated volcano distribution, which is identified by a nonparametric kernel method, is found to be consistent with the spatial extent of P-wave velocity anomalies in the lower crust and upper mantle, supporting the idea that the spatial density map of volcanic vents reflects the geometry of a mantle diapir. Estimated basalt supply to the lower crust is constant. This observation and the spatial distribution of volcanic vents suggest stability of magma productivity and essentially constant two-dimensional size of the source mantle diapir. We mapped conduits, dike segments, and sills in the San Rafael sub-volcanic field, Utah, where the shallowest part of a Pliocene magmatic system is exceptionally well exposed. The distribution of conduits matches the major features of dike distribution, including development of clusters and distribution of outliers. The comparison of San Rafael conduit distribution and the distributions of volcanoes in several recently active volcanic fields supports the use of statistical models, such as nonparametric kernel methods, in probabilistic hazard assessment for distributed volcanism. We developed a new recurrence rate calculation method that uses a Monte Carlo procedure to better reflect and understand the impact of uncertainties of radiometric age determinations on uncertainty of recurrence rate estimates for volcanic activity in the Abu, Yucca Mountain Region, and Izu-Tobu volcanic fields. Results suggest that the recurrence rates of volcanic fields can change by more than one order of magnitude on time scales of several hundred thousand to several million years. This suggests that magma generation rate beneath volcanic fields may change over these time scales. Also, recurrence rate varies more than one order of magnitude between these volcanic fields, consistent with the idea that distributed volcanism may be influenced by both the rate of magma generation and the potential for dike interaction during ascent.

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

PubMed

Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

2011-06-01

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

Generation of dark hollow femtosecond pulsed beam by phase-only liquid crystal spatial light modulator

NASA Astrophysics Data System (ADS)

Nie, Yongming; Ma, Haotong; Li, Xiujian; Hu, Wenhua; Yang, Jiankun

2011-07-01

Based on the refractive laser beam shaping system, the dark hollow femtosecond pulse beam shaping technique with a phase-only liquid crystal spatial light modulator (LC-SLM) is demonstrated. The phase distribution of the LC-SLM is derived by the energy conservation and constant optical path principle. The effects of the shaping system on the temporal properties, including spectral phase distribution and bandwidth of the femtosecond pulse, are analyzed in detail. Experimental results show that the hollow intensity distribution of the output pulsed beam can be maintained much at more than 1200mm. The spectral phase of the pulse is changed, and the pulse width is expanded from 199 to 230fs, which is caused by the spatial--temporal coupling effect. The coupling effect mainly depends on the phase-only LC-SLM itself, not on its loaded phase distribution. The experimental results indicate that the proposed shaping setup can generate a dark hollow femtosecond pulsed beam effectively, because the temporal Gaussian waveform is unchanged.

Local and Widely Distributed EEG Activity in Schizophrenia With Prevalence of Negative Symptoms.

PubMed

Grin-Yatsenko, Vera A; Ponomarev, Valery A; Pronina, Marina V; Poliakov, Yury I; Plotnikova, Irina V; Kropotov, Juri D

2017-09-01

We evaluated EEG frequency abnormalities in resting state (eyes closed and eyes open) EEG in a group of chronic schizophrenia patients as compared with healthy subjects. The study included 3 methods of analysis of deviation of EEG characteristics: genuine EEG, current source density (CSD), and group independent component (gIC). All 3 methods have shown that the EEG in schizophrenia patients is characterized by enhanced low-frequency (delta and theta) and high-frequency (beta) activity in comparison with the control group. However, the spatial pattern of differences was dependent on the type of method used. Comparative analysis has shown that increased EEG power in schizophrenia patients apparently concerns both widely spatially distributed components and local components of signal. Furthermore, the observed differences in the delta and theta range can be described mainly by the local components, and those in the beta range mostly by spatially widely distributed ones. The possible nature of the widely distributed activity is discussed.

A comparative study of the spatial distribution of mast cells and microvessels in the foetal, adult human thymus and thymoma.

PubMed

Raica, Marius; Cimpean, Anca Maria; Nico, Beatrice; Guidolin, Diego; Ribatti, Domenico

2010-02-01

Mast cells (MCs) are widely distributed in human and animal tissues and have been shown to play an important role in angiogenesis in normal and pathological conditions. Few data are available about the relationship between MCs and blood vessels in the normal human thymus, and there are virtually no data about their distribution and significance in thymoma. The aim of this study was to analyse the spatial distribution of MCs and microvessels in the normal foetal and adult thymus and thymoma. Twenty biopsy specimens of human thymus, including foetal and adult normal thymus and thymoma were analysed. Double staining with CD34 and mast cell tryptase was used to count both mast cells and microvessels in the same fields. Computer-assisted image analysis was performed to characterize the spatial distribution of MCs and blood vessels in selected specimens. Results demonstrated that MCs were localized exclusively to the medulla. Their number was significantly higher in thymoma specimens as compared with adult and foetal normal specimens respectively. In contrast the microvessel area was unchanged. The analysis of the spatial distribution and relationship between MCs and microvessels revealed that only in the thymoma specimens was there a significant spatial association between MCs and microvessels. Overall, these data suggest that MCs do not contribute significantly to the development of the vascular network in foetal and adult thymus, whereas in thymoma they show a close relationship to blood vessels. This could be an expression of their involvement not only in endothelial cells but also in tumour cell proliferation.

Lightning characteristics of derecho producing mesoscale convective systems

NASA Astrophysics Data System (ADS)

Bentley, Mace L.; Franks, John R.; Suranovic, Katelyn R.; Barbachem, Brent; Cannon, Declan; Cooper, Stonie R.

2016-06-01

Derechos, or widespread, convectively induced wind storms, are a common warm season phenomenon in the Central and Eastern United States. These damaging and severe weather events are known to sweep quickly across large spatial regions of more than 400 km and produce wind speeds exceeding 121 km h-1. Although extensive research concerning derechos and their parent mesoscale convective systems already exists, there have been few investigations of the spatial and temporal distribution of associated cloud-to-ground lightning with these events. This study analyzes twenty warm season (May through August) derecho events between 2003 and 2013 in an effort to discern their lightning characteristics. Data used in the study included cloud-to-ground flash data derived from the National Lightning Detection Network, WSR-88D imagery from the University Corporation for Atmospheric Research, and damaging wind report data obtained from the Storm Prediction Center. A spatial and temporal analysis was conducted by incorporating these data into a geographic information system to determine the distribution and lightning characteristics of the environments of derecho producing mesoscale convective systems. Primary foci of this research include: (1) finding the approximate size of the lightning activity region for individual and combined event(s); (2) determining the intensity of each event by examining the density and polarity of lightning flashes; (3) locating areas of highest lightning flash density; and (4) to provide a lightning spatial analysis that outlines the temporal and spatial distribution of flash activity for particularly strong derecho producing thunderstorm episodes.

Spatially Resolved Chemical Imaging for Biosignature Analysis: Terrestrial and Extraterrestrial Examples

NASA Astrophysics Data System (ADS)

Bhartia, R.; Wanger, G.; Orphan, V. J.; Fries, M.; Rowe, A. R.; Nealson, K. H.; Abbey, W. J.; DeFlores, L. P.; Beegle, L. W.

2014-12-01

Detection of in situ biosignatures on terrestrial and planetary missions is becoming increasingly more important. Missions that target the Earth's deep biosphere, Mars, moons of Jupiter (including Europa), moons of Saturn (Titan and Enceladus), and small bodies such as asteroids or comets require methods that enable detection of materials for both in-situ analysis that preserve context and as a means to select high priority sample for return to Earth. In situ instrumentation for biosignature detection spans a wide range of analytical and spectroscopic methods that capitalize on amino acid distribution, chirality, lipid composition, isotopic fractionation, or textures that persist in the environment. Many of the existing analytical instruments are bulk analysis methods and while highly sensitive, these require sample acquisition and sample processing. However, by combining with triaging spectroscopic methods, biosignatures can be targeted on a surface and preserve spatial context (including mineralogy, textures, and organic distribution). To provide spatially correlated chemical analysis at multiple spatial scales (meters to microns) we have employed a dual spectroscopic approach that capitalizes on high sensitivity deep UV native fluorescence detection and high specificity deep UV Raman analysis.. Recently selected as a payload on the Mars 2020 mission, SHERLOC incorporates these optical methods for potential biosignatures detection on Mars. We present data from both Earth analogs that operate as our only examples known biosignatures and meteorite samples that provide an example of abiotic organic formation, and demonstrate how provenance effects the spatial distribution and composition of organics.

Spatial distribution of malaria in Peninsular Malaysia from 2000 to 2009.

PubMed

Alias, Haridah; Surin, Johari; Mahmud, Rohela; Shafie, Aziz; Mohd Zin, Junaidden; Mohamad Nor, Mahadzir; Ibrahim, Ahmad Shah; Rundi, Christina

2014-04-15

Malaria is still an endemic disease of public health importance in Malaysia. Populations at risk of contracting malaria includes indigenous people, traditional villagers, mobile ethnic groups and land scheme settlers, immigrants from malaria endemic countries as well as jungle workers and loggers. The predominant species are Plasmodium falciparum and P. vivax. An increasing number of P. knowlesi infections have also been encountered. The principal vectors in Peninsular Malaysia are Anopheles maculatus and An. cracens. This study aims to determine the changes in spatial distribution of malaria in Peninsular Malaysia from year 2000-2009. Data for the study was collected from Ministry of Health, Malaysia and was analysed using Geographic Information System (GIS). Changes for a period of 10 years of malaria spatial distribution in 12 states of Peninsular Malaysia were documented and discussed. This is illustrated by digital mapping according to five variables; incidence rate (IR), fatality rate (FR), annual blood examination rate (ABER), annual parasite index (API) and slide positivity rate (SPR). There is a profound change in the spatial distribution of malaria within a 10-year period. This is evident from the digital mapping of the infection in Peninsular Malaysia.

Spatial and space-time distribution of Plasmodium vivax and Plasmodium falciparum malaria in China, 2005-2014.

PubMed

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.

Historical and ecological drivers of the spatial pattern of Chondrichthyes species richness in the Mediterranean Sea.

PubMed

Meléndez, María José; Báez, José Carlos; Serna-Quintero, José Miguel; Camiñas, Juan Antonio; Fernández, Ignacio de Loyola; Real, Raimundo; Macías, David

2017-01-01

Chondrichthyes, which include Elasmobranchii (sharks and batoids) and Holocephali (chimaeras), are a relatively small group in the Mediterranean Sea (89 species) playing a key role in the ecosystems where they are found. At present, many species of this group are threatened as a result of anthropogenic effects, including fishing activity. Knowledge of the spatial distribution of these species is of great importance to understand their ecological role and for the efficient management of their populations, particularly if affected by fisheries. This study aims to analyze the spatial patterns of the distribution of Chondrichthyes species richness in the Mediterranean Sea. Information provided by the studied countries was used to model geographical and ecological variables affecting the Chondrichthyes species richness. The species were distributed in 16 Operational Geographical Units (OGUs), derived from the Geographical Sub-Areas (GSA) adopted by the General Fisheries Commission of the Mediterranean Sea (GFCM). Regression analyses with the species richness as a target variable were adjusted with a set of environmental and geographical variables, being the model that links richness of Chondrichthyes species with distance to the Strait of Gibraltar and number of taxonomic families of bony fishes the one that best explains it. This suggests that both historical and ecological factors affect the current distribution of Chondrichthyes within the Mediterranean Sea.

GSHR-Tree: a spatial index tree based on dynamic spatial slot and hash table in grid environments

NASA Astrophysics Data System (ADS)

Chen, Zhanlong; Wu, Xin-cai; Wu, Liang

2008-12-01

Computation Grids enable the coordinated sharing of large-scale distributed heterogeneous computing resources that can be used to solve computationally intensive problems in science, engineering, and commerce. Grid spatial applications are made possible by high-speed networks and a new generation of Grid middleware that resides between networks and traditional GIS applications. The integration of the multi-sources and heterogeneous spatial information and the management of the distributed spatial resources and the sharing and cooperative of the spatial data and Grid services are the key problems to resolve in the development of the Grid GIS. The performance of the spatial index mechanism is the key technology of the Grid GIS and spatial database affects the holistic performance of the GIS in Grid Environments. In order to improve the efficiency of parallel processing of a spatial mass data under the distributed parallel computing grid environment, this paper presents a new grid slot hash parallel spatial index GSHR-Tree structure established in the parallel spatial indexing mechanism. Based on the hash table and dynamic spatial slot, this paper has improved the structure of the classical parallel R tree index. The GSHR-Tree index makes full use of the good qualities of R-Tree and hash data structure. This paper has constructed a new parallel spatial index that can meet the needs of parallel grid computing about the magnanimous spatial data in the distributed network. This arithmetic splits space in to multi-slots by multiplying and reverting and maps these slots to sites in distributed and parallel system. Each sites constructs the spatial objects in its spatial slot into an R tree. On the basis of this tree structure, the index data was distributed among multiple nodes in the grid networks by using large node R-tree method. The unbalance during process can be quickly adjusted by means of a dynamical adjusting algorithm. This tree structure has considered the distributed operation, reduplication operation transfer operation of spatial index in the grid environment. The design of GSHR-Tree has ensured the performance of the load balance in the parallel computation. This tree structure is fit for the parallel process of the spatial information in the distributed network environments. Instead of spatial object's recursive comparison where original R tree has been used, the algorithm builds the spatial index by applying binary code operation in which computer runs more efficiently, and extended dynamic hash code for bit comparison. In GSHR-Tree, a new server is assigned to the network whenever a split of a full node is required. We describe a more flexible allocation protocol which copes with a temporary shortage of storage resources. It uses a distributed balanced binary spatial tree that scales with insertions to potentially any number of storage servers through splits of the overloaded ones. The application manipulates the GSHR-Tree structure from a node in the grid environment. The node addresses the tree through its image that the splits can make outdated. This may generate addressing errors, solved by the forwarding among the servers. In this paper, a spatial index data distribution algorithm that limits the number of servers has been proposed. We improve the storage utilization at the cost of additional messages. The structure of GSHR-Tree is believed that the scheme of this grid spatial index should fit the needs of new applications using endlessly larger sets of spatial data. Our proposal constitutes a flexible storage allocation method for a distributed spatial index. The insertion policy can be tuned dynamically to cope with periods of storage shortage. In such cases storage balancing should be favored for better space utilization, at the price of extra message exchanges between servers. This structure makes a compromise in the updating of the duplicated index and the transformation of the spatial index data. Meeting the needs of the grid computing, GSHRTree has a flexible structure in order to satisfy new needs in the future. The GSHR-Tree provides the R-tree capabilities for large spatial datasets stored over interconnected servers. The analysis, including the experiments, confirmed the efficiency of our design choices. The scheme should fit the needs of new applications of spatial data, using endlessly larger datasets. Using the system response time of the parallel processing of spatial scope query algorithm as the performance evaluation factor, According to the result of the simulated the experiments, GSHR-Tree is performed to prove the reasonable design and the high performance of the indexing structure that the paper presented.

Determinants of the geographic distribution of Puumala virus and Lyme borreliosis infections in Belgium

PubMed Central

Linard, Catherine; Lamarque, Pénélope; Heyman, Paul; Ducoffre, Geneviève; Luyasu, Victor; Tersago, Katrien; Vanwambeke, Sophie O; Lambin, Eric F

2007-01-01

Background Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover and land use influence disease transmission by controlling both the spatial distribution of vectors or hosts, and the probability of contact with susceptible human populations. The objective of this study was to combine environmental and socio-economic factors to explain the spatial distribution of two emerging human diseases in Belgium, Puumala virus (PUUV) and Lyme borreliosis. Municipalities were taken as units of analysis. Results Negative binomial regressions including a correction for spatial endogeneity show that the spatial distribution of PUUV and Lyme borreliosis infections are associated with a combination of factors linked to the vector and host populations, to human behaviours, and to landscape attributes. Both diseases are associated with the presence of forests, which are the preferred habitat for vector or host populations. The PUUV infection risk is higher in remote forest areas, where the level of urbanisation is low, and among low-income populations. The Lyme borreliosis transmission risk is higher in mixed landscapes with forests and spatially dispersed houses, mostly in wealthy peri-urban areas. The spatial dependence resulting from a combination of endogenous and exogenous processes could be accounted for in the model on PUUV but not for Lyme borreliosis. Conclusion A large part of the spatial variation in disease risk can be explained by environmental and socio-economic factors. The two diseases not only are most prevalent in different regions but also affect different groups of people. Combining these two criteria may increase the efficiency of information campaigns through appropriate targeting. PMID:17474974

Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology.

PubMed

VoPham, Trang; Hart, Jaime E; Laden, Francine; Chiang, Yao-Yi

2018-04-17

Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to extract knowledge from spatial big data. In environmental epidemiology, exposure modeling is a commonly used approach to conduct exposure assessment to determine the distribution of exposures in study populations. geoAI technologies provide important advantages for exposure modeling in environmental epidemiology, including the ability to incorporate large amounts of big spatial and temporal data in a variety of formats; computational efficiency; flexibility in algorithms and workflows to accommodate relevant characteristics of spatial (environmental) processes including spatial nonstationarity; and scalability to model other environmental exposures across different geographic areas. The objectives of this commentary are to provide an overview of key concepts surrounding the evolving and interdisciplinary field of geoAI including spatial data science, machine learning, deep learning, and data mining; recent geoAI applications in research; and potential future directions for geoAI in environmental epidemiology.

A Quantitative Three-Dimensional Image Analysis Tool for Maximal Acquisition of Spatial Heterogeneity Data.

PubMed

Allenby, Mark C; Misener, Ruth; Panoskaltsis, Nicki; Mantalaris, Athanasios

2017-02-01

Three-dimensional (3D) imaging techniques provide spatial insight into environmental and cellular interactions and are implemented in various fields, including tissue engineering, but have been restricted by limited quantification tools that misrepresent or underutilize the cellular phenomena captured. This study develops image postprocessing algorithms pairing complex Euclidean metrics with Monte Carlo simulations to quantitatively assess cell and microenvironment spatial distributions while utilizing, for the first time, the entire 3D image captured. Although current methods only analyze a central fraction of presented confocal microscopy images, the proposed algorithms can utilize 210% more cells to calculate 3D spatial distributions that can span a 23-fold longer distance. These algorithms seek to leverage the high sample cost of 3D tissue imaging techniques by extracting maximal quantitative data throughout the captured image.

Neighborhood-Level and Spatial Characteristics Associated with Lay Naloxone Reversal Events and Opioid Overdose Deaths.

PubMed

Rowe, Christopher; Santos, Glenn-Milo; Vittinghoff, Eric; Wheeler, Eliza; Davidson, Peter; Coffin, Philip O

2016-02-01

There were over 23,000 opioid overdose deaths in the USA in 2013, and opioid-related mortality is increasing. Increased access to naloxone, particularly through community-based lay naloxone distribution, is a widely supported strategy to reduce opioid overdose mortality; however, little is known about the ecological and spatial patterns of the distribution and utilization of lay naloxone. This study aims to investigate the neighborhood-level correlates and spatial relationships of lay naloxone distribution and utilization and opioid overdose deaths. We determined the locations of lay naloxone distribution sites and the number of unintentional opioid overdose deaths and reported reversal events in San Francisco census tracts (n = 195) from 2010 to 2012. We used Wilcoxon rank-sum tests to compare census tract characteristics across tracts adjacent and not adjacent to distribution sites and multivariable negative binomial regression models to assess the association between census tract characteristics, including distance to the nearest site, and counts of opioid overdose deaths and naloxone reversal events. Three hundred forty-two opioid overdose deaths and 316 overdose reversals with valid location data were included in our analysis. Census tracts including or adjacent to a distribution site had higher income inequality, lower percentage black or African American residents, more drug arrests, higher population density, more overdose deaths, and more reversal events (all p < 0.05). In multivariable analysis, greater distance to the nearest distribution site (up to a distance of 4000 m) was associated with a lower count of Naloxone reversals [incidence rate ratio (IRR) = 0.51 per 500 m increase, 95% CI 0.39-0.67, p < 0.001] but was not significantly associated with opioid overdose deaths. These findings affirm that locating lay naloxone distribution sites in areas with high levels of substance use and overdose risk facilitates reversals of opioid overdoses in those immediate areas but suggests that alternative delivery methods may be necessary to reach individuals in other areas with less concentrated risk.

Tactile mapping system: a novel imaging technology for surface topography and elasticity of tissues or organs.

PubMed

Oie, Tomonori; Suzuki, Hisato; Fukuda, Toru; Murayama, Yoshinobu; Omata, Sadao; Kanda, Keiichi; Nakayama, Yasuhide

2009-11-01

: We demonstrated that the tactile mapping system (TMS) has a high degree of spatial precision in the distribution mapping of surface elasticity of tissues or organs. : Samples used were a circumferential section of a small-caliber porcine artery (diameter: ∼3 mm) and an elasticity test pattern with a line and space configuration for the distribution mapping of elasticity, prepared by regional micropatterning of a 14-μm thick gelatin hydrogel coating on a polyurethane sheet. Surface topography and elasticity in normal saline were simultaneously investigated by TMS using a probe with a diameter of 5 or 12 μm, a spatial interval of 1 to 5 μm, and an indentation depth of 4 μm. : In the test pattern, a spatial resolution in TMS of <5 μm was acquired under water with a minimal probe diameter and spatial interval of the probe movement. TMS was used for the distribution mapping of surface elasticity in a flat, circumferential section (thickness: ∼0.5 mm) of a porcine artery, and the concentric layers of the vascular wall, including the collagen-rich and elastin-rich layers, could be clearly differentiated in terms of surface elasticity at the spatial resolution of <2 μm. : TMS is a simple and inexpensive technique for the distribution mapping of the surface elasticity in vascular tissues at the spatial resolution <2 μm. TMS has the ability to analyze a complex structure of the tissue samples under normal saline.

Analytic score distributions for a spatially continuous tridirectional Monte Carol transport problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Booth, T.E.

1996-01-01

The interpretation of the statistical error estimates produced by Monte Carlo transport codes is still somewhat of an art. Empirically, there are variance reduction techniques whose error estimates are almost always reliable, and there are variance reduction techniques whose error estimates are often unreliable. Unreliable error estimates usually result from inadequate large-score sampling from the score distribution`s tail. Statisticians believe that more accurate confidence interval statements are possible if the general nature of the score distribution can be characterized. Here, the analytic score distribution for the exponential transform applied to a simple, spatially continuous Monte Carlo transport problem is provided.more » Anisotropic scattering and implicit capture are included in the theory. In large part, the analytic score distributions that are derived provide the basis for the ten new statistical quality checks in MCNP.« less

Experimental study on secondary electron emission characteristics of Cu

NASA Astrophysics Data System (ADS)

Liu, Shenghua; Liu, Yudong; Wang, Pengcheng; Liu, Weibin; Pei, Guoxi; Zeng, Lei; Sun, Xiaoyang

2018-02-01

Secondary electron emission (SEE) of a surface is the origin of the multipacting effect which could seriously deteriorate beam quality and even perturb the normal operation of particle accelerators. Experimental measurements on secondary electron yield (SEY) for different materials and coatings have been developed in many accelerator laboratories. In fact, the SEY is just one parameter of secondary electron emission characteristics which include spatial and energy distribution of emitted electrons. A novel experimental apparatus was set up in China Spallation Neutron Source, and an innovative method was applied to obtain the whole characteristics of SEE. Taking Cu as the sample, secondary electron yield, its dependence on beam injection angle, and the spatial and energy distribution of secondary electrons were achieved with this measurement device. The method for spatial distribution measurement was first proposed and verified experimentally. This contribution also tries to give all the experimental results a reasonable theoretical analysis and explanation.

Lung Cancer Pathological Image Analysis Using a Hidden Potts Model

PubMed Central

Li, Qianyun; Yi, Faliu; Wang, Tao; Xiao, Guanghua; Liang, Faming

2017-01-01

Nowadays, many biological data are acquired via images. In this article, we study the pathological images scanned from 205 patients with lung cancer with the goal to find out the relationship between the survival time and the spatial distribution of different types of cells, including lymphocyte, stroma, and tumor cells. Toward this goal, we model the spatial distribution of different types of cells using a modified Potts model for which the parameters represent interactions between different types of cells and estimate the parameters of the Potts model using the double Metropolis-Hastings algorithm. The double Metropolis-Hastings algorithm allows us to simulate samples approximately from a distribution with an intractable normalizing constant. Our numerical results indicate that the spatial interaction between the lymphocyte and tumor cells is significantly associated with the patient’s survival time, and it can be used together with the cell count information to predict the survival of the patients. PMID:28615918

Comparison of different interpolation methods for spatial distribution of soil organic carbon and some soil properties in the Black Sea backward region of Turkey

NASA Astrophysics Data System (ADS)

Göl, Ceyhun; Bulut, Sinan; Bolat, Ferhat

2017-10-01

The purpose of this research is to compare the spatial variability of soil organic carbon (SOC) in four adjacent land uses including the cultivated area, the grassland area, the plantation area and the natural forest area in the semi - arid region of Black Sea backward region of Turkey. Some of the soil properties, including total nitrogen, SOC, soil organic matter, and bulk density were measured on a grid with a 50 m sampling distance on the top soil (0-15 cm depth). Accordingly, a total of 120 samples were taken from the four adjacent land uses. Data was analyzed using geostatistical methods. The methods used were: Block kriging (BK), co - kriging (CK) with organic matter, total nitrogen and bulk density as auxiliary variables and inverse distance weighting (IDW) methods with the power of 1, 2 and 4. The methods were compared using a performance criteria that included root mean square error (RMSE), mean absolute error (MAE) and the coefficient of correlation (r). The one - way ANOVA test showed that differences between the natural (0.6653 ± 0.2901) - plantation forest (0.7109 ± 0.2729) areas and the grassland (1.3964 ± 0.6828) - cultivated areas (1.5851 ± 0.5541) were statistically significant at 0.05 level (F = 28.462). The best model for describing spatially variation of SOC was CK with the lowest error criteria (RMSE = 0.3342, MAE = 0.2292) and the highest coefficient of correlation (r = 0.84). The spatial structure of SOC could be well described by the spherical model. The nugget effect indicated that SOC was moderately dependent on the study area. The error distributions of the model showed that the improved model was unbiased in predicting the spatial distribution of SOC. This study's results revealed that an explanatory variable linked SOC increased success of spatial interpolation methods. In subsequent studies, this case should be taken into account for reaching more accurate outputs.

Pickup Ion Velocity Distributions at Titan: Effects of Spatial Gradients

NASA Technical Reports Server (NTRS)

Hartle, R. E.; Sittler, E. C.

2004-01-01

The principle source of pickup ions at Titan is its neutral exosphere, extending well above the ionopause into the magnetosphere of Saturn or the solar wind, depending on the moon's orbital position. Thermal and nonthermal processes in the thermosphere generate the distribution of neutral atoms and molecules in the exosphere. The combination of these processes and the range of mass numbers, 1 to over 28, contribute to an exospheric source structure that produces pickup ions with gyroradii that are much larger or smaller than the corresponding scale heights of their neutral sources. The resulting phase space distributions are dependent on the spatial structure of the exosphere as well as that of the magnetic field and background plasma. When the pickup ion gyroradius is less than the source gas scale height, the pickup ion velocity distribution is characterized by a sharp cutoff near the maximum speed, which is twice that of the ambient plasma times the sine of the angle between the magnetic field and the flow velocity. This was the case for pickup H(sup +) ions identified during the Voyager 1 flyby. In contrast, as the gyroradius becomes much larger than the scale height, the peak of the velocity distribution in the source region recedes from the maximum speed. Iri addition, the amplitude of the distribution near the maximum speed decreases. These more beam like distributions of heavy ions were not observed from Voyager 1 , but should be observable by more sensitive instruments on future spacecraft, including Cassini. The finite gyroradius effects in the pickup ion velocity distributions are studied by including in the analysis the possible range of spatial structures in the neutral exosphere and background plasma.

Canopies to Continents: What spatial scales are needed to represent landcover distributions in earth system models?

NASA Astrophysics Data System (ADS)

Guenther, A. B.; Duhl, T.

2011-12-01

Increasing computational resources have enabled a steady improvement in the spatial resolution used for earth system models. Land surface models and landcover distributions have kept ahead by providing higher spatial resolution than typically used in these models. Satellite observations have played a major role in providing high resolution landcover distributions over large regions or the entire earth surface but ground observations are needed to calibrate these data and provide accurate inputs for models. As our ability to resolve individual landscape components improves, it is important to consider what scale is sufficient for providing inputs to earth system models. The required spatial scale is dependent on the processes being represented and the scientific questions being addressed. This presentation will describe the development a contiguous U.S. landcover database using high resolution imagery (1 to 1000 meters) and surface observations of species composition and other landcover characteristics. The database includes plant functional types and species composition and is suitable for driving land surface models (CLM and MEGAN) that predict land surface exchange of carbon, water, energy and biogenic reactive gases (e.g., isoprene, sesquiterpenes, and NO). We investigate the sensitivity of model results to landcover distributions with spatial scales ranging over six orders of magnitude (1 meter to 1000000 meters). The implications for predictions of regional climate and air quality will be discussed along with recommendations for regional and global earth system modeling.

Research on key technologies for data-interoperability-based metadata, data compression and encryption, and their application

NASA Astrophysics Data System (ADS)

Yu, Xu; Shao, Quanqin; Zhu, Yunhai; Deng, Yuejin; Yang, Haijun

2006-10-01

With the development of informationization and the separation between data management departments and application departments, spatial data sharing becomes one of the most important objectives for the spatial information infrastructure construction, and spatial metadata management system, data transmission security and data compression are the key technologies to realize spatial data sharing. This paper discusses the key technologies for metadata based on data interoperability, deeply researches the data compression algorithms such as adaptive Huffman algorithm, LZ77 and LZ78 algorithm, studies to apply digital signature technique to encrypt spatial data, which can not only identify the transmitter of spatial data, but also find timely whether the spatial data are sophisticated during the course of network transmission, and based on the analysis of symmetric encryption algorithms including 3DES,AES and asymmetric encryption algorithm - RAS, combining with HASH algorithm, presents a improved mix encryption method for spatial data. Digital signature technology and digital watermarking technology are also discussed. Then, a new solution of spatial data network distribution is put forward, which adopts three-layer architecture. Based on the framework, we give a spatial data network distribution system, which is efficient and safe, and also prove the feasibility and validity of the proposed solution.

A hierarchical model for estimating the spatial distribution and abundance of animals detected by continuous-time recorders

USGS Publications Warehouse

Dorazio, Robert; Karanth, K. Ullas

2017-01-01

MotivationSeveral spatial capture-recapture (SCR) models have been developed to estimate animal abundance by analyzing the detections of individuals in a spatial array of traps. Most of these models do not use the actual dates and times of detection, even though this information is readily available when using continuous-time recorders, such as microphones or motion-activated cameras. Instead most SCR models either partition the period of trap operation into a set of subjectively chosen discrete intervals and ignore multiple detections of the same individual within each interval, or they simply use the frequency of detections during the period of trap operation and ignore the observed times of detection. Both practices make inefficient use of potentially important information in the data.Model and data analysisWe developed a hierarchical SCR model to estimate the spatial distribution and abundance of animals detected with continuous-time recorders. Our model includes two kinds of point processes: a spatial process to specify the distribution of latent activity centers of individuals within the region of sampling and a temporal process to specify temporal patterns in the detections of individuals. We illustrated this SCR model by analyzing spatial and temporal patterns evident in the camera-trap detections of tigers living in and around the Nagarahole Tiger Reserve in India. We also conducted a simulation study to examine the performance of our model when analyzing data sets of greater complexity than the tiger data.BenefitsOur approach provides three important benefits: First, it exploits all of the information in SCR data obtained using continuous-time recorders. Second, it is sufficiently versatile to allow the effects of both space use and behavior of animals to be specified as functions of covariates that vary over space and time. Third, it allows both the spatial distribution and abundance of individuals to be estimated, effectively providing a species distribution model, even in cases where spatial covariates of abundance are unknown or unavailable. We illustrated these benefits in the analysis of our data, which allowed us to quantify differences between nocturnal and diurnal activities of tigers and to estimate their spatial distribution and abundance across the study area. Our continuous-time SCR model allows an analyst to specify many of the ecological processes thought to be involved in the distribution, movement, and behavior of animals detected in a spatial trapping array of continuous-time recorders. We plan to extend this model to estimate the population dynamics of animals detected during multiple years of SCR surveys.

Does scale matter? A systematic review of incorporating biological realism when predicting changes in species distributions.

PubMed

Record, Sydne; Strecker, Angela; Tuanmu, Mao-Ning; Beaudrot, Lydia; Zarnetske, Phoebe; Belmaker, Jonathan; Gerstner, Beth

2018-01-01

There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species' responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. We systematically reviewed SDM studies published from 2003-2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis.

Adaptive web sampling.

PubMed

Thompson, Steven K

2006-12-01

A flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values. The new designs have certain advantages compared with previously existing adaptive and link-tracing designs, including control over sample sizes and of the proportion of effort allocated to adaptive selections. Efficient inference involves averaging over sample paths consistent with the minimal sufficient statistic. A Markov chain resampling method makes the inference computationally feasible. The designs are evaluated in network and spatial settings using two empirical populations: a hidden human population at high risk for HIV/AIDS and an unevenly distributed bird population.

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions

PubMed Central

Wilson, Adam M.; Jetz, Walter

2016-01-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties. PMID:27031693

Time-dependent density functional theory (TD-DFT) coupled with reference interaction site model self-consistent field explicitly including spatial electron density distribution (RISM-SCF-SEDD)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yokogawa, D., E-mail: d.yokogawa@chem.nagoya-u.ac.jp; Institute of Transformative Bio-Molecules

2016-09-07

Theoretical approach to design bright bio-imaging molecules is one of the most progressing ones. However, because of the system size and computational accuracy, the number of theoretical studies is limited to our knowledge. To overcome the difficulties, we developed a new method based on reference interaction site model self-consistent field explicitly including spatial electron density distribution and time-dependent density functional theory. We applied it to the calculation of indole and 5-cyanoindole at ground and excited states in gas and solution phases. The changes in the optimized geometries were clearly explained with resonance structures and the Stokes shift was correctly reproduced.

Dynamics of Learning in Cultured Neuronal Networks with Antagonists of Glutamate Receptors

PubMed Central

Li, Yanling; Zhou, Wei; Li, Xiangning; Zeng, Shaoqun; Luo, Qingming

2007-01-01

Cognitive dysfunction may result from abnormality of ionotropic glutamate receptors. Although various forms of synaptic plasticity in learning that rely on altering of glutamate receptors have been considered, the evidence is insufficient from an informatics view. Dynamics could reflect neuroinformatics encoding, including temporal pattern encoding, spatial pattern encoding, and energy distribution. Discovering informatics encoding is fundamental and crucial to understanding the working principle of the neural system. In this article, we analyzed the dynamic characteristics of response activities during learning training in cultured hippocampal networks under normal and abnormal conditions of ionotropic glutamate receptors, respectively. The rate, which is one of the temporal configurations, was decreased markedly by inhibition of α-amino-3-hydroxy-5-methylisoxazole-4-proprionic acid (AMPA) receptors. Moreover, the energy distribution in different characteristic frequencies was changed markedly by inhibition of AMPA receptors. Spatial configurations, including regularization, correlation, and synchrony, were changed significantly by inhibition of N-methyl-d-aspartate receptors. These results suggest that temporal pattern encoding and energy distribution of response activities in cultured hippocampal neuronal networks during learning training are modulated by AMPA receptors, whereas spatial pattern encoding of response activities is modulated by N-methyl-d-aspartate receptors. PMID:17766359

Spatiospectral Analysis of Accelerated Protons from Sub-Micron Liquid Crystal Films

NASA Astrophysics Data System (ADS)

Willis, Christopher; Poole, Patrick; Cochran, Ginevra; van Woerkom, Linn; Schumacher, Douglass

2017-10-01

Recent studies on ion acceleration have trended towards ultra-thin (<1 μm) targets due to improved ion energies and yields from these targets. As discussed here, ultra-thin targets may exhibit unusual spatial distributions in the accelerated ions, such that ion spectrometer data may not be representative of the overall distribution. More complete characterization of the ions requires spectral unfolding of radiochromic film (RCF) data, yielding spatially dependent spectra. Spatiospectral data will be presented from several experiments using sub-micron liquid crystal film targets at the Scarlet (OSU), Texas Petawatt (UT, Austin) and PHELIX (GSI, Darmstadt) laser facilities, including evidence of >75 MeV protons from 300 nm films at PHELIX. Analysis of RCF data is supported by Monte-Carlo modeling of RCF response to ions and electrons using FLUKA. Trends in the resulting ion distributions will be discussed including spatially varying slope temperature and observation of annular ring features at moderate ion energies on many shots. This material is based upon work supported by the AFOSR under award FA9550-14-1-0085, by the DARPA PULSE program through a Grant from AMRDEC, and by the NNSA under contract DE-NA0003107.

A new cryptic species and review of the east-Andean leaf chafer genus Mesomerodon Ohaus, 1905 (Coleoptera, Scarabaeidae, Rutelinae).

PubMed

Seidel, Matthias; Jameson, Mary L; Stone, Rachel L

2017-01-01

The Neotropical scarab beetle genus Mesomerodon Ohaus (Scarabaeidae: Rutelinae: Rutelini) is distributed in the western (lowland) Amazonian region from Colombia to Bolivia. Based on our research, the genus includes three species including a new cryptic species from Ecuador. We use niche modeling to predict potential suitable habitat and identify environmental factors associated with the distribution of Mesomerodon species. We characterize the genus, provide a key to species, diagnose each species, describe a new species, provide spatial and temporal distributions, and discuss distributions of the species in relation to Amazonian landscape biodiversity.

Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks

PubMed Central

Lam, William H. K.; Li, Qingquan

2017-01-01

Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks. PMID:29210978

Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks.

PubMed

Shi, Chaoyang; Chen, Bi Yu; Lam, William H K; Li, Qingquan

2017-12-06

Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks.

Investigating distribution pattern of species in a warm-temperate conifer-broadleaved-mixed forest in China for sustainably utilizing forest and soils.

PubMed

Song, Houjuan; Xu, Yudan; Hao, Jing; Zhao, Bingqing; Guo, Donggang; Shao, Hongbo

2017-02-01

The maintaining mechanisms and potential ecological processes of species diversity in warm temperate- conifer-broadleaved-mixed forest are far from clear understanding. In this paper, the relative neighborhood density Ω was used to analyze the spatial distribution patterns of 34 species with ≥11 individuals in a warm- temperate-conifer-broadleaved-mixed forest, northern China. Then we used canonical correspondence analysis (CCA) and Torus-translation test (TTT) to explain the distribution of observed species. Our results show that aggregated distribution is the dominant pattern in warm-temperate natural forest and four species regular distribution at the spatial scale >30m. The aggregated percentage and intensity decline with spatial scale, abundance and size classes increasing. Rare species are aggregated more than intermediate and abundant species. These results prove sufficiently the effects existence of scale separation, self-thinning and Janzen-Connell hypothesis. In addition, functional traits (dispersal modes and shade tolerance) also have a significant influence on distribution of species. The results of CCA confirm that slope and convexity are the most important factors affecting the distribution of tree species distribution, elevation and slope of shrub species though the combination of topographic variables only explained 1% of distribution of tree species and 2% of shrub species. Most species don't have habitat preference; however 47.1% (16/34) species including absolutely dominant tree (Pinus tabulaeformis and Quercus wutaishanica) and shrub species (Rosa xanthina) and most other species with important value in the front, are strongly positively or negatively associated with at least one habitat. The valley and ridge are most distinct habitat with association of 12 species in the plot. However, high elevation slope with 257 quadrats is the most extensive habitat with only four species. Therefore, there is obvious evidence that habitat heterogeneity play an important role on shaping spatial distribution of species in warm temperate forest. Our research results provide significant evidence that dispersal limitation and habitat heterogeneity have a contribution jointly to regulating the spatial distribution pattern of species in warm-temperate-forest in China. Copyright © 2016 Elsevier B.V. All rights reserved.

Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; Mai, Juliane; Mendiguren, Gorka; Koch, Julian; Samaniego, Luis; Stisen, Simon

2018-02-01

Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex evolution optimiser. The calibration results reveal a limited trade-off between streamflow dynamics and spatial patterns illustrating the benefit of combining separate observation types and objective functions. At the same time, the simulated spatial patterns of AET significantly improved when an objective function based on observed AET patterns and a novel spatial performance metric compared to traditional streamflow-only calibration were included. Since the overall water balance is usually a crucial goal in hydrologic modelling, spatial-pattern-oriented optimisation should always be accompanied by traditional discharge measurements. In such a multi-objective framework, the current study promotes the use of a novel bias-insensitive spatial pattern metric, which exploits the key information contained in the observed patterns while allowing the water balance to be informed by discharge observations.

Macular pigment optical density spatial distribution measured in a subject with oculocutaneous albinism.

PubMed

Putnam, Christopher M; Bland, Pauline J

2014-01-01

Previous studies of macular pigment optical density (MPOD) distribution in individuals with oculocutaneous albinism (OCA) have primarily used objective measurement techniques including fundus reflectometry and autofluorescence. We report here on a subject with OCA and their corresponding MPOD distribution assessed through heterochromatic flicker photometry (HFP). A subject with a history of OCA presented with an ocular history including strabismus surgery of the LE with persistent amblyopia and mild, latent nystagmus. Best corrected visual acuity was 20/25- RE and 20/40- LE. Spectral domain optical coherence tomography (SD-OCT) and fundus photography were also obtained. Evaluation of MPOD spatial distribution up to 8 degrees eccentricity from the fovea was performed using HFP. SD-OCT indicated a persistence of multiple inner retinal layers within the foveal region in the RE and LE including symmetric foveal thickening consistent with foveal hypoplasia. Fundus photography showed mild retinal pigmented epithelial (RPE) hypopigmentation and a poorly demarcated macula. OriginPro 9 was used to plot MPOD spatial distribution of the subject and a 33-subject sample. The OCA subject demonstrated a foveal MPOD of 0.10 with undetectable levels at 6 degrees eccentricity. The study sample showed a mean foveal MPOD of 0.34 and mean 6 degree eccentricity values of 0.03. Consistent with previous macular pigment (MP) studies of OCA, overall MPOD is reduced in our subject. Mild phenotypic expression of OCA with high functional visual acuity may represent a Henle fiber layer amenable to additional MP deposition. Further study of MP supplementation in OCA patients is warranted. Copyright © 2014 Spanish General Council of Optometry. Published by Elsevier Espana. All rights reserved.

Spatial arrangement and size distribution of normal faults, Buckskin detachment upper plate, Western Arizona

NASA Astrophysics Data System (ADS)

Laubach, S. E.; Hundley, T. H.; Hooker, J. N.; Marrett, R. A.

2018-03-01

Fault arrays typically include a wide range of fault sizes and those faults may be randomly located, clustered together, or regularly or periodically located in a rock volume. Here, we investigate size distribution and spatial arrangement of normal faults using rigorous size-scaling methods and normalized correlation count (NCC). Outcrop data from Miocene sedimentary rocks in the immediate upper plate of the regional Buckskin detachment-low angle normal-fault, have differing patterns of spatial arrangement as a function of displacement (offset). Using lower size-thresholds of 1, 0.1, 0.01, and 0.001 m, displacements range over 5 orders of magnitude and have power-law frequency distributions spanning ∼ four orders of magnitude from less than 0.001 m to more than 100 m, with exponents of -0.6 and -0.9. The largest faults with >1 m displacement have a shallower size-distribution slope and regular spacing of about 20 m. In contrast, smaller faults have steep size-distribution slopes and irregular spacing, with NCC plateau patterns indicating imposed clustering. Cluster widths are 15 m for the 0.1-m threshold, 14 m for 0.01-m, and 1 m for 0.001-m displacement threshold faults. Results demonstrate normalized correlation count effectively characterizes the spatial arrangement patterns of these faults. Our example from a high-strain fault pattern above a detachment is compatible with size and spatial organization that was influenced primarily by boundary conditions such as fault shape, mechanical unit thickness and internal stratigraphy on a range of scales rather than purely by interaction among faults during their propagation.

Modeling the Spatiotemporal Evolution of the Melanoma Tumor Microenvironment

NASA Astrophysics Data System (ADS)

Signoriello, Alexandra; Bosenberg, Marcus; Shattuck, Mark; O'Hern, Corey

The tumor microenvironment, which includes tumor cells, tumor-associated macrophages (TAM), cancer-associated fibroblasts, and endothelial cells, drives the formation and progression of melanoma tumors. Using quantitative analysis of in vivo confocal images of melanoma tumors in three spatial dimensions, we examine the physical properties of the melanoma tumor microenvironment, including the numbers of different cells types, cell size, and morphology. We also compute the nearest neighbor statistics and measure intermediate range spatial correlations between different cell types. We also calculate the step size distribution, mean-square displacement, and non-Gaussian parameter from the spatial trajectories of different cell types in the tumor microenvironment.

Spatial distribution of traffic in a cellular mobile data network

NASA Astrophysics Data System (ADS)

Linnartz, J. P. M. G.

1987-02-01

The use of integral transforms of the probability density function for the received power to analyze the relation between the spatial distributions of offered and throughout packet traffic in a mobile radio network with Rayleigh fading channels and ALOHA multiple access was assessed. A method to obtain the spatial distribution of throughput traffic from a prescribed spatial distribution of offered traffic is presented. Incoherent and coherent addition of interference signals is considered. The channel behavior for heavy traffic loads is studied. In both the incoherent and coherent case, the spatial distribution of offered traffic required to ensure a prescribed spatially uniform throughput is synthesized numerically.

Simulation of net infiltration and potential recharge using a distributed-parameter watershed model of the Death Valley region, Nevada and California

USGS Publications Warehouse

Hevesi, Joseph A.; Flint, Alan L.; Flint, Lorraine E.

2003-01-01

This report presents the development and application of the distributed-parameter watershed model, INFILv3, for estimating the temporal and spatial distribution of net infiltration and potential recharge in the Death Valley region, Nevada and California. The estimates of net infiltration quantify the downward drainage of water across the lower boundary of the root zone and are used to indicate potential recharge under variable climate conditions and drainage basin characteristics. Spatial variability in recharge in the Death Valley region likely is high owing to large differences in precipitation, potential evapotranspiration, bedrock permeability, soil thickness, vegetation characteristics, and contributions to recharge along active stream channels. The quantity and spatial distribution of recharge representing the effects of variable climatic conditions and drainage basin characteristics on recharge are needed to reduce uncertainty in modeling ground-water flow. The U.S. Geological Survey, in cooperation with the Department of Energy, developed a regional saturated-zone ground-water flow model of the Death Valley regional ground-water flow system to help evaluate the current hydrogeologic system and the potential effects of natural or human-induced changes. Although previous estimates of recharge have been made for most areas of the Death Valley region, including the area defined by the boundary of the Death Valley regional ground-water flow system, the uncertainty of these estimates is high, and the spatial and temporal variability of the recharge in these basins has not been quantified. To estimate the magnitude and distribution of potential recharge in response to variable climate and spatially varying drainage basin characteristics, the INFILv3 model uses a daily water-balance model of the root zone with a primarily deterministic representation of the processes controlling net infiltration and potential recharge. The daily water balance includes precipitation (as either rain or snow), snow accumulation, sublimation, snowmelt, infiltration into the root zone, evapotranspiration, drainage, water content change throughout the root-zone profile (represented as a 6-layered system), runoff (defined as excess rainfall and snowmelt) and surface water run-on (defined as runoff that is routed downstream), and net infiltration (simulated as drainage from the bottom root-zone layer). Potential evapotranspiration is simulated using an hourly solar radiation model to simulate daily net radiation, and daily evapotranspiration is simulated as an empirical function of root zone water content and potential evapotranspiration. The model uses daily climate records of precipitation and air temperature from a regionally distributed network of 132 climate stations and a spatially distributed representation of drainage basin characteristics defined by topography, geology, soils, and vegetation to simulate daily net infiltration at all locations, including stream channels with intermittent streamflow in response to runoff from rain and snowmelt. The temporal distribution of daily, monthly, and annual net infiltration can be used to evaluate the potential effect of future climatic conditions on potential recharge. The INFILv3 model inputs representing drainage basin characteristics were developed using a geographic information system (GIS) to define a set of spatially distributed input parameters uniquely assigned to each grid cell of the INFILv3 model grid. The model grid, which was defined by a digital elevation model (DEM) of the Death Valley region, consists of 1,252,418 model grid cells with a uniform grid cell dimension of 278.5 meters in the north-south and east-west directions. The elevation values from the DEM were used with monthly regression models developed from the daily climate data to estimate the spatial distribution of daily precipitation and air temperature. The elevation values were also used to simulate atmosp

One-loop gravitational wave spectrum in de Sitter spacetime

NASA Astrophysics Data System (ADS)

Fröb, Markus B.; Roura, Albert; Verdaguer, Enric

2012-08-01

The two-point function for tensor metric perturbations around de Sitter spacetime including one-loop corrections from massless conformally coupled scalar fields is calculated exactly. We work in the Poincaré patch (with spatially flat sections) and employ dimensional regularization for the renormalization process. Unlike previous studies we obtain the result for arbitrary time separations rather than just equal times. Moreover, in contrast to existing results for tensor perturbations, ours is manifestly invariant with respect to the subgroup of de Sitter isometries corresponding to a simultaneous time translation and rescaling of the spatial coordinates. Having selected the right initial state for the interacting theory via an appropriate iepsilon prescription is crucial for that. Finally, we show that although the two-point function is a well-defined spacetime distribution, the equal-time limit of its spatial Fourier transform is divergent. Therefore, contrary to the well-defined distribution for arbitrary time separations, the power spectrum is strictly speaking ill-defined when loop corrections are included.

Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands

PubMed Central

Baldwin, Robert F.; Leonard, Paul B.

2015-01-01

Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection. PMID:26465155

Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands.

PubMed

Baldwin, Robert F; Leonard, Paul B

2015-01-01

Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection.

A spatial approach to environmental risk assessment of PAH contamination.

PubMed

Bengtsson, Göran; Törneman, Niklas

2009-01-01

The extent of remediation of contaminated industrial sites depends on spatial heterogeneity of contaminant concentration and spatially explicit risk characterization. We used sequential Gaussian simulation (SGS) and indicator kriging (IK) to describe the spatial distribution of polycyclic aromatic hydrocarbons (PAHs), pH, electric conductivity, particle aggregate distribution, water holding capacity, and total organic carbon, and quantitative relations among them, in a creosote polluted soil in southern Sweden. The geostatistical analyses were combined with risk analyses, in which the total toxic equivalent concentration of the PAH mixture was calculated from the soil concentrations of individual PAHs and compared with ecotoxicological effect concentrations and regulatory threshold values in block sizes of 1.8 x 1.8 m. Most PAHs were spatially autocorrelated and appeared in several hot spots. The risk calculated by SGS was more confined to specific hot spot areas than the risk calculated by IK, and 40-50% of the site had PAH concentrations exceeding the threshold values with a probability of 80% and higher. The toxic equivalent concentration of the PAH mixture was dependent on the spatial distribution of organic carbon, showing the importance of assessing risk by a combination of measurements of PAH and organic carbon concentrations. Essentially, the same risk distribution pattern was maintained when Monte Carlo simulations were used for implementation of risk in larger (5 x 5 m), economically more feasible remediation blocks, but a smaller area became of great concern for remediation when the simulations included PAH partitioning to two separate sources, creosote and natural, of organic matter, rather than one general.

Spatial Distribution and Trends of Waterborne Diseases in Tashkent Province

PubMed Central

Subramanian, Veluswami Saravanan; Cho, Min Jung; Tan, Siwei Zoe; Fayzieva, Dilorom; Sebaly, Christian

2017-01-01

Introduction: The cumulative effect of limited investment in public water systems, inadequate public health infrastructure, and gaps in infectious disease prevention increased the incidence of waterborne diseases in Uzbekistan. The objectives of this study were: (1) to spatially analyze the distribution of the diseases in Tashkent Province, (2) to identify the intensity of spatial trends in the province, (3) to identify urban-rural characteristics of the disease distribution, and (4) to identify the differences in disease incidence between pediatric and adult populations of the province. Methods: Data on four major waterborne diseases and socio-demographics factors were collected in Tashkent Province from 2011 to 2014. Descriptive epidemiological methods and spatial-temporal methods were used to investigate the distribution and trends, and to identify waterborne diseases hotspots and vulnerable population groups in the province. Results: Hepatitis A and enterobiasis had a high incidence in most of Tashkent Province, with higher incidences in the eastern and western districts. Residents of rural areas, including children, were found to be more vulnerable to the waterborne diseases compared to other populations living in the province. Conclusions: This pilot study calls for more scientific investigations of waterborne diseases and their effect on public health in the region, which could facilitate targeted public health interventions in vulnerable regions of Uzbekistan. PMID:29138738

Spatial Distribution and Trends of Waterborne Diseases in Tashkent Province.

PubMed

Subramanian, Veluswami Saravanan; Cho, Min Jung; Tan, Siwei Zoe; Fayzieva, Dilorom; Sebaly, Christian

2017-01-01

The cumulative effect of limited investment in public water systems, inadequate public health infrastructure, and gaps in infectious disease prevention increased the incidence of waterborne diseases in Uzbekistan. The objectives of this study were: (1) to spatially analyze the distribution of the diseases in Tashkent Province, (2) to identify the intensity of spatial trends in the province, (3) to identify urban-rural characteristics of the disease distribution, and (4) to identify the differences in disease incidence between pediatric and adult populations of the province. Data on four major waterborne diseases and socio-demographics factors were collected in Tashkent Province from 2011 to 2014. Descriptive epidemiological methods and spatial-temporal methods were used to investigate the distribution and trends, and to identify waterborne diseases hotspots and vulnerable population groups in the province. Hepatitis A and enterobiasis had a high incidence in most of Tashkent Province, with higher incidences in the eastern and western districts. Residents of rural areas, including children, were found to be more vulnerable to the waterborne diseases compared to other populations living in the province. This pilot study calls for more scientific investigations of waterborne diseases and their effect on public health in the region, which could facilitate targeted public health interventions in vulnerable regions of Uzbekistan.

Generation of dark hollow femtosecond pulsed beam by phase-only liquid crystal spatial light modulator.

PubMed

Nie, Yongming; Ma, Haotong; Li, Xiujian; Hu, Wenhua; Yang, Jiankun

2011-07-20

Based on the refractive laser beam shaping system, the dark hollow femtosecond pulse beam shaping technique with a phase-only liquid crystal spatial light modulator (LC-SLM) is demonstrated. The phase distribution of the LC-SLM is derived by the energy conservation and constant optical path principle. The effects of the shaping system on the temporal properties, including spectral phase distribution and bandwidth of the femtosecond pulse, are analyzed in detail. Experimental results show that the hollow intensity distribution of the output pulsed beam can be maintained much at more than 1200 mm. The spectral phase of the pulse is changed, and the pulse width is expanded from 199 to 230 fs, which is caused by the spatial-temporal coupling effect. The coupling effect mainly depends on the phase-only LC-SLM itself, not on its loaded phase distribution. The experimental results indicate that the proposed shaping setup can generate a dark hollow femtosecond pulsed beam effectively, because the temporal Gaussian waveform is unchanged. © 2011 Optical Society of America

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.

The effect of the electric wind on the spatial distribution of chemical species in the positive corona discharge

NASA Astrophysics Data System (ADS)

Yanallah, K.; Pontiga, F.; Bouazza, M. R.; Chen, J. H.

2017-08-01

The electrohydrodynamic air flow generated by a positive corona discharge, and its effect on the spatial distribution of chemical species within a wire-plate corona reactor, have been numerically simulated. The computational model is based on the solutions of the Navier-Stokes equation and the continuity equation of each chemical species generated by the electrical discharge. A simplified analytical expression of the electric force density, which only requires the current density as the input parameter, has been used in the Navier-Stokes equation to obtain the velocity field. For the solution of the continuity equations, a plasma chemistry model that includes the most important reactions between electrons, atoms and molecules in air has been used. Similar to the electric force, the electron density distribution has been approximated by using a semi-analytical expression appropriate for the electrode geometry. The results of the study show that the spatial distribution of chemical species can be very different, and depends on the interplay between the electrohydrodynamic flow, the chemical kinetics of the species and its characteristic lifetime.

Spatial modelling of disease using data- and knowledge-driven approaches.

PubMed

Stevens, Kim B; Pfeiffer, Dirk U

2011-09-01

The purpose of spatial modelling in animal and public health is three-fold: describing existing spatial patterns of risk, attempting to understand the biological mechanisms that lead to disease occurrence and predicting what will happen in the medium to long-term future (temporal prediction) or in different geographical areas (spatial prediction). Traditional methods for temporal and spatial predictions include general and generalized linear models (GLM), generalized additive models (GAM) and Bayesian estimation methods. However, such models require both disease presence and absence data which are not always easy to obtain. Novel spatial modelling methods such as maximum entropy (MAXENT) and the genetic algorithm for rule set production (GARP) require only disease presence data and have been used extensively in the fields of ecology and conservation, to model species distribution and habitat suitability. Other methods, such as multicriteria decision analysis (MCDA), use knowledge of the causal factors of disease occurrence to identify areas potentially suitable for disease. In addition to their less restrictive data requirements, some of these novel methods have been shown to outperform traditional statistical methods in predictive ability (Elith et al., 2006). This review paper provides details of some of these novel methods for mapping disease distribution, highlights their advantages and limitations, and identifies studies which have used the methods to model various aspects of disease distribution. Copyright © 2011. Published by Elsevier Ltd.

Soil moisture optimal sampling strategy for Sentinel 1 validation super-sites in Poland

NASA Astrophysics Data System (ADS)

Usowicz, Boguslaw; Lukowski, Mateusz; Marczewski, Wojciech; Lipiec, Jerzy; Usowicz, Jerzy; Rojek, Edyta; Slominska, Ewa; Slominski, Jan

2014-05-01

Soil moisture (SM) exhibits a high temporal and spatial variability that is dependent not only on the rainfall distribution, but also on the topography of the area, physical properties of soil and vegetation characteristics. Large variability does not allow on certain estimation of SM in the surface layer based on ground point measurements, especially in large spatial scales. Remote sensing measurements allow estimating the spatial distribution of SM in the surface layer on the Earth, better than point measurements, however they require validation. This study attempts to characterize the SM distribution by determining its spatial variability in relation to the number and location of ground point measurements. The strategy takes into account the gravimetric and TDR measurements with different sampling steps, abundance and distribution of measuring points on scales of arable field, wetland and commune (areas: 0.01, 1 and 140 km2 respectively), taking into account the different status of SM. Mean values of SM were lowly sensitive on changes in the number and arrangement of sampling, however parameters describing the dispersion responded in a more significant manner. Spatial analysis showed autocorrelations of the SM, which lengths depended on the number and the distribution of points within the adopted grids. Directional analysis revealed a differentiated anisotropy of SM for different grids and numbers of measuring points. It can therefore be concluded that both the number of samples, as well as their layout on the experimental area, were reflected in the parameters characterizing the SM distribution. This suggests the need of using at least two variants of sampling, differing in the number and positioning of the measurement points, wherein the number of them must be at least 20. This is due to the value of the standard error and range of spatial variability, which show little change with the increase in the number of samples above this figure. Gravimetric method gives a more varied distribution of SM than those derived from TDR measurements. It should be noted that reducing the number of samples in the measuring grid leads to flattening the distribution of SM from both methods and increasing the estimation error at the same time. Grid of sensors for permanent measurement points should include points that have similar distributions of SM in the vicinity. Results of the analysis including number, the maximum correlation ranges and the acceptable estimation error should be taken into account when choosing of the measurement points. Adoption or possible adjustment of the distribution of the measurement points should be verified by performing additional measuring campaigns during the dry and wet periods. Presented approach seems to be appropriate for creation of regional-scale test (super) sites, to validate products of satellites equipped with SAR (Synthetic Aperture Radar), operating in C-band, with spatial resolution suited to single field scale, as for example: ERS-1, ERS-2, Radarsat and Sentinel-1, which is going to be launched in next few months. The work was partially funded by the Government of Poland through an ESA Contract under the PECS ELBARA_PD project No. 4000107897/13/NL/KML.

Historical and ecological drivers of the spatial pattern of Chondrichthyes species richness in the Mediterranean Sea

PubMed Central

Serna-Quintero, José Miguel; Camiñas, Juan Antonio; Fernández, Ignacio de Loyola; Real, Raimundo; Macías, David

2017-01-01

Chondrichthyes, which include Elasmobranchii (sharks and batoids) and Holocephali (chimaeras), are a relatively small group in the Mediterranean Sea (89 species) playing a key role in the ecosystems where they are found. At present, many species of this group are threatened as a result of anthropogenic effects, including fishing activity. Knowledge of the spatial distribution of these species is of great importance to understand their ecological role and for the efficient management of their populations, particularly if affected by fisheries. This study aims to analyze the spatial patterns of the distribution of Chondrichthyes species richness in the Mediterranean Sea. Information provided by the studied countries was used to model geographical and ecological variables affecting the Chondrichthyes species richness. The species were distributed in 16 Operational Geographical Units (OGUs), derived from the Geographical Sub-Areas (GSA) adopted by the General Fisheries Commission of the Mediterranean Sea (GFCM). Regression analyses with the species richness as a target variable were adjusted with a set of environmental and geographical variables, being the model that links richness of Chondrichthyes species with distance to the Strait of Gibraltar and number of taxonomic families of bony fishes the one that best explains it. This suggests that both historical and ecological factors affect the current distribution of Chondrichthyes within the Mediterranean Sea. PMID:28406963

A model for the spatial distribution of snow water equivalent parameterized from the spatial variability of precipitation

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Weltzien, Ingunn H.

