Spatial effects, sampling errors, and task specialization in the honey bee.

PubMed

Johnson, B R

2010-05-01

Task allocation patterns should depend on the spatial distribution of work within the nest, variation in task demand, and the movement patterns of workers, however, relatively little research has focused on these topics. This study uses a spatially explicit agent based model to determine whether such factors alone can generate biases in task performance at the individual level in the honey bees, Apis mellifera. Specialization (bias in task performance) is shown to result from strong sampling error due to localized task demand, relatively slow moving workers relative to nest size, and strong spatial variation in task demand. To date, specialization has been primarily interpreted with the response threshold concept, which is focused on intrinsic (typically genotypic) differences between workers. Response threshold variation and sampling error due to spatial effects are not mutually exclusive, however, and this study suggests that both contribute to patterns of task bias at the individual level. While spatial effects are strong enough to explain some documented cases of specialization; they are relatively short term and not explanatory for long term cases of specialization. In general, this study suggests that the spatial layout of tasks and fluctuations in their demand must be explicitly controlled for in studies focused on identifying genotypic specialists.

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.

Coherent optical adaptive technique improves the spatial resolution of STED microscopy in thick samples

PubMed Central

Yan, Wei; Yang, Yanlong; Tan, Yu; Chen, Xun; Li, Yang; Qu, Junle; Ye, Tong

2018-01-01

Stimulated emission depletion microscopy (STED) is one of far-field optical microscopy techniques that can provide sub-diffraction spatial resolution. The spatial resolution of the STED microscopy is determined by the specially engineered beam profile of the depletion beam and its power. However, the beam profile of the depletion beam may be distorted due to aberrations of optical systems and inhomogeneity of specimens’ optical properties, resulting in a compromised spatial resolution. The situation gets deteriorated when thick samples are imaged. In the worst case, the sever distortion of the depletion beam profile may cause complete loss of the super resolution effect no matter how much depletion power is applied to specimens. Previously several adaptive optics approaches have been explored to compensate aberrations of systems and specimens. However, it is hard to correct the complicated high-order optical aberrations of specimens. In this report, we demonstrate that the complicated distorted wavefront from a thick phantom sample can be measured by using the coherent optical adaptive technique (COAT). The full correction can effectively maintain and improve the spatial resolution in imaging thick samples. PMID:29400356

Joint Effect of Habitat Identity and Spatial Distance on Spiders' Community Similarity in a Fragmented Transition Zone.

PubMed

Gavish, Yoni; Ziv, Yaron

2016-01-01

Understanding the main processes that affect community similarity have been the focus of much ecological research. However, the relative effects of environmental and spatial aspects in structuring ecological communities is still unresolved and is probably scale-dependent. Here, we examine the effect of habitat identity and spatial distance on fine-grained community similarity within a biogeographic transition zone. We compared four hypotheses: i) habitat identity alone, ii) spatial proximity alone, iii) non-interactive effects of both habitat identity and spatial proximity, and iv) interactive effect of habitat identity and spatial proximity. We explored these hypotheses for spiders in three fragmented landscapes located along the sharp climatic gradient of Southern Judea Lowlands (SJL), Israel. We sampled 14,854 spiders (from 199 species or morphospecies) in 644 samples, taken in 35 patches and stratified to nine different habitats. We calculated the Bray-Curtis similarity between all samples-pairs. We divided the pairwise values to four functional distance categories (same patch, different patches from the same landscape, adjacent landscapes and distant landscapes) and two habitat categories (same or different habitats) and compared them using non-parametric MANOVA. A significant interaction between habitat identity and spatial distance was found, such that the difference in mean similarity between same-habitat pairs and different-habitat pairs decreases with spatial distance. Additionally, community similarity decayed with spatial distance. Furthermore, at all distances, same-habitat pairs had higher similarity than different-habitats pairs. Our results support the fourth hypothesis of interactive effect of habitat identity and spatial proximity. We suggest that the environmental complexity of habitats or increased habitat specificity of species near the edge of their distribution range may explain this pattern. Thus, in transitions zones care should be taken when using habitats as surrogate of community composition in conservation planning since similar habitats in different locations are more likely to support different communities.

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.

On the Effect of Preferential Sampling in Spatial Prediction

EPA Science Inventory

The choice of the sampling locations in a spatial network is often guided by practical demands. In particular, typically, locations are preferentially chosen to capture high values of a response, for example, air pollution levels in environmental monitoring. Then, model estimatio...

The effect of childhood trauma on spatial cognition in adults: a possible role of sex.

PubMed

Syal, Supriya; Ipser, Jonathan; Phillips, Nicole; Thomas, Kevin G F; van der Honk, Jack; Stein, Dan J

2014-06-01

Although animal evidence indicates that early life trauma results in pervasive hippocampal deficits underlying spatial and cognitive impairment, visuo-spatial data from adult humans with early childhood adversity are lacking. We administered 4 tests of visuo-spatial ability from the Cambridge Neuorpsychological Test Automated Battery (CANTAB) to adults with a history of childhood trauma (measured by the Childhood Trauma Questionnaire) and a matched sample of healthy controls (trauma/control = 27/28). We observed a significant effect of trauma history on spatial/pattern learning. These effects could not be accounted for by adverse adult experiences, and were sex-specific, with prior adversity improving performance in men but worsening performance in women, relative to controls. Limitations include the small sample size and reliance of our study design on a retrospective, self report measure. Our results suggest that early adversity can lead to specific and pervasive deficits in adult cognitive function.

Investigating Effect of Origami-Based Instruction on Elementary Students' Spatial Skills and Perceptions

ERIC Educational Resources Information Center

Cakmak, Sedanur; Isiksal, Mine; Koc, Yusuf

2014-01-01

The authors' purpose was to investigate the effect of origami-based instruction on elementary students' spatial ability. The students' self-reported perceptions related to the origami-based instruction were also examined. Data was collected via purposive sampling techniques from students enrolled in a private elementary school. A spatial ability…

Effect of different sampling schemes on the spatial placement of conservation reserves in Utah, USA

USGS Publications Warehouse

Bassett, S.D.; Edwards, T.C.

2003-01-01

We evaluated the effect of three different sampling schemes used to organize spatially explicit biological information had on the spatial placement of conservation reserves in Utah, USA. The three sampling schemes consisted of a hexagon representation developed by the EPA/EMAP program (statistical basis), watershed boundaries (ecological), and the current county boundaries of Utah (socio-political). Four decision criteria were used to estimate effects, including amount of area, length of edge, lowest number of contiguous reserves, and greatest number of terrestrial vertebrate species covered. A fifth evaluation criterion was the effect each sampling scheme had on the ability of the modeled conservation reserves to cover the six major ecoregions found in Utah. Of the three sampling schemes, county boundaries covered the greatest number of species, but also created the longest length of edge and greatest number of reserves. Watersheds maximized species coverage using the least amount of area. Hexagons and watersheds provide the least amount of edge and fewest number of reserves. Although there were differences in area, edge and number of reserves among the sampling schemes, all three schemes covered all the major ecoregions in Utah and their inclusive biodiversity. ?? 2003 Elsevier Science Ltd. All rights reserved.

A spatial model of bird abundance as adjusted for detection probability

USGS Publications Warehouse

Gorresen, P.M.; Mcmillan, G.P.; Camp, R.J.; Pratt, T.K.

2009-01-01

Modeling the spatial distribution of animals can be complicated by spatial and temporal effects (i.e. spatial autocorrelation and trends in abundance over time) and other factors such as imperfect detection probabilities and observation-related nuisance variables. Recent advances in modeling have demonstrated various approaches that handle most of these factors but which require a degree of sampling effort (e.g. replication) not available to many field studies. We present a two-step approach that addresses these challenges to spatially model species abundance. Habitat, spatial and temporal variables were handled with a Bayesian approach which facilitated modeling hierarchically structured data. Predicted abundance was subsequently adjusted to account for imperfect detection and the area effectively sampled for each species. We provide examples of our modeling approach for two endemic Hawaiian nectarivorous honeycreepers: 'i'iwi Vestiaria coccinea and 'apapane Himatione sanguinea. ?? 2009 Ecography.

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

Treesearch

Erin L. Landguth; Bradley C. Fedy; Sara J. Oyler-McCance; Andrew L. Garey; Sarah L. Emel; Matthew Mumma; Helene H. Wagner; Marie-Josee Fortin; Samuel A. Cushman

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population...

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 sampling considerations of the CERES (Clouds and Earth Radiant Energy System) instrument

NASA Astrophysics Data System (ADS)

Smith, G. L.; Manalo-Smith, Natividdad; Priestley, Kory

2014-10-01

The CERES (Clouds and Earth Radiant Energy System) instrument is a scanning radiometer with three channels for measuring Earth radiation budget. At present CERES models are operating aboard the Terra, Aqua and Suomi/NPP spacecraft and flights of CERES instruments are planned for the JPSS-1 spacecraft and its successors. CERES scans from one limb of the Earth to the other and back. The footprint size grows with distance from nadir simply due to geometry so that the size of the smallest features which can be resolved from the data increases and spatial sampling errors increase with nadir angle. This paper presents an analysis of the effect of nadir angle on spatial sampling errors of the CERES instrument. The analysis performed in the Fourier domain. Spatial sampling errors are created by smoothing of features which are the size of the footprint and smaller, or blurring, and inadequate sampling, that causes aliasing errors. These spatial sampling errors are computed in terms of the system transfer function, which is the Fourier transform of the point response function, the spacing of data points and the spatial spectrum of the radiance field.

Spatial Abilities across the Adult Life Span

ERIC Educational Resources Information Center

Borella, Erika; Meneghetti, Chiara; Ronconi, Lucia; De Beni, Rossana

2014-01-01

The study investigates age-related effects across the adult life span on spatial abilities (testing subabilities based on a distinction between spatial visualization, mental rotation, and perspective taking) and spatial self-assessments. The sample consisted of 454 participants (223 women and 231 men) from 20 to 91 years of age. Results showed…

Spatial design and strength of spatial signal: Effects on covariance estimation

USGS Publications Warehouse

Irvine, Kathryn M.; Gitelman, Alix I.; Hoeting, Jennifer A.

2007-01-01

In a spatial regression context, scientists are often interested in a physical interpretation of components of the parametric covariance function. For example, spatial covariance parameter estimates in ecological settings have been interpreted to describe spatial heterogeneity or “patchiness” in a landscape that cannot be explained by measured covariates. In this article, we investigate the influence of the strength of spatial dependence on maximum likelihood (ML) and restricted maximum likelihood (REML) estimates of covariance parameters in an exponential-with-nugget model, and we also examine these influences under different sampling designs—specifically, lattice designs and more realistic random and cluster designs—at differing intensities of sampling (n=144 and 361). We find that neither ML nor REML estimates perform well when the range parameter and/or the nugget-to-sill ratio is large—ML tends to underestimate the autocorrelation function and REML produces highly variable estimates of the autocorrelation function. The best estimates of both the covariance parameters and the autocorrelation function come under the cluster sampling design and large sample sizes. As a motivating example, we consider a spatial model for stream sulfate concentration.

A method to estimate the effect of deformable image registration uncertainties on daily dose mapping

PubMed Central

Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin

2012-01-01

Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties. PMID:22320766

Estimating abundance of mountain lions from unstructured spatial sampling

USGS Publications Warehouse

Russell, Robin E.; Royle, J. Andrew; Desimone, Richard; Schwartz, Michael K.; Edwards, Victoria L.; Pilgrim, Kristy P.; Mckelvey, Kevin S.

2012-01-01

Mountain lions (Puma concolor) are often difficult to monitor because of their low capture probabilities, extensive movements, and large territories. Methods for estimating the abundance of this species are needed to assess population status, determine harvest levels, evaluate the impacts of management actions on populations, and derive conservation and management strategies. Traditional mark–recapture methods do not explicitly account for differences in individual capture probabilities due to the spatial distribution of individuals in relation to survey effort (or trap locations). However, recent advances in the analysis of capture–recapture data have produced methods estimating abundance and density of animals from spatially explicit capture–recapture data that account for heterogeneity in capture probabilities due to the spatial organization of individuals and traps. We adapt recently developed spatial capture–recapture models to estimate density and abundance of mountain lions in western Montana. Volunteers and state agency personnel collected mountain lion DNA samples in portions of the Blackfoot drainage (7,908 km2) in west-central Montana using 2 methods: snow back-tracking mountain lion tracks to collect hair samples and biopsy darting treed mountain lions to obtain tissue samples. Overall, we recorded 72 individual capture events, including captures both with and without tissue sample collection and hair samples resulting in the identification of 50 individual mountain lions (30 females, 19 males, and 1 unknown sex individual). We estimated lion densities from 8 models containing effects of distance, sex, and survey effort on detection probability. Our population density estimates ranged from a minimum of 3.7 mountain lions/100 km2 (95% Cl 2.3–5.7) under the distance only model (including only an effect of distance on detection probability) to 6.7 (95% Cl 3.1–11.0) under the full model (including effects of distance, sex, survey effort, and distance x sex on detection probability). These numbers translate to a total estimate of 293 mountain lions (95% Cl 182–451) to 529 (95% Cl 245–870) within the Blackfoot drainage. Results from the distance model are similar to previous estimates of 3.6 mountain lions/100 km2 for the study area; however, results from all other models indicated greater numbers of mountain lions. Our results indicate that unstructured spatial sampling combined with spatial capture–recapture analysis can be an effective method for estimating large carnivore densities.

Effect of land use on the spatial variability of organic matter and nutrient status in an Oxisol

NASA Astrophysics Data System (ADS)

Paz-Ferreiro, Jorge; Alves, Marlene Cristina; Vidal Vázquez, Eva

2013-04-01

Heterogeneity is now considered as an inherent soil property. Spatial variability of soil attributes in natural landscapes results mainly from soil formation factors. In cultivated soils much heterogeneity can additionally occur as a result of land use, agricultural systems and management practices. Organic matter content (OMC) and nutrients associated to soil exchange complex are key attribute in the maintenance of a high quality soil. Neglecting spatial heterogeneity in soil OMC and nutrient status at the field scale might result in reduced yield and in environmental damage. We analyzed the impact of land use on the pattern of spatial variability of OMC and soil macronutrients at the stand scale. The study was conducted in São Paulo state, Brazil. Land uses were pasture, mango orchard and corn field. Soil samples were taken at 0-10 cm and 10-20 cm depth in 84 points, within 100 m x 100 m plots. Texture, pH, OMC, cation exchange capacity (CEC), exchangeable cations (Ca, Mg, K, H, Al) and resin extractable phosphorus were analyzed.. Statistical variability was found to be higher in parameters defining the soil nutrient status (resin extractable P, K, Ca and Mg) than in general soil properties (OMC, CEC, base saturation and pH). Geostatistical analysis showed contrasting patterns of spatial dependence for the different soil uses, sampling depths and studied properties. Most of the studied data sets collected at two different depths exhibited spatial dependence at the sampled scale and their semivariograms were modeled by a nugget effect plus a structure. The pattern of soil spatial variability was found to be different between the three study soil uses and at the two sampling depths, as far as model type, nugget effect or ranges of spatial dependence were concerned. Both statistical and geostatistical results pointed out the importance of OMC as a driver responsible for the spatial variability of soil nutrient status.

Uncertainty in the profitability of fertilizer management based on various sampling designs.

NASA Astrophysics Data System (ADS)

Muhammed, Shibu; Ben, Marchant; Webster, Richard; Milne, Alice; Dailey, Gordon; Whitmore, Andrew

2016-04-01

Many farmers sample their soil to measure the concentrations of plant nutrients, including phosphorus (P), so as to decide how much fertilizer to apply. Now that fertilizer can be applied at variable rates, farmers want to know whether maps of nutrient concentration made from grid samples or from field subdivisions (zones within their fields) are merited: do such maps lead to greater profit than would a single measurement on a bulked sample for each field when all costs are taken into account? We have examined the merits of grid-based and zone-based sampling strategies over single field-based averages using continuous spatial data on wheat yields at harvest in six fields in southern England and simulated concentrations of P in the soil. Features of the spatial variation in the yields provide predictions about which sampling scheme is likely to be most cost effective, but there is uncertainty associated with these predictions that must be communicated to farmers. Where variograms of the yield have large variances and long effective ranges, grid-sampling and mapping nutrients are likely to be cost-effective. Where effective ranges are short, sampling must be dense to reveal the spatial variation and may be expensive. In these circumstances variable-rate application of fertilizer is likely to be impracticable and almost certainly not cost-effective. We have explored several methods for communicating these results and found that the most effective method was using probability maps that show the likelihood of grid-based and zone-based sampling being more profitable that a field-based estimate.

A statistical model and national data set for partioning fish-tissue mercury concentration variation between spatiotemporal and sample characteristic effects

USGS Publications Warehouse

Wente, Stephen P.

2004-01-01

Many Federal, Tribal, State, and local agencies monitor mercury in fish-tissue samples to identify sites with elevated fish-tissue mercury (fish-mercury) concentrations, track changes in fish-mercury concentrations over time, and produce fish-consumption advisories. Interpretation of such monitoring data commonly is impeded by difficulties in separating the effects of sample characteristics (species, tissues sampled, and sizes of fish) from the effects of spatial and temporal trends on fish-mercury concentrations. Without such a separation, variation in fish-mercury concentrations due to differences in the characteristics of samples collected over time or across space can be misattributed to temporal or spatial trends; and/or actual trends in fish-mercury concentration can be misattributed to differences in sample characteristics. This report describes a statistical model and national data set (31,813 samples) for calibrating the aforementioned statistical model that can separate spatiotemporal and sample characteristic effects in fish-mercury concentration data. This model could be useful for evaluating spatial and temporal trends in fishmercury concentrations and developing fish-consumption advisories. The observed fish-mercury concentration data and model predictions can be accessed, displayed geospatially, and downloaded via the World Wide Web (http://emmma.usgs.gov). This report and the associated web site may assist in the interpretation of large amounts of data from widespread fishmercury monitoring efforts.

A multi-level analysis of the relationship between environmental factors and questing Ixodes ricinus dynamics in Belgium

PubMed Central

2012-01-01

Background Ticks are the most important pathogen vectors in Europe. They are known to be influenced by environmental factors, but these links are usually studied at specific temporal or spatial scales. Focusing on Ixodes ricinus in Belgium, we attempt to bridge the gap between current “single-sided” studies that focus on temporal or spatial variation only. Here, spatial and temporal patterns of ticks are modelled together. Methods A multi-level analysis of the Ixodes ricinus patterns in Belgium was performed. Joint effects of weather, habitat quality and hunting on field sampled tick abundance were examined at two levels, namely, sampling level, which is associated with temporal dynamics, and site level, which is related to spatial dynamics. Independent variables were collected from standard weather station records, game management data and remote sensing-based land cover data. Results At sampling level, only a marginally significant effect of daily relative humidity and temperature on the abundance of questing nymphs was identified. Average wind speed of seven days prior to the sampling day was found important to both questing nymphs and adults. At site level, a group of landscape-level forest fragmentation indices were highlighted for both questing nymph and adult abundance, including the nearest-neighbour distance, the shape and the aggregation level of forest patches. No cross-level effects or spatial autocorrelation were found. Conclusions Nymphal and adult ticks responded differently to environmental variables at different spatial and temporal scales. Our results can advise spatio-temporal extents of environment data collection for continuing empirical investigations and potential parameters for biological tick models. PMID:22830528

Sampling strategies for estimating brook trout effective population size

Treesearch

Andrew R. Whiteley; Jason A. Coombs; Mark Hudy; Zachary Robinson; Keith H. Nislow; Benjamin H. Letcher

2012-01-01

The influence of sampling strategy on estimates of effective population size (Ne) from single-sample genetic methods has not been rigorously examined, though these methods are increasingly used. For headwater salmonids, spatially close kin association among age-0 individuals suggests that sampling strategy (number of individuals and location from...

Hierarchical spatial capture-recapture models: Modeling population density from stratified populations

USGS Publications Warehouse

Royle, J. Andrew; Converse, Sarah J.

2014-01-01

Capture–recapture studies are often conducted on populations that are stratified by space, time or other factors. In this paper, we develop a Bayesian spatial capture–recapture (SCR) modelling framework for stratified populations – when sampling occurs within multiple distinct spatial and temporal strata.We describe a hierarchical model that integrates distinct models for both the spatial encounter history data from capture–recapture sampling, and also for modelling variation in density among strata. We use an implementation of data augmentation to parameterize the model in terms of a latent categorical stratum or group membership variable, which provides a convenient implementation in popular BUGS software packages.We provide an example application to an experimental study involving small-mammal sampling on multiple trapping grids over multiple years, where the main interest is in modelling a treatment effect on population density among the trapping grids.Many capture–recapture studies involve some aspect of spatial or temporal replication that requires some attention to modelling variation among groups or strata. We propose a hierarchical model that allows explicit modelling of group or strata effects. Because the model is formulated for individual encounter histories and is easily implemented in the BUGS language and other free software, it also provides a general framework for modelling individual effects, such as are present in SCR models.

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

NASA Technical Reports Server (NTRS)

Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;

EFFECTS OF SPATIAL EXTENT ON LANDSCAPE STRUCTURE AND SEDIMENT METAL CONCENTRATION RELATIONSHIPS IN SMALL ESTUARINE SYSTEMS OF THE US MID-ATLANTIC COAST

EPA Science Inventory

Prior studies exploring the quantitative relationship between landscape structure metrics and the ecological condition of receiving waters have used a variety of sampling units (e.g. a watershed, or a buffer around a sampling station) at a variety of spatial scales to generate la...

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...

Mapping spatial resources with GPS animal telemetry: foraging manatees locate seagrass beds in the Ten Thousand Islands, Florida, USA

USGS Publications Warehouse

Slone, Daniel H.; Reid, James P.; Kenworthy, W. Judson

2013-01-01

Turbid water conditions make the delineation and characterization of benthic habitats difficult by traditional in situ and remote sensing methods. Here, we develop and validate modeling and sampling methodology for detecting and characterizing seagrass beds by analyzing GPS telemetry records from radio-tagged manatees. Between October 2002 and October 2005, 14 manatees were tracked in the Ten Thousand Islands (TTI) in southwest Florida (USA) using Global Positioning System (GPS) tags. High density manatee use areas were found to occur off each island facing the open, nearshore waters of the Gulf of Mexico. We implemented a spatially stratified random sampling plan and used a camera-based sampling technique to observe and record bottom observations of seagrass and macroalgae presence and abundance. Five species of seagrass were identified in our study area: Halodule wrightii, Thalassia testudinum, Syringodium filiforme, Halophila engelmannii, and Halophila decipiens. A Bayesian model was developed to choose and parameterize a spatial process function that would describe the observed patterns of seagrass and macroalgae. The seagrasses were found in depths <2 m and in the higher manatee use strata, whereas macroalgae was found at moderate densities at all sampled depths and manatee use strata. The manatee spatial data showed a strong association with seagrass beds, a relationship that increased seagrass sampling efficiency. Our camera-based field sampling proved to be effective for assessing seagrass density and spatial coverage under turbid water conditions, and would be an effective monitoring tool to detect changes in seagrass beds.

In-flight edge response measurements for high-spatial-resolution remote sensing systems

NASA Astrophysics Data System (ADS)

Blonski, Slawomir; Pagnutti, Mary A.; Ryan, Robert; Zanoni, Vickie

2002-09-01

In-flight measurements of spatial resolution were conducted as part of the NASA Scientific Data Purchase Verification and Validation process. Characterization included remote sensing image products with ground sample distance of 1 meter or less, such as those acquired with the panchromatic imager onboard the IKONOS satellite and the airborne ADAR System 5500 multispectral instrument. Final image products were used to evaluate the effects of both the image acquisition system and image post-processing. Spatial resolution was characterized by full width at half maximum of an edge-response-derived line spread function. The edge responses were analyzed using the tilted-edge technique that overcomes the spatial sampling limitations of the digital imaging systems. As an enhancement to existing algorithms, the slope of the edge response and the orientation of the edge target were determined by a single computational process. Adjacent black and white square panels, either painted on a flat surface or deployed as tarps, formed the ground-based edge targets used in the tests. Orientation of the deployable tarps was optimized beforehand, based on simulations of the imaging system. The effects of such factors as acquisition geometry, temporal variability, Modulation Transfer Function compensation, and ground sample distance on spatial resolution were investigated.

Analysis of the effect of spatial and temporal sampling densities on accuracy of predicting the heating profile in windrowed broiler litter

USDA-ARS?s Scientific Manuscript database

A standard method for monitoring temperature in windrow piles of broiler litter to predict microbial population reductions is described. Temperature data collected every 2 min on a 10 cm x 10 cm spatial sampling grid in five identically-constructed litter windrow piles was utilized in this study. ...

Damage evolution analysis of coal samples under cyclic loading based on single-link cluster method

NASA Astrophysics Data System (ADS)

Zhang, Zhibo; Wang, Enyuan; Li, Nan; Li, Xuelong; Wang, Xiaoran; Li, Zhonghui

2018-05-01

In this paper, the acoustic emission (AE) response of coal samples under cyclic loading is measured. The results show that there is good positive relation between AE parameters and stress. The AE signal of coal samples under cyclic loading exhibits an obvious Kaiser Effect. The single-link cluster (SLC) method is applied to analyze the spatial evolution characteristics of AE events and the damage evolution process of coal samples. It is found that a subset scale of the SLC structure becomes smaller and smaller when the number of cyclic loading increases, and there is a negative linear relationship between the subset scale and the degree of damage. The spatial correlation length ξ of an SLC structure is calculated. The results show that ξ fluctuates around a certain value from the second cyclic loading process to the fifth cyclic loading process, but spatial correlation length ξ clearly increases in the sixth loading process. Based on the criterion of microcrack density, the coal sample failure process is the transformation from small-scale damage to large-scale damage, which is the reason for changes in the spatial correlation length. Through a systematic analysis, the SLC method is an effective method to research the damage evolution process of coal samples under cyclic loading, and will provide important reference values for studying coal bursts.

Spatial and Temporal Distribution of Multiple Cropping Indices in the North China Plain Using a Long Remote Sensing Data Time Series.

PubMed

Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui

2016-04-19

Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province.

Spatial and Temporal Distribution of Multiple Cropping Indices in the North China Plain Using a Long Remote Sensing Data Time Series

PubMed Central

Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui

2016-01-01

Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province. PMID:27104536

The effects of spatial sampling choices on MR temperature measurements.

PubMed

Todd, Nick; Vyas, Urvi; de Bever, Josh; Payne, Allison; Parker, Dennis L

2011-02-01

The purpose of this article is to quantify the effects that spatial sampling parameters have on the accuracy of magnetic resonance temperature measurements during high intensity focused ultrasound treatments. Spatial resolution and position of the sampling grid were considered using experimental and simulated data for two different types of high intensity focused ultrasound heating trajectories (a single point and a 4-mm circle) with maximum measured temperature and thermal dose volume as the metrics. It is demonstrated that measurement accuracy is related to the curvature of the temperature distribution, where regions with larger spatial second derivatives require higher resolution. The location of the sampling grid relative temperature distribution has a significant effect on the measured values. When imaging at 1.0 × 1.0 × 3.0 mm(3) resolution, the measured values for maximum temperature and volume dosed to 240 cumulative equivalent minutes (CEM) or greater varied by 17% and 33%, respectively, for the single-point heating case, and by 5% and 18%, respectively, for the 4-mm circle heating case. Accurate measurement of the maximum temperature required imaging at 1.0 × 1.0 × 3.0 mm(3) resolution for the single-point heating case and 2.0 × 2.0 × 5.0 mm(3) resolution for the 4-mm circle heating case. Copyright © 2010 Wiley-Liss, Inc.

Sex differences in visual-spatial working memory: A meta-analysis.

PubMed

Voyer, Daniel; Voyer, Susan D; Saint-Aubin, Jean

2017-04-01

Visual-spatial working memory measures are widely used in clinical and experimental settings. Furthermore, it has been argued that the male advantage in spatial abilities can be explained by a sex difference in visual-spatial working memory. Therefore, sex differences in visual-spatial working memory have important implication for research, theory, and practice, but they have yet to be quantified. The present meta-analysis quantified the magnitude of sex differences in visual-spatial working memory and examined variables that might moderate them. The analysis used a set of 180 effect sizes from healthy males and females drawn from 98 samples ranging in mean age from 3 to 86 years. Multilevel meta-analysis was used on the overall data set to account for non-independent effect sizes. The data also were analyzed in separate task subgroups by means of multilevel and mixed-effects models. Results showed a small but significant male advantage (mean d = 0.155, 95 % confidence interval = 0.087-0.223). All the tasks produced a male advantage, except for memory for location, where a female advantage emerged. Age of the participants was a significant moderator, indicating that sex differences in visual-spatial working memory appeared first in the 13-17 years age group. Removing memory for location tasks from the sample affected the pattern of significant moderators. The present results indicate a male advantage in visual-spatial working memory, although age and specific task modulate the magnitude and direction of the effects. Implications for clinical applications, cognitive model building, and experimental research are discussed.

So Close to a Deal: Spatial-Distance Cues Influence Economic Decision-Making in a Social Context.

PubMed

Fatfouta, Ramzi; Schulreich, Stefan; Meshi, Dar; Heekeren, Hauke

2015-01-01

Social distance (i.e., the degree of closeness to another person) affects the way humans perceive and respond to fairness during financial negotiations. Feeling close to someone enhances the acceptance of monetary offers. Here, we explored whether this effect also extends to the spatial domain. Specifically, using an iterated version of the Ultimatum Game in a within-subject design, we investigated whether different visual spatial distance-cues result in different rates of acceptance of otherwise identical monetary offers. Study 1 found that participants accepted significantly more offers when they were cued with spatial closeness than when they were cued with spatial distance. Study 2 replicated this effect using identical procedures but different spatial-distance cues in an independent sample. Importantly, our results could not be explained by feelings of social closeness. Our results demonstrate that mere perceptions of spatial closeness produce analogous-but independent-effects to those of social closeness.

Texture-adaptive hyperspectral video acquisition system with a spatial light modulator

NASA Astrophysics Data System (ADS)

Fang, Xiaojing; Feng, Jiao; Wang, Yongjin

2014-10-01

We present a new hybrid camera system based on spatial light modulator (SLM) to capture texture-adaptive high-resolution hyperspectral video. The hybrid camera system records a hyperspectral video with low spatial resolution using a gray camera and a high-spatial resolution video using a RGB camera. The hyperspectral video is subsampled by the SLM. The subsampled points can be adaptively selected according to the texture characteristic of the scene by combining with digital imaging analysis and computational processing. In this paper, we propose an adaptive sampling method utilizing texture segmentation and wavelet transform (WT). We also demonstrate the effectiveness of the sampled pattern on the SLM with the proposed method.

Persistent spatial information in the FEF during object-based short-term memory does not contribute to task performance.

PubMed

Clark, Kelsey L; Noudoost, Behrad; Moore, Tirin

2014-06-01

We previously reported the existence of a persistent spatial signal in the FEF during object-based STM. This persistent activity reflected the location at which the sample appeared, irrespective of the location of upcoming targets. We hypothesized that such a spatial signal could be used to maintain or enhance object-selective memory activity elsewhere in cortex, analogous to the role of a spatial signal during attention. Here, we inactivated a portion of the FEF with GABAa agonist muscimol to test whether the observed activity contributes to object memory performance. We found that, although RTs were slowed for saccades into the inactivated portion of retinotopic space, performance for samples appearing in that region was unimpaired. This contrasts with the devastating effects of the same FEF inactivation on purely spatial working memory, as assessed with the memory-guided saccade task. Thus, in a task in which a significant fraction of FEF neurons displayed persistent, sample location-based activity, disrupting this activity had no impact on task performance.

Effect of site level environmental variables, spatial autocorrelation and sampling intensity on arthropod communities in an ancient temperate lowland woodland area.

PubMed

Horak, Jakub

2013-01-01

The interaction of arthropods with the environment and the management of their populations is a focus of the ecological agenda. Spatial autocorrelation and under-sampling may generate bias and, when they are ignored, it is hard to determine if results can in any way be trusted. Arthropod communities were studied during two seasons and using two methods: window and panel traps, in an area of ancient temperate lowland woodland of Zebracka (Czech Republic). The composition of arthropod communities was studied focusing on four site level variables (canopy openness, diameter in the breast height and height of tree, and water distance) and finally analysed using two approaches: with and without effects of spatial autocorrelation. I found that the proportion of variance explained by space cannot be ignored (≈20% in both years). Potential bias in analyses of the response of arthropods to site level variables without including spatial co-variables is well illustrated by redundancy analyses. Inclusion of space led to more accurate results, as water distance and tree diameter were significant, showing approximately the same ratio of explained variance and direction in both seasons. Results without spatial co-variables were much more disordered and were difficult to explain. This study showed that neglecting the effects of spatial autocorrelation could lead to wrong conclusions in site level studies and, furthermore, that inclusion of space may lead to more accurate and unambiguous outcomes. Rarefactions showed that lower sampling intensity, when appropriately designed, can produce sufficient results without exploitation of the environment.