2016-09-01

Snow is an important and complicated element in hydrological modelling. The traditional catchment hydrological model with its many free calibration parameters, also in snow sub-models, is not a well-suited tool for predicting conditions for which it has not been calibrated. Such conditions include prediction in ungauged basins and assessing hydrological effects of climate change. In this study, a new model for the spatial distribution of snow water equivalent (SWE), parameterized solely from observed spatial variability of precipitation, is compared with the current snow distribution model used in the operational flood forecasting models in Norway. The former model uses a dynamic gamma distribution and is called Snow Distribution_Gamma, (SD_G), whereas the latter model has a fixed, calibrated coefficient of variation, which parameterizes a log-normal model for snow distribution and is called Snow Distribution_Log-Normal (SD_LN). The two models are implemented in the parameter parsimonious rainfall-runoff model Distance Distribution Dynamics (DDD), and their capability for predicting runoff, SWE and snow-covered area (SCA) is tested and compared for 71 Norwegian catchments. The calibration period is 1985-2000 and validation period is 2000-2014. Results show that SDG better simulates SCA when compared with MODIS satellite-derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" and giving spurious positive trends in SWE, typical for SD_LN, is prevented. The precision of runoff simulations using SDG is slightly inferior, with a reduction in Nash-Sutcliffe and Kling-Gupta efficiency criterion of 0.01, but it is shown that the high precision in runoff prediction using SD_LN is accompanied with erroneous simulations of SWE.

Spatial redistribution of radiation in flip-chip photodiodes based on InAsSbP/InAs double heterostructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zakgeim, A. L.; Il’inskaya, N. D.; Karandashev, S. A.

2017-02-15

The spatial distribution of equilibrium and nonequilibrium (including luminescent) IR (infrared) radiation in flip-chip photodiodes based on InAsSbP/InAs double heterostructures (λ{sub max} = 3.4 μm) is measured and analyzed; the structural features of the photodiodes, including the reflective properties of the ohmic contacts, are taken into account. Optical area enhancement due to multiple internal reflection in photodiodes with different geometric characteristics is estimated.

The National Map seamless digital elevation model specifications

USGS Publications Warehouse

Archuleta, Christy-Ann M.; Constance, Eric W.; Arundel, Samantha T.; Lowe, Amanda J.; Mantey, Kimberly S.; Phillips, Lori A.

2017-08-02

This specification documents the requirements and standards used to produce the seamless elevation layers for The National Map of the United States. Seamless elevation data are available for the conterminous United States, Hawaii, Alaska, and the U.S. territories, in three different resolutions—1/3-arc-second, 1-arc-second, and 2-arc-second. These specifications include requirements and standards information about source data requirements, spatial reference system, distribution tiling schemes, horizontal resolution, vertical accuracy, digital elevation model surface treatment, georeferencing, data source and tile dates, distribution and supporting file formats, void areas, metadata, spatial metadata, and quality assurance and control.

Multi-criteria decision analysis in conservation planning: Designing conservation area networks in San Diego County

NASA Astrophysics Data System (ADS)

MacDonald, Garrick Richard

To limit biodiversity loss caused by human activity, conservation planning must protect biodiversity while considering socio-economic cost criteria. This research aimed to determine the effects of socio-economic criteria and spatial configurations on the development of CANs for three species with different distribution patterns, while simultaneously attempting to address the uncertainty and sensitivity of CANs produced by ConsNet. The socio-economic factors and spatial criteria included the cost of land, population density, agricultural output value, area, average cluster area, number of clusters, shape, and perimeter. Three sensitive mammal species with different distribution patterns were selected and included the Bobcat, Ringtail, and a custom created mammal distribution. Forty problems and the corresponding number of CANs were formulated and computed by running each predicted presence species model with and without the four different socioeconomic threshold groups at two different resolutions. Thirty-two percent less area was conserved after considering multiple socio-economic constraints and spatial configurations in comparison to CANs that did not consider multiple socio-economic constraints and spatial configurations. Without including socio-economic costs, ConsNet's ALL_CELLS heuristic solution was the highest ranking CAN. After considering multiple socio-economic costs, the number one ranking CAN was no longer the ALL_CELLS heuristic solution, but a spatially different meta-heuristic solution. The effects of multiple constraints and objectives on the design of CANs with different distribution patterns did not vary significantly across the criteria. The CANs produced by ConsNet appeared to demonstrate some uncertainty surrounding particular criteria, but did not demonstrate substantial uncertainty across all criteria used to rank the CANs. Similarly, the range of socio-economic criteria thresholds did not have a substantial impact. ConsNet was very applicable to the research project, however, it did exhibit a few limitations. Both the advantages and disadvantages of ConsNet should be considered before using ConsNet for future conservation planning projects. The research project is an example of a large data scenario undertaken with a multiple criteria decision analysis (MCDA) approach.

Use of Anecdotal Occurrence Data in Species Distribution Models: An Example Based on the White-Nosed Coati (Nasua narica) in the American Southwest

PubMed Central

Frey, Jennifer K.; Lewis, Jeremy C.; Guy, Rachel K.; Stuart, James N.

2013-01-01

Simple Summary We evaluated the influence of occurrence records with different reliability on predicted distribution of a unique, rare mammal in the American Southwest, the white-nosed coati (Nasua narica). We concluded that occurrence datasets that include anecdotal records can be used to infer species distributions, providing such data are used only for easily-identifiable species and based on robust modeling methods such as maximum entropy. Use of a reliability rating system is critical for using anecdotal data. Abstract Species distributions are usually inferred from occurrence records. However, these records are prone to errors in spatial precision and reliability. Although influence of spatial errors has been fairly well studied, there is little information on impacts of poor reliability. Reliability of an occurrence record can be influenced by characteristics of the species, conditions during the observation, and observer’s knowledge. Some studies have advocated use of anecdotal data, while others have advocated more stringent evidentiary standards such as only accepting records verified by physical evidence, at least for rare or elusive species. Our goal was to evaluate the influence of occurrence records with different reliability on species distribution models (SDMs) of a unique mammal, the white-nosed coati (Nasua narica) in the American Southwest. We compared SDMs developed using maximum entropy analysis of combined bioclimatic and biophysical variables and based on seven subsets of occurrence records that varied in reliability and spatial precision. We found that the predicted distribution of the coati based on datasets that included anecdotal occurrence records were similar to those based on datasets that only included physical evidence. Coati distribution in the American Southwest was predicted to occur in southwestern New Mexico and southeastern Arizona and was defined primarily by evenness of climate and Madrean woodland and chaparral land-cover types. Coati distribution patterns in this region suggest a good model for understanding the biogeographic structure of range margins. We concluded that occurrence datasets that include anecdotal records can be used to infer species distributions, providing such data are used only for easily-identifiable species and based on robust modeling methods such as maximum entropy. Use of a reliability rating system is critical for using anecdotal data. PMID:26487405

Spatial patterns of distribution and abundance of Harrisia portoricensis, an endangered Caribbean cactus

Treesearch

J. Rojas-Sandoval; E. J. Melendez-Ackerman; NO-VALUE

2013-01-01

Aims The spatial distribution of biotic and abiotic factors may play a dominant role in determining the distribution and abundance of plants in arid and semiarid environments. In this study, we evaluated how spatial patterns of microhabitat variables and the degree of spatial dependence of these variables influence the distribution and abundance of the endangered...

A Big Spatial Data Processing Framework Applying to National Geographic Conditions Monitoring

NASA Astrophysics Data System (ADS)

Xiao, F.

2018-04-01

In this paper, a novel framework for spatial data processing is proposed, which apply to National Geographic Conditions Monitoring project of China. It includes 4 layers: spatial data storage, spatial RDDs, spatial operations, and spatial query language. The spatial data storage layer uses HDFS to store large size of spatial vector/raster data in the distributed cluster. The spatial RDDs are the abstract logical dataset of spatial data types, and can be transferred to the spark cluster to conduct spark transformations and actions. The spatial operations layer is a series of processing on spatial RDDs, such as range query, k nearest neighbor and spatial join. The spatial query language is a user-friendly interface which provide people not familiar with Spark with a comfortable way to operation the spatial operation. Compared with other spatial frameworks, it is highlighted that comprehensive technologies are referred for big spatial data processing. Extensive experiments on real datasets show that the framework achieves better performance than traditional process methods.

[Spatial distribution pattern of Chilo suppressalis analyzed by classical method and geostatistics].

PubMed

Yuan, Zheming; Fu, Wei; Li, Fangyi

2004-04-01

Two original samples of Chilo suppressalis and their grid, random and sequence samples were analyzed by classical method and geostatistics to characterize the spatial distribution pattern of C. suppressalis. The limitations of spatial distribution analysis with classical method, especially influenced by the original position of grid, were summarized rather completely. On the contrary, geostatistics characterized well the spatial distribution pattern, congregation intensity and spatial heterogeneity of C. suppressalis. According to geostatistics, the population was up to Poisson distribution in low density. As for higher density population, its distribution was up to aggregative, and the aggregation intensity and dependence range were 0.1056 and 193 cm, respectively. Spatial heterogeneity was also found in the higher density population. Its spatial correlativity in line direction was more closely than that in row direction, and the dependence ranges in line and row direction were 115 and 264 cm, respectively.

The relative roles of environment, history and local dispersal in controlling the distributions of common tree and shrub species in a tropical forest landscape, Panama

USGS Publications Warehouse

Svenning, J.-C.; Engelbrecht, B.M.J.; Kinner, D.A.; Kursar, T.A.; Stallard, R.F.; Wright, S.J.

2006-01-01

We used regression models and information-theoretic model selection to assess the relative importance of environment, local dispersal and historical contingency as controls of the distributions of 26 common plant species in tropical forest on Barro Colorado Island (BCI), Panama. We censused eighty-eight 0.09-ha plots scattered across the landscape. Environmental control, local dispersal and historical contingency were represented by environmental variables (soil moisture, slope, soil type, distance to shore, old-forest presence), a spatial autoregressive parameter (??), and four spatial trend variables, respectively. We built regression models, representing all combinations of the three hypotheses, for each species. The probability that the best model included the environmental variables, spatial trend variables and ?? averaged 33%, 64% and 50% across the study species, respectively. The environmental variables, spatial trend variables, ??, and a simple intercept model received the strongest support for 4, 15, 5 and 2 species, respectively. Comparing the model results to information on species traits showed that species with strong spatial trends produced few and heavy diaspores, while species with strong soil moisture relationships were particularly drought-sensitive. In conclusion, history and local dispersal appeared to be the dominant controls of the distributions of common plant species on BCI. Copyright ?? 2006 Cambridge University Press.

Spatial analysis to identify hotspots of prevalence of schizophrenia.

PubMed

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.

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

USGS Publications Warehouse

Bahn, V.; O'Connor, R.J.; Krohn, W.B.

2006-01-01

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.

SPATIAL DISTRIBUTION OF PAIR PRODUCTION OVER THE PULSAR POLAR CAP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belyaev, Mikhail A.; Parfrey, Kyle, E-mail: mbelyaev@berkeley.edu

2016-10-20

Using an analytic, axisymmetric approach that includes general relativity, coupled to a condition for pair production deduced from simulations, we derive general results about the spatial distribution of pair-producing field lines over the pulsar polar cap. In particular, we show that pair production on magnetic field lines operates over only a fraction of the polar cap for an aligned rotator for general magnetic field configurations, assuming the magnetic field varies spatially on a scale that is larger than the size of the polar cap. We compare our result to force-free simulations of a pulsar with a dipole surface field andmore » find excellent agreement. Our work has implications for first-principles simulations of pulsar magnetospheres and for explaining observations of pulsed radio and high-energy emission.« less

Spatial and temporal structure of typhoid outbreaks in Washington, D.C., 1906–1909: evaluating local clustering with the Gi* statistic

PubMed Central

Hinman, Sarah E; Blackburn, Jason K; Curtis, Andrew

2006-01-01

Background To better understand the distribution of typhoid outbreaks in Washington, D.C., the U.S. Public Health Service (PHS) conducted four investigations of typhoid fever. These studies included maps of cases reported between 1 May – 31 October 1906 – 1909. These data were entered into a GIS database and analyzed using Ripley's K-function followed by the Gi* statistic in yearly intervals to evaluate spatial clustering, the scale of clustering, and the temporal stability of these clusters. Results The Ripley's K-function indicated no global spatial autocorrelation. The Gi* statistic indicated clustering of typhoid at multiple scales across the four year time period, refuting the conclusions drawn in all four PHS reports concerning the distribution of cases. While the PHS reports suggested an even distribution of the disease, this study quantified both areas of localized disease clustering, as well as mobile larger regions of clustering. Thus, indicating both highly localized and periodic generalized sources of infection within the city. Conclusion The methodology applied in this study was useful for evaluating the spatial distribution and annual-level temporal patterns of typhoid outbreaks in Washington, D.C. from 1906 to 1909. While advanced spatial analyses of historical data sets must be interpreted with caution, this study does suggest that there is utility in these types of analyses and that they provide new insights into the urban patterns of typhoid outbreaks during the early part of the twentieth century. PMID:16566830

Spatial and temporal structure of typhoid outbreaks in Washington, D.C., 1906-1909: evaluating local clustering with the Gi* statistic.

PubMed

Hinman, Sarah E; Blackburn, Jason K; Curtis, Andrew

2006-03-27

To better understand the distribution of typhoid outbreaks in Washington, D.C., the U.S. Public Health Service (PHS) conducted four investigations of typhoid fever. These studies included maps of cases reported between 1 May - 31 October 1906 - 1909. These data were entered into a GIS database and analyzed using Ripley's K-function followed by the Gi* statistic in yearly intervals to evaluate spatial clustering, the scale of clustering, and the temporal stability of these clusters. The Ripley's K-function indicated no global spatial autocorrelation. The Gi* statistic indicated clustering of typhoid at multiple scales across the four year time period, refuting the conclusions drawn in all four PHS reports concerning the distribution of cases. While the PHS reports suggested an even distribution of the disease, this study quantified both areas of localized disease clustering, as well as mobile larger regions of clustering. Thus, indicating both highly localized and periodic generalized sources of infection within the city. The methodology applied in this study was useful for evaluating the spatial distribution and annual-level temporal patterns of typhoid outbreaks in Washington, D.C. from 1906 to 1909. While advanced spatial analyses of historical data sets must be interpreted with caution, this study does suggest that there is utility in these types of analyses and that they provide new insights into the urban patterns of typhoid outbreaks during the early part of the twentieth century.

A Geospatial Information Grid Framework for Geological Survey.

PubMed

Wu, Liang; Xue, Lei; Li, Chaoling; Lv, Xia; Chen, Zhanlong; Guo, Mingqiang; Xie, Zhong

2015-01-01

The use of digital information in geological fields is becoming very important. Thus, informatization in geological surveys should not stagnate as a result of the level of data accumulation. The integration and sharing of distributed, multi-source, heterogeneous geological information is an open problem in geological domains. Applications and services use geological spatial data with many features, including being cross-region and cross-domain and requiring real-time updating. As a result of these features, desktop and web-based geographic information systems (GISs) experience difficulties in meeting the demand for geological spatial information. To facilitate the real-time sharing of data and services in distributed environments, a GIS platform that is open, integrative, reconfigurable, reusable and elastic would represent an indispensable tool. The purpose of this paper is to develop a geological cloud-computing platform for integrating and sharing geological information based on a cloud architecture. Thus, the geological cloud-computing platform defines geological ontology semantics; designs a standard geological information framework and a standard resource integration model; builds a peer-to-peer node management mechanism; achieves the description, organization, discovery, computing and integration of the distributed resources; and provides the distributed spatial meta service, the spatial information catalog service, the multi-mode geological data service and the spatial data interoperation service. The geological survey information cloud-computing platform has been implemented, and based on the platform, some geological data services and geological processing services were developed. Furthermore, an iron mine resource forecast and an evaluation service is introduced in this paper.

A Geospatial Information Grid Framework for Geological Survey

PubMed Central

Wu, Liang; Xue, Lei; Li, Chaoling; Lv, Xia; Chen, Zhanlong; Guo, Mingqiang; Xie, Zhong

2015-01-01

The use of digital information in geological fields is becoming very important. Thus, informatization in geological surveys should not stagnate as a result of the level of data accumulation. The integration and sharing of distributed, multi-source, heterogeneous geological information is an open problem in geological domains. Applications and services use geological spatial data with many features, including being cross-region and cross-domain and requiring real-time updating. As a result of these features, desktop and web-based geographic information systems (GISs) experience difficulties in meeting the demand for geological spatial information. To facilitate the real-time sharing of data and services in distributed environments, a GIS platform that is open, integrative, reconfigurable, reusable and elastic would represent an indispensable tool. The purpose of this paper is to develop a geological cloud-computing platform for integrating and sharing geological information based on a cloud architecture. Thus, the geological cloud-computing platform defines geological ontology semantics; designs a standard geological information framework and a standard resource integration model; builds a peer-to-peer node management mechanism; achieves the description, organization, discovery, computing and integration of the distributed resources; and provides the distributed spatial meta service, the spatial information catalog service, the multi-mode geological data service and the spatial data interoperation service. The geological survey information cloud-computing platform has been implemented, and based on the platform, some geological data services and geological processing services were developed. Furthermore, an iron mine resource forecast and an evaluation service is introduced in this paper. PMID:26710255

Spatial distribution of protons at high and low altitudes in the radiation belts. Comparison of theory and experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Panasyuk, M.I.; Reizman, S.Y.; Sosnovets, E.N.

1986-05-01

A comparative analysis of experimental data on the spatial distributions of protons with energies (E) greater than 0.1 MeV at high and low latitudes, which were obtained on the Molniya-1, Kosmos-900, Elektron, and 1964-45A satellites, is carried out. As a result of the comparison of the experimental data relating to the measurements of protons with E - 0.2 MeV with the calculation including radial drift of particles under the action of electric and magnetic field fluctuations, it is shown that radial diffusion with a diffusion coefficient independent of geomagnetic latitude is the primary mechanism shaping the spatial distributions of protonsmore » at geomagnetic latitudes up to ..lambda.. approx. = 40/sup 0/. The results of the experiments and the calculations agree under the assumption of both magnetic and electric diffusion, but the latter case requires the inclusion of the model of a spatially inhomogeneous convection electric field. At ..lambda.. greater than or equal to 50/sup 0/ pitchangle scattering makes the primary contribution to the shaping of the spatial structure of the protons at low altitudes. A value of 2 less than or equal to n less than or equal to 4 is obtained for the exponent of the slope of the radial distribution of cold electrons N /sub e/ (r)..cap alpha.. /sup -n/ at 2 less than or equal to L less than or equal to 4.« less

Spatial Distribution and Conservation of Speckled Hind and Warsaw Grouper in the Atlantic Ocean off the Southeastern U.S.

PubMed Central

Farmer, Nicholas A.; Karnauskas, Mandy

2013-01-01

There is broad interest in the development of efficient marine protected areas (MPAs) to reduce bycatch and end overfishing of speckled hind (Epinephelus drummondhayi) and warsaw grouper (Hyporthodus nigritus) in the Atlantic Ocean off the southeastern U.S. We assimilated decades of data from many fishery-dependent, fishery-independent, and anecdotal sources to describe the spatial distribution of these data limited stocks. A spatial classification model was developed to categorize depth-grids based on the distribution of speckled hind and warsaw grouper point observations and identified benthic habitats. Logistic regression analysis was used to develop a quantitative model to predict the spatial distribution of speckled hind and warsaw grouper as a function of depth, latitude, and habitat. Models, controlling for sampling gear effects, were selected based on AIC and 10-fold cross validation. The best-fitting model for warsaw grouper included latitude and depth to explain 10.8% of the variability in probability of detection, with a false prediction rate of 28–33%. The best-fitting model for speckled hind, per cross-validation, included latitude and depth to explain 36.8% of the variability in probability of detection, with a false prediction rate of 25–27%. The best-fitting speckled hind model, per AIC, also included habitat, but had false prediction rates up to 36%. Speckled hind and warsaw grouper habitats followed a shelf-edge hardbottom ridge from North Carolina to southeast Florida, with speckled hind more common to the north and warsaw grouper more common to the south. The proportion of habitat classifications and model-estimated stock contained within established and proposed MPAs was computed. Existing MPAs covered 10% of probable shelf-edge habitats for speckled hind and warsaw grouper, protecting 3–8% of speckled hind and 8% of warsaw grouper stocks. Proposed MPAs could add 24% more probable shelf-edge habitat, and protect an additional 14–29% of speckled hind and 20% of warsaw grouper stocks. PMID:24260126

Search for quark contact interactions and extra spatial dimensions using dijet angular distributions in proton–proton collisions at $$\\sqrt s =$$ 8 TeV

DOE PAGES

Khachatryan, Vardan

2015-04-24

Our search is presented for quark contact interactions and extra spatial dimensions in proton–proton collisions at √s=8TeVusing dijet angular distributions. The search is based on a data set corresponding to an integrated luminosity of 19.7fb -1collected by the CMS detector at the CERN LHC. Dijet angular distributions are found to be in agreement with the perturbative QCD predictions that include electroweak corrections. Limits on the contact interaction scale from a variety of models at next-to-leading order in QCD corrections are obtained. A benchmark model in which only left-handed quarks participate is excluded up to a scale of 9.0 (11.7)TeV formore » destructive (constructive) interference at 95% confidence level. Finally, lower limits between 5.9 and 8.4TeV on the scale of virtual graviton exchange are extracted for the Arkani-Hamed–Dimopoulos–Dvali model of extra spatial dimensions.« less

An automated system for the study of ionospheric spatial structures

NASA Astrophysics Data System (ADS)

Belinskaya, I. V.; Boitman, O. N.; Vugmeister, B. O.; Vyborova, V. M.; Zakharov, V. N.; Laptev, V. A.; Mamchenko, M. S.; Potemkin, A. A.; Radionov, V. V.

The system is designed for the study of the vertical distribution of electron density and the parameters of medium-scale ionospheric irregularities over the sounding site as well as the reconstruction of the spatial distribution of electron density within the range of up to 300 km from the sounding location. The system comprises an active central station as well as passive companion stations. The central station is equipped with the digital ionosonde ``Basis'', the measuring-and-computing complex IVK-2, and the receiver-recorder PRK-3M. The companion stations are equipped with receivers-recorders PRK-3. The automated comlex software system includes 14 subsystems. Data transfer between them is effected using magnetic disk data sets. The system is operated in both ionogram mode and Doppler shift and angle-of-arrival mode. Using data obtained in these two modes, the reconstruction of the spatial distribution of electron density in the region is carried out. Reconstruction is checked for accuracy using data from companion stations.

A review on the sources and spatial-temporal distributions of Pb in Jiaozhou Bay

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Zhang, Jie; Wang, Ming; Zhu, Sixi; Wu, Yunjie

2017-12-01

This paper provided a review on the source, spatial-distribution, temporal variations of Pb in Jiaozhou Bay based on investigation of Pb in surface and waters in different seasons during 1979-1983. The source strengths of Pb sources in Jiaozhou Bay were showing increasing trends, and the pollution level of Pb in this bay was slight or moderate in the early stage of reform and opening-up. Pb contents in the marine bay were mainly determined by the strength and frequency of Pb inputs from human activities, and Pb could be moving from high content areas to low content areas in the ocean interior. Surface waters in the ocean was polluted by human activities, and bottom waters was polluted by means of vertical water’s effect. The process of spatial distribution of Pb in waters was including three steps, i.e., 1), Pb was transferring to surface waters in the bay, 2) Pb was transferring to surface waters, and 3) Pb was transferring to and accumulating in bottom waters.

Search for quark contact interactions and extra spatial dimensions using dijet angular distributions in proton-proton collisions at √{ s} = 8 TeV

NASA Astrophysics Data System (ADS)

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V.; Vinogradov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Ershov, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Obraztsov, S.; Perfilov, M.; Petrushanko, S.; Savrin, V.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Ekmedzic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Albajar, C.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Brochero Cifuentes, J. A.; Cabrillo, I. J.; Calderon, A.; Duarte Campderros, J.; Fernandez, M.; Gomez, G.; Graziano, A.; Lopez Virto, A.; Marco, J.; Marco, R.; Martinez Rivero, C.; Matorras, F.; Munoz Sanchez, F. J.; Piedra Gomez, J.; Rodrigo, T.; Rodríguez-Marrero, A. Y.; Ruiz-Jimeno, A.; Scodellaro, L.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Benaglia, A.; Bendavid, J.; Benhabib, L.; Benitez, J. F.; Bernet, C.; Bloch, P.; Bocci, A.; Bonato, A.; Bondu, O.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Colafranceschi, S.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; David, A.; De Guio, F.; De Roeck, A.; De Visscher, S.; Di Marco, E.; Dobson, M.; Dordevic, M.; Dorney, B.; Dupont-Sagorin, N.; Elliott-Peisert, A.; Eugster, J.; Franzoni, G.; Funk, W.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Glege, F.; Guida, R.; Gundacker, S.; Guthoff, M.; Hammer, J.; Hansen, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lourenço, C.; Magini, N.; Malgeri, L.; Mannelli, M.; Marrouche, J.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Musella, P.; Orsini, L.; Pape, L.; Perez, E.; Perrozzi, L.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Pimiä, M.; Piparo, D.; Plagge, M.; Racz, A.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Steggemann, J.; Stieger, B.; Stoye, M.; Takahashi, Y.; Treille, D.; Tsirou, A.; Veres, G. I.; Wardle, N.; Wöhri, H. K.; Wollny, H.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Buchmann, M. A.; Casal, B.; Chanon, N.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Hits, D.; Hoss, J.; Lustermann, W.; Mangano, B.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meister, D.; Mohr, N.; Nägeli, C.; Nessi-Tedaldi, F.; Pandolfi, F.; Pauss, F.; Peruzzi, M.; Quittnat, M.; Rebane, L.; Rossini, M.; Starodumov, A.; Takahashi, M.; Theofilatos, K.; Wallny, R.; Weber, H. A.; Amsler, C.; Canelli, M. F.; Chiochia, V.; De Cosa, A.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Millan Mejias, B.; Ngadiuba, J.; Robmann, P.; Ronga, F. J.; Taroni, S.; Verzetti, M.; Yang, Y.; Cardaci, M.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Grundler, U.; Hou, W.-S.; Kao, K. Y.; Lei, Y. J.; Liu, Y. F.; Lu, R.-S.; Majumder, D.; Petrakou, E.; Tzeng, Y. M.; Wilken, R.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Bakirci, M. N.; Cerci, S.; Dozen, C.; Dumanoglu, I.; Eskut, E.; Girgis, S.; Gokbulut, G.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, M.; Akin, I. V.; Bilin, B.; Bilmis, S.; Gamsizkan, H.; Isildak, B.; Karapinar, G.; Ocalan, K.; Sekmen, S.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Albayrak, E. A.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, T.; Cankocak, K.; Vardarlı, F. I.; Levchuk, L.; Sorokin, P.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Meng, Z.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Senkin, S.; Smith, V. J.; Williams, T.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Burton, D.; Colling, D.; Cripps, N.; Cutajar, M.; Dauncey, P.; Davies, G.; Della Negra, M.; Dunne, P.; Ferguson, W.; Fulcher, J.; Futyan, D.; Hall, G.; Iles, G.; Jarvis, M.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mathias, B.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Rogerson, S.; Rose, A.; Seez, C.; Sharp, P.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Martin, W.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Scarborough, T.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Lawson, P.; Richardson, C.; Rohlf, J.; St. John, J.; Sulak, L.; Alimena, J.; Berry, E.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Segala, M.; Sinthuprasith, T.; Speer, T.; Swanson, J.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Gardner, M.; Ko, W.; Lander, R.; Miceli, T.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Searle, M.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Rakness, G.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Rikova, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Luthra, A.; Malberti, M.; Olmedo Negrete, M.; Shrinivas, A.; Sumowidagdo, S.; Wimpenny, S.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Holzner, A.; Kelley, R.; Klein, D.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Palmer, C.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Welke, C.; Würthwein, F.; Yagil, A.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Danielson, T.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Incandela, J.; Justus, C.; Mccoll, N.; Richman, J.; Stuart, D.; To, W.; West, C.; Yoo, J.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; Iiyama, Y.; Paulini, M.; Russ, J.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Gaz, A.; Krohn, M.; Luiggi Lopez, E.; Nauenberg, U.; Smith, J. G.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Chaves, J.; Chu, J.; Dittmer, S.; Eggert, N.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Ryd, A.; Salvati, E.; Skinnari, L.; Sun, W.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Winstrom, L.; Wittich, P.; Winn, D.; Abdullin, S.; Albrow, M.; Anderson, J.; Apollinari, G.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gao, Y.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Hare, D.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Kaadze, K.; Klima, B.; Kreis, B.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Sharma, S.; Soha, A.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vidal, R.; Whitbeck, A.; Whitmore, J.; Yang, F.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carver, M.; Curry, D.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Field, R. D.; Fisher, M.; Furic, I. K.; Hugon, J.; Konigsberg, J.; Korytov, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rinkevicius, A.; Shchutska, L.; Snowball, M.; Sperka, D.; Yelton, J.; Zakaria, M.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Bazterra, V. E.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Kurt, P.; Moon, D. H.; O'Brien, C.; Silkworth, C.; Turner, P.; Varelas, N.; Bilki, B.; Clarida, W.; Dilsiz, K.; Duru, F.; Haytmyradov, M.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P., III; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Shrestha, S.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bauer, G.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Ma, T.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Stöckli, F.; Sumorok, K.; Velicanu, D.; Veverka, J.; Wyslouch, B.; Yang, M.; Zanetti, M.; Zhukova, V.; Dahmes, B.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Meier, F.; Snow, G. R.; Zvada, M.; Dolen, J.; Godshalk, A.; Iashvili, I.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Pearson, T.; Planer, M.; Ruchti, R.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Hunt, A.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; De Mattia, M.; Gutay, L.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Lopes Pegna, D.; Maroussov, V.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Yoo, H. D.; Zablocki, J.; Zheng, Y.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Michlin, B.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Khukhunaishvili, A.; Korjenevski, S.; Petrillo, G.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Salur, S.; Schnetzer, S.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Suarez, I.; Tatarinov, A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kovitanggoon, K.; Kunori, S.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wood, J.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Lazaridis, C.; Levine, A.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Sarangi, T.; Savin, A.; Smith, W. H.; Taylor, D.; Verwilligen, P.; Vuosalo, C.; Woods, N.

2015-06-01

A search is presented for quark contact interactions and extra spatial dimensions in proton-proton collisions at √{ s} = 8 TeV using dijet angular distributions. The search is based on a data set corresponding to an integrated luminosity of 19.7 fb-1 collected by the CMS detector at the CERN LHC. Dijet angular distributions are found to be in agreement with the perturbative QCD predictions that include electroweak corrections. Limits on the contact interaction scale from a variety of models at next-to-leading order in QCD corrections are obtained. A benchmark model in which only left-handed quarks participate is excluded up to a scale of 9.0 (11.7) TeV for destructive (constructive) interference at 95% confidence level. Lower limits between 5.9 and 8.4 TeV on the scale of virtual graviton exchange are extracted for the Arkani-Hamed-Dimopoulos-Dvali model of extra spatial dimensions.

Solving Large-scale Spatial Optimization Problems in Water Resources Management through Spatial Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Wang, J.; Cai, X.

2007-12-01

A water resources system can be defined as a large-scale spatial system, within which distributed ecological system interacts with the stream network and ground water system. Water resources management, the causative factors and hence the solutions to be developed have a significant spatial dimension. This motivates a modeling analysis of water resources management within a spatial analytical framework, where data is usually geo- referenced and in the form of a map. One of the important functions of Geographic information systems (GIS) is to identify spatial patterns of environmental variables. The role of spatial patterns in water resources management has been well established in the literature particularly regarding how to design better spatial patterns for satisfying the designated objectives of water resources management. Evolutionary algorithms (EA) have been demonstrated to be successful in solving complex optimization models for water resources management due to its flexibility to incorporate complex simulation models in the optimal search procedure. The idea of combining GIS and EA motivates the development and application of spatial evolutionary algorithms (SEA). SEA assimilates spatial information into EA, and even changes the representation and operators of EA. In an EA used for water resources management, the mathematical optimization model should be modified to account the spatial patterns; however, spatial patterns are usually implicit, and it is difficult to impose appropriate patterns to spatial data. Also it is difficult to express complex spatial patterns by explicit constraints included in the EA. The GIS can help identify the spatial linkages and correlations based on the spatial knowledge of the problem. These linkages are incorporated in the fitness function for the preference of the compatible vegetation distribution. Unlike a regular GA for spatial models, the SEA employs a special hierarchical hyper-population and spatial genetic operators to represent spatial variables in a more efficient way. The hyper-population consists of a set of populations, which correspond to the spatial distributions of the individual agents (organisms). Furthermore spatial crossover and mutation operators are designed in accordance with the tree representation and then applied to both organisms and populations. This study applies the SEA to a specific problem of water resources management- maximizing the riparian vegetation coverage in accordance with the distributed groundwater system in an arid region. The vegetation coverage is impacted greatly by the nonlinear feedbacks and interactions between vegetation and groundwater and the spatial variability of groundwater. The SEA is applied to search for an optimal vegetation configuration compatible to the groundwater flow. The results from this example demonstrate the effectiveness of the SEA. Extension of the algorithm for other water resources management problems is discussed.

Transport lattice models of heat transport in skin with spatially heterogeneous, temperature-dependent perfusion.

PubMed

Gowrishankar, T R; Stewart, Donald A; Martin, Gregory T; Weaver, James C

2004-11-17

Investigation of bioheat transfer problems requires the evaluation of temporal and spatial distributions of temperature. This class of problems has been traditionally addressed using the Pennes bioheat equation. Transport of heat by conduction, and by temperature-dependent, spatially heterogeneous blood perfusion is modeled here using a transport lattice approach. We represent heat transport processes by using a lattice that represents the Pennes bioheat equation in perfused tissues, and diffusion in nonperfused regions. The three layer skin model has a nonperfused viable epidermis, and deeper regions of dermis and subcutaneous tissue with perfusion that is constant or temperature-dependent. Two cases are considered: (1) surface contact heating and (2) spatially distributed heating. The model is relevant to the prediction of the transient and steady state temperature rise for different methods of power deposition within the skin. Accumulated thermal damage is estimated by using an Arrhenius type rate equation at locations where viable tissue temperature exceeds 42 degrees C. Prediction of spatial temperature distributions is also illustrated with a two-dimensional model of skin created from a histological image. The transport lattice approach was validated by comparison with an analytical solution for a slab with homogeneous thermal properties and spatially distributed uniform sink held at constant temperatures at the ends. For typical transcutaneous blood gas sensing conditions the estimated damage is small, even with prolonged skin contact to a 45 degrees C surface. Spatial heterogeneity in skin thermal properties leads to a non-uniform temperature distribution during a 10 GHz electromagnetic field exposure. A realistic two-dimensional model of the skin shows that tissue heterogeneity does not lead to a significant local temperature increase when heated by a hot wire tip. The heat transport system model of the skin was solved by exploiting the mathematical analogy between local thermal models and local electrical (charge transport) models, thereby allowing robust, circuit simulation software to obtain solutions to Kirchhoff's laws for the system model. Transport lattices allow systematic introduction of realistic geometry and spatially heterogeneous heat transport mechanisms. Local representations for both simple, passive functions and more complex local models can be easily and intuitively included into the system model of a tissue.

Hybrid fs/ps Coherent Anti-Stokes Raman Scattering for Multiparameter Measurements of Combustion and Nonequilibrium

NASA Astrophysics Data System (ADS)

Dedic, Chloe Elizabeth

Hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (fs/ps CARS) is developed for measuring internal energy distributions, species concentration, and pressure for highly dynamic gas-phase environments. Systems of interest include next-generation combustors, plasma-based manufacturing and plasma-assisted combustion, and high-speed aerodynamic flow. These challenging environments include spatial variations and fast dynamics that require the spatial and temporal resolution offered by hybrid fs/ps CARS. A novel dual-pump fs/ps CARS approach is developed to simultaneously excite pure-rotational and rovibrational Raman coherences for dynamic thermometry (300-2400 K) and detection of major combustion species. This approach was also used to measure single-shot vibrational and rotational energy distributions of the nonequilibrium environment of a dielectric barrier discharge plasma. Detailed spatial distributions and shot-to-shot fluctuations of rotational and vibrational temperatures spanning 325-450 K and 1200-5000 K were recorded across the plasma and surrounding flow, and are compared to plasma emission spectroscopy measurements. Dual-pump hybrid fs/ps CARS allows for concise, kHz-rate measurements of vibrational and rotational energy distributions or temperatures at equilibrium and nonequilibrium without nonresonant wave-mixing or molecular collisional interference. Additionally, a highly transient ns laser spark is explored using CARS to measure temperature and pressure behind the shock wave and temperature of the expanding plasma kernel. Vibrational energy distributions at the exit of a microscale gaseous detonation tube are presented. Theory required to model fs/ps CARS response, including nonthermal energy distributions, is presented. The impact of nonequilibrium on measurement accuracy is explored, and a coherent line-mixing model is validated with high-pressure measurements. Temperature and pressure sensitivity are investigated for multiple measurement configurations, and accuracy and precision is quantified as a function of signal-to-noise for the fs/ps CARS system.

Modeling spatially-varying landscape change points in species occurrence thresholds

USGS Publications Warehouse

Wagner, Tyler; Midway, Stephen R.

2014-01-01

Predicting species distributions at scales of regions to continents is often necessary, as large-scale phenomena influence the distributions of spatially structured populations. Land use and land cover are important large-scale drivers of species distributions, and landscapes are known to create species occurrence thresholds, where small changes in a landscape characteristic results in abrupt changes in occurrence. The value of the landscape characteristic at which this change occurs is referred to as a change point. We present a hierarchical Bayesian threshold model (HBTM) that allows for estimating spatially varying parameters, including change points. Our model also allows for modeling estimated parameters in an effort to understand large-scale drivers of variability in land use and land cover on species occurrence thresholds. We use range-wide detection/nondetection data for the eastern brook trout (Salvelinus fontinalis), a stream-dwelling salmonid, to illustrate our HBTM for estimating and modeling spatially varying threshold parameters in species occurrence. We parameterized the model for investigating thresholds in landscape predictor variables that are measured as proportions, and which are therefore restricted to values between 0 and 1. Our HBTM estimated spatially varying thresholds in brook trout occurrence for both the proportion agricultural and urban land uses. There was relatively little spatial variation in change point estimates, although there was spatial variability in the overall shape of the threshold response and associated uncertainty. In addition, regional mean stream water temperature was correlated to the change point parameters for the proportion of urban land use, with the change point value increasing with increasing mean stream water temperature. We present a framework for quantify macrosystem variability in spatially varying threshold model parameters in relation to important large-scale drivers such as land use and land cover. Although the model presented is a logistic HBTM, it can easily be extended to accommodate other statistical distributions for modeling species richness or abundance.

The Importance of Spatial Reasoning Skills in Undergraduate Geology Students and the Effect of Weekly Spatial Skill Trainings

NASA Astrophysics Data System (ADS)

Gold, Anne; Pendergast, Philip; Stempien, Jennifer; Ormand, Carol

2016-04-01

Spatial reasoning is a key skill for student success in STEM disciplines in general and for students in geosciences in particular. However, spatial reasoning is neither explicitly trained, nor evenly distributed, among students and by gender. This uneven playing field allows some students to perform geoscience tasks easily while others struggle. A lack of spatial reasoning skills has been shown to be a barrier to success in the geosciences, and for STEM disciplines in general. Addressing spatial abilities early in the college experience might therefore be effective in retaining students, especially females, in STEM disciplines. We have developed and implemented a toolkit for testing and training undergraduate student spatial reasoning skills in the classroom. In the academic year 2014/15, we studied the distribution of spatial abilities in more than 700 undergraduate Geology students from 4 introductory and 2 upper level courses. Following random assignment, four treatment groups received weekly online training and intermittent hands-on trainings in spatial thinking while four control groups only participated in a pre- and a posttest of spatial thinking skills. In this presentation we summarize our results and describe the distribution of spatial skills in undergraduate students enrolled in geology courses. We first discuss the factors that best account for differences in baseline spatial ability levels, including general intelligence (using standardized test scores as a proxy), major, video gaming, and other childhood play experiences, which help to explain the gender gap observed in most research. We found a statistically significant improvement of spatial thinking still with large effect sizes for the students who received the weekly trainings. Self-report data further shows that students improve their spatial thinking skills and report that their improved spatial thinking skills increase their performance in geoscience courses. We conclude by discussing the effects of the training modules on development of spatial skills, which helps to shed light on what types of interventions may be useful in leveling the playing field for students going into the geosciences and other STEM fields.

Spatiotemporal Distribution of Chinavia hilaris (Hemiptera: Pentatomidae) in Peanut-Cotton Farmscapes

PubMed Central

Tillman, P. Glynn; Cottrell, Ted E.

2015-01-01

The green stink bug, Chinavia hilaris (Say) (Hemiptera: Pentatomidae), is a pest of cotton in the southeastern United States, but little is known concerning its spatiotemporal distribution in agricultural farmscapes. Therefore, spatiotemporal distribution of C. hilaris in farmscapes where cotton fields adjoined peanut was examined weekly. Spatial patterns of C. hilaris counts were analyzed using SADIE (Spatial Analysis by Distance Indices) methodology. Interpolated maps of C. hilaris density were used to visualize abundance and distribution of C. hilaris in crops. For the six peanut-cotton farmscapes studied, the frequency of C. hilaris in cotton (94.8%) was significantly higher than in peanut (5.2%), and nymphs were rarely detected in peanut, indicating that peanut was not a source of C. hilaris into cotton. Significantly, aggregated spatial distributions were detected in cotton. Maps of local clustering indices depicted patches of C. hilaris in cotton, mainly at field edges including the peanut-to-cotton interface. Black cherry (Prunus serotina Ehrh.) and elderberry (Sambucus nigra subsp. canadensis [L.] R. Bolli) grew in habitats adjacent to crops, C. hilaris were captured in pheromone-baited stink bug traps in these habitats, and in most instances, C. hilaris were observed feeding on black cherry and elderberry in these habitats before colonization of cotton. Spatial distribution of C. hilaris in these farmscapes revealed that C. hilaris colonized cotton field edges near these two noncrop hosts. Altogether, these findings suggest that black cherry and elderberry were sources of C. hilaris into cotton. Factors affecting the spatiotemporal dynamics of C. hilaris in peanut-cotton farmscapes are discussed. PMID:26175464

Spatial disparity in the distribution of superfund sites in South Carolina: an ecological study.

PubMed

Burwell-Naney, Kristen; Zhang, Hongmei; Samantapudi, Ashok; Jiang, Chengsheng; Dalemarre, Laura; Rice, LaShanta; Williams, Edith; Wilson, Sacoby

2013-11-06

According to the US Environmental Protection Agency (EPA), Superfund is a federal government program implemented to clean up uncontrolled hazardous waste sites. Twenty-six sites in South Carolina (SC) have been included on the National Priorities List (NPL), which has serious human health and environmental implications. The purpose of this study was to assess spatial disparities in the distribution of Superfund sites in SC. The 2000 US census tract and block level data were used to generate population characteristics, which included race/ethnicity, socioeconomic status (SES), education, home ownership, and home built before 1950. Geographic Information Systems (GIS) were used to map Superfund facilities and develop choropleth maps based on the aforementioned sociodemographic variables. Spatial methods, including mean and median distance analysis, buffer analysis, and spatial approximation were employed to characterize burden disparities. Regression analysis was performed to assess the relationship between the number of Superfund facilities and population characteristics. Spatial coincidence results showed that of the 29.5% of Blacks living in SC, 55.9% live in Superfund host census tracts. Among all populations in SC living below poverty (14.2%), 57.2% were located in Superfund host census tracts. Buffer analyses results (0.5mi, 1.0mi, 5.0mi, 0.5km, 1.0km, and 5.0km) showed a higher percentage of Whites compared to Blacks hosting a Superfund facility. Conversely, a slightly higher percentage of Blacks hosted (30.2%) a Superfund facility than those not hosting (28.8%) while their White counterparts had more equivalent values (66.7% and 67.8%, respectively). Regression analyses in the reduced model (Adj. R2 = 0.038) only explained a small percentage of the variance. In addition, the mean distance for percent of Blacks in the 90th percentile for Superfund facilities was 0.48mi. Burden disparities exist in the distribution of Superfund facilities in SC at the block and census tract levels across varying levels of demographic composition for race/ethnicity and SES.

Spatial analysis of cities using Renyi entropy and fractal parameters

NASA Astrophysics Data System (ADS)

Chen, Yanguang; Feng, Jian

2017-12-01

The spatial distributions of cities fall into two groups: one is the simple distribution with characteristic scale (e.g. exponential distribution), and the other is the complex distribution without characteristic scale (e.g. power-law distribution). The latter belongs to scale-free distributions, which can be modeled with fractal geometry. However, fractal dimension is not suitable for the former distribution. In contrast, spatial entropy can be used to measure any types of urban distributions. This paper is devoted to generalizing multifractal parameters by means of dual relation between Euclidean and fractal geometries. The main method is mathematical derivation and empirical analysis, and the theoretical foundation is the discovery that the normalized fractal dimension is equal to the normalized entropy. Based on this finding, a set of useful spatial indexes termed dummy multifractal parameters are defined for geographical analysis. These indexes can be employed to describe both the simple distributions and complex distributions. The dummy multifractal indexes are applied to the population density distribution of Hangzhou city, China. The calculation results reveal the feature of spatio-temporal evolution of Hangzhou's urban morphology. This study indicates that fractal dimension and spatial entropy can be combined to produce a new methodology for spatial analysis of city development.

The Canadian Hydrological Model (CHM): A multi-scale, variable-complexity hydrological model for cold regions

NASA Astrophysics Data System (ADS)

Marsh, C.; Pomeroy, J. W.; Wheater, H. S.

2016-12-01

There is a need for hydrological land surface schemes that can link to atmospheric models, provide hydrological prediction at multiple scales and guide the development of multiple objective water predictive systems. Distributed raster-based models suffer from an overrepresentation of topography, leading to wasted computational effort that increases uncertainty due to greater numbers of parameters and initial conditions. The Canadian Hydrological Model (CHM) is a modular, multiphysics, spatially distributed modelling framework designed for representing hydrological processes, including those that operate in cold-regions. Unstructured meshes permit variable spatial resolution, allowing coarse resolutions at low spatial variability and fine resolutions as required. Model uncertainty is reduced by lessening the necessary computational elements relative to high-resolution rasters. CHM uses a novel multi-objective approach for unstructured triangular mesh generation that fulfills hydrologically important constraints (e.g., basin boundaries, water bodies, soil classification, land cover, elevation, and slope/aspect). This provides an efficient spatial representation of parameters and initial conditions, as well as well-formed and well-graded triangles that are suitable for numerical discretization. CHM uses high-quality open source libraries and high performance computing paradigms to provide a framework that allows for integrating current state-of-the-art process algorithms. The impact of changes to model structure, including individual algorithms, parameters, initial conditions, driving meteorology, and spatial/temporal discretization can be easily tested. Initial testing of CHM compared spatial scales and model complexity for a spring melt period at a sub-arctic mountain basin. The meshing algorithm reduced the total number of computational elements and preserved the spatial heterogeneity of predictions.

Distribution of Aboveground Live Biomass in the Amazon Basin

NASA Technical Reports Server (NTRS)

Saatchi, S. S.; Houghton, R. A.; DosSantos Alvala, R. C.; Soares, J. V.; Yu, Y.

2007-01-01

The amount and spatial distribution of forest biomass in the Amazon basin is a major source of uncertainty in estimating the flux of carbon released from land-cover and land-use change. Direct measurements of aboveground live biomass (AGLB) are limited to small areas of forest inventory plots and site-specific allometric equations that cannot be readily generalized for the entire basin. Furthermore, there is no spaceborne remote sensing instrument that can measure tropical forest biomass directly. To determine the spatial distribution of forest biomass of the Amazon basin, we report a method based on remote sensing metrics representing various forest structural parameters and environmental variables, and more than 500 plot measurements of forest biomass distributed over the basin. A decision tree approach was used to develop the spatial distribution of AGLB for seven distinct biomass classes of lowland old-growth forests with more than 80% accuracy. AGLB for other vegetation types, such as the woody and herbaceous savanna and secondary forests, was directly estimated with a regression based on satellite data. Results show that AGLB is highest in Central Amazonia and in regions to the east and north, including the Guyanas. Biomass is generally above 300Mgha(sup 1) here except in areas of intense logging or open floodplains. In Western Amazonia, from the lowlands of Peru, Ecuador, and Colombia to the Andean mountains, biomass ranges from 150 to 300Mgha(sup 1). Most transitional and seasonal forests at the southern and northwestern edges of the basin have biomass ranging from 100 to 200Mgha(sup 1). The AGLB distribution has a significant correlation with the length of the dry season. We estimate that the total carbon in forest biomass of the Amazon basin, including the dead and below ground biomass, is 86 PgC with +/- 20% uncertainty.

Spatial and size-frequency distribution of Acropora (Cnidaria: Scleractinia) species in Chinchorro Bank, Mexican Caribbean: implications for management

NASA Astrophysics Data System (ADS)

Vega-Zepeda, A.; Hernández-Arana, H.; Carricart-Ganivet, J. P.

2007-09-01

The Mexican Government decreed Chinchorro Bank reef as a Biosphere Reserve in 1996. The aim of this study was to evaluate the spatial and size-frequency distribution of Acropora spp. in order to provide further knowledge and tools to enhance management. A field survey was conducted, within six regions, to locate and measure Acropora patches in the reef lagoon. Density, colony size and living tissue cover of Acropora colonies were evaluated using the line-intercept transect technique, combining direct observations and video transects. The results showed that Acropora spp. was preferentially distributed in the southern regions; where cover and density were high. Based on these results and considering that Acropora spp. produces landscape heterogeneity, which in turn generates shelter for other species, including some of considerable economic importance, then at least the South East region should be considered as a key area for Acropora species conservation, and should be included in the Chinchorro Bank management plan.

Effect of small-molecule modification on single-cell pharmacokinetics of PARP inhibitors.

PubMed

Thurber, Greg M; Reiner, Thomas; Yang, Katherine S; Kohler, Rainer H; Weissleder, Ralph

2014-04-01

The heterogeneous delivery of drugs in tumors is an established process contributing to variability in treatment outcome. Despite the general acceptance of variable delivery, the study of the underlying causes is challenging, given the complex tumor microenvironment including intra- and intertumor heterogeneity. The difficulty in studying this distribution is even more significant for small-molecule drugs where radiolabeled compounds or mass spectrometry detection lack the spatial and temporal resolution required to quantify the kinetics of drug distribution in vivo. In this work, we take advantage of the synthesis of fluorescent drug conjugates that retain their target binding but are designed with different physiochemical and thus pharmacokinetic properties. Using these probes, we followed the drug distribution in cell culture and tumor xenografts with temporal resolution of seconds and subcellular spatial resolution. These measurements, including in vivo permeability of small-molecule drugs, can be used directly in predictive pharmacokinetic models for the design of therapeutics and companion imaging agents as demonstrated by a finite element model.

Effect of Small Molecule Modification on Single Cell Pharmacokinetics of PARP Inhibitors

PubMed Central

Thurber, Greg M.; Reiner, Thomas; Yang, Katherine S; Kohler, Rainer; Weissleder, Ralph

2014-01-01

The heterogeneous delivery of drugs in tumors is an established process contributing to variability in treatment outcome. Despite the general acceptance of variable delivery, the study of the underlying causes is challenging given the complex tumor microenvironment including intra- and inter-tumor heterogeneity. The difficulty in studying this distribution is even more significant for small molecule drugs where radiolabeled compounds or mass spectrometry detection lack the spatial and temporal resolution required to quantify the kinetics of drug distribution in vivo. In this work, we take advantage of the synthesis of fluorescent drug conjugates that retain their target binding but are designed with different physiochemical and thus pharmacokinetic properties. Using these probes, we followed the drug distribution in cell culture and tumor xenografts with temporal resolution of seconds and subcellular spatial resolution. These measurements, including in vivo permeability of small molecule drugs, can be used directly in predictive pharmacokinetic models for the design of therapeutics and companion imaging agents as demonstrated by a finite element model. PMID:24552776

The Potential for Spatial Distribution Indices to Signal Thresholds in Marine Fish Biomass

PubMed Central

Reuchlin-Hugenholtz, Emilie

2015-01-01

The frequently observed positive relationship between fish population abundance and spatial distribution suggests that changes in distribution can be indicative of trends in abundance. If contractions in spatial distribution precede declines in spawning stock biomass (SSB), spatial distribution reference points could complement the SSB reference points that are commonly used in marine conservation biology and fisheries management. When relevant spatial distribution information is integrated into fisheries management and recovery plans, risks and uncertainties associated with a plan based solely on the SSB criterion would be reduced. To assess the added value of spatial distribution data, we examine the relationship between SSB and four metrics of spatial distribution intended to reflect changes in population range, concentration, and density for 10 demersal populations (9 species) inhabiting the Scotian Shelf, Northwest Atlantic. Our primary purpose is to assess their potential to serve as indices of SSB, using fisheries independent survey data. We find that metrics of density offer the best correlate of spawner biomass. A decline in the frequency of encountering high density areas is associated with, and in a few cases preceded by, rapid declines in SSB in 6 of 10 populations. Density-based indices have considerable potential to serve both as an indicator of SSB and as spatially based reference points in fisheries management. PMID:25789624

[Spatial distribution prediction of surface soil Pb in a battery contaminated site].

PubMed

Liu, Geng; Niu, Jun-Jie; Zhang, Chao; Zhao, Xin; Guo, Guan-Lin

2014-12-01

In order to enhance the reliability of risk estimation and to improve the accuracy of pollution scope determination in a battery contaminated site with the soil characteristic pollutant Pb, four spatial interpolation models, including Combination Prediction Model (OK(LG) + TIN), kriging model (OK(BC)), Inverse Distance Weighting model (IDW), and Spline model were employed to compare their effects on the spatial distribution and pollution assessment of soil Pb. The results showed that Pb concentration varied significantly and the data was severely skewed. The variation coefficient of the site was higher in the local region. OK(LG) + TIN was found to be more accurate than the other three models in predicting the actual pollution situations of the contaminated site. The prediction accuracy of other models was lower, due to the effect of the principle of different models and datum feature. The interpolation results of OK(BC), IDW and Spline could not reflect the detailed characteristics of seriously contaminated areas, and were not suitable for mapping and spatial distribution prediction of soil Pb in this site. This study gives great contributions and provides useful references for defining the remediation boundary and making remediation decision of contaminated sites.

A GIS-based multi-source and multi-box modeling approach (GMSMB) for air pollution assessment--a North American case study.

PubMed

Wang, Bao-Zhen; Chen, Zhi

2013-01-01

This article presents a GIS-based multi-source and multi-box modeling approach (GMSMB) to predict the spatial concentration distributions of airborne pollutant on local and regional scales. In this method, an extended multi-box model combined with a multi-source and multi-grid Gaussian model are developed within the GIS framework to examine the contributions from both point- and area-source emissions. By using GIS, a large amount of data including emission sources, air quality monitoring, meteorological data, and spatial location information required for air quality modeling are brought into an integrated modeling environment. It helps more details of spatial variation in source distribution and meteorological condition to be quantitatively analyzed. The developed modeling approach has been examined to predict the spatial concentration distribution of four air pollutants (CO, NO(2), SO(2) and PM(2.5)) for the State of California. The modeling results are compared with the monitoring data. Good agreement is acquired which demonstrated that the developed modeling approach could deliver an effective air pollution assessment on both regional and local scales to support air pollution control and management planning.

Design and implementation of a distributed large-scale spatial database system based on J2EE

NASA Astrophysics Data System (ADS)

Gong, Jianya; Chen, Nengcheng; Zhu, Xinyan; Zhang, Xia

2003-03-01

With the increasing maturity of distributed object technology, CORBA, .NET and EJB are universally used in traditional IT field. However, theories and practices of distributed spatial database need farther improvement in virtue of contradictions between large scale spatial data and limited network bandwidth or between transitory session and long transaction processing. Differences and trends among of CORBA, .NET and EJB are discussed in details, afterwards the concept, architecture and characteristic of distributed large-scale seamless spatial database system based on J2EE is provided, which contains GIS client application, web server, GIS application server and spatial data server. Moreover the design and implementation of components of GIS client application based on JavaBeans, the GIS engine based on servlet, the GIS Application server based on GIS enterprise JavaBeans(contains session bean and entity bean) are explained.Besides, the experiments of relation of spatial data and response time under different conditions are conducted, which proves that distributed spatial database system based on J2EE can be used to manage, distribute and share large scale spatial data on Internet. Lastly, a distributed large-scale seamless image database based on Internet is presented.

Dynamic granularity of imaging systems

DOE PAGES

Geissel, Matthias; Smith, Ian C.; Shores, Jonathon E.; ...

2015-11-04

Imaging systems that include a specific source, imaging concept, geometry, and detector have unique properties such as signal-to-noise ratio, dynamic range, spatial resolution, distortions, and contrast. Some of these properties are inherently connected, particularly dynamic range and spatial resolution. It must be emphasized that spatial resolution is not a single number but must be seen in the context of dynamic range and consequently is better described by a function or distribution. We introduce the “dynamic granularity” G dyn as a standardized, objective relation between a detector’s spatial resolution (granularity) and dynamic range for complex imaging systems in a given environmentmore » rather than the widely found characterization of detectors such as cameras or films by themselves. We found that this relation can partly be explained through consideration of the signal’s photon statistics, background noise, and detector sensitivity, but a comprehensive description including some unpredictable data such as dust, damages, or an unknown spectral distribution will ultimately have to be based on measurements. Measured dynamic granularities can be objectively used to assess the limits of an imaging system’s performance including all contributing noise sources and to qualify the influence of alternative components within an imaging system. Our article explains the construction criteria to formulate a dynamic granularity and compares measured dynamic granularities for different detectors used in the X-ray backlighting scheme employed at Sandia’s Z-Backlighter facility.« less

The Distribution of Basal Water Beneath the Greenland Ice Sheet from Radio-Echo Sounding

NASA Astrophysics Data System (ADS)

Jordan, T.; Williams, C.; Schroeder, D. M.; Martos, Y. M.; Cooper, M.; Siegert, M. J.; Paden, J. D.; Huybrechts, P.; Bamber, J. L.

2017-12-01

There is widespread, but often indirect, evidence that a significant fraction of the Greenland Ice Sheet is thawed at the bed. This includes major outlet glaciers and around the NorthGRIP ice-core in the interior. However, the ice-sheet-wide distribution of basal water is poorly constrained by existing observations, and the spatial relationship between basal water and other ice-sheet and subglacial properties is therefore largely unexplored. In principle, airborne radio-echo sounding (RES) surveys provide the necessary information and spatial coverage to infer the presence of basal water at the ice-sheet scale. However, due to uncertainty and spatial variation in radar signal attenuation, the commonly used water diagnostic, bed-echo reflectivity, is highly ambiguous and prone to spatial bias. Here we introduce a new RES diagnostic for the presence of basal water which incorporates both sharp step-transitions and rapid fluctuations in bed-echo reflectivity. This has the advantage of being (near) independent of attenuation model, and enables a decade of recent Operation Ice Bride RES survey data to be combined in a single map for basal water. The ice-sheet-wide water predictions are compared with: bed topography and drainage network structure, existing knowledge of the thermal state and geothermal heat flux, and ice velocity. In addition to the fast flowing ice-sheet margins, we also demonstrate widespread water routing and storage in parts of the slow-flowing northern interior. Notably, this includes a quasi-linear `corridor' of basal water, extending from NorthGRIP to Petermann glacier, which spatially correlates with a region of locally high (magnetic-derived) geothermal heat flux. The predicted water distribution places a new constraint upon the basal thermal state of the Greenland Ice Sheet, and could be used as an input for ice-sheet model simulations.

Utah FORGE Groundwater Data

DOE Data Explorer

Joe Moore

2016-07-20

This submission includes two modelled drawdown scenarios with new supply well locations, a total dissolved solids (TDS) concentration grid (raster dataset representing the spatial distribution of TDS), and an excel spreadsheet containing well data.

Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Y Churmakov, D.; Meglinski, I. V.; Piletsky, S. A.; Greenhalgh, D. A.

2003-07-01

A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an `effective' depth.

On species persistence-time distributions.