Effects of sampling interval on spatial patterns and statistics of watershed nitrogen concentration

USGS Publications Warehouse

Wu, S.-S.D.; Usery, E.L.; Finn, M.P.; Bosch, D.D.

2009-01-01

This study investigates how spatial patterns and statistics of a 30 m resolution, model-simulated, watershed nitrogen concentration surface change with sampling intervals from 30 m to 600 m for every 30 m increase for the Little River Watershed (Georgia, USA). The results indicate that the mean, standard deviation, and variogram sills do not have consistent trends with increasing sampling intervals, whereas the variogram ranges remain constant. A sampling interval smaller than or equal to 90 m is necessary to build a representative variogram. The interpolation accuracy, clustering level, and total hot spot areas show decreasing trends approximating a logarithmic function. The trends correspond to the nitrogen variogram and start to level at a sampling interval of 360 m, which is therefore regarded as a critical spatial scale of the Little River Watershed. Copyright ?? 2009 by Bellwether Publishing, Ltd. All right reserved.

Cost-effective sampling of (137)Cs-derived net soil redistribution: part 2 - estimating the spatial mean change over time.

PubMed

Chappell, A; Li, Y; Yu, H Q; Zhang, Y Z; Li, X Y

2015-06-01

The caesium-137 ((137)Cs) technique for estimating net, time-integrated soil redistribution by the processes of wind, water and tillage is increasingly being used with repeated sampling to form a baseline to evaluate change over small (years to decades) timeframes. This interest stems from knowledge that since the 1950s soil redistribution has responded dynamically to different phases of land use change and management. Currently, there is no standard approach to detect change in (137)Cs-derived net soil redistribution and thereby identify the driving forces responsible for change. We outline recent advances in space-time sampling in the soil monitoring literature which provide a rigorous statistical and pragmatic approach to estimating the change over time in the spatial mean of environmental properties. We apply the space-time sampling framework, estimate the minimum detectable change of net soil redistribution and consider the information content and cost implications of different sampling designs for a study area in the Chinese Loess Plateau. Three phases (1954-1996, 1954-2012 and 1996-2012) of net soil erosion were detectable and attributed to well-documented historical change in land use and management practices in the study area and across the region. We recommend that the design for space-time sampling is considered carefully alongside cost-effective use of the spatial mean to detect and correctly attribute cause of change over time particularly across spatial scales of variation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-05-25

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-11-23

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

The relationship between observational scale and explained variance in benthic communities

PubMed Central

Flood, Roger D.; Frisk, Michael G.; Garza, Corey D.; Lopez, Glenn R.; Maher, Nicole P.

2018-01-01

This study addresses the impact of spatial scale on explaining variance in benthic communities. In particular, the analysis estimated the fraction of community variation that occurred at a spatial scale smaller than the sampling interval (i.e., the geographic distance between samples). This estimate is important because it sets a limit on the amount of community variation that can be explained based on the spatial configuration of a study area and sampling design. Six benthic data sets were examined that consisted of faunal abundances, common environmental variables (water depth, grain size, and surficial percent cover), and sonar backscatter treated as a habitat proxy (categorical acoustic provinces). Redundancy analysis was coupled with spatial variograms generated by multiscale ordination to quantify the explained and residual variance at different spatial scales and within and between acoustic provinces. The amount of community variation below the sampling interval of the surveys (< 100 m) was estimated to be 36–59% of the total. Once adjusted for this small-scale variation, > 71% of the remaining variance was explained by the environmental and province variables. Furthermore, these variables effectively explained the spatial structure present in the infaunal community. Overall, no scale problems remained to compromise inferences, and unexplained infaunal community variation had no apparent spatial structure within the observational scale of the surveys (> 100 m), although small-scale gradients (< 100 m) below the observational scale may be present. PMID:29324746

The Effect of Origami-Based Instruction on Spatial Visualization, Geometry Achievement, and Geometric Reasoning

ERIC Educational Resources Information Center

Arici, Sevil; Aslan-Tutak, Fatma

2015-01-01

This research study examined the effect of origami-based geometry instruction on spatial visualization, geometry achievement, and geometric reasoning of tenth-grade students in Turkey. The sample ("n" = 184) was chosen from a tenth-grade population of a public high school in Turkey. It was a quasi-experimental pretest/posttest design. A…

An enhanced droplet-based liquid microjunction surface sampling system coupled with HPLC-ESI-MS/MS for spatially resolved analysis

DOE PAGES

Van Berkel, Gary J.; Weiskittel, Taylor M.; Kertesz, Vilmos

2014-11-07

Droplet-based liquid microjunction surface sampling coupled with high-performance liquid chromatography (HPLC)-electrospray ionization (ESI)-tandem mass spectrometry (MS/MS) for spatially resolved analysis provides the possibility of effective analysis of complex matrix samples and can provide a greater degree of chemical information from a single spot sample than is typically possible with a direct analysis of an extract. Described here is the setup and enhanced capabilities of a discrete droplet liquid microjunction surface sampling system employing a commercially available CTC PAL autosampler. The system enhancements include incorporation of a laser distance sensor enabling unattended analysis of samples and sample locations of dramatically disparatemore » height as well as reliably dispensing just 0.5 μL of extraction solvent to make the liquid junction to the surface, wherein the extraction spot size was confined to an area about 0.7 mm in diameter; software modifications improving the spatial resolution of sampling spot selection from 1.0 to 0.1 mm; use of an open bed tray system to accommodate samples as large as whole-body rat thin tissue sections; and custom sample/solvent holders that shorten sampling time to approximately 1 min per sample. Lastly, the merit of these new features was demonstrated by spatially resolved sampling, HPLC separation, and mass spectral detection of pharmaceuticals and metabolites from whole-body rat thin tissue sections and razor blade (“crude”) cut mouse tissue.« less

An enhanced droplet-based liquid microjunction surface sampling system coupled with HPLC-ESI-MS/MS for spatially resolved analysis

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

Van Berkel, Gary J.; Weiskittel, Taylor M.; Kertesz, Vilmos

Droplet-based liquid microjunction surface sampling coupled with high-performance liquid chromatography (HPLC)-electrospray ionization (ESI)-tandem mass spectrometry (MS/MS) for spatially resolved analysis provides the possibility of effective analysis of complex matrix samples and can provide a greater degree of chemical information from a single spot sample than is typically possible with a direct analysis of an extract. Described here is the setup and enhanced capabilities of a discrete droplet liquid microjunction surface sampling system employing a commercially available CTC PAL autosampler. The system enhancements include incorporation of a laser distance sensor enabling unattended analysis of samples and sample locations of dramatically disparatemore » height as well as reliably dispensing just 0.5 μL of extraction solvent to make the liquid junction to the surface, wherein the extraction spot size was confined to an area about 0.7 mm in diameter; software modifications improving the spatial resolution of sampling spot selection from 1.0 to 0.1 mm; use of an open bed tray system to accommodate samples as large as whole-body rat thin tissue sections; and custom sample/solvent holders that shorten sampling time to approximately 1 min per sample. Lastly, the merit of these new features was demonstrated by spatially resolved sampling, HPLC separation, and mass spectral detection of pharmaceuticals and metabolites from whole-body rat thin tissue sections and razor blade (“crude”) cut mouse tissue.« less

Topographic effects on denitrification in drained agricultural fields

USDA-ARS?s Scientific Manuscript database

Denitrification is affected by soil moisture, while soil moisture can be affected by topography. Therefore, denitrification can be spatially correlated to topographic gradients. Three prior converted fields on the Delmarva Peninsula were sampled spatially for denitrification enzyme activity. The up...

Mesoscale spatial variability of selected aquatic invertebrate community metrics from a minimally impaired stream segment

USGS Publications Warehouse

Gebler, J.B.

2004-01-01

The related topics of spatial variability of aquatic invertebrate community metrics, implications of spatial patterns of metric values to distributions of aquatic invertebrate communities, and ramifications of natural variability to the detection of human perturbations were investigated. Four metrics commonly used for stream assessment were computed for 9 stream reaches within a fairly homogeneous, minimally impaired stream segment of the San Pedro River, Arizona. Metric variability was assessed for differing sampling scenarios using simple permutation procedures. Spatial patterns of metric values suggest that aquatic invertebrate communities are patchily distributed on subsegment and segment scales, which causes metric variability. Wide ranges of metric values resulted in wide ranges of metric coefficients of variation (CVs) and minimum detectable differences (MDDs), and both CVs and MDDs often increased as sample size (number of reaches) increased, suggesting that any particular set of sampling reaches could yield misleading estimates of population parameters and effects that can be detected. Mean metric variabilities were substantial, with the result that only fairly large differences in metrics would be declared significant at ?? = 0.05 and ?? = 0.20. The number of reaches required to obtain MDDs of 10% and 20% varied with significance level and power, and differed for different metrics, but were generally large, ranging into tens and hundreds of reaches. Study results suggest that metric values from one or a small number of stream reach(es) may not be adequate to represent a stream segment, depending on effect sizes of interest, and that larger sample sizes are necessary to obtain reasonable estimates of metrics and sample statistics. For bioassessment to progress, spatial variability may need to be investigated in many systems and should be considered when designing studies and interpreting data.

Detecting spatial structures in throughfall data: the effect of extent, sample size, sampling design, and variogram estimation method

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-04-01

In the last three decades, an increasing number of studies analyzed spatial patterns in throughfall to investigate the consequences of rainfall redistribution for biogeochemical and hydrological processes in forests. In the majority of cases, variograms were used to characterize the spatial properties of the throughfall data. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and an appropriate layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation methods on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with heavy outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling), and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the numbers recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous throughfall studies relied on method-of-moments variogram estimation and sample sizes << 200, our current knowledge about throughfall spatial variability stands on shaky ground.

Sample design effects in landscape genetics

USGS Publications Warehouse

Oyler-McCance, Sara J.; Fedy, Bradley C.; Landguth, Erin L.

2012-01-01

An important research gap in landscape genetics is the impact of different field sampling designs on the ability to detect the effects of landscape pattern on gene flow. We evaluated how five different sampling regimes (random, linear, systematic, cluster, and single study site) affected the probability of correctly identifying the generating landscape process of population structure. Sampling regimes were chosen to represent a suite of designs common in field studies. We used genetic data generated from a spatially-explicit, individual-based program and simulated gene flow in a continuous population across a landscape with gradual spatial changes in resistance to movement. Additionally, we evaluated the sampling regimes using realistic and obtainable number of loci (10 and 20), number of alleles per locus (5 and 10), number of individuals sampled (10-300), and generational time after the landscape was introduced (20 and 400). For a simulated continuously distributed species, we found that random, linear, and systematic sampling regimes performed well with high sample sizes (>200), levels of polymorphism (10 alleles per locus), and number of molecular markers (20). The cluster and single study site sampling regimes were not able to correctly identify the generating process under any conditions and thus, are not advisable strategies for scenarios similar to our simulations. Our research emphasizes the importance of sampling data at ecologically appropriate spatial and temporal scales and suggests careful consideration for sampling near landscape components that are likely to most influence the genetic structure of the species. In addition, simulating sampling designs a priori could help guide filed data collection efforts.

Influence of hydration and annealing on structure, PSL yield and spatial resolution of pressed powder imaging plates of the X-ray storage phosphor CsBr:Eu2+

NASA Astrophysics Data System (ADS)

Kersting, E.; von Seggern, H.

2017-08-01

A new production route for europium doped cesium bromide (CsBr:Eu2+) imaging plates has been developed, synthesizing CsBr:Eu2+ powder from a precipitation reaction of aqueous CsBr solution with ethanol. This new route allows the control of features like homogeneous grain size and grain shape of the obtained powder. After drying and subsequent compacting the powder, disk-like samples were fabricated, and their resulting photostimulated luminescence (PSL) properties like yield and spatial resolution were determined. It will be shown that hydration of such disks causes the CsBr:Eu2+ powder to recrystallize starting from the humidity exposed surfaces to the sample interior up to a completely polycrystalline sample resulting in a decreasing PSL yield and an increasing resolution. Subsequent annealing leads to grain refinement combined with a large PSL yield increment and a minor effect on the spatial resolution. By first annealing the "as made" disk, one observes a strong increment of the PSL yield and almost no effect on the spatial resolution. During subsequent hydration, the recrystallization is hindered by minor structural changes of the grains. The related PSL yield drops slightly with increasing hydration time, and the spatial resolution drops considerably. The obtained PSL properties with respect to structure will be discussed with a simple model.

Modelling individual tree height to crown base of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.)

PubMed Central

Jansa, Václav

2017-01-01

Height to crown base (HCB) of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM), basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure) or Hegyi’s competition index (HCI—spatially explicit measure), and basal area proportion of a species of interest (BAPOR), respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset). The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce), 0.85 (beech)] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce), 0.83 (beech)]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed that the model was precise enough for the prediction of HCB for a range of site quality, tree size, stand density, and stand structure. We therefore recommend measuring of HCB on four randomly selected trees of a species of interest on each sample plot for localizing the mixed-effects model and predicting HCB of the remaining trees on the plot. Growth simulations can be made from the data that lack the values for either crown ratio or HCB using the HCB models. PMID:29049391

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, Erin L.; Gedy, Bradley C.; Oyler-McCance, Sara J.; Garey, Andrew L.; Emel, Sarah L.; Mumma, Matthew; Wagner, Helene H.; Fortin, Marie-Josée; Cushman, Samuel A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, E.L.; Fedy, B.C.; Oyler-McCance, S.J.; Garey, A.L.; Emel, S.L.; Mumma, M.; Wagner, H.H.; Fortin, M.-J.; Cushman, S.A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals. ?? 2011 Blackwell Publishing Ltd.

Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data.

PubMed

Redding, David W; Lucas, Tim C D; Blackburn, Tim M; Jones, Kate E

2017-01-01

Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs) commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT), to a spatial Bayesian SDM method (fitted using R-INLA), when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account for spatial autocorrelation in an SDM context and, by taking account of random effects, produce outputs that can better elucidate the role of covariates in predicting species occurrence. Given that it is often unclear what the drivers are behind data clumping in an empirical occurrence dataset, or indeed how geographically restricted these data are, spatially-explicit Bayesian SDMs may be the better choice when modelling the spatial distribution of target species.

a Novel Deep Convolutional Neural Network for Spectral-Spatial Classification of Hyperspectral Data

NASA Astrophysics Data System (ADS)

Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D.

2018-04-01

Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectral image classification. In this paper, a novel deep convolutional neural network (CNN) is proposed, which extracts spectral-spatial information of hyperspectral images correctly. The proposed model not only learns sufficient knowledge from the limited number of samples, but also has powerful generalization ability. The proposed framework based on three-dimensional convolution can extract spectral-spatial features of labeled samples effectively. Though CNN has shown its robustness to distortion, it cannot extract features of different scales through the traditional pooling layer that only have one size of pooling window. Hence, spatial pyramid pooling (SPP) is introduced into three-dimensional local convolutional filters for hyperspectral classification. Experimental results with a widely used hyperspectral remote sensing dataset show that the proposed model provides competitive performance.

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.

Correcting the effect of refraction and dispersion of light in FT-IR spectroscopic imaging in transmission through thick infrared windows.

PubMed

Chan, K L Andrew; Kazarian, Sergei G

2013-01-15

Transmission mode is one of the most common sampling methods for FT-IR spectroscopic imaging because the spectra obtained generally have a reasonable signal-to-noise ratio. However, dispersion and refraction of infrared light occurs when samples are sandwiched between infrared windows or placed underneath a layer of liquid. Dispersion and refraction cause infrared light to focus with different focal lengths depending on the wavelength (wavenumber) of the light. As a result, images obtained are in focus only at a particular wavenumber while they are defocused at other wavenumber values. In this work, a solution to correct this spread of focus by means of adding a lens on top of the infrared transparent window, such that a pseudo hemisphere is formed, has been investigated. Through this lens (or pseudo hemisphere), refraction of light is removed and the light across the spectral range has the same focal depth. Furthermore, the lens acts as a solid immersion objective and an increase of both magnification and spatial resolution (by 1.4 times) is demonstrated. The spatial resolution was investigated using an USAF resolution target, showing that the Rayleigh criterion can be achieved, as well as a sample with a sharp polymer interface to indicate the spatial resolution that can be expected in real samples. The reported approach was used to obtain chemical images of cross sections of cancer tissue and hair samples sandwiched between infrared windows showing the versatility and applicability of the method. In addition to the improved spatial resolution, the results reported herein also demonstrate that the lens can reduce the effect of scattering near the edges of tissue samples. The advantages of the presented approach, obtaining FT-IR spectroscopic images in transmission mode with the same focus across all wavenumber values and simultaneous improvement in spatial resolution, will have wide implications ranging from studies of live cells to sorption of drugs into tissues.

Spatial Dependence and Sampling of Phytoseiid Populations on Hass Avocados in Southern California.

PubMed

Lara, Jesús R; Amrich, Ruth; Saremi, Naseem T; Hoddle, Mark S

2016-04-22

Research on phytoseiid mites has been critical for developing an effective biocontrol strategy for suppressing Oligonchus perseae Tuttle, Baker, and Abatiello (Acari: Tetranychidae) in California avocado orchards. However, basic understanding of the spatial ecology of natural populations of phytoseiids in relation to O. perseae infestations and the validation of research-based strategies for assessing densities of these predators has been limited. To address these shortcomings, cross-sectional and longitudinal observations consisting of >3,000 phytoseiids and 500,000 O. perseae counted on 11,341 leaves were collected across 10 avocado orchards during a 10-yr period. Subsets of these data were analyzed statistically to characterize the spatial distribution of phytoseiids in avocado orchards and to evaluate the merits of developing binomial and enumerative sampling strategies for these predators. Spatial correlation of phytoseiids between trees was detected at one site, and a strong association of phytoseiids with elevated O. perseae densities was detected at four sites. Sampling simulations revealed that enumeration-based sampling performed better than binomial sampling for estimating phytoseiid densities. The ecological implications of these findings and potential for developing a custom sampling plan to estimate densities of phytoseiids inhabiting sampled trees in avocado orchards in California are discussed. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Improving tritium exposure reconstructions using accelerator mass spectrometry

PubMed Central

Hunt, J. R.; Vogel, J. S.; Knezovich, J. P.

2010-01-01

Direct measurement of tritium atoms by accelerator mass spectrometry (AMS) enables rapid low-activity tritium measurements from milligram-sized samples and permits greater ease of sample collection, faster throughput, and increased spatial and/or temporal resolution. Because existing methodologies for quantifying tritium have some significant limitations, the development of tritium AMS has allowed improvements in reconstructing tritium exposure concentrations from environmental measurements and provides an important additional tool in assessing the temporal and spatial distribution of chronic exposure. Tritium exposure reconstructions using AMS were previously demonstrated for a tree growing on known levels of tritiated water and for trees exposed to atmospheric releases of tritiated water vapor. In these analyses, tritium levels were measured from milligram-sized samples with sample preparation times of a few days. Hundreds of samples were analyzed within a few months of sample collection and resulted in the reconstruction of spatial and temporal exposure from tritium releases. Although the current quantification limit of tritium AMS is not adequate to determine natural environmental variations in tritium concentrations, it is expected to be sufficient for studies assessing possible health effects from chronic environmental tritium exposure. PMID:14735274

The effects of environmental variability and spatial sampling on the three-dimensional inversion problem.

PubMed

Bender, Christopher M; Ballard, Megan S; Wilson, Preston S

2014-06-01

The overall goal of this work is to quantify the effects of environmental variability and spatial sampling on the accuracy and uncertainty of estimates of the three-dimensional ocean sound-speed field. In this work, ocean sound speed estimates are obtained with acoustic data measured by a sparse autonomous observing system using a perturbative inversion scheme [Rajan, Lynch, and Frisk, J. Acoust. Soc. Am. 82, 998-1017 (1987)]. The vertical and horizontal resolution of the solution depends on the bandwidth of acoustic data and on the quantity of sources and receivers, respectively. Thus, for a simple, range-independent ocean sound speed profile, a single source-receiver pair is sufficient to estimate the water-column sound-speed field. On the other hand, an environment with significant variability may not be fully characterized by a large number of sources and receivers, resulting in uncertainty in the solution. This work explores the interrelated effects of environmental variability and spatial sampling on the accuracy and uncertainty of the inversion solution though a set of case studies. Synthetic data representative of the ocean variability on the New Jersey shelf are used.

SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CHICAGO: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND ENVIRONMENTAL RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CZECH REPUBLIC: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

LAND USE AND LOTIC DIATOM ASSEMBLAGES: A MULTI-SPATIAL AND TEMPORAL ASSESSMENT

EPA Science Inventory

We assessed the effects of land-use at multiple spatial scales (e.g., catchment, stream network, and stream reach) on periphyton from 25 wadeable streams along a land-use gradient in the Willamette River Basin, Oregon, in a dry season. Additional water chemistry samples were col...

How beta diversity and the underlying causes vary with sampling scales in the Changbai mountain forests.

PubMed

Tan, Lingzhao; Fan, Chunyu; Zhang, Chunyu; von Gadow, Klaus; Fan, Xiuhua

2017-12-01

This study aims to establish a relationship between the sampling scale and tree species beta diversity temperate forests and to identify the underlying causes of beta diversity at different sampling scales. The data were obtained from three large observational study areas in the Changbai mountain region in northeastern China. All trees with a dbh ≥1 cm were stem-mapped and measured. The beta diversity was calculated for four different grain sizes, and the associated variances were partitioned into components explained by environmental and spatial variables to determine the contributions of environmental filtering and dispersal limitation to beta diversity. The results showed that both beta diversity and the causes of beta diversity were dependent on the sampling scale. Beta diversity decreased with increasing scales. The best-explained beta diversity variation was up to about 60% which was discovered in the secondary conifer and broad-leaved mixed forest (CBF) study area at the 40 × 40 m scale. The variation partitioning result indicated that environmental filtering showed greater effects at bigger grain sizes, while dispersal limitation was found to be more important at smaller grain sizes. What is more, the result showed an increasing explanatory ability of environmental effects with increasing sampling grains but no clearly trend of spatial effects. The study emphasized that the underlying causes of beta diversity variation may be quite different within the same region depending on varying sampling scales. Therefore, scale effects should be taken into account in future studies on beta diversity, which is critical in identifying different relative importance of spatial and environmental drivers on species composition variation.

Characterizing spatial structure of sediment E. coli populations to inform sampling design.

PubMed

Piorkowski, Gregory S; Jamieson, Rob C; Hansen, Lisbeth Truelstrup; Bezanson, Greg S; Yost, Chris K

2014-01-01

Escherichia coli can persist in streambed sediments and influence water quality monitoring programs through their resuspension into overlying waters. This study examined the spatial patterns in E. coli concentration and population structure within streambed morphological features during baseflow and following stormflow to inform sampling strategies for representative characterization of E. coli populations within a stream reach. E. coli concentrations in bed sediments were significantly different (p = 0.002) among monitoring sites during baseflow, and significant interactive effects (p = 0.002) occurred among monitoring sites and morphological features following stormflow. Least absolute shrinkage and selection operator (LASSO) regression revealed that water velocity and effective particle size (D 10) explained E. coli concentration during baseflow, whereas sediment organic carbon, water velocity and median particle diameter (D 50) were important explanatory variables following stormflow. Principle Coordinate Analysis illustrated the site-scale differences in sediment E. coli populations between disconnected stream segments. Also, E. coli populations were similar among depositional features within a reach, but differed in relation to high velocity features (e.g., riffles). Canonical correspondence analysis resolved that E. coli population structure was primarily explained by spatial (26.9–31.7 %) over environmental variables (9.2–13.1 %). Spatial autocorrelation existed among monitoring sites and morphological features for both sampling events, and gradients in mean particle diameter and water velocity influenced E. coli population structure for the baseflow and stormflow sampling events, respectively. Representative characterization of streambed E. coli requires sampling of depositional and high velocity environments to accommodate strain selectivity among these features owing to sediment and water velocity heterogeneity.

Exploring the spatial variability of soil properties in an Alfisol Catena

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

Rosemary, F.; Vitharana, U. W. A.; Indraratne, S. P.

Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzedmore » for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m –1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg –1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post-hoc test showed significant effect of land use on the spatial variability of EC. Our study revealed a structured variability of topsoil properties in the selected tropical Alfisol catena. Except for EC, observed variability was not modified by the land uses. Investigated soil properties showed distinct spatial structures at different scales and magnitudes of strength. Our results will be useful for digital soil mapping, site specific management of soil properties, developing appropriate land use plans and quantifying anthropogenic impacts on the soil system.« less

Quantitative phase imaging of biological cells using spatially low and temporally high coherent light source.

PubMed

Ahmad, Azeem; Dubey, Vishesh; Singh, Gyanendra; Singh, Veena; Mehta, Dalip Singh

2016-04-01

In this Letter, we demonstrate quantitative phase imaging of biological samples, such as human red blood cells (RBCs) and onion cells using narrow temporal frequency and wide angular frequency spectrum light source. This type of light source was synthesized by the combined effect of spatial, angular, and temporal diversity of speckle reduction technique. The importance of using low spatial and high temporal coherence light source over the broad band and narrow band light source is that it does not require any dispersion compensation mechanism for biological samples. Further, it avoids the formation of speckle or spurious fringes which arises while using narrow band light source.

Multiscale spatial and small-scale temporal variation in the composition of Riverine fish communities.

PubMed

Growns, Ivor; Astles, Karen; Gehrke, Peter

2006-03-01

We studied the multiscale (sites, river reaches and rivers) and short-term temporal (monthly) variability in a freshwater fish assemblage. We found that small-scale spatial variation and short-term temporal variability significantly influenced fish community structure in the Macquarie and Namoi Rivers. However, larger scale spatial differences between rivers were the largest source of variation in the data. The interaction between temporal change and spatial variation in fish community structure, whilst statistically significant, was smaller than the variation between rivers. This suggests that although the fish communities within each river changed between sampling occasions, the underlying differences between rivers were maintained. In contrast, the strongest interaction between temporal and spatial effects occurred at the smallest spatial scale, at the level of individual sites. This means whilst the composition of the fish assemblage at a given site may fluctuate, the magnitude of these changes is unlikely to affect larger scale differences between reaches within rivers or between rivers. These results suggest that sampling at any time within a single season will be sufficient to show spatial differences that occur over large spatial scales, such as comparisons between rivers or between biogeographical regions.

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

Di, Zichao; Leyffer, Sven; Wild, Stefan M.

Fluorescence tomographic reconstruction, based on the detection of photons coming from fluorescent emission, can be used for revealing the internal elemental composition of a sample. On the other hand, conventional X-ray transmission tomography can be used for reconstructing the spatial distribution of the absorption coefficient inside a sample. In this work, we integrate both X-ray fluorescence and X-ray transmission data modalities and formulate a nonlinear optimization-based approach for reconstruction of the elemental composition of a given object. This model provides a simultaneous reconstruction of both the quantitative spatial distribution of all elements and the absorption effect in the sample. Mathematicallymore » speaking, we show that compared with the single-modality inversion (i.e., the X-ray transmission or fluorescence alone), the joint inversion provides a better-posed problem, which implies a better recovery. Therefore, the challenges in X-ray fluorescence tomography arising mainly from the effects of self-absorption in the sample are partially mitigated. The use of this technique is demonstrated on the reconstruction of several synthetic samples.« less

Phylogenetic congruence of lichenised fungi and algae is affected by spatial scale and taxonomic diversity.

PubMed

Buckley, Hannah L; Rafat, Arash; Ridden, Johnathon D; Cruickshank, Robert H; Ridgway, Hayley J; Paterson, Adrian M

2014-01-01

The role of species' interactions in structuring biological communities remains unclear. Mutualistic symbioses, involving close positive interactions between two distinct organismal lineages, provide an excellent means to explore the roles of both evolutionary and ecological processes in determining how positive interactions affect community structure. In this study, we investigate patterns of co-diversification between fungi and algae for a range of New Zealand lichens at the community, genus, and species levels and explore explanations for possible patterns related to spatial scale and pattern, taxonomic diversity of the lichens considered, and the level sampling replication. We assembled six independent datasets to compare patterns in phylogenetic congruence with varied spatial extent of sampling, taxonomic diversity and level of specimen replication. For each dataset, we used the DNA sequences from the ITS regions of both the fungal and algal genomes from lichen specimens to produce genetic distance matrices. Phylogenetic congruence between fungi and algae was quantified using distance-based redundancy analysis and we used geographic distance matrices in Moran's eigenvector mapping and variance partitioning to evaluate the effects of spatial variation on the quantification of phylogenetic congruence. Phylogenetic congruence was highly significant for all datasets and a large proportion of variance in both algal and fungal genetic distances was explained by partner genetic variation. Spatial variables, primarily at large and intermediate scales, were also important for explaining genetic diversity patterns in all datasets. Interestingly, spatial structuring was stronger for fungal than algal genetic variation. As the spatial extent of the samples increased, so too did the proportion of explained variation that was shared between the spatial variables and the partners' genetic variation. Different lichen taxa showed some variation in their phylogenetic congruence and spatial genetic patterns and where greater sample replication was used, the amount of variation explained by partner genetic variation increased. Our results suggest that the phylogenetic congruence pattern, at least at small spatial scales, is likely due to reciprocal co-adaptation or co-dispersal. However, the detection of these patterns varies among different lichen taxa, across spatial scales and with different levels of sample replication. This work provides insight into the complexities faced in determining how evolutionary and ecological processes may interact to generate diversity in symbiotic association patterns at the population and community levels. Further, it highlights the critical importance of considering sample replication, taxonomic diversity and spatial scale in designing studies of co-diversification.

Efficient space-time sampling with pixel-wise coded exposure for high-speed imaging.

PubMed

Liu, Dengyu; Gu, Jinwei; Hitomi, Yasunobu; Gupta, Mohit; Mitsunaga, Tomoo; Nayar, Shree K

2014-02-01

Cameras face a fundamental trade-off between spatial and temporal resolution. Digital still cameras can capture images with high spatial resolution, but most high-speed video cameras have relatively low spatial resolution. It is hard to overcome this trade-off without incurring a significant increase in hardware costs. In this paper, we propose techniques for sampling, representing, and reconstructing the space-time volume to overcome this trade-off. Our approach has two important distinctions compared to previous works: 1) We achieve sparse representation of videos by learning an overcomplete dictionary on video patches, and 2) we adhere to practical hardware constraints on sampling schemes imposed by architectures of current image sensors, which means that our sampling function can be implemented on CMOS image sensors with modified control units in the future. We evaluate components of our approach, sampling function and sparse representation, by comparing them to several existing approaches. We also implement a prototype imaging system with pixel-wise coded exposure control using a liquid crystal on silicon device. System characteristics such as field of view and modulation transfer function are evaluated for our imaging system. Both simulations and experiments on a wide range of scenes show that our method can effectively reconstruct a video from a single coded image while maintaining high spatial resolution.

High-resolution imaging of magnetic fields using scanning superconducting quantum interference device (SQUID) microscopy

NASA Astrophysics Data System (ADS)

Fong de Los Santos, Luis E.

Development of a scanning superconducting quantum interference device (SQUID) microscope system with interchangeable sensor configurations for imaging magnetic fields of room-temperature (RT) samples with sub-millimeter resolution. The low-critical-temperature (Tc) niobium-based monolithic SQUID sensor is mounted in the tip of a sapphire rod and thermally anchored to the cryostat helium reservoir. A 25 mum sapphire window separates the vacuum space from the RT sample. A positioning mechanism allows adjusting the sample-to-sensor spacing from the top of the Dewar. I have achieved a sensor-to-sample spacing of 100 mum, which could be maintained for periods of up to 4 weeks. Different SQUID sensor configurations are necessary to achieve the best combination of spatial resolution and field sensitivity for a given magnetic source. For imaging thin sections of geological samples, I used a custom-designed monolithic low-Tc niobium bare SQUID sensor, with an effective diameter of 80 mum, and achieved a field sensitivity of 1.5 pT/Hz1/2 and a magnetic moment sensitivity of 5.4 x 10-18 Am2/Hz1/2 at a sensor-to-sample spacing of 100 mum in the white noise region for frequencies above 100 Hz. Imaging action currents in cardiac tissue requires higher field sensitivity, which can only be achieved by compromising spatial resolution. I developed a monolithic low-Tc niobium multiloop SQUID sensor, with sensor sizes ranging from 250 mum to 1 mm, and achieved sensitivities of 480 - 180 fT/Hz1/2 in the white noise region for frequencies above 100 Hz, respectively. For all sensor configurations, the spatial resolution was comparable to the effective diameter and limited by the sensor-to-sample spacing. Spatial registration allowed us to compare high-resolution images of magnetic fields associated with action currents and optical recordings of transmembrane potentials to study the bidomain nature of cardiac tissue or to match petrography to magnetic field maps in thin sections of geological samples.