PubMed

Suweis, S; Bertuzzo, E; Mari, L; Rodriguez-Iturbe, I; Maritan, A; Rinaldo, A

2012-06-21

We present new theoretical and empirical results on the probability distributions of species persistence times in natural ecosystems. Persistence times, defined as the timespans occurring between species' colonization and local extinction in a given geographic region, are empirically estimated from local observations of species' presence/absence. A connected sampling problem is presented, generalized and solved analytically. Species persistence is shown to provide a direct connection with key spatial macroecological patterns like species-area and endemics-area relationships. Our empirical analysis pertains to two different ecosystems and taxa: a herbaceous plant community and a estuarine fish database. Despite the substantial differences in ecological interactions and spatial scales, we confirm earlier evidence on the general properties of the scaling of persistence times, including the predicted effects of the structure of the spatial interaction network. The framework tested here allows to investigate directly nature and extent of spatial effects in the context of ecosystem dynamics. The notable coherence between spatial and temporal macroecological patterns, theoretically derived and empirically verified, is suggested to underlie general features of the dynamic evolution of ecosystems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatial Analysis of PAHs in Soils along an Urban-Suburban-Rural Gradient: scale effect, distribution patterns, diffusion and influencing factors

NASA Astrophysics Data System (ADS)

Peng, Chi; Wang, Meie; Chen, Weiping

2016-11-01

Spatial statistical methods including Cokriging interpolation, Morans I analysis, and geographically weighted regression (GWR) were used for studying the spatial characteristics of polycyclic aromatic hydrocarbon (PAH) accumulation in urban, suburban, and rural soils of Beijing. The concentrations of PAHs decreased spatially as the level of urbanization decreased. Generally, PAHs in soil showed two spatial patterns on the regional scale: (1) regional baseline depositions with a radius of 16.5 km related to the level of urbanization and (2) isolated pockets of soil contaminated with PAHs were found up to around 3.5 km from industrial point sources. In the urban areas, soil PAHs showed high spatial heterogeneity on the block scale, which was probably related to vegetation cover, land use, and physical soil disturbance. The distribution of total PAHs in urban blocks was unrelated to the indicators of the intensity of anthropogenic activity, namely population density, light intensity at night, and road density, but was significantly related to the same indicators in the suburban and rural areas. The moving averages of molecular ratios suggested that PAHs in the suburban and rural soils were a mix of local emissions and diffusion from urban areas.

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

NASA Astrophysics Data System (ADS)

Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

Is a matrix exponential specification suitable for the modeling of spatial correlation structures?

PubMed Central

Strauß, Magdalena E.; Mezzetti, Maura; Leorato, Samantha

2018-01-01

This paper investigates the adequacy of the matrix exponential spatial specifications (MESS) as an alternative to the widely used spatial autoregressive models (SAR). To provide as complete a picture as possible, we extend the analysis to all the main spatial models governed by matrix exponentials comparing them with their spatial autoregressive counterparts. We propose a new implementation of Bayesian parameter estimation for the MESS model with vague prior distributions, which is shown to be precise and computationally efficient. Our implementations also account for spatially lagged regressors. We further allow for location-specific heterogeneity, which we model by including spatial splines. We conclude by comparing the performances of the different model specifications in applications to a real data set and by running simulations. Both the applications and the simulations suggest that the spatial splines are a flexible and efficient way to account for spatial heterogeneities governed by unknown mechanisms. PMID:29492375

Improving removal-based estimates of abundance by sampling a population of spatially distinct subpopulations

USGS Publications Warehouse

Dorazio, R.M.; Jelks, H.L.; Jordan, F.

2005-01-01

 A statistical modeling framework is described for estimating the abundances of spatially distinct subpopulations of animals surveyed using removal sampling. To illustrate this framework, hierarchical models are developed using the Poisson and negative-binomial distributions to model variation in abundance among subpopulations and using the beta distribution to model variation in capture probabilities. These models are fitted to the removal counts observed in a survey of a federally endangered fish species. The resulting estimates of abundance have similar or better precision than those computed using the conventional approach of analyzing the removal counts of each subpopulation separately. Extension of the hierarchical models to include spatial covariates of abundance is straightforward and may be used to identify important features of an animal's habitat or to predict the abundance of animals at unsampled locations.

Spatial study of homicide rates in the state of Bahia, Brazil, 1996-2010

PubMed Central

de Souza, Tiago Oliveira; Pinto, Liana Wernersbach; de Souza, Edinilsa Ramos

2014-01-01

OBJECTIVE To analyze the spatial distribution of homicide mortality in the state of Bahia, Northeastern Brazil. METHODS Ecological study of the 15 to 39-year old male population in the state of Bahia in the period 1996-2010. Data from the Mortality Information System, relating to homicide (X85-Y09) and population estimates from the Brazilian Institute of Geography and Statistics were used. The existence of spatial correlation, the presence of clusters and critical areas of the event studied were analyzed using Moran’s I Global and Local indices. RESULTS A non-random spatial pattern was observed in the distribution of rates, as was the presence of three clusters, the first in the north health district, the second in the eastern region, and the third cluster included townships in the south and the far south of Bahia. CONCLUSIONS The homicide mortality in the three different critical areas requires further studies that consider the socioeconomic, cultural and environmental characteristics in order to guide specific preventive and interventionist practices. PMID:25119942

Traveltime-based descriptions of transport and mixing in heterogeneous domains

NASA Astrophysics Data System (ADS)

Luo, Jian; Cirpka, Olaf A.

2008-09-01

Modeling mixing-controlled reactive transport using traditional spatial discretization of the domain requires identifying the spatial distributions of hydraulic and reactive parameters including mixing-related quantities such as dispersivities and kinetic mass transfer coefficients. In most applications, breakthrough curves (BTCs) of conservative and reactive compounds are measured at only a few locations and spatially explicit models are calibrated by matching these BTCs. A common difficulty in such applications is that the individual BTCs differ too strongly to justify the assumption of spatial homogeneity, whereas the number of observation points is too small to identify the spatial distribution of the decisive parameters. The key objective of the current study is to characterize physical transport by the analysis of conservative tracer BTCs and predict the macroscopic BTCs of compounds that react upon mixing from the interpretation of conservative tracer BTCs and reactive parameters determined in the laboratory. We do this in the framework of traveltime-based transport models which do not require spatially explicit, costly aquifer characterization. By considering BTCs of a conservative tracer measured on different scales, one can distinguish between mixing, which is a prerequisite for reactions, and spreading, which per se does not foster reactions. In the traveltime-based framework, the BTC of a solute crossing an observation plane, or ending in a well, is interpreted as the weighted average of concentrations in an ensemble of non-interacting streamtubes, each of which is characterized by a distinct traveltime value. Mixing is described by longitudinal dispersion and/or kinetic mass transfer along individual streamtubes, whereas spreading is characterized by the distribution of traveltimes, which also determines the weights associated with each stream tube. Key issues in using the traveltime-based framework include the description of mixing mechanisms and the estimation of the traveltime distribution. In this work, we account for both apparent longitudinal dispersion and kinetic mass transfer as mixing mechanisms, thus generalizing the stochastic-convective model with or without inter-phase mass transfer and the advective-dispersive streamtube model. We present a nonparametric approach of determining the traveltime distribution, given a BTC integrated over an observation plane and estimated mixing parameters. The latter approach is superior to fitting parametric models in cases wherein the true traveltime distribution exhibits multiple peaks or long tails. It is demonstrated that there is freedom for the combinations of mixing parameters and traveltime distributions to fit conservative BTCs and describe the tailing. A reactive transport case of a dual Michaelis-Menten problem demonstrates that the reactive mixing introduced by local dispersion and mass transfer may be described by apparent mean mass transfer with coefficients evaluated by local BTCs.

Considering spatial heterogeneity in the distributed lag non-linear model when analyzing spatiotemporal data.

PubMed

Chien, Lung-Chang; Guo, Yuming; Li, Xiao; Yu, Hwa-Lung

2018-01-01

The distributed lag non-linear (DLNM) model has been frequently used in time series environmental health research. However, its functionality for assessing spatial heterogeneity is still restricted, especially in analyzing spatiotemporal data. This study proposed a solution to take a spatial function into account in the DLNM, and compared the influence with and without considering spatial heterogeneity in a case study. This research applied the DLNM to investigate non-linear lag effect up to 7 days in a case study about the spatiotemporal impact of fine particulate matter (PM 2.5 ) on preschool children's acute respiratory infection in 41 districts of northern Taiwan during 2005 to 2007. We applied two spatiotemporal methods to impute missing air pollutant data, and included the Markov random fields to analyze district boundary data in the DLNM. When analyzing the original data without a spatial function, the overall PM 2.5 effect accumulated from all lag-specific effects had a slight variation at smaller PM 2.5 measurements, but eventually decreased to relative risk significantly <1 when PM 2.5 increased. While analyzing spatiotemporal imputed data without a spatial function, the overall PM 2.5 effect did not decrease but increased in monotone as PM 2.5 increased over 20 μg/m 3 . After adding a spatial function in the DLNM, spatiotemporal imputed data conducted similar results compared with the overall effect from the original data. Moreover, the spatial function showed a clear and uneven pattern in Taipei, revealing that preschool children living in 31 districts of Taipei were vulnerable to acute respiratory infection. Our findings suggest the necessity of including a spatial function in the DLNM to make a spatiotemporal analysis available and to conduct more reliable and explainable research. This study also revealed the analytical impact if spatial heterogeneity is ignored.

Evaluating the Spatial Distribution of Toxic Air Contaminants in Multiple Ecosystem Indicators in the Sierra Nevada-Southern Cascades

NASA Astrophysics Data System (ADS)

Nanus, L.; Simonich, S. L.; Rocchio, J.; Flanagan, C.

2013-12-01

Toxic air contaminants originating from agricultural areas of the Central Valley in California threaten vulnerable sensitive receptors including surface water, vegetation, snow, sediments, fish, and amphibians in the Sierra Nevada-Southern Cascades region. The spatial distribution of toxic air contaminants in different ecosystem indicators depends on variation in atmospheric concentrations and deposition, and variation in air toxics accumulation in ecosystems. The spatial distribution of organic air toxics and mercury at over 330 unique sampling locations and sample types over two decades (1990-2009) in the Sierra Nevada-Southern Cascades region were compiled and maps were developed to further understand spatial patterns and linkages between air toxics deposition and ecological effects. Potential ecosystem impacts in the Sierra Nevada-Southern Cascades region include bioaccumulation of air toxics in both aquatic and terrestrial ecosystems, reproductive disruption, and immune suppression. The most sensitive ecological end points in the region that are affected by bioaccumulation of toxic air contaminants are fish. Mercury was detected in all fish and approximately 6% exceeded human consumption thresholds. Organic air toxics were also detected in fish yielding variable spatial patterns. For amphibians, which are sensitive to pesticide exposure and potential immune suppression, increasing trends in current and historic use pesticides are observed from north to south across the region. In other indicators, such as vegetation, pesticide concentrations in lichen increase with increasing elevation. Current and historic use pesticides and mercury were also observed in snowpack at high elevations in the study area. This study shows spatial patterns in toxic air contaminants, evaluates associated risks to sensitive receptors, and identifies data gaps. Future research on atmospheric modeling and information on sources is needed in order to predict which ecosystems are the most sensitive to toxic air contaminants in the Sierra Nevada-Southern Cascades region.

Pickup Ion Distributions from Three Dimensional Neutral Exospheres

NASA Technical Reports Server (NTRS)

Hartle, R. E.; Sarantos, M.; Sittler, E. C., Jr.

2011-01-01

Pickup ions formed from ionized neutral exospheres in flowing plasmas have phase space distributions that reflect their source's spatial distributions. Phase space distributions of the ions are derived from the Vlasov equation with a delta function source using three.dimensional neutral exospheres. The ExB drift produced by plasma motion picks up the ions while the effects of magnetic field draping, mass loading, wave particle scattering, and Coulomb collisions near a planetary body are ignored. Previously, one.dimensional exospheres were treated, resulting in closed form pickup ion distributions that explicitly depend on the ratio rg/H, where rg is the ion gyroradius and H is the neutral scale height at the exobase. In general, the pickup ion distributions, based on three.dimensional neutral exospheres, cannot be written in closed form, but can be computed numerically. They continue to reflect their source's spatial distributions in an implicit way. These ion distributions and their moments are applied to several bodies, including He(+) and Na(+) at the Moon, H(+2) and CH(+4) at Titan, and H+ at Venus. The best places to use these distributions are upstream of the Moon's surface, the ionopause of Titan, and the bow shock of Venus.

[Spatial distribution of birth defects among children aged 0 to 5 years and its relationship with soil chemical elements in Chongqing].

PubMed

Dong, Yan; Zhong, Zhao-hui; Li, Hong; Li, Jie; Wang, Ying-xiong; Peng, Bin; Zhang, Mao-zhong; Huang, Qiao; Yan, Ju; Xu, Fei-long

2013-10-01

To explore the correlation between the incidence of birth defects and the contents of soil elements so as to provide a scientific basis for screening the related pathogenic factors that inducing birth defects for the development of related preventive and control strategies. MapInfo 7.0 software was used to draw the maps on spatial distribution regarding the incidence rates of birth defects and the contents of 11 chemical elements in soil in the 33 studied areas. Variables on the two maps were superposed for analyzing the spatial correlation. SAS 8.0 software was used to analyze single factor, multi-factors and principal components as well as to comprehensively evaluate the degrees of relevance. Different incidence rates of birth defects showed in the maps of spatial distribution presented certain degrees of negative correlation with anomalies of soil chemical elements, including copper, chrome, iodine, selenium, zinc while positively correlated with the levels of lead. Results from the principal component regression equation indicating that the contents of copper(0.002), arsenic(-0.07), cadmium(0.05), chrome (-0.001), zinc (0.001), iodine(-0.03), lead (0.08), fluorine(-0.002)might serve as important factors that related to the prevalence of birth defects. Through the study on spatial distribution, we noticed that the incidence rates of birth defects were related to the contents of copper, chrome, iodine, selenium, zinc, lead in soil while the contents of chrome, iodine and lead might lead to the occurrence of birth defects.

Spatial distribution and sources of heavy metals in natural pasture soil around copper-molybdenum mine in Northeast China.

PubMed

Wang, Zhiqiang; Hong, Chen; Xing, Yi; Wang, Kang; Li, Yifei; Feng, Lihui; Ma, Silu

2018-06-15

The characterization of the content and source of heavy metals are essential to assess the potential threat of metals to human health. The present study collected 140 topsoil samples around a Cu-Mo mine (Wunugetushan, China) and investigated the concentrations and spatial distribution pattern of Cr, Ni, Zn, Cu, Mo and Cd in soil using multivariate and geostatistical analytical methods. Results indicated that the average concentrations of six heavy metals, especially Cu and Mo, were obviously higher than the local background values. Correlation analysis and principal component analysis divided these metals into three groups, including Cr and Ni, Cu and Mo, Zn and Cd. Meanwhile, the spatial distribution maps of heavy metals indicated that Cr and Ni in soil were no notable anthropogenic inputs and mainly controlled by natural factors because their spatial maps exhibited non-point source contamination. The concentrations of Cu and Mo gradually decreased with distance away from the mine area, suggesting that human mining activities may be crucial in the spreading of contaminants. Soil contamination of Zn were associated with livestock manure produced from grazing. In addition, the environmental risk of heavy metal pollution was assessed by geo-accumulation index. All the results revealed that the spatial distribution of heavy metals in soil were in agreement with the local human activities. Investigating and identifying the origin of heavy metals in pasture soil will lay the foundation for taking effective measures to preserve soil from the long-term accumulation of heavy metals. Copyright © 2018 Elsevier Inc. All rights reserved.

Trees grow on money: urban tree canopy cover and environmental justice.

PubMed

Schwarz, Kirsten; Fragkias, Michail; Boone, Christopher G; Zhou, Weiqi; McHale, Melissa; Grove, J Morgan; O'Neil-Dunne, Jarlath; McFadden, Joseph P; Buckley, Geoffrey L; Childers, Dan; Ogden, Laura; Pincetl, Stephanie; Pataki, Diane; Whitmer, Ali; Cadenasso, Mary L

2015-01-01

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman's correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns.

[Spatial distribution pattern of Pontania dolichura larvae and sampling technique].

PubMed

Zhang, Feng; Chen, Zhijie; Zhang, Shulian; Zhao, Huiyan

2006-03-01

In this paper, the spatial distribution pattern of Pontania dolichura larvae was analyzed with Taylor's power law, Iwao's distribution function, and six aggregation indexes. The results showed that the spatial distribution pattern of P. dolichura larvae was of aggregated, and the basic component of the distribution was individual colony, with the aggregation intensity increased with density. On branches, the aggregation was caused by the adult behavior of laying eggs and the spatial position of leaves, while on leaves, the aggregation was caused by the spatial position of news leaves in spring when m < 2.37, and by the spatial position of news leaves in spring and the behavior of eclosion and laying eggs when m > 2.37. By using the parameters alpha and beta in Iwao's m * -m regression equation, the optimal and sequential sampling numbers were determined.

Effects of natural factors on the spatial distribution of heavy metals in soils surrounding mining regions.

PubMed

Ding, Qian; Cheng, Gong; Wang, Yong; Zhuang, Dafang

2017-02-01

Various studies have shown that soils surrounding mining areas are seriously polluted with heavy metals. Determining the effects of natural factors on spatial distribution of heavy metals is important for determining the distribution characteristics of heavy metals in soils. In this study, an 8km buffer zone surrounding a typical non-ferrous metal mine in Suxian District of Hunan Province, China, was selected as the study area, and statistical, spatial autocorrelation and spatial interpolation analyses were used to obtain descriptive statistics and spatial autocorrelation characteristics of As, Pb, Cu, and Zn in soil. Additionally, the distributions of soil heavy metals under the influences of natural factors, including terrain (elevation and slope), wind direction and distance from a river, were determined. Layout of sampling sites, spatial changes of heavy metal contents at high elevations and concentration differences between upwind and downwind directions were then evaluated. The following results were obtained: (1) At low elevations, heavy metal concentrations decreased slightly, then increased considerably with increasing elevation. At high elevations, heavy metal concentrations first decreased, then increased, then decreased with increasing elevation. As the slope increased, heavy metal contents increased then decreased. (2) Heavy metal contents changed consistently in the upwind and downwind directions. Heavy metal contents were highest in 1km buffer zone and decreased with increasing distance from the mining area. The largest decrease in heavy metal concentrations was in 2km buffer zone. Perennial wind promotes the transport of heavy metals in downwind direction. (3) The spatial extent of the influence of the river on Pb, Zn and Cu in the soil was 800m. (4) The influence of the terrain on the heavy metal concentrations was greater than that of the wind. These results provide a scientific basis for preventing and mitigating heavy metal soil pollution in areas surrounding mines. Copyright © 2016 Elsevier B.V. All rights reserved.

[Ecological risk assessment of land use based on exploratory spatial data analysis (ESDA): a case study of Haitan Island, Fujian Province].

PubMed

Wu, Jian; Chen, Peng; Wen, Chao-Xiang; Fu, Shi-Feng; Chen, Qing-Hui

2014-07-01

As a novel environment management tool, ecological risk assessment has provided a new perspective for the quantitative evaluation of ecological effects of land-use change. In this study, Haitan Island in Fujian Province was taken as a case. Based on the Landsat TM obtained in 1990, SPOT5 RS images obtained in 2010, general layout planning map of Pingtan Comprehensive Experimental Zone in 2030, as well as the field investigation data, we established an ecological risk index to measure ecological endpoints. By using spatial autocorrelation and semivariance analysis of Exploratory Spatial Data Analysis (ESDA), the ecological risk of Haitan Island under different land-use situations was assessed, including the past (1990), present (2010) and future (2030), and the potential risk and its changing trend were analyzed. The results revealed that the ecological risk index showed obvious scale effect, with strong positive correlation within 3000 meters. High-high (HH) and low-low (LL) aggregations were predominant types in spatial distribution of ecological risk index. The ecological risk index showed significant isotropic characteristics, and its spatial distribution was consistent with Anselin Local Moran I (LISA) distribution during the same period. Dramatic spatial distribution change of each ecological risk area was found among 1990, 2010 and 2030, and the fluctuation trend and amplitude of different ecological risk areas were diverse. The low ecological risk area showed a rise-to-fall trend while the medium and high ecological risk areas showed a fall-to-rise trend. In the planning period, due to intensive anthropogenic disturbance, the high ecological risk area spread throughout the whole region. To reduce the ecological risk in land-use and maintain the regional ecological security, the following ecological risk control strategies could be adopted, i.e., optimizing the spatial pattern of land resources, protecting the key ecoregions and controlling the scale of construction land use.

Inner membrane fusion mediates spatial distribution of axonal mitochondria

PubMed Central

Yu, Yiyi; Lee, Hao-Chih; Chen, Kuan-Chieh; Suhan, Joseph; Qiu, Minhua; Ba, Qinle; Yang, Ge

2016-01-01

In eukaryotic cells, mitochondria form a dynamic interconnected network to respond to changing needs at different subcellular locations. A fundamental yet unanswered question regarding this network is whether, and if so how, local fusion and fission of individual mitochondria affect their global distribution. To address this question, we developed high-resolution computational image analysis techniques to examine the relations between mitochondrial fusion/fission and spatial distribution within the axon of Drosophila larval neurons. We found that stationary and moving mitochondria underwent fusion and fission regularly but followed different spatial distribution patterns and exhibited different morphology. Disruption of inner membrane fusion by knockdown of dOpa1, Drosophila Optic Atrophy 1, not only increased the spatial density of stationary and moving mitochondria but also changed their spatial distributions and morphology differentially. Knockdown of dOpa1 also impaired axonal transport of mitochondria. But the changed spatial distributions of mitochondria resulted primarily from disruption of inner membrane fusion because knockdown of Milton, a mitochondrial kinesin-1 adapter, caused similar transport velocity impairment but different spatial distributions. Together, our data reveals that stationary mitochondria within the axon interconnect with moving mitochondria through fusion and fission and that local inner membrane fusion between individual mitochondria mediates their global distribution. PMID:26742817

Temperature drives abundance fluctuations, but spatial dynamics is constrained by landscape configuration: Implications for climate-driven range shift in a butterfly.

PubMed

Fourcade, Yoan; Ranius, Thomas; Öckinger, Erik

2017-10-01

Prediction of species distributions in an altered climate requires knowledge on how global- and local-scale factors interact to limit their current distributions. Such knowledge can be gained through studies of spatial population dynamics at climatic range margins. Here, using a butterfly (Pyrgus armoricanus) as model species, we first predicted based on species distribution modelling that its climatically suitable habitats currently extend north of its realized range. Projecting the model into scenarios of future climate, we showed that the distribution of climatically suitable habitats may shift northward by an additional 400 km in the future. Second, we used a 13-year monitoring dataset including the majority of all habitat patches at the species northern range margin to assess the synergetic impact of temperature fluctuations and spatial distribution of habitat, microclimatic conditions and habitat quality, on abundance and colonization-extinction dynamics. The fluctuation in abundance between years was almost entirely determined by the variation in temperature during the species larval development. In contrast, colonization and extinction dynamics were better explained by patch area, between-patch connectivity and host plant density. This suggests that the response of the species to future climate change may be limited by future land use and how its host plants respond to climate change. It is, thus, probable that dispersal limitation will prevent P. armoricanus from reaching its potential future distribution. We argue that models of range dynamics should consider the factors influencing metapopulation dynamics, especially at the range edges, and not only broad-scale climate. It includes factors acting at the scale of habitat patches such as habitat quality and microclimate and landscape-scale factors such as the spatial configuration of potentially suitable patches. Knowledge of population dynamics under various environmental conditions, and the incorporation of realistic scenarios of future land use, appears essential to provide predictions useful for actions mitigating the negative effects of climate change. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Spatial variability of soil moisture retrieved by SMOS satellite

NASA Astrophysics Data System (ADS)

Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

2015-04-01

Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies ergodicity and quasi-stationarity assumptions, required for geostatistical analysis. The semivariograms examinations revealed that spatial dependences occurring in the surface soil moisture distributions for the selected area were more or less 200 km. The exception was the driest of the studied days, when the spatial correlations of soil moisture were not disturbed for a long time by any rainfall. Spatial correlation length on that day was about 400 km. Because of zonal character of frost, the spatial dependences in the examined surface soil moisture distributions during freezing/thawing found to be disturbed. Probably, the amount of water remains the same, but it is not detected by SMOS, hence analysing dielectric constant instead of soil moisture would be more appropriate. Some spatial relations of soil moisture and freezing distribution with existing maps of soil granulometric fractions and soil specific surface area for Poland have also been found. The work was partially funded under the ELBARA_PD (Penetration Depth) project No. 4000107897/13/NL/KML. ELBARA_PD project is funded by the Government of Poland through an ESA (European Space Agency) Contract under the PECS (Plan for European Cooperating States).

A Bayesian kriging approach for blending satellite and ground precipitation observations

USGS Publications Warehouse

Verdin, Andrew P.; Rajagopalan, Balaji; Kleiber, William; Funk, Christopher C.

2015-01-01

Drought and flood management practices require accurate estimates of precipitation. Gauge observations, however, are often sparse in regions with complicated terrain, clustered in valleys, and of poor quality. Consequently, the spatial extent of wet events is poorly represented. Satellite-derived precipitation data are an attractive alternative, though they tend to underestimate the magnitude of wet events due to their dependency on retrieval algorithms and the indirect relationship between satellite infrared observations and precipitation intensities. Here we offer a Bayesian kriging approach for blending precipitation gauge data and the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates for Central America, Colombia, and Venezuela. First, the gauge observations are modeled as a linear function of satellite-derived estimates and any number of other variables—for this research we include elevation. Prior distributions are defined for all model parameters and the posterior distributions are obtained simultaneously via Markov chain Monte Carlo sampling. The posterior distributions of these parameters are required for spatial estimation, and thus are obtained prior to implementing the spatial kriging model. This functional framework is applied to model parameters obtained by sampling from the posterior distributions, and the residuals of the linear model are subject to a spatial kriging model. Consequently, the posterior distributions and uncertainties of the blended precipitation estimates are obtained. We demonstrate this method by applying it to pentadal and monthly total precipitation fields during 2009. The model's performance and its inherent ability to capture wet events are investigated. We show that this blending method significantly improves upon the satellite-derived estimates and is also competitive in its ability to represent wet events. This procedure also provides a means to estimate a full conditional distribution of the “true” observed precipitation value at each grid cell.

Research on Grid Size Suitability of Gridded Population Distribution in Urban Area: A Case Study in Urban Area of Xuanzhou District, China.

PubMed

Dong, Nan; Yang, Xiaohuan; Cai, Hongyan; Xu, Fengjiao

2017-01-01

The research on the grid size suitability is important to provide improvement in accuracies of gridded population distribution. It contributes to reveal the actual spatial distribution of population. However, currently little research has been done in this area. Many well-modeled gridded population dataset are basically built at a single grid scale. If the grid cell size is not appropriate, it will result in spatial information loss or data redundancy. Therefore, in order to capture the desired spatial variation of population within the area of interest, it is necessary to conduct research on grid size suitability. This study summarized three expressed levels to analyze grid size suitability, which include location expressed level, numeric information expressed level, and spatial relationship expressed level. This study elaborated the reasons for choosing the five indexes to explore expression suitability. These five indexes are consistency measure, shape index rate, standard deviation of population density, patches diversity index, and the average local variance. The suitable grid size was determined by constructing grid size-indicator value curves and suitable grid size scheme. Results revealed that the three expressed levels on 10m grid scale are satisfying. And the population distribution raster data with 10m grid size provide excellent accuracy without loss. The 10m grid size is recommended as the appropriate scale for generating a high-quality gridded population distribution in our study area. Based on this preliminary study, it indicates the five indexes are coordinated with each other and reasonable and effective to assess grid size suitability. We also suggest choosing these five indexes in three perspectives of expressed level to carry out the research on grid size suitability of gridded population distribution.

Research on Grid Size Suitability of Gridded Population Distribution in Urban Area: A Case Study in Urban Area of Xuanzhou District, China

PubMed Central

Dong, Nan; Yang, Xiaohuan; Cai, Hongyan; Xu, Fengjiao

2017-01-01

The research on the grid size suitability is important to provide improvement in accuracies of gridded population distribution. It contributes to reveal the actual spatial distribution of population. However, currently little research has been done in this area. Many well-modeled gridded population dataset are basically built at a single grid scale. If the grid cell size is not appropriate, it will result in spatial information loss or data redundancy. Therefore, in order to capture the desired spatial variation of population within the area of interest, it is necessary to conduct research on grid size suitability. This study summarized three expressed levels to analyze grid size suitability, which include location expressed level, numeric information expressed level, and spatial relationship expressed level. This study elaborated the reasons for choosing the five indexes to explore expression suitability. These five indexes are consistency measure, shape index rate, standard deviation of population density, patches diversity index, and the average local variance. The suitable grid size was determined by constructing grid size-indicator value curves and suitable grid size scheme. Results revealed that the three expressed levels on 10m grid scale are satisfying. And the population distribution raster data with 10m grid size provide excellent accuracy without loss. The 10m grid size is recommended as the appropriate scale for generating a high-quality gridded population distribution in our study area. Based on this preliminary study, it indicates the five indexes are coordinated with each other and reasonable and effective to assess grid size suitability. We also suggest choosing these five indexes in three perspectives of expressed level to carry out the research on grid size suitability of gridded population distribution. PMID:28122050

Interpolating Non-Parametric Distributions of Hourly Rainfall Intensities Using Random Mixing

NASA Astrophysics Data System (ADS)

Mosthaf, Tobias; Bárdossy, András; Hörning, Sebastian

2015-04-01

The correct spatial interpolation of hourly rainfall intensity distributions is of great importance for stochastical rainfall models. Poorly interpolated distributions may lead to over- or underestimation of rainfall and consequently to wrong estimates of following applications, like hydrological or hydraulic models. By analyzing the spatial relation of empirical rainfall distribution functions, a persistent order of the quantile values over a wide range of non-exceedance probabilities is observed. As the order remains similar, the interpolation weights of quantile values for one certain non-exceedance probability can be applied to the other probabilities. This assumption enables the use of kernel smoothed distribution functions for interpolation purposes. Comparing the order of hourly quantile values over different gauges with the order of their daily quantile values for equal probabilities, results in high correlations. The hourly quantile values also show high correlations with elevation. The incorporation of these two covariates into the interpolation is therefore tested. As only positive interpolation weights for the quantile values assure a monotonically increasing distribution function, the use of geostatistical methods like kriging is problematic. Employing kriging with external drift to incorporate secondary information is not applicable. Nonetheless, it would be fruitful to make use of covariates. To overcome this shortcoming, a new random mixing approach of spatial random fields is applied. Within the mixing process hourly quantile values are considered as equality constraints and correlations with elevation values are included as relationship constraints. To profit from the dependence of daily quantile values, distribution functions of daily gauges are used to set up lower equal and greater equal constraints at their locations. In this way the denser daily gauge network can be included in the interpolation of the hourly distribution functions. The applicability of this new interpolation procedure will be shown for around 250 hourly rainfall gauges in the German federal state of Baden-Württemberg. The performance of the random mixing technique within the interpolation is compared to applicable kriging methods. Additionally, the interpolation of kernel smoothed distribution functions is compared with the interpolation of fitted parametric distributions.

The importance of data quality for generating reliable distribution models for rare, elusive, and cryptic species

Treesearch

Keith B. Aubry; Catherine M. Raley; Kevin S. McKelvey

2017-01-01

The availability of spatially referenced environmental data and species occurrence records in online databases enable practitioners to easily generate species distribution models (SDMs) for a broad array of taxa. Such databases often include occurrence records of unknown reliability, yet little information is available on the influence of data quality on SDMs generated...

Distribution and interaction of white-tailed deer and cattle in a semi-arid grazing system

Treesearch

Susan M. Cooper; Humberto L. Perotto-Baldivieso; M. Keith Owens; Michael G. Meek; Manuel Figueroa-Pagan

2008-01-01

In order to optimize production, range managers need to understand and manage the spatial distribution of free-ranging herbivores, although this task becomes increasingly difficult as ranching operations diversify to include management of wildlife for recreational hunting. White-tailed deer are sympatric with cattle throughout much of their range and are a valuable...

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds

PubMed Central

Vaughn, Nicholas R.; Asner, Gregory P.; Smit, Izak P. J.; Riddel, Edward S.

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50–450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques. PMID:26660502

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds.

PubMed

Vaughn, Nicholas R; Asner, Gregory P; Smit, Izak P J; Riddel, Edward S

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50-450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques.

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.

Effects of Fiber Type and Size on the Heterogeneity of Oxygen Distribution in Exercising Skeletal Muscle

PubMed Central

Liu, Gang; Mac Gabhann, Feilim; Popel, Aleksander S.

2012-01-01

The process of oxygen delivery from capillary to muscle fiber is essential for a tissue with variable oxygen demand, such as skeletal muscle. Oxygen distribution in exercising skeletal muscle is regulated by convective oxygen transport in the blood vessels, oxygen diffusion and consumption in the tissue. Spatial heterogeneities in oxygen supply, such as microvascular architecture and hemodynamic variables, had been observed experimentally and their marked effects on oxygen exchange had been confirmed using mathematical models. In this study, we investigate the effects of heterogeneities in oxygen demand on tissue oxygenation distribution using a multiscale oxygen transport model. Muscles are composed of different ratios of the various fiber types. Each fiber type has characteristic values of several parameters, including fiber size, oxygen consumption, myoglobin concentration, and oxygen diffusivity. Using experimentally measured parameters for different fiber types and applying them to the rat extensor digitorum longus muscle, we evaluated the effects of heterogeneous fiber size and fiber type properties on the oxygen distribution profile. Our simulation results suggest a marked increase in spatial heterogeneity of oxygen due to fiber size distribution in a mixed muscle. Our simulations also suggest that the combined effects of fiber type properties, except size, do not contribute significantly to the tissue oxygen spatial heterogeneity. However, the incorporation of the difference in oxygen consumption rates of different fiber types alone causes higher oxygen heterogeneity compared to control cases with uniform fiber properties. In contrast, incorporating variation in other fiber type-specific properties, such as myoglobin concentration, causes little change in spatial tissue oxygenation profiles. PMID:23028531

Metabolic Flexibility as a Major Predictor of Spatial Distribution in Microbial Communities

PubMed Central

Carbonero, Franck; Oakley, Brian B.; Purdy, Kevin J.

2014-01-01

A better understand the ecology of microbes and their role in the global ecosystem could be achieved if traditional ecological theories can be applied to microbes. In ecology organisms are defined as specialists or generalists according to the breadth of their niche. Spatial distribution is often used as a proxy measure of niche breadth; generalists have broad niches and a wide spatial distribution and specialists a narrow niche and spatial distribution. Previous studies suggest that microbial distribution patterns are contrary to this idea; a microbial generalist genus (Desulfobulbus) has a limited spatial distribution while a specialist genus (Methanosaeta) has a cosmopolitan distribution. Therefore, we hypothesise that this counter-intuitive distribution within generalist and specialist microbial genera is a common microbial characteristic. Using molecular fingerprinting the distribution of four microbial genera, two generalists, Desulfobulbus and the methanogenic archaea Methanosarcina, and two specialists, Methanosaeta and the sulfate-reducing bacteria Desulfobacter were analysed in sediment samples from along a UK estuary. Detected genotypes of both generalist genera showed a distinct spatial distribution, significantly correlated with geographic distance between sites. Genotypes of both specialist genera showed no significant differential spatial distribution. These data support the hypothesis that the spatial distribution of specialist and generalist microbes does not match that seen with specialist and generalist large organisms. It may be that generalist microbes, while having a wider potential niche, are constrained, possibly by intrageneric competition, to exploit only a small part of that potential niche while specialists, with far fewer constraints to their niche, are more capable of filling their potential niche more effectively, perhaps by avoiding intrageneric competition. We suggest that these counter-intuitive distribution patterns may be a common feature of microbes in general and represent a distinct microbial principle in ecology, which is a real challenge if we are to develop a truly inclusive ecology. PMID:24465487

The spatial distribution of cropland carbon transfer in Jilin province during 2014

NASA Astrophysics Data System (ADS)

Cai, Xintong; Meng, Jian; Li, Qiuhui; Gao, Shuang; Zhu, Xianjin

2018-01-01

Cropland carbon transfer (CCT, gC yr-1) is an important component in the carbon budget of terrestrial ecosystems. Analyzing the value of CCT and its spatial variation would provide a data basis for assessing the regional carbon balance. Based on the data from Jilin statistical yearbook 2015, we investigated the spatial variation of CCT in Jilin province during 2014. Results suggest that the CCT of Jilin province was 30.83 TgC, which exhibited a decreasing trend from the centre to the border but the west side was higher than the east. The magnitude of carbon transfer per area (MCT), which showed a similar spatial distribution with CCT, was the dominating component of CCT spatial distribution. The spatial distribution of MCT was jointly affected by that of the ratio of planting area to regional area (RPR) and carbon transfer per planting area (CTP), where RPR and CTP contributed 65.55% and 34.5% of MCT spatial distribution, respectively. Therefore, CCT in Jilin province spatially varied, which made it highly needed to consider the difference in CCT among regions when we assessing the regional carbon budget.

Marine protected areas and the value of spatially optimized fishery management

PubMed Central

Rassweiler, Andrew; Costello, Christopher; Siegel, David A.

2012-01-01

There is a growing focus around the world on marine spatial planning, including spatial fisheries management. Some spatial management approaches are quite blunt, as when marine protected areas (MPAs) are established to restrict fishing in specific locations. Other management tools, such as zoning or spatial user rights, will affect the distribution of fishing effort in a more nuanced manner. Considerable research has focused on the ability of MPAs to increase fishery returns, but the potential for the broader class of spatial management approaches to outperform MPAs has received far less attention. We use bioeconomic models of seven nearshore fisheries in Southern California to explore the value of optimized spatial management in which the distribution of fishing is chosen to maximize profits. We show that fully optimized spatial management can substantially increase fishery profits relative to optimal nonspatial management but that the magnitude of this increase depends on characteristics of the fishing fleet and target species. Strategically placed MPAs can also increase profits substantially compared with nonspatial management, particularly if fishing costs are low, although profit increases available through optimal MPA-based management are roughly half those from fully optimized spatial management. However, if the same total area is protected by randomly placing MPAs, starkly contrasting results emerge: most random MPA designs reduce expected profits. The high value of spatial management estimated here supports continued interest in spatially explicit fisheries regulations but emphasizes that predicted increases in profits can only be achieved if the fishery is well understood and the regulations are strategically designed. PMID:22753469

Marine protected areas and the value of spatially optimized fishery management.

PubMed

Rassweiler, Andrew; Costello, Christopher; Siegel, David A

2012-07-17

There is a growing focus around the world on marine spatial planning, including spatial fisheries management. Some spatial management approaches are quite blunt, as when marine protected areas (MPAs) are established to restrict fishing in specific locations. Other management tools, such as zoning or spatial user rights, will affect the distribution of fishing effort in a more nuanced manner. Considerable research has focused on the ability of MPAs to increase fishery returns, but the potential for the broader class of spatial management approaches to outperform MPAs has received far less attention. We use bioeconomic models of seven nearshore fisheries in Southern California to explore the value of optimized spatial management in which the distribution of fishing is chosen to maximize profits. We show that fully optimized spatial management can substantially increase fishery profits relative to optimal nonspatial management but that the magnitude of this increase depends on characteristics of the fishing fleet and target species. Strategically placed MPAs can also increase profits substantially compared with nonspatial management, particularly if fishing costs are low, although profit increases available through optimal MPA-based management are roughly half those from fully optimized spatial management. However, if the same total area is protected by randomly placing MPAs, starkly contrasting results emerge: most random MPA designs reduce expected profits. The high value of spatial management estimated here supports continued interest in spatially explicit fisheries regulations but emphasizes that predicted increases in profits can only be achieved if the fishery is well understood and the regulations are strategically designed.

Comparison of two spatially-resolved fossil fuel CO2 emissions inventories at the urban scale in four US cities

NASA Astrophysics Data System (ADS)

Liang, J.; Gurney, K. R.; O'Keeffe, D.; Patarasuk, R.; Hutchins, M.; Rao, P.

2017-12-01

Spatially-resolved fossil fuel CO2 (FFCO2) emissions are used not only in complex atmospheric modeling systems as prior scenarios to simulate concentrations of CO2 in the atmosphere, but to improve understanding of relationships with socioeconomic factors in support of sustainability policymaking. We present a comparison of ODIAC, a top-down global gridded FFCO2 emissions dataset, and Hesita, a bottom-up FFCO2 emissions dataset, in four US cities, including Los Angles, Indianapolis, Salt Lake City and Baltimore City. ODIAC was developed by downscaling national total emissions to 1km-by-1km grid cells using satellite nightlight imagery as proxy. Hesita was built from the ground up by allocating sector-specific county-level emissions to urban-level spatial surrogates including facility locations, road maps, building footprints/parcels, railroad maps and shipping lanes. The differences in methodology and data sources could lead to large discrepancies in FFCO2 estimates at the urban scale, and these discrepancies need to be taken into account in conducting atmospheric modeling or socioeconomic analysis. This comparison work is aimed at quantifying the statistical and spatial difference between the two FFCO2 inventories. An analysis of the difference in total emissions, spatial distribution and statistical distribution resulted in the following findings: (1) ODIAC agrees well with Hestia in total FFCO2 emissions estimates across the four cities with a difference from 3%-20%; (2) Small-scale areal and linear spatial features such as roads and buildings are either entirely missing or not very well represented in ODIAC, since nightlight imagery might not be able to capture these information. This might further lead to underestimated on-road FFCO2 emissions in ODIAC; (3) The statistical distribution of ODIAC is more concentrated around the mean with much less samples in the lower range. These phenomena could result from the nightlight halo and saturation effects; (4) The grid-cell cumulative emissions of ODIAC appear in good agreement with that of Hestia, implying the two inventories have similar overall spatial structures at the city scale.

Can we improve streamflow simulation by using higher resolution rainfall information?

NASA Astrophysics Data System (ADS)

Lobligeois, Florent; Andréassian, Vazken; Perrin, Charles

2013-04-01

The catchment response to rainfall is the interplay between space-time variability of precipitation, catchment characteristics and antecedent hydrological conditions. Precipitation dominates the high frequency hydrological response, and its simulation is thus dependent on the way rainfall is represented. One of the characteristics which distinguishes distributed from lumped models is their ability to represent explicitly the spatial variability of precipitation and catchment characteristics. The sensitivity of runoff hydrographs to the spatial variability of forcing data has been a major concern of researchers over the last three decades. However, although the literature on the relationship between spatial rainfall and runoff response is abundant, results are contrasted and sometimes contradictory. Several studies concluded that including information on rainfall spatial distribution improves discharge simulation (e.g. Ajami et al., 2004, among others) whereas other studies showed the lack of significant improvement in simulations with better information on rainfall spatial pattern (e.g. Andréassian et al., 2004, among others). The difficulties to reach a clear consensus is mainly due to the fact that each modeling study is implemented only on a few catchments whereas the impact of the spatial distribution of rainfall on runoff is known to be catchment and event characteristics-dependent. Many studies are virtual experiments and only compare flow simulations, which makes it difficult to reach conclusions transposable to real-life case studies. Moreover, the hydrological rainfall-runoff models differ between the studies and the parameterization strategies sometimes tend to advantage the distributed approach (or the lumped one). Recently, Météo-France developed a rainfall reanalysis over the whole French territory at the 1-kilometer resolution and the hourly time step over a 10-year period combining radar data and raingauge measurements: weather radar data were corrected and adjusted with both hourly and daily raingauge data. Based on this new high resolution product, we propose a framework to evaluate the improvements in streamflow simulation by using higher resolution rainfall information. Semi-distributed modelling is performed for different spatial resolution of precipitation forcing: from lumped to semi-distributed simulations. Here we do not work on synthetic (simulated) streamflow, but with actual measurements, on a large set of 181 French catchments representing a variety of size and climate. The rainfall-runoff model is re-calibrated for each resolution of rainfall spatial distribution over a 5-year sub-period and evaluated on the complementary sub-period in validation mode. The results are analysed by catchment classes based on catchment area and for various types of rainfall events based on the spatial variability of precipitation. References Ajami, N. K., Gupta, H. V, Wagener, T. & Sorooshian, S. (2004) Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology 298(1-4), 112-135. Andréassian, V., Oddos, A., Michel, C., Anctil, F., Perrin, C. & Loumagne, C. (2004) Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall-runoff models: A theoretical study using chimera watersheds. Water Resources Research 40(5), 1-9.

MosquitoMap and the Mal-area calculator: new web tools to relate mosquito species distribution with vector borne disease

PubMed Central

2010-01-01

Background Mosquitoes are important vectors of diseases but, in spite of various mosquito faunistic surveys globally, there is a need for a spatial online database of mosquito collection data and distribution summaries. Such a resource could provide entomologists with the results of previous mosquito surveys, and vector disease control workers, preventative medicine practitioners, and health planners with information relating mosquito distribution to vector-borne disease risk. Results A web application called MosquitoMap was constructed comprising mosquito collection point data stored in an ArcGIS 9.3 Server/SQL geodatabase that includes administrative area and vector species x country lookup tables. In addition to the layer containing mosquito collection points, other map layers were made available including environmental, and vector and pathogen/disease distribution layers. An application within MosquitoMap called the Mal-area calculator (MAC) was constructed to quantify the area of overlap, for any area of interest, of vector, human, and disease distribution models. Data standards for mosquito records were developed for MosquitoMap. Conclusion MosquitoMap is a public domain web resource that maps and compares georeferenced mosquito collection points to other spatial information, in a geographical information system setting. The MAC quantifies the Mal-area, i.e. the area where it is theoretically possible for vector-borne disease transmission to occur, thus providing a useful decision tool where other disease information is limited. The Mal-area approach emphasizes the independent but cumulative contribution to disease risk of the vector species predicted present. MosquitoMap adds value to, and makes accessible, the results of past collecting efforts, as well as providing a template for other arthropod spatial databases. PMID:20167090

MosquitoMap and the Mal-area calculator: new web tools to relate mosquito species distribution with vector borne disease.

PubMed

Foley, Desmond H; Wilkerson, Richard C; Birney, Ian; Harrison, Stanley; Christensen, Jamie; Rueda, Leopoldo M

2010-02-18

Mosquitoes are important vectors of diseases but, in spite of various mosquito faunistic surveys globally, there is a need for a spatial online database of mosquito collection data and distribution summaries. Such a resource could provide entomologists with the results of previous mosquito surveys, and vector disease control workers, preventative medicine practitioners, and health planners with information relating mosquito distribution to vector-borne disease risk. A web application called MosquitoMap was constructed comprising mosquito collection point data stored in an ArcGIS 9.3 Server/SQL geodatabase that includes administrative area and vector species x country lookup tables. In addition to the layer containing mosquito collection points, other map layers were made available including environmental, and vector and pathogen/disease distribution layers. An application within MosquitoMap called the Mal-area calculator (MAC) was constructed to quantify the area of overlap, for any area of interest, of vector, human, and disease distribution models. Data standards for mosquito records were developed for MosquitoMap. MosquitoMap is a public domain web resource that maps and compares georeferenced mosquito collection points to other spatial information, in a geographical information system setting. The MAC quantifies the Mal-area, i.e. the area where it is theoretically possible for vector-borne disease transmission to occur, thus providing a useful decision tool where other disease information is limited. The Mal-area approach emphasizes the independent but cumulative contribution to disease risk of the vector species predicted present. MosquitoMap adds value to, and makes accessible, the results of past collecting efforts, as well as providing a template for other arthropod spatial databases.

Ectomycorrhizal-dominated boreal and tropical forests have distinct fungal communities, but analogous spatial patterns across soil horizons.

PubMed

McGuire, Krista L; Allison, Steven D; Fierer, Noah; Treseder, Kathleen K

2013-01-01

Fungi regulate key nutrient cycling processes in many forest ecosystems, but their diversity and distribution within and across ecosystems are poorly understood. Here, we examine the spatial distribution of fungi across a boreal and tropical ecosystem, focusing on ectomycorrhizal fungi. We analyzed fungal community composition across litter (organic horizons) and underlying soil horizons (0-20 cm) using 454 pyrosequencing and clone library sequencing. In both forests, we found significant clustering of fungal communities by site and soil horizons with analogous patterns detected by both sequencing technologies. Free-living saprotrophic fungi dominated the recently-shed leaf litter and ectomycorrhizal fungi dominated the underlying soil horizons. This vertical pattern of fungal segregation has also been found in temperate and European boreal forests, suggesting that these results apply broadly to ectomycorrhizal-dominated systems, including tropical rain forests. Since ectomycorrhizal and free-living saprotrophic fungi have different influences on soil carbon and nitrogen dynamics, information on the spatial distribution of these functional groups will improve our understanding of forest nutrient cycling.

Transport lattice models of heat transport in skin with spatially heterogeneous, temperature-dependent perfusion

PubMed Central

Gowrishankar, TR; Stewart, Donald A; Martin, Gregory T; Weaver, James C

2004-01-01

Background Investigation of bioheat transfer problems requires the evaluation of temporal and spatial distributions of temperature. This class of problems has been traditionally addressed using the Pennes bioheat equation. Transport of heat by conduction, and by temperature-dependent, spatially heterogeneous blood perfusion is modeled here using a transport lattice approach. Methods We represent heat transport processes by using a lattice that represents the Pennes bioheat equation in perfused tissues, and diffusion in nonperfused regions. The three layer skin model has a nonperfused viable epidermis, and deeper regions of dermis and subcutaneous tissue with perfusion that is constant or temperature-dependent. Two cases are considered: (1) surface contact heating and (2) spatially distributed heating. The model is relevant to the prediction of the transient and steady state temperature rise for different methods of power deposition within the skin. Accumulated thermal damage is estimated by using an Arrhenius type rate equation at locations where viable tissue temperature exceeds 42°C. Prediction of spatial temperature distributions is also illustrated with a two-dimensional model of skin created from a histological image. Results The transport lattice approach was validated by comparison with an analytical solution for a slab with homogeneous thermal properties and spatially distributed uniform sink held at constant temperatures at the ends. For typical transcutaneous blood gas sensing conditions the estimated damage is small, even with prolonged skin contact to a 45°C surface. Spatial heterogeneity in skin thermal properties leads to a non-uniform temperature distribution during a 10 GHz electromagnetic field exposure. A realistic two-dimensional model of the skin shows that tissue heterogeneity does not lead to a significant local temperature increase when heated by a hot wire tip. Conclusions The heat transport system model of the skin was solved by exploiting the mathematical analogy between local thermal models and local electrical (charge transport) models, thereby allowing robust, circuit simulation software to obtain solutions to Kirchhoff's laws for the system model. Transport lattices allow systematic introduction of realistic geometry and spatially heterogeneous heat transport mechanisms. Local representations for both simple, passive functions and more complex local models can be easily and intuitively included into the system model of a tissue. PMID:15548324

Remote Sensing of Spatial Distributions of Greenhouse Gases in the Los Angles Basin

NASA Technical Reports Server (NTRS)

Fu, Dejian; Pongetti, Thomas J.; Sander, Stanley P.; Cheung, Ross; Stutz, Jochen; Park, Chang Hyoun; Li, Qinbin

2011-01-01

The Los Angeles air basin is a significant anthropogenic source of greenhouse gases and pollutants including CO2, CH4, N2O, and CO, contributing significantly to regional and global climate change. Recent legislation in California, the California Global Warming Solutions Act (AB32), established a statewide cap for greenhouse gas emissions for 2020 based on 1990 emissions. Verifying the effectiveness of regional greenhouse gas emissions controls requires high-precision, regional-scale measurement methods combined with models that capture the principal anthropogenic and biogenic sources and sinks. We present a novel approach for monitoring the spatial distributions of greenhouse gases in the Los Angeles basin using high resolution remote sensing spectroscopy. We participated in the CalNex 2010 campaign to provide greenhouse gas distributions for comparison between top-down and bottom-up emission estimates.

Remote Sensing of Spatial Distributions of Greenhouse Gases in the Los Angeles Basin

NASA Technical Reports Server (NTRS)

Fu, Dejian; Sander, Stanley P.; Pongetti, Thomas J.; Cheung, Ross; Stutz, Jochen

2010-01-01

The Los Angeles air basin is a significant anthropogenic source of greenhouse gasses and pollutants including CO2, CH4, N2O, and CO, contributing significantly to regional and global climate change. Recent legislation in California, the California Global Warning Solutions Act (AB32), established a statewide cap for greenhouse gas emissions for 2020 based on 1990 emissions. Verifying the effectiveness of regional greenhouse gas emissions controls requires high-precision, regional-scale measurement methods combined with models that capture the principal anthropogenic and biogenic sources and sinks. We present a novel approach for monitoring the spatial distribution of greenhouse gases in the Los Angeles basin using high resolution remote sensing spectroscopy. We participated in the CalNex 2010 campaign to provide greenhouse gas distributions for comparison between top-down and bottom-up emission estimates.

Carrying capacity in a heterogeneous environment with habitat connectivity.

PubMed

Zhang, Bo; Kula, Alex; Mack, Keenan M L; Zhai, Lu; Ryce, Arrix L; Ni, Wei-Ming; DeAngelis, Donald L; Van Dyken, J David

2017-09-01

A large body of theory predicts that populations diffusing in heterogeneous environments reach higher total size than if non-diffusing, and, paradoxically, higher size than in a corresponding homogeneous environment. However, this theory and its assumptions have not been rigorously tested. Here, we extended previous theory to include exploitable resources, proving qualitatively novel results, which we tested experimentally using spatially diffusing laboratory populations of yeast. Consistent with previous theory, we predicted and experimentally observed that spatial diffusion increased total equilibrium population abundance in heterogeneous environments, with the effect size depending on the relationship between r and K. Refuting previous theory, however, we discovered that homogeneously distributed resources support higher total carrying capacity than heterogeneously distributed resources, even with species diffusion. Our results provide rigorous experimental tests of new and old theory, demonstrating how the traditional notion of carrying capacity is ambiguous for populations diffusing in spatially heterogeneous environments. © 2017 John Wiley & Sons Ltd/CNRS.

Carrying capacity in a heterogeneous environment with habitat connectivity

USGS Publications Warehouse

Zhang, Bo; Kula, Alex; Mack, Keenan M.L.; Zhai, Lu; Ryce, Arrix L.; Ni, Wei-Ming; DeAngelis, Donald L.; Van Dyken, J. David

2017-01-01

A large body of theory predicts that populations diffusing in heterogeneous environments reach higher total size than if non-diffusing, and, paradoxically, higher size than in a corresponding homogeneous environment. However, this theory and its assumptions have not been rigorously tested. Here, we extended previous theory to include exploitable resources, proving qualitatively novel results, which we tested experimentally using spatially diffusing laboratory populations of yeast. Consistent with previous theory, we predicted and experimentally observed that spatial diffusion increased total equilibrium population abundance in heterogeneous environments, with the effect size depending on the relationship between r and K. Refuting previous theory, however, we discovered that homogeneously distributed resources support higher total carrying capacity than heterogeneously distributed resources, even with species diffusion. Our results provide rigorous experimental tests of new and old theory, demonstrating how the traditional notion of carrying capacity is ambiguous for populations diffusing in spatially heterogeneous environments.

Evaluating the impact of sea surface temperature (SST) on spatial distribution of chlorophyll-a concentration in the East China Sea

NASA Astrophysics Data System (ADS)

Ji, Chenxu; Zhang, Yuanzhi; Cheng, Qiuming; Tsou, JinYeu; Jiang, Tingchen; Liang, X. San

2018-06-01

In this study, we analyze spatial and temporal sea surface temperature (SST) and chlorophylla (Chl-a) concentration in the East China Sea (ECS) during the period 2003-2016. Level 3 (4 km) monthly SST and Chl-a data from the Moderate Resolution Imaging Spectroradiometer Satellite (MODIS-Aqua) were reconstructed using the data interpolation empirical orthogonal function (DINEOF) method and used to evaluated the relationship between the two variables. The approaches employed included correlation analysis, regression analysis, and so forth. Our results show that certain strong oceanic SSTs affect Chl-a concentration, with particularly high correlation seen in the coastal area of Jiangsu and Zhejiang provinces. The mean temperature of the high correlated region was 18.67 °C. This finding may suggest that the SST has an important impact on the spatial distribution of Chl-a concentration in the ECS.

A flexible cure rate model for spatially correlated survival data based on generalized extreme value distribution and Gaussian process priors.

PubMed

Li, Dan; Wang, Xia; Dey, Dipak K

2016-09-01

Our present work proposes a new survival model in a Bayesian context to analyze right-censored survival data for populations with a surviving fraction, assuming that the log failure time follows a generalized extreme value distribution. Many applications require a more flexible modeling of covariate information than a simple linear or parametric form for all covariate effects. It is also necessary to include the spatial variation in the model, since it is sometimes unexplained by the covariates considered in the analysis. Therefore, the nonlinear covariate effects and the spatial effects are incorporated into the systematic component of our model. Gaussian processes (GPs) provide a natural framework for modeling potentially nonlinear relationship and have recently become extremely powerful in nonlinear regression. Our proposed model adopts a semiparametric Bayesian approach by imposing a GP prior on the nonlinear structure of continuous covariate. With the consideration of data availability and computational complexity, the conditionally autoregressive distribution is placed on the region-specific frailties to handle spatial correlation. The flexibility and gains of our proposed model are illustrated through analyses of simulated data examples as well as a dataset involving a colon cancer clinical trial from the state of Iowa. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Organismal and spatial partitioning of energy and macronutrient transformations within a hypersaline mat

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mobberley, Jennifer M.; Lindemann, Stephen R.; Bernstein, Hans C.

2017-03-21

Phototrophic mat communities are model ecosystems for studying energy cycling and elemental transformations because complete biogeochemical cycles occur over millimeter-to-centimeter scales. Characterization of energy and nutrient capture within hypersaline phototrophic mats has focused on specific processes and organisms, however little is known about community-wide distribution of and linkages between these processes. To investigate energy and macronutrient capture and flow through a structured community, the spatial and organismal distribution of metabolic functions within a compact hypersaline mat community from Hot Lake have been broadly elucidated through species-resolved metagenomics and geochemical, microbial diversity, and metabolic gradient measurements. Draft reconstructed genomes of abundantmore » organisms revealed three dominant cyanobacterial populations differentially distributed across the top layers of the mat suggesting niche separation along light and oxygen gradients. Many organisms contained diverse functional profiles, allowing for metabolic response to changing conditions within the mat. Organisms with partial nitrogen and sulfur metabolisms were widespread indicating dependence upon metabolite exchange. In addition, changes in community spatial structure were observed over the diel. These results indicate that organisms within the mat community have adapted to the temporally dynamic environmental gradients in this hypersaline mat through metabolic flexibility and fluid syntrophic interactions, including shifts in spatial arrangements.« less

Relations between Spatial Distribution, Social Affiliations and Dominance Hierarchy in a Semi-Free Mandrill Population

PubMed Central

Naud, Alexandre; Chailleux, Eloise; Kestens, Yan; Bret, Céline; Desjardins, Dominic; Petit, Odile; Ngoubangoye, Barthélémy; Sueur, Cédric

2016-01-01

Although there exist advantages to group-living in comparison to a solitary lifestyle, costs and gains of group-living may be unequally distributed among group members. Predation risk, vigilance levels and food intake may be unevenly distributed across group spatial geometry and certain within-group spatial positions may be more or less advantageous depending on the spatial distribution of these factors. In species characterized with dominance hierarchy, high-ranking individuals are commonly observed in advantageous spatial position. However, in complex social systems, individuals can develop affiliative relationships that may balance the effect of dominance relationships in individual's spatial distribution. The objective of the present study is to investigate how the group spatial distribution of a semi-free ranging colony of Mandrills relates to its social organization. Using spatial observations in an area surrounding the feeding zone, we tested the three following hypothesis: (1) does dominance hierarchy explain being observed in proximity or far from a food patch? (2) Do affiliative associations also explain being observed in proximity or far from a food patch? (3) Do the differences in rank in the group hierarchy explain being co-observed in proximity of a food patch? Our results showed that high-ranking individuals were more observed in proximity of the feeding zone while low-ranking individuals were more observed at the boundaries of the observation area. Furthermore, we observed that affiliative relationships were also associated with individual spatial distributions and explain more of the total variance of the spatial distribution in comparison with dominance hierarchy. Finally, we found that individuals observed at a same moment in proximity of the feeding zone were more likely to be distant in the hierarchy while controlling for maternal kinship, age and sex similarity. This study brings some elements about how affiliative networks and dominance hierarchy are related to spatial positions in primates. PMID:27199845

Relations between Spatial Distribution, Social Affiliations and Dominance Hierarchy in a Semi-Free Mandrill Population.