Does participation in art classes influence performance on two different cognitive tasks?

PubMed

Schindler, Manuel; Maihöfner, Christian; Bolwerk, Anne; Lang, Frieder R

2017-04-01

Effects of two mentally stimulating art interventions on processing speed and visuo-spatial cognition were compared in three samples. In a randomized 10-week art intervention study with a pre-post follow-up design, 113 adults (27 healthy older adults with subjective memory complaints, 50 healthy older adults and 36 healthy younger adults) were randomly assigned to one of two groups: visual art production or cognitive art evaluation, where the participants either produced or evaluated art. ANOVAs with repeated measures were computed to observe effects on the Symbol-Digit Test, and the Stick Test. Significant Time effects were found with regard to processing speed and visuo-spatial cognition. Additionally, there was found a significant Time × Sample interaction for processing speed. The effects proved robust after testing for education and adding sex as additional factor. Mental stimulation by participation in art classes leads to an improvement of processing speed and visuo-spatial cognition. Further investigation is required to improve understanding of the potential impact of art intervention on cognitive abilities across adulthood.

A statistical evaluation of non-ergodic variogram estimators

USGS Publications Warehouse

Curriero, F.C.; Hohn, M.E.; Liebhold, A.M.; Lele, S.R.

2002-01-01

Geostatistics is a set of statistical techniques that is increasingly used to characterize spatial dependence in spatially referenced ecological data. A common feature of geostatistics is predicting values at unsampled locations from nearby samples using the kriging algorithm. Modeling spatial dependence in sampled data is necessary before kriging and is usually accomplished with the variogram and its traditional estimator. Other types of estimators, known as non-ergodic estimators, have been used in ecological applications. Non-ergodic estimators were originally suggested as a method of choice when sampled data are preferentially located and exhibit a skewed frequency distribution. Preferentially located samples can occur, for example, when areas with high values are sampled more intensely than other areas. In earlier studies the visual appearance of variograms from traditional and non-ergodic estimators were compared. Here we evaluate the estimators' relative performance in prediction. We also show algebraically that a non-ergodic version of the variogram is equivalent to the traditional variogram estimator. Simulations, designed to investigate the effects of data skewness and preferential sampling on variogram estimation and kriging, showed the traditional variogram estimator outperforms the non-ergodic estimators under these conditions. We also analyzed data on carabid beetle abundance, which exhibited large-scale spatial variability (trend) and a skewed frequency distribution. Detrending data followed by robust estimation of the residual variogram is demonstrated to be a successful alternative to the non-ergodic approach.

Spatial variation in mandibular bone elastic modulus and its effect on structural bending stiffness: A test case using the Taï Forest monkeys.

PubMed

Le, Kim N; Marsik, Matthew; Daegling, David J; Duque, Ana; McGraw, William Scott

2017-03-01

We investigated how heterogeneity in material stiffness affects structural stiffness in the cercopithecid mandibular cortical bone. We assessed (1) whether this effect changes the interpretation of interspecific structural stiffness variation across four primate species, (2) whether the heterogeneity is random, and (3) whether heterogeneity mitigates bending stress in the jaw associated with food processing. The sample consisted of Taï Forest, Cote d'Ivoire, monkeys: Cercocebus atys, Piliocolobus badius, Colobus polykomos, and Cercopithecus diana. Vickers indentation hardness samples estimated elastic moduli throughout the cortical bone area of each coronal section of postcanine corpus. For each section, we calculated maximum area moment of inertia, I max (structural mechanical property), under three models of material heterogeneity, as well as spatial autocorrelation statistics (Moran's I, I MORAN ). When the model considered material stiffness variation and spatial patterning, I max decreased and individual ranks based on structural stiffness changed. Rank changes were not significant across models. All specimens showed positive (nonrandom) spatial autocorrelation. Differences in I MORAN were not significant among species, and there were no discernable patterns of autocorrelation within species. Across species, significant local I MORAN was often attributed to proximity of low moduli in the alveolar process and high moduli in the basal process. While our sample did not demonstrate species differences in the degree of spatial autocorrelation of elastic moduli, there may be mechanical effects of heterogeneity (relative strength and rigidity) that do distinguish at the species or subfamilial level (i.e., colobines vs. cercopithecines). The potential connections of heterogeneity to diet and/or taxonomy remain to be discovered. © 2016 Wiley Periodicals, Inc.

LINKAGES AMONG LAND-USE, WATER QUALITY, PHYSICAL HABITAT CONDITIONS AND LOTIC DIATOM ASSEMBLAGES: A MULTI-SPATIAL SCALE ASSESSMENT

EPA Science Inventory

We assessed the importance of spatial scales (catchment, stream network, and sample reach) on the effects of agricultural land-use on lotic diatom assemblages along a land-use gradient in the agricultural Willamette Valley Ecoregion of Oregon. Periphyton, water chemistry, and ph...

Analysis of spatial distribution of land cover maps accuracy

NASA Astrophysics Data System (ADS)

Khatami, R.; Mountrakis, G.; Stehman, S. V.

2017-12-01

Land cover maps have become one of the most important products of remote sensing science. However, classification errors will exist in any classified map and affect the reliability of subsequent map usage. Moreover, classification accuracy often varies over different regions of a classified map. These variations of accuracy will affect the reliability of subsequent analyses of different regions based on the classified maps. The traditional approach of map accuracy assessment based on an error matrix does not capture the spatial variation in classification accuracy. Here, per-pixel accuracy prediction methods are proposed based on interpolating accuracy values from a test sample to produce wall-to-wall accuracy maps. Different accuracy prediction methods were developed based on four factors: predictive domain (spatial versus spectral), interpolation function (constant, linear, Gaussian, and logistic), incorporation of class information (interpolating each class separately versus grouping them together), and sample size. Incorporation of spectral domain as explanatory feature spaces of classification accuracy interpolation was done for the first time in this research. Performance of the prediction methods was evaluated using 26 test blocks, with 10 km × 10 km dimensions, dispersed throughout the United States. The performance of the predictions was evaluated using the area under the curve (AUC) of the receiver operating characteristic. Relative to existing accuracy prediction methods, our proposed methods resulted in improvements of AUC of 0.15 or greater. Evaluation of the four factors comprising the accuracy prediction methods demonstrated that: i) interpolations should be done separately for each class instead of grouping all classes together; ii) if an all-classes approach is used, the spectral domain will result in substantially greater AUC than the spatial domain; iii) for the smaller sample size and per-class predictions, the spectral and spatial domain yielded similar AUC; iv) for the larger sample size (i.e., very dense spatial sample) and per-class predictions, the spatial domain yielded larger AUC; v) increasing the sample size improved accuracy predictions with a greater benefit accruing to the spatial domain; and vi) the function used for interpolation had the smallest effect on AUC.

Spectral-spatial hyperspectral image classification using super-pixel-based spatial pyramid representation

NASA Astrophysics Data System (ADS)

Fan, Jiayuan; Tan, Hui Li; Toomik, Maria; Lu, Shijian

2016-10-01

Spatial pyramid matching has demonstrated its power for image recognition task by pooling features from spatially increasingly fine sub-regions. Motivated by the concept of feature pooling at multiple pyramid levels, we propose a novel spectral-spatial hyperspectral image classification approach using superpixel-based spatial pyramid representation. This technique first generates multiple superpixel maps by decreasing the superpixel number gradually along with the increased spatial regions for labelled samples. By using every superpixel map, sparse representation of pixels within every spatial region is then computed through local max pooling. Finally, features learned from training samples are aggregated and trained by a support vector machine (SVM) classifier. The proposed spectral-spatial hyperspectral image classification technique has been evaluated on two public hyperspectral datasets, including the Indian Pines image containing 16 different agricultural scene categories with a 20m resolution acquired by AVIRIS and the University of Pavia image containing 9 land-use categories with a 1.3m spatial resolution acquired by the ROSIS-03 sensor. Experimental results show significantly improved performance compared with the state-of-the-art works. The major contributions of this proposed technique include (1) a new spectral-spatial classification approach to generate feature representation for hyperspectral image, (2) a complementary yet effective feature pooling approach, i.e. the superpixel-based spatial pyramid representation that is used for the spatial correlation study, (3) evaluation on two public hyperspectral image datasets with superior image classification performance.

Sampling methods to detect and estimate populations of Tyrophagus putrescentiae (Schrank) (Sarcoptiformes: Acaridae) infesting dry-cured hams

USDA-ARS?s Scientific Manuscript database

Spatial and temporal dynamics of pest populations is an important aspect of effective pest management. However, absolute sampling of some pest populations such as the ham mite, Tyrophagus putrescentiae (Schrank) (Sarcoptiformes: Acaridae), a serious pest of dry-cured ham, can be difficult. Sampling ...

A rotating hot-wire technique for spatial sampling of disturbed and manipulated duct flows

NASA Technical Reports Server (NTRS)

Wark, C. E.; Nagib, H. M.; Jennings, M. J.

1990-01-01

A duct flow spatial sampling technique, in which an X-wire probe is rotated about the center of a cylindrical test section at a radius equal to one-half that of the test section in order to furnish nearly instantaneous multipoint measurements of the streamwise and azimuthal components, is presently evaluated in view of the control of flow disturbances downstream of various open inlet contractions. The effectiveness of a particular contraction in controlling ingested flow disturbances was ascertained by artificially introducing disturbances upstream of the contractions; control effectiveness if found to be strongly dependent on inlet contraction, with consequences for the reduction of passing-blade frequency noise during gas turbine engine ground testing.

EEG source localization: Sensor density and head surface coverage.

PubMed

Song, Jasmine; Davey, Colin; Poulsen, Catherine; Luu, Phan; Turovets, Sergei; Anderson, Erik; Li, Kai; Tucker, Don

2015-12-30

The accuracy of EEG source localization depends on a sufficient sampling of the surface potential field, an accurate conducting volume estimation (head model), and a suitable and well-understood inverse technique. The goal of the present study is to examine the effect of sampling density and coverage on the ability to accurately localize sources, using common linear inverse weight techniques, at different depths. Several inverse methods are examined, using the popular head conductivity. Simulation studies were employed to examine the effect of spatial sampling of the potential field at the head surface, in terms of sensor density and coverage of the inferior and superior head regions. In addition, the effects of sensor density and coverage are investigated in the source localization of epileptiform EEG. Greater sensor density improves source localization accuracy. Moreover, across all sampling density and inverse methods, adding samples on the inferior surface improves the accuracy of source estimates at all depths. More accurate source localization of EEG data can be achieved with high spatial sampling of the head surface electrodes. The most accurate source localization is obtained when the voltage surface is densely sampled over both the superior and inferior surfaces. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Sex effects on spatial learning but not on spatial memory retrieval in healthy young adults.

PubMed

Piber, Dominique; Nowacki, Jan; Mueller, Sven C; Wingenfeld, Katja; Otte, Christian

2018-01-15

Sex differences have been found in spatial learning and spatial memory, with several studies indicating that males outperform females. We tested in the virtual Morris Water Maze (vMWM) task, whether sex differences in spatial cognitive processes are attributable to differences in spatial learning or spatial memory retrieval in a large student sample. We tested 90 healthy students (45 women and 45 men) with a mean age of 23.5 years (SD=3.5). Spatial learning and spatial memory retrieval were measured by using the vMWM task, during which participants had to search a virtual pool for a hidden platform, facilitated by visual cues surrounding the pool. Several learning trials assessed spatial learning, while a separate probe trial assessed spatial memory retrieval. We found a significant sex effect during spatial learning, with males showing shorter latency and shorter path length, as compared to females (all p<0.001). Yet, there was no significant sex effect in spatial memory retrieval (p=0.615). Furthermore, post-hoc analyses revealed significant sex differences in spatial search strategies (p<0.05), but no difference in the number of platform crossings (p=0.375). Our results indicate that in healthy young adults, males show faster spatial learning in a virtual environment, as compared to females. Interestingly, we found no significant sex differences during spatial memory retrieval. Our study raises the question, whether men and women use different learning strategies, which nevertheless result in equal performances of spatial memory retrieval. Copyright © 2017 Elsevier B.V. All rights reserved.

Multidimensional System Analysis of Electro-Optic Sensors with Sampled Deterministic Output.

DTIC Science & Technology

1987-12-18

System descriptions of scanning and staring electro - optic sensors with sampled output are developed as follows. Functions representing image...to complete the system descriptions. The results should be useful for designing electro - optic sensor systems and correcting data for instrumental...effects and other experimental conditions. Keywords include: Electro - optic system analysis, Scanning sensors, Staring sensors, Spatial sampling, and Temporal sampling.

Spatial and Temporal Dynamics of Pacific Oyster Hemolymph Microbiota across Multiple Scales

PubMed Central

Lokmer, Ana; Goedknegt, M. Anouk; Thieltges, David W.; Fiorentino, Dario; Kuenzel, Sven; Baines, John F.; Wegner, K. Mathias

2016-01-01

Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics. PMID:27630625

Temporal and Spatial Variation of Soil Bacteria Richness, Composition, and Function in a Neotropical Rainforest

PubMed Central

Kivlin, Stephanie N; Hawkes, Christine V

2016-01-01

The high diversity of tree species has traditionally been considered an important controller of belowground processes in tropical rainforests. However, soil water availability and resources are also primary regulators of soil bacteria in many ecosystems. Separating the effects of these biotic and abiotic factors in the tropics is challenging because of their high spatial and temporal heterogeneity. To determine the drivers of tropical soil bacteria, we examined tree species effects using experimental tree monocultures and secondary forests at La Selva Biological Station in Costa Rica. A randomized block design captured spatial variation and we sampled at four dates across two years to assess temporal variation. We measured bacteria richness, phylogenetic diversity, community composition, biomass, and functional potential. All bacteria parameters varied significantly across dates. In addition, bacteria richness and phylogenetic diversity were affected by the interaction of vegetation type and date, whereas bacteria community composition was affected by the interaction of vegetation type and block. Shifts in bacteria community richness and composition were unrelated to shifts in enzyme function, suggesting physiological overlap among taxa. Based on the observed temporal and spatial heterogeneity, our understanding of tropical soil bacteria will benefit from additional work to determine the optimal temporal and spatial scales for sampling. Understanding spatial and temporal variation will facilitate prediction of how tropical soil microbes will respond to future environmental change. PMID:27391450

Temporal and Spatial Variation of Soil Bacteria Richness, Composition, and Function in a Neotropical Rainforest.

PubMed

Kivlin, Stephanie N; Hawkes, Christine V

2016-01-01

The high diversity of tree species has traditionally been considered an important controller of belowground processes in tropical rainforests. However, soil water availability and resources are also primary regulators of soil bacteria in many ecosystems. Separating the effects of these biotic and abiotic factors in the tropics is challenging because of their high spatial and temporal heterogeneity. To determine the drivers of tropical soil bacteria, we examined tree species effects using experimental tree monocultures and secondary forests at La Selva Biological Station in Costa Rica. A randomized block design captured spatial variation and we sampled at four dates across two years to assess temporal variation. We measured bacteria richness, phylogenetic diversity, community composition, biomass, and functional potential. All bacteria parameters varied significantly across dates. In addition, bacteria richness and phylogenetic diversity were affected by the interaction of vegetation type and date, whereas bacteria community composition was affected by the interaction of vegetation type and block. Shifts in bacteria community richness and composition were unrelated to shifts in enzyme function, suggesting physiological overlap among taxa. Based on the observed temporal and spatial heterogeneity, our understanding of tropical soil bacteria will benefit from additional work to determine the optimal temporal and spatial scales for sampling. Understanding spatial and temporal variation will facilitate prediction of how tropical soil microbes will respond to future environmental change.

[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.

Structured illumination diffuse optical tomography for noninvasive functional neuroimaging in mice.

PubMed

Reisman, Matthew D; Markow, Zachary E; Bauer, Adam Q; Culver, Joseph P

2017-04-01

Optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to superficial cortical tissues. Diffuse optical tomography (DOT) techniques provide noninvasive imaging, but previous DOT systems for rodent neuroimaging have been limited either by sparse spatial sampling or by slow speed. Here, we develop a DOT system with asymmetric source-detector sampling that combines the high-density spatial sampling (0.4 mm) detection of a scientific complementary metal-oxide-semiconductor camera with the rapid (2 Hz) imaging of a few ([Formula: see text]) structured illumination (SI) patterns. Analysis techniques are developed to take advantage of the system's flexibility and optimize trade-offs among spatial sampling, imaging speed, and signal-to-noise ratio. An effective source-detector separation for the SI patterns was developed and compared with light intensity for a quantitative assessment of data quality. The light fall-off versus effective distance was also used for in situ empirical optimization of our light model. We demonstrated the feasibility of this technique by noninvasively mapping the functional response in the somatosensory cortex of the mouse following electrical stimulation of the forepaw.

The Impact of Sampling Schemes on the Site Frequency Spectrum in Nonequilibrium Subdivided Populations

PubMed Central

Städler, Thomas; Haubold, Bernhard; Merino, Carlos; Stephan, Wolfgang; Pfaffelhuber, Peter

2009-01-01

Using coalescent simulations, we study the impact of three different sampling schemes on patterns of neutral diversity in structured populations. Specifically, we are interested in two summary statistics based on the site frequency spectrum as a function of migration rate, demographic history of the entire substructured population (including timing and magnitude of specieswide expansions), and the sampling scheme. Using simulations implementing both finite-island and two-dimensional stepping-stone spatial structure, we demonstrate strong effects of the sampling scheme on Tajima's D (DT) and Fu and Li's D (DFL) statistics, particularly under specieswide (range) expansions. Pooled samples yield average DT and DFL values that are generally intermediate between those of local and scattered samples. Local samples (and to a lesser extent, pooled samples) are influenced by local, rapid coalescence events in the underlying coalescent process. These processes result in lower proportions of external branch lengths and hence lower proportions of singletons, explaining our finding that the sampling scheme affects DFL more than it does DT. Under specieswide expansion scenarios, these effects of spatial sampling may persist up to very high levels of gene flow (Nm > 25), implying that local samples cannot be regarded as being drawn from a panmictic population. Importantly, many data sets on humans, Drosophila, and plants contain signatures of specieswide expansions and effects of sampling scheme that are predicted by our simulation results. This suggests that validating the assumption of panmixia is crucial if robust demographic inferences are to be made from local or pooled samples. However, future studies should consider adopting a framework that explicitly accounts for the genealogical effects of population subdivision and empirical sampling schemes. PMID:19237689

[Spatial variation characteristics of surface soil water content, bulk density and saturated hydraulic conductivity on Karst slopes].

PubMed

Zhang, Chuan; Chen, Hong-Song; Zhang, Wei; Nie, Yun-Peng; Ye, Ying-Ying; Wang, Ke-Lin

2014-06-01

Surface soil water-physical properties play a decisive role in the dynamics of deep soil water. Knowledge of their spatial variation is helpful in understanding the processes of rainfall infiltration and runoff generation, which will contribute to the reasonable utilization of soil water resources in mountainous areas. Based on a grid sampling scheme (10 m x 10 m) and geostatistical methods, this paper aimed to study the spatial variability of surface (0-10 cm) soil water content, soil bulk density and saturated hydraulic conductivity on a typical shrub slope (90 m x 120 m, projected length) in Karst area of northwest Guangxi, southwest China. The results showed that the surface soil water content, bulk density and saturated hydraulic conductivity had different spatial dependence and spatial structure. Sample variogram of the soil water content was fitted well by Gaussian models with the nugget effect, while soil bulk density and saturated hydraulic conductivity were fitted well by exponential models with the nugget effect. Variability of soil water content showed strong spatial dependence, while the soil bulk density and saturated hydraulic conductivity showed moderate spatial dependence. The spatial ranges of the soil water content and saturated hydraulic conductivity were small, while that of the soil bulk density was much bigger. In general, the soil water content increased with the increase of altitude while it was opposite for the soil bulk densi- ty. However, the soil saturated hydraulic conductivity had a random distribution of large amounts of small patches, showing high spatial heterogeneity. Soil water content negatively (P < 0.01) correlated with the bulk density and saturated hydraulic conductivity, while there was no significant correlation between the soil bulk density and saturated hydraulic conductivity.

Optimal sampling design for estimating spatial distribution and abundance of a freshwater mussel population

USGS Publications Warehouse

Pooler, P.S.; Smith, D.R.

2005-01-01

We compared the ability of simple random sampling (SRS) and a variety of systematic sampling (SYS) designs to estimate abundance, quantify spatial clustering, and predict spatial distribution of freshwater mussels. Sampling simulations were conducted using data obtained from a census of freshwater mussels in a 40 X 33 m section of the Cacapon River near Capon Bridge, West Virginia, and from a simulated spatially random population generated to have the same abundance as the real population. Sampling units that were 0.25 m 2 gave more accurate and precise abundance estimates and generally better spatial predictions than 1-m2 sampling units. Systematic sampling with ???2 random starts was more efficient than SRS. Estimates of abundance based on SYS were more accurate when the distance between sampling units across the stream was less than or equal to the distance between sampling units along the stream. Three measures for quantifying spatial clustering were examined: Hopkins Statistic, the Clumping Index, and Morisita's Index. Morisita's Index was the most reliable, and the Hopkins Statistic was prone to false rejection of complete spatial randomness. SYS designs with units spaced equally across and up stream provided the most accurate predictions when estimating the spatial distribution by kriging. Our research indicates that SYS designs with sampling units equally spaced both across and along the stream would be appropriate for sampling freshwater mussels even if no information about the true underlying spatial distribution of the population were available to guide the design choice. ?? 2005 by The North American Benthological Society.

Modeling Alaska boreal forests with a controlled trend surface approach

Treesearch

Mo Zhou; Jingjing Liang

2012-01-01

An approach of Controlled Trend Surface was proposed to simultaneously take into consideration large-scale spatial trends and nonspatial effects. A geospatial model of the Alaska boreal forest was developed from 446 permanent sample plots, which addressed large-scale spatial trends in recruitment, diameter growth, and mortality. The model was tested on two sets of...

Motor expertise and performance in spatial tasks: A meta-analysis.

PubMed

Voyer, Daniel; Jansen, Petra

2017-08-01

The present study aimed to provide a summary of findings relevant to the influence of motor expertise on performance in spatial tasks and to examine potential moderators of this effect. Studies of relevance were those in which individuals involved in activities presumed to require motor expertise were compared to non-experts in such activities. A final set of 62 effect sizes from 33 samples was included in a multilevel meta-analysis. The results showed an overall advantage in favor of motor experts in spatial tasks (d=0.38). However, the magnitude of that effect was moderated by expert type (athlete, open skills/ball sports, runner/cyclist, gymnast/dancers, musicians), stimulus type (2D, blocks, bodies, others), test category (mental rotation, spatial perception, spatial visualization), specific test (Mental Rotations Test, generic mental rotation, disembedding, rod-and-frame test, other), and publication status. These findings are discussed in the context of embodied cognition and the potential role of activities requiring motor expertise in promoting good spatial performance. Copyright © 2017 Elsevier B.V. All rights reserved.

[Sampling optimization for tropical invertebrates: an example using dung beetles (Coleoptera: Scarabaeinae) in Venezuela].

PubMed

Ferrer-Paris, José Rafael; Sánchez-Mercado, Ada; Rodríguez, Jon Paul

2013-03-01

The development of efficient sampling protocols is an essential prerequisite to evaluate and identify priority conservation areas. There are f ew protocols for fauna inventory and monitoring in wide geographical scales for the tropics, where the complexity of communities and high biodiversity levels, make the implementation of efficient protocols more difficult. We proposed here a simple strategy to optimize the capture of dung beetles, applied to sampling with baited traps and generalizable to other sampling methods. We analyzed data from eight transects sampled between 2006-2008 withthe aim to develop an uniform sampling design, that allows to confidently estimate species richness, abundance and composition at wide geographical scales. We examined four characteristics of any sampling design that affect the effectiveness of the sampling effort: the number of traps, sampling duration, type and proportion of bait, and spatial arrangement of the traps along transects. We used species accumulation curves, rank-abundance plots, indicator species analysis, and multivariate correlograms. We captured 40 337 individuals (115 species/morphospecies of 23 genera). Most species were attracted by both dung and carrion, but two thirds had greater relative abundance in traps baited with human dung. Different aspects of the sampling design influenced each diversity attribute in different ways. To obtain reliable richness estimates, the number of traps was the most important aspect. Accurate abundance estimates were obtained when the sampling period was increased, while the spatial arrangement of traps was determinant to capture the species composition pattern. An optimum sampling strategy for accurate estimates of richness, abundance and diversity should: (1) set 50-70 traps to maximize the number of species detected, (2) get samples during 48-72 hours and set trap groups along the transect to reliably estimate species abundance, (3) set traps in groups of at least 10 traps to suitably record the local species composition, and (4) separate trap groups by a distance greater than 5-10km to avoid spatial autocorrelation. For the evaluation of other sampling protocols we recommend to, first, identify the elements of sampling design that could affect the sampled effort (the number of traps, sampling duration, type and proportion of bait) and their spatial distribution (spatial arrangement of the traps) and then, to evaluate how they affect richness, abundance and species composition estimates.

Evaluating single-pass catch as a tool for identifying spatial pattern in fish distribution

USGS Publications Warehouse

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

2005-01-01

We evaluate the efficacy of single-pass electrofishing without blocknets as a tool for collecting spatially continuous fish distribution data in headwater streams. We compare spatial patterns in abundance, sampling effort, and length-frequency distributions from single-pass sampling of coastal cutthroat trout (Oncorhynchus clarki clarki) to data obtained from a more precise multiple-pass removal electrofishing method in two mid-sized (500–1000 ha) forested watersheds in western Oregon. Abundance estimates from single- and multiple-pass removal electrofishing were positively correlated in both watersheds, r = 0.99 and 0.86. There were no significant trends in capture probabilities at the watershed scale (P > 0.05). Moreover, among-sample variation in fish abundance was higher than within-sample error in both streams indicating that increased precision of unit-scale abundance estimates would provide less information on patterns of abundance than increasing the fraction of habitat units sampled. In the two watersheds, respectively, single-pass electrofishing captured 78 and 74% of the estimated population of cutthroat trout with 7 and 10% of the effort. At the scale of intermediate-sized watersheds, single-pass electrofishing exhibited a sufficient level of precision to be effective in detecting spatial patterns of cutthroat trout abundance and may be a useful tool for providing the context for investigating fish-habitat relationships at multiple scales.

Spatial distribution, sampling precision and survey design optimisation with non-normal variables: The case of anchovy (Engraulis encrasicolus) recruitment in Spanish Mediterranean waters

NASA Astrophysics Data System (ADS)

Tugores, M. Pilar; Iglesias, Magdalena; Oñate, Dolores; Miquel, Joan

2016-02-01

In the Mediterranean Sea, the European anchovy (Engraulis encrasicolus) displays a key role in ecological and economical terms. Ensuring stock sustainability requires the provision of crucial information, such as species spatial distribution or unbiased abundance and precision estimates, so that management strategies can be defined (e.g. fishing quotas, temporal closure areas or marine protected areas MPA). Furthermore, the estimation of the precision of global abundance at different sampling intensities can be used for survey design optimisation. Geostatistics provide a priori unbiased estimations of the spatial structure, global abundance and precision for autocorrelated data. However, their application to non-Gaussian data introduces difficulties in the analysis in conjunction with low robustness or unbiasedness. The present study applied intrinsic geostatistics in two dimensions in order to (i) analyse the spatial distribution of anchovy in Spanish Western Mediterranean waters during the species' recruitment season, (ii) produce distribution maps, (iii) estimate global abundance and its precision, (iv) analyse the effect of changing the sampling intensity on the precision of global abundance estimates and, (v) evaluate the effects of several methodological options on the robustness of all the analysed parameters. The results suggested that while the spatial structure was usually non-robust to the tested methodological options when working with the original dataset, it became more robust for the transformed datasets (especially for the log-backtransformed dataset). The global abundance was always highly robust and the global precision was highly or moderately robust to most of the methodological options, except for data transformation.

High-resolution room-temperature sample scanning superconducting quantum interference device microscope configurable for geological and biomagnetic applications

NASA Astrophysics Data System (ADS)

Fong, L. E.; Holzer, J. R.; McBride, K. K.; Lima, E. A.; Baudenbacher, F.; Radparvar, M.

2005-05-01

We have developed a scanning superconducting quantum interference device (SQUID) microscope system with interchangeable sensor configurations for imaging magnetic fields of room-temperature (RT) samples with submillimeter resolution. The low-critical-temperature (Tc) niobium-based monolithic SQUID sensors are mounted on the tip of a sapphire and thermally anchored to the helium reservoir. A 25μm sapphire window separates the vacuum space from the RT sample. A positioning mechanism allows us to adjust the sample-to-sensor spacing from the top of the Dewar. We achieved a sensor-to-sample spacing of 100μm, which could be maintained for periods of up to four weeks. Different SQUID sensor designs are necessary to achieve the best combination of spatial resolution and field sensitivity for a given source configuration. For imaging thin sections of geological samples, we used a custom-designed monolithic low-Tc niobium bare SQUID sensor, with an effective diameter of 80μm, and achieved a field sensitivity of 1.5pT/Hz1/2 and a magnetic moment sensitivity of 5.4×10-18Am2/Hz1/2 at a sensor-to-sample spacing of 100μm in the white noise region for frequencies above 100Hz. Imaging action currents in cardiac tissue requires a higher field sensitivity, which can only be achieved by compromising spatial resolution. We developed a monolithic low-Tc niobium multiloop SQUID sensor, with sensor sizes ranging from 250μm to 1mm, and achieved sensitivities of 480-180fT /Hz1/2 in the white noise region for frequencies above 100Hz, respectively. For all sensor configurations, the spatial resolution was comparable to the effective diameter and limited by the sensor-to-sample spacing. Spatial registration allowed us to compare high-resolution images of magnetic fields associated with action currents and optical recordings of transmembrane potentials to study the bidomain nature of cardiac tissue or to match petrography to magnetic field maps in thin sections of geological samples.

Persistence of Gender Related-Effects on Visuo-Spatial and Verbal Working Memory in Right Brain-Damaged Patients.

PubMed

Piccardi, Laura; Matano, Alessandro; D'Antuono, Giovanni; Marin, Dario; Ciurli, Paola; Incoccia, Chiara; Verde, Paola; Guariglia, Paola

2016-01-01

The aim of the present study was to verify if gender differences in verbal and visuo-spatial working memory would persist following right cerebral lesions. To pursue our aim we investigated a large sample (n. 346) of right brain-damaged patients and healthy participants (n. 272) for the presence of gender effects in performing Corsi and Digit Test. We also assessed a subgroup of patients (n. 109) for the nature (active vs. passive) of working memory tasks. We tested working memory (WM) administering the Corsi Test (CBT) and the Digit Span (DS) using two different versions: forward (fCBT and fDS), subjects were required to repeat stimuli in the same order that they were presented; and backward (bCBT and bDS), subjects were required to repeat stimuli in the opposite order of presentation. In this way, passive storage and active processing of working memory were assessed. Our results showed the persistence of gender-related effects in spite of the presence of right brain lesions. We found that men outperformed women both in CBT and DS, regardless of active and passive processing of verbal and visuo-spatial stimuli. The presence of visuo-spatial disorders (i.e., hemineglect) can affect the performance on Corsi Test. In our sample, men and women were equally affected by hemineglect, therefore it did not mask the gender effect. Generally speaking, the persistence of the men's superiority in visuo-spatial tasks may be interpreted as a protective factor, at least for men, within other life factors such as level of education or kind of profession before retirement.