PubMed

Naud, Alexandre; Chailleux, Eloise; Kestens, Yan; Bret, Céline; Desjardins, Dominic; Petit, Odile; Ngoubangoye, Barthélémy; Sueur, Cédric

2016-01-01

Although there exist advantages to group-living in comparison to a solitary lifestyle, costs and gains of group-living may be unequally distributed among group members. Predation risk, vigilance levels and food intake may be unevenly distributed across group spatial geometry and certain within-group spatial positions may be more or less advantageous depending on the spatial distribution of these factors. In species characterized with dominance hierarchy, high-ranking individuals are commonly observed in advantageous spatial position. However, in complex social systems, individuals can develop affiliative relationships that may balance the effect of dominance relationships in individual's spatial distribution. The objective of the present study is to investigate how the group spatial distribution of a semi-free ranging colony of Mandrills relates to its social organization. Using spatial observations in an area surrounding the feeding zone, we tested the three following hypothesis: (1) does dominance hierarchy explain being observed in proximity or far from a food patch? (2) Do affiliative associations also explain being observed in proximity or far from a food patch? (3) Do the differences in rank in the group hierarchy explain being co-observed in proximity of a food patch? Our results showed that high-ranking individuals were more observed in proximity of the feeding zone while low-ranking individuals were more observed at the boundaries of the observation area. Furthermore, we observed that affiliative relationships were also associated with individual spatial distributions and explain more of the total variance of the spatial distribution in comparison with dominance hierarchy. Finally, we found that individuals observed at a same moment in proximity of the feeding zone were more likely to be distant in the hierarchy while controlling for maternal kinship, age and sex similarity. This study brings some elements about how affiliative networks and dominance hierarchy are related to spatial positions in primates.

Considering the Spatial Layout Information of Bag of Features (BoF) Framework for Image Classification.

PubMed

Mu, Guangyu; Liu, Ying; Wang, Limin

2015-01-01

The spatial pooling method such as spatial pyramid matching (SPM) is very crucial in the bag of features model used in image classification. SPM partitions the image into a set of regular grids and assumes that the spatial layout of all visual words obey the uniform distribution over these regular grids. However, in practice, we consider that different visual words should obey different spatial layout distributions. To improve SPM, we develop a novel spatial pooling method, namely spatial distribution pooling (SDP). The proposed SDP method uses an extension model of Gauss mixture model to estimate the spatial layout distributions of the visual vocabulary. For each visual word type, SDP can generate a set of flexible grids rather than the regular grids from the traditional SPM. Furthermore, we can compute the grid weights for visual word tokens according to their spatial coordinates. The experimental results demonstrate that SDP outperforms the traditional spatial pooling methods, and is competitive with the state-of-the-art classification accuracy on several challenging image datasets.

Wave actions and topography determine the small-scale spatial distribution of newly settled Asari clams Ruditapes philippinarum on a tidal flat

NASA Astrophysics Data System (ADS)

Nambu, Ryogen; Saito, Hajime; Tanaka, Yoshio; Higano, Junya; Kuwahara, Hisami

2012-03-01

There are many studies on spatial distributions of Asari clam Ruditapes philippinarum adults on tidal flats but few have dealt with spatial distributions of newly settled Asari clam (<0.3 mm shell length, indicative of settlement patterns) in relation to physical/topographical conditions on tidal flats. We examined small-scale spatial distributions of newly settled individuals on the Matsunase tidal flat, central Japan, during the low spring tides on two days 29th-30th June 2007, together with the shear stress from waves and currents on the flat. The characteristics of spatial distribution of newly settled Asari clam markedly varied depending on both of hydrodynamic and topographical conditions on the tidal flat. Using generalized linear models (GLMs), factors responsible for affecting newly settled Asari clam density and its spatial distribution were distinguished between sampling days, with "crest" sites always having a negative influence each on the density and the distribution on both sampling days. The continuously recorded data for the wave-current flows at the "crest" site on the tidal flat showed that newly settled Asari clam, as well as bottom sediment particles, at the "crest" site to be easily displaced. Small-scale spatial distributions of newly settled Asari clam changed with more advanced benthic stages in relation to the wave shear stress.

Spatial distributions of dose enhancement around a gold nanoparticle at several depths of proton Bragg peak

NASA Astrophysics Data System (ADS)

Kwon, Jihun; Sutherland, Kenneth; Hashimoto, Takayuki; Shirato, Hiroki; Date, Hiroyuki

2016-10-01

Gold nanoparticles (GNPs) have been recognized as a promising candidate for a radiation sensitizer. A proton beam incident on a GNP can produce secondary electrons, resulting in an enhancement of the dose around the GNP. However, little is known about the spatial distribution of dose enhancement around the GNP, especially in the direction along the incident proton. The purpose of this study is to determine the spatial distribution of dose enhancement by taking the incident direction into account. Two steps of calculation were conducted using the Geant4 Monte Carlo simulation toolkit. First, the energy spectra of 100 and 195 MeV protons colliding with a GNP were calculated at the Bragg peak and three other depths around the peak in liquid water. Second, the GNP was bombarded by protons with the obtained energy spectra. Radial dose distributions were computed along the incident beam direction. The spatial distributions of the dose enhancement factor (DEF) and subtracted dose (Dsub) were then evaluated. The spatial DEF distributions showed hot spots in the distal radial region from the proton beam axis. The spatial Dsub distribution isotropically spread out around the GNP. Low energy protons caused higher and wider dose enhancement. The macroscopic dose enhancement in clinical applications was also evaluated. The results suggest that the consideration of the spatial distribution of GNPs in treatment planning will maximize the potential of GNPs.

Spatial Distribution of Surface Soil Moisture in a Small Forested Catchment

EPA Science Inventory

Predicting the spatial distribution of soil moisture is an important hydrological question. We measured the spatial distribution of surface soil moisture (upper 6 cm) using an Amplitude Domain Reflectometry sensor at the plot scale (2 × 2 m) and small catchment scale (0.84 ha) in...

[Analysis of influence on spatial distribution of fishing ground for Antarctic krill fishery in the northern South Shetland Islands based on GWR model].

PubMed

Chen, Lyu Feng; Zhu, Guo Ping

2018-03-01

Based on Antarctic krill fishery and marine environmental data collected by scientific observers, using geographically weighted regression (GWR) model, we analyzed the effects of the factors with spatial attributes, i.e., depth of krill swarm (DKS) and distance from fishing position to shore (DTS), and sea surface temperature (SST), on the spatial distribution of fishing ground in the northern South Shetland Islands. The results showed that there was no significant aggregation in spatial distribution of catch per unit fishing effort (CPUE). Spatial autocorrelations (positive) among three factors were observed in 2010 and 2013, but were not in 2012 and 2016. Results from GWR model showed that the extent for the impacts on spatial distribution of CPUEs varied among those three factors, following the order DKS>SST>DTS. Compared to the DKS and DTS, the impact of SST on the spatial distribution of CPUEs presented adverse trend in the eastern and western parts of the South Shetland Islands. Negative correlations occurred for the spatial effects of DKS and DTS on distribution of CPUEs, though with inter-annual and regional variation. Our results provide metho-dological reference for researches on the underlying mechanism for fishing ground formation for Antarctic krill fishery.

Real-time distribution of pelagic fish: combining hydroacoustics, GIS and spatial modelling at a fine spatial scale.

PubMed

Muška, Milan; Tušer, Michal; Frouzová, Jaroslava; Mrkvička, Tomáš; Ricard, Daniel; Seďa, Jaromír; Morelli, Federico; Kubečka, Jan

2018-03-29

Understanding spatial distribution of organisms in heterogeneous environment remains one of the chief issues in ecology. Spatial organization of freshwater fish was investigated predominantly on large-scale, neglecting important local conditions and ecological processes. However, small-scale processes are of an essential importance for individual habitat preferences and hence structuring trophic cascades and species coexistence. In this work, we analysed the real-time spatial distribution of pelagic freshwater fish in the Římov Reservoir (Czechia) observed by hydroacoustics in relation to important environmental predictors during 48 hours at 3-h interval. Effect of diurnal cycle was revealed of highest significance in all spatial models with inverse trends between fish distribution and predictors in day and night in general. Our findings highlighted daytime pelagic fish distribution as highly aggregated, with general fish preferences for central, deep and highly illuminated areas, whereas nighttime distribution was more disperse and fish preferred nearshore steep sloped areas with higher depth. This turnover suggests prominent movements of significant part of fish assemblage between pelagic and nearshore areas on a diel basis. In conclusion, hydroacoustics, GIS and spatial modelling proved as valuable tool for predicting local fish distribution and elucidate its drivers, which has far reaching implications for understanding freshwater ecosystem functioning.

Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level Set Transformation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammond, Glenn Edward; Song, Xuehang; Ye, Ming

A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. Themore » spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.« less

Methodology to study the three-dimensional spatial distribution of prostate cancer and their dependence on clinical parameters

PubMed Central

Rojas, Kristians Diaz; Montero, Maria L.; Yao, Jorge; Messing, Edward; Fazili, Anees; Joseph, Jean; Ou, Yangming; Rubens, Deborah J.; Parker, Kevin J.; Davatzikos, Christos; Castaneda, Benjamin

2015-01-01

Abstract. A methodology to study the relationship between clinical variables [e.g., prostate specific antigen (PSA) or Gleason score] and cancer spatial distribution is described. Three-dimensional (3-D) models of 216 glands are reconstructed from digital images of whole mount histopathological slices. The models are deformed into one prostate model selected as an atlas using a combination of rigid, affine, and B-spline deformable registration techniques. Spatial cancer distribution is assessed by counting the number of tumor occurrences among all glands in a given position of the 3-D registered atlas. Finally, a difference between proportions is used to compare different spatial distributions. As a proof of concept, we compare spatial distributions from patients with PSA greater and less than 5  ng/ml and from patients older and younger than 60 years. Results suggest that prostate cancer has a significant difference in the right zone of the prostate between populations with PSA greater and less than 5  ng/ml. Age does not have any impact in the spatial distribution of the disease. The proposed methodology can help to comprehend prostate cancer by understanding its spatial distribution and how it changes according to clinical parameters. Finally, this methodology can be easily adapted to other organs and pathologies. PMID:26236756

Mesoscale Raised Rim Depressions (MRRDs) on Earth: A Review of the Characteristics, Processes, and Spatial Distributions of Analogs for Mars

NASA Technical Reports Server (NTRS)

Burr, Devon M.; Bruno, Barbara C.; Lanagan, Peter D.; Glaze, Lori; Jaeger, Windy L.; Soare, Richard J.; Tseung, Jean-Michel Wan Bun; Skinner, James A. Jr.; Baloga, Stephen M.

2008-01-01

Fields of mesoscale raised rim depressions (MRRDs) of various origins are found on Earth and Mars. Examples include rootless cones, mud volcanoes, collapsed pingos, rimmed kettle holes, and basaltic ring structures. Correct identification of MRRDs on Mars is valuable because different MRRD types have different geologic and/or climatic implications and are often associated with volcanism and/or water, which may provide locales for biotic or prebiotic activity. In order to facilitate correct identification of fields of MRRDs on Mars and their implications, this work provides a review of common terrestrial MRRD types that occur in fields. In this review, MRRDs by formation mechanism, including hydrovolcanic (phreatomagmatic cones, basaltic ring structures), sedimentological (mud volcanoes), and ice-related (pingos, volatile ice-block forms) mechanisms. For each broad mechanism, we present a comparative synopsis of (i) morphology and observations, (ii) physical formation processes, and (iii) published hypothesized locations on Mars. Because the morphology for MRRDs may be ambiguous, an additional tool is provided for distinguishing fields of MRRDs by origin on Mars, namely, spatial distribution analyses for MRRDs within fields on Earth. We find that MRRDs have both distinguishing and similar characteristics, and observation that applies both to their mesoscale morphology and to their spatial distribution statistics. Thus, this review provides tools for distinguishing between various MRRDs, while highlighting the utility of the multiple working hypotheses approach.

Interannual evolutions of (sub)mesoscale dynamics in the Bay of Biscay and the English Channel

NASA Astrophysics Data System (ADS)

Charria, G.; Vandermeirsch, F.; Theetten, S.; Yelekçi, Ö.; Assassi, C.; Audiffren, N. J.

2016-02-01

In a context of global change, ocean regions as the Bay of the Biscay and the English Channel represent key domains to estimate the local impact on the coasts of interannual evolutions. Indeed, the coastal (considering in this project regions above the continental shelf) and regional (including the continental slope and the abyssal plain) environments are sensitive to the long-term fluctuations driven by the open ocean, the atmosphere and the watersheds. These evolutions can have impacts on the whole ecosystem. To understand and, by extension, forecast evolutions of these ecosystems, we need to go further in the description and the analysis of the past interannual variability over decadal to pluri-decadal periods. This variability can be described at different spatial scales from small (< 1 km) to basin scales (> 100 km). With a focus on smaller scales, the modelled dynamics, using a Coastal Circulation Model on national computing resources (GENCI/CINES), is discussed from interannual simulations (10 to 53 years) with different spatial (4 km to 1 km) and vertical (40 to 100 sigma levels) resolutions compared with available in situ observations. Exploring vorticity and kinetic energy based diagnostics; dynamical patterns are described including the vertical distribution of the mesoscale activity. Despite the lack of deep and spatially distributed observations, present numerical experiments draw a first picture of the 3D mesoscale distribution and its evolution at interannual time scales.

Regional scale prioritisation for key ecosystem services, renewable energy production and urban development.

PubMed

Casalegno, Stefano; Bennie, Jonathan J; Inger, Richard; Gaston, Kevin J

2014-01-01

Although the importance of addressing ecosystem service benefits in regional land use planning and decision-making is evident, substantial practical challenges remain. In particular, methods to identify priority areas for the provision of key ecosystem services and other environmental services (benefits from the environment not directly linked to the function of ecosystems) need to be developed. Priority areas are locations which provide disproportionally high benefits from one or more service. Here we map a set of ecosystem and environmental services and delineate priority areas according to different scenarios. Each scenario is produced by a set of weightings allocated to different services and corresponds to different landscape management strategies which decision makers could undertake. Using the county of Cornwall, U.K., as a case study, we processed gridded maps of key ecosystem services and environmental services, including renewable energy production and urban development. We explored their spatial distribution patterns and their spatial covariance and spatial stationarity within the region. Finally we applied a complementarity-based priority ranking algorithm (zonation) using different weighting schemes. Our conclusions are that (i) there are two main patterns of service distribution in this region, clustered services (including agriculture, carbon stocks, urban development and plant production) and dispersed services (including cultural services, energy production and floods mitigation); (ii) more than half of the services are spatially correlated and there is high non-stationarity in the spatial covariance between services; and (iii) it is important to consider both ecosystem services and other environmental services in identifying priority areas. Different weighting schemes provoke drastic changes in the delineation of priority areas and therefore decision making processes need to carefully consider the relative values attributed to different services.

Regional Scale Prioritisation for Key Ecosystem Services, Renewable Energy Production and Urban Development

PubMed Central

Casalegno, Stefano; Bennie, Jonathan J.; Inger, Richard; Gaston, Kevin J.

2014-01-01

Although the importance of addressing ecosystem service benefits in regional land use planning and decision-making is evident, substantial practical challenges remain. In particular, methods to identify priority areas for the provision of key ecosystem services and other environmental services (benefits from the environment not directly linked to the function of ecosystems) need to be developed. Priority areas are locations which provide disproportionally high benefits from one or more service. Here we map a set of ecosystem and environmental services and delineate priority areas according to different scenarios. Each scenario is produced by a set of weightings allocated to different services and corresponds to different landscape management strategies which decision makers could undertake. Using the county of Cornwall, U.K., as a case study, we processed gridded maps of key ecosystem services and environmental services, including renewable energy production and urban development. We explored their spatial distribution patterns and their spatial covariance and spatial stationarity within the region. Finally we applied a complementarity-based priority ranking algorithm (zonation) using different weighting schemes. Our conclusions are that (i) there are two main patterns of service distribution in this region, clustered services (including agriculture, carbon stocks, urban development and plant production) and dispersed services (including cultural services, energy production and floods mitigation); (ii) more than half of the services are spatially correlated and there is high non-stationarity in the spatial covariance between services; and (iii) it is important to consider both ecosystem services and other environmental services in identifying priority areas. Different weighting schemes provoke drastic changes in the delineation of priority areas and therefore decision making processes need to carefully consider the relative values attributed to different services. PMID:25250775

Resolution of VTI anisotropy with elastic full-waveform inversion: theory and basic numerical examples

NASA Astrophysics Data System (ADS)

Podgornova, O.; Leaney, S.; Liang, L.

2018-07-01

Extracting medium properties from seismic data faces some limitations due to the finite frequency content of the data and restricted spatial positions of the sources and receivers. Some distributions of the medium properties make low impact on the data (including none). If these properties are used as the inversion parameters, then the inverse problem becomes overparametrized, leading to ambiguous results. We present an analysis of multiparameter resolution for the linearized inverse problem in the framework of elastic full-waveform inversion. We show that the spatial and multiparameter sensitivities are intertwined and non-sensitive properties are spatial distributions of some non-trivial combinations of the conventional elastic parameters. The analysis accounts for the Hessian information and frequency content of the data; it is semi-analytical (in some scenarios analytical), easy to interpret and enhances results of the widely used radiation pattern analysis. Single-type scattering is shown to have limited sensitivity, even for full-aperture data. Finite-frequency data lose multiparameter sensitivity at smooth and fine spatial scales. Also, we establish ways to quantify a spatial-multiparameter coupling and demonstrate that the theoretical predictions agree well with the numerical results.

GIS-based regionalized life cycle assessment: how big is small enough? Methodology and case study of electricity generation.

PubMed

Mutel, Christopher L; Pfister, Stephan; Hellweg, Stefanie

2012-01-17

We describe a new methodology for performing regionalized life cycle assessment and systematically choosing the spatial scale of regionalized impact assessment methods. We extend standard matrix-based calculations to include matrices that describe the mapping from inventory to impact assessment spatial supports. Uncertainty in inventory spatial data is modeled using a discrete spatial distribution function, which in a case study is derived from empirical data. The minimization of global spatial autocorrelation is used to choose the optimal spatial scale of impact assessment methods. We demonstrate these techniques on electricity production in the United States, using regionalized impact assessment methods for air emissions and freshwater consumption. Case study results show important differences between site-generic and regionalized calculations, and provide specific guidance for future improvements of inventory data sets and impact assessment methods.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Gul, M. Shahzeb Khan; Gunturk, Bahadir K.

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks.

PubMed

Gul, M Shahzeb Khan; Gunturk, Bahadir K

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

Oregon Cascades Play Fairway Analysis: Raster Datasets and Models

DOE Data Explorer

Adam Brandt

2015-11-15

This submission includes maps of the spatial distribution of basaltic, and felsic rocks in the Oregon Cascades. It also includes a final Play Fairway Analysis (PFA) model, with the heat and permeability composite risk segments (CRS) supplied separately. Metadata for each raster dataset can be found within the zip files, in the TIF images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Efroymson, Rebecca Ann; Dale, Virginia H; Kline, Keith L

Indicators of the environmental sustainability of biofuel production, distribution, and use should be selected, measured, and interpreted with respect to the context in which they are used. These indicators include measures of soil quality, water quality and quantity, greenhouse-gas emissions, biodiversity, air quality, and vegetation productivity. Contextual considerations include the purpose for the sustainability analysis, the particular biofuel production and distribution system (including supply chain, management aspects, and system viability), policy conditions, stakeholder values, location, temporal influences, spatial scale, baselines, and reference scenarios. Recommendations presented in this paper include formulating the problem for particular analyses, selecting appropriate context-specific indicators ofmore » environmental sustainability, and developing indicators that can reflect multiple environmental properties at low cost within a defined context. In addition, contextual considerations such as technical objectives, varying values and perspectives of stakeholder groups, and availability and reliability of data need to be understood and considered. Sustainability indicators for biofuels are most useful if adequate historical data are available, information can be collected at appropriate spatial and temporal scales, organizations are committed to use indicator information in the decision-making process, and indicators can effectively guide behavior toward more sustainable practices.« less

Comparing Spatial Distributions of Solar Prominence Mass Derived from Coronal Absorption

NASA Technical Reports Server (NTRS)

Gilbert, Holly; Kilper, Gary; Alexander, David; Kucera, Therese

2010-01-01

In the present work we extend the use of this mass-inference technique to a sample of prominences observed in at least two coronal lines. This approach, in theory, allows a direct calculation of prominence mass and helium abundance and how these properties vary spatially and temporally. Our motivation is two-fold: to obtain a He(exp 0)/H(exp 0) abundance ratio, and to determine how the relative spatial distribution of the two species varies in prominences. The first of these relies on the theoretical expectation that the amount of absorption at each EUV wavelength is well-characterized. However, in this work we show that due to a saturation of the continuum absorption in the 625 A and 368 A lines (which have much higher opacity compared to 195 A-) the uncertainties in obtaining the relative abundances are too high to give meaningful estimates. This is an important finding because of its impact on future studies in this area. The comparison of the spatial distribution of helium and hydrogen presented here augments previous observational work indicating that cross-field diffusion of neutrals is an important mechanism for mass loss. Significantly different loss timescales for neutral He and H (helium drains much more rapidly than hydrogen) can impact prominence structure, and both the present and past studies suggest this mechanism is playing a role in structure and possibly dynamics. Section 2 of this paper contains a description of the observations and Section 3 summarizes the method used to infer mass along with the criteria imposed in choosing prominences appropriate for this study. Section 3 also contains a discussion of the problems due to limitations of the available data and the implications for determining relative abundances. We present our results in Section 4, including plots of radial-like scans of prominence mass in different lines to show the spatial distribution of the different species. The last section contains a discussion summarizing the importance of the qualitative results found in this work. The Appendix provides a detailed derivation of how to obtain prominence mass and helium abundance (A 1) and includes the data for all prominences studied (A2).

SARANA: language, compiler and run-time system support for spatially aware and resource-aware mobile computing.

PubMed

Hari, Pradip; Ko, Kevin; Koukoumidis, Emmanouil; Kremer, Ulrich; Martonosi, Margaret; Ottoni, Desiree; Peh, Li-Shiuan; Zhang, Pei

2008-10-28

Increasingly, spatial awareness plays a central role in many distributed and mobile computing applications. Spatially aware applications rely on information about the geographical position of compute devices and their supported services in order to support novel functionality. While many spatial application drivers already exist in mobile and distributed computing, very little systems research has explored how best to program these applications, to express their spatial and temporal constraints, and to allow efficient implementations on highly dynamic real-world platforms. This paper proposes the SARANA system architecture, which includes language and run-time system support for spatially aware and resource-aware applications. SARANA allows users to express spatial regions of interest, as well as trade-offs between quality of result (QoR), latency and cost. The goal is to produce applications that use resources efficiently and that can be run on diverse resource-constrained platforms ranging from laptops to personal digital assistants and to smart phones. SARANA's run-time system manages QoR and cost trade-offs dynamically by tracking resource availability and locations, brokering usage/pricing agreements and migrating programs to nodes accordingly. A resource cost model permeates the SARANA system layers, permitting users to express their resource needs and QoR expectations in units that make sense to them. Although we are still early in the system development, initial versions have been demonstrated on a nine-node system prototype.

Disease spread across multiple scales in a spatial hierarchy: effect of host spatial structure and of inoculum quantity and distribution.

PubMed

Gosme, Marie; Lucas, Philippe

2009-07-01

Spatial patterns of both the host and the disease influence disease spread and crop losses. Therefore, the manipulation of these patterns might help improve control strategies. Considering disease spread across multiple scales in a spatial hierarchy allows one to capture important features of epidemics developing in space without using explicitly spatialized variables. Thus, if the system under study is composed of roots, plants, and planting hills, the effect of host spatial pattern can be studied by varying the number of plants per planting hill. A simulation model based on hierarchy theory was used to simulate the effects of large versus small planting hills, low versus high level of initial infections, and aggregated versus uniform distribution of initial infections. The results showed that aggregating the initially infected plants always resulted in slower epidemics than spreading out the initial infections uniformly. Simulation results also showed that, in most cases, disease epidemics were slower in the case of large host aggregates (100 plants/hill) than with smaller aggregates (25 plants/hill), except when the initially infected plants were both numerous and spread out uniformly. The optimal strategy for disease control depends on several factors, including initial conditions. More importantly, the model offers a framework to account for the interplay between the spatial characteristics of the system, rates of infection, and aggregation of the disease.

RockFall analyst: A GIS extension for three-dimensional and spatially distributed rockfall hazard modeling

NASA Astrophysics Data System (ADS)

Lan, Hengxing; Derek Martin, C.; Lim, C. H.

2007-02-01

Geographic information system (GIS) modeling is used in combination with three-dimensional (3D) rockfall process modeling to assess rockfall hazards. A GIS extension, RockFall Analyst (RA), which is capable of effectively handling large amounts of geospatial information relative to rockfall behaviors, has been developed in ArcGIS using ArcObjects and C#. The 3D rockfall model considers dynamic processes on a cell plane basis. It uses inputs of distributed parameters in terms of raster and polygon features created in GIS. Two major components are included in RA: particle-based rockfall process modeling and geostatistics-based rockfall raster modeling. Rockfall process simulation results, 3D rockfall trajectories and their velocity features either for point seeders or polyline seeders are stored in 3D shape files. Distributed raster modeling, based on 3D rockfall trajectories and a spatial geostatistical technique, represents the distribution of spatial frequency, the flying and/or bouncing height, and the kinetic energy of falling rocks. A distribution of rockfall hazard can be created by taking these rockfall characteristics into account. A barrier analysis tool is also provided in RA to aid barrier design. An application of these modeling techniques to a case study is provided. The RA has been tested in ArcGIS 8.2, 8.3, 9.0 and 9.1.

Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution.

PubMed

Alcala-Canto, Yazmin; Figueroa-Castillo, Juan Antonio; Ibarra-Velarde, Froylán; Vera-Montenegro, Yolanda; Cervantes-Valencia, María Eugenia; Salem, Abdelfattah Z M; Cuéllar-Ordaz, Jorge Alfredo

2018-05-07

The tick genus Ripicephalus (Boophilus), particularly R. microplus, is one of the most important ectoparasites that affects livestock health and considered an epidemiological risk because it causes significant economic losses due, mainly, to restrictions in the export of infested animals to several countries. Its spatial distribution has been tied to environmental factors, mainly warm temperatures and high relative humidity. In this work, we integrated a dataset consisting of 5843 records of Rhipicephalus spp., in Mexico covering close to 50 years to know which environmental variables mostly influence this ticks' distribution. Occurrences were georeferenced using the software DIVA-GIS and the potential current distribution was modelled using the maximum entropy method (Maxent). The algorithm generated a map of high predictive capability (Area under the curve = 0.942), providing the various contribution and permutation importance of the tested variables. Precipitation seasonality, particularly in March, and isothermality were found to be the most significant climate variables in determining the probability of spatial distribution of Rhipicephalus spp. in Mexico (15.7%, 36.0% and 11.1%, respectively). Our findings demonstrate that Rhipicephalus has colonized Mexico widely, including areas characterized by different types of climate. We conclude that the Maxent distribution model using Rhipicephalus records and a set of environmental variables can predict the extent of the tick range in this country, information that should support the development of integrated control strategies.

Spatial clustering of Borrelia burgdorferi sensu lato within populations of Allen's chipmunks and dusky-footed woodrats in northwestern California

PubMed Central

Brown, Richard N.; Fedorova, Natalia; Girard, Yvette A.; Higley, Mark; Clueit, Bernadette; Lane, Robert S.

2018-01-01

The ecology of Lyme borreliosis is complex in northwestern California, with several potential reservoir hosts, tick vectors, and genospecies of Borrelia burgdorferi sensu lato. The primary objective of this study was to determine the fine-scale spatial distribution of different genospecies in four rodent species, the California ground squirrel (Otospermophilus beecheyi), northern flying squirrel (Glaucomys sabrinus), dusky-footed woodrat (Neotoma fuscipes), and Allen’s chipmunk (Neotamias senex). Rodents were live-trapped between June 2004 and May 2005 at the Hoopa Valley Tribal Reservation (HVTR) in Humboldt County, California. Ear-punch biopsies obtained from each rodent were tested by polymerase chain reaction (PCR) and sequencing analysis. The programs ArcGIS and SaTScan were used to examine the spatial distribution of genospecies. Multinomial log-linear models were used to model habitat and host-specific characteristics and their effect on the presence of each borrelial genospecies. The Akaike information criterion (AICc) was used to compare models and determine model fit. Borrelia burgdorferi sensu stricto was primarily associated with chipmunks and B. bissettiae largely with woodrats. The top model included the variables “host species”, “month”, and “elevation” (weight = 0.84). Spatial clustering of B. bissettiae was detected in the northwestern section of the HVTR, whereas B. burgdorferi sensu stricto was clustered in the southeastern section. We conclude that the spatial distribution of these borreliae are driven at least in part by host species, time-of-year, and elevation. PMID:29634745

Spatial clustering of Borrelia burgdorferi sensu lato within populations of Allen's chipmunks and dusky-footed woodrats in northwestern California.

PubMed

Hacker, Gregory M; Brown, Richard N; Fedorova, Natalia; Girard, Yvette A; Higley, Mark; Clueit, Bernadette; Lane, Robert S

2018-01-01

The ecology of Lyme borreliosis is complex in northwestern California, with several potential reservoir hosts, tick vectors, and genospecies of Borrelia burgdorferi sensu lato. The primary objective of this study was to determine the fine-scale spatial distribution of different genospecies in four rodent species, the California ground squirrel (Otospermophilus beecheyi), northern flying squirrel (Glaucomys sabrinus), dusky-footed woodrat (Neotoma fuscipes), and Allen's chipmunk (Neotamias senex). Rodents were live-trapped between June 2004 and May 2005 at the Hoopa Valley Tribal Reservation (HVTR) in Humboldt County, California. Ear-punch biopsies obtained from each rodent were tested by polymerase chain reaction (PCR) and sequencing analysis. The programs ArcGIS and SaTScan were used to examine the spatial distribution of genospecies. Multinomial log-linear models were used to model habitat and host-specific characteristics and their effect on the presence of each borrelial genospecies. The Akaike information criterion (AICc) was used to compare models and determine model fit. Borrelia burgdorferi sensu stricto was primarily associated with chipmunks and B. bissettiae largely with woodrats. The top model included the variables "host species", "month", and "elevation" (weight = 0.84). Spatial clustering of B. bissettiae was detected in the northwestern section of the HVTR, whereas B. burgdorferi sensu stricto was clustered in the southeastern section. We conclude that the spatial distribution of these borreliae are driven at least in part by host species, time-of-year, and elevation.

[Correlative analysis of the diversity patterns of regional surface water, NDVI and thermal environment].

PubMed

Duan, Jin-Long; Zhang, Xue-Lei

2012-10-01

Taking Zhengzhou City, the capital of Henan Province in Central China, as the study area, and by using the theories and methodologies of diversity, a discreteness evaluation on the regional surface water, normalized difference vegetation index (NDVI), and land surface temperature (LST) distribution was conducted in a 2 km x 2 km grid scale. Both the NDVI and the LST were divided into 4 levels, their spatial distribution diversity indices were calculated, and their connections were explored. The results showed that it was of operability and practical significance to use the theories and methodologies of diversity in the discreteness evaluation of the spatial distribution of regional thermal environment. There was a higher overlap of location between the distributions of surface water and the lowest temperature region, and the high vegetation coverage was often accompanied by low land surface temperature. In 1988-2009, the discreteness of the surface water distribution in the City had an obvious decreasing trend. The discreteness of the surface water distribution had a close correlation with the discreteness of the temperature region distribution, while the discreteness of the NDVI classification distribution had a more complicated correlation with the discreteness of the temperature region distribution. Therefore, more environmental factors were needed to be included for a better evaluation.

Spatial and temporal distribution of trunk-injected imidacloprid in apple tree canopies.

PubMed

Aćimović, Srđan G; VanWoerkom, Anthony H; Reeb, Pablo D; Vandervoort, Christine; Garavaglia, Thomas; Cregg, Bert M; Wise, John C

2014-11-01

Pesticide use in orchards creates drift-driven pesticide losses which contaminate the environment. Trunk injection of pesticides as a target-precise delivery system could greatly reduce pesticide losses. However, pesticide efficiency after trunk injection is associated with the underinvestigated spatial and temporal distribution of the pesticide within the tree crown. This study quantified the spatial and temporal distribution of trunk-injected imidacloprid within apple crowns after trunk injection using one, two, four or eight injection ports per tree. The spatial uniformity of imidacloprid distribution in apple crowns significantly increased with more injection ports. Four ports allowed uniform spatial distribution of imidacloprid in the crown. Uniform and non-uniform spatial distributions were established early and lasted throughout the experiment. The temporal distribution of imidacloprid was significantly non-uniform. Upper and lower crown positions did not significantly differ in compound concentration. Crown concentration patterns indicated that imidacloprid transport in the trunk occurred through radial diffusion and vertical uptake with a spiral pattern. By showing where and when a trunk-injected compound is distributed in the apple tree canopy, this study addresses a key knowledge gap in terms of explaining the efficiency of the compound in the crown. These findings allow the improvement of target-precise pesticide delivery for more sustainable tree-based agriculture. © 2014 Society of Chemical Industry.

Spatial disparity in the distribution of superfund sites in South Carolina: an ecological study

PubMed Central

2013-01-01

Background According to the US Environmental Protection Agency (EPA), Superfund is a federal government program implemented to clean up uncontrolled hazardous waste sites. Twenty-six sites in South Carolina (SC) have been included on the National Priorities List (NPL), which has serious human health and environmental implications. The purpose of this study was to assess spatial disparities in the distribution of Superfund sites in SC. Methods The 2000 US census tract and block level data were used to generate population characteristics, which included race/ethnicity, socioeconomic status (SES), education, home ownership, and home built before 1950. Geographic Information Systems (GIS) were used to map Superfund facilities and develop choropleth maps based on the aforementioned sociodemographic variables. Spatial methods, including mean and median distance analysis, buffer analysis, and spatial approximation were employed to characterize burden disparities. Regression analysis was performed to assess the relationship between the number of Superfund facilities and population characteristics. Results Spatial coincidence results showed that of the 29.5% of Blacks living in SC, 55.9% live in Superfund host census tracts. Among all populations in SC living below poverty (14.2%), 57.2% were located in Superfund host census tracts. Buffer analyses results (0.5mi, 1.0mi, 5.0mi, 0.5km, 1.0km, and 5.0km) showed a higher percentage of Whites compared to Blacks hosting a Superfund facility. Conversely, a slightly higher percentage of Blacks hosted (30.2%) a Superfund facility than those not hosting (28.8%) while their White counterparts had more equivalent values (66.7% and 67.8%, respectively). Regression analyses in the reduced model (Adj. R2 = 0.038) only explained a small percentage of the variance. In addition, the mean distance for percent of Blacks in the 90th percentile for Superfund facilities was 0.48mi. Conclusion Burden disparities exist in the distribution of Superfund facilities in SC at the block and census tract levels across varying levels of demographic composition for race/ethnicity and SES. PMID:24195573

Modeling evolution of spatially distributed bacterial communities: a simulation with the haploid evolutionary constructor

PubMed Central

2015-01-01

Background Multiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members. Results Haploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate. Conclusion In spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members. PMID:25708911

Spatial patterns, ecological niches, and interspecific competition of avian brood parasites: inferring from a case study of Korea.

PubMed

Lee, Jin-Won; Noh, Hee-Jin; Lee, Yunkyoung; Kwon, Young-Soo; Kim, Chang-Hoe; Yoo, Jeong-Chil

2014-09-01

Since obligate avian brood parasites depend completely on the effort of other host species for rearing their progeny, the availability of hosts will be a critical resource for their life history. Circumstantial evidence suggests that intense competition for host species may exist not only within but also between species. So far, however, few studies have demonstrated whether the interspecific competition really occurs in the system of avian brood parasitism and how the nature of brood parasitism is related to their niche evolution. Using the occurrence data of five avian brood parasites from two sources of nationwide bird surveys in South Korea and publically available environmental/climatic data, we identified their distribution patterns and ecological niches, and applied species distribution modeling to infer the effect of interspecific competition on their spatial distribution. We found that the distribution patterns of five avian brood parasites could be characterized by altitude and climatic conditions, but overall their spatial ranges and ecological niches extensively overlapped with each other. We also found that the predicted distribution areas of each species were generally comparable to the realized distribution areas, and the numbers of individuals in areas where multiple species were predicted to coexist showed positive relationships among species. In conclusion, despite following different coevolutionary trajectories to adapt to their respect host species, five species of avian brood parasites breeding in South Korea occupied broadly similar ecological niches, implying that they tend to conserve ancestral preferences for ecological conditions. Furthermore, our results indicated that contrary to expectation interspecific competition for host availability between avian brood parasites seemed to be trivial, and thus, play little role in shaping their spatial distributions and ecological niches. Future studies, including the complete ranges of avian brood parasites and ecological niches of host species, will be worthwhile to further elucidate these issues.

The effects of plasma inhomogeneity on the nanoparticle coating in a low pressure plasma reactor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pourali, N.; Foroutan, G.

2015-10-15

A self-consistent model is used to study the surface coating of a collection of charged nanoparticles trapped in the sheath region of a low pressure plasma reactor. The model consists of multi-fluid plasma sheath module, including nanoparticle dynamics, as well as the surface deposition and particle heating modules. The simulation results show that the mean particle radius increases with time and the nanoparticle size distribution is broadened. The mean radius is a linear function of time, while the variance exhibits a quadratic dependence. The broadening in size distribution is attributed to the spatial inhomogeneity of the deposition rate which inmore » turn depends on the plasma inhomogeneity. The spatial inhomogeneity of the ions has strong impact on the broadening of the size distribution, as the ions contribute both in the nanoparticle charging and in direct film deposition. The distribution width also increases with increasing of the pressure, gas temperature, and the ambient temperature gradient.« less

Investigation of the Reactions and Distribution of Polycyclic Aromatic Hydrocarbons and Fullerenes in Extraterrestrial Material

NASA Technical Reports Server (NTRS)

Zare, Richard N.

2005-01-01

The work funded by this research grant includes four specific projects: (1) Mapping the spatial distribution of polycyclic aromatic hydrocarbons (PAHs) in a variety of meteoritic samples and comparing this distribution with mineralogical features of the meteorite to determine whether a correlation exists between the two. (2) Developing a method for detection of fullerenes in extraterrestrial samples using microprobe laser-desorption laser-ionization mass spectrometry ( pL2MS) and utilizing this technique to investigate fullerene presence, while exploring the possibility of spatially mapping the fullerene distribution in these samples through in situ detection. (3) Investigating a possible formation pathway for meteoritic and ancient terrestrial kerogen involving the photochemical reactions of PAHs with alkanes under prebiotic and astrophysically relevant conditions. (4) Studying reaction pathways and identifying the photoproducts generated during the photochemical evolution of PAH-containing interstellar ice analogs as part of an ongoing collaboration with researchers at the Astrochemistry Lab at NASA Ames.

Another look at the question of density and rail transit.

DOT National Transportation Integrated Search

2011-07-01

Long community discussions about rail often include whether a citys spatial distribution of : housing, employment and other trip generators is conducive to supporting rail transit. A citys : decision to construct rail transit is based on an arr...

Attenuation Modified by DIG and Dust as Seen in M31

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tomičić, Neven; Kreckel, Kathryn; Schinnerer, Eva

The spatial distribution of dust in galaxies affects the global attenuation, and hence inferred properties, of galaxies. We trace the spatial distribution of dust in five approximately kiloparsec fields of M31 by comparing optical attenuation with the total dust mass distribution. We measure the attenuation from the Balmer decrement using Integral Field Spectroscopy and the dust mass from Herschel far-IR observations. Our results show that M31's dust attenuation closely follows a foreground screen model, contrary to what was previously found in other nearby galaxies. By smoothing the M31 data, we find that spatial resolution is not the cause for thismore » difference. Based on the emission-line ratios and two simple models, we conclude that previous models of dust/gas geometry need to include a weakly or non-attenuated diffuse ionized gas (DIG) component. Due to the variation of dust and DIG scale heights with galactic radius, we conclude that different locations in galaxies will have different vertical distributions of gas and dust and therefore different measured attenuation. The difference between our result in M31 with that found in other nearby galaxies can be explained by our fields in M31 lying at larger galactic radii than the previous studies that focused on the centers of galaxies.« less

What Is Better Than Coulomb Failure Stress? A Ranking of Scalar Static Stress Triggering Mechanisms from 105 Mainshock-Aftershock Pairs

NASA Astrophysics Data System (ADS)

Meade, Brendan J.; DeVries, Phoebe M. R.; Faller, Jeremy; Viegas, Fernanda; Wattenberg, Martin

2017-11-01

Aftershocks may be triggered by the stresses generated by preceding mainshocks. The temporal frequency and maximum size of aftershocks are well described by the empirical Omori and Bath laws, but spatial patterns are more difficult to forecast. Coulomb failure stress is perhaps the most common criterion invoked to explain spatial distributions of aftershocks. Here we consider the spatial relationship between patterns of aftershocks and a comprehensive list of 38 static elastic scalar metrics of stress (including stress tensor invariants, maximum shear stress, and Coulomb failure stress) from 213 coseismic slip distributions worldwide. The rates of true-positive and false-positive classification of regions with and without aftershocks are assessed with receiver operating characteristic analysis. We infer that the stress metrics that are most consistent with observed aftershock locations are maximum shear stress and the magnitude of the second and third invariants of the stress tensor. These metrics are significantly better than random assignment at a significance level of 0.005 in over 80% of the slip distributions. In contrast, the widely used Coulomb failure stress criterion is distinguishable from random assignment in only 51-64% of the slip distributions. These results suggest that a number of alternative scalar metrics are better predictors of aftershock locations than classic Coulomb failure stress change.

Attenuation Modified by DIG and Dust as Seen in M31

NASA Astrophysics Data System (ADS)

Tomičić, Neven; Kreckel, Kathryn; Groves, Brent; Schinnerer, Eva; Sandstrom, Karin; Kapala, Maria; Blanc, Guillermo A.; Leroy, Adam

2017-08-01

The spatial distribution of dust in galaxies affects the global attenuation, and hence inferred properties, of galaxies. We trace the spatial distribution of dust in five approximately kiloparsec fields of M31 by comparing optical attenuation with the total dust mass distribution. We measure the attenuation from the Balmer decrement using Integral Field Spectroscopy and the dust mass from Herschel far-IR observations. Our results show that M31's dust attenuation closely follows a foreground screen model, contrary to what was previously found in other nearby galaxies. By smoothing the M31 data, we find that spatial resolution is not the cause for this difference. Based on the emission-line ratios and two simple models, we conclude that previous models of dust/gas geometry need to include a weakly or non-attenuated diffuse ionized gas (DIG) component. Due to the variation of dust and DIG scale heights with galactic radius, we conclude that different locations in galaxies will have different vertical distributions of gas and dust and therefore different measured attenuation. The difference between our result in M31 with that found in other nearby galaxies can be explained by our fields in M31 lying at larger galactic radii than the previous studies that focused on the centers of galaxies.

The seven sisters DANCe. III. Projected spatial distribution

NASA Astrophysics Data System (ADS)

Olivares, J.; Moraux, E.; Sarro, L. M.; Bouy, H.; Berihuete, A.; Barrado, D.; Huelamo, N.; Bertin, E.; Bouvier, J.

2018-04-01

Context. Membership analyses of the DANCe and Tycho + DANCe data sets provide the largest and least contaminated sample of Pleiades candidate members to date. Aims: We aim at reassessing the different proposals for the number surface density of the Pleiades in the light of the new and most complete list of candidate members, and inferring the parameters of the most adequate model. Methods: We compute the Bayesian evidence and Bayes Factors for variations of the classical radial models. These include elliptical symmetry, and luminosity segregation. As a by-product of the model comparison, we obtain posterior distributions for each set of model parameters. Results: We find that the model comparison results depend on the spatial extent of the region used for the analysis. For a circle of 11.5 parsecs around the cluster centre (the most homogeneous and complete region), we find no compelling reason to abandon King's model, although the Generalised King model introduced here has slightly better fitting properties. Furthermore, we find strong evidence against radially symmetric models when compared to the elliptic extensions. Finally, we find that including mass segregation in the form of luminosity segregation in the J band is strongly supported in all our models. Conclusions: We have put the question of the projected spatial distribution of the Pleiades cluster on a solid probabilistic framework, and inferred its properties using the most exhaustive and least contaminated list of Pleiades candidate members available to date. Our results suggest however that this sample may still lack about 20% of the expected number of cluster members. Therefore, this study should be revised when the completeness and homogeneity of the data can be extended beyond the 11.5 parsecs limit. Such a study will allow for more precise determination of the Pleiades spatial distribution, its tidal radius, ellipticity, number of objects and total mass.

Environmental determinants of the spatial distribution of Angiostrongylus vasorum, Crenosoma vulpis and Eucoleus aerophilus in Hungary.

PubMed

Tolnai, Z; Széll, Z; Sréter, T

2015-01-30

Angiostrongylus vasorum, Crenosoma vulpis and Eucoleus aerophilus (syn. Capillaria aerophila) are the most important lungworm species infecting wild and domesticated canids in Europe. To investigate the spatial distribution of these parasites and the factors influencing their circulation in the fox populations, 937 red foxes (Vulpes vulpes) were tested for lungworm infection in Hungary. The prevalence of A. vasorum, C. vulpis and E. aerophilus infection was high (17.9, 24.6 and 61.7%). The distribution pattern of infection in foxes and the relationship of this pattern with landscape and climate was analyzed by geographic information system. Based on the analysis, the annual precipitation was the major determinant of the spatial distribution of A. vasorum and C. vulpis and E. aerophilus. Nevertheless, the mean annual temperature also influenced the distribution of A. vasorum and E. aerophilus. The positive relationship with annual precipitation and the negative relationship with mean annual temperature can be attributed to the sensitivity of larvae, eggs and intermediate hosts (snails and slugs) of lungworms for desiccation. Based on the highly clumped distribution of A. vasorum and C. vulpis, the indirect life cycle (larvae, slugs and snails) of these parasites seems to be particularly sensitive for environmental effects. The distribution of E. aerophilus was considerably less clumped indicating a lower sensitivity of the direct life cycle (eggs) of this parasite for environmental factors. Based on these results, lungworm infections in canids including dogs can be expected mainly in relatively wet and cool areas. Copyright © 2014 Elsevier B.V. All rights reserved.

The spatial distribution of pet dogs and pet cats on the island of Ireland

PubMed Central

2011-01-01

Background There is considerable international research regarding the link between human demographics and pet ownership. In several international studies, pet ownership was associated with household demographics including: the presence of children in the household, urban/rural location, level of education and age/family structure. What is lacking across all these studies, however, is an understanding of how these pets are spatially distributed throughout the regions under study. This paper describes the spatial distribution of pet dog and pet cat owning households on the island of Ireland. Results In 2006, there were an estimated 640,620 pet dog owning households and 215,542 pet cat owning households in Ireland. These estimates are derived from logistic regression modelling, based on household composition to determine pet dog ownership and the type of house to determine pet cat ownership. Results are presented using chloropleth maps. There is a higher density of pet dog owning households in the east of Ireland and in the cities than the west of Ireland and rural areas. However, in urban districts there are a lower proportion of households owning pet dogs than in rural districts. There are more households with cats in the urban areas, but the proportion of households with cats is greater in rural areas. Conclusions The difference in spatial distribution of dog ownership is a reflection of a generally higher density of households in the east of Ireland and in major cities. The higher proportion of ownership in the west is understandable given the higher proportion of farmers and rural dwellings in this area. Spatial representation allows us to visualise the impact of human household distribution on the density of both pet dogs and pet cats on the island of Ireland. This information can be used when analysing risk of disease spread, for market research and for instigating veterinary care. PMID:21663606

Examining spatiotemporal distribution and CPUE-environment relationships for the jumbo flying squid Dosidicus gigas offshore Peru based on spatial autoregressive model

NASA Astrophysics Data System (ADS)

Feng, Yongjiu; Chen, Xinjun; Liu, Yang

2017-09-01

The spatiotemporal distribution and relationship between nominal catch-per-unit-effort (CPUE) and environment for the jumbo flying squid (Dosidicus gigas) were examined in offshore Peruvian waters during 2009-2013. Three typical oceanographic factors affecting the squid habitat were investigated in this research, including sea surface temperature (SST), sea surface salinity (SSS) and sea surface height (SSH). We studied the CPUE-environment relationships for D. gigas using a spatially-lagged version of spatial autoregressive (SAR) model and a generalized additive model (GAM), with the latter for auxiliary and comparative purposes. The annual fishery centroids were distributed broadly in an area bounded by 79.5°-82.7°W and 11.9°-17.1°S, while the monthly fishery centroids were spatially close and lay in a smaller area bounded by 81.0°-81.2°W and 14.3°-15.4°S. Our results show that the preferred environmental ranges for D. gigas offshore Peru were 20.9°-21.9°C for SST, 35.16-35.32 for SSS and 27.2-31.5 cm for SSH in the areas bounded by 78°-80°W/82-84°W and 15°-18°S. Monthly spatial distributions during October to December were predicted using the calibrated GAM and SAR models and general similarities were found between the observed and predicted patterns for the nominal CPUE of D. gigas. The overall accuracies for the hotspots generated by the SAR model were much higher than those produced by the GAM model for all three months. Our results contribute to a better understanding of the spatiotemporal distributions of D. gigas offshore Peru, and offer a new SAR modeling method for advancing fishery science.

Competitive exclusion over broad spatial extents is a slow process: Evidence and implications for species distribution modeling

USGS Publications Warehouse

Yackulic, Charles B.

2016-01-01

There is considerable debate about the role of competition in shaping species distributions over broad spatial extents. This debate has practical implications because predicting changes in species' geographic ranges in response to ongoing environmental change would be simpler if competition could be ignored. While this debate has been the subject of many reviews, recent literature has not addressed the rates of relevant processes. This omission is surprising in that ecologists hypothesized decades ago that regional competitive exclusion is a slow process. The goal of this review is to reassess the debate under the hypothesis that competitive exclusion over broad spatial extents is a slow process.Available evidence, including simulations presented for the first time here, suggests that competitive exclusion over broad spatial extents occurs slowly over temporal extents of many decades to millennia. Ecologists arguing against an important role for competition frequently study modern patterns and/or range dynamics over periods of decades, while much of the evidence for competition shaping geographic ranges at broad spatial extents comes from paleoecological studies over time scales of centuries or longer. If competition is slow, as evidence suggests, the geographic distributions of some, perhaps many species, would continue to change over time scales of decades to millennia, even if environmental conditions did not continue to change. If the distributions of competing species are at equilibrium it is possible to predict species distributions based on observed species–environment relationships. However, disequilibrium is widespread as a result of competition and many other processes. Studies whose goal is accurate predictions over intermediate time scales (decades to centuries) should focus on factors associated with range expansion (colonization) and loss (local extinction), as opposed to current patterns. In general, understanding of modern range dynamics would be enhanced by considering the rates of relevant processes.

The spatial distribution of pet dogs and pet cats on the island of Ireland.

PubMed

Downes, Martin J; Clegg, Tracy A; Collins, Daniel M; McGrath, Guy; More, Simon J

2011-06-10

There is considerable international research regarding the link between human demographics and pet ownership. In several international studies, pet ownership was associated with household demographics including: the presence of children in the household, urban/rural location, level of education and age/family structure. What is lacking across all these studies, however, is an understanding of how these pets are spatially distributed throughout the regions under study. This paper describes the spatial distribution of pet dog and pet cat owning households on the island of Ireland. In 2006, there were an estimated 640,620 pet dog owning households and 215,542 pet cat owning households in Ireland. These estimates are derived from logistic regression modelling, based on household composition to determine pet dog ownership and the type of house to determine pet cat ownership. Results are presented using chloropleth maps. There is a higher density of pet dog owning households in the east of Ireland and in the cities than the west of Ireland and rural areas. However, in urban districts there are a lower proportion of households owning pet dogs than in rural districts. There are more households with cats in the urban areas, but the proportion of households with cats is greater in rural areas. The difference in spatial distribution of dog ownership is a reflection of a generally higher density of households in the east of Ireland and in major cities. The higher proportion of ownership in the west is understandable given the higher proportion of farmers and rural dwellings in this area. Spatial representation allows us to visualise the impact of human household distribution on the density of both pet dogs and pet cats on the island of Ireland. This information can be used when analysing risk of disease spread, for market research and for instigating veterinary care.

Impact of urban built environment on urban short-distance taxi travel: the case of Shanghai

NASA Astrophysics Data System (ADS)

Wu, Zhuoye; Zhuo, Jian

2018-05-01

The excessive individual motorized transport is the main cause of urban congestion and generates negative consequences on urban environmental quality, energy consumption, infrastructure supply and urban security. Bicycle can compete effectively with automobile for short-distance travels within 3km. If we take action to encourage the rider to shift from automobile to bike for the short-distance travels, it leaves us a great chance to reduce the modal share of individual motorized mode. This paper focus on the spatial impact of built environment on short-distance taxi riders’ travel behaviour. The data sources include taxi trajectory data for a week, demographic data of the Sixth National Census, POI data. In this paper, we figure out the volumes and spatial distribution of short-distance taxi travel in the central city of Shanghai. We build a multiple regression model to quantitative analyze the impact of urban built environment on urban short-distance taxi travel. The findings explain the spatial distribution short-distance taxi travel. In the conclusion, some advice are provided on how planners change the spatial settings to discourage short-distance individual motorized travel.

Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

NASA Astrophysics Data System (ADS)

Gaitan, S.; ten Veldhuis, J. A. E.

2015-06-01

Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

Characterization of spatial distribution of Tetranychus urticae in peppermint in California and implication for improving sampling plan.

PubMed

Rijal, Jhalendra P; Wilson, Rob; Godfrey, Larry D

2016-02-01

Twospotted spider mite, Tetranychus urticae Koch, is an important pest of peppermint in California, USA. Spider mite feeding on peppermint leaves causes physiological changes in the plant, which coupling with the favorable environmental condition can lead to increased mite infestations. Significant yield loss can occur in absence of pest monitoring and timely management. Understating the within-field spatial distribution of T. urticae is critical for the development of reliable sampling plan. The study reported here aims to characterize the spatial distribution of mite infestation in four commercial peppermint fields in northern California using spatial techniques, variogram and Spatial Analysis by Distance IndicEs (SADIE). Variogram analysis revealed that there was a strong evidence for spatially dependent (aggregated) mite population in 13 of 17 sampling dates and the physical distance of the aggregation reached maximum to 7 m in peppermint fields. Using SADIE, 11 of 17 sampling dates showed aggregated distribution pattern of mite infestation. Combining results from variogram and SADIE analysis, the spatial aggregation of T. urticae was evident in all four fields for all 17 sampling dates evaluated. Comparing spatial association using SADIE, ca. 62% of the total sampling pairs showed a positive association of mite spatial distribution patterns between two consecutive sampling dates, which indicates a strong spatial and temporal stability of mite infestation in peppermint fields. These results are discussed in relation to behavior of spider mite distribution within field, and its implications for improving sampling guidelines that are essential for effective pest monitoring and management.

Thematic and spatial resolutions affect model-based predictions of tree species distribution.

PubMed

Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei

2013-01-01

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

Thematic and Spatial Resolutions Affect Model-Based Predictions of Tree Species Distribution

PubMed Central

Liang, Yu; He, Hong S.; Fraser, Jacob S.; Wu, ZhiWei

2013-01-01

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution. PMID:23861828

Fine-scale spatial distribution of the common lugworm Arenicola marina, and effects of intertidal clam fishing

NASA Astrophysics Data System (ADS)

Boldina, Inna; Beninger, Peter G.

2014-04-01

Despite its ubiquity and its role as an ecosystem engineer on temperate intertidal mudflats, little is known of the spatial ecology of the lugworm Arenicola marina. We estimated lugworm densities and analyzed the spatial distribution of A. marina on a French Atlantic mudflat subjected to long-term clam digging activities, and compared these to a nearby pristine reference mudflat, using a combination of geostatistical techniques: point-pattern analysis, autocorrelation, and wavelet analysis. Lugworm densities were an order of magnitude greater at the reference site. Although A. marina showed an aggregative spatial distribution at both sites, the characteristics and intensity of aggregation differed markedly between sites. The reference site showed an inhibition process (regular distribution) at distances <7.5 cm, whereas the impacted site showed a random distribution at this scale. At distances from 15 cm to several tens of meters, the spatial distribution of A. marina was clearly aggregated at both sites; however, the autocorrelation strength was much weaker at the impacted site. In addition, the non-impacted site presented multi-scale spatial distribution, which was not evident at the impacted site. The differences observed between the spatial distributions of the fishing-impacted vs. the non-impacted site reflect similar findings for other components of these two mudflat ecosystems, suggesting common community-level responses to prolonged mechanical perturbation: a decrease in naturally-occurring aggregation. This change may have consequences for basic biological characteristics such as reproduction, recruitment, growth, and feeding.

Effects of cyclic flexure on endothelial permeability and apoptosis in arterial segments perfused ex vivo.

PubMed

Van Epps, J Scott; Chew, Douglas W; Vorp, David A

2009-10-01

Certain arteries (e.g., coronary, femoral, etc.) are exposed to cyclic flexure due to their tethering to surrounding tissue beds. It is believed that such stimuli result in a spatially variable biomechanical stress distribution, which has been implicated as a key modulator of remodeling associated with atherosclerotic lesion localization. In this study we utilized a combined ex vivo experimental/computational methodology to address the hypothesis that local variations in shear and mural stress associated with cyclic flexure influence the distribution of early markers of atherogenesis. Bilateral porcine femoral arteries were surgically harvested and perfused ex vivo under pulsatile arterial conditions. One of the paired vessels was exposed to cyclic flexure (0-0.7 cm(-1)) at 1 Hz for 12 h. During the last hour, the perfusate was supplemented with Evan's blue dye-labeled albumin. A custom tissue processing protocol was used to determine the spatial distribution of endothelial permeability, apoptosis, and proliferation. Finite element and computational fluid dynamics techniques were used to determine the mural and shear stress distributions, respectively, for each perfused segment. Biological data obtained experimentally and mechanical stress data estimated computationally were combined in an experiment-specific manner using multiple linear regression analyses. Arterial segments exposed to cyclic flexure had significant increases in intimal and medial apoptosis (3.42+/-1.02 fold, p=0.029) with concomitant increases in permeability (1.14+/-0.04 fold, p=0.026). Regression analyses revealed specific mural stress measures including circumferential stress at systole, and longitudinal pulse stress were quantitatively correlated with the distribution of permeability and apoptosis. The results demonstrated that local variation in mechanical stress in arterial segments subjected to cyclic flexure indeed influence the extent and spatial distribution of the early atherogenic markers. In addition, the importance of including mural stresses in the investigation of vascular mechanopathobiology was highlighted. Specific example results were used to describe a potential mechanism by which systemic risk factors can lead to a heterogeneous disease.

Geographical ecology of the palms (Arecaceae): determinants of diversity and distributions across spatial scales

PubMed Central

Eiserhardt, Wolf L.; Svenning, Jens-Christian; Kissling, W. Daniel; Balslev, Henrik

2011-01-01

Background The palm family occurs in all tropical and sub-tropical regions of the world. Palms are of high ecological and economical importance, and display complex spatial patterns of species distributions and diversity. Scope This review summarizes empirical evidence for factors that determine palm species distributions, community composition and species richness such as the abiotic environment (climate, soil chemistry, hydrology and topography), the biotic environment (vegetation structure and species interactions) and dispersal. The importance of contemporary vs. historical impacts of these factors and the scale at which they function is discussed. Finally a hierarchical scale framework is developed to guide predictor selection for future studies. Conclusions Determinants of palm distributions, composition and richness vary with spatial scale. For species distributions, climate appears to be important at landscape and broader scales, soil, topography and vegetation at landscape and local scales, hydrology at local scales, and dispersal at all scales. For community composition, soil appears important at regional and finer scales, hydrology, topography and vegetation at landscape and local scales, and dispersal again at all scales. For species richness, climate and dispersal appear to be important at continental to global scales, soil at landscape and broader scales, and topography at landscape and finer scales. Some scale–predictor combinations have not been studied or deserve further attention, e.g. climate on regional to finer scales, and hydrology and topography on landscape and broader scales. The importance of biotic interactions – apart from general vegetation structure effects – for the geographic ecology of palms is generally underexplored. Future studies should target scale–predictor combinations and geographic domains not studied yet. To avoid biased inference, one should ideally include at least all predictors previously found important at the spatial scale of investigation. PMID:21712297

Characterizing the Spatial and Temporal Distribution of Aerosol Optical Thickness Over the Atlantic Basin Utilizing GOES-8 Multispectral Data

NASA Technical Reports Server (NTRS)

Fox, Robert; Prins, Elaine Mae; Feltz, Joleen M.