OpenMSI Arrayed Analysis Toolkit: Analyzing Spatially Defined Samples Using Mass Spectrometry Imaging

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

de Raad, Markus; de Rond, Tristan; Rübel, Oliver

Mass spectrometry imaging (MSI) has primarily been applied in localizing biomolecules within biological matrices. Although well-suited, the application of MSI for comparing thousands of spatially defined spotted samples has been limited. One reason for this is a lack of suitable and accessible data processing tools for the analysis of large arrayed MSI sample sets. In this paper, the OpenMSI Arrayed Analysis Toolkit (OMAAT) is a software package that addresses the challenges of analyzing spatially defined samples in MSI data sets. OMAAT is written in Python and is integrated with OpenMSI (http://openmsi.nersc.gov), a platform for storing, sharing, and analyzing MSI data.more » By using a web-based python notebook (Jupyter), OMAAT is accessible to anyone without programming experience yet allows experienced users to leverage all features. OMAAT was evaluated by analyzing an MSI data set of a high-throughput glycoside hydrolase activity screen comprising 384 samples arrayed onto a NIMS surface at a 450 μm spacing, decreasing analysis time >100-fold while maintaining robust spot-finding. The utility of OMAAT was demonstrated for screening metabolic activities of different sized soil particles, including hydrolysis of sugars, revealing a pattern of size dependent activities. Finally, these results introduce OMAAT as an effective toolkit for analyzing spatially defined samples in MSI. OMAAT runs on all major operating systems, and the source code can be obtained from the following GitHub repository: https://github.com/biorack/omaat.« less

Wide-band tunable photonic bandgap device and laser in dye-doped liquid crystal refilled cholesteric liquid crystal polymer template system

NASA Astrophysics Data System (ADS)

Lin, Jia-De; Lin, Hong-Lin; Lin, Hsin-Yu; Wei, Guan-Jhong; Lee, Chia-Rong

2017-02-01

The scientists in the field of liquid crystal (LC) have paid significant attention in the exploration of novel cholesteric LC (CLC) polymer template (simply called template) in recent years. The self-assembling nanostructural template with chirality can effectively overcome the limitation in the optical features of traditional CLCs, such as enhancement of reflectivity over 50%, multiple photonic bandgaps (PBGs), and changeable optical characteristics by flexibly replacing the refilling LC materials, and so on. This work fabricates two gradient-pitched CLC templates with two opposite handednesses, which are then merged as a spatially tunable and highly reflective CLC template sample. This sample can simultaneously reflect right- and left-circularly polarized lights and the tunable spectral range includes the entire visible region. By increasing the temperature of the template sample exceeding the clearing point of the refilling LC, the light scattering significantly decreases and the reflectance effectively increase to exceed 50% in the entire visible region. This device has a maximum reflectance over 85% and a wide-band spatial tunability in PBG between 400 nm and 800 nm which covers the entire visible region. Not only the sample can be employed as a wide-band spatially tunable filter, but also the system doping with two suitable laser dyes which emitted fluorescence can cover entire visible region can develop a low-threshold, mirror-less laser with a spatial tunability at spectral regions including blue to red region (from 484 nm to 634 nm) and simultaneous lasing emission of left- and right-circular polarizations.

Single molecule tracking

DOEpatents

Shera, E. Brooks

1988-01-01

A detection system is provided for identifying individual particles or molecules having characteristic emission in a flow train of the particles in a flow cell. A position sensitive sensor is located adjacent the flow cell in a position effective to detect the emissions from the particles within the flow cell and to assign spatial and temporal coordinates for the detected emissions. A computer is then enabled to predict spatial and temporal coordinates for the particle in the flow train as a function of a first detected emission. Comparison hardware or software then compares subsequent detected spatial and temporal coordinates with the predicted spatial and temporal coordinates to determine whether subsequently detected emissions originate from a particle in the train of particles. In one embodiment, the particles include fluorescent dyes which are excited to fluoresce a spectrum characteristic of the particular particle. Photones are emitted adjacent at least one microchannel plate sensor to enable spatial and temporal coordinates to be assigned. The effect of comparing detected coordinates with predicted coordinates is to define a moving sample volume which effectively precludes the effects of background emissions.

Single molecule tracking

DOEpatents

Shera, E.B.

1987-10-07

A detection system is provided for identifying individual particles or molecules having characteristic emission in a flow train of the particles in a flow cell. A position sensitive sensor is located adjacent the flow cell in a position effective to detect the emissions from the particles within the flow cell and to assign spatial and temporal coordinates for the detected emissions. A computer is then enabled to predict spatial and temporal coordinates for the particle in the flow train as a function of a first detected emission. Comparison hardware or software then compares subsequent detected spatial and temporal coordinates with the predicted spatial and temporal coordinates to determine whether subsequently detected emissions originate from a particle in the train of particles. In one embodiment, the particles include fluorescent dyes which are excited to fluoresce a spectrum characteristic of the particular particle. Photons are emitted adjacent at least one microchannel plate sensor to enable spatial and temporal coordinates to be assigned. The effect of comparing detected coordinates with predicted coordinates is to define a moving sample volume which effectively precludes the effects of background emissions. 3 figs.

Statistical characteristics of the spatial distribution of territorial contamination by radionuclides from the Chernobyl accident

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

Arutyunyan, R.V.; Bol`shov, L.A.; Vasil`ev, S.K.

1994-06-01

The objective of this study was to clarify a number of issues related to the spatial distribution of contaminants from the Chernobyl accident. The effects of local statistics were addressed by collecting and analyzing (for Cesium 137) soil samples from a number of regions, and it was found that sample activity differed by a factor of 3-5. The effect of local non-uniformity was estimated by modeling the distribution of the average activity of a set of five samples for each of the regions, with the spread in the activities for a {+-}2 range being equal to 25%. The statistical characteristicsmore » of the distribution of contamination were then analyzed and found to be a log-normal distribution with the standard deviation being a function of test area. All data for the Bryanskaya Oblast area were analyzed statistically and were adequately described by a log-normal function.« less

Hybrid Optimal Design of the Eco-Hydrological Wireless Sensor Network in the Middle Reach of the Heihe River Basin, China

PubMed Central

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-01-01

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables. PMID:25317762

Hybrid optimal design of the eco-hydrological wireless sensor network in the middle reach of the Heihe River Basin, China.

PubMed

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-10-14

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables.

Optimization-Based Approach for Joint X-Ray Fluorescence and Transmission Tomographic Inversion

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

Di, Zichao; Leyffer, Sven; Wild, Stefan M.

2016-01-01

Fluorescence tomographic reconstruction, based on the detection of photons coming from fluorescent emission, can be used for revealing the internal elemental composition of a sample. On the other hand, conventional X-ray transmission tomography can be used for reconstructing the spatial distribution of the absorption coefficient inside a sample. In this work, we integrate both X-ray fluorescence and X-ray transmission data modalities and formulate a nonlinear optimization-based approach for reconstruction of the elemental composition of a given object. This model provides a simultaneous reconstruction of both the quantitative spatial distribution of all elements and the absorption effect in the sample. Mathematicallymore » speaking, we show that compared with the single-modality inversion (i.e., the X-ray transmission or fluorescence alone), the joint inversion provides a better-posed problem, which implies a better recovery. Therefore, the challenges in X-ray fluorescence tomography arising mainly from the effects of self-absorption in the sample are partially mitigated. The use of this technique is demonstrated on the reconstruction of several synthetic samples.« less

Impact of Spatial Sampling on Continuity of MODIS-VIIRS Land Surface Reflectance Products: A Simulation Approach

NASA Technical Reports Server (NTRS)

Pahlevan, Nima; Sarkar, Sudipta; Devadiga, Sadashiva; Wolfe, Robert E.; Roman, Miguel; Vermote, Eric; Lin, Guoqing; Xiong, Xiaoxiong

2016-01-01

With the increasing need to construct long-term climate-quality data records to understand, monitor, and predict climate variability and change, it is vital to continue systematic satellite measurements along with the development of new technology for more quantitative and accurate observations. The Suomi National Polar-orbiting Partnership mission provides continuity in monitoring the Earths surface and its atmosphere in a similar fashion as the heritage MODIS instruments onboard the National Aeronautics and Space Administrations Terra and Aqua satellites. In this paper, we aim at quantifying the consistency of Aqua MODIS and Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Reflectance (LSR) and NDVI products as related to their inherent spatial sampling characteristics. To avoid interferences from sources of measurement and/or processing errors other than spatial sampling, including calibration, atmospheric correction, and the effects of the bidirectional reflectance distribution function, the MODIS and VIIRSLSR products were simulated using the Landsat-8s Operational Land Imager (OLI) LSR products. The simulations were performed using the instruments point spread functions on a daily basis for various OLI scenes over a 16-day orbit cycle. It was found that the daily mean differences due to discrepancies in spatial sampling remain below 0.0015 (1) in absolute surface reflectance at subgranule scale (i.e., OLI scene size).We also found that the MODISVIIRS product intercomparisons appear to be minimally impacted when differences in the corresponding view zenith angles (VZAs) are within the range of -15deg to -35deg (VZA(sub v) - VZA(sub m)), where VIIRS and MODIS footprints resemble in size. In general, depending on the spatial heterogeneity of the OLI scene contents, per-grid-cell differences can reach up to 20.Further spatial analysis of the simulated NDVI and LSR products revealed that, depending on the user accuracy requirements for product intercomparisons, spatial aggregations may be used. It was found that if per-grid-cell differences on the order of 10(in LSR or NDVI) are tolerated, the product intercomparisons are expected to be immune from differences in spatial sampling.

Spatial profile of thermoelectric effects during Peltier pulsing in Bi and Bi/MnBi eutectic

NASA Technical Reports Server (NTRS)

Silberstein, R. P.; Larson, D. J., Jr.

1987-01-01

The spatial profile of the thermal transients that occur during and following the current pulsing associated with Peltier Interface Demarcation during directional solidification is studied. Results for pure Bi are presented in detail and compared with corresponding results for the Bi/MnBi eutectic. Significant thermal transients occur throughout the sample that can be accounted for by the Peltier effect, the Thomson effect, and Joule heating. These effects are separated and their behavior is studied as a function of time, current density, and position with respect to the solid/liquid interface.

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.

Taking a statistical approach

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

Wild, M.; Rouhani, S.

1995-02-01

A typical site investigation entails extensive sampling and monitoring. In the past, sampling plans have been designed on purely ad hoc bases, leading to significant expenditures and, in some cases, collection of redundant information. In many instances, sampling costs exceed the true worth of the collected data. The US Environmental Protection Agency (EPA) therefore has advocated the use of geostatistics to provide a logical framework for sampling and analysis of environmental data. Geostatistical methodology uses statistical techniques for the spatial analysis of a variety of earth-related data. The use of geostatistics was developed by the mining industry to estimate oremore » concentrations. The same procedure is effective in quantifying environmental contaminants in soils for risk assessments. Unlike classical statistical techniques, geostatistics offers procedures to incorporate the underlying spatial structure of the investigated field. Sample points spaced close together tend to be more similar than samples spaced further apart. This can guide sampling strategies and determine complex contaminant distributions. Geostatistic techniques can be used to evaluate site conditions on the basis of regular, irregular, random and even spatially biased samples. In most environmental investigations, it is desirable to concentrate sampling in areas of known or suspected contamination. The rigorous mathematical procedures of geostatistics allow for accurate estimates at unsampled locations, potentially reducing sampling requirements. The use of geostatistics serves as a decision-aiding and planning tool and can significantly reduce short-term site assessment costs, long-term sampling and monitoring needs, as well as lead to more accurate and realistic remedial design criteria.« less

Spatial and Temporal Monitoring Resolutions for CO2 Leakage Detection at Carbon Storage Sites

NASA Astrophysics Data System (ADS)

Yang, Y. M.; Dilmore, R. M.; Daley, T. M.; Carroll, S.; Mansoor, K.; Gasperikova, E.; Harbert, W.; Wang, Z.; Bromhal, G. S.; Small, M.

2016-12-01

Different leakage monitoring techniques offer different strengths in detection sensitivity, coverage, feedback time, cost, and technology availability, such that they may complement each other when applied together. This research focuses on quantifying the spatial coverage and temporal resolution of detection response for several geophysical remote monitoring and direct groundwater monitoring techniques for an optimal monitoring plan for CO2 leakage detection. Various monitoring techniques with different monitoring depths are selected: 3D time-lapse seismic survey, wellbore pressure, groundwater chemistry and soil gas. The spatial resolution in terms of leakage detectability is quantified through the effective detection distance between two adjacent monitors, given the magnitude of leakage and specified detection probability. The effective detection distances are obtained either from leakage simulations with various monitoring densities or from information garnered from field test data. These spatial leakage detection resolutions are affected by physically feasible monitoring design and detection limits. Similarly, the temporal resolution, in terms of leakage detectability, is quantified through the effective time to positive detection of a given size of leak and a specified detection probability, again obtained either from representative leakage simulations with various monitoring densities or from field test data. The effective time to positive detection is also affected by operational feedback time (associated with sampling, sample analysis and data interpretation), with values obtained mainly through expert interviews and literature review. In additional to the spatial and temporal resolutions of these monitoring techniques, the impact of CO2 plume migration speed and leakage detection sensitivity of each monitoring technique are also discussed with consideration of how much monitoring is necessary for effective leakage detection and how these monitoring techniques can be better combined in a time-space framework. The results of the spatial and temporal leakage detection resolutions for several geophysical monitoring techniques and groundwater monitoring are summarized to inform future monitoring designs at carbon storage sites.

PAHs and PCBs in an Eastern Mediterranean megacity, Istanbul: Their spatial and temporal distributions, air-soil exchange and toxicological effects.

PubMed

Cetin, Banu; Ozturk, Fatma; Keles, Melek; Yurdakul, Sema

2017-01-01

Istanbul, one of the mega cities in the world located between Asia and Europe, has suffered from severe air pollution problems due to rapid population growth, traffic and industry. Atmospheric levels of PAHs and PCBs were investigated in Istanbul at 22 sampling sites during four different sampling periods using PUF disk passive air samplers and spatial and temporal variations of these chemicals were determined. Soil samples were also taken at the air sampling sites. At all sites, the average ambient air Σ 15 PAH and Σ 41 PCB concentrations were found as 85.6 ± 68.3 ng m -3 and 246 ± 122 pg m -3 , respectively. Phenanthrene and anthracene were the predominant PAHs and low molecular weight congeners dominated the PCBs. The PAH concentrations were higher especially at urban sites close to highways. However, the PCBs showed moderately uniform spatial variations. Except four sites, the PAH concentrations were increased with decreasing temperatures during the sampling period, indicating the contributions of combustion sources for residential heating, while PCB concentrations were mostly increased with the temperature, probably due to enhanced volatilization at higher temperatures from their sources. The results of the Factor Analysis represented the impact of traffic, petroleum, coal/biomass and natural gas combustion and medical waste incineration plants on ambient air concentrations. A similar spatial distribution trend was observed in the soil samples. Fugacity ratio results indicated that the source/sink tendency of soil for PAHs and PCBs depends on their volatility and temperature; soil generally acts as a source for lighter PAHs and PCBs particularly in higher temperatures while atmospheric deposition is a main source for higher molecular weight compounds in local soils. Toxicological effect studies also revealed the severity of air and soil pollution especially in terms of PAHs in Istanbul. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Variable Grid Method, an Approach for the Simultaneous Visualization and Assessment of Spatial Trends and Uncertainty

NASA Astrophysics Data System (ADS)

Rose, K.; Glosser, D.; Bauer, J. R.; Barkhurst, A.

2015-12-01

The products of spatial analyses that leverage the interpolation of sparse, point data to represent continuous phenomena are often presented without clear explanations of the uncertainty associated with the interpolated values. As a result, there is frequently insufficient information provided to effectively support advanced computational analyses and individual research and policy decisions utilizing these results. This highlights the need for a reliable approach capable of quantitatively producing and communicating spatial data analyses and their inherent uncertainties for a broad range of uses. To address this need, we have developed the Variable Grid Method (VGM), and associated Python tool, which is a flexible approach that can be applied to a variety of analyses and use case scenarios where users need a method to effectively study, evaluate, and analyze spatial trends and patterns while communicating the uncertainty in the underlying spatial datasets. The VGM outputs a simultaneous visualization representative of the spatial data analyses and quantification of underlying uncertainties, which can be calculated using data related to sample density, sample variance, interpolation error, uncertainty calculated from multiple simulations, etc. We will present examples of our research utilizing the VGM to quantify key spatial trends and patterns for subsurface data interpolations and their uncertainties and leverage these results to evaluate storage estimates and potential impacts associated with underground injection for CO2 storage and unconventional resource production and development. The insights provided by these examples identify how the VGM can provide critical information about the relationship between uncertainty and spatial data that is necessary to better support their use in advance computation analyses and informing research, management and policy decisions.

HydroCrowd: a citizen science snapshot to assess the spatial control of nitrogen solutes in surface waters

PubMed Central

Breuer, Lutz; Hiery, Noreen; Kraft, Philipp; Bach, Martin; Aubert, Alice H.; Frede, Hans-Georg

2015-01-01

We organized a crowdsourcing experiment in the form of a snapshot sampling campaign to assess the spatial distribution of nitrogen solutes, namely, nitrate, ammonium and dissolved organic nitrogen (DON), in German surface waters. In particular, we investigated (i) whether crowdsourcing is a reasonable sampling method in hydrology and (ii) what the effects of population density, soil humus content and arable land were on actual nitrogen solute concentrations and surface water quality. The statistical analyses revealed a significant correlation between nitrate and arable land (0.46), as well as soil humus content (0.37) but a weak correlation with population density (0.12). DON correlations were weak but significant with humus content (0.14) and arable land (0.13). The mean contribution of DON to total dissolved nitrogen was 22%. Samples were classified as water quality class II or above, following the European Water Framework Directive for nitrate and ammonium (53% and 82%, respectively). Crowdsourcing turned out to be a useful method to assess the spatial distribution of stream solutes, as considerable amounts of samples were collected with comparatively little effort. PMID:26561200

Multiobjective design of aquifer monitoring networks for optimal spatial prediction and geostatistical parameter estimation

NASA Astrophysics Data System (ADS)

Alzraiee, Ayman H.; Bau, Domenico A.; Garcia, Luis A.

2013-06-01

Effective sampling of hydrogeological systems is essential in guiding groundwater management practices. Optimal sampling of groundwater systems has previously been formulated based on the assumption that heterogeneous subsurface properties can be modeled using a geostatistical approach. Therefore, the monitoring schemes have been developed to concurrently minimize the uncertainty in the spatial distribution of systems' states and parameters, such as the hydraulic conductivity K and the hydraulic head H, and the uncertainty in the geostatistical model of system parameters using a single objective function that aggregates all objectives. However, it has been shown that the aggregation of possibly conflicting objective functions is sensitive to the adopted aggregation scheme and may lead to distorted results. In addition, the uncertainties in geostatistical parameters affect the uncertainty in the spatial prediction of K and H according to a complex nonlinear relationship, which has often been ineffectively evaluated using a first-order approximation. In this study, we propose a multiobjective optimization framework to assist the design of monitoring networks of K and H with the goal of optimizing their spatial predictions and estimating the geostatistical parameters of the K field. The framework stems from the combination of a data assimilation (DA) algorithm and a multiobjective evolutionary algorithm (MOEA). The DA algorithm is based on the ensemble Kalman filter, a Monte-Carlo-based Bayesian update scheme for nonlinear systems, which is employed to approximate the posterior uncertainty in K, H, and the geostatistical parameters of K obtained by collecting new measurements. Multiple MOEA experiments are used to investigate the trade-off among design objectives and identify the corresponding monitoring schemes. The methodology is applied to design a sampling network for a shallow unconfined groundwater system located in Rocky Ford, Colorado. Results indicate that the effect of uncertainties associated with the geostatistical parameters on the spatial prediction might be significantly alleviated (by up to 80% of the prior uncertainty in K and by 90% of the prior uncertainty in H) by sampling evenly distributed measurements with a spatial measurement density of more than 1 observation per 60 m × 60 m grid block. In addition, exploration of the interaction of objective functions indicates that the ability of head measurements to reduce the uncertainty associated with the correlation scale is comparable to the effect of hydraulic conductivity measurements.

Assessing the effects of land use changes on soil sensitivity to erosion in a highland ecosystem of semi-arid Turkey.

PubMed

Bayramin, Ilhami; Basaran, Mustafa; Erpul, Günay; Canga, Mustafa R

2008-05-01

There has been increasing concern in highlands of semiarid Turkey that conversion of these systems results in excessive soil erosion, ecosystem degradation, and loss of sustainable resources. An increasing rate of land use/cover changes especially in semiarid mountainous areas has resulted in important effects on physical and ecological processes, causing many regions to undergo accelerated environmental degradation in terms of soil erosion, mass movement and reservoir sedimentation. This paper, therefore, explores the impact of land use changes on land degradation in a linkage to the soil erodibility, RUSLE-K, in Cankiri-Indagi Mountain Pass, Turkey. The characterization of soil erodibility in this ecosystem is important from the standpoint of conserving fragile ecosystems and planning management practices. Five adjacent land uses (cropland, grassland, woodland, plantation, and recreational land) were selected for this research. Analysis of variance showed that soil properties and RUSLE-K statistically changed with land use changes and soils of the recreational land and cropland were more sensitive to water erosion than those of the woodland, grassland, and plantation. This was mainly due to the significant decreases in soil organic matter (SOM) and hydraulic conductivity (HC) in those lands. Additionally, soil samples randomly collected from the depths of 0-10 cm (D1) and 10-20 cm (D2) with irregular intervals in an area of 1,200 by 4,200 m sufficiently characterized not only the spatial distribution of soil organic matter (SOM), hydraulic conductivity (HC), clay (C), silt (Si), sand (S) and silt plus very fine sand (Si + VFS) but also the spatial distribution of RUSLE-K as an algebraically estimate of these parameters together with field assessment of soil structure to assess the dynamic relationships between soil properties and land use types. In this study, in order to perform the spatial analyses, the mean sampling intervals were 43, 50, 64, 78, 85 m for woodland, plantation, grassland, recreation, and cropland with the sample numbers of 56, 79, 72, 13, and 69, respectively, resulting in an average interval of 64 m for whole study area. Although nugget effect and nugget effect-sill ratio gave an idea about the sampling design adequacy, the better results are undoubtedly likely by both equi-probable spatial sampling and random sampling representative of all land uses.

Longitudinal spatial coherence gated high-resolution tomography and quantitative phase microscopy of biological cells and tissues with uniform illumination

NASA Astrophysics Data System (ADS)

Mehta, Dalip Singh; Ahmad, Azeem; Dubey, Vishesh; Singh, Veena; Butola, Ankit; Mohanty, Tonmoy; Nandi, Sreyankar

2018-02-01

We report longitudinal spatial coherence (LSC) gated high-resolution tomography and quantitative phase microscopy of biological cells and tissues with uniform illumination using laser as a light source. To accomplish this a pseudo thermal light source was synthesized by passing laser beams through an optical system, which is basically a speckle reduction system with combined effect of spatial, temporal, angular and polarisation diversity. The longitudinal spatial coherence length of such light was significantly reduced by synthesizing a pseudo thermal source with the combined effect of spatial, angular and temporal diversity. This results in a low spatially coherent (i.e., broad angular frequency spectrum) light source with narrow temporal frequency spectrum. Light from such a pseudo thermal light source was passed through an interference microscope with varying magnification, such as, 10X and 50X. The interference microscope was used for full-field OCT imaging of multilayer objects and topography of industrial objects. Experimental results of optical sectioning of multilayer biological objects with high axial-resolution less than 10μm was achieved which is comparable to broadband white light source. The synthesized light source with reduced speckles having uniform illumination on the sample, which can be very useful for fluorescence microscopy as well as quantitative phase microscopy with less phase noise. The present system does not require any dispersion compensation optical system for biological samples as a highly monochromatic light source is used.

Towards the Development of a More Accurate Monitoring Procedure for Invertebrate Populations, in the Presence of an Unknown Spatial Pattern of Population Distribution in the Field

PubMed Central

Petrovskaya, Natalia B.; Forbes, Emily; Petrovskii, Sergei V.; Walters, Keith F. A.

2018-01-01

Studies addressing many ecological problems require accurate evaluation of the total population size. In this paper, we revisit a sampling procedure used for the evaluation of the abundance of an invertebrate population from assessment data collected on a spatial grid of sampling locations. We first discuss how insufficient information about the spatial population density obtained on a coarse sampling grid may affect the accuracy of an evaluation of total population size. Such information deficit in field data can arise because of inadequate spatial resolution of the population distribution (spatially variable population density) when coarse grids are used, which is especially true when a strongly heterogeneous spatial population density is sampled. We then argue that the average trap count (the quantity routinely used to quantify abundance), if obtained from a sampling grid that is too coarse, is a random variable because of the uncertainty in sampling spatial data. Finally, we show that a probabilistic approach similar to bootstrapping techniques can be an efficient tool to quantify the uncertainty in the evaluation procedure in the presence of a spatial pattern reflecting a patchy distribution of invertebrates within the sampling grid. PMID:29495513

Effects of spatial heterogeneity on butterfly species richness in Rocky Mountain National Park, CO, USA

USGS Publications Warehouse

Kumar, S.; Simonson, S.E.; Stohlgren, T.J.

2009-01-01

We investigated butterfly responses to plot-level characteristics (plant species richness, vegetation height, and range in NDVI [normalized difference vegetation index]) and spatial heterogeneity in topography and landscape patterns (composition and configuration) at multiple spatial scales. Stratified random sampling was used to collect data on butterfly species richness from seventy-six 20 ?? 50 m plots. The plant species richness and average vegetation height data were collected from 76 modified-Whittaker plots overlaid on 76 butterfly plots. Spatial heterogeneity around sample plots was quantified by measuring topographic variables and landscape metrics at eight spatial extents (radii of 300, 600 to 2,400 m). The number of butterfly species recorded was strongly positively correlated with plant species richness, proportion of shrubland and mean patch size of shrubland. Patterns in butterfly species richness were negatively correlated with other variables including mean patch size, average vegetation height, elevation, and range in NDVI. The best predictive model selected using Akaike's Information Criterion corrected for small sample size (AICc), explained 62% of the variation in butterfly species richness at the 2,100 m spatial extent. Average vegetation height and mean patch size were among the best predictors of butterfly species richness. The models that included plot-level information and topographic variables explained relatively less variation in butterfly species richness, and were improved significantly after including landscape metrics. Our results suggest that spatial heterogeneity greatly influences patterns in butterfly species richness, and that it should be explicitly considered in conservation and management actions. ?? 2008 Springer Science+Business Media B.V.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

PubMed

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

PubMed Central

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points. PMID:26807579

Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization

PubMed Central

2017-01-01

Synchronization of population dynamics in different habitats is a frequently observed phenomenon. A common mathematical tool to reveal synchronization is the (cross)correlation coefficient between time courses of values of the population size of a given species where the population size is evaluated from spatial sampling data. The corresponding sampling net or grid is often coarse, i.e. it does not resolve all details of the spatial configuration, and the evaluation error—i.e. the difference between the true value of the population size and its estimated value—can be considerable. We show that this estimation error can make the value of the correlation coefficient very inaccurate or even irrelevant. We consider several population models to show that the value of the correlation coefficient calculated on a coarse sampling grid rarely exceeds 0.5, even if the true value is close to 1, so that the synchronization is effectively lost. We also observe ‘ghost synchronization’ when the correlation coefficient calculated on a coarse sampling grid is close to 1 but in reality the dynamics are not correlated. Finally, we suggest a simple test to check the sampling grid coarseness and hence to distinguish between the true and artifactual values of the correlation coefficient. PMID:28202589

Sampling design optimization for spatial functions

USGS Publications Warehouse

Olea, R.A.

1984-01-01

A new procedure is presented for minimizing the sampling requirements necessary to estimate a mappable spatial function at a specified level of accuracy. The technique is based on universal kriging, an estimation method within the theory of regionalized variables. Neither actual implementation of the sampling nor universal kriging estimations are necessary to make an optimal design. The average standard error and maximum standard error of estimation over the sampling domain are used as global indices of sampling efficiency. The procedure optimally selects those parameters controlling the magnitude of the indices, including the density and spatial pattern of the sample elements and the number of nearest sample elements used in the estimation. As an illustration, the network of observation wells used to monitor the water table in the Equus Beds of Kansas is analyzed and an improved sampling pattern suggested. This example demonstrates the practical utility of the procedure, which can be applied equally well to other spatial sampling problems, as the procedure is not limited by the nature of the spatial function. ?? 1984 Plenum Publishing Corporation.

Spatial Variation of Selenium in Appalachian Coal Seams

NASA Astrophysics Data System (ADS)

Le, L.; Tyner, J. S.; Perfect, E.; Yoder, D. C.

2013-12-01

The potential environmental impacts from coal extraction have led to many investigations of the geochemistry of coal. Previous studies have shown that selenium (Se) is an environmental contaminant due to its mutagenic effects on sensitive macro-organisms as a result of bioaccumulation in affected waters. Some regulatory authorities have responded by requiring the sampling of coal seams and adjacent rock for Se prior to authorizing a given coal mining permit. In at least one case, a single continuous rock core was sampled for Se to determine the threshold of Se across a 2.2 square kilometer proposed surface coal mine. To examine the adequacy of such an approach, we investigated the spatial variability and correlation of a West Virginia Geological and Economic Survey (WVGES) dataset of Se concentrations from coal seams collected within Appalachia (1088 samples). We conducted semi-variogram and Kriging cross-validation analyses on six coal seams from the dataset. Our findings suggest no significant spatial correlation of Se within a given coal seam.

Ecology of coarse wood decomposition by the saprotrophic fungus Fomes fomentarius.

PubMed

Větrovský, Tomáš; Voříšková, Jana; Snajdr, Jaroslav; Gabriel, Jiří; Baldrian, Petr

2011-07-01

Saprotrophic wood-inhabiting basidiomycetes are the most important decomposers of lignin and cellulose in dead wood and as such they attracted considerable attention. The aims of this work were to quantify the activity and spatial distribution of extracellular enzymes in coarse wood colonised by the white-rot basidiomycete Fomes fomentarius and in adjacent fruitbodies of the fungus and to analyse the diversity of the fungal and bacterial community in a fungus-colonised wood and its potential effect on enzyme production by F. fomentarius. Fungus-colonised wood and fruitbodies were collected in low management intensity forests in the Czech Republic. There were significant differences in enzyme production by F. fomentarius between Betula pendula and Fagus sylvatica wood, the activity of cellulose and xylan-degrading enzymes was significantly higher in beech wood than in birch wood. Spatial analysis of a sample B. pendula log segment proved that F. fomentarius was the single fungal representative found in the log. There was a high level of spatial variability in the amount of fungal biomass detected, but no effects on enzyme activities were observed. Samples from the fruiting body showed high β-glucosidase and chitinase activities compared to wood samples. Significantly higher levels of xylanase and cellobiohydrolase were found in samples located near the fruitbody (proximal), and higher laccase and Mn-peroxidase activities were found in the distal ones. The microbial community in wood was dominated by the fungus (fungal to bacterial DNA ratio of 62-111). Bacterial abundance composition was lower in proximal than distal parts of wood by a factor of 24. These results show a significant level of spatial heterogeneity in coarse wood. One of the explanations may be the successive colonization of wood by the fungus: due to differential enzyme production, the rates of biodegradation of coarse wood are also spatially inhomogeneous.

Sound-field measurement with moving microphones

PubMed Central

Katzberg, Fabrice; Mazur, Radoslaw; Maass, Marco; Koch, Philipp; Mertins, Alfred

2017-01-01

Closed-room scenarios are characterized by reverberation, which decreases the performance of applications such as hands-free teleconferencing and multichannel sound reproduction. However, exact knowledge of the sound field inside a volume of interest enables the compensation of room effects and allows for a performance improvement within a wide range of applications. The sampling of sound fields involves the measurement of spatially dependent room impulse responses, where the Nyquist-Shannon sampling theorem applies in the temporal and spatial domains. The spatial measurement often requires a huge number of sampling points and entails other difficulties, such as the need for exact calibration of a large number of microphones. In this paper, a method for measuring sound fields using moving microphones is presented. The number of microphones is customizable, allowing for a tradeoff between hardware effort and measurement time. The goal is to reconstruct room impulse responses on a regular grid from data acquired with microphones between grid positions, in general. For this, the sound field at equidistant positions is related to the measurements taken along the microphone trajectories via spatial interpolation. The benefits of using perfect sequences for excitation, a multigrid recovery, and the prospects for reconstruction by compressed sensing are presented. PMID:28599533

Application of spatially gridded temperature and land cover data sets for urban heat island analysis

USGS Publications Warehouse

Gallo, Kevin; Xian, George Z.

2014-01-01

Two gridded data sets that included (1) daily mean temperatures from 2006 through 2011 and (2) satellite-derived impervious surface area, were combined for a spatial analysis of the urban heat-island effect within the Dallas-Ft. Worth Texas region. The primary advantage of using these combined datasets included the capability to designate each 1 × 1 km grid cell of available temperature data as urban or rural based on the level of impervious surface area within the grid cell. Generally, the observed differences in urban and rural temperature increased as the impervious surface area thresholds used to define an urban grid cell were increased. This result, however, was also dependent on the size of the sample area included in the analysis. As the spatial extent of the sample area increased and included a greater number of rural defined grid cells, the observed urban and rural differences in temperature also increased. A cursory comparison of the spatially gridded temperature observations with observations from climate stations suggest that the number and location of stations included in an urban heat island analysis requires consideration to assure representative samples of each (urban and rural) environment are included in the analysis.

Assessing the spatial distribution of Tuta absoluta (Lepidoptera: Gelechiidae) eggs in open-field tomato cultivation through geostatistical analysis.

PubMed

Martins, Júlio C; Picanço, Marcelo C; Silva, Ricardo S; Gonring, Alfredo Hr; Galdino, Tarcísio Vs; Guedes, Raul Nc

2018-01-01

The spatial distribution of insects is due to the interaction between individuals and the environment. Knowledge about the within-field pattern of spatial distribution of a pest is critical to planning control tactics, developing efficient sampling plans, and predicting pest damage. The leaf miner Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) is the main pest of tomato crops in several regions of the world. Despite the importance of this pest, the pattern of spatial distribution of T. absoluta on open-field tomato cultivation remains unknown. Therefore, this study aimed to characterize the spatial distribution of T. absoluta in 22 commercial open-field tomato cultivations with plants at the three phenological development stages by using geostatistical analysis. Geostatistical analysis revealed that there was strong evidence for spatially dependent (aggregated) T. absoluta eggs in 19 of the 22 sample tomato cultivations. The maps that were obtained demonstrated the aggregated structure of egg densities at the edges of the crops. Further, T. absoluta was found to accomplish egg dispersal along the rows more frequently than it does between rows. Our results indicate that the greatest egg densities of T. absoluta occur at the edges of tomato crops. These results are discussed in relation to the behavior of T. absoluta distribution within fields and in terms of their implications for improved sampling guidelines and precision targeting control methods that are essential for effective pest monitoring and management. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Object-based vegetation classification with high resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Yu, Qian

Vegetation species are valuable indicators to understand the earth system. Information from mapping of vegetation species and community distribution at large scales provides important insight for studying the phenological (growth) cycles of vegetation and plant physiology. Such information plays an important role in land process modeling including climate, ecosystem and hydrological models. The rapidly growing remote sensing technology has increased its potential in vegetation species mapping. However, extracting information at a species level is still a challenging research topic. I proposed an effective method for extracting vegetation species distribution from remotely sensed data and investigated some ways for accuracy improvement. The study consists of three phases. Firstly, a statistical analysis was conducted to explore the spatial variation and class separability of vegetation as a function of image scale. This analysis aimed to confirm that high resolution imagery contains the information on spatial vegetation variation and these species classes can be potentially separable. The second phase was a major effort in advancing classification by proposing a method for extracting vegetation species from high spatial resolution remote sensing data. The proposed classification employs an object-based approach that integrates GIS and remote sensing data and explores the usefulness of ancillary information. The whole process includes image segmentation, feature generation and selection, and nearest neighbor classification. The third phase introduces a spatial regression model for evaluating the mapping quality from the above vegetation classification results. The effects of six categories of sample characteristics on the classification uncertainty are examined: topography, sample membership, sample density, spatial composition characteristics, training reliability and sample object features. This evaluation analysis answered several interesting scientific questions such as (1) whether the sample characteristics affect the classification accuracy and how significant if it does; (2) how much variance of classification uncertainty can be explained by above factors. This research is carried out on a hilly peninsular area in Mediterranean climate, Point Reyes National Seashore (PRNS) in Northern California. The area mainly consists of a heterogeneous, semi-natural broadleaf and conifer woodland, shrub land, and annual grassland. A detailed list of vegetation alliances is used in this study. Research results from the first phase indicates that vegetation spatial variation as reflected by the average local variance (ALV) keeps a high level of magnitude between 1 m and 4 m resolution. (Abstract shortened by UMI.)

Sampling design for spatially distributed hydrogeologic and environmental processes

USGS Publications Warehouse

Christakos, G.; Olea, R.A.

1992-01-01

A methodology for the design of sampling networks over space is proposed. The methodology is based on spatial random field representations of nonhomogeneous natural processes, and on optimal spatial estimation techniques. One of the most important results of random field theory for physical sciences is its rationalization of correlations in spatial variability of natural processes. This correlation is extremely important both for interpreting spatially distributed observations and for predictive performance. The extent of site sampling and the types of data to be collected will depend on the relationship of subsurface variability to predictive uncertainty. While hypothesis formulation and initial identification of spatial variability characteristics are based on scientific understanding (such as knowledge of the physics of the underlying phenomena, geological interpretations, intuition and experience), the support offered by field data is statistically modelled. This model is not limited by the geometric nature of sampling and covers a wide range in subsurface uncertainties. A factorization scheme of the sampling error variance is derived, which possesses certain atttactive properties allowing significant savings in computations. By means of this scheme, a practical sampling design procedure providing suitable indices of the sampling error variance is established. These indices can be used by way of multiobjective decision criteria to obtain the best sampling strategy. Neither the actual implementation of the in-situ sampling nor the solution of the large spatial estimation systems of equations are necessary. The required values of the accuracy parameters involved in the network design are derived using reference charts (readily available for various combinations of data configurations and spatial variability parameters) and certain simple yet accurate analytical formulas. Insight is gained by applying the proposed sampling procedure to realistic examples related to sampling problems in two dimensions. ?? 1992.

Persistence of Gender Related-Effects on Visuo-Spatial and Verbal Working Memory in Right Brain-Damaged Patients

PubMed Central

Piccardi, Laura; Matano, Alessandro; D’Antuono, Giovanni; Marin, Dario; Ciurli, Paola; Incoccia, Chiara; Verde, Paola; Guariglia, Paola

2016-01-01

The aim of the present study was to verify if gender differences in verbal and visuo-spatial working memory would persist following right cerebral lesions. To pursue our aim we investigated a large sample (n. 346) of right brain-damaged patients and healthy participants (n. 272) for the presence of gender effects in performing Corsi and Digit Test. We also assessed a subgroup of patients (n. 109) for the nature (active vs. passive) of working memory tasks. We tested working memory (WM) administering the Corsi Test (CBT) and the Digit Span (DS) using two different versions: forward (fCBT and fDS), subjects were required to repeat stimuli in the same order that they were presented; and backward (bCBT and bDS), subjects were required to repeat stimuli in the opposite order of presentation. In this way, passive storage and active processing of working memory were assessed. Our results showed the persistence of gender-related effects in spite of the presence of right brain lesions. We found that men outperformed women both in CBT and DS, regardless of active and passive processing of verbal and visuo-spatial stimuli. The presence of visuo-spatial disorders (i.e., hemineglect) can affect the performance on Corsi Test. In our sample, men and women were equally affected by hemineglect, therefore it did not mask the gender effect. Generally speaking, the persistence of the men’s superiority in visuo-spatial tasks may be interpreted as a protective factor, at least for men, within other life factors such as level of education or kind of profession before retirement. PMID:27445734

[Spatial distribution and scale effect of species diversity of secondary forests in montane region of eastern Liaoning Province, China.

PubMed

Deng, Li Ping; Bai, Xue Jiao; Qin, Sheng Jin; Wei, Ya Wei; Zhou, Yong Bin; Li, Lu Lu; Niu, Sha Sha; Han, Mei Na

2016-07-01

With secondary forest in the montane region of eastern Liaoning Province as research object, this paper analyzed the spatial distribution and scale effect of Gleason richness index, Simpson dominance index, Shannon diversity index and Pielou evenness index in a 4 hm 2 plot. The results showed that spatial distributions of the four diversity indices showed higher spatial heterogeneity. Variance of the four diversity indices varied with increasing scale. Coefficients of variation of the four diversity indices decreased with increasing scale. The four diversity indices of the tree layer were higher than those of the shrub layer, and the variation tendency varied with increasing scale. The results indicated that sampling scale should be taken into account when studying species diversity in the montane region of eastern Liaoning Province.

Exploring the spatially varying innovation capacity of the US counties in the framework of Griliches' knowledge production function: a mixed GWR approach

NASA Astrophysics Data System (ADS)

Kang, Dongwoo; Dall'erba, Sandy

2016-04-01

Griliches' knowledge production function has been increasingly adopted at the regional level where location-specific conditions drive the spatial differences in knowledge creation dynamics. However, the large majority of such studies rely on a traditional regression approach that assumes spatially homogenous marginal effects of knowledge input factors. This paper extends the authors' previous work (Kang and Dall'erba in Int Reg Sci Rev, 2015. doi: 10.1177/0160017615572888) to investigate the spatial heterogeneity in the marginal effects by using nonparametric local modeling approaches such as geographically weighted regression (GWR) and mixed GWR with two distinct samples of the US Metropolitan Statistical Area (MSA) and non-MSA counties. The results indicate a high degree of spatial heterogeneity in the marginal effects of the knowledge input variables, more specifically for the local and distant spillovers of private knowledge measured across MSA counties. On the other hand, local academic knowledge spillovers are found to display spatially homogenous elasticities in both MSA and non-MSA counties. Our results highlight the strengths and weaknesses of each county's innovation capacity and suggest policy implications for regional innovation strategies.

Application of an imputation method for geospatial inventory of forest structural attributes across multiple spatial scales in the Lake States, U.S.A

NASA Astrophysics Data System (ADS)

Deo, Ram K.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

PubMed

Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

2017-08-01

Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM 2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM 2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R 2  = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM 2.5 estimates.

Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories

PubMed Central

Donovan, Rory M.; Tapia, Jose-Juan; Sullivan, Devin P.; Faeder, James R.; Murphy, Robert F.; Dittrich, Markus; Zuckerman, Daniel M.

2016-01-01

The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation—by orders of magnitude for some observables. PMID:26845334

Effect of gold wire bonding process on angular correlated color temperature uniformity of white light-emitting diode.

PubMed

Wu, Bulong; Luo, Xiaobing; Zheng, Huai; Liu, Sheng

2011-11-21

Gold wire bonding is an important packaging process of lighting emitting diode (LED). In this work, we studied the effect of gold wire bonding on the angular uniformity of correlated color temperature (CCT) in white LEDs whose phosphor layers were coated by freely dispersed coating process. Experimental study indicated that different gold wire bonding impacts the geometry of phosphor layer, and it results in different fluctuation trends of angular CCT at different spatial planes in one LED sample. It also results in various fluctuating amplitudes of angular CCT distributions at the same spatial plane for samples with different wire bonding angles. The gold wire bonding process has important impact on angular uniformity of CCT in LED package. © 2011 Optical Society of America

Chronic treatment with sulbutiamine improves memory in an object recognition task and reduces some amnesic effects of dizocilpine in a spatial delayed-non-match-to-sample task.

PubMed

Bizot, Jean-Charles; Herpin, Alexandre; Pothion, Stéphanie; Pirot, Sylvain; Trovero, Fabrice; Ollat, Hélène

2005-07-01

The effect of a sulbutiamine chronic treatment on memory was studied in rats with a spatial delayed-non-match-to-sample (DNMTS) task in a radial maze and a two trial object recognition task. After completion of training in the DNMTS task, animals were subjected for 9 weeks to daily injections of either saline or sulbutiamine (12.5 or 25 mg/kg). Sulbutiamine did not modify memory in the DNMTS task but improved it in the object recognition task. Dizocilpine, impaired both acquisition and retention of the DNMTS task in the saline-treated group, but not in the two sulbutiamine-treated groups, suggesting that sulbutiamine may counteract the amnesia induced by a blockade of the N-methyl-D-aspartate glutamate receptors. Taken together, these results are in favor of a beneficial effect of sulbutiamine on working and episodic memory.

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys

PubMed Central

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield. PMID:27203697

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys.

PubMed

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield.

A Japanese New Altimetry Mission, COMPIRA - Towards High Temporal and Spatial Sampling of Sea Surface Height Measurement

NASA Astrophysics Data System (ADS)

Ito, N.; Uematsu, A.; Yajima, Y.; Isoguchi, O.

2014-12-01

Japan Aerospace Exploration Agency (JAXA) is working on a conceptual study of altimeter mission named Coastal and Ocean measurement Mission with Precise and Innovative Radar Altimeter (COMPIRA), which will carry a wide-swath altimeter named Synthetic aperture radar (SAR) Height Imaging Oceanic Sensor with Advanced Interferometry (SHIOSAI). Capturing meso/submeso-scale phenomena is one of important objectives of the COMPIRA mission, as well as operational oceanography and fishery. For operational oceanography including coastal forecast, swath of SHIOSAI is selected to be 80 km in left and right sides to maximize temporal and spatial sampling of the sea surface height. Orbit specifications are also designed to be better sampling especially for mid-latitude region. That is, a spatial grid sampling is 5 km and an observation times per revisit period (about 10 days) is 2 to 3 times. In order to meet both sampling frequency and spatial coverage requirements as much as possible, orbit inclination was set relatively low, 51 degrees. Although this sampling frequency is, of course, not enough high to capture time evolution of coastal phenomena, an assimilation process would compensate its time evolution if 2D SSH fields was observed at least once within decal time scale of phenomena. JAXA has launched a framework called "Coastal forecast core team" to aim at developing coastal forecast system through pre-launch activities toward COMPIRA. Assimilation segment as well as satellite and in situ data provision will play an important role on these activities. As a first step, we evaluated effects of ocean current forecast improvement with COMPIRA-simulated wide-swath and high sampling sea surface heights (SSH) data. Simulated SSH data are generated from regional ocean numerical models and the COMPIRA orbit and error specifications. Then, identical twin experiments are conducted to investigate the effect of wide-swath SSH measurements on coastal forecast in the Tohoku Pacific coast region. The experiment shows that simulated sea surface current using COMPIRA data as an input data for assimilation well represents vortical feature, which cannot be reproduced by conventional nadir altimeters.

Dependence of B1+ and B1- Field Patterns of Surface Coils on the Electrical Properties of the Sample and the MR Operating Frequency.

PubMed

Vaidya, Manushka V; Collins, Christopher M; Sodickson, Daniel K; Brown, Ryan; Wiggins, Graham C; Lattanzi, Riccardo

2016-02-01

In high field MRI, the spatial distribution of the radiofrequency magnetic ( B 1 ) field is usually affected by the presence of the sample. For hardware design and to aid interpretation of experimental results, it is important both to anticipate and to accurately simulate the behavior of these fields. Fields generated by a radiofrequency surface coil were simulated using dyadic Green's functions, or experimentally measured over a range of frequencies inside an object whose electrical properties were varied to illustrate a variety of transmit [Formula: see text] and receive [Formula: see text] field patterns. In this work, we examine how changes in polarization of the field and interference of propagating waves in an object can affect the B 1 spatial distribution. Results are explained conceptually using Maxwell's equations and intuitive illustrations. We demonstrate that the electrical conductivity alters the spatial distribution of distinct polarized components of the field, causing "twisted" transmit and receive field patterns, and asymmetries between [Formula: see text] and [Formula: see text]. Additionally, interference patterns due to wavelength effects are observed at high field in samples with high relative permittivity and near-zero conductivity, but are not present in lossy samples due to the attenuation of propagating EM fields. This work provides a conceptual framework for understanding B 1 spatial distributions for surface coils and can provide guidance for RF engineers.

sGD: software for estimating spatially explicit indices of genetic diversity.

PubMed

Shirk, A J; Cushman, S A

2011-09-01

Anthropogenic landscape changes have greatly reduced the population size, range and migration rates of many terrestrial species. The small local effective population size of remnant populations favours loss of genetic diversity leading to reduced fitness and adaptive potential, and thus ultimately greater extinction risk. Accurately quantifying genetic diversity is therefore crucial to assessing the viability of small populations. Diversity indices are typically calculated from the multilocus genotypes of all individuals sampled within discretely defined habitat patches or larger regional extents. Importantly, discrete population approaches do not capture the clinal nature of populations genetically isolated by distance or landscape resistance. Here, we introduce spatial Genetic Diversity (sGD), a new spatially explicit tool to estimate genetic diversity based on grouping individuals into potentially overlapping genetic neighbourhoods that match the population structure, whether discrete or clinal. We compared the estimates and patterns of genetic diversity using patch or regional sampling and sGD on both simulated and empirical populations. When the population did not meet the assumptions of an island model, we found that patch and regional sampling generally overestimated local heterozygosity, inbreeding and allelic diversity. Moreover, sGD revealed fine-scale spatial heterogeneity in genetic diversity that was not evident with patch or regional sampling. These advantages should provide a more robust means to evaluate the potential for genetic factors to influence the viability of clinal populations and guide appropriate conservation plans. © 2011 Blackwell Publishing Ltd.

Temporal and spatial resolution required for imaging myocardial function

NASA Astrophysics Data System (ADS)

Eusemann, Christian D.; Robb, Richard A.

2004-05-01

4-D functional analysis of myocardial mechanics is an area of significant interest and research in cardiology and vascular/interventional radiology. Current multidimensional analysis is limited by insufficient temporal resolution of x-ray and magnetic resonance based techniques, but recent improvements in system design holds hope for faster and higher resolution scans to improve images of moving structures allowing more accurate functional studies, such as in the heart. This paper provides a basis for the requisite temporal and spatial resolution for useful imaging during individual segments of the cardiac cycle. Multiple sample rates during systole and diastole are compared to determine an adequate sample frequency to reduce regional myocardial tracking errors. Concurrently, out-of-plane resolution has to be sufficiently high to minimize partial volume effect. Temporal resolution and out-of-plane spatial resolution are related factors that must be considered together. The data used for this study is a DSR dynamic volume image dataset with high temporal and spatial resolution using implanted fiducial markers to track myocardial motion. The results of this study suggest a reduced exposure and scan time for x-ray and magnetic resonance imaging methods, since a lower sample rate during systole is sufficient, whereas the period of rapid filling during diastole requires higher sampling. This could potentially reduce the cost of these procedures and allow higher patient throughput.

Tree species, spatial heterogeneity, and seasonality drive soil fungal abundance, richness, and composition in Neotropical rainforests.

PubMed

Kivlin, Stephanie N; Hawkes, Christine V

2016-12-01

Tropical ecosystems remain poorly understood and this is particularly true for belowground soil fungi. Soil fungi may respond to plant identity when, for example, plants differentially allocate resources belowground. However, spatial and temporal heterogeneity in factors such as plant inputs, moisture, or nutrients can also affect fungal communities and obscure our ability to detect plant effects in single time point studies or within diverse forests. To address this, we sampled replicated monocultures of four tree species and secondary forest controls sampled in the drier and wetter seasons over 2 years. Fungal community composition was primarily related to vegetation type and spatial heterogeneity in the effects of vegetation type, with increasing divergence partly reflecting greater differences in soil pH and soil moisture. Across wetter versus drier dates, fungi were 7% less diverse, but up to four-fold more abundant. The combined effects of tree species and seasonality suggest that predicted losses of tropical tree diversity and intensification of drought have the potential to cascade belowground to affect both diversity and abundance of tropical soil fungi. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Spatial-temporal discriminant analysis for ERP-based brain-computer interface.

PubMed

Zhang, Yu; Zhou, Guoxu; Zhao, Qibin; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

2013-03-01

Linear discriminant analysis (LDA) has been widely adopted to classify event-related potential (ERP) in brain-computer interface (BCI). Good classification performance of the ERP-based BCI usually requires sufficient data recordings for effective training of the LDA classifier, and hence a long system calibration time which however may depress the system practicability and cause the users resistance to the BCI system. In this study, we introduce a spatial-temporal discriminant analysis (STDA) to ERP classification. As a multiway extension of the LDA, the STDA method tries to maximize the discriminant information between target and nontarget classes through finding two projection matrices from spatial and temporal dimensions collaboratively, which reduces effectively the feature dimensionality in the discriminant analysis, and hence decreases significantly the number of required training samples. The proposed STDA method was validated with dataset II of the BCI Competition III and dataset recorded from our own experiments, and compared to the state-of-the-art algorithms for ERP classification. Online experiments were additionally implemented for the validation. The superior classification performance in using few training samples shows that the STDA is effective to reduce the system calibration time and improve the classification accuracy, thereby enhancing the practicability of ERP-based BCI.

Consequences of kriging and land use regression for PM2.5 predictions in epidemiologic analyses: Insights into spatial variability using high-resolution satellite data

PubMed Central

Alexeeff, Stacey E.; Schwartz, Joel; Kloog, Itai; Chudnovsky, Alexandra; Koutrakis, Petros; Coull, Brent A.

2016-01-01

Many epidemiological studies use predicted air pollution exposures as surrogates for true air pollution levels. These predicted exposures contain exposure measurement error, yet simulation studies have typically found negligible bias in resulting health effect estimates. However, previous studies typically assumed a statistical spatial model for air pollution exposure, which may be oversimplified. We address this shortcoming by assuming a realistic, complex exposure surface derived from fine-scale (1km x 1km) remote-sensing satellite data. Using simulation, we evaluate the accuracy of epidemiological health effect estimates in linear and logistic regression when using spatial air pollution predictions from kriging and land use regression models. We examined chronic (long-term) and acute (short-term) exposure to air pollution. Results varied substantially across different scenarios. Exposure models with low out-of-sample R2 yielded severe biases in the health effect estimates of some models, ranging from 60% upward bias to 70% downward bias. One land use regression exposure model with greater than 0.9 out-of-sample R2 yielded upward biases up to 13% for acute health effect estimates. Almost all models drastically underestimated the standard errors. Land use regression models performed better in chronic effects simulations. These results can help researchers when interpreting health effect estimates in these types of studies. PMID:24896768

Spatial complexity of character-based writing systems and arithmetic in primary school: a longitudinal study

PubMed Central

Rodic, Maja; Tikhomirova, Tatiana; Kolienko, Tatiana; Malykh, Sergey; Bogdanova, Olga; Zueva, Dina Y.; Gynku, Elena I.; Wan, Sirui; Zhou, Xinlin; Kovas, Yulia

2015-01-01

Previous research has consistently found an association between spatial and mathematical abilities. We hypothesized that this link may partially explain the consistently observed advantage in mathematics demonstrated by East Asian children. Spatial complexity of the character-based writing systems may reflect or lead to a cognitive advantage relevant to mathematics. Seven hundered and twenty one 6–9-year old children from the UK and Russia were assessed on a battery of cognitive skills and arithmetic. The Russian children were recruited from specialist linguistic schools and divided into four different language groups, based on the second language they were learning (i.e., English, Spanish, Chinese, and Japanese). The UK children attended regular schools and were not learning any second language. The testing took place twice across the school year, once at the beginning, before the start of the second language acquisition, and once at the end of the year. The study had two aims: (1) to test whether spatial ability predicts mathematical ability in 7–9 year-old children across the samples; (2) to test whether acquisition and usage of a character-based writing system leads to an advantage in performance in arithmetic and related cognitive tasks. The longitudinal link from spatial ability to mathematics was found only in the Russian sample. The effect of second language acquisition on mathematics or other cognitive skills was negligible, although some effect of Chinese language on mathematical reasoning was suggested. Overall, the findings suggest that although spatial ability is related to mathematics at this age, one academic year of exposure to spatially complex writing systems is not enough to provide a mathematical advantage. Other educational and socio-cultural factors might play a greater role in explaining individual and cross-cultural differences in arithmetic at this age. PMID:25859235

Spatial complexity of character-based writing systems and arithmetic in primary school: a longitudinal study.

PubMed

Rodic, Maja; Tikhomirova, Tatiana; Kolienko, Tatiana; Malykh, Sergey; Bogdanova, Olga; Zueva, Dina Y; Gynku, Elena I; Wan, Sirui; Zhou, Xinlin; Kovas, Yulia

2015-01-01

Previous research has consistently found an association between spatial and mathematical abilities. We hypothesized that this link may partially explain the consistently observed advantage in mathematics demonstrated by East Asian children. Spatial complexity of the character-based writing systems may reflect or lead to a cognitive advantage relevant to mathematics. Seven hundered and twenty one 6-9-year old children from the UK and Russia were assessed on a battery of cognitive skills and arithmetic. The Russian children were recruited from specialist linguistic schools and divided into four different language groups, based on the second language they were learning (i.e., English, Spanish, Chinese, and Japanese). The UK children attended regular schools and were not learning any second language. The testing took place twice across the school year, once at the beginning, before the start of the second language acquisition, and once at the end of the year. The study had two aims: (1) to test whether spatial ability predicts mathematical ability in 7-9 year-old children across the samples; (2) to test whether acquisition and usage of a character-based writing system leads to an advantage in performance in arithmetic and related cognitive tasks. The longitudinal link from spatial ability to mathematics was found only in the Russian sample. The effect of second language acquisition on mathematics or other cognitive skills was negligible, although some effect of Chinese language on mathematical reasoning was suggested. Overall, the findings suggest that although spatial ability is related to mathematics at this age, one academic year of exposure to spatially complex writing systems is not enough to provide a mathematical advantage. Other educational and socio-cultural factors might play a greater role in explaining individual and cross-cultural differences in arithmetic at this age.

The Effects of Video Game Experience on Computer-Based Air Traffic Controller Specialist, Air Traffic Scenario Test Scores.

DTIC Science & Technology

1997-02-01

application with a strong resemblance to a video game , concern has been raised that prior video game experience might have a moderating effect on scores. Much...such as spatial ability. The effects of computer or video game experience on work sample scores have not been systematically investigated. The purpose...of this study was to evaluate the incremental validity of prior video game experience over that of general aptitude as a predictor of work sample test

Soil nutrient-landscape relationships in a lowland tropical rainforest in Panama

USGS Publications Warehouse

Barthold, F.K.; Stallard, R.F.; Elsenbeer, H.

2008-01-01

Soils play a crucial role in biogeochemical cycles as spatially distributed sources and sinks of nutrients. Any spatial patterns depend on soil forming processes, our understanding of which is still limited, especially in regards to tropical rainforests. The objective of our study was to investigate the effects of landscape properties, with an emphasis on the geometry of the land surface, on the spatial heterogeneity of soil chemical properties, and to test the suitability of soil-landscape modeling as an appropriate technique to predict the spatial variability of exchangeable K and Mg in a humid tropical forest in Panama. We used a design-based, stratified sampling scheme to collect soil samples at 108 sites on Barro Colorado Island, Panama. Stratifying variables are lithology, vegetation and topography. Topographic variables were generated from high-resolution digital elevation models with a grid size of 5 m. We took samples from five depths down to 1 m, and analyzed for total and exchangeable K and Mg. We used simple explorative data analysis techniques to elucidate the importance of lithology for soil total and exchangeable K and Mg. Classification and Regression Trees (CART) were adopted to investigate importance of topography, lithology and vegetation for the spatial distribution of exchangeable K and Mg and with the intention to develop models that regionalize the point observations using digital terrain data as explanatory variables. Our results suggest that topography and vegetation do not control the spatial distribution of the selected soil chemical properties at a landscape scale and lithology is important to some degree. Exchangeable K is distributed equally across the study area indicating that other than landscape processes, e.g. biogeochemical processes, are responsible for its spatial distribution. Lithology contributes to the spatial variation of exchangeable Mg but controlling variables could not be detected. The spatial variation of soil total K and Mg is mainly influenced by lithology. ?? 2007 Elsevier B.V. All rights reserved.

Ecological and sampling constraints on defining landscape fire severity

USGS Publications Warehouse

Key, C.H.

2006-01-01

Ecological definition and detection of fire severity are influenced by factors of spatial resolution and timing. Resolution determines the aggregation of effects within a sampling unit or pixel (alpha variation), hence limiting the discernible ecological responses, and controlling the spatial patchiness of responses distributed throughout a burn (beta variation). As resolution decreases, alpha variation increases, extracting beta variation and complexity from the spatial model of the whole burn. Seasonal timing impacts the quality of radiometric data in terms of transmittance, sun angle, and potential contrast between responses within burns. Detection sensitivity candegrade toward the end of many fire seasons when low sun angles, vegetation senescence, incomplete burning, hazy conditions, or snow are common. Thus, a need exists to supersede many rapid response applications when remote sensing conditions improve. Lag timing, or timesince fire, notably shapes the ecological character of severity through first-order effects that only emerge with time after fire, including delayed survivorship and mortality. Survivorship diminishes the detected magnitude of severity, as burned vegetation remains viable and resprouts, though at first it may appear completely charred or consumed above ground. Conversely, delayed mortality increases the severity estimate when apparently healthy vegetation is in fact damaged by heat to the extent that it dies over time. Both responses dependon fire behavior and various species-specific adaptations to fire that are unique to the pre-firecomposition of each burned area. Both responses can lead initially to either over- or underestimating severity. Based on such implications, three sampling intervals for short-term burn severity are identified; rapid, initial, and extended assessment, sampled within about two weeks, two months, and depending on the ecotype, from three months to one year after fire, respectively. Spatial and temporal conditions of sampling strategies constrain data quality and ecological information obtained about fire severity. Though commonly overlooked, such considerations determine the objectives and hypotheses that are appropriate for each application, and are especially important when building comparative studies or long-term reference databases on fire severity.

Assessing efficiency of spatial sampling using combined coverage analysis in geographical and feature spaces

NASA Astrophysics Data System (ADS)

Hengl, Tomislav

2015-04-01

Efficiency of spatial sampling largely determines success of model building. This is especially important for geostatistical mapping where an initial sampling plan should provide a good representation or coverage of both geographical (defined by the study area mask map) and feature space (defined by the multi-dimensional covariates). Otherwise the model will need to extrapolate and, hence, the overall uncertainty of the predictions will be high. In many cases, geostatisticians use point data sets which are produced using unknown or inconsistent sampling algorithms. Many point data sets in environmental sciences suffer from spatial clustering and systematic omission of feature space. But how to quantify these 'representation' problems and how to incorporate this knowledge into model building? The author has developed a generic function called 'spsample.prob' (Global Soil Information Facilities package for R) and which simultaneously determines (effective) inclusion probabilities as an average between the kernel density estimation (geographical spreading of points; analysed using the spatstat package in R) and MaxEnt analysis (feature space spreading of points; analysed using the MaxEnt software used primarily for species distribution modelling). The output 'iprob' map indicates whether the sampling plan has systematically missed some important locations and/or features, and can also be used as an input for geostatistical modelling e.g. as a weight map for geostatistical model fitting. The spsample.prob function can also be used in combination with the accessibility analysis (cost of field survey are usually function of distance from the road network, slope and land cover) to allow for simultaneous maximization of average inclusion probabilities and minimization of total survey costs. The author postulates that, by estimating effective inclusion probabilities using combined geographical and feature space analysis, and by comparing survey costs to representation efficiency, an optimal initial sampling plan can be produced which satisfies both criteria: (a) good representation (i.e. within a tolerance threshold), and (b) minimized survey costs. This sampling analysis framework could become especially interesting for generating sampling plans in new areas e.g. for which no previous spatial prediction model exists. The presentation includes data processing demos with standard soil sampling data sets Ebergotzen (Germany) and Edgeroi (Australia), also available via the GSIF package.

Copper Decoration of Carbon Nanotubes and High Resolution Electron Microscopy

NASA Astrophysics Data System (ADS)

Probst, Camille

A new process of decorating carbon nanotubes with copper was developed for the fabrication of nanocomposite aluminum-nanotubes. The process consists of three stages: oxidation, activation and electroless copper plating on the nanotubes. The oxidation step was required to create chemical function on the nanotubes, essential for the activation step. Then, catalytic nanoparticles of tin-palladium were deposited on the tubes. Finally, during the electroless copper plating, copper particles with a size between 20 and 60 nm were uniformly deposited on the nanotubes surface. The reproducibility of the process was shown by using another type of carbon nanotube. The fabrication of nanocomposites aluminum-nanotubes was tested by aluminum vacuum infiltration. Although the infiltration of carbon nanotubes did not produce the expected results, an interesting electron microscopy sample was discovered during the process development: the activated carbon nanotubes. Secondly, scanning transmitted electron microscopy (STEM) imaging in SEM was analysed. The images were obtained with a new detector on the field emission scanning electron microscope (Hitachi S-4700). Various parameters were analysed with the use of two different samples: the activated carbon nanotubes (previously obtained) and gold-palladium nanodeposits. Influences of working distance, accelerating voltage or sample used on the spatial resolution of images obtained with SMART (Scanning Microscope Assessment and Resolution Testing) were analysed. An optimum working distance for the best spatial resolution related to the sample analysed was found for the imaging in STEM mode. Finally, relation between probe size and spatial resolution of backscattered electrons (BSE) images was studied. An image synthesis method was developed to generate the BSE images from backscattered electrons coefficients obtained with CASINO software. Spatial resolution of images was determined using SMART. The analysis shown that using a probe size smaller than the size of the observed object (sample features) does not improve the spatial resolution. In addition, the effects of the accelerating voltage, the current intensity and the sample geometry and composition were analysed.