2001-01-01

In recent years, modeling and analysis efforts have suggested that the direct and indirect radiative effects of both anthropogenic and natural aerosols play a major role in the radiative balance of the earth and are an important factor in climate change calculations. The direct effects of aerosols on radiation and indirect effects on cloud properties are not well understood at this time. In order to improve the characterization of aerosols within climate models it is important to accurately parameterize aerosol forcing mechanisms at the local, regional, and global scales. This includes gaining information on the spatial and temporal distribution of aerosols, transport regimes and mechanisms, aerosol optical thickness, and size distributions. Although there is an expanding global network of ground measurements of aerosol optical thickness and size distribution at specific locations, satellite data must be utilized to characterize the spatial and temporal extent of aerosols and transport regimes on regional and global scales. This study was part of a collaborative effort to characterize aerosol radiative forcing over the Atlantic basin associated with the following three major aerosol components in this region: urban/sulfate, Saharan dust, and biomass burning. In-situ ground measurements obtained by a network of sun photometers during the Smoke Clouds and Radiation Experiment in Brazil (SCAR-B) and the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX) were utilized to develop, calibrate, and validate a Geostationary Operational Environmental Satellite (GOES)-8 aerosol optical thickness (AOT) product. Regional implementation of the GOES-8 AOT product was used to augment point source measurements to gain a better understanding of the spatial and temporal distributions of Atlantic basin aerosols during SCAR-B and TARFOX.

Projected Irrigation Requirement Under Climate Change in Korean Peninsula by Apply Global Hydrologic Model to Local Scale.

NASA Astrophysics Data System (ADS)

Yang, B.; Lee, D. K.

2016-12-01

Understanding spatial distribution of irrigation requirement is critically important for agricultural water management. However, many studies considering future agricultural water management in Korea assessed irrigation requirement on watershed or administrative district scale, but have not accounted the spatial distribution. Lumped hydrologic model has typically used in Korea for simulating watershed scale irrigation requirement, while distribution hydrologic model can simulate the spatial distribution grid by grid. To overcome this shortcoming, here we applied a grid base global hydrologic model (H08) into local scale to estimate spatial distribution under future irrigation requirement of Korean Peninsula. Korea is one of the world's most densely populated countries, with also high produce and demand of rice which requires higher soil moisture than other crops. Although, most of the precipitation concentrate in particular season and disagree with crop growth season. This precipitation character makes management of agricultural water which is approximately 60% of total water usage critical issue in Korea. Furthermore, under future climate change, the precipitation predicted to be more concentrated and necessary need change of future water management plan. In order to apply global hydrological model into local scale, we selected appropriate major crops under social and local climate condition in Korea to estimate cropping area and yield, and revised the cropping area map more accurately. As a result, future irrigation requirement estimation varies under each projection, however, slightly decreased in most case. The simulation reveals, evapotranspiration increase slightly while effective precipitation also increase to balance the irrigation requirement. This finding suggest practical guideline to decision makers for further agricultural water management plan including future development of water supply plan to resolve water scarcity.

Mapping plant species ranges in the Hawaiian Islands: developing a methodology and associated GIS layers

USGS Publications Warehouse

Price, Jonathan P.; Jacobi, James D.; Gon, Samuel M.; Matsuwaki, Dwight; Mehrhoff, Loyal; Wagner, Warren; Lucas, Matthew; Rowe, Barbara

2012-01-01

This report documents a methodology for projecting the geographic ranges of plant species in the Hawaiian Islands. The methodology consists primarily of the creation of several geographic information system (GIS) data layers depicting attributes related to the geographic ranges of plant species. The most important spatial-data layer generated here is an objectively defined classification of climate as it pertains to the distribution of plant species. By examining previous zonal-vegetation classifications in light of spatially detailed climate data, broad zones of climate relevant to contemporary concepts of vegetation in the Hawaiian Islands can be explicitly defined. Other spatial-data layers presented here include the following: substrate age, as large areas of the island of Hawai'i, in particular, are covered by very young lava flows inimical to the growth of many plant species; biogeographic regions of the larger islands that are composites of multiple volcanoes, as many of their species are restricted to a given topographically isolated mountain or a specified group of them; and human impact, which can reduce the range of many species relative to where they formerly were found. Other factors influencing the geographic ranges of species that are discussed here but not developed further, owing to limitations in rendering them spatially, include topography, soils, and disturbance. A method is described for analyzing these layers in a GIS, in conjunction with a database of species distributions, to project the ranges of plant species, which include both the potential range prior to human disturbance and the projected present range. Examples of range maps for several species are given as case studies that demonstrate different spatial characteristics of range. Several potential applications of species-range maps are discussed, including facilitating field surveys, informing restoration efforts, studying range size and rarity, studying biodiversity, managing invasive species, and planning of conservation efforts.

Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice

PubMed Central

Schwarz, Kirsten; Fragkias, Michail; Boone, Christopher G.; Zhou, Weiqi; McHale, Melissa; Grove, J. Morgan; O’Neil-Dunne, Jarlath; McFadden, Joseph P.; Buckley, Geoffrey L.; Childers, Dan; Ogden, Laura; Pincetl, Stephanie; Pataki, Diane; Whitmer, Ali; Cadenasso, Mary L.

2015-01-01

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman’s correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns. PMID:25830303

Determination of spatial dose distribution in UCC treatments with LDR brachytherapy using Monte Carlo methods.

PubMed

Benites-Rengifo, Jorge Luis; Vega-Carrillo, Hector Rene

2018-05-19

Using Monte Carlos methods, with the MCNP5 code, a gynecological phantom and a vaginal cylinder were modeled. The spatial distribution of absorbed dose rates in Uterine Cervical Cancer treatment through low dose rate brachytherapy was determined. A liquid water gynecology computational phantom, including a vaginal cylinder applicator made of Lucite, was designed. The applicator has a linear array of four radioactive sources of Cesium 137. Around the vaginal cylinder, 13 water spherical cells of 0.5 cm-diameter were modeled to calculate absorbed dose emulating the procedure made by the treatment planning system. The gamma-ray fluence distribution was estimated, as well as the absorbed doses resulting approximately symmetrical for cells located at upper and lower of vaginal cylinder. Obtained results allow the use of the radioactive decay law to determine dose rate for Uterine Cervical Cancer using low dose rate brachytherapy. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial vs. individual variability with inheritance in a stochastic Lotka-Volterra system

NASA Astrophysics Data System (ADS)

Dobramysl, Ulrich; Tauber, Uwe C.

2012-02-01

We investigate a stochastic spatial Lotka-Volterra predator-prey model with randomized interaction rates that are either affixed to the lattice sites and quenched, and / or specific to individuals in either population. In the latter situation, we include rate inheritance with mutations from the particles' progenitors. Thus we arrive at a simple model for competitive evolution with environmental variability and selection pressure. We employ Monte Carlo simulations in zero and two dimensions to study the time evolution of both species' densities and their interaction rate distributions. The predator and prey concentrations in the ensuing steady states depend crucially on the environmental variability, whereas the temporal evolution of the individualized rate distributions leads to largely neutral optimization. Contrary to, e.g., linear gene expression models, this system does not experience fixation at extreme values. An approximate description of the resulting data is achieved by means of an effective master equation approach for the interaction rate distribution.

CNMM: a Catchment Environmental Model for Managing Water Quality and Greenhouse Gas Emissions

NASA Astrophysics Data System (ADS)

Li, Y.

2015-12-01

Mitigating agricultural diffuse pollution and greenhouse gas emissions is a complicated task due to tempo-spatial lags between the field practices and the watershed responses. Spatially-distributed modeling is essential to the implementation of cost-effective and best management practices (BMPs) to optimize land uses and nutrient applications as well as to project the impact of climate change on the watershed service functions. CNMM (the Catchment Nutrients Management Model) is a 3D spatially-distributed, grid-based and process-oriented biophysical model comprehensively developed to simulate energy balance, hydrology, plant/crop growth, biogeochemistry of life elements (e.g., C, N and P), waste treatment, waterway vegetation/purification, stream water quality and land management in agricultural watersheds as affected by land utilization strategies such as BMPs and by climate change. The CNMM is driven by a number of spatially-distributed data such as weather, topography (including DEM and shading), stream network, stream water, soil, vegetation and land management (including waste treatments), and runs at an hourly time step. It represents a catchment as a matrix of square uniformly-sized cells, where each cell is defined as a homogeneous hydrological response unit with all the hydrologically-significant parameters the same but varied at soil depths in fine intervals. Therefore, spatial variability is represented by allowing parameters to vary horizontally and vertically in space. A four-direction flux routing algorithm is applied to route water and nutrients across soils of cells governed by the gradients of either water head or elevation. A linear channel reservoir scheme is deployed to route water and nutrients in stream networks. The model is capable of computing CO2, CH4, NH3, NO, N2O and N2 emissions from soils and stream waters. The CNMM can serve as an idea modelling tool to investigate the overwhelming critical zone research at various catchment scales.

Surficial geologic map of the Amboy 30' x 60' quadrangle, San Bernardino County, California

USGS Publications Warehouse

Bedford, David R.; Miller, David M.; Phelps, Geoffrey A.

2010-01-01

The surficial geologic map of the Amboy 30' x 60' quadrangle presents characteristics of surficial materials for an area of approximately 5,000 km2 in the eastern Mojave Desert of southern California. This map consists of new surficial mapping conducted between 2000 and 2007, as well as compilations from previous surficial mapping. Surficial geologic units are mapped and described based on depositional process and age categories that reflect the mode of deposition, pedogenic effects following deposition, and, where appropriate, the lithologic nature of the material. Many physical properties were noted and measured during the geologic mapping. This information was used to classify surficial deposits and to understand their ecological importance. We focus on physical properties that drive hydrologic, biologic, and physical processes such as particle-size distribution (PSD) and bulk density. The database contains point data representing locations of samples for both laboratory determined physical properties and semiquantitative field-based information in the database. We include the locations of all field observations and note the type of information collected in the field to help assist in assessing the quality of the mapping. The publication is separated into three parts: documentation, spatial data, and printable map graphics of the database. Documentation includes this pamphlet, which provides a discussion of the surficial geology and units and the map. Spatial data are distributed as ArcGIS Geodatabase in Microsoft Access format and are accompanied by a readme file, which describes the database contents, and FGDC metadata for the spatial map information. Map graphics files are distributed as Postscript and Adobe Portable Document Format (PDF) files that provide a view of the spatial database at the mapped scale.

A comparison of regional flood frequency analysis approaches in a simulation framework

NASA Astrophysics Data System (ADS)

Ganora, D.; Laio, F.

2016-07-01

Regional frequency analysis (RFA) is a well-established methodology to provide an estimate of the flood frequency curve at ungauged (or scarcely gauged) sites. Different RFA approaches exist, depending on the way the information is transferred to the site of interest, but it is not clear in the literature if a specific method systematically outperforms the others. The aim of this study is to provide a framework wherein carrying out the intercomparison by building up a virtual environment based on synthetically generated data. The considered regional approaches include: (i) a unique regional curve for the whole region; (ii) a multiple-region model where homogeneous subregions are determined through cluster analysis; (iii) a Region-of-Influence model which defines a homogeneous subregion for each site; (iv) a spatially smooth estimation procedure where the parameters of the regional model vary continuously along the space. Virtual environments are generated considering different patterns of heterogeneity, including step change and smooth variations. If the region is heterogeneous, with the parent distribution changing continuously within the region, the spatially smooth regional approach outperforms the others, with overall errors 10-50% lower than the other methods. In the case of a step-change, the spatially smooth and clustering procedures perform similarly if the heterogeneity is moderate, while clustering procedures work better when the step-change is severe. To extend our findings, an extensive sensitivity analysis has been performed to investigate the effect of sample length, number of virtual stations, return period of the predicted quantile, variability of the scale parameter of the parent distribution, number of predictor variables and different parent distribution. Overall, the spatially smooth approach appears as the most robust approach as its performances are more stable across different patterns of heterogeneity, especially when short records are considered.

Geologic database for digital geology of California, Nevada, and Utah: an application of the North American Data Model

USGS Publications Warehouse

Bedford, David R.; Ludington, Steve; Nutt, Constance M.; Stone, Paul A.; Miller, David M.; Miller, Robert J.; Wagner, David L.; Saucedo, George J.

2003-01-01

The USGS is creating an integrated national database for digital state geologic maps that includes stratigraphic, age, and lithologic information. The majority of the conterminous 48 states have digital geologic base maps available, often at scales of 1:500,000. This product is a prototype, and is intended to demonstrate the types of derivative maps that will be possible with the national integrated database. This database permits the creation of a number of types of maps via simple or sophisticated queries, maps that may be useful in a number of areas, including mineral-resource assessment, environmental assessment, and regional tectonic evolution. This database is distributed with three main parts: a Microsoft Access 2000 database containing geologic map attribute data, an Arc/Info (Environmental Systems Research Institute, Redlands, California) Export format file containing points representing designation of stratigraphic regions for the Geologic Map of Utah, and an ArcView 3.2 (Environmental Systems Research Institute, Redlands, California) project containing scripts and dialogs for performing a series of generalization and mineral resource queries. IMPORTANT NOTE: Spatial data for the respective stage geologic maps is not distributed with this report. The digital state geologic maps for the states involved in this report are separate products, and two of them are produced by individual state agencies, which may be legally and/or financially responsible for this data. However, the spatial datasets for maps discussed in this report are available to the public. Questions regarding the distribution, sale, and use of individual state geologic maps should be sent to the respective state agency. We do provide suggestions for obtaining and formatting the spatial data to make it compatible with data in this report. See section ‘Obtaining and Formatting Spatial Data’ in the PDF version of the report.

Spatial distribution and influence factors of interprovincial terrestrial physical geographical names in China

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.

Predicting probability of occurrence and factors affecting distribution and abundance of three Ozark endemic crayfish species at multiple spatial scales

USGS Publications Warehouse

Nolen, Matthew S.; Magoulick, Daniel D.; DiStefano, Robert J.; Imhoff, Emily M.; Wagner, Brian K.

2014-01-01

We found that a range of environmental variables were important in predicting crayfish distribution and abundance at multiple spatial scales and their importance was species-, response variable- and scale dependent. We would encourage others to examine the influence of spatial scale on species distribution and abundance patterns.

Data set: 31 years of spatially distributed air temperature, humidity, precipitation amount and precipitation phase from a mountain catchment in the rain-snow transition zone

USDA-ARS?s Scientific Manuscript database

Thirty one years of spatially distributed air temperature, relative humidity, dew point temperature, precipitation amount, and precipitation phase data are presented for the Reynolds Creek Experimental Watershed. The data are spatially distributed over a 10m Lidar-derived digital elevation model at ...

Predicting the spatial distribution of Lonicera japonica, based on species occurrence data from two watersheds in Western Kentucky and Tennessee

Treesearch

Dongjiao Liu; Hao Jiang; Robin Zhang; Kate S. He

2011-01-01

The spatial distribution of most invasive plants is poorly documented and studied. This project examined and compared the spatial distribution of a successful invasive plant, Japanese honeysuckle (Lonicera japonica), in two similar-sized but ecologically distinct watersheds in western Kentucky (Ledbetter Creek) and western Tennessee (Panther Creek)....

Understanding the spatial complexity of surface hoar from slope to range scale

NASA Astrophysics Data System (ADS)

Hendrikx, J.

2015-12-01

Surface hoar, once buried, is a common weak layer type in avalanche accidents in continental and intermountain snowpacks around the World. Despite this, there is still limited understanding of the spatial variability in both the formation of, and eventual burial of, surface hoar at spatial scales which are of critical importance to avalanche forecasters. While it is relatively well understood that aspect plays an important role in the spatial location of the formation, and burial of these grain forms, due to the unequal distribution of incoming radiation, this factor alone does not explain the complex and often confusing spatial pattern of these grains forms throughout the landscape at different spatial scales. In this paper we present additional data from a unique data set including over two hundred days of manual observations of surface hoar at sixteen locations on Pioneer Mountain at the Yellowstone Club in southwestern Montana. Using this wealth of observational data located on different aspects, elevations and exposures, coupled with detailed meteorological observations, and detailed slope scale observation, we examine the spatial variability of surface hoar at this scale, and examine the factors that control its spatial distribution. Our results further supports our preliminary work, which shows that small-scale slope conditions, meteorological differences, and local scale lapse rates, can greatly influence the spatial variability of surface hoar, over and above that which aspect alone can explain. These results highlight our incomplete understanding of the processes at both the slope and range scale, and are likely to have implications for both regional and local scale avalanche forecasting in environments where surface hoar cause ongoing instabilities.

Spatial distribution of soil organic carbon stock in Moso bamboo forests in subtropical China.

PubMed

Tang, Xiaolu; Xia, Mingpeng; Pérez-Cruzado, César; Guan, Fengying; Fan, Shaohui

2017-02-14

Moso bamboo (Phyllostachys heterocycla (Carr.) Mitford cv. Pubescens) is an important timber substitute in China. Site specific stand management requires an accurate estimate of soil organic carbon (SOC) stock for maintaining stand productivity and understanding global carbon cycling. This study compared ordinary kriging (OK) and inverse distance weighting (IDW) approaches to study the spatial distribution of SOC stock within 0-60 cm using 111 soil samples in Moso bamboo forests in subtropical China. Similar spatial patterns but different spatial distribution ranges of SOC stock from OK and IDW highlighted the necessity to apply different approaches to obtain accurate and consistent results of SOC stock distribution. Different spatial patterns of SOC stock suggested the use of different fertilization treatments in Moso bamboo forests across the study area. SOC pool within 0-60 cm was 6.46 and 6.22 Tg for OK and IDW; results which were lower than that of conventional approach (CA, 7.41 Tg). CA is not recommended unless coordinates of the sampling locations are missing and the spatial patterns of SOC stock are not required. OK is recommended for the uneven distribution of sampling locations. Our results can improve methodology selection for investigating spatial distribution of SOC stock in Moso bamboo forests.

Spatial distribution of soil organic carbon stock in Moso bamboo forests in subtropical China

PubMed Central

Tang, Xiaolu; Xia, Mingpeng; Pérez-Cruzado, César; Guan, Fengying; Fan, Shaohui

2017-01-01

Moso bamboo (Phyllostachys heterocycla (Carr.) Mitford cv. Pubescens) is an important timber substitute in China. Site specific stand management requires an accurate estimate of soil organic carbon (SOC) stock for maintaining stand productivity and understanding global carbon cycling. This study compared ordinary kriging (OK) and inverse distance weighting (IDW) approaches to study the spatial distribution of SOC stock within 0–60 cm using 111 soil samples in Moso bamboo forests in subtropical China. Similar spatial patterns but different spatial distribution ranges of SOC stock from OK and IDW highlighted the necessity to apply different approaches to obtain accurate and consistent results of SOC stock distribution. Different spatial patterns of SOC stock suggested the use of different fertilization treatments in Moso bamboo forests across the study area. SOC pool within 0–60 cm was 6.46 and 6.22 Tg for OK and IDW; results which were lower than that of conventional approach (CA, 7.41 Tg). CA is not recommended unless coordinates of the sampling locations are missing and the spatial patterns of SOC stock are not required. OK is recommended for the uneven distribution of sampling locations. Our results can improve methodology selection for investigating spatial distribution of SOC stock in Moso bamboo forests. PMID:28195207

Imaging of the Li spatial distribution within V 2O 5 cathode in a coin cell by neutron computed tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yuxuan; Chandran, K. S. Ravi; Bilheux, Hassina Z.

An understanding of Lithium (Li) spatial distribution within the electrodes of a Li-ion cell, during charge and discharge cycles, is essential to optimize the electrode parameters for increased performance under cycling. In this work, it is demonstrated that the spatial distribution of Li within Vanadium Pentoxide (V 2O 5) electrodes of a small coin cell can be imaged by neutron computed tomography. The neutron attenuation data has been used to construct the three-dimensional Li spatial images. Specifically, it is shown that there is sufficient neutron imaging contrast between lithiated and delithiated regions of V 2O 5 electrode making it possiblemore » to map Li distributions even in small electrodes with thicknesses <1 mm. The images reveal that the Li spatial distribution is inhomogeneous and a relatively higher C-rate leads to more non-uniform Li distribution after Li insertion. The non-uniform distribution suggests the limitation of Li diffusion within the electrode during the lithiation process under the relatively high cycling rates.« less

Imaging of the Li spatial distribution within V2O5 cathode in a coin cell by neutron computed tomography

NASA Astrophysics Data System (ADS)

Zhang, Yuxuan; Chandran, K. S. Ravi; Bilheux, Hassina Z.

2018-02-01

An understanding of Lithium (Li) spatial distribution within the electrodes of a Li-ion cell, during charge and discharge cycles, is essential to optimize the electrode parameters for increased performance under cycling. In this work, it is demonstrated that the spatial distribution of Li within Vanadium Pentoxide (V2O5) electrodes of a small coin cell can be imaged by neutron computed tomography. The neutron attenuation data has been used to construct the three-dimensional Li spatial images. Specifically, it is shown that there is sufficient neutron imaging contrast between lithiated and delithiated regions of V2O5 electrode making it possible to map Li distributions even in small electrodes with thicknesses <1 mm. The images reveal that the Li spatial distribution is inhomogeneous and a relatively higher C-rate leads to more non-uniform Li distribution after Li insertion. The non-uniform distribution suggests the limitation of Li diffusion within the electrode during the lithiation process under the relatively high cycling rates.

Imaging of the Li spatial distribution within V 2O 5 cathode in a coin cell by neutron computed tomography

DOE PAGES

Zhang, Yuxuan; Chandran, K. S. Ravi; Bilheux, Hassina Z.

2017-11-30

An understanding of Lithium (Li) spatial distribution within the electrodes of a Li-ion cell, during charge and discharge cycles, is essential to optimize the electrode parameters for increased performance under cycling. In this work, it is demonstrated that the spatial distribution of Li within Vanadium Pentoxide (V 2O 5) electrodes of a small coin cell can be imaged by neutron computed tomography. The neutron attenuation data has been used to construct the three-dimensional Li spatial images. Specifically, it is shown that there is sufficient neutron imaging contrast between lithiated and delithiated regions of V 2O 5 electrode making it possiblemore » to map Li distributions even in small electrodes with thicknesses <1 mm. The images reveal that the Li spatial distribution is inhomogeneous and a relatively higher C-rate leads to more non-uniform Li distribution after Li insertion. The non-uniform distribution suggests the limitation of Li diffusion within the electrode during the lithiation process under the relatively high cycling rates.« less

COST-EFFECTIVE SAMPLING FOR SPATIALLY DISTRIBUTED PHENOMENA

EPA Science Inventory

Various measures of sampling plan cost and loss are developed and analyzed as they relate to a variety of multidisciplinary sampling techniques. The sampling choices examined include methods from design-based sampling, model-based sampling, and geostatistics. Graphs and tables ar...

Biogeography of dinoflagellate cysts in northwest Atlantic estuaries

EPA Science Inventory

Few biogeographic studies of dinoflagellate cysts include the near-shore estuarine environment. We determine the effect of estuary type, biogeography, and water quality on the spatial distribution of organic-walled dinoflagellate cysts from the Northeast USA (Maine to Delaware) a...

Spatial pattern of diarrhea based on regional economic and environment by spatial autoregressive model

NASA Astrophysics Data System (ADS)

Bekti, Rokhana Dwi; Nurhadiyanti, Gita; Irwansyah, Edy

2014-10-01

The diarrhea case pattern information, especially for toddler, is very important. It is used to show the distribution of diarrhea in every region, relationship among that locations, and regional economic characteristic or environmental behavior. So, this research uses spatial pattern to perform them. This method includes: Moran's I, Spatial Autoregressive Models (SAR), and Local Indicator of Spatial Autocorrelation (LISA). It uses sample from 23 sub districts of Bekasi Regency, West Java, Indonesia. Diarrhea case, regional economic, and environmental behavior of households have a spatial relationship among sub district. SAR shows that the percentage of Regional Gross Domestic Product is significantly effect on diarrhea at α = 10%. Therefore illiteracy and health center facilities are significant at α = 5%. With LISA test, sub districts in southern Bekasi have high dependencies with Cikarang Selatan, Serang Baru, and Setu. This research also builds development application that is based on java and R to support data analysis.

A mathematical model of a large open fire

NASA Technical Reports Server (NTRS)

Harsha, P. T.; Bragg, W. N.; Edelman, R. B.

1981-01-01

A mathematical model capable of predicting the detailed characteristics of large, liquid fuel, axisymmetric, pool fires is described. The predicted characteristics include spatial distributions of flame gas velocity, soot concentration and chemical specie concentrations including carbon monoxide, carbon dioxide, water, unreacted oxygen, unreacted fuel and nitrogen. Comparisons of the predictions with experimental values are also given.

A Kinetic Study of Microwave Start-up of Tokamak Plasmas

NASA Astrophysics Data System (ADS)

du Toit, E. J.; O'Brien, M. R.; Vann, R. G. L.

2017-07-01

A kinetic model for studying the time evolution of the distribution function for microwave startup is presented. The model for the distribution function is two dimensional in momentum space, but, for simplicity and rapid calculations, has no spatial dependence. Experiments on the Mega Amp Spherical Tokamak have shown that the plasma current is carried mainly by electrons with energies greater than 70 keV, and effects thought to be important in these experiments are included, i.e. particle sources, orbital losses, the loop voltage and microwave heating, with suitable volume averaging where necessary to give terms independent of spatial dimensions. The model predicts current carried by electrons with the same energies as inferred from the experiments, though the current drive efficiency is smaller.

SPATIAL DISTRIBUTIONS OF ABSORPTION, LOCAL SUPPRESSION, AND EMISSIVITY REDUCTION OF SOLAR ACOUSTIC WAVES IN MAGNETIC REGIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chou, D.-Y.; Yang, M.-H.; Zhao Hui

Observed acoustic power in magnetic regions is lower than the quiet Sun because of absorption, emissivity reduction, and local suppression of solar acoustic waves in magnetic regions. In the previous studies, we have developed a method to measure the coefficients of absorption, emissivity reduction, and local suppression of sunspots. In this study, we go one step further to measure the spatial distributions of three coefficients in two active regions, NOAA 9055 and 9057. The maps of absorption, emissivity reduction, and local suppression coefficients correlate with the magnetic map, including plage regions, except the emissivity reduction coefficient of NOAA 9055 wheremore » the emissivity reduction coefficient is too weak and lost among the noise.« less

A Permutation-Randomization Approach to Test the Spatial Distribution of Plant Diseases.

PubMed

Lione, G; Gonthier, P

2016-01-01

The analysis of the spatial distribution of plant diseases requires the availability of trustworthy geostatistical methods. The mean distance tests (MDT) are here proposed as a series of permutation and randomization tests to assess the spatial distribution of plant diseases when the variable of phytopathological interest is categorical. A user-friendly software to perform the tests is provided. Estimates of power and type I error, obtained with Monte Carlo simulations, showed the reliability of the MDT (power > 0.80; type I error < 0.05). A biological validation on the spatial distribution of spores of two fungal pathogens causing root rot on conifers was successfully performed by verifying the consistency between the MDT responses and previously published data. An application of the MDT was carried out to analyze the relation between the plantation density and the distribution of the infection of Gnomoniopsis castanea, an emerging fungal pathogen causing nut rot on sweet chestnut. Trees carrying nuts infected by the pathogen were randomly distributed in areas with different plantation densities, suggesting that the distribution of G. castanea was not related to the plantation density. The MDT could be used to analyze the spatial distribution of plant diseases both in agricultural and natural ecosystems.

Crop yield response to climate change varies with crop spatial distribution pattern

DOE PAGES

Leng, Guoyong; Huang, Maoyi

2017-05-03

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40%more » by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.« less

Crop yield response to climate change varies with crop spatial distribution pattern

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Guoyong; Huang, Maoyi

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40%more » by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.« less

Incorporation of a spatial source distribution and a spatial sensor sensitivity in a laser ultrasound propagation model using a streamlined Huygens' principle.

PubMed

Laloš, Jernej; Babnik, Aleš; Možina, Janez; Požar, Tomaž

2016-03-01

The near-field, surface-displacement waveforms in plates are modeled using interwoven concepts of Green's function formalism and streamlined Huygens' principle. Green's functions resemble the building blocks of the sought displacement waveform, superimposed and weighted according to the simplified distribution. The approach incorporates an arbitrary circular spatial source distribution and an arbitrary circular spatial sensitivity in the area probed by the sensor. The displacement histories for uniform, Gaussian and annular normal-force source distributions and the uniform spatial sensor sensitivity are calculated, and the corresponding weight distributions are compared. To demonstrate the applicability of the developed scheme, measurements of laser ultrasound induced solely by the radiation pressure are compared with the calculated waveforms. The ultrasound is induced by laser pulse reflection from the mirror-surface of a glass plate. The measurements show excellent agreement not only with respect to various wave-arrivals but also in the shape of each arrival. Their shape depends on the beam profile of the excitation laser pulse and its corresponding spatial normal-force distribution. Copyright © 2015 Elsevier B.V. All rights reserved.

A fast integrated mobility spectrometer for rapid measurement of sub-micrometer aerosol size distribution, Part I: Design and model evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jian; Pikridas, Michael; Spielman, Steven R.

This study discusses, a fast integrated mobility spectrometer (FIMS) was previously developed to characterize submicron aerosol size distributions at a frequency of 1 Hz and with high size resolution and counting statistics. However, the dynamic size range of the FIMS was limited to one decade in particle electrical mobility. It was proposed that the FIMS dynamic size range can be greatly increased by using a spatially varying electric field. This electric field creates regions with drastically different field strengths in the separator, such that particles of a wide diameter range can be simultaneously classified and subsequently measured. A FIMS incorporatingmore » this spatially varying electric field is developed. This paper describes the theoretical frame work and numerical simulations of the FIMS with extended dynamic size range, including the spatially varying electric field, particle trajectories, activation of separated particles in the condenser, and the transfer function, transmission efficiency, and mobility resolution. The influences of the particle Brownian motion on FIMS transfer function and mobility resolution are examined. The simulation results indicate that the FIMS incorporating the spatially varying electric field is capable of measuring aerosol size distribution from 8 to 600 nm with high time resolution. As a result, the experimental characterization of the FIMS is presented in an accompanying paper.« less

Including the third dimension: a spatial analysis of TB cases in Houston Harris County.

PubMed

Feske, Marsha L; Teeter, Larry D; Musser, James M; Graviss, Edward A

2011-12-01

To reach the tuberculosis (TB) elimination goals established by the Institute of Medicine (IOM) and the Centers for Disease Control and Prevention (CDC), measures must be taken to speed the currently stagnant TB elimination rate and curtail a future peak in TB incidence. Increases in TB incidence have historically coincided with immigration, poverty, and joblessness; all situations that are currently occurring worldwide. Effective TB elimination strategies will require the geographical elucidation of areas within the U.S. that have endemic TB, and systematic surveillance of the locations and location-based risk factors associated with TB transmission. Surveillance data was used to assess the spatial distribution of cases, the yearly TB incidence by census tract, and the statistical significance of case clustering. The analysis revealed that there are neighborhoods within Houston/Harris County that had a heavy TB burden. The maximum yearly incidence varied from 245/100,000-754/100,000 and was not exclusively dependent of the number of cases reported. Geographically weighted regression identified risk factors associated with the spatial distribution of cases such as: poverty, age, Black race, and foreign birth. Public transportation was also associated with the spatial distribution of cases and census tracts identified as high incidence were found to be irregularly clustered within communities of varied SES. Copyright © 2011 Elsevier Ltd. All rights reserved.

Development of a Heterogenic Distributed Environment for Spatial Data Processing Using Cloud Technologies

NASA Astrophysics Data System (ADS)

Garov, A. S.; Karachevtseva, I. P.; Matveev, E. V.; Zubarev, A. E.; Florinsky, I. V.

2016-06-01

We are developing a unified distributed communication environment for processing of spatial data which integrates web-, desktop- and mobile platforms and combines volunteer computing model and public cloud possibilities. The main idea is to create a flexible working environment for research groups, which may be scaled according to required data volume and computing power, while keeping infrastructure costs at minimum. It is based upon the "single window" principle, which combines data access via geoportal functionality, processing possibilities and communication between researchers. Using an innovative software environment the recently developed planetary information system (http://cartsrv.mexlab.ru/geoportal) will be updated. The new system will provide spatial data processing, analysis and 3D-visualization and will be tested based on freely available Earth remote sensing data as well as Solar system planetary images from various missions. Based on this approach it will be possible to organize the research and representation of results on a new technology level, which provides more possibilities for immediate and direct reuse of research materials, including data, algorithms, methodology, and components. The new software environment is targeted at remote scientific teams, and will provide access to existing spatial distributed information for which we suggest implementation of a user interface as an advanced front-end, e.g., for virtual globe system.

A fast integrated mobility spectrometer for rapid measurement of sub-micrometer aerosol size distribution, Part I: Design and model evaluation

DOE PAGES

Wang, Jian; Pikridas, Michael; Spielman, Steven R.; ...

2017-06-01

This study discusses, a fast integrated mobility spectrometer (FIMS) was previously developed to characterize submicron aerosol size distributions at a frequency of 1 Hz and with high size resolution and counting statistics. However, the dynamic size range of the FIMS was limited to one decade in particle electrical mobility. It was proposed that the FIMS dynamic size range can be greatly increased by using a spatially varying electric field. This electric field creates regions with drastically different field strengths in the separator, such that particles of a wide diameter range can be simultaneously classified and subsequently measured. A FIMS incorporatingmore » this spatially varying electric field is developed. This paper describes the theoretical frame work and numerical simulations of the FIMS with extended dynamic size range, including the spatially varying electric field, particle trajectories, activation of separated particles in the condenser, and the transfer function, transmission efficiency, and mobility resolution. The influences of the particle Brownian motion on FIMS transfer function and mobility resolution are examined. The simulation results indicate that the FIMS incorporating the spatially varying electric field is capable of measuring aerosol size distribution from 8 to 600 nm with high time resolution. As a result, the experimental characterization of the FIMS is presented in an accompanying paper.« less

Stick-slip behavior in a continuum-granular experiment.

PubMed

Geller, Drew A; Ecke, Robert E; Dahmen, Karin A; Backhaus, Scott

2015-12-01

We report moment distribution results from a laboratory experiment, similar in character to an isolated strike-slip earthquake fault, consisting of sheared elastic plates separated by a narrow gap filled with a two-dimensional granular medium. Local measurement of strain displacements of the plates at 203 spatial points located adjacent to the gap allows direct determination of the event moments and their spatial and temporal distributions. We show that events consist of spatially coherent, larger motions and spatially extended (noncoherent), smaller events. The noncoherent events have a probability distribution of event moment consistent with an M(-3/2) power law scaling with Poisson-distributed recurrence times. Coherent events have a log-normal moment distribution and mean temporal recurrence. As the applied normal pressure increases, there are more coherent events and their log-normal distribution broadens and shifts to larger average moment.

High-energy Gamma Rays from the Milky Way: Three-dimensional Spatial Models for the Cosmic-Ray and Radiation Field Densities in the Interstellar Medium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Porter, T. A.; Moskalenko, I. V.; Jóhannesson, G., E-mail: tporter@stanford.edu

High-energy γ -rays of interstellar origin are produced by the interaction of cosmic-ray (CR) particles with the diffuse gas and radiation fields in the Galaxy. The main features of this emission are well understood and are reproduced by existing CR propagation models employing 2D galactocentric cylindrically symmetrical geometry. However, the high-quality data from instruments like the Fermi Large Area Telescope reveal significant deviations from the model predictions on few to tens of degrees scales, indicating the need to include the details of the Galactic spiral structure and thus requiring 3D spatial modeling. In this paper, the high-energy interstellar emissions frommore » the Galaxy are calculated using the new release of the GALPROP code employing 3D spatial models for the CR source and interstellar radiation field (ISRF) densities. Three models for the spatial distribution of CR sources are used that are differentiated by their relative proportion of input luminosity attributed to the smooth disk or spiral arms. Two ISRF models are developed based on stellar and dust spatial density distributions taken from the literature that reproduce local near- to far-infrared observations. The interstellar emission models that include arms and bulges for the CR source and ISRF densities provide plausible physical interpretations for features found in the residual maps from high-energy γ -ray data analysis. The 3D models for CR and ISRF densities provide a more realistic basis that can be used for the interpretation of the nonthermal interstellar emissions from the Galaxy.« less

Dengue Vectors and their Spatial Distribution

PubMed Central

Higa, Yukiko

2011-01-01

The distribution of dengue vectors, Ae. aegypti and Ae. albopictus, is affected by climatic factors. In addition, since their life cycles are well adapted to the human environment, environmental changes resulting from human activity such as urbanization exert a great impact on vector distribution. The different responses of Ae. aegypti and Ae albopictus to various environments result in a difference in spatial distribution along north-south and urban-rural gradients, and between the indoors and outdoors. In the north-south gradient, climate associated with survival is an important factor in spatial distribution. In the urban-rural gradient, different distribution reflects a difference in adult niches and is modified by geographic and human factors. The direct response of the two species to the environment around houses is related to different spatial distribution indoors and outdoors. Dengue viruses circulate mainly between human and vector mosquitoes, and the vector presence is a limiting factor of transmission. Therefore, spatial distribution of dengue vectors is a significant concern in the epidemiology of the disease. Current technologies such as GIS, satellite imagery and statistical models allow researchers to predict the spatial distribution of vectors in the changing environment. Although it is difficult to confirm the actual effect of environmental and climate changes on vector abundance and vector-borne diseases, environmental changes caused by humans and human behavioral changes due to climate change can be expected to exert an impact on dengue vectors. Longitudinal monitoring of dengue vectors and viruses is therefore necessary. PMID:22500133

Reserch on Spatial and Temporal Distribution of Color Steel Building Based on Multi-Source High-Resolution Satellite Imagery

NASA Astrophysics Data System (ADS)

Yang, S. W.; Ma, J. J.; Wang, J. M.

2018-04-01

As representative vulnerable regions of the city, dense distribution areas of temporary color steel building are a major target for control of fire risks, illegal buildings, environmental supervision, urbanization quality and enhancement for city's image. In the domestic and foreign literature, the related research mainly focuses on fire risks and violation monitoring. However, due to temporary color steel building's special characteristics, the corresponding research about temporal and spatial distribution, and influence on urban spatial form etc. has not been reported. Therefore, firstly, the paper research aim plans to extract information of large-scale color steel building from high-resolution images. Secondly, the color steel plate buildings were classified, and the spatial and temporal distribution and aggregation characteristics of small (temporary buildings) and large (factory building, warehouse, etc.) buildings were studied respectively. Thirdly, the coupling relationship between the spatial distribution of color steel plate and the spatial pattern of urban space was analysed. The results show that there is a good coupling relationship between the color steel plate building and the urban spatial form. Different types of color steel plate building represent the pattern of regional differentiation of urban space and the phased pattern of urban development.

[Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

PubMed

Zhang, Ling Yu; Liu, Zhao Gang

2017-12-01

Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.

Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.

NASA Astrophysics Data System (ADS)

Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Tian, Y.; Zeng, J.

2007-05-01

The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.

Spatial distribution of low birthweight infants in Taubaté, São Paulo, Brazil

PubMed Central

Nascimento, Luiz Fernando C.; Costa, Thais Moreira; Zöllner, Maria Stella A. da C.

2013-01-01

OBJECTIVE: To identify the spatial pattern of low birth weight infants in the city of Taubaté, São Paulo, Southeast Brazil. METHODS: Ecological and exploratory study, developed with the data acquired from the Health Department of Taubaté, regarding the period from January 1st 2006 and December 31st 2010. Birth certificates were used to obtain the data from infants weighing less than 2500g. A digital basis of census tracts was applied and the Global Moran index (IM) was estimated. Thematic maps were built for the distribution of low birth weight, health centers and tracts, according to the priority care (Moran map). The adopted statistical significance was α=5% and TerraView software conducted the spatial analysis. RESULTS: There were 18,915 live births during the study period, with 1,817 low birth weight infants (9.6%). The low birth weight infants' prevalence during the period ranged from 9.3 to 9.8%. A total of 1,185 infants with known addresses, compatible with the digital base (65.2% of low birth weight infants), were included. The IM for low birth weight was 0.12, with p<0.01; regarding the health centers distribution, IM was -0.07, with p=0.01. The Moran map identified 11 census tracts with high priority for intervention by health managers, located in the outskirts of the city. CONCLUSIONS: The spatial analysis identified the low birth weight distribution by census tracts and the sectors with a high priority for intervention. PMID:24473951

Implications of the spatial dynamics of fire spread for the bistability of savanna and forest.

PubMed

Schertzer, E; Staver, A C; Levin, S A

2015-01-01

The role of fire in expanding the global distribution of savanna is well recognized. Empirical observations and modeling suggest that fire spread has a threshold response to fuel-layer continuity, which sets up a positive feedback that maintains savanna-forest bistability. However, modeling has so far failed to examine fire spread as a spatial process that interacts with vegetation. Here, we use simple, well-supported assumptions about fire spread as an infection process and its effects on trees to ask whether spatial dynamics qualitatively change the potential for savanna-forest bistability. We show that the spatial effects of fire spread are the fundamental reason that bistability is possible: because fire spread is an infection process, it exhibits a threshold response to fuel continuity followed by a rapid increase in fire size. Other ecological processes affecting fire spread may also contribute including temporal variability in demography or fire spread. Finally, including the potential for spatial aggregation increases the potential both for savanna-forest bistability and for savanna and forest to coexist in a landscape mosaic.

Using geographical semi-variogram method to quantify the difference between NO2 and PM2.5 spatial distribution characteristics in urban areas.

PubMed

Song, Weize; Jia, Haifeng; Li, Zhilin; Tang, Deliang

2018-08-01

Urban air pollutant distribution is a concern in environmental and health studies. Particularly, the spatial distribution of NO 2 and PM 2.5 , which represent photochemical smog and haze pollution in urban areas, is of concern. This paper presents a study quantifying the seasonal differences between urban NO 2 and PM 2.5 distributions in Foshan, China. A geographical semi-variogram analysis was conducted to delineate the spatial variation in daily NO 2 and PM 2.5 concentrations. The data were collected from 38 sites in the government-operated monitoring network. The results showed that the total spatial variance of NO 2 is 38.5% higher than that of PM 2.5 . The random spatial variance of NO 2 was 1.6 times than that of PM 2.5 . The nugget effect (i.e., random to total spatial variance ratio) values of NO 2 and PM 2.5 were 29.7 and 20.9%, respectively. This indicates that urban NO 2 distribution was affected by both local and regional influencing factors, while urban PM 2.5 distribution was dominated by regional influencing factors. NO 2 had a larger seasonally averaged spatial autocorrelation distance (48km) than that of PM 2.5 (33km). The spatial range of NO 2 autocorrelation was larger in winter than the other seasons, and PM 2.5 has a smaller range of spatial autocorrelation in winter than the other seasons. Overall, the geographical semi-variogram analysis is a very effective method to enrich the understanding of NO 2 and PM 2.5 distributions. It can provide scientific evidences for the buffering radius selection of spatial predictors for land use regression models. It will also be beneficial for developing the targeted policies and measures to reduce NO 2 and PM 2.5 pollution levels. Copyright © 2018 Elsevier B.V. All rights reserved.

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

DOE PAGES

Andres, Robert J.; Boden, Thomas A.; Higdon, David M.

2016-12-05

Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2) emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughoutmore » this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4–190 %, with an average of 120 % (2 σ) for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC) FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.« less

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andres, Robert J.; Boden, Thomas A.; Higdon, David M.

Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2) emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughoutmore » this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4–190 %, with an average of 120 % (2 σ) for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC) FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.« less

High spatiotemporal resolution monitoring of hydrological function across degraded peatlands in the south west UK.

NASA Astrophysics Data System (ADS)

Ashe, Josie; Luscombe, David; Grand-Clement, Emilie; Gatis, Naomi; Anderson, Karen; Brazier, Richard

2014-05-01

The Exmoor/Dartmoor Mires Project is a peatland restoration programme focused on the geoclimatically marginal blanket bogs of South West England. In order to better understand the hydrological functioning of degraded/restored peatlands and support land management decisions across these uplands, this study is providing robust spatially distributed, hydrological monitoring at a high temporal resolution and in near real time. This paper presents the conceptual framework and experimental design for three hydrological monitoring arrays situated in headwater catchments dominated by eroding and drained blanket peatland. Over 250 individual measurements are collected at a high temporal resolution (15 minute time-step) via sensors integrated within a remote telemetry system. These are sent directly to a dedicated server over VHF and GPRS mobile networks. Sensors arrays are distributed at varying spatial scales throughout the studied catchments and record multiple parameters including: water table depth, channel flow, temperature, conductivity and pH measurements. A full suite of meteorological sensors and ten spatially distributed automatic flow based water samplers are also connected to the telemetry system and controlled remotely. This paper will highlight the challenges and solutions to obtaining these data in exceptionally remote and harsh field conditions over long (multi annual) temporal scales.

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

NASA Astrophysics Data System (ADS)

Andres, Robert J.; Boden, Thomas A.; Higdon, David M.

2016-12-01

Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2) emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughout this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4-190 %, with an average of 120 % (2σ) for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC) FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.

Wide size range fast integrated mobility spectrometer

DOEpatents

Wang, Jian

2013-10-29

A mobility spectrometer to measure a nanometer particle size distribution is disclosed. The mobility spectrometer includes a conduit and a detector. The conduit is configured to receive and provide fluid communication of a fluid stream having a charged nanometer particle mixture. The conduit includes a separator section configured to generate an electrical field of two dimensions transverse to a dimension associated with the flow of the charged nanometer particle mixture through the separator section to spatially separate charged nanometer particles of the charged nanometer particle mixture in said two dimensions. The detector is disposed downstream of the conduit to detect concentration and position of the spatially-separated nanometer particles.

Detecting changes in the spatial distribution of nitrate contamination in ground water

USGS Publications Warehouse

Liu, Z.-J.; Hallberg, G.R.; Zimmerman, D.L.; Libra, R.D.

1997-01-01

Many studies of ground water pollution in general and nitrate contamination in particular have often relied on a one-time investigation, tracking of individual wells, or aggregate summaries. Studies of changes in spatial distribution of contaminants over time are lacking. This paper presents a method to compare spatial distributions for possible changes over time. The large-scale spatial distribution at a given time can be considered as a surface over the area (a trend surface). The changes in spatial distribution from period to period can be revealed by the differences in the shape and/or height of surfaces. If such a surface is described by a polynomial function, changes in surfaces can be detected by testing statistically for differences in their corresponding polynomial functions. This method was applied to nitrate concentration in a population of wells in an agricultural drainage basin in Iowa, sampled in three different years. For the period of 1981-1992, the large-scale spatial distribution of nitrate concentration did not show significant change in the shape of spatial surfaces; while the magnitude of nitrate concentration in the basin, or height of the computed surfaces showed significant fluctuations. The change in magnitude of nitrate concentration is closely related to climatic variations, especially in precipitation. The lack of change in the shape of spatial surfaces means that either the influence of land use/nitrogen management was overshadowed by climatic influence, or the changes in land use/management occurred in a random fashion.

Spatial Distribution of Bed Particles in Natural Boulder-Bed Streams

NASA Astrophysics Data System (ADS)

Clancy, K. F.; Prestegaard, K. L.

2001-12-01

The Wolman pebble count is used to obtain the size distribution of bed particles in natural streams. Statistics such as median particle size (D50) are used in resistance calculations. Additional information such as bed particle heterogeneity may also be obtained from the particle distribution, which is used to predict sediment transport rates (Hey, 1979), (Ferguson, Prestegaard, Ashworth, 1989). Boulder-bed streams have an extreme range of particles in the particle size distribution ranging from sand size particles to particles larger than 0.5-m. A study of a natural boulder-bed reach demonstrated that the spatial distribution of the particles is a significant factor in predicting sediment transport and stream bed and bank stability. Further experiments were performed to test the limits of the spatial distribution's effect on sediment transport. Three stream reaches 40-m in length were selected with similar hydrologic characteristics and spatial distributions but varying average size particles. We used a grid 0.5 by 0.5-m and measured four particles within each grid cell. Digital photographs of the streambed were taken in each grid cell. The photographs were examined using image analysis software to obtain particle size and position of the largest particles (D84) within the reach's particle distribution. Cross section, topography and stream depth were surveyed. Velocity and velocity profiles were measured and recorded. With these data and additional surveys of bankfull floods, we tested the significance of the spatial distributions as average particle size decreases. The spatial distribution of streambed particles may provide information about stream valley formation, bank stability, sediment transport, and the growth rate of riparian vegetation.

Integrating biological and social values when prioritizing places for biodiversity conservation.

PubMed

Whitehead, Amy L; Kujala, Heini; Ives, Christopher D; Gordon, Ascelin; Lentini, Pia E; Wintle, Brendan A; Nicholson, Emily; Raymond, Christopher M

2014-08-01

The consideration of information on social values in conjunction with biological data is critical for achieving both socially acceptable and scientifically defensible conservation planning outcomes. However, the influence of social values on spatial conservation priorities has received limited attention and is poorly understood. We present an approach that incorporates quantitative data on social values for conservation and social preferences for development into spatial conservation planning. We undertook a public participation GIS survey to spatially represent social values and development preferences and used species distribution models for 7 threatened fauna species to represent biological values. These spatially explicit data were simultaneously included in the conservation planning software Zonation to examine how conservation priorities changed with the inclusion of social data. Integrating spatially explicit information about social values and development preferences with biological data produced prioritizations that differed spatially from the solution based on only biological data. However, the integrated solutions protected a similar proportion of the species' distributions, indicating that Zonation effectively combined the biological and social data to produce socially feasible conservation solutions of approximately equivalent biological value. We were able to identify areas of the landscape where synergies and conflicts between different value sets are likely to occur. Identification of these synergies and conflicts will allow decision makers to target communication strategies to specific areas and ensure effective community engagement and positive conservation outcomes. © 2014 Society for Conservation Biology.

Spatial distribution and optimal harvesting of an age-structured population in a fluctuating environment.

PubMed

Engen, Steinar; Lee, Aline Magdalena; Sæther, Bernt-Erik

2018-02-01

We analyze a spatial age-structured model with density regulation, age specific dispersal, stochasticity in vital rates and proportional harvesting. We include two age classes, juveniles and adults, where juveniles are subject to logistic density dependence. There are environmental stochastic effects with arbitrary spatial scales on all birth and death rates, and individuals of both age classes are subject to density independent dispersal with given rates and specified distributions of dispersal distances. We show how to simulate the joint density fields of the age classes and derive results for the spatial scales of all spatial autocovariance functions for densities. A general result is that the squared scale has an additive term equal to the squared scale of the environmental noise, corresponding to the Moran effect, as well as additive terms proportional to the dispersal rate and variance of dispersal distance for the age classes and approximately inversely proportional to the strength of density regulation. We show that the optimal harvesting strategy in the deterministic case is to harvest only juveniles when their relative value (e.g. financial) is large, and otherwise only adults. With increasing environmental stochasticity there is an interval of increasing length of values of juveniles relative to adults where both age classes should be harvested. Harvesting generally tends to increase all spatial scales of the autocovariances of densities. Copyright © 2017. Published by Elsevier Inc.

Using Electromagnetic Induction Technique to Detect Hydropedological Dynamics: Principles and Applications

NASA Astrophysics Data System (ADS)

Zhu, Qing; Liao, Kaihua; Doolittle, James; Lin, Henry

2014-05-01

Hydropedological dynamics including soil moisture variation, subsurface flow, and spatial distributions of different soil properties are important parameters in ecological, environmental, hydrological, and agricultural modeling and applications. However, technical gap exists in mapping these dynamics at intermediate spatial scale (e.g., farm and catchment scales). At intermediate scales, in-situ monitoring provides detailed data, but is restricted in number and spatial coverage; while remote sensing provides more acceptable spatial coverage, but has comparatively low spatial resolution, limited observation depths, and is greatly influenced by the surface condition and climate. As a non-invasive, fast, and convenient geophysical tool, electromagnetic induction (EMI) measures soil apparent electrical conductivity (ECa) and has great potential to bridge this technical gap. In this presentation, principles of different EMI meters are briefly introduced. Then, case studies of using repeated EMI to detect spatial distributions of subsurface convergent flow, soil moisture dynamics, soil types and their transition zones, and different soil properties are presented. The suitability, effectiveness, and accuracy of EMI are evaluated for mapping different hydropedological dynamics. Lastly, contributions of different hydropedological and terrain properties on soil ECa are quantified under different wetness conditions, seasons, and land use types using Classification and Regression Tree model. Trend removal and residual analysis are then used for further mining of EMI survey data. Based on these analyses, proper EMI survey designs and data processing are proposed.

The Spatial Distribution of Forest Biomass in the Brazilian Amazon: A Comparison of Estimates

NASA Technical Reports Server (NTRS)

Houghton, R. A.; Lawrence, J. L.; Hackler, J. L.; Brown, S.

2001-01-01

The amount of carbon released to the atmosphere as a result of deforestation is determined, in part, by the amount of carbon held in the biomass of the forests converted to other uses. Uncertainty in forest biomass is responsible for much of the uncertainty in current estimates of the flux of carbon from land-use change. We compared several estimates of forest biomass for the Brazilian Amazon, based on spatial interpolations of direct measurements, relationships to climatic variables, and remote sensing data. We asked three questions. First, do the methods yield similar estimates? Second, do they yield similar spatial patterns of distribution of biomass? And, third, what factors need most attention if we are to predict more accurately the distribution of forest biomass over large areas? Amazonian forests (including dead and below-ground biomass) vary by more than a factor of two, from a low of 39 PgC to a high of 93 PgC. Furthermore, the estimates disagree as to the regions of high and low biomass. The lack of agreement among estimates confirms the need for reliable determination of aboveground biomass over large areas. Potential methods include direct measurement of biomass through forest inventories with improved allometric regression equations, dynamic modeling of forest recovery following observed stand-replacing disturbances (the approach used in this research), and estimation of aboveground biomass from airborne or satellite-based instruments sensitive to the vertical structure plant canopies.

Mesoscale raised rim depressions (MRRDs) on Earth: A review of the characteristics, processes, and spatial distributions of analogs for Mars

USGS Publications Warehouse

Burr, D.M.; Bruno, B.C.; Lanagan, P.D.; Glaze, L.S.; Jaeger, W.L.; Soare, R.J.; Wan, Bun Tseung J.-M.; Skinner, J.A.; Baloga, S.M.

2009-01-01

Fields of mesoscale raised rim depressions (MRRDs) of various origins are found on Earth and Mars. Examples include rootless cones, mud volcanoes, collapsed pingos, rimmed kettle holes, and basaltic ring structures. Correct identification of MRRDs on Mars is valuable because different MRRD types have different geologic and/or climatic implications and are often associated with volcanism and/or water, which may provide locales for biotic or prebiotic activity. In order to facilitate correct identification of fields of MRRDs on Mars and their implications, this work provides a review of common terrestrial MRRD types that occur in fields. In this review, MRRDs by formation mechanism, including hydrovolcanic (phreatomagmatic cones, basaltic ring structures), sedimentological (mud volcanoes), and ice-related (pingos, volatile ice-block forms) mechanisms. For each broad mechanism, we present a comparative synopsis of (i) morphology and observations, (ii) physical formation processes, and (iii) published hypothesized locations on Mars. Because the morphology for MRRDs may be ambiguous, an additional tool is provided for distinguishing fields of MRRDs by origin on Mars, namely, spatial distribution analyses for MRRDs within fields on Earth. We find that MRRDs have both distinguishing and similar characteristics, and observation that applies both to their mesoscale morphology and to their spatial distribution statistics. Thus, this review provides tools for distinguishing between various MRRDs, while highlighting the utility of the multiple working hypotheses approach. ?? 2008 Elsevier Ltd.

The multisensor payload 'Structura' for the observation of atmospheric night glows from the ISS board

NASA Astrophysics Data System (ADS)

Krot, Yury; Beliaev, Boris; Katkovsky, Leonid

2016-10-01

Aerospace Research Department of the Institute of Applied Physical Problems at Belarusian State University has developed a prototype of the optical payload intended for a space experiment on the ISS board. The prototype includes four optical modules for the night glows observation, in particular spatial-brightness and spectral characteristics in the altitude range of 80-320 km. Objects of the interest are emitting top layers of the atmosphere including exited OH radicals, atomic and molecular oxygen and sodium layers. The goal of the space experiment is a research of night glows over different regions of the Earth and a connection with natural disasters like earthquakes, cyclones, etc. Two optical modules for spatial distribution of atomic oxygen layers along the altitude consist of input lenses, spectral interferential filters and line CCD detectors. The optical module for registration of exited OH radical emissions is formed from CCD array spectrometer. The payload includes also a panchromatic (400-900 nm) high sensitive imaging camera for observing of the glows general picture. The optical modules of the prototype have been tested and general optical characteristics were determined in laboratory conditions. A solution of an astigmatism reducing of a concave diffraction grating and a method of the second diffraction order correction were applied and improved spectrometer's optical characteristics. Laboratory equipment and software were developed to imitate a dynamic scene of the night glows in laboratory conditions including an imitation of linear spectra and the spatial distribution of emissions.

Effect of long-term mechanical perturbation on intertidal soft-bottom meiofaunal community spatial structure

NASA Astrophysics Data System (ADS)

Boldina, Inna; Beninger, Peter G.; Le Coz, Maïwen

2014-01-01

Situated at the interface of the microbial and macrofaunal compartments, soft-bottom meiofauna accomplish important ecological functions. However, little is known of their spatial distribution in the benthic environment. To assess the effects of long-term mechanical disturbance on soft-bottom meiofaunal spatial distribution, we compared a site subjected to long-term clam digging to a nearby site untouched by such activities, in Bourgneuf Bay, on the Atlantic coast of France. Six patterned replicate samples were taken at 3, 6, 9, 12, 15, 18, 21 and 24 cm lags, all sampling stations being separated by 5 m. A combined correlogram-variogram approach was used to enhance interpretation of the meiofaunal spatial distribution; in particular, the definition of autocorrelation strength and its statistical significance, as well as the detailed characteristics of the periodic spatial structure of nematode assemblages, and the determination of the maximum distance of their spatial autocorrelation. At both sites, nematodes and copepods clearly exhibited aggregated spatial structure at the meso scale; this structure was attenuated at the impacted site. The nematode spatial distribution showed periodicity at the non-impacted site, but not at the impacted site. This is the first explicit report of a periodic process in meiofaunal spatial distribution. No such cyclic spatial process was observed for the more motile copepods at either site. This first study to indicate the impacts of long-term anthropogenic mechanical perturbation on meiofaunal spatial structure opens the door to a new dimension of mudflat ecology. Since macrofaunal predator search behaviour is known to be strongly influenced by prey spatial structure, the alteration of this structure may have important consequences for ecosystem functioning.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Monitoring Method of Cow Anthrax Based on Gis and Spatial Statistical Analysis

NASA Astrophysics Data System (ADS)

Li, Lin; Yang, Yong; Wang, Hongbin; Dong, Jing; Zhao, Yujun; He, Jianbin; Fan, Honggang

Geographic information system (GIS) is a computer application system, which possesses the ability of manipulating spatial information and has been used in many fields related with the spatial information management. Many methods and models have been established for analyzing animal diseases distribution models and temporal-spatial transmission models. Great benefits have been gained from the application of GIS in animal disease epidemiology. GIS is now a very important tool in animal disease epidemiological research. Spatial analysis function of GIS can be widened and strengthened by using spatial statistical analysis, allowing for the deeper exploration, analysis, manipulation and interpretation of spatial pattern and spatial correlation of the animal disease. In this paper, we analyzed the cow anthrax spatial distribution characteristics in the target district A (due to the secret of epidemic data we call it district A) based on the established GIS of the cow anthrax in this district in combination of spatial statistical analysis and GIS. The Cow anthrax is biogeochemical disease, and its geographical distribution is related closely to the environmental factors of habitats and has some spatial characteristics, and therefore the correct analysis of the spatial distribution of anthrax cow for monitoring and the prevention and control of anthrax has a very important role. However, the application of classic statistical methods in some areas is very difficult because of the pastoral nomadic context. The high mobility of livestock and the lack of enough suitable sampling for the some of the difficulties in monitoring currently make it nearly impossible to apply rigorous random sampling methods. It is thus necessary to develop an alternative sampling method, which could overcome the lack of sampling and meet the requirements for randomness. The GIS computer application software ArcGIS9.1 was used to overcome the lack of data of sampling sites.Using ArcGIS 9.1 and GEODA to analyze the cow anthrax spatial distribution of district A. we gained some conclusions about cow anthrax' density: (1) there is a spatial clustering model. (2) there is an intensely spatial autocorrelation. We established a prediction model to estimate the anthrax distribution based on the spatial characteristic of the density of cow anthrax. Comparing with the true distribution, the prediction model has a well coincidence and is feasible to the application. The method using a GIS tool facilitates can be implemented significantly in the cow anthrax monitoring and investigation, and the space statistics - related prediction model provides a fundamental use for other study on space-related animal diseases.

Electric crosstalk impairs spatial resolution of multi-electrode arrays in retinal implants

NASA Astrophysics Data System (ADS)

Wilke, R. G. H.; Khalili Moghadam, G.; Lovell, N. H.; Suaning, G. J.; Dokos, S.

2011-08-01

Active multi-electrode arrays are used in vision prostheses, including optic nerve cuffs and cortical and retinal implants for stimulation of neural tissue. For retinal implants, arrays with up to 1500 electrodes are used in clinical trials. The ability to convey information with high spatial resolution is critical for these applications. To assess the extent to which spatial resolution is impaired by electric crosstalk, finite-element simulation of electric field distribution in a simplified passive tissue model of the retina is performed. The effects of electrode size, electrode spacing, distance to target cells, and electrode return configuration (monopolar, tripolar, hexagonal) on spatial resolution is investigated in the form of a mathematical model of electric field distribution. Results show that spatial resolution is impaired with increased distance from the electrode array to the target cells. This effect can be partly compensated by non-monopolar electrode configurations and larger electrode diameters, albeit at the expense of lower pixel densities due to larger covering areas by each stimulation electrode. In applications where multi-electrode arrays can be brought into close proximity to target cells, as presumably with epiretinal implants, smaller electrodes in monopolar configuration can provide the highest spatial resolution. However, if the implantation site is further from the target cells, as is the case in suprachoroidal approaches, hexagonally guarded electrode return configurations can convey higher spatial resolution. This paper was originally submitted for the special issue containing contributions from the Sixth Biennial Research Congress of The Eye and the Chip.

A log-Weibull spatial scan statistic for time to event data.

PubMed

Usman, Iram; Rosychuk, Rhonda J

2018-06-13

Spatial scan statistics have been used for the identification of geographic clusters of elevated numbers of cases of a condition such as disease outbreaks. These statistics accompanied by the appropriate distribution can also identify geographic areas with either longer or shorter time to events. Other authors have proposed the spatial scan statistics based on the exponential and Weibull distributions. We propose the log-Weibull as an alternative distribution for the spatial scan statistic for time to events data and compare and contrast the log-Weibull and Weibull distributions through simulation studies. The effect of type I differential censoring and power have been investigated through simulated data. Methods are also illustrated on time to specialist visit data for discharged patients presenting to emergency departments for atrial fibrillation and flutter in Alberta during 2010-2011. We found northern regions of Alberta had longer times to specialist visit than other areas. We proposed the spatial scan statistic for the log-Weibull distribution as a new approach for detecting spatial clusters for time to event data. The simulation studies suggest that the test performs well for log-Weibull data.

Preliminary surficial geologic map of a Calico Mountains piedmont and part of Coyote Lake, Mojave desert, San Bernardino County, California

USGS Publications Warehouse

Dudash, Stephanie L.

2006-01-01

This 1:24,000 scale detailed surficial geologic map and digital database of a Calico Mountains piedmont and part of Coyote Lake in south-central California depicts surficial deposits and generalized bedrock units. The mapping is part of a USGS project to investigate the spatial distribution of deposits linked to changes in climate, to provide framework geology for land use management (http://deserts.wr.usgs.gov), to understand the Quaternary tectonic history of the Mojave Desert, and to provide additional information on the history of Lake Manix, of which Coyote Lake is a sub-basin. Mapping is displayed on parts of four USGS 7.5 minute series topographic maps. The map area lies in the central Mojave Desert of California, northeast of Barstow, Calif. and south of Fort Irwin, Calif. and covers 258 sq.km. (99.5 sq.mi.). Geologic deposits in the area consist of Paleozoic metamorphic rocks, Mesozoic plutonic rocks, Miocene volcanic rocks, Pliocene-Pleistocene basin fill, and Quaternary surficial deposits. McCulloh (1960, 1965) conducted bedrock mapping and a generalized version of his maps are compiled into this map. McCulloh's maps contain many bedrock structures within the Calico Mountains that are not shown on the present map. This study resulted in several new findings, including the discovery of previously unrecognized faults, one of which is the Tin Can Alley fault. The north-striking Tin Can Alley fault is part of the Paradise fault zone (Miller and others, 2005), a potentially important feature for studying neo-tectonic strain in the Mojave Desert. Additionally, many Anodonta shells were collected in Coyote Lake lacustrine sediments for radiocarbon dating. Preliminary results support some of Meek's (1999) conclusions on the timing of Mojave River inflow into the Coyote Basin. The database includes information on geologic deposits, samples, and geochronology. The database is distributed in three parts: spatial map-based data, documentation, and printable map graphics of the database. Spatial data are distributed as an ArcInfo personal geodatabase, or as tabular data in the form of Microsoft Access Database (MDB) or dBase Format (DBF) file formats. Documentation includes this file, which provides a discussion of the surficial geology and describes the format and content of the map data, and Federal Geographic Data Committee (FGDC) metadata for the spatial map information. Map graphics files are distributed as Postscript and Adobe Acrobat Portable Document Format (PDF) files, and are appropriate for representing a view of the spatial database at the mapped scale.

Spatially distributed multipartite entanglement enables EPR steering of atomic clouds

NASA Astrophysics Data System (ADS)

Kunkel, Philipp; Prüfer, Maximilian; Strobel, Helmut; Linnemann, Daniel; Frölian, Anika; Gasenzer, Thomas; Gärttner, Martin; Oberthaler, Markus K.

2018-04-01

A key resource for distributed quantum-enhanced protocols is entanglement between spatially separated modes. However, the robust generation and detection of entanglement between spatially separated regions of an ultracold atomic system remain a challenge. We used spin mixing in a tightly confined Bose-Einstein condensate to generate an entangled state of indistinguishable particles in a single spatial mode. We show experimentally that this entanglement can be spatially distributed by self-similar expansion of the atomic cloud. We used spatially resolved spin read-out to reveal a particularly strong form of quantum correlations known as Einstein-Podolsky-Rosen (EPR) steering between distinct parts of the expanded cloud. Based on the strength of EPR steering, we constructed a witness, which confirmed genuine 5-partite entanglement.

Population at risk: using areal interpolation and Twitter messages to create population models for burglaries and robberies

PubMed Central

2018-01-01

ABSTRACT Population at risk of crime varies due to the characteristics of a population as well as the crime generator and attractor places where crime is located. This establishes different crime opportunities for different crimes. However, there are very few efforts of modeling structures that derive spatiotemporal population models to allow accurate assessment of population exposure to crime. This study develops population models to depict the spatial distribution of people who have a heightened crime risk for burglaries and robberies. The data used in the study include: Census data as source data for the existing population, Twitter geo-located data, and locations of schools as ancillary data to redistribute the source data more accurately in the space, and finally gridded population and crime data to evaluate the derived population models. To create the models, a density-weighted areal interpolation technique was used that disaggregates the source data in smaller spatial units considering the spatial distribution of the ancillary data. The models were evaluated with validation data that assess the interpolation error and spatial statistics that examine their relationship with the crime types. Our approach derived population models of a finer resolution that can assist in more precise spatial crime analyses and also provide accurate information about crime rates to the public. PMID:29887766

Identifying the driving forces of urban expansion and its environmental impact in Jakarta-Bandung mega urban region

NASA Astrophysics Data System (ADS)

Pravitasari, A. E.; Rustiadi, E.; Mulya, S. P.; Setiawan, Y.; Fuadina, L. N.; Murtadho, A.

2018-05-01

The socio-economic development in Jakarta-Bandung Mega Urban Region (JBMUR) caused the increasing of urban expansion and led to a variety of environmental damage such as uncontrolled land use conversion and raising anthropogenic disaster. The objectives of this study are: (1) to identify the driving forces of urban expansion that occurs on JBMUR and (2) to analyze the environmental quality decline on JBMUR by producing time series spatial distribution map and spatial autocorrelation of floods and landslide as the proxy of anthropogenic disaster. The driving forces of urban expansion in this study were identified by employing Geographically Weighted Regression (GWR) model using 6 (six) independent variables, namely: population density, percentage of agricultural land, distance to the center of capital city/municipality, percentage of household who works in agricultural sector, distance to the provincial road, and distance to the local road. The GWR results showed that local demographic, social and economic factors including distance to the road spatially affect urban expansion in JBMUR. The time series spatial distribution map of floods and landslide event showed the spatial cluster of anthropogenic disaster in some areas. Through Local Moran Index, we found that environmental damage in one location has a significant impact on the condition of its surrounding area.

A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores

PubMed Central

Neelon, Brian; Gelfand, Alan E.; Miranda, Marie Lynn

2013-01-01

Summary Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from different cognitive domains. We propose a multivariate spatial mixture model for the joint analysis of continuous individual-level outcomes that are referenced to areal units. The responses are modeled as a finite mixture of multivariate normals, which accommodates a wide range of marginal response distributions and allows investigators to examine covariate effects within subpopulations of interest. The model has a hierarchical structure built at the individual level (i.e., individuals are nested within areal units), and thus incorporates both individual- and areal-level predictors as well as spatial random effects for each mixture component. Conditional autoregressive (CAR) priors on the random effects provide spatial smoothing and allow the shape of the multivariate distribution to vary flexibly across geographic regions. We adopt a Bayesian modeling approach and develop an efficient Markov chain Monte Carlo model fitting algorithm that relies primarily on closed-form full conditionals. We use the model to explore geographic patterns in end-of-grade math and reading test scores among school-age children in North Carolina. PMID:26401059

Spatial and seasonal dynamics of brook trout populations inhabiting a central Appalachian watershed

USGS Publications Warehouse

Petty, J.T.; Lamothe, P.J.; Mazik, P.M.

2005-01-01

We quantified the watershed-scale spatial population dynamics of brook trout Salvelinus fontinalis in the Second Fork, a third-order tributary of Shavers Fork in eastern West Virginia. We used visual surveys, electrofishing, and mark-recapture techniques to quantify brook trout spawning intensity, population density, size structure, and demographic rates (apparent survival and immigration) throughout the watershed. Our analyses produced the following results. Spawning by brook trout was concentrated in streams with small basin areas (i.e., segments draining less than 3 km2), relatively high alkalinity (>10 mg CaCO3/L), and high amounts of instream cover. The spatial distribution of juvenile and small-adult brook trout within the watershed was relatively stable and was significantly correlated with spawning intensity. However, no such relationship was observed for large adults, which exhibited highly variable distribution patterns related to seasonally important habitat features, including instream cover, stream depth and width, and riparian canopy cover. Brook trout survival and immigration rates varied seasonally, spatially, and among size-classes. Differential survival and immigration tended to concentrate juveniles and small adults in small, alkaline streams, whereas dispersal tended to redistribute large adults at the watershed scale. Our results suggest that spatial and temporal variations in spawning, survival, and movement interact to determine the distribution, abundance, and size structure of brook trout populations at a watershed scale. These results underscore the importance of small tributaries for the persistence of brook trout in this watershed and the need to consider watershed-scale processes when designing management plans for Appalachian brook trout populations. ?? Copyright by the American Fisheries Society 2005.

Estimated home ranges can misrepresent habitat relationships on patchy landscapes

USGS Publications Warehouse

Mitchell, M.S.; Powell, R.A.

2008-01-01

Home ranges of animals are generally structured by the selective use of resource-bearing patches that comprise habitat. Based on this concept, home ranges of animals estimated from location data are commonly used to infer habitat relationships. Because home ranges estimated from animal locations are largely continuous in space, the resource-bearing patches selected by an animal from a fragmented distribution of patches would be difficult to discern; unselected patches included in the home range estimate would bias an understanding of important habitat relationships. To evaluate potential for this bias, we generated simulated home ranges based on optimal selection of resource-bearing patches across a series of simulated resource distributions that varied in the spatial continuity of resources. For simulated home ranges where selected patches were spatially disjunct, we included interstitial, unselected cells most likely to be traveled by an animal moving among selected patches. We compared characteristics of the simulated home ranges with and without interstitial patches to evaluate how insights derived from field estimates can differ from actual characteristics of home ranges, depending on patchiness of landscapes. Our results showed that contiguous home range estimates could lead to misleading insights on the quality, size, resource content, and efficiency of home ranges, proportional to the spatial discontinuity of resource-bearing patches. We conclude the potential bias of including unselected, largely irrelevant patches in the field estimates of home ranges of animals can be high, particularly for home range estimators that assume uniform use of space within home range boundaries. Thus, inferences about the habitat relationships that ultimately define an animal's home range can be misleading where animals occupy landscapes with patchily distributed resources.

Coordination of genomic structure and transcription by the main bacterial nucleoid-associated protein HU

PubMed Central

Berger, Michael; Farcas, Anca; Geertz, Marcel; Zhelyazkova, Petya; Brix, Klaudia; Travers, Andrew; Muskhelishvili, Georgi

2010-01-01

The histone-like protein HU is a highly abundant DNA architectural protein that is involved in compacting the DNA of the bacterial nucleoid and in regulating the main DNA transactions, including gene transcription. However, the coordination of the genomic structure and function by HU is poorly understood. Here, we address this question by comparing transcript patterns and spatial distributions of RNA polymerase in Escherichia coli wild-type and hupA/B mutant cells. We demonstrate that, in mutant cells, upregulated genes are preferentially clustered in a large chromosomal domain comprising the ribosomal RNA operons organized on both sides of OriC. Furthermore, we show that, in parallel to this transcription asymmetry, mutant cells are also impaired in forming the transcription foci—spatially confined aggregations of RNA polymerase molecules transcribing strong ribosomal RNA operons. Our data thus implicate HU in coordinating the global genomic structure and function by regulating the spatial distribution of RNA polymerase in the nucleoid. PMID:20010798

What are the most crucial soil factors for predicting the distribution of alpine plant species?

NASA Astrophysics Data System (ADS)

Buri, A.; Pinto-Figueroa, E.; Yashiro, E.; Guisan, A.

2017-12-01

Nowadays the use of species distribution models (SDM) is common to predict in space and time the distribution of organisms living in the critical zone. The realized environmental niche concept behind the development of SDM imply that many environmental factors must be accounted for simultaneously to predict species distributions. Climatic and topographic factors are often primary included, whereas soil factors are frequently neglected, mainly due to the paucity of soil information available spatially and temporally. Furthermore, among existing studies, most included soil pH only, or few other soil parameters. In this study we aimed at identifying what are the most crucial soil factors for explaining alpine plant distributions and, among those identified, which ones further improve the predictive power of plant SDMs. To test the relative importance of the soil factors, we performed plant SDMs using as predictors 52 measured soil properties of various types such as organic/inorganic compounds, chemical/physical properties, water related variables, mineral composition or grain size distribution. We added them separately to a standard set of topo-climatic predictors (temperature, slope, solar radiation and topographic position). We used ensemble forecasting techniques combining together several predictive algorithms to model the distribution of 116 plant species over 250 sites in the Swiss Alps. We recorded the variable importance for each model and compared the quality of the models including different soil proprieties (one at a time) as predictors to models having only topo-climatic variables as predictors. Results show that 46% of the soil proprieties tested become the second most important variable, after air temperature, to explain spatial distribution of alpine plants species. Moreover, we also assessed that addition of certain soil factors, such as bulk soil water density, could improve over 80% the quality of some plant species models. We confirm that soil pH remains one of the most important soil factor for predicting plant species distributions, closely followed by water, organic and inorganic carbon related properties. Finally, we were able to extract three main categories of important soil properties for plant species distributions: grain size distribution, acidity and water in the soil.

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Bhaskar, A.; Fleming, B.; Hogan, D. M.

2016-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Burke, W.; Tague, C.

2017-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

Simulation of space-based (GRACE) gravity variations caused by storage changes in large confined and unconfined aquifers

NASA Astrophysics Data System (ADS)

Pool, D. R.; Scanlon, B. R.

2017-12-01

There is uncertainty of how storage change in confined and unconfined aquifers would register from space-based platforms, such as the GRACE (Gravity Recovery and Climate Experiment) satellites. To address this concern, superposition groundwater models (MODFLOW) of equivalent storage change in simplified confined and unconfined aquifers of extent, 500 km2 or approximately 5X5 degrees at mid-latitudes, and uniform transmissivity were constructed. Gravity change resulting from the spatial distribution of aquifer storage change for each aquifer type was calculated at the initial GRACE satellite altitude ( 500 km). To approximate real-world conditions, the confined aquifer includes a small region of unconfined conditions at one margin. A uniform storage coefficient (specific yield) was distributed across the unconfined aquifer. For both cases, storage change was produced by 1 year of groundwater withdrawal from identical aquifer-centered well distributions followed by decades of no withdrawal and redistribution of the initial storage loss toward a new steady-state condition. The transient simulated storage loss includes equivalent volumes for both conceptualizations, but spatial distributions differ because of the contrasting aquifer diffusivity (Transmissivity/Storativity). Much higher diffusivity in the confined aquifer results in more rapid storage redistribution across a much larger area than for the unconfined aquifer. After the 1 year of withdrawals, the two simulated storage loss distributions are primarily limited to small regions within the model extent. Gravity change after 1 year observed at the satellite altitude is similar for both aquifers including maximum gravity reductions that are coincident with the aquifer center. With time, the maximum gravity reduction for the confined aquifer case shifts toward the aquifer margin as much as 200 km because of increased storage loss in the unconfined region. Results of the exercise indicate that GRACE observations are largely insensitive to confined or unconfined conditions for most aquifers. Lateral shifts in storage change with time in confined aquifers could be resolved by space-based gravity missions with durations of decades and improved spatial resolution, 1 degree or less ( 100 km), over the GRACE resolution of 3 degrees ( 300 km).

Silver hake tracks changes in Northwest Atlantic circulation.

PubMed

Nye, Janet A; Joyce, Terrence M; Kwon, Young-Oh; Link, Jason S

2011-08-02

Recent studies documenting shifts in spatial distribution of many organisms in response to a warming climate highlight the need to understand the mechanisms underlying species distribution at large spatial scales. Here we present one noteworthy example of remote oceanographic processes governing the spatial distribution of adult silver hake, Merluccius bilinearis, a commercially important fish in the Northeast US shelf region. Changes in spatial distribution of silver hake over the last 40 years are highly correlated with the position of the Gulf Stream. These changes in distribution are in direct response to local changes in bottom temperature on the continental shelf that are responding to the same large scale circulation change affecting the Gulf Stream path, namely changes in the Atlantic meridional overturning circulation (AMOC). If the AMOC weakens, as is suggested by global climate models, silver hake distribution will remain in a poleward position, the extent to which could be forecast at both decadal and multidecadal scales.

Mosquito-producing containers, spatial distribution, and relationship between Aedes aegypti population indices on the southern boundary of its distribution in South America (Salto, Uruguay).

PubMed

Basso, César; Caffera, Ruben M; García da Rosa, Elsa; Lairihoy, Rosario; González, Cristina; Norbis, Walter; Roche, Ingrid

2012-12-01

A study was conducted in the city of Salto, Uruguay, to identify mosquito-producing containers, the spatial distribution of mosquitoes and the relationship between the different population indices of Aedes aegypti. On each of 312 premises visited, water-filled containers and immature Ae. aegypti mosquitoes were identified. The containers were counted and classified into six categories. Pupae per person and Stegomyia indices were calculated. Pupae per person were represented spatially. The number of each type of container and number of mosquitoes in each were analyzed and compared, and their spatial distribution was analyzed. No significant differences in the number of the different types of containers with mosquitoes or in the number of mosquitoes in each were found. The distribution of the containers with mosquito was random and the distribution of mosquitoes by type of container was aggregated or highly aggregated.

Mosquito-Producing Containers, Spatial Distribution, and Relationship between Aedes aegypti Population Indices on the Southern Boundary of its Distribution in South America (Salto, Uruguay)

PubMed Central

Basso, César; Caffera, Ruben M.; García da Rosa, Elsa; Lairihoy, Rosario; González, Cristina; Norbis, Walter; Roche, Ingrid

2012-01-01

A study was conducted in the city of Salto, Uruguay, to identify mosquito-producing containers, the spatial distribution of mosquitoes and the relationship between the different population indices of Aedes aegypti. On each of 312 premises visited, water-filled containers and immature Ae. aegypti mosquitoes were identified. The containers were counted and classified into six categories. Pupae per person and Stegomyia indices were calculated. Pupae per person were represented spatially. The number of each type of container and number of mosquitoes in each were analyzed and compared, and their spatial distribution was analyzed. No significant differences in the number of the different types of containers with mosquitoes or in the number of mosquitoes in each were found. The distribution of the containers with mosquito was random and the distribution of mosquitoes by type of container was aggregated or highly aggregated. PMID:23128295

Quantitative characterization of the spatial distribution of particles in materials: Application to materials processing

NASA Technical Reports Server (NTRS)

Parse, Joseph B.; Wert, J. A.

1991-01-01

Inhomogeneities in the spatial distribution of second phase particles in engineering materials are known to affect certain mechanical properties. Progress in this area has been hampered by the lack of a convenient method for quantitative description of the spatial distribution of the second phase. This study intends to develop a broadly applicable method for the quantitative analysis and description of the spatial distribution of second phase particles. The method was designed to operate on a desktop computer. The Dirichlet tessellation technique (geometrical method for dividing an area containing an array of points into a set of polygons uniquely associated with the individual particles) was selected as the basis of an analysis technique implemented on a PC. This technique is being applied to the production of Al sheet by PM processing methods; vacuum hot pressing, forging, and rolling. The effect of varying hot working parameters on the spatial distribution of aluminum oxide particles in consolidated sheet is being studied. Changes in distributions of properties such as through-thickness near-neighbor distance correlate with hot-working reduction.

Benefits of incorporating spatial organisation of catchments for a semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

Schumann, Andreas; Oppel, Henning

2017-04-01

To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark model setups (lumped and semi-distributed by common approaches) to address the benefits for different time and spatial scales. Moreover, the benefits for calibration effort, model performance in validation periods and process extrapolation are shown.

Spatial distribution of citizen science casuistic observations for different taxonomic groups.

PubMed

Tiago, Patrícia; Ceia-Hasse, Ana; Marques, Tiago A; Capinha, César; Pereira, Henrique M

2017-10-16

Opportunistic citizen science databases are becoming an important way of gathering information on species distributions. These data are temporally and spatially dispersed and could have limitations regarding biases in the distribution of the observations in space and/or time. In this work, we test the influence of landscape variables in the distribution of citizen science observations for eight taxonomic groups. We use data collected through a Portuguese citizen science database (biodiversity4all.org). We use a zero-inflated negative binomial regression to model the distribution of observations as a function of a set of variables representing the landscape features plausibly influencing the spatial distribution of the records. Results suggest that the density of paths is the most important variable, having a statistically significant positive relationship with number of observations for seven of the eight taxa considered. Wetland coverage was also identified as having a significant, positive relationship, for birds, amphibians and reptiles, and mammals. Our results highlight that the distribution of species observations, in citizen science projects, is spatially biased. Higher frequency of observations is driven largely by accessibility and by the presence of water bodies. We conclude that efforts are required to increase the spatial evenness of sampling effort from volunteers.

Spatial distribution patterns of soil mite communities and their relationships with edaphic factors in a 30-year tillage cornfield in northeast China.

PubMed

Liu, Jie; Gao, Meixiang; Liu, Jinwen; Guo, Yuxi; Liu, Dong; Zhu, Xinyu; Wu, Donghui

2018-01-01

Spatial distribution is an important topic in community ecology and a key to understanding the structure and dynamics of populations and communities. However, the available information related to the spatial patterns of soil mite communities in long-term tillage agroecosystems remains insufficient. In this study, we examined the spatial patterns of soil mite communities to explain the spatial relationships between soil mite communities and soil parameters. Soil fauna were sampled three times (August, September and October 2015) at 121 locations arranged regularly within a 400 m × 400 m monitoring plot. Additionally, we estimated the physical and chemical parameters of the same sampling locations. The distribution patterns of the soil mite community and the edaphic parameters were analyzed using a range of geostatistical tools. Moran's I coefficient showed that, during each sampling period, the total abundance of the soil mite communities and the abundance of the dominant mite populations were spatially autocorrelated. The soil mite communities demonstrated clear patchy distribution patterns within the study plot. These patterns were sampling period-specific. Cross-semivariograms showed both negative and positive cross-correlations between soil mite communities and environmental factors. Mantel tests showed a significant and positive relationship between soil mite community and soil organic matter and soil pH only in August. This study demonstrated that in the cornfield, the soil mite distribution exhibited strong or moderate spatial dependence, and the mites formed patches with sizes less than one hundred meters. In addition, in this long-term tillage agroecosystem, soil factors had less influence on the observed pattern of soil mite communities. Further experiments that take into account human activity and spatial factors should be performed to study the factors that drive the spatial distribution of soil microarthropods.

Distributed condition monitoring techniques of optical fiber composite power cable in smart grid

NASA Astrophysics Data System (ADS)

Sun, Zhihui; Liu, Yuan; Wang, Chang; Liu, Tongyu

2011-11-01

Optical fiber composite power cable such as optical phase conductor (OPPC) is significant for the development of smart grid. This paper discusses the distributed cable condition monitoring techniques of the OPPC, which adopts embedded single-mode fiber as the sensing medium. By applying optical time domain reflection and laser Raman scattering, high-resolution spatial positioning and high-precision distributed temperature measurement is executed. And the OPPC cable condition parameters including temperature and its location, current carrying capacity, and location of fracture and loss can be monitored online. OPPC cable distributed condition monitoring experimental system is set up, and the main parts including pulsed fiber laser, weak Raman signal reception, high speed acquisition and cumulative average processing, temperature demodulation and current carrying capacity analysis are introduced. The distributed cable condition monitoring techniques of the OPPC is significant for power transmission management and security.

Understanding the Distribution of Marine Megafauna in the English Channel Region: Identifying Key Habitats for Conservation within the Busiest Seaway on Earth

PubMed Central

McClellan, Catherine M.; Brereton, Tom; Dell'Amico, Florence; Johns, David G.; Cucknell, Anna-C.; Patrick, Samantha C.; Penrose, Rod; Ridoux, Vincent; Solandt, Jean-Luc; Stephan, Eric; Votier, Stephen C.; Williams, Ruth; Godley, Brendan J.

2014-01-01

The temperate waters of the North-Eastern Atlantic have a long history of maritime resource richness and, as a result, the European Union is endeavouring to maintain regional productivity and biodiversity. At the intersection of these aims lies potential conflict, signalling the need for integrated, cross-border management approaches. This paper focuses on the marine megafauna of the region. This guild of consumers was formerly abundant, but is now depleted and protected under various national and international legislative structures. We present a meta-analysis of available megafauna datasets using presence-only distribution models to characterise suitable habitat and identify spatially-important regions within the English Channel and southern bight of the North Sea. The integration of studies from dedicated and opportunistic observer programmes in the United Kingdom and France provide a valuable perspective on the spatial and seasonal distribution of various taxonomic groups, including large pelagic fishes and sharks, marine mammals, seabirds and marine turtles. The Western English Channel emerged as a hotspot of biodiversity for megafauna, while species richness was low in the Eastern English Channel. Spatial conservation planning is complicated by the highly mobile nature of marine megafauna, however they are important components of the marine environment and understanding their distribution is a first crucial step toward their inclusion into marine ecosystem management. PMID:24586985

Variations in spatial patterns of soil-vegetation properties and the emergence of multiple resilience thresholds within different debris flow fan positions

NASA Astrophysics Data System (ADS)

Mohseni, Neda; Hosseinzadeh, Seyed Reza; Sepehr, Adel; Golzarian, Mahmood Reza; Shabani, Farzin

2017-08-01

Debris flow fans are non-equilibrium landforms resulting from the spatial variations of debris flows deposited on them. This geomorphic disturbance involving the asymmetric redistribution of water and sediment may create spatially heterogeneous patterns of soil-vegetation along landforms. In this research, founded on field-based observations, we characterized the spatial patterns of some soil (e.g., particle size distribution including fine and coarse covers, and infiltration capacity) and vegetation (e.g., plant distance, vegetation density, patch size, and average number of patches) properties within different debris flow fan positions (Upper, Middle, and Lower fan) located at the base of the Binaloud Mountain hillslope in northeastern Iran. Thereafter, using a mathematical model of dry land vegetation dynamics, we calculated response trends of the different positions to the same environmental harshness gradient. Field measurements of soil-vegetation properties and infiltration rates showed that the asymmetric redistribution of debris flow depositions can cause statistically significant differences (P < 0.05) in the spatial patterns of soil and eco-hydrological characteristics along different landform positions. The results showed that mean plant distance, mean vegetation density, and the average number of patches decreased as the coarse covers increased toward the Lower fan plots. Conversely, an increase in infiltration rate was observed. The simulation results on the aerial images taken from different positions, illustrated that positions with a heterogeneous distribution of vegetation patterns were not desertified to the same degree of aridity. Thus, the Middle and Lower positions could survive under harsher aridity conditions, due to the emergence of more varied spatial vegetation patterns than at the Upper fan position. The findings, based on a combined field and modeling approach, highlighted that debris flow as a geomorphic process with the asymmetric distribution of depositions on the gentle slope of an alluvial fan, can incur multiple resilience thresholds with different degrees of self-organization under stressful conditions over the spatial heterogeneities of soil-dependent vegetation structures.

Wolverine conservation and management.

Treesearch

L.F. Ruggiero; K.S. McKelvey; K.B. Aubry; J.P. Copeland; D.H. Pletscher; M.G. Hornocker

2007-01-01

This Special Section includes 8 peer-reviewed papers on the wolverine (Gulo gulo) in southern North America. These papers provide new information on current and historical distribution, habitat relations at multiple spatial scales, and interaction with humans. In aggregate, these papers substantially increase our knowledge of wolverine ecology and...

Wolverine conservation and management

Treesearch

Leonard F. Ruggiero; Kevin S. Mckelvey; Keith B. Aubry; Jeffrey P. Copeland; Daniel H. Pletscher; Maurice G. Hornocker

2007-01-01

This Special Section includes 8 peer-reviewed papers on the wolverine (Gulo gulo) in southern North America. These papers provide new information on current and historical distribution, habitat relations at multiple spatial scales, and interactions with humans. In aggregate, these papers substantially increase our knowledge of wolverine ecology and...

Irrigation system management assisted by thermal imagery and spatial statistics

USDA-ARS?s Scientific Manuscript database

Thermal imaging has the potential to assist with many aspects of irrigation management including scheduling water application, detecting leaky irrigation canals, and gauging the overall effectiveness of water distribution networks used in furrow irrigation. Many challenges exist for the use of therm...

Using ESAP Software for Predicting the Spatial Distributions of NDVI and Transpiration of Cotton

USDA-ARS?s Scientific Manuscript database

The normalized difference vegetation index (NDVI) has many applications in agricultural management, including monitoring real-time crop coefficients for estimating crop evapotranspiration (ET). However, frequent monitoring of NDVI as needed in such applications is generally not feasible from aerial ...

Predicted altitudinal shifts and reduced spatial distribution of Leishmania infantum vector species under climate change scenarios in Colombia.

PubMed

González, Camila; Paz, Andrea; Ferro, Cristina

2014-01-01

Visceral leishmaniasis (VL) is caused by the trypanosomatid parasite Leishmania infantum (=Leishmania chagasi), and is epidemiologically relevant due to its wide geographic distribution, the number of annual cases reported and the increase in its co-infection with HIV. Two vector species have been incriminated in the Americas: Lutzomyia longipalpis and Lutzomyia evansi. In Colombia, L. longipalpis is distributed along the Magdalena River Valley while L. evansi is only found in the northern part of the Country. Regarding the epidemiology of the disease, in Colombia the incidence of VL has decreased over the last few years without any intervention being implemented. Additionally, changes in transmission cycles have been reported with urban transmission occurring in the Caribbean Coast. In Europe and North America climate change seems to be driving a latitudinal shift of leishmaniasis transmission. Here, we explored the spatial distribution of the two known vector species of L. infantum in Colombia and projected its future distribution into climate change scenarios to establish the expansion potential of the disease. An updated database including L. longipalpis and L. evansi collection records from Colombia was compiled. Ecological niche models were performed for each species using the Maxent software and 13 Worldclim bioclimatic coverages. Projections were made for the pessimistic CSIRO A2 scenario, which predicts the higher increase in temperature due to non-emission reduction, and the optimistic Hadley B2 Scenario predicting the minimum increase in temperature. The database contained 23 records for L. evansi and 39 records for L. longipalpis, distributed along the Magdalena River Valley and the Caribbean Coast, where the potential distribution areas of both species were also predicted by Maxent. Climate change projections showed a general overall reduction in the spatial distribution of the two vector species, promoting a shift in altitudinal distribution for L. longipalpis and confining L. evansi to certain regions in the Caribbean Coast. Altitudinal shifts have been reported for cutaneous leishmaniasis vectors in Colombia and Peru. Here, we predict the same outcome for VL vectors in Colombia. Changes in spatial distribution patterns could be affecting local abundances due to climatic pressures on vector populations thus reducing the incidence of human cases. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Separating the effects of environment and space on tree species distribution: from population to community.

PubMed

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.

Self-consistent Langmuir waves in resonantly driven thermal plasmas

NASA Astrophysics Data System (ADS)

Lindberg, R. R.; Charman, A. E.; Wurtele, J. S.

2007-12-01

The longitudinal dynamics of a resonantly driven Langmuir wave are analyzed in the limit that the growth of the electrostatic wave is slow compared to the bounce frequency. Using simple physical arguments, the nonlinear distribution function is shown to be nearly invariant in the canonical particle action, provided both a spatially uniform term and higher-order spatial harmonics are included along with the fundamental in the longitudinal electric field. Requirements of self-consistency with the electrostatic potential yield the basic properties of the nonlinear distribution function, including a frequency shift that agrees closely with driven, electrostatic particle simulations over a range of temperatures. This extends earlier work on nonlinear Langmuir waves by Morales and O'Neil [G. J. Morales and T. M. O'Neil, Phys. Rev. Lett. 28, 417 (1972)] and Dewar [R. L. Dewar, Phys. Plasmas 15, 712 (1972)], and could form the basis of a reduced kinetic treatment of plasma dynamics for accelerator applications or Raman backscatter.

Measuring spatially varying, multispectral, ultraviolet bidirectional reflectance distribution function with an imaging spectrometer

NASA Astrophysics Data System (ADS)

Li, Hongsong; Lyu, Hang; Liao, Ningfang; Wu, Wenmin

2016-12-01

The bidirectional reflectance distribution function (BRDF) data in the ultraviolet (UV) band are valuable for many applications including cultural heritage, material analysis, surface characterization, and trace detection. We present a BRDF measurement instrument working in the near- and middle-UV spectral range. The instrument includes a collimated UV light source, a rotation stage, a UV imaging spectrometer, and a control computer. The data captured by the proposed instrument describe spatial, spectral, and angular variations of the light scattering from a sample surface. Such a multidimensional dataset of an example sample is captured by the proposed instrument and analyzed by a k-mean clustering algorithm to separate surface regions with same material but different surface roughnesses. The clustering results show that the angular dimension of the dataset can be exploited for surface roughness characterization. The two clustered BRDFs are fitted to a theoretical BRDF model. The fitting results show good agreement between the measurement data and the theoretical model.

Spatial distribution of dust in galaxies from the Integral field unit data

NASA Astrophysics Data System (ADS)

Zafar, Tayyaba; Sophie Dubber, Andrew Hopkins

2018-01-01

An important characteristic of the dust is it can be used as a tracer of stars (and gas) and tell us about the composition of galaxies. Sub-mm and infrared studies can accurately determine the total dust mass and its spatial distribution in massive, bright galaxies. However, faint and distant galaxies are hampered by resolution to dust spatial dust distribution. In the era of integral-field spectrographs (IFS), Balmer decrement is a useful quantity to infer the spatial extent of the dust in distant and low-mass galaxies. We conducted a study to estimate the spatial distribution of dust using the Sydney-Australian Astronomical Observatory (AAO) Multi-object Integral field spectrograph (SAMI) galaxies. Our methodology is unique to exploit the potential of IFS and using the spatial and spectral information together to study dust in galaxies of various morphological types. The spatial extent and content of dust are compared with the star-formation rate, reddening, and inclination of galaxies. We find a right correlation of dust spatial extent with the star-formation rate. The results also indicate a decrease in dust extent radius from Late Spirals to Early Spirals.

Extracting information on the spatial variability in erosion rate stored in detrital cooling age distributions in river sands

NASA Astrophysics Data System (ADS)

Braun, Jean; Gemignani, Lorenzo; van der Beek, Peter

2018-03-01

One of the main purposes of detrital thermochronology is to provide constraints on the regional-scale exhumation rate and its spatial variability in actively eroding mountain ranges. Procedures that use cooling age distributions coupled with hypsometry and thermal models have been developed in order to extract quantitative estimates of erosion rate and its spatial distribution, assuming steady state between tectonic uplift and erosion. This hypothesis precludes the use of these procedures to assess the likely transient response of mountain belts to changes in tectonic or climatic forcing. Other methods are based on an a priori knowledge of the in situ distribution of ages to interpret the detrital age distributions. In this paper, we describe a simple method that, using the observed detrital mineral age distributions collected along a river, allows us to extract information about the relative distribution of erosion rates in an eroding catchment without relying on a steady-state assumption, the value of thermal parameters or an a priori knowledge of in situ age distributions. The model is based on a relatively low number of parameters describing lithological variability among the various sub-catchments and their sizes and only uses the raw ages. The method we propose is tested against synthetic age distributions to demonstrate its accuracy and the optimum conditions for it use. In order to illustrate the method, we invert age distributions collected along the main trunk of the Tsangpo-Siang-Brahmaputra river system in the eastern Himalaya. From the inversion of the cooling age distributions we predict present-day erosion rates of the catchments along the Tsangpo-Siang-Brahmaputra river system, as well as some of its tributaries. We show that detrital age distributions contain dual information about present-day erosion rate, i.e., from the predicted distribution of surface ages within each catchment and from the relative contribution of any given catchment to the river distribution. The method additionally allows comparing modern erosion rates to long-term exhumation rates. We provide a simple implementation of the method in Python code within a Jupyter Notebook that includes the data used in this paper for illustration purposes.

Leads Detection Using Mixture Statistical Distribution Based CRF Algorithm from Sentinel-1 Dual Polarization SAR Imagery

NASA Astrophysics Data System (ADS)

Zhang, Yu; Li, Fei; Zhang, Shengkai; Zhu, Tingting

2017-04-01

Synthetic Aperture Radar (SAR) is significantly important for polar remote sensing since it can provide continuous observations in all days and all weather. SAR can be used for extracting the surface roughness information characterized by the variance of dielectric properties and different polarization channels, which make it possible to observe different ice types and surface structure for deformation analysis. In November, 2016, Chinese National Antarctic Research Expedition (CHINARE) 33rd cruise has set sails in sea ice zone in Antarctic. Accurate leads spatial distribution in sea ice zone for routine planning of ship navigation is essential. In this study, the semantic relationship between leads and sea ice categories has been described by the Conditional Random Fields (CRF) model, and leads characteristics have been modeled by statistical distributions in SAR imagery. In the proposed algorithm, a mixture statistical distribution based CRF is developed by considering the contexture information and the statistical characteristics of sea ice for improving leads detection in Sentinel-1A dual polarization SAR imagery. The unary potential and pairwise potential in CRF model is constructed by integrating the posteriori probability estimated from statistical distributions. For mixture statistical distribution parameter estimation, Method of Logarithmic Cumulants (MoLC) is exploited for single statistical distribution parameters estimation. The iteration based Expectation Maximal (EM) algorithm is investigated to calculate the parameters in mixture statistical distribution based CRF model. In the posteriori probability inference, graph-cut energy minimization method is adopted in the initial leads detection. The post-processing procedures including aspect ratio constrain and spatial smoothing approaches are utilized to improve the visual result. The proposed method is validated on Sentinel-1A SAR C-band Extra Wide Swath (EW) Ground Range Detected (GRD) imagery with a pixel spacing of 40 meters near Prydz Bay area, East Antarctica. Main work is listed as follows: 1) A mixture statistical distribution based CRF algorithm has been developed for leads detection from Sentinel-1A dual polarization images. 2) The assessment of the proposed mixture statistical distribution based CRF method and single distribution based CRF algorithm has been presented. 3) The preferable parameters sets including statistical distributions, the aspect ratio threshold and spatial smoothing window size have been provided. In the future, the proposed algorithm will be developed for the operational Sentinel series data sets processing due to its less time consuming cost and high accuracy in leads detection.

Changes in the Spatial Distribution of Elementary Schools and Their Impact on Rural Communities in Czechia in the Second Half of the 20th Century

ERIC Educational Resources Information Center

Kucerova, Silvie; Kucera, Zdenek

2012-01-01

This article addresses the changes in the spatial distribution of elementary schools in Czechia in the second half of the 20th century and the consequences of these changes on the functioning of rural communities. The spatial distribution of elementary schools, the shape of their catchment areas, and the regional and local communities connected…

Projecting changes in the distribution and productivity of living marine resources: A critical review of the suite of modelling approaches used in the large European project VECTORS

NASA Astrophysics Data System (ADS)

Peck, Myron A.; Arvanitidis, Christos; Butenschön, Momme; Canu, Donata Melaku; Chatzinikolaou, Eva; Cucco, Andrea; Domenici, Paolo; Fernandes, Jose A.; Gasche, Loic; Huebert, Klaus B.; Hufnagl, Marc; Jones, Miranda C.; Kempf, Alexander; Keyl, Friedemann; Maar, Marie; Mahévas, Stéphanie; Marchal, Paul; Nicolas, Delphine; Pinnegar, John K.; Rivot, Etienne; Rochette, Sébastien; Sell, Anne F.; Sinerchia, Matteo; Solidoro, Cosimo; Somerfield, Paul J.; Teal, Lorna R.; Travers-Trolet, Morgan; van de Wolfshaar, Karen E.

2018-02-01

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

Population trends and distribution of Common Murre Uria aalge colonies in Washington, 1996-2015

USGS Publications Warehouse

Thomas, Susan M; Lyons, James E.

2017-01-01

Periodic assessments of population trends and changes in spatial distribution are valuable for managing marine birds and their breeding habitats, particularly when evaluating long-term response to threats such as oil spills, predation pressure, and changing ocean conditions. We evaluated recent trends in abundance and distribution of the Common Murre Uria aalge within Copalis, Quillayute Needles, and Flattery Rocks National Wildlife Refuges, which include all murre colonies in Washington except one, off-refuge, on Tatoosh Island. In 1996-2001 and 2010-2015, aerial photographic surveys were conducted during the incubation phase (mid-June through mid-July) each year. Using images from film (1996-2001) and digital (2010-2015) cameras that included all parts of each colony, we manually counted murres. We estimated population trend as annual percent change in whole-colony counts using an overdispersed Poisson regression model. Overall, numbers of murres counted at breeding colonies in Washington increased by 8.8% per year (95% CI 3.0%-14.9%) during 1996–2015. The overall statewide increase was driven by an increase at colonies in northern Washington of approximately 11% per year (95% CI 4.5%-17.8%). Despite an increasing trend, abundance remains lower than levels in the late 1970s, and the spatial distribution has changed. Colonies in southern Washington - where murres were historically the most abundant - are no longer active, or only minimally so, whereas colonies in the north - which were rarely active in the early 1970s - are now the largest. There was high variability in spatial distribution among years, a pattern that indicates a need for coordinated monitoring and movement studies throughout the California Current System to understand dispersal and colonization. Our results indicate that future management of refuge islands could protect both current and historic colony locations, given the patterns of colony dynamics and the uncertainty about long-term effects of a changing ocean ecosystem and predation pressure on the status of murres.

Analysis of shifts in the spatial distribution of vegetation due to climate change

NASA Astrophysics Data System (ADS)

del Jesus, Manuel; Díez-Sierra, Javier; Rinaldo, Andrea; Rodríguez-Iturbe, Ignacio

2017-04-01

Climate change will modify the statistical regime of most climatological variables, inducing changes on average values and in the natural variability of environmental variables. These environmental variables may be used to explain the spatial distribution of functional types of vegetation in arid and semiarid watersheds through the use of plant optimization theories. Therefore, plant optimization theories may be used to approximate the response of the spatial distribution of vegetation to a changing climate. Predicting changes in these spatial distributions is important to understand how climate change may affect vegetated ecosystems, but it is also important for hydrological engineering applications where climate change effects on water availability are assessed. In this work, Maximum Entropy Production (MEP) is used as the plant optimization theory that describes the spatial distribution of functional types of vegetation. Current climatological conditions are obtained from direct observations from meteorological stations. Climate change effects are evaluated for different temporal horizons and different climate change scenarios using numerical model outputs from the CMIP5. Rainfall estimates are downscaled by means of a stochastic point process used to model rainfall. The study is carried out for the Rio Salado watershed, located within the Sevilleta LTER site, in New Mexico (USA). Results show the expected changes in the spatial distribution of vegetation and allow to evaluate the expected variability of the changes. The updated spatial distributions allow to evaluate the vegetated ecosystem health and its updated resilience. These results can then be used to inform the hydrological modeling part of climate change assessments analyzing water availability in arid and semiarid watersheds.

The spatial distribution of umbral dots and granules

NASA Astrophysics Data System (ADS)

Lawrence, J. K.

1983-08-01

It is pointed out that the study of point patterns in two dimensions is of extremely broad interest in both the natural and social sciences. The subjects to which this study has been applied include tree distributions in forests, bird nesting patterns, the growth of towns, crystal formation in rocks, and the distribution of galaxies on the sky. The present investigation is concerned with the particular example of the distribution of umbral dots and their similarity, or dissimilarity, to photospheric granules. Attention is given to a collection of N points in an area A, statistical comparisons of distributions, and studies conducted by Bumba and Suda (1980) and Adjabshirzadeh and Koutchmy (1980, 1982).

Bayesian spatial transformation models with applications in neuroimaging data

PubMed Central

Miranda, Michelle F.; Zhu, Hongtu; Ibrahim, Joseph G.

2013-01-01

Summary The aim of this paper is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. Our STMs include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov Random Field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. PMID:24128143

Web-based GIS for collaborative planning and public participation: an application to the strategic planning of wind farm sites.

PubMed

Simão, Ana; Densham, Paul J; Haklay, Mordechai Muki

2009-05-01

Spatial planning typically involves multiple stakeholders. To any specific planning problem, stakeholders often bring different levels of knowledge about the components of the problem and make assumptions, reflecting their individual experiences, that yield conflicting views about desirable planning outcomes. Consequently, stakeholders need to learn about the likely outcomes that result from their stated preferences; this learning can be supported through enhanced access to information, increased public participation in spatial decision-making and support for distributed collaboration amongst planners, stakeholders and the public. This paper presents a conceptual system framework for web-based GIS that supports public participation in collaborative planning. The framework combines an information area, a Multi-Criteria Spatial Decision Support System (MC-SDSS) and an argumentation map to support distributed and asynchronous collaboration in spatial planning. After analysing the novel aspects of this framework, the paper describes its implementation, as a proof of concept, in a system for Web-based Participatory Wind Energy Planning (WePWEP). Details are provided on the specific implementation of each of WePWEP's four tiers, including technical and structural aspects. Throughout the paper, particular emphasis is placed on the need to support user learning throughout the planning process.

Complementary aspects of spatial resolution and signal-to-noise ratio in computational imaging

NASA Astrophysics Data System (ADS)

Gureyev, T. E.; Paganin, D. M.; Kozlov, A.; Nesterets, Ya. I.; Quiney, H. M.

2018-05-01

A generic computational imaging setup is considered which assumes sequential illumination of a semitransparent object by an arbitrary set of structured coherent illumination patterns. For each incident illumination pattern, all transmitted light is collected by a photon-counting bucket (single-pixel) detector. The transmission coefficients measured in this way are then used to reconstruct the spatial distribution of the object's projected transmission. It is demonstrated that the square of the spatial resolution of such a setup is usually equal to the ratio of the image area to the number of linearly independent illumination patterns. If the noise in the measured transmission coefficients is dominated by photon shot noise, then the ratio of the square of the mean signal to the noise variance is proportional to the ratio of the mean number of registered photons to the number of illumination patterns. The signal-to-noise ratio in a reconstructed transmission distribution is always lower if the illumination patterns are nonorthogonal, because of spatial correlations in the measured data. Examples of imaging methods relevant to the presented analysis include conventional imaging with a pixelated detector, computational ghost imaging, compressive sensing, super-resolution imaging, and computed tomography.

Bacteria and game theory: the rise and fall of cooperation in spatially heterogeneous environments.

PubMed

Lambert, Guillaume; Vyawahare, Saurabh; Austin, Robert H

2014-08-06

One of the predictions of game theory is that cooperative behaviours are vulnerable to exploitation by selfish individuals, but this result seemingly contradicts the survival of cooperation observed in nature. In this review, we will introduce game theoretical concepts that lead to this conclusion and show how the spatial competition dynamics between microorganisms can be used to model the survival and maintenance of cooperation. In particular, we focus on how Escherichia coli bacteria with a growth advantage in stationary phase (GASP) phenotype maintain a proliferative phenotype when faced with overcrowding to gain a fitness advantage over wild-type populations. We review recent experimental approaches studying the growth dynamics of competing GASP and wild-type strains of E. coli inside interconnected microfabricated habitats and use a game theoretical approach to analyse the observed inter-species interactions. We describe how the use of evolutionary game theory and the ideal free distribution accurately models the spatial distribution of cooperative and selfish individuals in spatially heterogeneous environments. Using bacteria as a model system of cooperative and selfish behaviours may lead to a better understanding of the competition dynamics of other organisms-including tumour-host interactions during cancer development and metastasis.

Modelling of Space-Time Soil Moisture in Savannas and its Relation to Vegetation Patterns

NASA Astrophysics Data System (ADS)

Rodriguez-Iturbe, I.; Mohanty, B.; Chen, Z.

2017-12-01

A physically derived space-time representation of the soil moisture field is presented. It includes the incorporation of a "jitter" process acting over the space-time soil moisture field and accounting for the short distance heterogeneities in topography, soil, and vegetation characteristics. The modelling scheme allows for the representation of spatial random fluctuations of soil moisture at small spatial scales and reproduces quite well the space-time correlation structure of soil moisture from a field study in Oklahoma. It is shown that the islands of soil moisture above different thresholds have sizes which follow power distributions over an extended range of scales. A discussion is provided about the possible links of this feature with the observed power law distributions of the clusters of trees in savannas.

Radiofrequency field inhomogeneity compensation in high spatial resolution magnetic resonance spectroscopic imaging

NASA Astrophysics Data System (ADS)

Passeri, Alessandro; Mazzuca, Stefano; Del Bene, Veronica

2014-06-01

Clinical magnetic resonance spectroscopy imaging (MRSI) is a non-invasive functional technique, whose mathematical framework falls into the category of linear inverse problems. However, its use in medical diagnostics is hampered by two main problems, both linked to the Fourier-based technique usually implemented for spectra reconstruction: poor spatial resolution and severe blurring in the spatial localization of the reconstructed spectra. Moreover, the intrinsic ill-posedness of the MRSI problem might be worsened by (i) spatially dependent distortions of the static magnetic field (B0) distribution, as well as by (ii) inhomogeneity in the power deposition distribution of the radiofrequency magnetic field (B1). Among several alternative methods, slim (Spectral Localization by IMaging) and bslim (B0 compensated slim) are reconstruction algorithms in which a priori information concerning the spectroscopic target is introduced into the reconstruction kernel. Nonetheless, the influence of the B1 field, particularly when its operating wavelength is close to the size of the human organs being studied, continues to be disregarded. starslim (STAtic and Radiofrequency-compensated slim), an evolution of the slim and bslim methods, is therefore proposed, in which the transformation kernel also includes the B1 field inhomogeneity map, thus allowing almost complete 3D modelling of the MRSI problem. Moreover, an original method for the experimental determination of the B1 field inhomogeneity map specific to the target under evaluation is also included. The compensation capabilities of the proposed method have been tested and illustrated using synthetic raw data reproducing the human brain.

Spatial and temporal relationships between the invasive snail Bithynia tentaculata and submersed aquatic vegetation in Pool 8 of the Upper Mississippi River

USGS Publications Warehouse

Weeks, Alicia M.; DeJager, Nathan R.; Haro, Roger J.; Sandland, Greg J.

2017-01-01

Bithynia tentaculata is an invasive snail that was first reported in Lake Michigan in 1871 and has since spread throughout a number of freshwater systems of the USA. This invasion has been extremely problematic in the Upper Mississippi River as the snails serve as intermediate hosts for several trematode parasites that have been associated with waterfowl mortality in the region. This study was designed to assess the abundance and distribution of B. tentaculata relative to submersed aquatic vegetation as macrophytes provide important nesting and food resources for migrating waterfowl. Temporal changes in both vegetation and snail densities were compared between 2007 and 2015. Between these years, B. tentaculata densities have nearly quadrupled despite minor changes in vegetation abundance, distribution and composition. Understanding the spatial distribution of B. tentaculata in relation to other habitat features, including submersed vegetation, and quantifying any further changes in the abundance and distribution of B. tentaculata over time will be important for better identifying areas of risk for disease transmission to waterfowl.

Quantitative imaging of single-shot liquid distributions in sprays using broadband flash x-ray radiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halls, B. R.; Roy, S.; Gord, J. R.

Flash x-ray radiography is used to capture quantitative, two-dimensional line-of-sight averaged, single-shot liquid distribution measurements in impinging jet sprays. The accuracy of utilizing broadband x-ray radiation from compact flash tube sources is investigated for a range of conditions by comparing the data with radiographic high-speed measurements from a narrowband, high-intensity synchrotron x-ray facility at the Advanced Photon Source (APS) of Argonne National Laboratory. The path length of the liquid jets is varied to evaluate the effects of energy dependent x-ray attenuation, also known as spectral beam hardening. The spatial liquid distributions from flash x-ray and synchrotron-based radiography are compared, alongmore » with spectral characteristics using Taylor’s hypothesis. The results indicate that quantitative, single-shot imaging of liquid distributions can be achieved using broadband x-ray sources with nanosecond temporal resolution. Practical considerations for optimizing the imaging system performance are discussed, including the coupled effects of x-ray bandwidth, contrast, sensitivity, spatial resolution, temporal resolution, and spectral beam hardening.« less

Evidence of remediation-induced alteration of subsurface poly- and perfluoroalkyl substance distribution at a former firefighter training area.

PubMed

McGuire, Meghan E; Schaefer, Charles; Richards, Trenton; Backe, Will J; Field, Jennifer A; Houtz, Erika; Sedlak, David L; Guelfo, Jennifer L; Wunsch, Assaf; Higgins, Christopher P

2014-06-17

Poly- and perfluoroalkyl substances (PFASs) are a class of fluorinated chemicals that are utilized in firefighting and have been reported in groundwater and soil at several firefighter training areas. In this study, soil and groundwater samples were collected from across a former firefighter training area to examine the extent to which remedial activities have altered the composition and spatial distribution of PFASs in the subsurface. Log Koc values for perfluoroalkyl acids (PFAAs), estimated from analysis of paired samples of groundwater and aquifer solids, indicated that solid/water partitioning was not entirely consistent with predictions based on laboratory studies. Differential PFAA transport was not strongly evident in the subsurface, likely due to remediation-induced conditions. When compared to the surface soil spatial distributions, the relative concentrations of perfluorooctanesulfonate (PFOS) and PFAA precursors in groundwater strongly suggest that remedial activities altered the subsurface PFAS distribution, presumably through significant pumping of groundwater and transformation of precursors to PFAAs. Additional evidence for transformation of PFAA precursors during remediation included elevated ratios of perfluorohexanesulfonate (PFHxS) to PFOS in groundwater near oxygen sparging wells.

Applications of synergistic combination of remote sensing and in-situ measurements on urban monitoring of air quality

NASA Astrophysics Data System (ADS)

Diaz, Adrian; Dominguez, Victor; Campmier, Mark; Wu, Yonghua; Arend, Mark; Vladutescu, Daniela Viviana; Gross, Barry; Moshary, Fred

2017-08-01

In this study, multiple remote sensing and in-situ measurements are combined in order to obtain a comprehensive understanding of the aerosol distribution in New York City. Measurement of the horizontal distribution of aerosols is performed using a scanning eye-safe elastic-backscatter micro-pulse lidar. Vertical distribution of aerosols is measured with a co-located ceilometer. Furthermore, our analysis also includes in-situ measurements of particulate matter and wind speed and direction. These observations combined show boundary layer dynamics as well as transport and inhomogeneous spatial distribution of aerosols, which are of importance for air quality monitoring.

Information hidden in the velocity distribution of ions and the exact kinetic Bohm criterion

NASA Astrophysics Data System (ADS)

Tsankov, Tsanko V.; Czarnetzki, Uwe

2017-05-01

Non-equilibrium distribution functions of electrons and ions play an important role in plasma physics. A prominent example is the kinetic Bohm criterion. Since its first introduction it has been controversial for theoretical reasons and due to the lack of experimental data, in particular on the ion distribution function. Here we resolve the theoretical as well as the experimental difficulties by an exact solution of the kinetic Boltzmann equation including charge exchange collisions and ionization. This also allows for the first time non-invasive measurement of spatially resolved ion velocity distributions, absolute values of the ion and electron densities, temperatures, and mean energies as well as the electric field and the plasma potential in the entire plasma. The non-invasive access to the spatially resolved distribution functions of electrons and ions is applied to the problem of the kinetic Bohm criterion. Theoretically a so far missing term in the criterion is derived and shown to be of key importance. With the new term the validity of the kinetic criterion at high collisionality and its agreement with the fluid picture are restored. All findings are supported by experimental data, theory and a numerical model with excellent agreement throughout.

Fine-scale habitat modeling of a top marine predator: do prey data improve predictive capacity?

PubMed

Torres, Leigh G; Read, Andrew J; Halpin, Patrick

2008-10-01

Predators and prey assort themselves relative to each other, the availability of resources and refuges, and the temporal and spatial scale of their interaction. Predictive models of predator distributions often rely on these relationships by incorporating data on environmental variability and prey availability to determine predator habitat selection patterns. This approach to predictive modeling holds true in marine systems where observations of predators are logistically difficult, emphasizing the need for accurate models. In this paper, we ask whether including prey distribution data in fine-scale predictive models of bottlenose dolphin (Tursiops truncatus) habitat selection in Florida Bay, Florida, U.S.A., improves predictive capacity. Environmental characteristics are often used as predictor variables in habitat models of top marine predators with the assumption that they act as proxies of prey distribution. We examine the validity of this assumption by comparing the response of dolphin distribution and fish catch rates to the same environmental variables. Next, the predictive capacities of four models, with and without prey distribution data, are tested to determine whether dolphin habitat selection can be predicted without recourse to describing the distribution of their prey. The final analysis determines the accuracy of predictive maps of dolphin distribution produced by modeling areas of high fish catch based on significant environmental characteristics. We use spatial analysis and independent data sets to train and test the models. Our results indicate that, due to high habitat heterogeneity and the spatial variability of prey patches, fine-scale models of dolphin habitat selection in coastal habitats will be more successful if environmental variables are used as predictor variables of predator distributions rather than relying on prey data as explanatory variables. However, predictive modeling of prey distribution as the response variable based on environmental variability did produce high predictive performance of dolphin habitat selection, particularly foraging habitat.

Mapping spatial patterns of denitrifiers at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Data center thermal management

DOEpatents

Hamann, Hendrik F.; Li, Hongfei

2016-02-09

Historical high-spatial-resolution temperature data and dynamic temperature sensor measurement data may be used to predict temperature. A first formulation may be derived based on the historical high-spatial-resolution temperature data for determining a temperature at any point in 3-dimensional space. The dynamic temperature sensor measurement data may be calibrated based on the historical high-spatial-resolution temperature data at a corresponding historical time. Sensor temperature data at a plurality of sensor locations may be predicted for a future time based on the calibrated dynamic temperature sensor measurement data. A three-dimensional temperature spatial distribution associated with the future time may be generated based on the forecasted sensor temperature data and the first formulation. The three-dimensional temperature spatial distribution associated with the future time may be projected to a two-dimensional temperature distribution, and temperature in the future time for a selected space location may be forecasted dynamically based on said two-dimensional temperature distribution.

Spatially Distributed Assimilation of Remotely Sensed Leaf Area Index and Potential Evapotranspiration for Hydrologic Modeling in Wetland Landscapes

EPA Science Inventory

Evapotranspiration (ET), a highly dynamic flux in wetland landscapes, regulates the accuracy of surface/sub-surface runoff simulation in a hydrologic model. However, considerable uncertainty in simulating ET-related processes remains, including our limited ability to incorporate ...

SPATIAL DISTRIBUTIONS OF ARSENIC EXPOSURE AND MINING COMMUNITIES FROM NHEXAS ARIZONA

EPA Science Inventory

Within the context of the National Human Exposure Assessment Survey (NHEXAS), metals were evaluated in the air, soil, dust, water, food, beverages, and urine of a single respondent. Potential doses were calculated for five metals including arsenic. In this paper, we seek to val...

Comparison of the common spatial interpolation methods used to analyze potentially toxic elements surrounding mining regions.

PubMed

Ding, Qian; Wang, Yong; Zhuang, Dafang

2018-04-15

The appropriate spatial interpolation methods must be selected to analyze the spatial distributions of Potentially Toxic Elements (PTEs), which is a precondition for evaluating PTE pollution. The accuracy and effect of different spatial interpolation methods, which include inverse distance weighting interpolation (IDW) (power = 1, 2, 3), radial basis function interpolation (RBF) (basis function: thin-plate spline (TPS), spline with tension (ST), completely regularized spline (CRS), multiquadric (MQ) and inverse multiquadric (IMQ)) and ordinary kriging interpolation (OK) (semivariogram model: spherical, exponential, gaussian and linear), were compared using 166 unevenly distributed soil PTE samples (As, Pb, Cu and Zn) in the Suxian District, Chenzhou City, Hunan Province as the study subject. The reasons for the accuracy differences of the interpolation methods and the uncertainties of the interpolation results are discussed, then several suggestions for improving the interpolation accuracy are proposed, and the direction of pollution control is determined. The results of this study are as follows: (i) RBF-ST and OK (exponential) are the optimal interpolation methods for As and Cu, and the optimal interpolation method for Pb and Zn is RBF-IMQ. (ii) The interpolation uncertainty is positively correlated with the PTE concentration, and higher uncertainties are primarily distributed around mines, which is related to the strong spatial variability of PTE concentrations caused by human interference. (iii) The interpolation accuracy can be improved by increasing the sample size around the mines, introducing auxiliary variables in the case of incomplete sampling and adopting the partition prediction method. (iv) It is necessary to strengthen the prevention and control of As and Pb pollution, particularly in the central and northern areas. The results of this study can provide an effective reference for the optimization of interpolation methods and parameters for unevenly distributed soil PTE data in mining areas. Copyright © 2018 Elsevier Ltd. All rights reserved.