The BRAVE Program. I. Improved Bulge Stellar Velocity Dispersion Estimates for a Sample of Active Galaxies

NASA Astrophysics Data System (ADS)

Batiste, Merida; Bentz, Misty C.; Manne-Nicholas, Emily R.; Onken, Christopher A.; Bershady, Matthew A.

2017-02-01

We present new bulge stellar velocity dispersion measurements for 10 active galaxies with secure MBH determinations from reverberation mapping. These new velocity dispersion measurements are based on spatially resolved kinematics from integral-field (IFU) spectroscopy. In all but one case, the field of view of the IFU extends beyond the effective radius of the galaxy, and in the case of Mrk 79 it extends to almost one half the effective radius. This combination of spatial resolution and field of view allows for secure determinations of stellar velocity dispersion within the effective radius for all 10 target galaxies. Spatially resolved maps of the first (V) and second (σ⋆) moments of the line of sight velocity distribution indicate the presence of kinematic substructure in most cases. In future projects we plan to explore methods of correcting for the effects of kinematic substructure in the derived bulge stellar velocity dispersion measurements.

Effects of land use and seasonality on stream water quality in a small tropical catchment: The headwater of Córrego Água Limpa, São Paulo (Brazil).

PubMed

Rodrigues, Valdemir; Estrany, Joan; Ranzini, Mauricio; de Cicco, Valdir; Martín-Benito, José Mª Tarjuelo; Hedo, Javier; Lucas-Borja, Manuel E

2018-05-01

Stream water quality is controlled by the interaction of natural and anthropogenic factors over a range of temporal and spatial scales. Among these anthropogenic factors, land cover changes at catchment scale can affect stream water quality. This work aims to evaluate the influence of land use and seasonality on stream water quality in a representative tropical headwater catchment named as Córrego Água Limpa (Sao Paulo, Brasil), which is highly influenced by intensive agricultural activities and urban areas. Two systematic sampling approach campaigns were implemented with six sampling points along the stream of the headwater catchment to evaluate water quality during the rainy and dry seasons. Three replicates were collected at each sampling point in 2011. Electrical conductivity, nitrates, nitrites, sodium superoxide, Chemical Oxygen Demand (DQO), colour, turbidity, suspended solids, soluble solids and total solids were measured. Water quality parameters differed among sampling points, being lower at the headwater sampling point (0m above sea level), and then progressively higher until the last downstream sampling point (2500m above sea level). For the dry season, the mean discharge was 39.5ls -1 (from April to September) whereas 113.0ls -1 were averaged during the rainy season (from October to March). In addition, significant temporal and spatial differences were observed (P<0.05) for the fourteen parameters during the rainy and dry period. The study enhance significant relationships among land use and water quality and its temporal effect, showing seasonal differences between the land use and water quality connection, highlighting the importance of multiple spatial and temporal scales for understanding the impacts of human activities on catchment ecosystem services. Copyright © 2017 Elsevier B.V. All rights reserved.

The effects of an inquiry-based earth science course on the spatial thinking of pre-service elementary teacher education students

NASA Astrophysics Data System (ADS)

Weakley, Kevin Douglas

This study examined the effectiveness of two geography courses at improving student spatial thinking skills. Spatial thinking is an important cognitive skill in the sciences and everyday life. A taxonomy of spatial thinking was constructed by Gersmehl (2008) in geography education which included core modes assessed in this study: comparison, region, transition, analogy, pattern, and association. Two additional modes related to space over time, change and movement, were also assessed. The central research question in this study is: What are the effects of a pre-service teacher education earth science content course (Geography 1900) that is conceptually designed and inquiry-based on the spatial thinking of university students compared to the Geography 1020 course that follows a lecture format with an atlas study component? The six sub-questions to this central question were: (1) What spatial thinking modes are embedded in the Geography 1900 course based on the Gersmehl (2008) classification of modes of spatial thinking? (2) What modes of spatial thinking do pre-service elementary education students exhibit prior to instruction in Geography 1900 and 1020? (3) What changes occur in spatial thinking and spatial skills as a result of enrolling in and completing a conceptually based, inquiry course (Geography 1900) that has embedded clearly identifiable spatial tasks based on Gersmehl's classification? (4) What are the effects of Geography 1900 on the modes of spatial thinking that students apply at the completion of the course? (5) What modes of spatial thinking do students transfer from the classroom to the outdoors as they move about campus? (6) Are there differences in spatial thinking between the Geography 1900 population and the Geography 1020 comparison sample of students that received a different course treatment? The research used a mixed methods approach with both quantitative and qualitative information. Statistically significant changes were observed in the use of spatial constructs and concepts by students in each of the course treatments that were compared. Students were also observed to apply spatial modes outside the classroom that represented the spatial thinking within the new context of the university environment as they observed and described the landscape.

Feasibility of conducting wetfall chemistry investigations around the Bowen Power Plant

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

Chen, N.C.J.; Patrinos, A.A.N.

1979-10-01

The feasibility of expanding the Meteorological Effects of Thermal Energy Releases - Oak Ridge National Laboratory (METER-ORNL) research at Bower Power Plant, a coal-fired power plant in northwest Georgia, to include wetfall chemistry is evaluated using results of similar studies around other power plants, several atmospheric washout models, analysis of spatial variability in precipitation, and field logistical considerations. An optimal wetfall chemistry network design is proposed, incorporating the inner portion of the existing rain-gauge network and augmented by additional sites to ensure adequate coverage of probable target areas. The predicted sulfate production rate differs by about four orders of magnitudemore » among the models reviewed with a pH of 3. No model can claim superiority over any other model without substantive data verification. The spatial uniformity in rain amount is evaluated using four storms that occurred at the METER-ORNL network. Values of spatial variability ranged from 8 to 31% and decreased as the mean rainfall increased. The field study of wetfall chemistry will require a minimum of 5 persons to operate the approximately 50 collectors covering an area of 740 km/sup 2/. Preliminary wetfall-only samples collected on an event basis showed lower pH and higher electrical conductivity of precipitation collected about 5 km downwind of the power plant relative to samples collected upwind. Wetfall samples collected on a weekly basis using automatic samplers, however, showed variable results, with no consistent pattern. This suggests the need for event sampling to minimize variable rain volume and multiple-source effects often associated with weekly samples.« less

The Effect of 3D-Modeling Training on Students' Spatial Reasoning Relative to Gender and Grade

ERIC Educational Resources Information Center

Šafhalter, Andrej; Vukman, Karin Bakracevic; Glodež, Srecko

2016-01-01

The aim of this research was to establish whether gender and age have an impact on spatial reasoning and its development through the use of 3D modeling. The study was conducted on a sample of 196 children from sixth to ninth grade, of whom 95 represented the experimental group and 101 the control group. The experimental group received 3D modeling…

A hierarchical model for spatial capture-recapture data

USGS Publications Warehouse

Royle, J. Andrew; Young, K.V.

2008-01-01

Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed populations is widespread, but ineffective for estimating absolute density because most populations are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates because the effective sample area is unknown. A number of methods involving the adjustment of estimates based on heuristic considerations are in widespread use. In this paper, a hierarchical model of spatially indexed capture recapture data is proposed for sampling based on area searches of spatial sample units subject to uniform sampling intensity. The hierarchical model contains explicit models for the distribution of individuals and their movements, in addition to an observation model that is conditional on the location of individuals during sampling. Bayesian analysis of the hierarchical model is achieved by the use of data augmentation, which allows for a straightforward implementation in the freely available software WinBUGS. We present results of a simulation study that was carried out to evaluate the operating characteristics of the Bayesian estimator under variable densities and movement patterns of individuals. An application of the model is presented for survey data on the flat-tailed horned lizard (Phrynosoma mcallii) in Arizona, USA.

A novel mobile monitoring approach to characterize spatial and temporal variation in traffic-related air pollutants in an urban community

NASA Astrophysics Data System (ADS)

Yu, Chang Ho; Fan, Zhihua; Lioy, Paul J.; Baptista, Ana; Greenberg, Molly; Laumbach, Robert J.

2016-09-01

Air concentrations of traffic-related air pollutants (TRAPs) vary in space and time within urban communities, presenting challenges for estimating human exposure and potential health effects. Conventional stationary monitoring stations/networks cannot effectively capture spatial characteristics. Alternatively, mobile monitoring approaches became popular to measure TRAPs along roadways or roadsides. However, these linear mobile monitoring approaches cannot thoroughly distinguish spatial variability from temporal variations in monitored TRAP concentrations. In this study, we used a novel mobile monitoring approach to simultaneously characterize spatial/temporal variations in roadside concentrations of TRAPs in urban settings. We evaluated the effectiveness of this mobile monitoring approach by performing concurrent measurements along two parallel paths perpendicular to a major roadway and/or along heavily trafficked roads at very narrow scale (one block away each other) within short time period (<30 min) in an urban community. Based on traffic and particulate matter (PM) source information, we selected 4 neighborhoods to study. The sampling activities utilized real-time monitors, including battery-operated PM2.5 monitor (SidePak), condensation particle counter (CPC 3007), black carbon (BC) monitor (Micro-Aethalometer), carbon monoxide (CO) monitor (Langan T15), and portable temperature/humidity data logger (HOBO U12), and a GPS-based tracker (Trackstick). Sampling was conducted for ∼3 h in the morning (7:30-10:30) in 7 separate days in March/April and 6 days in May/June 2012. Two simultaneous samplings were made at 5 spatially-distributed locations on parallel roads, usually distant one block each other, in each neighborhood. The 5-min averaged BC concentrations (AVG ± SD, [range]) were 2.53 ± 2.47 [0.09-16.3] μg/m3, particle number concentrations (PNC) were 33,330 ± 23,451 [2512-159,130] particles/cm3, PM2.5 mass concentrations were 8.87 ± 7.65 [0.27-46.5] μg/m3, and CO concentrations were 1.22 ± 0.60 [0.22-6.29] ppm in the community. The traffic-related air pollutants, BC and PNC, but not PM2.5 or CO, varied spatially depending on proximity to local stationary/mobile sources. Seasonal differences were observed for all four TRAPs, significantly higher in colder months than in warmer months. The coefficients of variation (CVs) in concurrent measurements from two parallel routes were calculated around 0.21 ± 0.17, and variations were attributed by meteorological variation (25%), temporal variability (19%), concentration level (6%), and spatial variability (2%), respectively. Overall study findings suggest this mobile monitoring approach could effectively capture and distinguish spatial/temporal characteristics in TRAP concentrations for communities impacted by heavy motor vehicle traffic and mixed urban air pollution sources.

Performance of some biotic indices in the real variable world: a case study at different spatial scales in North-Western Mediterranean Sea.

PubMed

Tataranni, Mariella; Lardicci, Claudio

2010-01-01

The aim of this study was to analyse the variability of four different benthic biotic indices (AMBI, BENTIX, H', M-AMBI) in two marine coastal areas of the North-Western Mediterranean Sea. In each coastal area, 36 replicates were randomly selected according to a hierarchical sampling design, which allowed estimating the variance components of the indices associated with four different spatial scales (ranging from metres to kilometres). All the analyses were performed at two different sampling periods in order to evaluate if the observed trends were consistent over the time. The variance components of the four indices revealed complex trends and different patterns in the two sampling periods. These results highlighted that independently from the employed index, a rigorous and appropriate sampling design taking into account different scales should always be used in order to avoid erroneous classifications and to develop effective monitoring programs.

Application of spatial Poisson process models to air mass thunderstorm rainfall

NASA Technical Reports Server (NTRS)

Eagleson, P. S.; Fennessy, N. M.; Wang, Qinliang; Rodriguez-Iturbe, I.

1987-01-01

Eight years of summer storm rainfall observations from 93 stations in and around the 154 sq km Walnut Gulch catchment of the Agricultural Research Service, U.S. Department of Agriculture, in Arizona are processed to yield the total station depths of 428 storms. Statistical analysis of these random fields yields the first two moments, the spatial correlation and variance functions, and the spatial distribution of total rainfall for each storm. The absolute and relative worth of three Poisson models are evaluated by comparing their prediction of the spatial distribution of storm rainfall with observations from the second half of the sample. The effect of interstorm parameter variation is examined.

Effects of cue types on sex differences in human spatial memory.

PubMed

Chai, Xiaoqian J; Jacobs, Lucia F

2010-04-02

We examined the effects of cue types on human spatial memory in 3D virtual environments adapted from classical animal and human tasks. Two classes of cues of different functions were investigated: those that provide directional information, and those that provide positional information. Adding a directional cue (geographical slant) to the spatial delayed-match-to-sample task improved performance in males but not in females. When the slant directional cue was removed in a hidden-target location task, male performance was impaired but female performance was unaffected. The removal of positional cues, on the other hand, impaired female performance but not male performance. These results are consistent with results from laboratory rodents and thus support the hypothesis that sex differences in spatial memory arise from the dissociation between a preferential reliance on directional cues in males and on positional cues in females. Copyright 2009 Elsevier B.V. All rights reserved.

Interannual and Spatial Variability in Maturity of Walleye Pollock Gadus chalcogrammus and Implications for Spawning Stock Biomass Estimates in the Gulf of Alaska

PubMed Central

Kruse, Gordon H.; Dorn, Martin W.

2016-01-01

Catch quotas for walleye pollock Gadus chalcogrammus, the dominant species in the groundfish fishery off Alaska, are set by applying harvest control rules to annual estimates of spawning stock biomass (SSB) from age-structured stock assessments. Adult walleye pollock abundance and maturity status have been monitored in early spring in Shelikof Strait in the Gulf of Alaska for almost three decades. The sampling strategy for maturity status is largely characterized as targeted, albeit opportunistic, sampling of trawl tows made during hydroacoustic surveys. Trawl sampling during pre-spawning biomass surveys, which do not adequately account for spatial patterns in the distribution of immature and mature fish, can bias estimated maturity ogives from which SSB is calculated. Utilizing these maturity data, we developed mixed-effects generalized additive models to examine spatial and temporal patterns in walleye pollock maturity and the influence of these patterns on estimates of SSB. Current stock assessment practice is to estimate SSB as the product of annual estimates of numbers at age, weight at age, and mean maturity at age for 1983-present. In practice, we found this strategy to be conservative for a time period from 2003–2013 as, on average, it underestimates SSB by a 4.7 to 11.9% difference when compared to our estimates of SSB that account for spatial structure or both temporal and spatial structure. Inclusion of spatially explicit information for walleye pollock maturity has implications for understanding stock reproductive biology and thus the setting of sustainable harvest rates used to manage this valuable fishery. PMID:27736982

Interception loss, throughfall and stemflow in a maritime pine stand. I. Variability of throughfall and stemflow beneath the pine canopy

NASA Astrophysics Data System (ADS)

Loustau, D.; Berbigier, P.; Granier, A.; Moussa, F. El Hadj

1992-10-01

Patterns of spatial variability of throughfall and stemflow were determined in a maritime pine ( Pinus pinaster Ait.) stand for two consecutive years. Data were obtained from 52 fixed rain gauges and 12 stemflow measuring devices located in a 50m × 50m plot at the centre of an 18-year-old stand. The pine trees had been sown in rows 4m apart and had reached an average height of 12.6m. The spatial distribution of stems had a negligible effect on the throughfall partitioning beneath the canopy. Variograms of throughfall computed for a sample of storms did not reveal any spatial autocorrelation of throughfall for the sampling design used. Differences in throughfall, in relation to the distance from the rows, were not consistently significant. In addition, the distance from the tree stem did not influence the amount of throughfall. The confidence interval on the amount of throughfall per storm was between 3 and 8%. The stemflow was highly variable between trees. The effect of individual trees on stemflow was significant but the amount of stemflow per tree was not related to tree size (i.e. height, trunk diameter, etc.). The cumulative sampling errors on stemflow and throughfall for a single storm created a confidence interval of between ±7 and ±51% on interception. This resulted mainly from the low interception rate and sampling error on throughfall.

Kolmogorov-Smirnov test for spatially correlated data

USGS Publications Warehouse

Olea, R.A.; Pawlowsky-Glahn, V.

2009-01-01

The Kolmogorov-Smirnov test is a convenient method for investigating whether two underlying univariate probability distributions can be regarded as undistinguishable from each other or whether an underlying probability distribution differs from a hypothesized distribution. Application of the test requires that the sample be unbiased and the outcomes be independent and identically distributed, conditions that are violated in several degrees by spatially continuous attributes, such as topographical elevation. A generalized form of the bootstrap method is used here for the purpose of modeling the distribution of the statistic D of the Kolmogorov-Smirnov test. The innovation is in the resampling, which in the traditional formulation of bootstrap is done by drawing from the empirical sample with replacement presuming independence. The generalization consists of preparing resamplings with the same spatial correlation as the empirical sample. This is accomplished by reading the value of unconditional stochastic realizations at the sampling locations, realizations that are generated by simulated annealing. The new approach was tested by two empirical samples taken from an exhaustive sample closely following a lognormal distribution. One sample was a regular, unbiased sample while the other one was a clustered, preferential sample that had to be preprocessed. Our results show that the p-value for the spatially correlated case is always larger that the p-value of the statistic in the absence of spatial correlation, which is in agreement with the fact that the information content of an uncorrelated sample is larger than the one for a spatially correlated sample of the same size. ?? Springer-Verlag 2008.

Reducing representativeness and sampling errors in radio occultation-radiosonde comparisons

NASA Astrophysics Data System (ADS)

Gilpin, Shay; Rieckh, Therese; Anthes, Richard

2018-05-01

Radio occultation (RO) and radiosonde (RS) comparisons provide a means of analyzing errors associated with both observational systems. Since RO and RS observations are not taken at the exact same time or location, temporal and spatial sampling errors resulting from atmospheric variability can be significant and inhibit error analysis of the observational systems. In addition, the vertical resolutions of RO and RS profiles vary and vertical representativeness errors may also affect the comparison. In RO-RS comparisons, RO observations are co-located with RS profiles within a fixed time window and distance, i.e. within 3-6 h and circles of radii ranging between 100 and 500 km. In this study, we first show that vertical filtering of RO and RS profiles to a common vertical resolution reduces representativeness errors. We then test two methods of reducing horizontal sampling errors during RO-RS comparisons: restricting co-location pairs to within ellipses oriented along the direction of wind flow rather than circles and applying a spatial-temporal sampling correction based on model data. Using data from 2011 to 2014, we compare RO and RS differences at four GCOS Reference Upper-Air Network (GRUAN) RS stations in different climatic locations, in which co-location pairs were constrained to a large circle ( ˜ 666 km radius), small circle ( ˜ 300 km radius), and ellipse parallel to the wind direction ( ˜ 666 km semi-major axis, ˜ 133 km semi-minor axis). We also apply a spatial-temporal sampling correction using European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim) gridded data. Restricting co-locations to within the ellipse reduces root mean square (RMS) refractivity, temperature, and water vapor pressure differences relative to RMS differences within the large circle and produces differences that are comparable to or less than the RMS differences within circles of similar area. Applying the sampling correction shows the most significant reduction in RMS differences, such that RMS differences are nearly identical to the sampling correction regardless of the geometric constraints. We conclude that implementing the spatial-temporal sampling correction using a reliable model will most effectively reduce sampling errors during RO-RS comparisons; however, if a reliable model is not available, restricting spatial comparisons to within an ellipse parallel to the wind flow will reduce sampling errors caused by horizontal atmospheric variability.

Method for Pre-Conditioning a Measured Surface Height Map for Model Validation

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2012-01-01

This software allows one to up-sample or down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. Because the re-sampling of a surface map is accomplished based on the analytical expressions of Zernike-polynomials and a power spectral density model, such re-sampling does not introduce any aliasing and interpolation errors as is done by the conventional interpolation and FFT-based (fast-Fourier-transform-based) spatial-filtering method. Also, this new method automatically eliminates the measurement noise and other measurement errors such as artificial discontinuity. The developmental cycle of an optical system, such as a space telescope, includes, but is not limited to, the following two steps: (1) deriving requirements or specs on the optical quality of individual optics before they are fabricated through optical modeling and simulations, and (2) validating the optical model using the measured surface height maps after all optics are fabricated. There are a number of computational issues related to model validation, one of which is the "pre-conditioning" or pre-processing of the measured surface maps before using them in a model validation software tool. This software addresses the following issues: (1) up- or down-sampling a measured surface map to match it with the gridded data format of a model validation tool, and (2) eliminating the surface measurement noise or measurement errors such that the resulted surface height map is continuous or smoothly-varying. So far, the preferred method used for re-sampling a surface map is two-dimensional interpolation. The main problem of this method is that the same pixel can take different values when the method of interpolation is changed among the different methods such as the "nearest," "linear," "cubic," and "spline" fitting in Matlab. The conventional, FFT-based spatial filtering method used to eliminate the surface measurement noise or measurement errors can also suffer from aliasing effects. During re-sampling of a surface map, this software preserves the low spatial-frequency characteristic of a given surface map through the use of Zernike-polynomial fit coefficients, and maintains mid- and high-spatial-frequency characteristics of the given surface map by the use of a PSD model derived from the two-dimensional PSD data of the mid- and high-spatial-frequency components of the original surface map. Because this new method creates the new surface map in the desired sampling format from analytical expressions only, it does not encounter any aliasing effects and does not cause any discontinuity in the resultant surface map.

Multi-scale approach to the environmental factors effects on spatio-temporal variability of Chironomus salinarius (Diptera: Chironomidae) in a French coastal lagoon

NASA Astrophysics Data System (ADS)

Cartier, V.; Claret, C.; Garnier, R.; Fayolle, S.; Franquet, E.

2010-03-01

The complexity of the relationships between environmental factors and organisms can be revealed by sampling designs which consider the contribution to variability of different temporal and spatial scales, compared to total variability. From a management perspective, a multi-scale approach can lead to time-saving. Identifying environmental patterns that help maintain patchy distribution is fundamental in studying coastal lagoons, transition zones between continental and marine waters characterised by great environmental variability on spatial and temporal scales. They often present organic enrichment inducing decreased species richness and increased densities of opportunist species like C hironomus salinarius, a common species that tends to swarm and thus constitutes a nuisance for human populations. This species is dominant in the Bolmon lagoon, a French Mediterranean coastal lagoon under eutrophication. Our objective was to quantify variability due to both spatial and temporal scales and identify the contribution of different environmental factors to this variability. The population of C. salinarius was sampled from June 2007 to June 2008 every two months at 12 sites located in two areas of the Bolmon lagoon, at two different depths, with three sites per area-depth combination. Environmental factors (temperature, dissolved oxygen both in sediment and under water surface, sediment organic matter content and grain size) and microbial activities (i.e. hydrolase activities) were also considered as explanatory factors of chironomid densities and distribution. ANOVA analysis reveals significant spatial differences regarding the distribution of chironomid larvae for the area and the depth scales and their interaction. The spatial effect is also revealed for dissolved oxygen (water), salinity and fine particles (area scale), and for water column depth. All factors but water column depth show a temporal effect. Spearman's correlations highlight the seasonal effect (temperature, dissolved oxygen in sediment and water) as well as the effect of microbial activities on chironomid larvae. Our results show that a multi-scale approach identifies patchy distribution, even when there is relative environmental homogeneity.

Study the effects of varying interference upon the optical properties of turbid samples using NIR spatial light modulation

NASA Astrophysics Data System (ADS)

Shaul, Oren; Fanrazi-Kahana, Michal; Meitav, Omri; Pinhasi, Gad A.; Abookasis, David

2018-03-01

Optical properties of biological tissues are valuable diagnostic parameters which can provide necessary information regarding tissue state during disease pathogenesis and therapy. However, different sources of interference, such as temperature changes may modify these properties, introducing confounding factors and artifacts to data, consequently skewing their interpretation and misinforming clinical decision-making. In the current study, we apply spatial light modulation, a type of diffuse reflectance hyperspectral imaging technique, to monitor the variation in optical properties of highly scattering turbid media in the presence varying levels of the following sources of interference: scattering concentration, temperature, and pressure. Spatial near-infrared (NIR) light modulation is a wide-field, non-contact emerging optical imaging platform capable of separating the effects of tissue scattering from those of absorption, thereby accurately estimating both parameters. With this technique, periodic NIR illumination patterns at alternately low and high spatial frequencies, at six discrete wavelengths between 690 to 970 nm, were sequentially projected upon the medium while a CCD camera collects the diffusely reflected light. Data analysis based assumptions is then performed off-line to recover the medium's optical properties. We conducted a series of experiments demonstrating the changes in absorption and reduced scattering coefficients of commercially available fresh milk and chicken breast tissue under different interference conditions. In addition, information on the refractive index was study under increased pressure. This work demonstrates the utility of NIR spatial light modulation to detect varying sources of interference upon the optical properties of biological samples.

Where do the Field Plots Belong? A Multiple-Constraint Sampling Design for the BigFoot Project

NASA Astrophysics Data System (ADS)

Kennedy, R. E.; Cohen, W. B.; Kirschbaum, A. A.; Gower, S. T.

2002-12-01

A key component of a MODIS validation project is effective characterization of biophysical measures on the ground. Fine-grain ecological field measurements must be placed strategically to capture variability at the scale of the MODIS imagery. Here we describe the BigFoot project's revised sampling scheme, designed to simultaneously meet three important goals: capture landscape variability, avoid spatial autocorrelation between field plots, and minimize time and expense of field sampling. A stochastic process places plots in clumped constellations to reduce field sampling costs, while minimizing spatial autocorrelation. This stochastic process is repeated, creating several hundred realizations of plot constellations. Each constellation is scored and ranked according to its ability to match landscape variability in several Landsat-based spectral indices, and its ability to minimize field sampling costs. We show how this approach has recently been used to place sample plots at the BigFoot project's two newest study areas, one in a desert system and one in a tundra system. We also contrast this sampling approach to that already used at the four prior BigFoot project sites.

Spatial coherence effect on layer thickness determination in narrowband full-field optical coherence tomography.

PubMed

Safrani, Avner; Abdulhalim, Ibrahim

2011-06-20

Longitudinal spatial coherence (LSC) is determined by the spatial frequency content of an optical beam. The use of lenses with a high numerical aperture (NA) in full-field optical coherence tomography and a narrowband light source makes the LSC length much shorter than the temporal coherence length, hence suggesting that high-resolution 3D images of biological and multilayered samples can be obtained based on the low LSC. A simplified model is derived, supported by experimental results, which describes the expected interference output signal of multilayered samples when high-NA lenses are used together with a narrowband light source. An expression for the correction factor for the layer thickness determination is found valid for high-NA objectives. Additionally, the method was applied to a strongly scattering layer, demonstrating the potential of this method for high-resolution imaging of scattering media.

Time-cumulated visible and infrared histograms used as descriptor of cloud cover

NASA Technical Reports Server (NTRS)

Seze, G.; Rossow, W.

1987-01-01

To study the statistical behavior of clouds for different climate regimes, the spatial and temporal stability of VIS-IR bidimensional histograms is tested. Also, the effect of data sampling and averaging on the histogram shapes is considered; in particular the sampling strategy used by the International Satellite Cloud Climatology Project is tested.

Measuring environmental change in forest ecosystems by repeated soil sampling: A North American perspective

Treesearch

Gregory B. Lawrence; Ivan J. Fernandez; Daniel D. Richter; Donald S. Ross; Paul W. Hazlett; Scott W. Bailey; Rock Ouimet; Richard A. F. Warby; Arthur H. Johnson; Henry Lin; James M. Kaste; Andrew G. Lapenis; Timothy J. Sullivan

2013-01-01

Environmental change is monitored in North America through repeated measurements of weather, stream and river flow, air and water quality, and most recently, soil properties. Some skepticism remains, however, about whether repeated soil sampling can effectively distinguish between temporal and spatial variability, and efforts to document soil change in forest...

Latent spatial models and sampling design for landscape genetics

Treesearch

Ephraim M. Hanks; Melvin B. Hooten; Steven T. Knick; Sara J. Oyler-McCance; Jennifer A. Fike; Todd B. Cross; Michael K. Schwartz

2016-01-01

We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial...

How Much Can Remotely-Sensed Natural Resource Inventories Benefit from Finer Spatial Resolutions?

NASA Astrophysics Data System (ADS)

Hou, Z.; Xu, Q.; McRoberts, R. E.; Ståhl, G.; Greenberg, J. A.

2017-12-01

For remote sensing facilitated natural resource inventories, the effects of spatial resolution in the form of pixel size and the effects of subpixel information on estimates of population parameters were evaluated by comparing results obtained using Landsat 8 and RapidEye auxiliary imagery. The study area was in Burkina Faso, and the variable of interest was the stem volume (m3/ha) convertible to the woodland aboveground biomass. A sample consisting of 160 field plots was selected and measured from the population following a two-stage sampling design. Models were fit using weighted least squares; the population mean, mu, and the variance of the estimator of the population mean, Var(mu.hat), were estimated in two inferential frameworks, model-based and model-assisted, and compared; for each framework, Var(mu.hat) was estimated both analytically and empirically. Empirical variances were estimated with bootstrapping that for resampling takes clustering effects into account. The primary results were twofold. First, for the effects of spatial resolution and subpixel information, four conclusions are relevant: (1) finer spatial resolution imagery indeed contributes to greater precision for estimators of population parameter, but this increase is slight at a maximum rate of 20% considering that RapidEye data are 36 times finer resolution than Landsat 8 data; (2) subpixel information on texture is marginally beneficial when it comes to making inference for population of large areas; (3) cost-effectiveness is more favorable for the free of charge Landsat 8 imagery than RapidEye imagery; and (4) for a given plot size, candidate remote sensing auxiliary datasets are more cost-effective when their spatial resolutions are similar to the plot size than with much finer alternatives. Second, for the comparison between estimators, three conclusions are relevant: (1) model-based variance estimates are consistent with each other and about half as large as stabilized model-assisted estimates, suggesting superior effectiveness of model-based inference to model-assisted inference; (2) bootstrapping is an effective alternative to analytical variance estimators; and (3) prediction accuracy expressed by RMSE is useful for screening candidate models to be used for population inferences.

Sleep Enhances Recognition Memory for Conspecifics as Bound into Spatial Context

PubMed Central

Sawangjit, Anuck; Kelemen, Eduard; Born, Jan; Inostroza, Marion

2017-01-01

Social memory refers to the fundamental ability of social species to recognize their conspecifics in quite different contexts. Sleep has been shown to benefit consolidation, especially of hippocampus-dependent episodic memory whereas effects of sleep on social memory are less well studied. Here, we examined the effect of sleep on memory for conspecifics in rats. To discriminate interactions between the consolidation of social memory and of spatial context during sleep, adult Long Evans rats performed on a social discrimination task in a radial arm maze. The Learning phase comprised three 10-min sampling sessions in which the rats explored a juvenile rat presented at a different arm of the maze in each session. Then the rats were allowed to sleep (n = 18) or stayed awake (n = 18) for 120 min. During the following 10-min Test phase, the familiar juvenile rat (of the Learning phase) was presented along with a novel juvenile rat, each rat at an opposite arm of the maze. Significant social recognition memory, as indicated by preferential exploration of the novel over the familiar conspecific, occurred only after post-learning sleep, but not after wakefulness. Sleep, compared with wakefulness, significantly enhanced social recognition during the first minute of the Test phase. However, memory expression depended on the spatial configuration: Significant social recognition memory emerged only after sleep when the rat encountered the novel conspecific at a place different from that of the familiar juvenile in the last sampling session before sleep. Though unspecific retrieval-related effects cannot entirely be excluded, our findings suggest that sleep, rather than independently enhancing social and spatial aspects of memory, consolidates social memory by acting on an episodic representation that binds the memory of the conspecific together with the spatial context in which it was recently encountered. PMID:28270755

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.

Two-generation analysis of pollen flow across a landscape. I. Male gamete heterogeneity among females.

PubMed

Smouse, P E; Dyer, R J; Westfall, R D; Sork, V L

2001-02-01

Gene flow is a key factor in the spatial genetic structure in spatially distributed species. Evolutionary biologists interested in microevolutionary processess and conservation biologists interested in the impact of landscape change require a method that measures the real time process of gene movement. We present a novel two-generation (parent-offspring) approach to the study of genetic structure (TwoGener) that allows us to quantify heterogeneity among the male gamete pools sampled by maternal trees scattered across the landscape and to estimate mean pollination distance and effective neighborhood size. First, we describe the model's elements: genetic distance matrices to estimate intergametic distances, molecular analysis of variance to determine whether pollen profiles differ among mothers, and optimal sampling considerations. Second, we evaluate the model's effectiveness by simulating spatially distributed populations. Spatial heterogeneity in male gametes can be estimated by phiFT, a male gametic analogue of Wright's F(ST) and an inverse function of mean pollination distance. We illustrate TwoGener in cases where the male gamete can be categorically or ambiguously determined. This approach does not require the high level of genetic resolution needed by parentage analysis, but the ambiguous case is vulnerable to bias in the absence of adequate genetic resolution. Finally, we apply TwoGener to an empirical study of Quercus alba in Missouri Ozark forests. We find that phiFT = 0.06, translating into about eight effective pollen donors per female and an effective pollination neighborhood as a circle of radius about 17 m. Effective pollen movement in Q. alba is more restricted than previously realized, even though pollen is capable of moving large distances. This case study illustrates that, with a modest investment in field survey and laboratory analysis, the TwoGener approach permits inferences about landscape-level gene movements.

Temporal and spatial variations of the Chesapeake Bay plume

NASA Technical Reports Server (NTRS)

Ruzecki, E. P.

1981-01-01

Historical records and data obtained during the Superflux experiments are used to describe the temporal and spatial variations of the effluent waters of Chesapeake Bay. The alongshore extent of the plume resulting from variations of freshwater discharge into the Bay and the effects of wind are illustrated. Variations of the cross sectional configuration of the plume over portions of a tidal cycle and results of a rapid underway water sampling system are discussed.

Evaluation of spatial and temporal patterns of insect damage and aflatoxin level in the pre-harvest corn fields to improve management tactics.

PubMed

Ni, Xinzhi; Wilson, Jeffrey P; Toews, Michael D; Buntin, G David; Lee, R Dewey; Li, Xin; Lei, Zhongren; He, Kanglai; Xu, Wenwei; Li, Xianchun; Huffaker, Alisa; Schmelz, Eric A

2014-10-01

Spatial and temporal patterns of insect damage in relation to aflatoxin contamination in a corn field with plants of uniform genetic background are not well understood. After previous examination of spatial patterns of insect damage and aflatoxin in pre-harvest corn fields, we further examined both spatial and temporal patterns of cob- and kernel-feeding insect damage, and aflatoxin level with two samplings at pre-harvest in 2008 and 2009. The feeding damage by each of the ear/kernel-feeding insects (i.e., corn earworm/fall armyworm damage on the silk/cob, and discoloration of corn kernels by stink bugs) and maize weevil population were assessed at each grid point with five ears. Sampling data showed a field edge effect in both insect damage and aflatoxin contamination in both years. Maize weevils tended toward an aggregated distribution more frequently than either corn earworm or stink bug damage in both years. The frequency of detecting aggregated distribution for aflatoxin level was less than any of the insect damage assessments. Stink bug damage and maize weevil number were more closely associated with aflatoxin level than was corn earworm damage. In addition, the indices of spatial-temporal association (χ) demonstrated that the number of maize weevils was associated between the first (4 weeks pre-harvest) and second (1 week pre-harvest) samplings in both years on all fields. In contrast, corn earworm damage between the first and second samplings from the field on the Belflower Farm, and aflatoxin level and corn earworm damage from the field on the Lang Farm were dissociated in 2009. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

Effects of methylphenidate on working memory components: influence of measurement.

PubMed

Bedard, Anne-Claude; Jain, Umesh; Johnson, Sheilah Hogg; Tannock, Rosemary

2007-09-01

To investigate the effects of methylphenidate (MPH) on components of working memory (WM) in attention-deficit hyperactivity disorder (ADHD) and determine the responsiveness of WM measures to MPH. Participants were a clinical sample of 50 children and adolescents with ADHD, aged 6 to 16 years old, who participated in an acute randomized, double-blind, placebo-controlled, crossover trial with single challenges of three MPH doses. Four components of WM were investigated, which varied in processing demands (storage versus manipulation of information) and modality (auditory-verbal; visual-spatial), each of which was indexed by a minimum of two separate measures. MPH improved the ability to store visual-spatial information irrespective of instrument used, but had no effects on the storage of auditory-verbal information. By contrast, MPH enhanced the ability to manipulate both auditory-verbal and visual-spatial information, although effects were instrument specific in both cases. MPH effects on WM are selective: they vary as a function of WM component and measurement.

How large is large enough for insects? Forest fragmentation effects at three spatial scales

NASA Astrophysics Data System (ADS)

Ribas, C. R.; Sobrinho, T. G.; Schoereder, J. H.; Sperber, C. F.; Lopes-Andrade, C.; Soares, S. M.

2005-02-01

Several mechanisms may lead to species loss in fragmented habitats, such as edge and shape effects, loss of habitat and heterogeneity. Ants and crickets were sampled in 18 forest remnants in south-eastern Brazil, to test whether a group of small remnants maintains the same insect species richness as similar sized large remnants, at three spatial scales. We tested hypotheses about alpha and gamma diversity to explain the results. Groups of remnants conserve as many species of ants as a single one. Crickets, however, showed a scale-dependent pattern: at small scales there was no significant or important difference between groups of remnants and a single one, while at the larger scale the group of remnants maintained more species. Alpha diversity (local species richness) was similar in a group of remnants and in a single one, at the three spatial scales, both for ants and crickets. Gamma diversity, however, varied both with taxa (ants and crickets) and spatial scale, which may be linked to insect mobility, remnant isolation, and habitat heterogeneity. Biological characteristics of the organisms involved have to be considered when studying fragmentation effects, as well as spatial scale at which it operates. Mobility of the organisms influences fragmentation effects, and consequently conservation strategies.

Super resolution PLIF demonstrated in turbulent jet flows seeded with I2

NASA Astrophysics Data System (ADS)

Xu, Wenjiang; Liu, Ning; Ma, Lin

2018-05-01

Planar laser induced fluorescence (PLIF) represents an indispensable tool for flow and flame imaging. However, the PLIF technique suffers from limited spatial resolution or blurring in many situations, which restricts its applicability and capability. This work describes a new method, named SR-PLIF (super-resolution PLIF), to overcome these limitations and enhance the capability of PLIF. The method uses PLIF images captured simultaneously from two (or more) orientations to reconstruct a final PLIF image with resolution enhanced or blurring removed. This paper reports the development of the reconstruction algorithm, and the experimental demonstration of the SR-PLIF method both with controlled samples and with turbulent flows seeded with iodine vapor. Using controlled samples with two cameras, the spatial resolution in the best case was improved from 0.06 mm in the projections to 0.03 mm in the SR image, in terms of the spreading width of a sharp edge. With turbulent flows, an image sharpness measure was developed to quantify the spatial resolution, and SR reconstruction with two cameras can effectively improve the spatial resolution compared to the projections in terms of the sharpness measure.

Estimation of the spatial autocorrelation function: consequences of sampling dynamic populations in space and time

Treesearch

Patrick C. Tobin

2004-01-01

The estimation of spatial autocorrelation in spatially- and temporally-referenced data is fundamental to understanding an organism's population biology. I used four sets of census field data, and developed an idealized space-time dynamic system, to study the behavior of spatial autocorrelation estimates when a practical method of sampling is employed. Estimates...

The acute effects of cocoa flavanols on temporal and spatial attention.

PubMed

Karabay, Aytaç; Saija, Jefta D; Field, David T; Akyürek, Elkan G

2018-05-01

In this study, we investigated how the acute physiological effects of cocoa flavanols might result in specific cognitive changes, in particular in temporal and spatial attention. To this end, we pre-registered and implemented a randomized, double-blind, placebo- and baseline-controlled crossover design. A sample of 48 university students participated in the study and each of them completed the experimental tasks in four conditions (baseline, placebo, low dose, and high-dose flavanol), administered in separate sessions with a 1-week washout interval. A rapid serial visual presentation task was used to test flavanol effects on temporal attention and integration, and a visual search task was similarly employed to investigate spatial attention. Results indicated that cocoa flavanols improved visual search efficiency, reflected by reduced reaction time. However, cocoa flavanols did not facilitate temporal attention nor integration, suggesting that flavanols may affect some aspects of attention, but not others. Potential underlying mechanisms are discussed.

Accurate mask-based spatially regularized correlation filter for visual tracking

NASA Astrophysics Data System (ADS)

Gu, Xiaodong; Xu, Xinping

2017-01-01

Recently, discriminative correlation filter (DCF)-based trackers have achieved extremely successful results in many competitions and benchmarks. These methods utilize a periodic assumption of the training samples to efficiently learn a classifier. However, this assumption will produce unwanted boundary effects, which severely degrade the tracking performance. Correlation filters with limited boundaries and spatially regularized DCFs were proposed to reduce boundary effects. However, their methods used the fixed mask or predesigned weights function, respectively, which was unsuitable for large appearance variation. We propose an accurate mask-based spatially regularized correlation filter for visual tracking. Our augmented objective can reduce the boundary effect even in large appearance variation. In our algorithm, the masking matrix is converted into the regularized function that acts on the correlation filter in frequency domain, which makes the algorithm fast convergence. Our online tracking algorithm performs favorably against state-of-the-art trackers on OTB-2015 Benchmark in terms of efficiency, accuracy, and robustness.

SPATIALLY-BALANCED SAMPLING OF NATURAL RESOURCES

EPA Science Inventory

The spatial distribution of a natural resource is an important consideration in designing an efficient survey or monitoring program for the resource. Generally, sample sites that are spatially-balanced, that is, more or less evenly dispersed over the extent of the resource, will ...

Sampling Strategies for Three-Dimensional Spatial Community Structures in IBD Microbiota Research

PubMed Central

Zhang, Shaocun; Cao, Xiaocang; Huang, He

2017-01-01

Identifying intestinal microbiota is arguably an important task that is performed to determine the pathogenesis of inflammatory bowel diseases (IBD); thus, it is crucial to collect and analyze intestinally-associated microbiota. Analyzing a single niche to categorize individuals does not enable researchers to comprehensively study the spatial variations of the microbiota. Therefore, characterizing the spatial community structures of the inflammatory bowel disease microbiome is critical for advancing our understanding of the inflammatory landscape of IBD. However, at present there is no universally accepted consensus regarding the use of specific sampling strategies in different biogeographic locations. In this review, we discuss the spatial distribution when screening sample collections in IBD microbiota research. Here, we propose a novel model, a three-dimensional spatial community structure, which encompasses the x-, y-, and z-axis distributions; it can be used in some sampling sites, such as feces, colonoscopic biopsy, the mucus gel layer, and oral cavity. On the basis of this spatial model, this article also summarizes various sampling and processing strategies prior to and after DNA extraction and recommends guidelines for practical application in future research. PMID:28286741

3D sensitivity encoded ellipsoidal MR spectroscopic imaging of gliomas at 3T☆

PubMed Central

Ozturk-Isik, Esin; Chen, Albert P.; Crane, Jason C.; Bian, Wei; Xu, Duan; Han, Eric T.; Chang, Susan M.; Vigneron, Daniel B.; Nelson, Sarah J.

2010-01-01

Purpose The goal of this study was to implement time efficient data acquisition and reconstruction methods for 3D magnetic resonance spectroscopic imaging (MRSI) of gliomas at a field strength of 3T using parallel imaging techniques. Methods The point spread functions, signal to noise ratio (SNR), spatial resolution, metabolite intensity distributions and Cho:NAA ratio of 3D ellipsoidal, 3D sensitivity encoding (SENSE) and 3D combined ellipsoidal and SENSE (e-SENSE) k-space sampling schemes were compared with conventional k-space data acquisition methods. Results The 3D SENSE and e-SENSE methods resulted in similar spectral patterns as the conventional MRSI methods. The Cho:NAA ratios were highly correlated (P<.05 for SENSE and P<.001 for e-SENSE) with the ellipsoidal method and all methods exhibited significantly different spectral patterns in tumor regions compared to normal appearing white matter. The geometry factors ranged between 1.2 and 1.3 for both the SENSE and e-SENSE spectra. When corrected for these factors and for differences in data acquisition times, the empirical SNRs were similar to values expected based upon theoretical grounds. The effective spatial resolution of the SENSE spectra was estimated to be same as the corresponding fully sampled k-space data, while the spectra acquired with ellipsoidal and e-SENSE k-space samplings were estimated to have a 2.36–2.47-fold loss in spatial resolution due to the differences in their point spread functions. Conclusion The 3D SENSE method retained the same spatial resolution as full k-space sampling but with a 4-fold reduction in scan time and an acquisition time of 9.28 min. The 3D e-SENSE method had a similar spatial resolution as the corresponding ellipsoidal sampling with a scan time of 4:36 min. Both parallel imaging methods provided clinically interpretable spectra with volumetric coverage and adequate SNR for evaluating Cho, Cr and NAA. PMID:19766422

A priori evaluation of two-stage cluster sampling for accuracy assessment of large-area land-cover maps

USGS Publications Warehouse

Wickham, J.D.; Stehman, S.V.; Smith, J.H.; Wade, T.G.; Yang, L.

2004-01-01

Two-stage cluster sampling reduces the cost of collecting accuracy assessment reference data by constraining sample elements to fall within a limited number of geographic domains (clusters). However, because classification error is typically positively spatially correlated, within-cluster correlation may reduce the precision of the accuracy estimates. The detailed population information to quantify a priori the effect of within-cluster correlation on precision is typically unavailable. Consequently, a convenient, practical approach to evaluate the likely performance of a two-stage cluster sample is needed. We describe such an a priori evaluation protocol focusing on the spatial distribution of the sample by land-cover class across different cluster sizes and costs of different sampling options, including options not imposing clustering. This protocol also assesses the two-stage design's adequacy for estimating the precision of accuracy estimates for rare land-cover classes. We illustrate the approach using two large-area, regional accuracy assessments from the National Land-Cover Data (NLCD), and describe how the a priorievaluation was used as a decision-making tool when implementing the NLCD design.

Housing price prediction: parametric versus semi-parametric spatial hedonic models

NASA Astrophysics Data System (ADS)

Montero, José-María; Mínguez, Román; Fernández-Avilés, Gema

2018-01-01

House price prediction is a hot topic in the economic literature. House price prediction has traditionally been approached using a-spatial linear (or intrinsically linear) hedonic models. It has been shown, however, that spatial effects are inherent in house pricing. This article considers parametric and semi-parametric spatial hedonic model variants that account for spatial autocorrelation, spatial heterogeneity and (smooth and nonparametrically specified) nonlinearities using penalized splines methodology. The models are represented as a mixed model that allow for the estimation of the smoothing parameters along with the other parameters of the model. To assess the out-of-sample performance of the models, the paper uses a database containing the price and characteristics of 10,512 homes in Madrid, Spain (Q1 2010). The results obtained suggest that the nonlinear models accounting for spatial heterogeneity and flexible nonlinear relationships between some of the individual or areal characteristics of the houses and their prices are the best strategies for house price prediction.

Breathing life into fisheries stock assessments with citizen science

PubMed Central

Fairclough, D. V.; Brown, J. I.; Carlish, B. J.; Crisafulli, B. M.; Keay, I. S.

2014-01-01

Citizen science offers a potentially cost-effective way for researchers to obtain large data sets over large spatial scales. However, it is not used widely to support biological data collection for fisheries stock assessments. Overfishing of demersal fishes along 1,000 km of the west Australian coast led to restrictive management to recover stocks. This diminished opportunities for scientists to cost-effectively monitor stock recovery via fishery-dependent sampling, particularly of the recreational fishing sector. As fishery-independent methods would be too expensive and logistically-challenging to implement, a citizen science program, Send us your skeletons (SUYS), was developed. SUYS asks recreational fishers to voluntarily donate fish skeletons of important species from their catch to allow biological data extraction by scientists to produce age structures and conduct stock assessment analyses. During SUYS, recreational fisher involvement, sample sizes and spatial and temporal coverage of samples have dramatically increased, while the collection cost per skeleton has declined substantially. SUYS is ensuring sampling objectives for stock assessments are achieved via fishery-dependent collection and reliable and timely scientific advice can be provided to managers. The program is also encouraging public ownership through involvement in the monitoring process, which can lead to greater acceptance of management decisions. PMID:25431103

Breathing life into fisheries stock assessments with citizen science.

PubMed

Fairclough, D V; Brown, J I; Carlish, B J; Crisafulli, B M; Keay, I S

2014-11-28

Citizen science offers a potentially cost-effective way for researchers to obtain large data sets over large spatial scales. However, it is not used widely to support biological data collection for fisheries stock assessments. Overfishing of demersal fishes along 1,000 km of the west Australian coast led to restrictive management to recover stocks. This diminished opportunities for scientists to cost-effectively monitor stock recovery via fishery-dependent sampling, particularly of the recreational fishing sector. As fishery-independent methods would be too expensive and logistically-challenging to implement, a citizen science program, Send us your skeletons (SUYS), was developed. SUYS asks recreational fishers to voluntarily donate fish skeletons of important species from their catch to allow biological data extraction by scientists to produce age structures and conduct stock assessment analyses. During SUYS, recreational fisher involvement, sample sizes and spatial and temporal coverage of samples have dramatically increased, while the collection cost per skeleton has declined substantially. SUYS is ensuring sampling objectives for stock assessments are achieved via fishery-dependent collection and reliable and timely scientific advice can be provided to managers. The program is also encouraging public ownership through involvement in the monitoring process, which can lead to greater acceptance of management decisions.

Spatial heterogeneity in parasite infections at different spatial scales in an intertidal bivalve.

PubMed

Thieltges, David W; Reise, Karsten

2007-01-01

Spatial heterogeneities in the abundance of free-living organisms as well as in infection levels of their parasites are a common phenomenon, but knowledge on parasitism in invertebrate intermediate hosts in this respect is scarce. We investigated the spatial pattern of four dominant trematode species which utilize a common intertidal bivalve, the cockle Cerastoderma edule, as second intermediate host in their life cycles. Sampling of cockles from the same cohort at 15 sites in the northern Wadden Sea (North Sea) over a distance of 50 km revealed a conspicuous spatial heterogeneity in infection levels in all four species over the total sample as well as among and within sampling sites. Whereas multiple regression analyses indicated the density of first intermediate upstream hosts to be the strongest determinant of infection levels in cockles, the situation within sites was more complex with no single strong predictor variable. However, host size was positively and host density negatively correlated with infection levels and there was an indication of differential susceptibility of cockle hosts. Small-scale differences in physical properties of the habitat in the form of residual water at low tide resulted in increased infection levels of cockles which we experimentally transferred into pools. A complex interplay of these factors may be responsible for within-site heterogeneities. At larger spatial scales, these factors may be overridden by the strong effect of upstream hosts. In contrast to first intermediate trematode hosts, there was no indication for inter-specific interactions. In other terms, the recruitment of trematodes in second intermediate hosts seems to be largely controlled by pre-settlement processes both among and within host populations.

Spatial Distribution of Megacopta cribraria (Hemiptera: Plataspidae) Adults, Eggs and Parasitism by Paratelenomus saccharalis (Hymenoptera: Platygastridae) in Soybean.

PubMed

Knight, Ian A; Roberts, Phillip M; Gardner, Wayne A; Oliver, Kerry M; Reay-Jones, Francis P F; Reisig, Dominic D; Toews, Michael D

2017-12-08

Since 2014, populations of the kudzu bug, Megacopta cribraria (F.) (Hemiptera: Plataspidae), have declined in the southeastern United States and seldom require treatment. This decline follows the discovery of Paratelenomus saccharalis (Dodd; Hymenoptera: Platygastridae), a non-native egg parasitoid. The objective of this project was to observe the temporal and spatial dynamics of P. saccharalis parasitism of kudzu bug egg masses in commercial soybean fields. Four fields were sampled weekly for kudzu bugs and egg masses at a density of one sample per 0.6 ha. Sampling commenced when soybean reached the R2 maturity stage and continued until no more egg masses were present. Responses including kudzu bugs, egg masses, and parasitism rates were analyzed using ANOVA, Spatial Analysis by Distance Indices (SADIE), and SaTScan spatial analysis software. Egg masses were collected from the field, held in the lab and monitored for emergence of kudzu bug nymphs or P. saccharalis. Kudzu bug populations were generally lower than previously reported in the literature and spatial aggregation was not consistently observed. Egg parasitism was first detected in early July and increased to nearly 40% in mid-August. Significant spatial patterns in parasitism were observed with spatio-temporal clusters being loosely associated with clusters of egg masses. There were no significant differences in parasitism rates between field margins and interiors, suggesting that P. saccharalis is an effective parasitoid of kudzu bug egg masses on a whole-field scale. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Spatial Distribution of Lead Iodide and Local Passivation on Organo-Lead Halide Perovskite.

PubMed

Chen, Sheng; Wen, Xiaoming; Yun, Jae S; Huang, Shujuan; Green, Martin; Jeon, Nam Joong; Yang, Woon Seok; Noh, Jun Hong; Seo, Jangwon; Seok, Sang Il; Ho-Baillie, Anita

2017-02-22

We identify nanoscale spatial distribution of PbI 2 on the (FAPbI 3 ) 0.85 (MAPbBr 3 ) 0.15 perovskite thin film and investigate the local passivation effect using confocal based optical microscopy of steady state and time-resolved photoluminescence (PL). Different from a typical scanning electron microscope (SEM) morphology study, confocal based PL spectroscopy and microscopy allow researchers to map the morphologies of both perovskite and PbI 2 grains simultaneously, by selectively detecting their characteristic fluorescent bands using band-pass filters. In this work, we compare the perovskite samples without and with excess PbI 2 incorporation and unambiguously reveal PbI 2 distribution for the PbI 2 -rich sample. In addition, using the nanoscale time-resolved PL technique we show that the PbI 2 -rich regions exhibit longer lifetime due to suppressed defect trapping, compared to the PbI 2 -poor regions. The measurement on the PbI 2 -rich sample indicates that the passivation effect of PbI 2 in perovskite film is effective, especially in localized regions. Hence, this finding is important for further improvement of the solar cells by considering the strategy of excess PbI 2 incorporation.

Network analysis reveals multiscale controls on streamwater chemistry

USGS Publications Warehouse

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Network analysis reveals multiscale controls on streamwater chemistry

PubMed Central

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks. PMID:24753575

Network analysis reveals multiscale controls on streamwater chemistry.

PubMed

McGuire, Kevin J; Torgersen, Christian E; Likens, Gene E; Buso, Donald C; Lowe, Winsor H; Bailey, Scott W

2014-05-13

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Instantaneous field of view and spatial sampling of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

NASA Technical Reports Server (NTRS)

Chrien, Thomas G.; Green, Robert O.

1993-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures the upwelling radiance in 224 spectral bands. These data are required as images of approximately 11 by up to 100 km in extent at nominally 20 by 20 meter spatial resolution. In this paper we describe the underlying spatial sampling and spatial response characteristics of AVIRIS.

[Study of spatial stratified sampling strategy of Oncomelania hupensis snail survey based on plant abundance].

PubMed

Xun-Ping, W; An, Z

2017-07-27

Objective To optimize and simplify the survey method of Oncomelania hupensis snails in marshland endemic regions of schistosomiasis, so as to improve the precision, efficiency and economy of the snail survey. Methods A snail sampling strategy (Spatial Sampling Scenario of Oncomelania based on Plant Abundance, SOPA) which took the plant abundance as auxiliary variable was explored and an experimental study in a 50 m×50 m plot in a marshland in the Poyang Lake region was performed. Firstly, the push broom surveyed data was stratified into 5 layers by the plant abundance data; then, the required numbers of optimal sampling points of each layer through Hammond McCullagh equation were calculated; thirdly, every sample point in the line with the Multiple Directional Interpolation (MDI) placement scheme was pinpointed; and finally, the comparison study among the outcomes of the spatial random sampling strategy, the traditional systematic sampling method, the spatial stratified sampling method, Sandwich spatial sampling and inference and SOPA was performed. Results The method (SOPA) proposed in this study had the minimal absolute error of 0.213 8; and the traditional systematic sampling method had the largest estimate, and the absolute error was 0.924 4. Conclusion The snail sampling strategy (SOPA) proposed in this study obtains the higher estimation accuracy than the other four methods.

Adapting populations in space: clonal interference and genetic diversity

NASA Astrophysics Data System (ADS)

Weissman, Daniel; Barton, Nick

Most species inhabit ranges much larger than the scales over which individuals interact. How does this spatial structure interact with adaptive evolution? We consider a simple model of a spatially-extended, adapting population and show that, while clonal interference severely limits the adaptation of purely asexual populations, even rare recombination is enough to allow adaptation at rates approaching those of well-mixed populations. We also find that the genetic hitchhiking produced by the adaptive alleles sweeping through the population has strange effects on the patterns of genetic diversity. In large spatial ranges, even low rates of adaptation cause all individuals in the population to rapidly trace their ancestry back to individuals living in a small region in the center of the range. The probability of fixation of an allele is thus strongly dependent on the allele's spatial location, with alleles from the center favored. Surprisingly, these effects are seen genome-wide (instead of being localized to the regions of the genome undergoing the sweeps). The spatial concentration of ancestry produces a power-law dependence of relatedness on distance, so that even individuals sampled far apart are likely to be fairly closely related, masking the underlying spatial structure.

Unbiased estimation of oceanic mean rainfall from satellite borne radiometer measurements

NASA Technical Reports Server (NTRS)

Mittal, M. C.

1981-01-01

The statistical properties of the radar derived rainfall obtained during the GARP Atlantic Tropical Experiment (GATE) are used to derive quantitative estimates of the spatial and temporal sampling errors associated with estimating rainfall from brightness temperature measurements such as would be obtained from a satelliteborne microwave radiometer employing a practical size antenna aperture. A basis for a method of correcting the so called beam filling problem, i.e., for the effect of nonuniformity of rainfall over the radiometer beamwidth is provided. The method presented employs the statistical properties of the observations themselves without need for physical assumptions beyond those associated with the radiative transfer model. The simulation results presented offer a validation of the estimated accuracy that can be achieved and the graphs included permit evaluation of the effect of the antenna resolution on both the temporal and spatial sampling errors.

A Bayesian hierarchical model with spatial variable selection: the effect of weather on insurance claims

PubMed Central

Scheel, Ida; Ferkingstad, Egil; Frigessi, Arnoldo; Haug, Ola; Hinnerichsen, Mikkel; Meze-Hausken, Elisabeth

2013-01-01

Climate change will affect the insurance industry. We develop a Bayesian hierarchical statistical approach to explain and predict insurance losses due to weather events at a local geographic scale. The number of weather-related insurance claims is modelled by combining generalized linear models with spatially smoothed variable selection. Using Gibbs sampling and reversible jump Markov chain Monte Carlo methods, this model is fitted on daily weather and insurance data from each of the 319 municipalities which constitute southern and central Norway for the period 1997–2006. Precise out-of-sample predictions validate the model. Our results show interesting regional patterns in the effect of different weather covariates. In addition to being useful for insurance pricing, our model can be used for short-term predictions based on weather forecasts and for long-term predictions based on downscaled climate models. PMID:23396890

What does visual suffix interference tell us about spatial location in working memory?

PubMed

Allen, Richard J; Castellà, Judit; Ueno, Taiji; Hitch, Graham J; Baddeley, Alan D

2015-01-01

A visual object can be conceived of as comprising a number of features bound together by their joint spatial location. We investigate the question of whether the spatial location is automatically bound to the features or whether the two are separable, using a previously developed paradigm whereby memory is disrupted by a visual suffix. Participants were shown a sample array of four colored shapes, followed by a postcue indicating the target for recall. On randomly intermixed trials, a to-be-ignored suffix array consisting of two different colored shapes was presented between the sample and the postcue. In a random half of suffix trials, one of the suffix items overlaid the location of the target. If location was automatically encoded, one might expect the colocation of target and suffix to differentially impair performance. We carried out three experiments, cuing for recall by spatial location (Experiment 1), color or shape (Experiment 2), or both randomly intermixed (Experiment 3). All three studies showed clear suffix effects, but the colocation of target and suffix was differentially disruptive only when a spatial cue was used. The results suggest that purely visual shape-color binding can be retained and accessed without requiring information about spatial location, even when task demands encourage the encoding of location, consistent with the idea of an abstract and flexible visual working memory system.

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.

The Corticostriatal Adenosine A2A Receptor Controls Maintenance and Retrieval of Spatial Working Memory.

PubMed

Li, Zhihui; Chen, Xingjun; Wang, Tao; Gao, Ying; Li, Fei; Chen, Long; Xue, Jin; He, Yan; Li, Yan; Guo, Wei; Zheng, Wu; Zhang, Liping; Ye, Fenfen; Ren, Xiangpeng; Feng, Yue; Chan, Piu; Chen, Jiang-Fan

2018-03-15

Working memory (WM) taps into multiple executive processes including encoding, maintenance, and retrieval of information, but the molecular and circuit modulation of these WM processes remains undefined due to the lack of methods to control G protein-coupled receptor signaling with temporal resolution of seconds. By coupling optogenetic control of the adenosine A 2A receptor (A 2A R) signaling, the Cre-loxP-mediated focal A 2A R knockdown with a delayed non-match-to-place (DNMTP) task, we investigated the effect of optogenetic activation and focal knockdown of A 2A Rs in the dorsomedial striatum (n = 8 to 14 per group) and medial prefrontal cortex (n = 16 to 22 per group) on distinct executive processes of spatial WM. We also evaluated the therapeutic effect of the A 2A R antagonist KW6002 on delayed match-to-sample/place tasks in 6 normal and 6 MPTP-treated cynomolgus monkeys. Optogenetic activation of striatopallidal A 2A Rs in the dorsomedial striatum selectively at the delay and choice (not sample) phases impaired DNMTP performance. Optogenetic activation of A 2A Rs in the medial prefrontal cortex selectively at the delay (not sample or choice) phase improved DNMTP performance. The corticostriatal A 2A R control of spatial WM was specific for a novel but not well-trained DNMTP task. Focal dorsomedial striatum A 2A R knockdown or KW6002 improved DNMTP performance in mice. Last, KW6002 improved spatial WM in delayed match-to-sample and delayed match-to-place tasks of normal and dopamine-depleted cynomolgus monkeys. The A 2A Rs in striatopallidal and medial prefrontal cortex neurons exert distinctive control of WM maintenance and retrieval to achieve cognitive stability and flexibility. The procognitive effect of KW6002 in nonhuman primates provides the preclinical data to translate A 2A R antagonists for improving cognitive impairments in Parkinson's disease. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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.

Sampling procedures for inventory of commercial volume tree species in Amazon Forest.

PubMed

Netto, Sylvio P; Pelissari, Allan L; Cysneiros, Vinicius C; Bonazza, Marcelo; Sanquetta, Carlos R

2017-01-01

The spatial distribution of tropical tree species can affect the consistency of the estimators in commercial forest inventories, therefore, appropriate sampling procedures are required to survey species with different spatial patterns in the Amazon Forest. For this, the present study aims to evaluate the conventional sampling procedures and introduce the adaptive cluster sampling for volumetric inventories of Amazonian tree species, considering the hypotheses that the density, the spatial distribution and the zero-plots affect the consistency of the estimators, and that the adaptive cluster sampling allows to obtain more accurate volumetric estimation. We use data from a census carried out in Jamari National Forest, Brazil, where trees with diameters equal to or higher than 40 cm were measured in 1,355 plots. Species with different spatial patterns were selected and sampled with simple random sampling, systematic sampling, linear cluster sampling and adaptive cluster sampling, whereby the accuracy of the volumetric estimation and presence of zero-plots were evaluated. The sampling procedures applied to species were affected by the low density of trees and the large number of zero-plots, wherein the adaptive clusters allowed concentrating the sampling effort in plots with trees and, thus, agglutinating more representative samples to estimate the commercial volume.

Sources of errors and uncertainties in the assessment of forest soil carbon stocks at different scales-review and recommendations.

PubMed

Vanguelova, E I; Bonifacio, E; De Vos, B; Hoosbeek, M R; Berger, T W; Vesterdal, L; Armolaitis, K; Celi, L; Dinca, L; Kjønaas, O J; Pavlenda, P; Pumpanen, J; Püttsepp, Ü; Reidy, B; Simončič, P; Tobin, B; Zhiyanski, M

2016-11-01

Spatially explicit knowledge of recent and past soil organic carbon (SOC) stocks in forests will improve our understanding of the effect of human- and non-human-induced changes on forest C fluxes. For SOC accounting, a minimum detectable difference must be defined in order to adequately determine temporal changes and spatial differences in SOC. This requires sufficiently detailed data to predict SOC stocks at appropriate scales within the required accuracy so that only significant changes are accounted for. When designing sampling campaigns, taking into account factors influencing SOC spatial and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need to be defined: profile, plot, forests, catchment, national or wider. Scaling up SOC stocks from point sample to landscape unit is challenging, and thus requires reliable baseline data. Knowledge of the associated uncertainties related to SOC measures at each particular scale and how to reduce them is crucial for assessing SOC stocks with the highest possible accuracy at each scale. This review identifies where potential sources of errors and uncertainties related to forest SOC stock estimation occur at five different scales-sample, profile, plot, landscape/regional and European. Recommendations are also provided on how to reduce forest SOC uncertainties and increase efficiency of SOC assessment at each scale.