Differential adult survival at close seabird colonies: The importance of spatial foraging segregation and bycatch risk during the breeding season.

PubMed

Genovart, Meritxell; Bécares, Juan; Igual, José-Manuel; Martínez-Abraín, Alejandro; Escandell, Raul; Sánchez, Antonio; Rodríguez, Beneharo; Arcos, José M; Oro, Daniel

2018-03-01

Marine megafauna, including seabirds, are critically affected by fisheries bycatch. However, bycatch risk may differ on temporal and spatial scales due to the uneven distribution and effort of fleets operating different fishing gear, and to focal species distribution and foraging behavior. Scopoli's shearwater Calonectris diomedea is a long-lived seabird that experiences high bycatch rates in longline fisheries and strong population-level impacts due to this type of anthropogenic mortality. Analyzing a long-term dataset on individual monitoring, we compared adult survival (by means of multi-event capture-recapture models) among three close predator-free Mediterranean colonies of the species. Unexpectedly for a long-lived organism, adult survival varied among colonies. We explored potential causes of this differential survival by (1) measuring egg volume as a proxy of food availability and parental condition; (2) building a specific longline bycatch risk map for the species; and (3) assessing the distribution patterns of breeding birds from the three study colonies via GPS tracking. Egg volume was very similar between colonies over time, suggesting that environmental variability related to habitat foraging suitability was not the main cause of differential survival. On the other hand, differences in foraging movements among individuals from the three colonies expose them to differential mortality risk, which likely influenced the observed differences in adult survival. The overlap of information obtained by the generation of specific bycatch risk maps, the quantification of population demographic parameters, and the foraging spatial analysis should inform managers about differential sensitivity to the anthropogenic impact at mesoscale level and guide decisions depending on the spatial configuration of local populations. The approach would apply and should be considered in any species where foraging distribution is colony-specific and mortality risk varies spatially. © 2017 John Wiley & Sons Ltd.

Temporal and spatial distribution characteristics in the natural plague foci of Chinese Mongolian gerbils based on spatial autocorrelation.

PubMed

Du, Hai-Wen; Wang, Yong; Zhuang, Da-Fang; Jiang, Xiao-San

2017-08-07

The nest flea index of Meriones unguiculatus is a critical indicator for the prevention and control of plague, which can be used not only to detect the spatial and temporal distributions of Meriones unguiculatus, but also to reveal its cluster rule. This research detected the temporal and spatial distribution characteristics of the plague natural foci of Mongolian gerbils by body flea index from 2005 to 2014, in order to predict plague outbreaks. Global spatial autocorrelation was used to describe the entire spatial distribution pattern of the body flea index in the natural plague foci of typical Chinese Mongolian gerbils. Cluster and outlier analysis and hot spot analysis were also used to detect the intensity of clusters based on geographic information system methods. The quantity of M. unguiculatus nest fleas in the sentinel surveillance sites from 2005 to 2014 and host density data of the study area from 2005 to 2010 used in this study were provided by Chinese Center for Disease Control and Prevention. The epidemic focus regions of the Mongolian gerbils remain the same as the hot spot regions relating to the body flea index. High clustering areas possess a similar pattern as the distribution pattern of the body flea index indicating that the transmission risk of plague is relatively high. In terms of time series, the area of the epidemic focus gradually increased from 2005 to 2007, declined rapidly in 2008 and 2009, and then decreased slowly and began trending towards stability from 2009 to 2014. For the spatial change, the epidemic focus regions began moving northward from the southwest epidemic focus of the Mongolian gerbils from 2005 to 2007, and then moved from north to south in 2007 and 2008. The body flea index of Chinese gerbil foci reveals significant spatial and temporal aggregation characteristics through the employing of spatial autocorrelation. The diversity of temporary and spatial distribution is mainly affected by seasonal variation, the human activity and natural factors.

Applications of Geomatics in Surface Mining

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Górniak-Zimroz, Justyna; Milczarek, Wojciech; Pactwa, Katarzyna

2017-12-01

In terms of method of extracting mineral from deposit, mining can be classified into: surface, underground, and borehole mining. Surface mining is a form of mining, in which the soil and the rock covering the mineral deposits are removed. Types of surface mining include mainly strip and open-cast methods, as well as quarrying. Tasks associated with surface mining of minerals include: resource estimation and deposit documentation, mine planning and deposit access, mine plant development, extraction of minerals from deposits, mineral and waste processing, reclamation and reclamation of former mining grounds. At each stage of mining, geodata describing changes occurring in space during the entire life cycle of surface mining project should be taken into consideration, i.e. collected, analysed, processed, examined, distributed. These data result from direct (e.g. geodetic) and indirect (i.e. remote or relative) measurements and observations including airborne and satellite methods, geotechnical, geological and hydrogeological data, and data from other types of sensors, e.g. located on mining equipment and infrastructure, mine plans and maps. Management of such vast sources and sets of geodata, as well as information resulting from processing, integrated analysis and examining such data can be facilitated with geomatic solutions. Geomatics is a discipline of gathering, processing, interpreting, storing and delivering spatially referenced information. Thus, geomatics integrates methods and technologies used for collecting, management, processing, visualizing and distributing spatial data. In other words, its meaning covers practically every method and tool from spatial data acquisition to distribution. In this work examples of application of geomatic solutions in surface mining on representative case studies in various stages of mine operation have been presented. These applications include: prospecting and documenting mineral deposits, assessment of land accessibility for a potential large-scale surface mining project, modelling mineral deposit (granite) management, concept of a system for management of conveyor belt network technical condition, project of a geoinformation system of former mining terrains and objects, and monitoring and control of impact of surface mining on mine surroundings with satellite radar interferometry.

A general modeling framework for describing spatially structured population dynamics

USGS Publications Warehouse

Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan

2017-01-01

Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles

Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska

NASA Astrophysics Data System (ADS)

Meade, N. G.; Hinzman, L. D.; Kane, D. L.

1999-01-01

A spatially distributed Model of Arctic Thermal and Hydrologic processes (MATH) has been developed. One of the attributes of this model is the spatial and temporal prediction of soil moisture in the active layer. The spatially distributed output from this model required verification data obtained through remote sensing to assess performance at the watershed scale independently. Therefore, a neural network was trained to predict soil moisture contents near the ground surface. The input to train the neural network is synthetic aperture radar (SAR) pixel value, and field measurements of soil moisture, and vegetation, which were used as a surrogate for surface roughness. Once the network was trained, soil moisture predictions were made based on SAR pixel value and vegetation. These results were then used for comparison with results from the hydrologic model. The quality of neural network input was less than anticipated. Our digital elevation model (DEM) was not of high enough resolution to allow exact co-registration with soil moisture measurements; therefore, the statistical correlations were not as good as hoped. However, the spatial pattern of the SAR derived soil moisture contents compares favorably with the hydrologic MATH model results. Primary surface parameters that effect SAR include topography, surface roughness, vegetation cover and soil texture. Single parameters that are considered to influence SAR include incident angle of the radar, polarization of the radiation, signal strength and returning signal integration, to name a few. These factors influence the reflectance, but if one adequately quantifies the influences of terrain and roughness, it is considered possible to extract information on soil moisture from SAR imagery analysis and in turn use SAR imagery to validate hydrologic models

Spatial Analysis of Hospital Incidence and in Hospital Mortality of Abdominal Aortic Aneurysms in Germany: Secondary Data Analysis of Nationwide Hospital Episode (DRG) Data.

PubMed

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.

Spatial patterns of schistosomiasis in Burkina Faso: relevance of human mobility and water resources development

NASA Astrophysics Data System (ADS)

Perez-Saez, Javier; Bertuzzo, Enrico; Frohelich, Jean-Marc; Mande, Theophile; Ceperley, Natalie; Sou, Mariam; Yacouba, Hamma; Maiga, Hamadou; Sokolow, Susanne; De Leo, Giulio; Casagrandi, Renato; Gatto, Marino; Mari, Lorenzo; Rinaldo, Andrea

2015-04-01

We study the spatial geography of schistosomiasis in the african context of Burkina Faso by means of a spatially explicit model of disease dynamics and spread. The relevance of our work lies in its ability to describe quantitatively a geographic stratification of the disease burden capable of reproducing important spatial differences, and drivers/controls of disease spread. Among the latters, we consider specifically the development and management of water resources which have been singled out empirically as an important risk factor for schistosomiasis. The model includes remotely acquired and objectively manipulated information on the distributions of population, infrastructure, elevation and climatic drivers. It also includes a general description of human mobility and addresses a first-order characterization of the ecology of the intermediate host of the parasite causing the disease based on maximum entropy learning of relevant environmenal covariates. Spatial patterns of the disease were analyzed about their disease-free equilibrium by proper extraction and mapping of suitable eigenvectors of the Jacobian matrix subsuming all stability properties of the system. Human mobility was found to be a primary control of both pathogen invasion success and of the overall distribution of disease burden. The effects of water resources development were studied by accounting for the (prior and posterior) average distances of human settlements from water bodies that may serve as suitable habitats to the intermediate host of the parasite. Water developments, in combination with human mobility, were quantitatively related to disease spread into regions previously nearly disease-free and to large-scale empirical incidence patterns. We concluded that while the model still needs refinements based on field and epidemiological evidence, the framework proposed provides a powerful tool for large-scale, long-term public health planning and management of schistosomiasis.

Spatial dynamics of warehousing and distribution in California : METRANS UTC draft 15-27.

DOT National Transportation Integrated Search

2017-01-01

The purpose of this research is to document and analyze the location patterns of warehousing and distribution activity in California. The growth of California's warehousing and distribution (W&D) activities and their spatial patterns is affected by s...

Scale Invariance in Lateral Head Scans During Spatial Exploration.

PubMed

Yadav, Chetan K; Doreswamy, Yoganarasimha

2017-04-14

Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.

Scale Invariance in Lateral Head Scans During Spatial Exploration

NASA Astrophysics Data System (ADS)

Yadav, Chetan K.; Doreswamy, Yoganarasimha

2017-04-01

Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.

Tree species exhibit complex patterns of distribution in bottomland hardwood forests

Treesearch

Luben D Dimov; Jim L Chambers; Brian R. Lockhart

2013-01-01

& Context Understanding tree interactions requires an insight into their spatial distribution. & Aims We looked for presence and extent of tree intraspecific spatial point pattern (random, aggregated, or overdispersed) and interspecific spatial point pattern (independent, aggregated, or segregated). & Methods We established twelve 0.64-ha plots in natural...

Spatial distribution and temporal trends of rainfall erosivity in mainland China for 1951-2010

Treesearch

Wei Qin; Qiankun Guo; Changqing Zuo; Zhijie Shan; Liang Ma; Ge Sun

2016-01-01

Rainfall erosivity is an important factor for estimating soil erosion rates. Understanding the spatial distributionand temporal trends of rainfall erosivity is especially critical for soil erosion risk assessment and soil conservationplanning in mainland China. However, reports on the spatial distribution and temporal trends of rainfall...

Seasonal change of topology and resilience of ecological networks in wetlandscapes

NASA Astrophysics Data System (ADS)

Bin, Kim; Park, Jeryang

2017-04-01

Wetlands distributed in a landscape provide various ecosystem services including habitat for flora and fauna, hydrologic controls, and biogeochemical processes. Hydrologic regime of each wetland at a given landscape varies by hydro-climatic and geological conditions as well as the bathymetry, forming a certain pattern in the wetland area distribution and spatial organization. However, its large-scale pattern also changes over time as this wetland complex is subject to stochastic hydro-climatic forcing in various temporal scales. Consequently, temporal variation in the spatial structure of wetlands inevitably affects the dispersal ability of species depending on those wetlands as habitat. Here, we numerically show (1) the spatiotemporal variation of wetlandscapes by forcing seasonally changing stochastic rainfall and (2) the corresponding ecological networks which either deterministically or stochastically forming the dispersal ranges. We selected four vernal pool regions with distinct climate conditions in California. The results indicate that the spatial structure of wetlands in a landscape by measuring the wetland area frequency distribution changes by seasonal hydro-climatic condition but eventually recovers to the initial state. However, the corresponding ecological networks, which the structure and function change by the change of distances between wetlands, and measured by degree distribution and network efficiency, may not recover to the initial state especially in the regions with high seasonal dryness index. Moreover, we observed that the changes in both the spatial structure of wetlands in a landscape and the corresponding ecological networks exhibit hysteresis over seasons. Our analysis indicates that the hydrologic and ecological resilience of a wetlandcape may be low in a dry region with seasonal hydro-climatic forcing. Implications of these results for modelling ecological networks depending on hydrologic systems especially for conservation purposes are discussed.

[Relationship between reference values of fibrinogen and geographical factors based on neural network analysis].

PubMed

Li, Meng-Jiao; Ge, Miao; Wang, Cong-Xia; Cen, Min-Yi; Jiang, Ji-Lin; He, Jin-Wei; Lin, Qian-Yi; Liu, Xin

2016-08-20

To analyze the relationship between the reference values of fibrinogen (FIB) in healthy Chinese adults and geographical factors to provide scientific evidences for establishing the uniform standard. The reference values of FIB of 10701 Chinese healthy adults from 103 cities were collected to investigate their relationship with 18 geographical factors including spatial index, terrain index, climate index, and soil index. Geographical factors that significantly correlated with the reference values were selected for constructing the BP neural network model. The spatial distribution map of the reference value of FIB of healthy Chinese adults was fitted by disjunctive kriging interpolation. We used the 5-layer neural network and selected 2000 times of training covering 11 hidden layers to build the simulation rule for simulating the relationship between FIB and geographical environmental factors using the MATLAB software. s The reference value of FIB in healthy Chinese adults was significantly correlated with the latitude, sunshine duration, annual average temperature, annual average relative humidity, annual precipitation, annual range of air temperature, average annual soil gravel content, and soil cation exchange capacity (silt). The artificial neural networks were created to analyze the simulation of the selected indicators of geographical factors. The spatial distribution map of the reference values of FIB in healthy Chinese adults showed a distribution pattern that FIB levels were higher in the South and lower in the North, and higher in the East and lower in the West. When the geographical factors of a certain area are known, the reference values of FIB in healthy Chinese adults can be obtained by establishing the neural network mode or plotting the spatial distribution map.

Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications

PubMed Central

Scarpino, Samuel V.; Jansen, Patrick A.; Garzon-Lopez, Carol X.; Winkelhagen, Annemarie J. S.; Bohlman, Stephanie A.; Walsh, Peter D.

2010-01-01

Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. PMID:21124927

Ultrasonic generator and detector using an optical mask having a grating for launching a plurality of spatially distributed, time varying strain pulses in a sample

DOEpatents

Maris, Humphrey J.

2003-01-01

A method and a system are disclosed for determining at least one characteristic of a sample that contains a substrate and at least one film disposed on or over a surface of the substrate. The method includes a first step of placing a mask over a free surface of the at least one film, where the mask has a top surface and a bottom surface that is placed adjacent to the free surface of the film. The bottom surface of the mask has formed therein or thereon a plurality of features for forming at least one grating. A next step directs optical pump pulses through the mask to the free surface of the film, where individual ones of the pump pulses are followed by at least one optical probe pulse. The pump pulses are spatially distributed by the grating for launching a plurality of spatially distributed, time varying strain pulses within the film, which cause a detectable change in optical constants of the film. A next step detects a reflected or a transmitted portion of the probe pulses, which are also spatially distributed by the grating. A next step measures a change in at least one characteristic of at least one of reflected or transmitted probe pulses due to the change in optical constants, and a further step determines the at least one characteristic of the sample from the measured change in the at least one characteristic of the probe pulses. An optical mask is also disclosed herein, and forms a part of these teachings.

Ultrasonic generator and detector using an optical mask having a grating for launching a plurality of spatially distributed, time varying strain pulses in a sample

DOEpatents

Maris, Humphrey J.

2002-01-01

A method and a system are disclosed for determining at least one characteristic of a sample that contains a substrate and at least one film disposed on or over a surface of the substrate. The method includes a first step of placing a mask over a free surface of the at least one film, where the mask has a top surface and a bottom surface that is placed adjacent to the free surface of the film. The bottom surface of the mask has formed therein or thereon a plurality of features for forming at least one grating. A next step directs optical pump pulses through the mask to the free surface of the film, where individual ones of the pump pulses are followed by at least one optical probe pulse. The pump pulses are spatially distributed by the grating for launching a plurality of spatially distributed, time varying strain pulses within the film, which cause a detectable change in optical constants of the film. A next step detects a reflected or a transmitted portion of the probe pulses, which are also spatially distributed by the grating. A next step measures a change in at least one characteristic of at least one of reflected or transmitted probe pulses due to the change in optical constants, and a further step determines the at least one characteristic of the sample from the measured change in the at least one characteristic of the probe pulses. An optical mask is also disclosed herein, and forms a part of these teachings.

Uncertainty quantification in flux balance analysis of spatially lumped and distributed models of neuron-astrocyte metabolism.

PubMed

Calvetti, Daniela; Cheng, Yougan; Somersalo, Erkki

2016-12-01

Identifying feasible steady state solutions of a brain energy metabolism model is an inverse problem that allows infinitely many solutions. The characterization of the non-uniqueness, or the uncertainty quantification of the flux balance analysis, is tantamount to identifying the degrees of freedom of the solution. The degrees of freedom of multi-compartment mathematical models for energy metabolism of a neuron-astrocyte complex may offer a key to understand the different ways in which the energetic needs of the brain are met. In this paper we study the uncertainty in the solution, using techniques of linear algebra to identify the degrees of freedom in a lumped model, and Markov chain Monte Carlo methods in its extension to a spatially distributed case. The interpretation of the degrees of freedom in metabolic terms, more specifically, glucose and oxygen partitioning, is then leveraged to derive constraints on the free parameters to guarantee that the model is energetically feasible. We demonstrate how the model can be used to estimate the stoichiometric energy needs of the cells as well as the household energy based on the measured oxidative cerebral metabolic rate of glucose and glutamate cycling. Moreover, our analysis shows that in the lumped model the net direction of lactate dehydrogenase (LDH) in the cells can be deduced from the glucose partitioning between the compartments. The extension of the lumped model to a spatially distributed multi-compartment setting that includes diffusion fluxes from capillary to tissue increases the number of degrees of freedom, requiring the use of statistical sampling techniques. The analysis of the distributed model reveals that some of the conclusions valid for the spatially lumped model, e.g., concerning the LDH activity and glucose partitioning, may no longer hold.

Relative importance of population size, fishing pressure and temperature on the spatial distribution of nine Northwest Atlantic groundfish stocks.

PubMed

Adams, Charles F; Alade, Larry A; Legault, Christopher M; O'Brien, Loretta; Palmer, Michael C; Sosebee, Katherine A; Traver, Michele L

2018-01-01

The spatial distribution of nine Northwest Atlantic groundfish stocks was documented using spatial indicators based on Northeast Fisheries Science Center spring and fall bottom trawl survey data, 1963-2016. We then evaluated the relative importance of population size, fishing pressure and bottom temperature on spatial distribution with an information theoretic approach. Northward movement in the spring was generally consistent with prior analyses, whereas changes in depth distribution and area occupancy were not. Only two stocks exhibited the same changes in spatiotemporal distribution in the fall as compared with the spring. Fishing pressure was the most important predictor of the center of gravity (i.e., bivariate mean location of the population) for the majority of stocks in the spring, whereas in the fall this was restricted to the east-west component. Fishing pressure was also the most important predictor of the dispersion around the center of gravity in both spring and fall. In contrast, biomass was the most important predictor of area occupancy for the majority of stocks in both seasons. The relative importance of bottom temperature was ranked highest in the fewest number of cases. This study shows that fishing pressure, in addition to the previously established role of climate, influences the spatial distribution of groundfish in the Northwest Atlantic. More broadly, this study is one of a small but growing body of literature to demonstrate that fishing pressure has an effect on the spatial distribution of marine resources. Future work must consider both fishing pressure and climate when examining mechanisms underlying fish distribution shifts.

Relative importance of population size, fishing pressure and temperature on the spatial distribution of nine Northwest Atlantic groundfish stocks

PubMed Central

Alade, Larry A.; Legault, Christopher M.; O’Brien, Loretta; Palmer, Michael C.; Sosebee, Katherine A.; Traver, Michele L.

2018-01-01

The spatial distribution of nine Northwest Atlantic groundfish stocks was documented using spatial indicators based on Northeast Fisheries Science Center spring and fall bottom trawl survey data, 1963–2016. We then evaluated the relative importance of population size, fishing pressure and bottom temperature on spatial distribution with an information theoretic approach. Northward movement in the spring was generally consistent with prior analyses, whereas changes in depth distribution and area occupancy were not. Only two stocks exhibited the same changes in spatiotemporal distribution in the fall as compared with the spring. Fishing pressure was the most important predictor of the center of gravity (i.e., bivariate mean location of the population) for the majority of stocks in the spring, whereas in the fall this was restricted to the east-west component. Fishing pressure was also the most important predictor of the dispersion around the center of gravity in both spring and fall. In contrast, biomass was the most important predictor of area occupancy for the majority of stocks in both seasons. The relative importance of bottom temperature was ranked highest in the fewest number of cases. This study shows that fishing pressure, in addition to the previously established role of climate, influences the spatial distribution of groundfish in the Northwest Atlantic. More broadly, this study is one of a small but growing body of literature to demonstrate that fishing pressure has an effect on the spatial distribution of marine resources. Future work must consider both fishing pressure and climate when examining mechanisms underlying fish distribution shifts. PMID:29698454

Towards Understanding the Timing and Frequency of Rain-on-Snow (ROS) Events in Alaska

NASA Astrophysics Data System (ADS)

Pan, C.; Kirchner, P. B.; Kimball, J. S.; Kim, Y.; Kamp, U.

2017-12-01

Rain-on-snow (ROS) events affect ecosystem processes at multiple spatial and temporal scales including hydrology, carbon cycling, wildlife movement and human transportation and result in marked changes to snowpack processes including enhanced snow melt, surface albedo and energy balance. Changes in the surface structure of the snowpack are visible through optical remote sensing and changes in the relative content and distribution of water, air and ice in the snowpack are detectable using passive microwave remote sensing. This project aims to develop ROS products to elucidate changes in frequency and distribution in ROS events using satellite data products derived from both optical and passive microwave satellite records. To detect ROS events, we use downscaled brightness temperature measurements derived from vertical and horizontal polarizations at 19 and 37 GHz from the Advanced Microwave Scanning Radiometer (AMSR-E/2) passive microwave satellites. Preliminary results indicate an overall classification accuracy of 77.6% relative to in situ weather observations including surface air temperature, precipitation, and snow depth. ROS events are spatially distributed largely to elevations below 500 m and occur most frequently on northern to western aspects in addition to southeastern. Regional ROS hot spots occur in southwest Alaska characterized by warmer climates and transient snowcover. The seasonal timing of ROS events indicates increasing frequency during the fall and spring months.

A new spatial snow distribution in hydrological models parameterized from observed spatial variability of precipitation.

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Weltzien, Ingunn

2016-04-01

The traditional catchment hydrological model with its many free calibration parameters is not a well suited tool for prediction under conditions for which is has not been calibrated. Important tasks for hydrological modelling such as prediction in ungauged basins and assessing hydrological effects of climate change are hence not solved satisfactory. In order to reduce the number of calibration parameters in hydrological models we have introduced a new model which uses a dynamic gamma distribution as the spatial frequency distribution of snow water equivalent (SWE). The parameters are estimated from observed spatial variability of precipitation and the magnitude of accumulation and melting events and are hence not subject to calibration. The relationship between spatial mean and variance of precipitation is found to follow a pattern where decreasing temporal correlation with increasing accumulation or duration of the event leads to a levelling off or even a decrease of the spatial variance. The new model for snow distribution is implemented in the, already parameter parsimonious, DDD (Distance Distribution Dynamics) hydrological model and was tested for 71 Norwegian catchments. We compared the new snow distribution model with the current operational snow distribution model where a fixed, calibrated coefficient of variation parameterizes a log-normal model for snow distribution. Results show that the precision of runoff simulations is equal, but that the new snow distribution model better simulates snow covered area (SCA) when compared with MODIS satellite derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" is prevented and hence spurious trends in SWE.

Alcohol outlets and clusters of violence

PubMed Central

2011-01-01

Background Alcohol related violence continues to be a major public health problem in the United States. In particular, there is substantial evidence of an association between alcohol outlets and assault. However, because the specific geographic relationships between alcohol outlets and the distribution of violence remains obscured, it is important to identify the spatial linkages that may exist, enhancing public health efforts to curb both violence and morbidity. Methods The present study utilizes police-recorded data on simple and aggravated assaults in Cincinnati, Ohio. Addresses of alcohol outlets for Cincinnati, including all bars, alcohol-serving restaurants, and off-premise liquor and convenience stores were obtained from the Ohio Division of Liquor Control and geocoded for analysis. A combination of proximity analysis, spatial cluster detection approaches and a geographic information system were used to identify clusters of alcohol outlets and the distribution of violence around them. Results A brief review of the empirical work relating to alcohol outlet density and violence is provided, noting that the majority of this literature is cross-sectional and ecological in nature, yielding a somewhat haphazard and aggregate view of how outlet type(s) and neighborhood characteristics like social organization and land use are related to assaultive violence. The results of the statistical analysis for Cincinnati suggest that while alcohol outlets are not problematic per se, assaultive violence has a propensity to cluster around agglomerations of alcohol outlets. This spatial relationship varies by distance and is also related to the characteristics of the alcohol outlet agglomeration. Specifically, spatially dense distributions of outlets appear to be more prone to clusters of assaultive violence when compared to agglomerations with a lower density of outlets. Conclusion With a more thorough understanding of the spatial relationships between alcohol outlets and the distribution of assaults, policymakers in urban areas can make more informed regulatory decisions regarding alcohol licenses. Further, this research suggests that public health officials and epidemiologists need to develop a better understanding of what actually occurs in and around alcohol outlets, determining what factors (whether outlet, neighborhood, or spatially related) help fuel their relationship with violence and other alcohol-related harm. PMID:21542932

Impacts of the spatial extent of pollen-climate calibration-set on the absolute values, range and trends of reconstructed Holocene precipitation

NASA Astrophysics Data System (ADS)

Cao, X.; Tian, F.; Telford, R.; Ni, J.; Xu, Q.; Chen, F.; Liu, X.; Stebich, M.; Zhao, Y.; Herzschuh, U.

2017-12-01

Pollen-based quantitative reconstructions of past climate variables is a standard palaeoclimatic approach. Despite knowing that the spatial extent of the calibration-set affects the reconstruction result, guidance is lacking as to how to determine a suitable spatial extent of the pollen-climate calibration-set. In this study, past mean annual precipitation (Pann) during the Holocene (since 11.5 cal ka BP) is reconstructed repeatedly for pollen records from Qinghai Lake (36.7°N, 100.5°E; north-east Tibetan Plateau), Gonghai Lake (38.9°N, 112.2°E; north China) and Sihailongwan Lake (42.3°N, 126.6°E; north-east China) using calibration-sets of varying spatial extents extracted from the modern pollen dataset of China and Mongolia (2559 sampling sites and 168 pollen taxa in total). Results indicate that the spatial extent of the calibration-set has a strong impact on model performance, analogue quality and reconstruction diagnostics (absolute value, range, trend, optimum). Generally, these effects are stronger with the modern analogue technique (MAT) than with weighted averaging partial least squares (WA-PLS). With respect to fossil spectra from northern China, the spatial extent of calibration-sets should be restricted to ca. 1000 km in radius because small-scale calibration-sets (<800 km radius) will likely fail to include enough spatial variation in the modern pollen assemblages to reflect the temporal range shifts during the Holocene, while too broad a scale calibration-set (>1500 km radius) will include taxa with very different pollen-climate relationships. Based on our results we conclude that the optimal calibration-set should 1) cover a reasonably large spatial extent with an even distribution of modern pollen samples; 2) possess good model performance as indicated by cross-validation, high analogue quality, and excellent fit with the target fossil pollen spectra; 3) possess high taxonomic resolution, and 4) obey the modern and past distribution ranges of taxa inferred from palaeo-genetic and macrofossil studies.

A spatially explicit approach to the study of socio-demographic inequality in the spatial distribution of trees across Boston neighborhoods.

PubMed

Duncan, Dustin T; Kawachi, Ichiro; Kum, Susan; Aldstadt, Jared; Piras, Gianfranco; Matthews, Stephen A; Arbia, Giuseppe; Castro, Marcia C; White, Kellee; Williams, David R

2014-04-01

The racial/ethnic and income composition of neighborhoods often influences local amenities, including the potential spatial distribution of trees, which are important for population health and community wellbeing, particularly in urban areas. This ecological study used spatial analytical methods to assess the relationship between neighborhood socio-demographic characteristics (i.e. minority racial/ethnic composition and poverty) and tree density at the census tact level in Boston, Massachusetts (US). We examined spatial autocorrelation with the Global Moran's I for all study variables and in the ordinary least squares (OLS) regression residuals as well as computed Spearman correlations non-adjusted and adjusted for spatial autocorrelation between socio-demographic characteristics and tree density. Next, we fit traditional regressions (i.e. OLS regression models) and spatial regressions (i.e. spatial simultaneous autoregressive models), as appropriate. We found significant positive spatial autocorrelation for all neighborhood socio-demographic characteristics (Global Moran's I range from 0.24 to 0.86, all P =0.001), for tree density (Global Moran's I =0.452, P =0.001), and in the OLS regression residuals (Global Moran's I range from 0.32 to 0.38, all P <0.001). Therefore, we fit the spatial simultaneous autoregressive models. There was a negative correlation between neighborhood percent non-Hispanic Black and tree density (r S =-0.19; conventional P -value=0.016; spatially adjusted P -value=0.299) as well as a negative correlation between predominantly non-Hispanic Black (over 60% Black) neighborhoods and tree density (r S =-0.18; conventional P -value=0.019; spatially adjusted P -value=0.180). While the conventional OLS regression model found a marginally significant inverse relationship between Black neighborhoods and tree density, we found no statistically significant relationship between neighborhood socio-demographic composition and tree density in the spatial regression models. Methodologically, our study suggests the need to take into account spatial autocorrelation as findings/conclusions can change when the spatial autocorrelation is ignored. Substantively, our findings suggest no need for policy intervention vis-à-vis trees in Boston, though we hasten to add that replication studies, and more nuanced data on tree quality, age and diversity are needed.

Skyshine study for next generation of fusion devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gohar, Y.; Yang, S.

1987-02-01

A shielding analysis for next generation of fusion devices (ETR/INTOR) was performed to study the dose equivalent outside the reactor building during operation including the contribution from neutrons and photons scattered back by collisions with air nuclei (skyshine component). Two different three-dimensional geometrical models for a tokamak fusion reactor based on INTOR design parameters were developed for this study. In the first geometrical model, the reactor geometry and the spatial distribution of the deuterium-tritium neutron source were simplified for a parametric survey. The second geometrical model employed an explicit representation of the toroidal geometry of the reactor chamber and themore » spatial distribution of the neutron source. The MCNP general Monte Carlo code for neutron and photon transport was used to perform all the calculations. The energy distribution of the neutron source was used explicitly in the calculations with ENDF/B-V data. The dose equivalent results were analyzed as a function of the concrete roof thickness of the reactor building and the location outside the reactor building.« less

Geologic Mapping of the Lunar South Pole Quadrangle (LQ-30)

NASA Technical Reports Server (NTRS)

Mest, S. C.; Berman, D. C.; Petro, N. E.

2010-01-01

In this study we use recent image, spectral and topographic data to map the geology of the lunar South Pole quadrangle (LQ-30) at 1:2.5M scale [1-7]. The overall objective of this research is to constrain the geologic evolution of LQ-30 (60 -90 S, 0 - 180 ) with specific emphasis on evaluation of a) the regional effects of impact basin formation, and b) the spatial distribution of ejecta, in particular resulting from formation of the South Pole-Aitken (SPA) basin and other large basins. Key scientific objectives include: 1) Determining the geologic history of LQ-30 and examining the spatial and temporal variability of geologic processes within the map area. 2) Constraining the distribution of impact-generated materials, and determining the timing and effects of major basin-forming impacts on crustal structure and stratigraphy in the map area. And 3) assessing the distribution of potential resources (e.g., H, Fe, Th) and their relationships with surface materials.

Spatial and Seasonal Distribution of American Whaling and Whales in the Age of Sail

PubMed Central

Smith, Tim D.; Reeves, Randall R.; Josephson, Elizabeth A.; Lund, Judith N.

2012-01-01

American whalemen sailed out of ports on the east coast of the United States and in California from the 18th to early 20th centuries, searching for whales throughout the world’s oceans. From an initial focus on sperm whales (Physeter macrocephalus) and right whales (Eubalaena spp.), the array of targeted whales expanded to include bowhead whales (Balaena mysticetus), humpback whales (Megaptera novaeangliae), and gray whales (Eschrichtius robustus). Extensive records of American whaling in the form of daily entries in whaling voyage logbooks contain a great deal of information about where and when the whalemen found whales. We plotted daily locations where the several species of whales were observed, both those caught and those sighted but not caught, on world maps to illustrate the spatial and temporal distribution of both American whaling activity and the whales. The patterns shown on the maps provide the basis for various inferences concerning the historical distribution of the target whales prior to and during this episode of global whaling. PMID:22558102

Spatial and seasonal distribution of American whaling and whales in the age of sail.

PubMed

Smith, Tim D; Reeves, Randall R; Josephson, Elizabeth A; Lund, Judith N

2012-01-01

American whalemen sailed out of ports on the east coast of the United States and in California from the 18(th) to early 20(th) centuries, searching for whales throughout the world's oceans. From an initial focus on sperm whales (Physeter macrocephalus) and right whales (Eubalaena spp.), the array of targeted whales expanded to include bowhead whales (Balaena mysticetus), humpback whales (Megaptera novaeangliae), and gray whales (Eschrichtius robustus). Extensive records of American whaling in the form of daily entries in whaling voyage logbooks contain a great deal of information about where and when the whalemen found whales. We plotted daily locations where the several species of whales were observed, both those caught and those sighted but not caught, on world maps to illustrate the spatial and temporal distribution of both American whaling activity and the whales. The patterns shown on the maps provide the basis for various inferences concerning the historical distribution of the target whales prior to and during this episode of global whaling.

Laterally Coupled Quantum-Dot Distributed-Feedback Lasers

NASA Technical Reports Server (NTRS)

Qui, Yueming; Gogna, Pawan; Muller, Richard; Maker, paul; Wilson, Daniel; Stintz, Andreas; Lester, Luke

2003-01-01

InAs quantum-dot lasers that feature distributed feedback and lateral evanescent- wave coupling have been demonstrated in operation at a wavelength of 1.3 m. These lasers are prototypes of optical-communication oscillators that are required to be capable of stable single-frequency, single-spatial-mode operation. A laser of this type (see figure) includes an active layer that comprises multiple stacks of InAs quantum dots embedded within InGaAs quantum wells. Distributed feedback is provided by gratings formed on both sides of a ridge by electron lithography and reactive-ion etching on the surfaces of an AlGaAs/GaAs waveguide. The lateral evanescent-wave coupling between the gratings and the wave propagating in the waveguide is strong enough to ensure operation at a single frequency, and the waveguide is thick enough to sustain a stable single spatial mode. In tests, the lasers were found to emit continuous-wave radiation at temperatures up to about 90 C. Side modes were found to be suppressed by more than 30 dB.

Control systems using modal domain optical fiber sensors for smart structure applications

NASA Technical Reports Server (NTRS)

Lindner, Douglas K.; Reichard, Karl M.

1991-01-01

Recently, a new class of sensors has emerged for structural control which respond to environmental changes over a significant gauge length; these sensors are called distributed-effect sensors. These sensors can be fabricated with spatially varying sensitivity to the distributed measurand, and can be configured to measure a variety of structural parameters which can not be measured directly using point sensors. Examples of distributed-effect sensors include piezoelectric film, holographic sensors, and modal domain optical fiber sensors. Optical fiber sensors are particularly attractive for smart structure applications because they are flexible, have low mass, and can easily be embedded directly into materials. In this paper we describe the implementation of weighted modal domain optical fiber sensors. The mathematical model of the modal domain optical fiber sensor model is described and used to derive an expression for the sensor sensitivity. The effects of parameter variations on the sensor sensitivity are demonstrated to illustrate methods of spatially varying the sensor sensitivity.

Onondaga Lake Watershed – A Geographic Information System Project Phase I – Needs assessment and spatial data framework

USGS Publications Warehouse

Freehafer, Douglas A.; Pierson, Oliver

2004-01-01

In the fall of 2002, the Onondaga Lake Partnership (OLP) formed a Geographic Information System (GIS) Planning Committee to begin the process of developing a comprehensive watershed geographic information system for Onondaga Lake. The goal of the Onondaga Lake Partnership geographic information system is to integrate the various types of spatial data used for scientific investigations, resource management, and planning and design of improvement projects in the Onondaga Lake Watershed. A needs-assessment survey was conducted and a spatial data framework developed to support the Onondaga Lake Partnership use of geographic information system technology. The design focused on the collection, management, and distribution of spatial data, maps, and internet mapping applications. A geographic information system library of over 100 spatial datasets and metadata links was assembled on the basis of the results of the needs assessment survey. Implementation options were presented, and the Geographic Information System Planning Committee offered recommendations for the management and distribution of spatial data belonging to Onondaga Lake Partnership members. The Onondaga Lake Partnership now has a strong foundation for building a comprehensive geographic information system for the Onondaga Lake watershed. The successful implementation of a geographic information system depends on the Onondaga Lake Partnership’s determination of: (1) the design and plan for a geographic information system, including the applications and spatial data that will be provided and to whom, (2) the level of geographic information system technology to be utilized and funded, and (3) the institutional issues of operation and maintenance of the system.

RiceAtlas, a spatial database of global rice calendars and production.

PubMed

Laborte, Alice G; Gutierrez, Mary Anne; Balanza, Jane Girly; Saito, Kazuki; Zwart, Sander J; Boschetti, Mirco; Murty, M V R; Villano, Lorena; Aunario, Jorrel Khalil; Reinke, Russell; Koo, Jawoo; Hijmans, Robert J; Nelson, Andrew

2017-05-30

Knowing where, when, and how much rice is planted and harvested is crucial information for understanding the effects of policy, trade, and global and technological change on food security. We developed RiceAtlas, a spatial database on the seasonal distribution of the world's rice production. It consists of data on rice planting and harvesting dates by growing season and estimates of monthly production for all rice-producing countries. Sources used for planting and harvesting dates include global and regional databases, national publications, online reports, and expert knowledge. Monthly production data were estimated based on annual or seasonal production statistics, and planting and harvesting dates. RiceAtlas has 2,725 spatial units. Compared with available global crop calendars, RiceAtlas is nearly ten times more spatially detailed and has nearly seven times more spatial units, with at least two seasons of calendar data, making RiceAtlas the most comprehensive and detailed spatial database on rice calendar and production.

Spatial Downscaling of Alien Species Presences using Machine Learning

NASA Astrophysics Data System (ADS)

Daliakopoulos, Ioannis N.; Katsanevakis, Stelios; Moustakas, Aristides

2017-07-01

Large scale, high-resolution data on alien species distributions are essential for spatially explicit assessments of their environmental and socio-economic impacts, and management interventions for mitigation. However, these data are often unavailable. This paper presents a method that relies on Random Forest (RF) models to distribute alien species presence counts at a finer resolution grid, thus achieving spatial downscaling. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The method is tested with an approximately 8×8 km2 grid containing floral alien species presence and several indices of climatic, habitat, land use covariates for the Mediterranean island of Crete, Greece. Alien species presence is aggregated at 16×16 km2 and used as a predictor of presence at the original resolution, thus simulating spatial downscaling. Potential explanatory variables included habitat types, land cover richness, endemic species richness, soil type, temperature, precipitation, and freshwater availability. Uncertainty assessment of the spatial downscaling of alien species’ occurrences was also performed and true/false presences and absences were quantified. The approach is promising for downscaling alien species datasets of larger spatial scale but coarse resolution, where the underlying environmental information is available at a finer resolution than the alien species data. Furthermore, the RF architecture allows for tuning towards operationally optimal sensitivity and specificity, thus providing a decision support tool for designing a resource efficient alien species census.

Mapping the spatial distribution of global anthropogenic mercury atmospheric emission inventories

NASA Astrophysics Data System (ADS)

Wilson, Simon J.; Steenhuisen, Frits; Pacyna, Jozef M.; Pacyna, Elisabeth G.

This paper describes the procedures employed to spatially distribute global inventories of anthropogenic emissions of mercury to the atmosphere, prepared by Pacyna, E.G., Pacyna, J.M., Steenhuisen, F., Wilson, S. [2006. Global anthropogenic mercury emission inventory for 2000. Atmospheric Environment, this issue, doi:10.1016/j.atmosenv.2006.03.041], and briefly discusses the results of this work. A new spatially distributed global emission inventory for the (nominal) year 2000, and a revised version of the 1995 inventory are presented. Emissions estimates for total mercury and major species groups are distributed within latitude/longitude-based grids with a resolution of 1×1 and 0.5×0.5°. A key component in the spatial distribution procedure is the use of population distribution as a surrogate parameter to distribute emissions from sources that cannot be accurately geographically located. In this connection, new gridded population datasets were prepared, based on the CEISIN GPW3 datasets (CIESIN, 2004. Gridded Population of the World (GPW), Version 3. Center for International Earth Science Information Network (CIESIN), Columbia University and Centro Internacional de Agricultura Tropical (CIAT). GPW3 data are available at http://beta.sedac.ciesin.columbia.edu/gpw/index.jsp). The spatially distributed emissions inventories and population datasets prepared in the course of this work are available on the Internet at www.amap.no/Resources/HgEmissions/

Soil nutrients influence spatial distributions of tropical tree species.

PubMed

John, Robert; Dalling, James W; Harms, Kyle E; Yavitt, Joseph B; Stallard, Robert F; Mirabello, Matthew; Hubbell, Stephen P; Valencia, Renato; Navarrete, Hugo; Vallejo, Martha; Foster, Robin B

2007-01-16

The importance of niche vs. neutral assembly mechanisms in structuring tropical tree communities remains an important unsettled question in community ecology [Bell G (2005) Ecology 86:1757-1770]. There is ample evidence that species distributions are determined by soils and habitat factors at landscape (<10(4) km(2)) and regional scales. At local scales (<1 km(2)), however, habitat factors and species distributions show comparable spatial aggregation, making it difficult to disentangle the importance of niche and dispersal processes. In this article, we test soil resource-based niche assembly at a local scale, using species and soil nutrient distributions obtained at high spatial resolution in three diverse neotropical forest plots in Colombia (La Planada), Ecuador (Yasuni), and Panama (Barro Colorado Island). Using spatial distribution maps of >0.5 million individual trees of 1,400 species and 10 essential plant nutrients, we used Monte Carlo simulations of species distributions to test plant-soil associations against null expectations based on dispersal assembly. We found that the spatial distributions of 36-51% of tree species at these sites show strong associations to soil nutrient distributions. Neutral dispersal assembly cannot account for these plant-soil associations or the observed niche breadths of these species. These results indicate that belowground resource availability plays an important role in the assembly of tropical tree communities at local scales and provide the basis for future investigations on the mechanisms of resource competition among tropical tree species.

Functional resilience of microbial ecosystems in soil: How important is a spatial analysis?

NASA Astrophysics Data System (ADS)

König, Sara; Banitz, Thomas; Centler, Florian; Frank, Karin; Thullner, Martin

2015-04-01

Microbial life in soil is exposed to fluctuating environmental conditions influencing the performance of microbially mediated ecosystem services such as biodegradation of contaminants. However, as this environment is typically very heterogeneous, spatial aspects can be expected to play a major role for the ability to recover from a stress event. To determine key processes for functional resilience, simple scenarios with varying stress intensities were simulated within a microbial simulation model and the biodegradation rate in the recovery phase monitored. Parameters including microbial growth and dispersal rates were varied over a typical range to consider microorganisms with varying properties. Besides an aggregated temporal monitoring, the explicit observation of the spatio-temporal dynamics proved essential to understand the recovery process. For a mechanistic understanding of the model system, scenarios were also simulated with selected processes being switched-off. Results of the mechanistic and the spatial view show that the key factors for functional recovery with respect to biodegradation after a simple stress event depend on the location of the observed habitats. The limiting factors near unstressed areas are spatial processes - the mobility of the bacteria as well as substrate diffusion - the longer the distance to the unstressed region the more important becomes the process growth. Furthermore, recovery depends on the stress intensity - after a low stress event the spatial configuration has no influence on the key factors for functional resilience. To confirm these results, we repeated the stress scenarios but this time including an additional dispersal network representing a fungal network in soil. The system benefits from an increased spatial performance due to the higher mobility of the degrading microorganisms. However, this effect appears only in scenarios where the spatial distribution of the stressed area plays a role. With these simulations we show that spatial aspects play a main role for recovering after a severe stress event in a highly heterogeneous environment such as soil, and thus the relevance of the exact distribution of the stressed area. In consequence a spatial-mechanistic view is necessary for examining the functional resilience as the aggregated temporal view alone could not have led to these conclusions. Further research should explore the importance of a spatial view for quantifying the recovery of the ecosystem service also after more complex stress regimes.

Spatial distribution visualization of PWM continuous variable-rate spray

USDA-ARS?s Scientific Manuscript database

Chemical application is a dynamic spatial distribution process, during which spray liquid covers the targets with certain thickness and uniformity. Therefore, it is important to study the 2-D and 3-D (dimensional) spray distribution to evaluate spraying quality. The curve-surface generation methods ...

Experimental study of the spatial distributions of relativistic electron beams reflected and refracted by a thin foil

DOE Office of Scientific and Technical Information (OSTI.GOV)

Serov, A. V., E-mail: serov@x4u.lebedev.ru; Mamonov, I. A.

2016-08-15

Photographs of cross sections of an electron beam scattered from thin foils have been obtained on a dosimetric film. The procession of images makes it possible to obtain the spatial distribution of particles both reflected from a foil and passed through it. The spatial distribution of electrons incident on aluminum, copper, and lead foils, as well as on bimetallic foils composed of aluminum and lead layers and of aluminum and copper layers, has been measured. The effect of the material and thickness of the foil, as well as of the angle between the initial beam trajectory and the target plane,more » on the spatial distribution of electrons has been studied. The effect of the sequence of the metal layers in bimetallic foils on the distribution of beams has been analyzed. A 7.4-MeV microtron has been used as a source of electrons.« less

BATSE analysis techniques for probing the GRB spatial and luminosity distributions

NASA Technical Reports Server (NTRS)

Hakkila, Jon; Meegan, Charles A.

1992-01-01

The Burst And Transient Source Experiment (BATSE) has measured homogeneity and isotropy parameters from an increasingly large sample of observed gamma-ray bursts (GRBs), while also maintaining a summary of the way in which the sky has been sampled. Measurement of both of these are necessary for any study of the BATSE data statistically, as they take into account the most serious observational selection effects known in the study of GRBs: beam-smearing and inhomogeneous, anisotropic sky sampling. Knowledge of these effects is important to analysis of GRB angular and intensity distributions. In addition to determining that the bursts are local, it is hoped that analysis of such distributions will allow boundaries to be placed on the true GRB spatial distribution and luminosity function. The technique for studying GRB spatial and luminosity distributions is direct. Results of BATSE analyses are compared to Monte Carlo models parameterized by a variety of spatial and luminosity characteristics.

Spatial transferability of habitat suitability models of Nephrops norvegicus among fished areas in the Northeast Atlantic: sufficiently stable for marine resource conservation?

PubMed

Lauria, Valentina; Power, Anne Marie; Lordan, Colm; Weetman, Adrian; Johnson, Mark P

2015-01-01

Knowledge of the spatial distribution and habitat associations of species in relation to the environment is essential for their management and conservation. Habitat suitability models are useful in quantifying species-environment relationships and predicting species distribution patterns. Little is known, however, about the stability and performance of habitat suitability models when projected into new areas (spatial transferability) and how this can inform resource management. The aims of this study were to model habitat suitability of Norway lobster (Nephrops norvegicus) in five fished areas of the Northeast Atlantic (Aran ground, Irish Sea, Celtic Sea, Scotland Inshore and Fladen ground), and to test for spatial transferability of habitat models among multiple regions. Nephrops burrow density was modelled using generalised additive models (GAMs) with predictors selected from four environmental variables (depth, slope, sediment and rugosity). Models were evaluated and tested for spatial transferability among areas. The optimum models (lowest AICc) for different areas always included depth and sediment as predictors. Burrow densities were generally greater at depth and in finer sediments, but relationships for individual areas were sometimes more complex. Aside from an inclusion of depth and sediment, the optimum models differed between fished areas. When it came to tests of spatial transferability, however, most of the models were able to predict Nephrops density in other areas. Furthermore, transferability was not dependent on use of the optimum models since competing models were also able to achieve a similar level of transferability to new areas. A degree of decoupling between model 'fitting' performance and spatial transferability supports the use of simpler models when extrapolating habitat suitability maps to different areas. Differences in the form and performance of models from different areas may supply further information on the processes shaping species' distributions. Spatial transferability of habitat models can be used to support fishery management when the information is scarce but caution needs to be applied when making inference and a multi-area transferability analysis is preferable to bilateral comparisons between areas.

Determinants of Spatial Distribution in a Bee Community: Nesting Resources, Flower Resources, and Body Size

PubMed Central

Torné-Noguera, Anna; Rodrigo, Anselm; Arnan, Xavier; Osorio, Sergio; Barril-Graells, Helena; da Rocha-Filho, Léo Correia; Bosch, Jordi

2014-01-01

Understanding biodiversity distribution is a primary goal of community ecology. At a landscape scale, bee communities are affected by habitat composition, anthropogenic land use, and fragmentation. However, little information is available on local-scale spatial distribution of bee communities within habitats that are uniform at the landscape scale. We studied a bee community along with floral and nesting resources over a 32 km2 area of uninterrupted Mediterranean scrubland. Our objectives were (i) to analyze floral and nesting resource composition at the habitat scale. We ask whether these resources follow a geographical pattern across the scrubland at bee-foraging relevant distances; (ii) to analyze the distribution of bee composition across the scrubland. Bees being highly mobile organisms, we ask whether bee composition shows a homogeneous distribution or else varies spatially. If so, we ask whether this variation is irregular or follows a geographical pattern and whether bees respond primarily to flower or to nesting resources; and (iii) to establish whether body size influences the response to local resource availability and ultimately spatial distribution. We obtained 6580 specimens belonging to 98 species. Despite bee mobility and the absence of environmental barriers, our bee community shows a clear geographical pattern. This pattern is mostly attributable to heterogeneous distribution of small (<55 mg) species (with presumed smaller foraging ranges), and is mostly explained by flower resources rather than nesting substrates. Even then, a large proportion (54.8%) of spatial variability remains unexplained by flower or nesting resources. We conclude that bee communities are strongly conditioned by local effects and may exhibit spatial heterogeneity patterns at a scale as low as 500–1000 m in patches of homogeneous habitat. These results have important implications for local pollination dynamics and spatial variation of plant-pollinator networks. PMID:24824445

Determinants of spatial distribution in a bee community: nesting resources, flower resources, and body size.

PubMed

Torné-Noguera, Anna; Rodrigo, Anselm; Arnan, Xavier; Osorio, Sergio; Barril-Graells, Helena; da Rocha-Filho, Léo Correia; Bosch, Jordi

2014-01-01

Understanding biodiversity distribution is a primary goal of community ecology. At a landscape scale, bee communities are affected by habitat composition, anthropogenic land use, and fragmentation. However, little information is available on local-scale spatial distribution of bee communities within habitats that are uniform at the landscape scale. We studied a bee community along with floral and nesting resources over a 32 km2 area of uninterrupted Mediterranean scrubland. Our objectives were (i) to analyze floral and nesting resource composition at the habitat scale. We ask whether these resources follow a geographical pattern across the scrubland at bee-foraging relevant distances; (ii) to analyze the distribution of bee composition across the scrubland. Bees being highly mobile organisms, we ask whether bee composition shows a homogeneous distribution or else varies spatially. If so, we ask whether this variation is irregular or follows a geographical pattern and whether bees respond primarily to flower or to nesting resources; and (iii) to establish whether body size influences the response to local resource availability and ultimately spatial distribution. We obtained 6580 specimens belonging to 98 species. Despite bee mobility and the absence of environmental barriers, our bee community shows a clear geographical pattern. This pattern is mostly attributable to heterogeneous distribution of small (<55 mg) species (with presumed smaller foraging ranges), and is mostly explained by flower resources rather than nesting substrates. Even then, a large proportion (54.8%) of spatial variability remains unexplained by flower or nesting resources. We conclude that bee communities are strongly conditioned by local effects and may exhibit spatial heterogeneity patterns at a scale as low as 500-1000 m in patches of homogeneous habitat. These results have important implications for local pollination dynamics and spatial variation of plant-pollinator networks.

Spatial distribution of precipitation extremes in Norway

NASA Astrophysics Data System (ADS)

Verpe Dyrrdal, Anita; Skaugen, Thomas; Lenkoski, Alex; Thorarinsdottir, Thordis; Stordal, Frode; Førland, Eirik J.

2015-04-01

Estimates of extreme precipitation, in terms of return levels, are crucial in planning and design of important infrastructure. Through two separate studies, we have examined the levels and spatial distribution of daily extreme precipitation over catchments in Norway, and hourly extreme precipitation in a point. The analyses were carried out through the development of two new methods for estimating extreme precipitation in Norway. For daily precipitation we fit the Generalized Extreme Value (GEV) distribution to areal time series from a gridded dataset, consisting of daily precipitation during the period 1957-today with a resolution of 1x1 km². This grid-based method is more objective and less manual and time-consuming compared to the existing method at MET Norway. In addition, estimates in ungauged catchments are easier to obtain, and the GEV approach includes a measure of uncertainty, which is a requirement in climate studies today. Further, we go into depth on the debated GEV shape parameter, which plays an important role for longer return periods. We show that it varies according to dominating precipitation types, having positive values in the southeast and negative values in the southwest. We also find indications that the degree of orographic enhancement might affect the shape parameter. For hourly precipitation, we estimate return levels on a 1x1 km² grid, by linking GEV distributions with latent Gaussian fields in a Bayesian hierarchical model (BHM). Generalized linear models on the GEV parameters, estimated from observations, are able to incorporate location-specific geographic and meteorological information and thereby accommodate these effects on extreme precipitation. Gaussian fields capture additional unexplained spatial heterogeneity and overcome the sparse grid on which observations are collected, while a Bayesian model averaging component directly assesses model uncertainty. We find that mean summer precipitation, mean summer temperature, latitude, longitude, mean annual precipitation and elevation are good covariate candidates for hourly precipitation in our model. Summer indices succeed because hourly precipitation extremes often occur during the convective season. The spatial distribution of hourly and daily precipitation differs in Norway. Daily precipitation extremes are larger along the southwestern coast, where large-scale frontal systems dominate during fall season and the mountain ridge generates strong orographic enhancement. The largest hourly precipitation extremes are mostly produced by intense convective showers during summer, and are thus found along the entire southern coast, including the Oslo-region.

A New Global LAI Product and Its Use for Terrestrial Carbon Cycle Estimation

NASA Astrophysics Data System (ADS)

Chen, J. M.; Liu, R.; Ju, W.; Liu, Y.

2014-12-01

For improving the estimation of the spatio-temporal dynamics of the terrestrial carbon cycle, a new time series of the leaf area index (LAI) is generated for the global land surface at 8 km resolution from 1981 to 2012 by combining AVHRR and MODIS satellite data. This product differs from existing LAI products in the following two aspects: (1) the non-random spatial distribution of leaves with the canopy is considered, and (2) the seasonal variation of the vegetation background is included. The non-randomness of the leaf spatial distribution in the canopy is considered using the second vegetation structural parameter named clumping index (CI), which quantifies the deviation of the leaf spatial distribution from the random case. Using the MODIS Bidirectional Reflectance Distribution Function product, a global map of CI is produced at 500 m resolution. In our LAI algorithm, CI is used to convert the effective LAI obtained from mono-angle remote sensing into the true LAI, otherwise LAI would be considerably underestimated. The vegetation background is soil in crop, grass and shrub but includes soil, grass, moss, and litter in forests. Through processing a large volume of MISR data from 2000 to 2010, monthly red and near-infrared reflectances of the vegetation background is mapped globally at 1 km resolution. This new LAI product has been validated extensively using ground-based LAI measurements distributed globally. In carbon cycle modeling, the use of CI in addition to LAI allows for accurate separation of sunlit and shaded leaves as an important step in terrestrial photosynthesis and respiration modeling. Carbon flux measurements over 100 sites over the globe are used to validate an ecosystem model named Boreal Ecosystem Productivity Simulator (BEPS). The validated model is run globally at 8 km resolution for the period from 1981 to 2012 using the LAI product and other spatial datasets. The modeled results suggest that changes in vegetation structure as quantified by LAI do not contribute significantly to the increasing trend in carbon sink over the last 32 years. The increases in atmospheric CO2 concentration and nitrogen deposition are found to be the major causes for the increases in plant productivity and carbon sink over the last 32 years.

A multiscale Bayesian data integration approach for mapping air dose rates around the Fukushima Daiichi Nuclear Power Plant.

PubMed

Wainwright, Haruko M; Seki, Akiyuki; Chen, Jinsong; Saito, Kimiaki

2017-02-01

This paper presents a multiscale data integration method to estimate the spatial distribution of air dose rates in the regional scale around the Fukushima Daiichi Nuclear Power Plant. We integrate various types of datasets, such as ground-based walk and car surveys, and airborne surveys, all of which have different scales, resolutions, spatial coverage, and accuracy. This method is based on geostatistics to represent spatial heterogeneous structures, and also on Bayesian hierarchical models to integrate multiscale, multi-type datasets in a consistent manner. The Bayesian method allows us to quantify the uncertainty in the estimates, and to provide the confidence intervals that are critical for robust decision-making. Although this approach is primarily data-driven, it has great flexibility to include mechanistic models for representing radiation transport or other complex correlations. We demonstrate our approach using three types of datasets collected at the same time over Fukushima City in Japan: (1) coarse-resolution airborne surveys covering the entire area, (2) car surveys along major roads, and (3) walk surveys in multiple neighborhoods. Results show that the method can successfully integrate three types of datasets and create an integrated map (including the confidence intervals) of air dose rates over the domain in high resolution. Moreover, this study provides us with various insights into the characteristics of each dataset, as well as radiocaesium distribution. In particular, the urban areas show high heterogeneity in the contaminant distribution due to human activities as well as large discrepancy among different surveys due to such heterogeneity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Distributed spatial information integration based on web service

NASA Astrophysics Data System (ADS)

Tong, Hengjian; Zhang, Yun; Shao, Zhenfeng

2008-10-01

Spatial information systems and spatial information in different geographic locations usually belong to different organizations. They are distributed and often heterogeneous and independent from each other. This leads to the fact that many isolated spatial information islands are formed, reducing the efficiency of information utilization. In order to address this issue, we present a method for effective spatial information integration based on web service. The method applies asynchronous invocation of web service and dynamic invocation of web service to implement distributed, parallel execution of web map services. All isolated information islands are connected by the dispatcher of web service and its registration database to form a uniform collaborative system. According to the web service registration database, the dispatcher of web services can dynamically invoke each web map service through an asynchronous delegating mechanism. All of the web map services can be executed at the same time. When each web map service is done, an image will be returned to the dispatcher. After all of the web services are done, all images are transparently overlaid together in the dispatcher. Thus, users can browse and analyze the integrated spatial information. Experiments demonstrate that the utilization rate of spatial information resources is significantly raised thought the proposed method of distributed spatial information integration.

Distributed spatial information integration based on web service

NASA Astrophysics Data System (ADS)

Tong, Hengjian; Zhang, Yun; Shao, Zhenfeng

2009-10-01

Spatial information systems and spatial information in different geographic locations usually belong to different organizations. They are distributed and often heterogeneous and independent from each other. This leads to the fact that many isolated spatial information islands are formed, reducing the efficiency of information utilization. In order to address this issue, we present a method for effective spatial information integration based on web service. The method applies asynchronous invocation of web service and dynamic invocation of web service to implement distributed, parallel execution of web map services. All isolated information islands are connected by the dispatcher of web service and its registration database to form a uniform collaborative system. According to the web service registration database, the dispatcher of web services can dynamically invoke each web map service through an asynchronous delegating mechanism. All of the web map services can be executed at the same time. When each web map service is done, an image will be returned to the dispatcher. After all of the web services are done, all images are transparently overlaid together in the dispatcher. Thus, users can browse and analyze the integrated spatial information. Experiments demonstrate that the utilization rate of spatial information resources is significantly raised thought the proposed method of distributed spatial information integration.

Life expectancy impacts due to heating energy utilization in China: Distribution, relations, and policy implications.

PubMed

Wang, Shaobin; Luo, Kunli

2018-01-01

The relation between life expectancy and energy utilization is of particular concern. Different viewpoints concerned the health impacts of heating policy in China. However, it is still obscure that what kind of heating energy or what pattern of heating methods is the most related with the difference of life expectancies in China. The aim of this paper is to comprehensively investigate the spatial relations between life expectancy at birth (LEB) and different heating energy utilization in China by using spatial autocorrelation models including global spatial autocorrelation, local spatial autocorrelation and hot spot analysis. The results showed that: (1) Most of heating energy exhibit a distinct north-south difference, such as central heating supply, stalks and domestic coal. Whereas spatial distribution of domestic natural gas and electricity exhibited west-east differences. (2) Consumption of central heating, stalks and domestic coal show obvious spatial dependence. Whereas firewood, natural gas and electricity did not show significant spatial autocorrelation. It exhibited an extinct south-north difference of heat supply, stalks and domestic coal which were identified to show significant positive spatial autocorrelation. (3) Central heating, residential boilers and natural gas did not show any significant correlations with LEB. While, the utilization of domestic coal and biomass showed significant negative correlations with LEB, and household electricity shows positive correlations. The utilization of domestic coal in China showed a negative effect on LEB, rather than central heating. To improve the solid fuel stoves and control consumption of domestic coal consumption and other low quality solid fuel is imperative to improve the public health level in China in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

The human footprint in Mexico: physical geography and historical legacies.

PubMed

González-Abraham, Charlotte; Ezcurra, Exequiel; Garcillán, Pedro P; Ortega-Rubio, Alfredo; Kolb, Melanie; Bezaury Creel, Juan E

2015-01-01

Using publicly available data on land use and transportation corridors we calculated the human footprint index for the whole of Mexico to identify large-scale spatial patterns in the anthropogenic transformation of the land surface. We developed a map of the human footprint for the whole country and identified the ecological regions that have most transformed by human action. Additionally, we analyzed the extent to which (a) physical geography, expressed spatially in the form of biomes and ecoregions, compared to (b) historical geography, expressed as the spatial distribution of past human settlements, have driven the patterns of human modification of the land. Overall Mexico still has 56% of its land surface with low impact from human activities, but these areas are not evenly distributed. The lowest values are on the arid north and northwest, and the tropical southeast, while the highest values run along the coast of the Gulf of Mexico and from there inland along an east-to-west corridor that follows the Mexican transversal volcanic ranges and the associated upland plateau. The distribution of low- and high footprint areas within ecoregions forms a complex mosaic: the generally well-conserved Mexican deserts have some highly transformed agro-industrial areas, while many well-conserved, low footprint areas still persist in the highly-transformed ecoregions of central Mexico. We conclude that the spatial spread of the human footprint in Mexico is both the result of the limitations imposed by physical geography to human development at the biome level, and, within different biomes, of a complex history of past civilizations and technologies, including the 20th Century demographic explosion but also the spatial pattern of ancient settlements that were occupied by the Spanish Colony.

The Human Footprint in Mexico: Physical Geography and Historical Legacies

PubMed Central

Ortega-Rubio, Alfredo; Kolb, Melanie; Bezaury Creel, Juan E.

2015-01-01

Using publicly available data on land use and transportation corridors we calculated the human footprint index for the whole of Mexico to identify large-scale spatial patterns in the anthropogenic transformation of the land surface. We developed a map of the human footprint for the whole country and identified the ecological regions that have most transformed by human action. Additionally, we analyzed the extent to which (a) physical geography, expressed spatially in the form of biomes and ecoregions, compared to (b) historical geography, expressed as the spatial distribution of past human settlements, have driven the patterns of human modification of the land. Overall Mexico still has 56% of its land surface with low impact from human activities, but these areas are not evenly distributed. The lowest values are on the arid north and northwest, and the tropical southeast, while the highest values run along the coast of the Gulf of Mexico and from there inland along an east-to-west corridor that follows the Mexican transversal volcanic ranges and the associated upland plateau. The distribution of low- and high footprint areas within ecoregions forms a complex mosaic: the generally well-conserved Mexican deserts have some highly transformed agro-industrial areas, while many well-conserved, low footprint areas still persist in the highly-transformed ecoregions of central Mexico. We conclude that the spatial spread of the human footprint in Mexico is both the result of the limitations imposed by physical geography to human development at the biome level, and, within different biomes, of a complex history of past civilizations and technologies, including the 20th Century demographic explosion but also the spatial pattern of ancient settlements that were occupied by the Spanish Colony. PMID:25803839

Inferring Processes from Spatial Patterns: The Role of Directional and Non–Directional Forces in Shaping Fish Larvae Distribution in a Freshwater Lake System

PubMed Central

Bertolo, Andrea; Blanchet, F. Guillaume; Magnan, Pierre; Brodeur, Philippe; Mingelbier, Marc; Legendre, Pierre

2012-01-01

Larval dispersal is a crucial factor for fish recruitment. For fishes with relatively small-bodied larvae, drift has the potential to play a more important role than active habitat selection in determining larval dispersal; therefore, we expect small-bodied fish larvae to be poorly associated with habitat characteristics. To test this hypothesis, we used as model yellow perch (Perca flavescens), whose larvae are among the smallest among freshwater temperate fishes. Thus, we analysed the habitat association of yellow perch larvae at multiple spatial scales in a large shallow fluvial lake by explicitly modelling directional (e.g. due to water currents) and non-directional (e.g. due to aggregation) spatial patterns. This allowed us to indirectly assess the relative roles of drift (directional process) and potential habitat choice on larval dispersal. Our results give weak support to the drift hypothesis, whereas yellow perch show a strong habitat association at unexpectedly small sizes, when compared to other systems. We found consistent non-directional patterns in larvae distributions at both broad and medium spatial scales but only few significant directional components. The environmental variables alone (e.g. vegetation) generally explained a significant and biologically relevant fraction of the variation in fish larvae distribution data. These results suggest that (i) drift plays a minor role in this shallow system, (ii) larvae display spatial patterns that only partially covary with environmental variables, and (iii) larvae are associated to specific habitats. By suggesting that habitat association potentially includes an active choice component for yellow perch larvae, our results shed new light on the ecology of freshwater fish larvae and should help in building more realistic recruitment models. PMID:23185585

Spatial and simultaneous seroepidemiology of anti-Leishmania spp. antibodies in dog owners and their dogs from randomly selected households in a major city of southern Brazil.

PubMed

Benitez, Aline do Nascimento; Martins, Felippe Danyel Cardoso; Mareze, Marcelle; Nino, Beatriz de Souza Lima; Caldart, Eloiza Teles; Ferreira, Fernanda Pinto; Mitsuka-Breganó, Regina; Freire, Roberta Lemos; Galhardo, Juliana Arena; Martins, Camila Marinelli; Biondo, Alexander Welker; Navarro, Italmar Teodorico

2018-06-01

Although leishmaniasis has been described as a classic example of a zoonosis requiring a comprehensive approach for control, to date, no study has been conducted on the spatial distribution of simultaneous Leishmania spp. seroprevalence in dog owners and dogs from randomly selected households in urban settings. Accordingly, the present study aimed to simultaneously identify the seroprevalence, spatial distribution and associated factors of infection with Leishmania spp. in dog owners and their dogs in the city of Londrina, a county seat in southern Brazil with a population of half a million people and ranked 18th in population and 145th in the human development index (HDI) out of 5570 Brazilian cities. Overall, 564 households were surveyed and included 597 homeowners and their 729 dogs. Anti-Leishmania spp. antibodies were detected by ELISA in 9/597 (1.50%) dog owners and in 32/729 (4.38%) dogs, with significantly higher prevalence (p = 0.0042) in dogs. Spatial analysis revealed associations between seropositive dogs and households located up to 500 m from the local railway. No clusters were found for either owner or dog case distributions. In summary, the seroepidemiological and spatial results collectively show a lack of association of the factors for infection, and the results demonstrated higher exposure for dogs than their owners. However, railway areas may provide favorable conditions for the maintenance of infected phlebotomines, thereby causing infection in nearby domiciled dogs. In such an urban scenario, local sanitary barriers should be focused on the terrestrial routes of people and surrounding areas, particularly railways, via continuous vector surveillance and identification of phlebotomines infected by Leishmania spp. Copyright © 2018. Published by Elsevier B.V.

Parameter estimation for a cohesive sediment transport model by assimilating satellite observations in the Hangzhou Bay: Temporal variations and spatial distributions

NASA Astrophysics Data System (ADS)

Wang, Daosheng; Zhang, Jicai; He, Xianqiang; Chu, Dongdong; Lv, Xianqing; Wang, Ya Ping; Yang, Yang; Fan, Daidu; Gao, Shu

2018-01-01

Model parameters in the suspended cohesive sediment transport models are critical for the accurate simulation of suspended sediment concentrations (SSCs). Difficulties in estimating the model parameters still prevent numerical modeling of the sediment transport from achieving a high level of predictability. Based on a three-dimensional cohesive sediment transport model and its adjoint model, the satellite remote sensing data of SSCs during both spring tide and neap tide, retrieved from Geostationary Ocean Color Imager (GOCI), are assimilated to synchronously estimate four spatially and temporally varying parameters in the Hangzhou Bay in China, including settling velocity, resuspension rate, inflow open boundary conditions and initial conditions. After data assimilation, the model performance is significantly improved. Through several sensitivity experiments, the spatial and temporal variation tendencies of the estimated model parameters are verified to be robust and not affected by model settings. The pattern for the variations of the estimated parameters is analyzed and summarized. The temporal variations and spatial distributions of the estimated settling velocity are negatively correlated with current speed, which can be explained using the combination of flocculation process and Stokes' law. The temporal variations and spatial distributions of the estimated resuspension rate are also negatively correlated with current speed, which are related to the grain size of the seabed sediments under different current velocities. Besides, the estimated inflow open boundary conditions reach the local maximum values near the low water slack conditions and the estimated initial conditions are negatively correlated with water depth, which is consistent with the general understanding. The relationships between the estimated parameters and the hydrodynamic fields can be suggestive for improving the parameterization in cohesive sediment transport models.

MAVEN Observations of Escaping Planetary Ions from the Martian Atmosphere: Mass, Velocity, and Spatial Distributions

NASA Astrophysics Data System (ADS)

Dong, Yaxue; Fang, Xiaohua; Brain, D. A.; McFadden, James P.; Halekas, Jasper; Connerney, Jack

2015-04-01

The Mars-solar wind interaction accelerates and transports planetary ions away from the Martian atmosphere through a number of processes, including ‘pick-up’ by electromagnetic fields. The MAVEN spacecraft has made routine observations of escaping planetary ions since its arrival at Mars in September 2014. The SupraThermal And Thermal Ion Composition (STATIC) instrument measures the ion energy, mass, and angular spectra. It has detected energetic planetary ions during most of the spacecraft orbits, which are attributed to the pick-up process. We found significant variations in the escaping ion mass and velocity distributions from the STATIC data, which can be explained by factors such as varying solar wind conditions, contributions of particles from different source locations and different phases during the pick-up process. We also study the spatial distributions of different planetary ion species, which can provide insight into the physics of ion escaping process and enhance our understanding of atmospheric erosion by the solar wind. Our results will be further interpreted within the context of the upstream solar wind conditions measured by the MAVEN Solar Wind Ion Analyzer (SWIA) instrument and the magnetic field environment measured by the Magnetometer (MAG) instrument. Our study shows that the ion spatial distribution in the Mars-Sun-Electric-Field (MSE) coordinate system and the velocity space distribution with respect to the local magnetic field line can be used to distinguish the ions escaping through the polar plume and those through the tail region. The contribution of the polar plume ion escape to the total escape rate will also be discussed.

Using VELMA to Quantify and Visualize the Effectiveness of Green Infrastructure Options for Protecting Water Quality

EPA Science Inventory

This webinar describes the use of VELMA, a spatially-distributed ecohydrological model, to identify green infrastructure (GI) best management practices for protecting water quality in intensively managed watersheds. The seminar will include a brief description of VELMA and an ex...

IMPACT OF EMISSION REDUCTIONS ON EXPOSURES AND EXPOSURE DISTRIBUTIONS: APPLICATION OF A GEOGRAPHIC EXPOSURE MODEL

EPA Science Inventory

Anticipated results include the following. (1) We will estimate intake fraction (i.e., the fraction of emissions that are inhaled) for major source categories, over time, and by spatial location. Higher intake fraction indicates a greater exposure reduction per emission reduct...

Thermal equilibrium and statistical thermometers in special relativity.

PubMed

Cubero, David; Casado-Pascual, Jesús; Dunkel, Jörn; Talkner, Peter; Hänggi, Peter

2007-10-26

There is an intense debate in the recent literature about the correct generalization of Maxwell's velocity distribution in special relativity. The most frequently discussed candidate distributions include the Jüttner function as well as modifications thereof. Here we report results from fully relativistic one-dimensional molecular dynamics simulations that resolve the ambiguity. The numerical evidence unequivocally favors the Jüttner distribution. Moreover, our simulations illustrate that the concept of "thermal equilibrium" extends naturally to special relativity only if a many-particle system is spatially confined. They make evident that "temperature" can be statistically defined and measured in an observer frame independent way.

Considerations in the use of fluorescence in situ hybridization (FISH) and confocal laser scanning microscopy to characterize rumen methanogens and define their spatial distributions.

PubMed

Valle, Edith R; Henderson, Gemma; Janssen, Peter H; Cox, Faith; Alexander, Trevor W; McAllister, Tim A

2015-06-01

In this study, methanogen-specific coenzyme F420 autofluorescence and confocal laser scanning microscopy were used to identify rumen methanogens and define their spatial distribution in free-living, biofilm-, and protozoa-associated microenvironments. Fluorescence in situ hybridization (FISH) with temperature-controlled hybridization was used in an attempt to describe methanogen diversity. A heat pretreatment (65 °C, 1 h) was found to be a noninvasive method to increase probe access to methanogen RNA targets. Despite efforts to optimize FISH, 16S rRNA methanogen-specific probes, including Arch915, bound to some cells that lacked F420, possibly identifying uncharacterized Methanomassiliicoccales or reflecting nonspecific binding to other members of the rumen bacterial community. A probe targeting RNA from the methanogenesis-specific methyl coenzyme M reductase (mcr) gene was shown to detect cultured Methanosarcina cells with signal intensities comparable to those of 16S rRNA probes. However, the probe failed to hybridize with the majority of F420-emitting rumen methanogens, possibly because of differences in cell wall permeability among methanogen species. Methanogens were shown to integrate into microbial biofilms and to exist as ecto- and endosymbionts with rumen protozoa. Characterizing rumen methanogens and defining their spatial distribution may provide insight into mitigation strategies for ruminal methanogenesis.

[Application of simulated annealing method and neural network on optimizing soil sampling schemes based on road distribution].

PubMed

Han, Zong-wei; Huang, Wei; Luo, Yun; Zhang, Chun-di; Qi, Da-cheng

2015-03-01

Taking the soil organic matter in eastern Zhongxiang County, Hubei Province, as a research object, thirteen sample sets from different regions were arranged surrounding the road network, the spatial configuration of which was optimized by the simulated annealing approach. The topographic factors of these thirteen sample sets, including slope, plane curvature, profile curvature, topographic wetness index, stream power index and sediment transport index, were extracted by the terrain analysis. Based on the results of optimization, a multiple linear regression model with topographic factors as independent variables was built. At the same time, a multilayer perception model on the basis of neural network approach was implemented. The comparison between these two models was carried out then. The results revealed that the proposed approach was practicable in optimizing soil sampling scheme. The optimal configuration was capable of gaining soil-landscape knowledge exactly, and the accuracy of optimal configuration was better than that of original samples. This study designed a sampling configuration to study the soil attribute distribution by referring to the spatial layout of road network, historical samples, and digital elevation data, which provided an effective means as well as a theoretical basis for determining the sampling configuration and displaying spatial distribution of soil organic matter with low cost and high efficiency.

Spatial Structures of the Environment and of Dispersal Impact Species Distribution in Competitive Metacommunities

PubMed Central

Ai, Dexiecuo; Gravel, Dominique; Chu, Chengjin; Wang, Gang

2013-01-01

The correspondence between species distribution and the environment depends on species’ ability to track favorable environmental conditions (via dispersal) and to maintain competitive hierarchy against the constant influx of migrants (mass effect) and demographic stochasticity (ecological drift). Here we report a simulation study of the influence of landscape structure on species distribution. We consider lottery competition for space in a spatially heterogeneous environment, where the landscape is represented as a network of localities connected by dispersal. We quantified the contribution of neutrality and species sorting to their spatial distribution. We found that neutrality increases and the strength of species-sorting decreases with the centrality of a community in the landscape when the average dispersal among communities is low, whereas the opposite was found at elevated dispersal. We also found that the strength of species-sorting increases with environmental heterogeneity. Our results illustrate that spatial structure of the environment and of dispersal must be taken into account for understanding species distribution. We stress the importance of spatial geographic structure on the relative importance of niche vs. neutral processes in controlling community dynamics. PMID:23874815

Spatial structures of the environment and of dispersal impact species distribution in competitive metacommunities.

PubMed

Ai, Dexiecuo; Gravel, Dominique; Chu, Chengjin; Wang, Gang

2013-01-01

The correspondence between species distribution and the environment depends on species' ability to track favorable environmental conditions (via dispersal) and to maintain competitive hierarchy against the constant influx of migrants (mass effect) and demographic stochasticity (ecological drift). Here we report a simulation study of the influence of landscape structure on species distribution. We consider lottery competition for space in a spatially heterogeneous environment, where the landscape is represented as a network of localities connected by dispersal. We quantified the contribution of neutrality and species sorting to their spatial distribution. We found that neutrality increases and the strength of species-sorting decreases with the centrality of a community in the landscape when the average dispersal among communities is low, whereas the opposite was found at elevated dispersal. We also found that the strength of species-sorting increases with environmental heterogeneity. Our results illustrate that spatial structure of the environment and of dispersal must be taken into account for understanding species distribution. We stress the importance of spatial geographic structure on the relative importance of niche vs. neutral processes in controlling community dynamics.

Direct numerical solution of the Ornstein-Zernike integral equation and spatial distribution of water around hydrophobic molecules

NASA Astrophysics Data System (ADS)

Ikeguchi, Mitsunori; Doi, Junta

1995-09-01

The Ornstein-Zernike integral equation (OZ equation) has been used to evaluate the distribution function of solvents around solutes, but its numerical solution is difficult for molecules with a complicated shape. This paper proposes a numerical method to directly solve the OZ equation by introducing the 3D lattice. The method employs no approximation the reference interaction site model (RISM) equation employed. The method enables one to obtain the spatial distribution of spherical solvents around solutes with an arbitrary shape. Numerical accuracy is sufficient when the grid-spacing is less than 0.5 Å for solvent water. The spatial water distribution around a propane molecule is demonstrated as an example of a nonspherical hydrophobic molecule using iso-value surfaces. The water model proposed by Pratt and Chandler is used. The distribution agrees with the molecular dynamics simulation. The distribution increases offshore molecular concavities. The spatial distribution of water around 5α-cholest-2-ene (C27H46) is visualized using computer graphics techniques and a similar trend is observed.

Spatial Preference Modelling for equitable infrastructure provision: an application of Sen's Capability Approach

NASA Astrophysics Data System (ADS)

Wismadi, Arif; Zuidgeest, Mark; Brussel, Mark; van Maarseveen, Martin

2014-01-01

To determine whether the inclusion of spatial neighbourhood comparison factors in Preference Modelling allows spatial decision support systems (SDSSs) to better address spatial equity, we introduce Spatial Preference Modelling (SPM). To evaluate the effectiveness of this model in addressing equity, various standardisation functions in both Non-Spatial Preference Modelling and SPM are compared. The evaluation involves applying the model to a resource location-allocation problem for transport infrastructure in the Special Province of Yogyakarta in Indonesia. We apply Amartya Sen's Capability Approach to define opportunity to mobility as a non-income indicator. Using the extended Moran's I interpretation for spatial equity, we evaluate the distribution output regarding, first, `the spatial distribution patterns of priority targeting for allocation' (SPT) and, second, `the effect of new distribution patterns after location-allocation' (ELA). The Moran's I index of the initial map and its comparison with six patterns for SPT as well as ELA consistently indicates that the SPM is more effective for addressing spatial equity. We conclude that the inclusion of spatial neighbourhood comparison factors in Preference Modelling improves the capability of SDSS to address spatial equity. This study thus proposes a new formal method for SDSS with specific attention on resource location-allocation to address spatial equity.

Exploring Spatial and Temporal Distribution of Cutaneous Leishmaniasis in the Americas, 2001–2011

PubMed Central

E. Yadón, Zaida; Idali Saboyá Díaz, Martha; de Fátima de Araújo Lucena, Francisca; Gerardo Castellanos, Luis; J. Sanchez-Vazquez, Manuel

2016-01-01

Leishmaniasis is an important health problem in several countries in the Americas and cases notification is limited and underreported. In 2008, the Pan American Health Organization (PAHO/WHO) met with endemic countries to discuss the status and need of improvement of systems region-wide. The objective is to describe the temporal and spatial distribution of cutaneous leishmaniasis (CL) cases reported to PAHO/WHO by the endemic countries between 2001 and 2011 in the Americas. Methods Cases reported in the period of 2001–2011 from 14/18 CL endemic countries were included in this study by using two spreadsheet to collect the data. Two indicators were analyzed: CL cases and incidence rate. The local regression method was used to analyze case trends and incidence rates for all the studied period, and for 2011 the spatial distribution of each indicator was analyzed by quartile and stratified into four groups. Results From 2001–2011, 636,683 CL cases were reported by 14 countries and with an increase of 30% of the reported cases. The average incidence rate in the Americas was 15.89/100,000 inhabitants. In 2011, 15 countries reported cases in 180 from a total of 292 units of first subnational level. The global incidence rate for all countries was 17.42 cases per 100,000 inhabitants; while in 180 administrative units at the first subnational level, the average incidence rate was 57.52/100,000 inhabitants. Nicaragua and Panama had the highest incidence but more cases occurred in Brazil and Colombia. Spatial distribution was heterogeneous for each indicator, and when analyzed in different administrative level. The results showed different distribution patterns, illustrating the limitation of the use of individual indicators and the need to classify higher-risk areas in order to prioritize the actions. This study shows the epidemiological patterns using secondary data and the importance of using multiple indicators to define and characterize smaller territorial units for surveillance and control of leishmaniasis. PMID:27824881

Individual and Interactive Effects of Socio-Ecological Factors on Dengue Fever at Fine Spatial Scale: A Geographical Detector-Based Analysis

PubMed Central

Li, Xing; Wang, Jin; Lin, Hualiang; Chen, Lingling; Wu, Zhifeng; Ma, Wenjun

2017-01-01

Background: Large spatial heterogeneity was observed in the dengue fever outbreak in Guangzhou in 2014, however, the underlying reasons remain unknown. We examined whether socio-ecological factors affected the spatial distribution and their interactive effects. Methods: Moran’s I was applied to first examine the spatial cluster of dengue fever in Guangzhou. Nine socio-ecological factors were chosen to represent the urbanization level, economy, accessibility, environment, and the weather of the 167 townships/streets in Guangzhou, and then the geographical detector was applied to analyze the individual and interactive effects of these factors on the dengue outbreak. Results: Four clusters of dengue fever were identified in Guangzhou in 2014, including one hot spot in the central area of Guangzhou and three cold spots in the suburban districts. For individual effects, the temperature (q = 0.33) was the dominant factor of dengue fever, followed by precipitation (q = 0.24), road density (q = 0.24), and water body area (q = 0.23). For the interactive effects, the combination of high precipitation, high temperature, and high road density might result in increased dengue fever incidence. Moreover, urban villages might be the dengue fever hot spots. Conclusions: Our study suggests that some socio-ecological factors might either separately or jointly influence the spatial distribution of dengue fever in Guangzhou. PMID:28714925

Subpixel target detection and enhancement in hyperspectral images

NASA Astrophysics Data System (ADS)

Tiwari, K. C.; Arora, M.; Singh, D.

2011-06-01

Hyperspectral data due to its higher information content afforded by higher spectral resolution is increasingly being used for various remote sensing applications including information extraction at subpixel level. There is however usually a lack of matching fine spatial resolution data particularly for target detection applications. Thus, there always exists a tradeoff between the spectral and spatial resolutions due to considerations of type of application, its cost and other associated analytical and computational complexities. Typically whenever an object, either manmade, natural or any ground cover class (called target, endmembers, components or class) gets spectrally resolved but not spatially, mixed pixels in the image result. Thus, numerous manmade and/or natural disparate substances may occur inside such mixed pixels giving rise to mixed pixel classification or subpixel target detection problems. Various spectral unmixing models such as Linear Mixture Modeling (LMM) are in vogue to recover components of a mixed pixel. Spectral unmixing outputs both the endmember spectrum and their corresponding abundance fractions inside the pixel. It, however, does not provide spatial distribution of these abundance fractions within a pixel. This limits the applicability of hyperspectral data for subpixel target detection. In this paper, a new inverse Euclidean distance based super-resolution mapping method has been presented that achieves subpixel target detection in hyperspectral images by adjusting spatial distribution of abundance fraction within a pixel. Results obtained at different resolutions indicate that super-resolution mapping may effectively aid subpixel target detection.

Individual and Interactive Effects of Socio-Ecological Factors on Dengue Fever at Fine Spatial Scale: A Geographical Detector-Based Analysis.

PubMed

Cao, Zheng; Liu, Tao; Li, Xing; Wang, Jin; Lin, Hualiang; Chen, Lingling; Wu, Zhifeng; Ma, Wenjun

2017-07-17

Background : Large spatial heterogeneity was observed in the dengue fever outbreak in Guangzhou in 2014, however, the underlying reasons remain unknown. We examined whether socio-ecological factors affected the spatial distribution and their interactive effects. Methods : Moran's I was applied to first examine the spatial cluster of dengue fever in Guangzhou. Nine socio-ecological factors were chosen to represent the urbanization level, economy, accessibility, environment, and the weather of the 167 townships/streets in Guangzhou, and then the geographical detector was applied to analyze the individual and interactive effects of these factors on the dengue outbreak. Results : Four clusters of dengue fever were identified in Guangzhou in 2014, including one hot spot in the central area of Guangzhou and three cold spots in the suburban districts. For individual effects, the temperature ( q = 0.33) was the dominant factor of dengue fever, followed by precipitation ( q = 0.24), road density ( q = 0.24), and water body area ( q = 0.23). For the interactive effects, the combination of high precipitation, high temperature, and high road density might result in increased dengue fever incidence. Moreover, urban villages might be the dengue fever hot spots. Conclusions : Our study suggests that some socio-ecological factors might either separately or jointly influence the spatial distribution of dengue fever in Guangzhou.

Multiscale spatial and temporal estimation of the b-value

NASA Astrophysics Data System (ADS)

García-Hernández, R.; D'Auria, L.; Barrancos, J.; Padilla, G.

2017-12-01

The estimation of the spatial and temporal variations of the Gutenberg-Richter b-value is of great importance in different seismological applications. One of the problems affecting its estimation is the heterogeneous distribution of the seismicity which makes its estimate strongly dependent upon the selected spatial and/or temporal scale. This is especially important in volcanoes where dense clusters of earthquakes often overlap the background seismicity. Proposed solutions for estimating temporal variations of the b-value include considering equally spaced time intervals or variable intervals having an equal number of earthquakes. Similar approaches have been proposed to image the spatial variations of this parameter as well.We propose a novel multiscale approach, based on the method of Ogata and Katsura (1993), allowing a consistent estimation of the b-value regardless of the considered spatial and/or temporal scales. Our method, named MUST-B (MUltiscale Spatial and Temporal characterization of the B-value), basically consists in computing estimates of the b-value at multiple temporal and spatial scales, extracting for a give spatio-temporal point a statistical estimator of the value, as well as and indication of the characteristic spatio-temporal scale. This approach includes also a consistent estimation of the completeness magnitude (Mc) and of the uncertainties over both b and Mc.We applied this method to example datasets for volcanic (Tenerife, El Hierro) and tectonic areas (Central Italy) as well as an example application at global scale.

The Spatial Distribution of Attention within and across Objects

ERIC Educational Resources Information Center

Hollingworth, Andrew; Maxcey-Richard, Ashleigh M.; Vecera, Shaun P.

2012-01-01

Attention operates to select both spatial locations and perceptual objects. However, the specific mechanism by which attention is oriented to objects is not well understood. We examined the means by which object structure constrains the distribution of spatial attention (i.e., a "grouped array"). Using a modified version of the Egly et…

[Spatial distribution of occupational disease prevalence in Guangzhou and Foshan city by geographic information system].

PubMed

Tan, Q; Tu, H W; Gu, C H; Li, X D; Li, R Z; Wang, M; Chen, S G; Cheng, Y J; Liu, Y M

2017-11-20

Objective: To explore the occupational disease spatial distribution characteristics in Guangzhou and Foshan city in 2006-2013 with Geographic Information System and to provide evidence for making control strategy. Methods: The data on occupational disease diagnosis in Guangzhou and Foshan city from 2006 through 2013 were collected and linked to the digital map at administrative county level with Arc GIS12.0 software for spatial analysis. Results: The maps of occupational disease and Moran's spatial autocor-relation analysis showed that the spatial aggregation existed in Shunde and Nanhai region with Moran's index 1.727, -0.003. Local Moran's I spatial autocorrelation analysis pointed out the "positive high incidence re-gion" and the "negative high incidence region" during 2006~2013. Trend analysis showed that the diagnosis case increased slightly then declined from west to east, increase obviously from north to south, declined from? southwest to northeast, high in the middle and low on both sides in northwest-southeast direction. Conclusions: The occupational disease is obviously geographical distribution in Guangzhou and Foshan city. The corresponding prevention measures should be made according to the geographical distribution.

High-latitude distributions of plasma waves and spatial irregularities from DE 2 alternating current electric field observations

NASA Technical Reports Server (NTRS)

Heppner, J. P.; Liebrecht, M. C.; Maynard, N. C.; Pfaff, R. F.

1993-01-01

The high-latitude spatial distributions of average signal intensities in 12 frequency channels between 4 Hz and 512 kHz as measured by the ac electric field spectrometers on the DE-2 spacecraft are analyzed for 18 mo of measurements. In MLT-INL (magnetic local time-invariant latitude) there are three distinct distributions that can be identified with 4-512 Hz signals from spatial irregularities and Alfven waves, 256-Hz to 4.1-kHz signals from ELF hiss, and 4.1-64 kHz signals from VLF auroral hiss, respectively. Overlap between ELF hiss and spatial irregularity signals occurs in the 256-512 Hz band. VLF hiss signals extend downward in frequency into the 1.0-4.1 kHz band and upward into the frequency range 128-512 kHz. The distinctly different spatial distribution patterns for the three bands, 4-256 Hz, 512-1204 Hz, and 4.1-64 kHz, indicate a lack of any causal relationships between VLF hiss, ELF hiss, and lower-frequency signals from spatial irregularities and Alfven waves.

Spatial analysis of malaria in Anhui province, China

PubMed Central

Zhang, Wenyi; Wang, Liping; Fang, Liqun; Ma, Jiaqi; Xu, Youfu; Jiang, Jiafu; Hui, Fengming; Wang, Jianjun; Liang, Song; Yang, Hong; Cao, Wuchun

2008-01-01

Background Malaria has re-emerged in Anhui Province, China, and this province was the most seriously affected by malaria during 2005–2006. It is necessary to understand the spatial distribution of malaria cases and to identify highly endemic areas for future public health planning and resource allocation in Anhui Province. Methods The annual average incidence at the county level was calculated using malaria cases reported between 2000 and 2006 in Anhui Province. GIS-based spatial analyses were conducted to detect spatial distribution and clustering of malaria incidence at the county level. Results The spatial distribution of malaria cases in Anhui Province from 2000 to 2006 was mapped at the county level to show crude incidence, excess hazard and spatial smoothed incidence. Spatial cluster analysis suggested 10 and 24 counties were at increased risk for malaria (P < 0.001) with the maximum spatial cluster sizes at < 50% and < 25% of the total population, respectively. Conclusion The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit malaria risks and to further identify environmental factors responsible for the re-emerged malaria risks. Future public health planning and resource allocation in Anhui Province should be focused on the maximum spatial cluster region. PMID:18847489

[Natural forming causes of China population distribution].

PubMed

Fang, Yu; Ouyang, Zhi-Yun; Zheng, Hua; Xiao, Yi; Niu, Jun-Feng; Chen, Sheng-Bin; Lu, Fei

2012-12-01

The diverse natural environment in China causes the spatial heterogeneity of China population distribution. It is essential to understand the interrelations between the population distribution pattern and natural environment to enhance the understanding of the man-land relationship and the realization of the sustainable management for the population, resources, and environment. This paper analyzed the China population distribution by adopting the index of population density (PD) in combining with spatial statistic method and Lorenz curve, and discussed the effects of the natural factors on the population distribution and the interrelations between the population distribution and 16 indices including average annual precipitation (AAP), average annual temperature (AAT), average annual sunshine duration (AASD), precipitation variation (PV), temperature variation (TV), sunshine duration variation (SDV), relative humidity (RH), aridity index (AI), warmth index ( WI), > or = 5 degrees C annual accumulated temperature (AACT), average elevation (AE), relative height difference (RHD), surface roughness (SR), water system density (WSD), net primary productivity (NPP), and shortest distance to seashore (SDTS). There existed an obvious aggregation phenomenon in the population distribution in China. The PD was high in east China, medium in central China, and low in west China, presenting an obvious positive spatial association. The PD was significantly positively correlated with WSD, AAT, AAP, NPP, AACT, PV, RH, and WI, and significantly negatively correlated with RHD, AE, SDV, SR, and SDTS. The climate factors (AAT, WI, PV, and NPP), topography factors (SR and RHD), and water system factor (WSD) together determined the basic pattern of the population distribution in China. It was suggested that the monitoring of the eco-environment in the east China of high population density should be strengthened to avoid the eco-environmental degradation due to the expanding population, and the conservation of the eco-environment in the central and west China with vulnerable eco-environment should also be strengthened to enhance the population carrying ability of these regions and to mitigate the eco-environmental pressure in the east China of high population density.

Verifying the Dependence of Fractal Coefficients on Different Spatial Distributions

NASA Astrophysics Data System (ADS)

Gospodinov, Dragomir; Marekova, Elisaveta; Marinov, Alexander

2010-01-01

A fractal distribution requires that the number of objects larger than a specific size r has a power-law dependence on the size N(r) = C/rD∝r-D where D is the fractal dimension. Usually the correlation integral is calculated to estimate the correlation fractal dimension of epicentres. A `box-counting' procedure could also be applied giving the `capacity' fractal dimension. The fractal dimension can be an integer and then it is equivalent to a Euclidean dimension (it is zero of a point, one of a segment, of a square is two and of a cube is three). In general the fractal dimension is not an integer but a fractional dimension and there comes the origin of the term `fractal'. The use of a power-law to statistically describe a set of events or phenomena reveals the lack of a characteristic length scale, that is fractal objects are scale invariant. Scaling invariance and chaotic behavior constitute the base of a lot of natural hazards phenomena. Many studies of earthquakes reveal that their occurrence exhibits scale-invariant properties, so the fractal dimension can characterize them. It has first been confirmed that both aftershock rate decay in time and earthquake size distribution follow a power law. Recently many other earthquake distributions have been found to be scale-invariant. The spatial distribution of both regional seismicity and aftershocks show some fractal features. Earthquake spatial distributions are considered fractal, but indirectly. There are two possible models, which result in fractal earthquake distributions. The first model considers that a fractal distribution of faults leads to a fractal distribution of earthquakes, because each earthquake is characteristic of the fault on which it occurs. The second assumes that each fault has a fractal distribution of earthquakes. Observations strongly favour the first hypothesis. The fractal coefficients analysis provides some important advantages in examining earthquake spatial distribution, which are:—Simple way to quantify scale-invariant distributions of complex objects or phenomena by a small number of parameters.—It is becoming evident that the applicability of fractal distributions to geological problems could have a more fundamental basis. Chaotic behaviour could underlay the geotectonic processes and the applicable statistics could often be fractal. The application of fractal distribution analysis has, however, some specific aspects. It is usually difficult to present an adequate interpretation of the obtained values of fractal coefficients for earthquake epicenter or hypocenter distributions. That is why in this paper we aimed at other goals—to verify how a fractal coefficient depends on different spatial distributions. We simulated earthquake spatial data by generating randomly points first in a 3D space - cube, then in a parallelepiped, diminishing one of its sides. We then continued this procedure in 2D and 1D space. For each simulated data set we calculated the points' fractal coefficient (correlation fractal dimension of epicentres) and then checked for correlation between the coefficients values and the type of spatial distribution. In that way one can obtain a set of standard fractal coefficients' values for varying spatial distributions. These then can be used when real earthquake data is analyzed by comparing the real data coefficients values to the standard fractal coefficients. Such an approach can help in interpreting the fractal analysis results through different types of spatial distributions.

Design and implementation of a scene-dependent dynamically selfadaptable wavefront coding imaging system

NASA Astrophysics Data System (ADS)

Carles, Guillem; Ferran, Carme; Carnicer, Artur; Bosch, Salvador

2012-01-01

A computational imaging system based on wavefront coding is presented. Wavefront coding provides an extension of the depth-of-field at the expense of a slight reduction of image quality. This trade-off results from the amount of coding used. By using spatial light modulators, a flexible coding is achieved which permits it to be increased or decreased as needed. In this paper a computational method is proposed for evaluating the output of a wavefront coding imaging system equipped with a spatial light modulator, with the aim of thus making it possible to implement the most suitable coding strength for a given scene. This is achieved in an unsupervised manner, thus the whole system acts as a dynamically selfadaptable imaging system. The program presented here controls the spatial light modulator and the camera, and also processes the images in a synchronised way in order to implement the dynamic system in real time. A prototype of the system was implemented in the laboratory and illustrative examples of the performance are reported in this paper. Program summaryProgram title: DynWFC (Dynamic WaveFront Coding) Catalogue identifier: AEKC_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKC_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 10 483 No. of bytes in distributed program, including test data, etc.: 2 437 713 Distribution format: tar.gz Programming language: Labview 8.5 and NI Vision and MinGW C Compiler Computer: Tested on PC Intel ® Pentium ® Operating system: Tested on Windows XP Classification: 18 Nature of problem: The program implements an enhanced wavefront coding imaging system able to adapt the degree of coding to the requirements of a specific scene. The program controls the acquisition by a camera, the display of a spatial light modulator and the image processing operations synchronously. The spatial light modulator is used to implement the phase mask with flexibility given the trade-off between depth-of-field extension and image quality achieved. The action of the program is to evaluate the depth-of-field requirements of the specific scene and subsequently control the coding established by the spatial light modulator, in real time.

A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

USGS Publications Warehouse

Irvine, Kathryn M.; Thornton, Jamie; Backus, Vickie M.; Hohmann, Matthew G.; Lehnhoff, Erik A.; Maxwell, Bruce D.; Michels, Kurt; Rew, Lisa

2013-01-01

Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

Projecting Future Urbanization with Prescott College's Spatial Growth Model to Promote Environmental Sustainability and Smart Growth, A Case Study in Atlanta, Georgia

NASA Technical Reports Server (NTRS)

Estes, Maurice G., Jr.; Crosson, William; Limaye, Ashutosh; Johnson, Hoyt; Quattrochi, Dale; Lapenta, William; Khan, Maudood

2006-01-01

Planning is an integral element of good management and necessary to anticipate events not merely respond to them. Projecting the quantity and spatial distribution of urban growth is essential to effectively plan for the delivery of city services and to evaluate potential environmental impacts. The major drivers of growth in large urban areas are increasing population, employment opportunities, and quality of life attractors such as a favorable climate and recreation opportunities. The spatial distribution of urban growth is dictated by the amount and location of developable land, topography, energy and water resources, transportation network, climate change, and the existing land use configuration. The Atlanta region is growing very rapidly both in population and the consumption of forestland or low-density residential development. Air pollution and water availability are significant ongoing environmental issues. The Prescott Spatial Growth Model (SGM) was used to make growth projections for the metropolitan Atlanta region to 2010,2020 and 2030 and results used for environmental assessment in both business as usual and smart growth scenarios. The Prescott SGM is a tool that uses an ESRI ArcView extension and can be applied at the parcel level or more coarse spatial scales and can accommodate a wide range of user inputs to develop any number of growth rules each of which can be weighted depending on growth assumptions. These projections were used in conjunction with meteorological and air quality models to evaluate future environmental impacts. This presentation will focus on the application of the SGM to the 13-County Atlanta Regional Commission planning jurisdiction as a case study. The SGM will be described, including how rule sets are developed and the decision process for allocation of future development to available land use categories. Data inputs required to effectively run the model will be discussed. Spatial growth projections for ten, twenty, and thirty year planning horizons will be presented and results discussed, including regional climate and air quality impacts.

Image processing techniques revealing the relationship between the field-measured ambient gamma dose equivalent rate and geological conditions at a granitic area, Velence Mountains, Hungary

NASA Astrophysics Data System (ADS)

Beltran Torres, Silvana; Petrik, Attila; Zsuzsanna Szabó, Katalin; Jordan, Gyozo; Szabó, Csaba

2017-04-01

In order to estimate the annual dose that the public receive from natural radioactivity, the identification of the potential risk areas is required which, in turn, necessitates understanding the relationship between the spatial distribution of natural radioactivity and the geogenic risk factors (e.g., rock types, dykes, faults, soil conditions, etc.). A detailed spatial analysis of ambient gamma dose equivalent rate was performed in the western side of Velence Mountains, the largest outcropped granitic area in Hungary. In order to assess the role of local geology in the spatial distribution of ambient gamma dose rates, field measurements were carried out at ground level at 300 sites along a 250 m x 250 m regular grid in a total surface of 14.7 km2. Digital image processing methods were applied to identify anomalies, heterogeneities and spatial patterns in the measured gamma dose rates, including local maxima and minima determination, digital cross sections, gradient magnitude and gradient direction, second derivative profile curvature, local variability, lineament density, 2D autocorrelation and directional variogram analyses. Statistical inference showed that different gamma dose rate levels are associated with the rock types (i.e., Carboniferous granite, Pleistocene colluvial, proluvial, deluvial sediments and talus, and Pannonian sand and pebble), with the highest level on the Carboniferous granite including outlying values. Moreover, digital image processing revealed that linear gamma dose rate spatial features are parallel to the SW-NE dyke system and possibly to the NW-SE main fractures. The results of this study underline the importance of understanding the role of geogenic risk factors influencing the ambient gamma dose rate received by public. The study also demonstrates the power of the image processing techniques for the identification of spatial pattern in field-measured geogenic radiation.

Explaining variation in tropical plant community composition: influence of environmental and spatial data quality.

PubMed

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.

Bayesian spatial transformation models with applications in neuroimaging data.

PubMed

Miranda, Michelle F; Zhu, Hongtu; Ibrahim, Joseph G

2013-12-01

The aim of this article is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. The proposed STM include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov random field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. © 2013, The International Biometric Society.

Effect of the corrected ionization potential and spatial distribution on the angular and energy distribution in tunnel ionization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrović, V. M.; Miladinović, T. B., E-mail: tanja.miladinovic@gmail.com

2016-05-15

Within the framework of the Ammosov–Delone–Krainov theory, we consider the angular and energy distribution of outgoing electrons due to ionization by a circularly polarized electromagnetic field. A correction of the ground ionization potential by the ponderomotive and Stark shift is incorporated in both distributions. Spatial dependence is analyzed.

Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.

PubMed

Li, Mingming; Zhang, Xingchang; Zhen, Qing; Han, Fengpeng

2013-01-01

Soil organic carbon (SOC) reflects soil quality and plays a critical role in soil protection, food safety, and global climate changes. This study involved grid sampling at different depths (6 layers) between 0 and 100 cm in a catchment. A total of 1282 soil samples were collected from 215 plots over 8.27 km(2). A combination of conventional analytical methods and geostatistical methods were used to analyze the data for spatial variability and soil carbon content patterns. The mean SOC content in the 1282 samples from the study field was 3.08 g · kg(-1). The SOC content of each layer decreased with increasing soil depth by a power function relationship. The SOC content of each layer was moderately variable and followed a lognormal distribution. The semi-variograms of the SOC contents of the six different layers were fit with the following models: exponential, spherical, exponential, Gaussian, exponential, and exponential, respectively. A moderate spatial dependence was observed in the 0-10 and 10-20 cm layers, which resulted from stochastic and structural factors. The spatial distribution of SOC content in the four layers between 20 and 100 cm exhibit were mainly restricted by structural factors. Correlations within each layer were observed between 234 and 562 m. A classical Kriging interpolation was used to directly visualize the spatial distribution of SOC in the catchment. The variability in spatial distribution was related to topography, land use type, and human activity. Finally, the vertical distribution of SOC decreased. Our results suggest that the ordinary Kriging interpolation can directly reveal the spatial distribution of SOC and the sample distance about this study is sufficient for interpolation or plotting. More research is needed, however, to clarify the spatial variability on the bigger scale and better understand the factors controlling spatial variability of soil carbon in the Loess Plateau region.

Cluster analysis for determining distribution center location

NASA Astrophysics Data System (ADS)

Lestari Widaningrum, Dyah; Andika, Aditya; Murphiyanto, Richard Dimas Julian

2017-12-01

Determination of distribution facilities is highly important to survive in the high level of competition in today’s business world. Companies can operate multiple distribution centers to mitigate supply chain risk. Thus, new problems arise, namely how many and where the facilities should be provided. This study examines a fast-food restaurant brand, which located in the Greater Jakarta. This brand is included in the category of top 5 fast food restaurant chain based on retail sales. There were three stages in this study, compiling spatial data, cluster analysis, and network analysis. Cluster analysis results are used to consider the location of the additional distribution center. Network analysis results show a more efficient process referring to a shorter distance to the distribution process.

Spatial Distribution of Cyanobacteria in Modern Stromatolites

NASA Technical Reports Server (NTRS)

Prufert-Bebout, Lee; Dacles-Mariani, Jennifer; Herbert, Alice; DeVincenzi, Donald (Technical Monitor)

2001-01-01

Living stromatolites consist of complex microbial communities with distinct distribution patterns for different microbial groups. The cyanobacterial populations of Highborne Cay Bahamas exemplify this phenomenon. Field observations reveal distinct distribution patterns for several of these cyanobacterial species. To date 10 different cyanobacterial cultures, including both filamentous and endolithic species, have been isolated from these stromatolites. We will present data on the growth and motility characteristics as well as on the nutritional requirements of these isolates. These data will then be correlated with the field observed distributions for these species. Lastly laboratory simulations of stromatolites grown under various conditions of irradiance, flow and cyanobacterial community composition will be presented. These experiments allow us to evaluate our predictions regarding controls on cyanobacterial distribution.

Spatially distributed multipartite entanglement enables EPR steering of atomic clouds.

PubMed

Kunkel, Philipp; Prüfer, Maximilian; Strobel, Helmut; Linnemann, Daniel; Frölian, Anika; Gasenzer, Thomas; Gärttner, Martin; Oberthaler, Markus K

2018-04-27

A key resource for distributed quantum-enhanced protocols is entanglement between spatially separated modes. However, the robust generation and detection of entanglement between spatially separated regions of an ultracold atomic system remain a challenge. We used spin mixing in a tightly confined Bose-Einstein condensate to generate an entangled state of indistinguishable particles in a single spatial mode. We show experimentally that this entanglement can be spatially distributed by self-similar expansion of the atomic cloud. We used spatially resolved spin read-out to reveal a particularly strong form of quantum correlations known as Einstein-Podolsky-Rosen (EPR) steering between distinct parts of the expanded cloud. Based on the strength of EPR steering, we constructed a witness, which confirmed genuine 5-partite entanglement. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Arc_Mat: a Matlab-based spatial data analysis toolbox

NASA Astrophysics Data System (ADS)

Liu, Xingjian; Lesage, James

2010-03-01

This article presents an overview of Arc_Mat, a Matlab-based spatial data analysis software package whose source code has been placed in the public domain. An earlier version of the Arc_Mat toolbox was developed to extract map polygon and database information from ESRI shapefiles and provide high quality mapping in the Matlab software environment. We discuss revisions to the toolbox that: utilize enhanced computing and graphing capabilities of more recent versions of Matlab, restructure the toolbox with object-oriented programming features, and provide more comprehensive functions for spatial data analysis. The Arc_Mat toolbox functionality includes basic choropleth mapping; exploratory spatial data analysis that provides exploratory views of spatial data through various graphs, for example, histogram, Moran scatterplot, three-dimensional scatterplot, density distribution plot, and parallel coordinate plots; and more formal spatial data modeling that draws on the extensive Spatial Econometrics Toolbox functions. A brief review of the design aspects of the revised Arc_Mat is described, and we provide some illustrative examples that highlight representative uses of the toolbox. Finally, we discuss programming with and customizing the Arc_Mat toolbox functionalities.

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir.

PubMed

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-09-23

The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies.

Linking movement and oviposition behaviour to spatial population distribution in the tree hole mosquito Ochlerotatus triseriatus.

PubMed

Ellis, Alicia M

2008-01-01

1. Researchers often use the spatial distribution of insect offspring as a measure of adult oviposition preferences, and then make conclusions about the consequences of these preferences for population growth and the relationship between life-history traits (e.g. oviposition preference and offspring performance). However, several processes other than oviposition preference can generate spatial patterns of offspring density (e.g. dispersal limitations, spatially heterogeneous mortality rates). Incorrectly assuming that offspring distributions reflect oviposition preferences may therefore compromise our ability to understand the mechanisms determining population distributions and the relationship between life-history traits. 2. The purpose of this study was to perform an empirical study at the whole-system scale to examine the movement and oviposition behaviours of the eastern tree hole mosquito Ochlerotatus triseriatus (Say) and test the importance of these behaviours in determining population distribution relative to other mechanisms. 3. A mark-release-recapture experiment was performed to distinguish among the following alternative hypotheses that may explain a previously observed aggregated distribution of tree hole mosquito offspring: (H(1)) mosquitoes prefer habitats with particular vegetation characteristics and these preferences determine the distribution of their offspring; (H(2)) mosquitoes distribute their eggs randomly or evenly throughout their environment, but spatial differences in developmental success generate an aggregated pattern of larval density; (H(3)) mosquitoes randomly colonize habitats, but have limited dispersal capability causing them to distribute offspring where founder populations were established; (H(4)) wind or other environmental factors may lead to passive aggregation, or spatial heterogeneity in adult mortality (H(5)), rather than dispersal, generates clumped offspring distributions. 4. Results indicate that the distribution of tree hole mosquito larvae is determined in part by adult habitat selection (H(1)), but do not exclude additional effects from passive aggregation (H(4)), or spatial patterns in adult mortality (H(5)). 5. This research illustrates the importance of studying oviposition behaviour at the population scale to better evaluate its relative importance in determining population distribution and dynamics. Moreover, this study demonstrates the importance of linking behavioural and population dynamics for understanding evolutionary relationships among life-history traits (e.g. preference and offspring performance) and predicting when behaviour will be important in determining population phenomena.

The Review of Nuclear Microscopy Techniques: An Approach for Nondestructive Trace Elemental Analysis and Mapping of Biological Materials.

PubMed

Mulware, Stephen Juma

2015-01-01

The properties of many biological materials often depend on the spatial distribution and concentration of the trace elements present in a matrix. Scientists have over the years tried various techniques including classical physical and chemical analyzing techniques each with relative level of accuracy. However, with the development of spatially sensitive submicron beams, the nuclear microprobe techniques using focused proton beams for the elemental analysis of biological materials have yielded significant success. In this paper, the basic principles of the commonly used microprobe techniques of STIM, RBS, and PIXE for trace elemental analysis are discussed. The details for sample preparation, the detection, and data collection and analysis are discussed. Finally, an application of the techniques to analysis of corn roots for elemental distribution and concentration is presented.

Far-infrared, submillimeter, and millimeter spectroscopy of the Galactic center - Radio ARC and +20/+50 kilometer per second clouds

NASA Technical Reports Server (NTRS)

Genzel, R.; Harris, A. I.; Geis, N.; Stacey, G. J.; Townes, C. H.

1990-01-01

Results are presented from FIR, sub-mm, and mm spectroscopic observations of the radio arc and the +20/+50 km/s molecular clouds in the Galactic center. The results for the radio arc are analyzed, including the spatial distribution of C II forbidden line emission, the spatial distribution of CO emission, the luminosity and mass of C(+) regions, and the CO 7 - 6 emission and line profiles. Model calculations are used to study molecular gas in the radio arc. In addition, forbidden C II, CO 7 - 6, and C(O-18) mapping is presented for the +20/+50 km/x clouds. Consideration is given to the impact of the results on the interpretation of the physical conditions, excitation, and heating of the gas clouds in the arc and near the center.

Dataset on spatial distribution and location of universities in Nigeria.

PubMed

Adeyemi, G A; Edeki, S O

2018-06-01

Access to quality educational system, and the location of educational institutions are of great importance for future prospect of youth in any nation. These in return, have great effects on the economy growth and development of any country. Thus, the dataset contained in this article examines and explains the spatial distribution of universities in the Nigeria system of education. Data from the university commission, Nigeria, as at December 2017 are used. These include all the 40 federal universities, 44 states universities, and 69 private universities making a total of 153 universities in the Nigerian system of education. The data analysis is via the Geographic Information System (GIS) software. The dataset contained in this article will be of immense assistance to the national educational policy makers, parents, and potential students as regards smart and reliable decision making academically.

[Spatial structure analysis and distribution simulation of Therioaphis trifolii population based on geostatistics and GIS].

PubMed

Zhang, Rong; Leng, Yun-fa; Zhu, Meng-meng; Wang, Fang

2007-11-01

Based on geographic information system and geostatistics, the spatial structure of Therioaphis trifolii population of different periods in Yuanzhou district of Guyuan City, the southern Ningxia Province, was analyzed. The spatial distribution of Therioaphis trifolii population was also simulated by ordinary Kriging interpretation. The results showed that Therioaphis trifolii population of different periods was correlated spatially in the study area. The semivariograms of Therioaphis trifolii could be described by exponential model, indicating an aggregated spatial arrangement. The spatial variance varied from 34.13%-48.77%, and the range varied from 8.751-12.049 km. The degree and direction of aggregation showed that the trend was increased gradually from southwest to northeast. The dynamic change of Therioaphis trifolii population in different periods could be analyzed intuitively on the simulated maps of the spatial distribution from the two aspects of time and space, The occurrence position and degree of Therioaphis trifolii to a state of certain time could be determined easily.

Self-organization of the magnetization in ferromagnetic nanowires

NASA Astrophysics Data System (ADS)

Ivanov, A. A.; Orlov, V. A.

2017-10-01

In this work we demonstrate the occurrence of the characteristic spatial scale in the distribution of magnetization unrelated to the domain wall or crystallite size with using computer simulation of magnetization in a polycrystalline ferromagnetic nanowire. This is the stochastic domain size. We show that this length is included in the spectral density of the pinning force of domain wall on inhomogeneities of the crystallographic anisotropy. The constant and distribution of easy axes directions of the effective anisotropy of stochastic domain, are analytically calculated.

Topographic controls on soil nutrient variations in a Silvopasture system

USDA-ARS?s Scientific Manuscript database

Topography plays a crucial role in the spatial distribution of nutrients in soils because of its influence on the flow and (re)distribution of water and energy in a landscape. Information on the spatial pattern of soil nutrient distribution would benefit management decisions to maximize crop yield a...

Exploring Spatial and Temporal Distribution of Cutaneous Leishmaniasis in the Americas, 2001-2011.

PubMed

Maia-Elkhoury, Ana Nilce Silveira; E Yadón, Zaida; Idali Saboyá Díaz, Martha; de Fátima de Araújo Lucena, Francisca; Gerardo Castellanos, Luis; J Sanchez-Vazquez, Manuel

2016-11-01

Cases reported in the period of 2001-2011 from 14/18 CL endemic countries were included in this study by using two spreadsheet to collect the data. Two indicators were analyzed: CL cases and incidence rate. The local regression method was used to analyze case trends and incidence rates for all the studied period, and for 2011 the spatial distribution of each indicator was analyzed by quartile and stratified into four groups. From 2001-2011, 636,683 CL cases were reported by 14 countries and with an increase of 30% of the reported cases. The average incidence rate in the Americas was 15.89/100,000 inhabitants. In 2011, 15 countries reported cases in 180 from a total of 292 units of first subnational level. The global incidence rate for all countries was 17.42 cases per 100,000 inhabitants; while in 180 administrative units at the first subnational level, the average incidence rate was 57.52/100,000 inhabitants. Nicaragua and Panama had the highest incidence but more cases occurred in Brazil and Colombia. Spatial distribution was heterogeneous for each indicator, and when analyzed in different administrative level. The results showed different distribution patterns, illustrating the limitation of the use of individual indicators and the need to classify higher-risk areas in order to prioritize the actions. This study shows the epidemiological patterns using secondary data and the importance of using multiple indicators to define and characterize smaller territorial units for surveillance and control of leishmaniasis.

Spatially Fourier-encoded photoacoustic microscopy using a digital micromirror device.

PubMed

Liang, Jinyang; Gao, Liang; Li, Chiye; Wang, Lihong V

2014-02-01

We have developed spatially Fourier-encoded photoacoustic (PA) microscopy using a digital micromirror device. The spatial intensity distribution of laser pulses is Fourier-encoded, and a series of such encoded PA measurements allows one to decode the spatial distribution of optical absorption. The throughput and Fellgett advantages were demonstrated by imaging a chromium target. By using 63 spatial elements, the signal-to-noise ratio in the recovered PA signal was enhanced by ∼4×. The system was used to image two biological targets, a monolayer of red blood cells and melanoma cells.

Spatially Fourier-encoded photoacoustic microscopy using a digital micromirror device

PubMed Central

Liang, Jinyang; Gao, Liang; Li, Chiye; Wang, Lihong V.

2014-01-01

We have developed spatially Fourier-encoded photoacoustic microscopy using a digital micromirror device. The spatial intensity distribution of laser pulses is Fourier-encoded, and a series of such encoded photoacoustic measurements allows one to decode the spatial distribution of optical absorption. The throughput and Fellgett advantages were demonstrated by imaging a chromium target. By using 63 spatial elements, the signal-to-noise ratio in the recovered photoacoustic signal was enhanced by ~4×. The system was used to image two biological targets, a monolayer of red blood cells and melanoma cells. PMID:24487832

A Global Survey of Cloud Thermodynamic Phase using High Spatial Resolution VSWIR Spectroscopy, 2005-2015

NASA Astrophysics Data System (ADS)

Thompson, D. R.; Kahn, B. H.; Green, R. O.; Chien, S.; Middleton, E.; Tran, D. Q.

2017-12-01

Clouds' variable ice and liquid content significantly influences their optical properties, evolution, and radiative forcing potential (Tan and Storelvmo, J. Atmos. Sci, 73, 2016). However, most remote measurements of thermodynamic phase have spatial resolutions of 1 km or more and are insensitive to mixed phases. This under-constrains important processes, such as spatial partitioning within mixed phase clouds, that carry outsize radiative forcing impacts. These uncertainties could shift Global Climate Model (GCM) predictions of future warming by over 1 degree Celsius (Tan et al., Science 352:6282, 2016). Imaging spectroscopy of reflected solar energy from the 1.4 - 1.8 μm shortwave infrared (SWIR) spectral range can address this observational gap. These observations can distinguish ice and water absorption, providing a robust and sensitive measurement of cloud top thermodynamic phase including mixed phases. Imaging spectrometers can resolve variations at scales of tens to hundreds of meters (Thompson et al., JGR-Atmospheres 121, 2016). We report the first such global high spatial resolution (30 m) survey, based on data from 2005-2015 acquired by the Hyperion imaging spectrometer onboard NASA's EO-1 spacecraft (Pearlman et al., Proc. SPIE 4135, 2001). Estimated seasonal and latitudinal distributions of cloud thermodynamic phase generally agree with observations made by other satellites such as the Atmospheric Infrared Sounder (AIRS). Variogram analyses reveal variability at different spatial scales. Our results corroborate previously observed zonal distributions, while adding insight into the spatial scales of processes governing cloud top thermodynamic phase. Figure: Thermodynamic phase retrievals. Top: Example of a cloud top thermodynamic phase map from the EO-1/Hyperion. Bottom: Latitudinal distributions of pure and mixed phase clouds, 2005-2015, showing Liquid Thickness Fraction (LTF). LTF=0 corresponds to pure ice absorption, while LTF=1 is pure liquid. The archive contains over 45,000 scenes. Copyright 2017, California Institute of Technology. Government Support Acknowledged.