The connection between the peaks in velocity dispersion and star-forming clumps of turbulent galaxies

NASA Astrophysics Data System (ADS)

Oliva-Altamirano, P.; Fisher, D. B.; Glazebrook, K.; Wisnioski, E.; Bekiaris, G.; Bassett, R.; Obreschkow, D.; Abraham, R.

2018-02-01

We present Keck/OSIRIS adaptive optics observations with 150-400 pc spatial sampling of 7 turbulent, clumpy disc galaxies from the DYNAMO sample ($0.07

The experiment of cooperative learning model type team assisted individualization (TAI) on three-dimensional space subject viewed from spatial intelligence

NASA Astrophysics Data System (ADS)

Manapa, I. Y. H.; Budiyono; Subanti, S.

2018-03-01

The aim of this research is to determine the effect of TAI or direct learning (DL) on student’s mathematics achievement viewed from spatial intelligence. This research was quasi experiment. The population was 10th grade senior high school students in Alor Regency on academic year of 2015/2016 chosen by stratified cluster random sampling. The data were collected through achievement and spatial intelligence test. The data were analyzed by two ways, ANOVA with unequal cell and scheffe test. This research showed that student’s mathematics achievement used in TAI had better results than DL models one. In spatial intelligence category, student’s mathematics achievement with high spatial intelligence has better result than the other spatial intelligence category and students with high spatial intelligence have better results than those with middle spatial intelligence category. At TAI, student’s mathematics achievement with high spatial intelligence has better result than those with the other spatial intelligence category and students with middle spatial intelligence have better results than students with low spatial intelligence. In DL model, student’s mathematics achievement with high and middle spatial intelligence has better result than those with low spatial intelligence, but students with high spatial intelligence and middle spatial intelligence have no significant difference. In each category of spatial intelligence and learning model, mathematics achievement has no significant difference.

The New Bedford Harbor Superfund site long-term monitoring program (1993-2009).

PubMed

Nelson, William G; Bergen, Barbara J

2012-12-01

New Bedford Harbor (NBH), located in southeastern Massachusetts, was designated as a marine Superfund site in 1983 due to sediment contamination by polychlorinated biphenyls (PCBs). Based on risks to human health and the environment, the first two phases of the site cleanup involved dredging PCB-contaminated sediments from the harbor. Therefore, a long-term monitoring program (LTM) was developed to measure spatial and temporal chemical and biological changes in sediment, water, and biota to assess the effects and effectiveness of the remedial activities. A systematic, probabilistic sampling design was used to select sediment sampling stations. This unbiased design allowed the three segments of the harbor to be compared spatially and temporally to quantify changes resulting from dredging the contaminated sediments. Sediment was collected at each station, and chemical (e.g., PCBs and metals), physical (e.g., grain size), and biological (e.g., benthic community) measurements were conducted on all samples. This paper describes the overall NBH-LTM approach and the results from the five rounds of sample collections. There is a decreasing spatial gradient in sediment PCB concentrations from the northern boundary (upper harbor) to the southern boundary (outer harbor) of the site. Along this same transect, there is an increase in biological condition (e.g., benthic community diversity). Temporally, the contaminant and biological gradients have been maintained since the 1993 baseline collection; however, since the onset of full-scale remediation, PCB concentrations have decreased throughout the site, and one of the benthic community indices has shown significant improvement in the lower and outer harbor areas.

An evaluation of potential sampling locations in a reservoir with emphasis on conserved spatial correlation structure.

PubMed

Yenilmez, Firdes; Düzgün, Sebnem; Aksoy, Aysegül

2015-01-01

In this study, kernel density estimation (KDE) was coupled with ordinary two-dimensional kriging (OK) to reduce the number of sampling locations in measurement and kriging of dissolved oxygen (DO) concentrations in Porsuk Dam Reservoir (PDR). Conservation of the spatial correlation structure in the DO distribution was a target. KDE was used as a tool to aid in identification of the sampling locations that would be removed from the sampling network in order to decrease the total number of samples. Accordingly, several networks were generated in which sampling locations were reduced from 65 to 10 in increments of 4 or 5 points at a time based on kernel density maps. DO variograms were constructed, and DO values in PDR were kriged. Performance of the networks in DO estimations were evaluated through various error metrics, standard error maps (SEM), and whether the spatial correlation structure was conserved or not. Results indicated that smaller number of sampling points resulted in loss of information in regard to spatial correlation structure in DO. The minimum representative sampling points for PDR was 35. Efficacy of the sampling location selection method was tested against the networks generated by experts. It was shown that the evaluation approach proposed in this study provided a better sampling network design in which the spatial correlation structure of DO was sustained for kriging.

Experiment, monitoring, and gradient methods used to infer climate change effects on plant communities yield consistent patterns.

PubMed

Elmendorf, Sarah C; Henry, Gregory H R; Hollister, Robert D; Fosaa, Anna Maria; Gould, William A; Hermanutz, Luise; Hofgaard, Annika; Jónsdóttir, Ingibjörg S; Jónsdóttir, Ingibjörg I; Jorgenson, Janet C; Lévesque, Esther; Magnusson, Borgþór; Molau, Ulf; Myers-Smith, Isla H; Oberbauer, Steven F; Rixen, Christian; Tweedie, Craig E; Walker, Marilyn D; Walker, Marilyn

2015-01-13

Inference about future climate change impacts typically relies on one of three approaches: manipulative experiments, historical comparisons (broadly defined to include monitoring the response to ambient climate fluctuations using repeat sampling of plots, dendroecology, and paleoecology techniques), and space-for-time substitutions derived from sampling along environmental gradients. Potential limitations of all three approaches are recognized. Here we address the congruence among these three main approaches by comparing the degree to which tundra plant community composition changes (i) in response to in situ experimental warming, (ii) with interannual variability in summer temperature within sites, and (iii) over spatial gradients in summer temperature. We analyzed changes in plant community composition from repeat sampling (85 plant communities in 28 regions) and experimental warming studies (28 experiments in 14 regions) throughout arctic and alpine North America and Europe. Increases in the relative abundance of species with a warmer thermal niche were observed in response to warmer summer temperatures using all three methods; however, effect sizes were greater over broad-scale spatial gradients relative to either temporal variability in summer temperature within a site or summer temperature increases induced by experimental warming. The effect sizes for change over time within a site and with experimental warming were nearly identical. These results support the view that inferences based on space-for-time substitution overestimate the magnitude of responses to contemporary climate warming, because spatial gradients reflect long-term processes. In contrast, in situ experimental warming and monitoring approaches yield consistent estimates of the magnitude of response of plant communities to climate warming.

Using larval fish community structure to guide long-term monitoring of fish spawning activity

USGS Publications Warehouse

Pritt, Jeremy J.; Roseman, Edward F.; Ross, Jason E.; DeBruyne, Robin L.

2015-01-01

Larval fishes provide a direct indication of spawning activity and may therefore be useful for long-term monitoring efforts in relation to spawning habitat restoration. However, larval fish sampling can be time intensive and costly. We sought to understand the spatial and temporal structure of larval fish communities in the St. Clair–Detroit River system, Michigan–Ontario, to determine whether targeted larval fish sampling can be made more efficient for long-term monitoring. We found that larval fish communities were highly nested, with lower river segments and late-spring samples containing the highest genus richness of larval fish. We created four sampling scenarios for each river system: (1) using all available data, (2) limiting temporal sampling to late spring, (3) limiting spatial sampling to lower river segments only, and (4) limiting both spatial and temporal sampling. By limiting the spatial extent of sampling to lower river sites and/or limiting the temporal extent to the late-spring period, we found that effort could be reduced by more than 50% while maintaining over 75% of the observed and estimated total genus richness. Similarly, limiting the sampling effort to lower river sites and/or the late-spring period maintained between 65% and 93% of the observed richness of lithophilic-spawning genera and invasive genera. In general, community composition remained consistent among sampling scenarios. Targeted sampling offers a lower-cost alternative to exhaustive spatial and temporal sampling and may be more readily incorporated into long-term monitoring.

Bayesian spatio-temporal discard model in a demersal trawl fishery

NASA Astrophysics Data System (ADS)

Grazia Pennino, M.; Muñoz, Facundo; Conesa, David; López-Quílez, Antonio; Bellido, José M.

2014-07-01

Spatial management of discards has recently been proposed as a useful tool for the protection of juveniles, by reducing discard rates and can be used as a buffer against management errors and recruitment failure. In this study Bayesian hierarchical spatial models have been used to analyze about 440 trawl fishing operations of two different metiers, sampled between 2009 and 2012, in order to improve our understanding of factors that influence the quantity of discards and to identify their spatio-temporal distribution in the study area. Our analysis showed that the relative importance of each variable was different for each metier, with a few similarities. In particular, the random vessel effect and seasonal variability were identified as main driving variables for both metiers. Predictive maps of the abundance of discards and maps of the posterior mean of the spatial component show several hot spots with high discard concentration for each metier. We argue how the seasonal/spatial effects, and the knowledge about the factors influential to discarding, could potentially be exploited as potential mitigation measures for future fisheries management strategies. However, misidentification of hotspots and uncertain predictions can culminate in inappropriate mitigation practices which can sometimes be irreversible. The proposed Bayesian spatial method overcomes these issues, since it offers a unified approach which allows the incorporation of spatial random-effect terms, spatial correlation of the variables and the uncertainty of the parameters in the modeling process, resulting in a better quantification of the uncertainty and accurate predictions.

Visual signal detection in structured backgrounds. II. Effects of contrast gain control, background variations, and white noise

NASA Technical Reports Server (NTRS)

Eckstein, M. P.; Ahumada, A. J. Jr; Watson, A. B.

1997-01-01

Studies of visual detection of a signal superimposed on one of two identical backgrounds show performance degradation when the background has high contrast and is similar in spatial frequency and/or orientation to the signal. To account for this finding, models include a contrast gain control mechanism that pools activity across spatial frequency, orientation and space to inhibit (divisively) the response of the receptor sensitive to the signal. In tasks in which the observer has to detect a known signal added to one of M different backgrounds grounds due to added visual noise, the main sources of degradation are the stochastic noise in the image and the suboptimal visual processing. We investigate how these two sources of degradation (contrast gain control and variations in the background) interact in a task in which the signal is embedded in one of M locations in a complex spatially varying background (structured background). We use backgrounds extracted from patient digital medical images. To isolate effects of the fixed deterministic background (the contrast gain control) from the effects of the background variations, we conduct detection experiments with three different background conditions: (1) uniform background, (2) a repeated sample of structured background, and (3) different samples of structured background. Results show that human visual detection degrades from the uniform background condition to the repeated background condition and degrades even further in the different backgrounds condition. These results suggest that both the contrast gain control mechanism and the background random variations degrade human performance in detection of a signal in a complex, spatially varying background. A filter model and added white noise are used to generate estimates of sampling efficiencies, an equivalent internal noise, an equivalent contrast-gain-control-induced noise, and an equivalent noise due to the variations in the structured background.

Persistent spatial information in the frontal eye field during object-based short-term memory.

PubMed

Clark, Kelsey L; Noudoost, Behrad; Moore, Tirin

2012-08-08

Spatial attention is known to gate entry into visual short-term memory, and some evidence suggests that spatial signals may also play a role in binding features or protecting object representations during memory maintenance. To examine the persistence of spatial signals during object short-term memory, the activity of neurons in the frontal eye field (FEF) of macaque monkeys was recorded during an object-based delayed match-to-sample task. In this task, monkeys were trained to remember an object image over a brief delay, regardless of the locations of the sample or target presentation. FEF neurons exhibited visual, delay, and target period activity, including selectivity for sample location and target location. Delay period activity represented the sample location throughout the delay, despite the irrelevance of spatial information for successful task completion. Furthermore, neurons continued to encode sample position in a variant of the task in which the matching stimulus never appeared in their response field, confirming that FEF maintains sample location independent of subsequent behavioral relevance. FEF neurons also exhibited target-position-dependent anticipatory activity immediately before target onset, suggesting that monkeys predicted target position within blocks. These results show that FEF neurons maintain spatial information during short-term memory, even when that information is irrelevant for task performance.

Collocation mismatch uncertainties in satellite aerosol retrieval validation

NASA Astrophysics Data System (ADS)

Virtanen, Timo H.; Kolmonen, Pekka; Sogacheva, Larisa; Rodríguez, Edith; Saponaro, Giulia; de Leeuw, Gerrit

2018-02-01

Satellite-based aerosol products are routinely validated against ground-based reference data, usually obtained from sun photometer networks such as AERONET (AEROsol RObotic NETwork). In a typical validation exercise a spatial sample of the instantaneous satellite data is compared against a temporal sample of the point-like ground-based data. The observations do not correspond to exactly the same column of the atmosphere at the same time, and the representativeness of the reference data depends on the spatiotemporal variability of the aerosol properties in the samples. The associated uncertainty is known as the collocation mismatch uncertainty (CMU). The validation results depend on the sampling parameters. While small samples involve less variability, they are more sensitive to the inevitable noise in the measurement data. In this paper we study systematically the effect of the sampling parameters in the validation of AATSR (Advanced Along-Track Scanning Radiometer) aerosol optical depth (AOD) product against AERONET data and the associated collocation mismatch uncertainty. To this end, we study the spatial AOD variability in the satellite data, compare it against the corresponding values obtained from densely located AERONET sites, and assess the possible reasons for observed differences. We find that the spatial AOD variability in the satellite data is approximately 2 times larger than in the ground-based data, and the spatial variability correlates only weakly with that of AERONET for short distances. We interpreted that only half of the variability in the satellite data is due to the natural variability in the AOD, and the rest is noise due to retrieval errors. However, for larger distances (˜ 0.5°) the correlation is improved as the noise is averaged out, and the day-to-day changes in regional AOD variability are well captured. Furthermore, we assess the usefulness of the spatial variability of the satellite AOD data as an estimate of CMU by comparing the retrieval errors to the total uncertainty estimates including the CMU in the validation. We find that accounting for CMU increases the fraction of consistent observations.

Two and three-dimensional quantitative neutron imaging of the water distribution during ponded infiltration

NASA Astrophysics Data System (ADS)

Sacha, Jan; Snehota, Michal; Jelinkova, Vladimira

2016-04-01

Information on spatial and temporal water and air distribution in a soil sample during hydrological processes is important for evaluating current and developing new water transport models. Modern imaging techniques such as neutron imaging (NI) allow relatively short acquisition times and high resolution of images. At the same time, the appropriate data processing has to be applied to obtain results free of bias and artifacts. In this study a ponded infiltration experiments were conducted on two soil samples packed into the quartz glass columns of inner diameter of 29 and 34 mm, respectively. First sample was prepared by packing of fine and coarse fractions of sand and the second sample was packed using coarse sand and disks of fine porous ceramic. Ponded infiltration experiments conducted on both samples were monitored by neutron radiography to produce two dimensional (2D) projection images during the transient phase of infiltration. During the steady state flow stage of experiments neutron tomography was utilized to obtain three-dimensional (3D) information on gradual water redistribution. The acquired radiographic images were normalized for background noise and spatial inhomogeneity of the detector, fluctuations of the neutron flux in time and for spatial inhomogeneity of the neutron beam. The radiograms of dry sample were subtracted from all subsequent radiograms to determine water thickness in the 2D projection images. All projections were corrected for beam hardening and neutron scattering by empirical method of Kang et al. (2013). Parameters of the correction method uses were identified by two different approaches. The first approach was based on fitting the NI derived water thickness representing the water filled region in the layer of water above the sample surface to actual water thickness. In the second approach the NI derived volume of water in the entire sample in given time was fitted to corresponding gravimetrically determined amount of water in the sample. Tomography images were reconstructed from the both corrected and uncorrected water thickness maps to obtain the 3D spatial distribution of water content within the sample. Without the correction the beam hardening and scattering effects overestimated the water content values close to the sample perimeter and underestimated the values close to the center of the sample, however the total water content of whole sample was the same in both cases.

Reducing uncertainty in dust monitoring to detect aeolian sediment transport responses to land cover change

NASA Astrophysics Data System (ADS)

Webb, N.; Chappell, A.; Van Zee, J.; Toledo, D.; Duniway, M.; Billings, B.; Tedela, N.

2017-12-01

Anthropogenic land use and land cover change (LULCC) influence global rates of wind erosion and dust emission, yet our understanding of the magnitude of the responses remains poor. Field measurements and monitoring provide essential data to resolve aeolian sediment transport patterns and assess the impacts of human land use and management intensity. Data collected in the field are also required for dust model calibration and testing, as models have become the primary tool for assessing LULCC-dust cycle interactions. However, there is considerable uncertainty in estimates of dust emission due to the spatial variability of sediment transport. Field sampling designs are currently rudimentary and considerable opportunities are available to reduce the uncertainty. Establishing the minimum detectable change is critical for measuring spatial and temporal patterns of sediment transport, detecting potential impacts of LULCC and land management, and for quantifying the uncertainty of dust model estimates. Here, we evaluate the effectiveness of common sampling designs (e.g., simple random sampling, systematic sampling) used to measure and monitor aeolian sediment transport rates. Using data from the US National Wind Erosion Research Network across diverse rangeland and cropland cover types, we demonstrate how only large changes in sediment mass flux (of the order 200% to 800%) can be detected when small sample sizes are used, crude sampling designs are implemented, or when the spatial variation is large. We then show how statistical rigour and the straightforward application of a sampling design can reduce the uncertainty and detect change in sediment transport over time and between land use and land cover types.

Functional cerebral distance and the effect of emotional music on spatial rotation scores in undergraduate women and men.

PubMed

Bertsch, Sharon; Knee, H Donald; Webb, Jeffrey L

2011-02-01

The influence of listening to music on subsequent spatial rotation scores has a controversial history. The effect is unreliable, seeming to depend on several as yet unexplored factors. Using a large sample (167 women, 160 men; M age = 18.9 yr.), two related variables were investigated: participants' sex and the emotion conveyed by the music. Participants listened to 90 sec. of music that portrayed emotions of approach (happiness), or withdrawal (anger), or heard no music at all. They then performed a two-dimensional spatial rotation task. No significant difference was found in spatial rotation scores between groups exposed to music and those who were not. However, a significant interaction was found based on the sex of the participants and the emotion portrayed in the music they heard. Women's scores increased (relative to a no-music condition) only after hearing withdrawal-based music, while men's scores increased only after listening to the approach-based music. These changes were explained using the theory of functional cerebral distance.

Spatial Mapping of Organic Carbon in Returned Samples from Mars

NASA Astrophysics Data System (ADS)

Siljeström, S.; Fornaro, T.; Greenwalt, D.; Steele, A.

2018-04-01

To map organic material spatially to minerals present in the sample will be essential for the understanding of the origin of any organics in returned samples from Mars. It will be shown how ToF-SIMS may be used to map organics in samples from Mars.

Optimization of Sample Points for Monitoring Arable Land Quality by Simulated Annealing while Considering Spatial Variations

PubMed Central

Wang, Junxiao; Wang, Xiaorui; Zhou, Shenglu; Wu, Shaohua; Zhu, Yan; Lu, Chunfeng

2016-01-01

With China’s rapid economic development, the reduction in arable land has emerged as one of the most prominent problems in the nation. The long-term dynamic monitoring of arable land quality is important for protecting arable land resources. An efficient practice is to select optimal sample points while obtaining accurate predictions. To this end, the selection of effective points from a dense set of soil sample points is an urgent problem. In this study, data were collected from Donghai County, Jiangsu Province, China. The number and layout of soil sample points are optimized by considering the spatial variations in soil properties and by using an improved simulated annealing (SA) algorithm. The conclusions are as follows: (1) Optimization results in the retention of more sample points in the moderate- and high-variation partitions of the study area; (2) The number of optimal sample points obtained with the improved SA algorithm is markedly reduced, while the accuracy of the predicted soil properties is improved by approximately 5% compared with the raw data; (3) With regard to the monitoring of arable land quality, a dense distribution of sample points is needed to monitor the granularity. PMID:27706051

Evaluating the effect of spatial subsetting on subpixel unmixing methodology applied to ASTER over a hydrothermally altered terrain

NASA Astrophysics Data System (ADS)

Ayoobi, Iman; Tangestani, Majid H.

2017-10-01

This study investigates the effect of spatial subsets of Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) L1B visible-near infrared and short wave-infrared (VNIR-SWIR) data on matched filtering results at the central part of Kerman magmatic arc, where abundant porphyry copper deposits exist. The matched filtering (MF) procedure was run separately at sites containing hydrothermal minerals such as sericite, kaolinite, chlorite, and jarosite to map the abundances of these minerals on spatial subsets containing 100, 75, 50, and 25 percent of the original scene. Results were evaluated by comparing the matched filtering scores with the mineral abundances obtained by semi-quantitative XRD analysis of corresponding field samples. It was concluded that MF method should be applied to the whole scene prior to any data subsetting.

Characterization of the spatial variability of soil available zinc at various sampling densities using grouped soil type information.

PubMed

Song, Xiao-Dong; Zhang, Gan-Lin; Liu, Feng; Li, De-Cheng; Zhao, Yu-Guo

2016-11-01

The influence of anthropogenic activities and natural processes involved high uncertainties to the spatial variation modeling of soil available zinc (AZn) in plain river network regions. Four datasets with different sampling densities were split over the Qiaocheng district of Bozhou City, China. The difference of AZn concentrations regarding soil types was analyzed by the principal component analysis (PCA). Since the stationarity was not indicated and effective ranges of four datasets were larger than the sampling extent (about 400 m), two investigation tools, namely F3 test and stationarity index (SI), were employed to test the local non-stationarity. Geographically weighted regression (GWR) technique was performed to describe the spatial heterogeneity of AZn concentrations under the non-stationarity assumption. GWR based on grouped soil type information (GWRG for short) was proposed so as to benefit the local modeling of soil AZn within each soil-landscape unit. For reference, the multiple linear regression (MLR) model, a global regression technique, was also employed and incorporated the same predictors as in the GWR models. Validation results based on 100 times realization demonstrated that GWRG outperformed MLR and can produce similar or better accuracy than the GWR approach. Nevertheless, GWRG can generate better soil maps than GWR for limit soil data. Two-sample t test of produced soil maps also confirmed significantly different means. Variogram analysis of the model residuals exhibited weak spatial correlation, rejecting the use of hybrid kriging techniques. As a heuristically statistical method, the GWRG was beneficial in this study and potentially for other soil properties.

Spatial mapping of lead, arsenic, iron, and polycyclic aromatic hydrocarbon soil contamination in Sydney, Nova Scotia: community impact from the coke ovens and steel plant.

PubMed

Lambert, Timothy W; Boehmer, Jennifer; Feltham, Jason; Guyn, Lindsay; Shahid, Rizwan

2011-01-01

This paper presents spatial maps of the arsenic, lead, and polycyclic aromatic hydrocarbon (PAH) soil contamination in Sydney, Nova Scotia, Canada. The spatial maps were designed to create exposure cohorts to help understand the observed increase in health effects. To assess whether contamination can be a proxy for exposures, the following hypothesis was tested: residential soils were impacted by the coke oven and steel plant industrial complex. The spatial map showed contaminants are centered on the industrial facility, significantly correlated, and exceed Canadian health risk-based soil quality guidelines. Core samples taken at 5-cm intervals suggest a consistent deposition over time. The concentrations in Sydney significantly exceed background Sydney soil concentrations, and are significantly elevated compared with North Sydney, an adjacent industrial community. The contaminant spatial maps will also be useful for developing cohorts of exposure and guiding risk management decisions.

Experiments to Evaluate and Implement Passive Tracer Gas Methods to Measure Ventilation Rates in Homes

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

Lunden, Melissa; Faulkner, David; Heredia, Elizabeth

2012-10-01

This report documents experiments performed in three homes to assess the methodology used to determine air exchange rates using passive tracer techniques. The experiments used four different tracer gases emitted simultaneously but implemented with different spatial coverage in the home. Two different tracer gas sampling methods were used. The results characterize the factors of the execution and analysis of the passive tracer technique that affect the uncertainty in the calculated air exchange rates. These factors include uncertainties in tracer gas emission rates, differences in measured concentrations for different tracer gases, temporal and spatial variability of the concentrations, the comparison betweenmore » different gas sampling methods, and the effect of different ventilation conditions.« less

Large-scale assessment of benthic communities across multiple marine protected areas using an autonomous underwater vehicle.

PubMed

Ferrari, Renata; Marzinelli, Ezequiel M; Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F; Byrne, Maria; Malcolm, Hamish A; Williams, Stefan B; Steinberg, Peter D

2018-01-01

Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate 'no-take' and 'general-use' (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5-10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales.

Large-scale assessment of benthic communities across multiple marine protected areas using an autonomous underwater vehicle

PubMed Central

Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F.; Byrne, Maria; Malcolm, Hamish A.; Williams, Stefan B.; Steinberg, Peter D.

2018-01-01

Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate ‘no-take’ and ‘general-use’ (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5–10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales. PMID:29547656

Environmental Controls on Multi-Scale Soil Nutrient Variability in the Tropics: the Importance of Land-Cover Change

NASA Astrophysics Data System (ADS)

Holmes, K. W.; Kyriakidis, P. C.; Chadwick, O. A.; Matricardi, E.; Soares, J. V.; Roberts, D. A.

2003-12-01

The natural controls on soil variability and the spatial scales at which correlation exists among soil and environmental variables are critical information for evaluating the effects of deforestation. We detect different spatial scales of variability in soil nutrient levels over a large region (hundreds of thousands of km2) in the Amazon, analyze correlations among soil properties at these different scales, and evaluate scale-specific relationships among soil properties and the factors potentially driving soil development. Statistical relationships among physical drivers of soil formation, namely geology, precipitation, terrain attributes, classified soil types, and land cover derived from remote sensing, were included to determine which factors are related to soil biogeochemistry at each spatial scale. Surface and subsurface soil profile data from a 3000 sample database collected in Rond“nia, Brazil, were used to investigate patterns in pH, phosphorus, nitrogen, organic carbon, effective cation exchange capacity, calcium, magnesium, potassium, aluminum, sand, and clay in this environment grading from closed canopy tropical forest to savanna. We focus on pH in this presentation for simplicity, because pH is the single most important soil characteristic for determining the chemical environment of higher plants and soil microbial activity. We determined four spatial scales which characterize integrated patterns of soil chemistry: less than 3 km; 3 to 10 km; 10 to 68 km; and from 68 to 550 km (extent of study area). Although the finest observable scale was fixed by the field sampling density, the coarser scales were determined from relationships in the data through coregionalization modeling, rather than being imposed by the researcher. Processes which affect soils over short distances, such as land cover and terrain attributes, were good predictors of fine scale spatial components of nutrients; processes which affect soils over very large distances, such as precipitation and geology, were better predictors at coarse spatial scales. However, this result may be affected by the resolution of the available predictor maps. Land-cover change exerted a strong influence on soil chemistry at fine spatial scales, and had progressively less of an effect at coarser scales. It is important to note that land cover, and interactions among land cover and the other predictors, continued to be a significant predictor of soil chemistry at every spatial scale up to hundreds of thousands of kilometers.

A heteroskedastic error covariance matrix estimator using a first-order conditional autoregressive Markov simulation for deriving asympotical efficient estimates from ecological sampled Anopheles arabiensis aquatic habitat covariates

PubMed Central

Jacob, Benjamin G; Griffith, Daniel A; Muturi, Ephantus J; Caamano, Erick X; Githure, John I; Novak, Robert J

2009-01-01

Background Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of An. arabiensis aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of An. arabiensis aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled Anopheles aquatic habitat covariates. A test for diagnostic checking error residuals in an An. arabiensis aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature. Methods Field and remote-sampled data were collected during July 2006 to December 2007 in Karima rice-village complex in Mwea, Kenya. SAS 9.1.4® was used to explore univariate statistics, correlations, distributions, and to generate global autocorrelation statistics from the ecological sampled datasets. A local autocorrelation index was also generated using spatial covariance parameters (i.e., Moran's Indices) in a SAS/GIS® database. The Moran's statistic was decomposed into orthogonal and uncorrelated synthetic map pattern components using a Poisson model with a gamma-distributed mean (i.e. negative binomial regression). The eigenfunction values from the spatial configuration matrices were then used to define expectations for prior distributions using a Markov chain Monte Carlo (MCMC) algorithm. A set of posterior means were defined in WinBUGS 1.4.3®. After the model had converged, samples from the conditional distributions were used to summarize the posterior distribution of the parameters. Thereafter, a spatial residual trend analyses was used to evaluate variance uncertainty propagation in the model using an autocovariance error matrix. Results By specifying coefficient estimates in a Bayesian framework, the covariate number of tillers was found to be a significant predictor, positively associated with An. arabiensis aquatic habitats. The spatial filter models accounted for approximately 19% redundant locational information in the ecological sampled An. arabiensis aquatic habitat data. In the residual error estimation model there was significant positive autocorrelation (i.e., clustering of habitats in geographic space) based on log-transformed larval/pupal data and the sampled covariate depth of habitat. Conclusion An autocorrelation error covariance matrix and a spatial filter analyses can prioritize mosquito control strategies by providing a computationally attractive and feasible description of variance uncertainty estimates for correctly identifying clusters of prolific An. arabiensis aquatic habitats based on larval/pupal productivity. PMID:19772590

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.

Visuo-spatial cueing in children with differential reading and spelling profiles

PubMed Central

Kemény, Ferenc; Gangl, Melanie; Schulte-Körne, Gerd; Moll, Kristina; Landerl, Karin

2017-01-01

Dyslexia has been claimed to be causally related to deficits in visuo-spatial attention. In particular, inefficient shifting of visual attention during spatial cueing paradigms is assumed to be associated with problems in graphemic parsing during sublexical reading. The current study investigated visuo-spatial attention performance in an exogenous cueing paradigm in a large sample (N = 191) of third and fourth graders with different reading and spelling profiles (controls, isolated reading deficit, isolated spelling deficit, combined deficit in reading and spelling). Once individual variability in reaction times was taken into account by means of z-transformation, a cueing deficit (i.e. no significant difference between valid and invalid trials) was found for children with combined deficits in reading and spelling. However, poor readers without spelling problems showed a cueing effect comparable to controls, but exhibited a particularly strong right-over-left advantage (position effect). Isolated poor spellers showed a significant cueing effect, but no position effect. While we replicated earlier findings of a reduced cueing effect among poor nonword readers (indicating deficits in sublexical processing), we also found a reduced cueing effect among children with particularly poor orthographic spelling (indicating deficits in lexical processing). Thus, earlier claims of a specific association with nonword reading could not be confirmed. Controlling for ADHD-symptoms reported in a parental questionnaire did not impact on the statistical analysis, indicating that cueing deficits are not caused by more general attentional limitations. Between 31 and 48% of participants in the three reading and/or spelling deficit groups as well as 32% of the control group showed reduced spatial cueing. These findings indicate a significant, but moderate association between certain aspects of visuo-spatial attention and subcomponents of written language processing, the causal status of which is yet unclear. PMID:28686635

Visuo-spatial cueing in children with differential reading and spelling profiles.

PubMed

Banfi, Chiara; Kemény, Ferenc; Gangl, Melanie; Schulte-Körne, Gerd; Moll, Kristina; Landerl, Karin

2017-01-01

Dyslexia has been claimed to be causally related to deficits in visuo-spatial attention. In particular, inefficient shifting of visual attention during spatial cueing paradigms is assumed to be associated with problems in graphemic parsing during sublexical reading. The current study investigated visuo-spatial attention performance in an exogenous cueing paradigm in a large sample (N = 191) of third and fourth graders with different reading and spelling profiles (controls, isolated reading deficit, isolated spelling deficit, combined deficit in reading and spelling). Once individual variability in reaction times was taken into account by means of z-transformation, a cueing deficit (i.e. no significant difference between valid and invalid trials) was found for children with combined deficits in reading and spelling. However, poor readers without spelling problems showed a cueing effect comparable to controls, but exhibited a particularly strong right-over-left advantage (position effect). Isolated poor spellers showed a significant cueing effect, but no position effect. While we replicated earlier findings of a reduced cueing effect among poor nonword readers (indicating deficits in sublexical processing), we also found a reduced cueing effect among children with particularly poor orthographic spelling (indicating deficits in lexical processing). Thus, earlier claims of a specific association with nonword reading could not be confirmed. Controlling for ADHD-symptoms reported in a parental questionnaire did not impact on the statistical analysis, indicating that cueing deficits are not caused by more general attentional limitations. Between 31 and 48% of participants in the three reading and/or spelling deficit groups as well as 32% of the control group showed reduced spatial cueing. These findings indicate a significant, but moderate association between certain aspects of visuo-spatial attention and subcomponents of written language processing, the causal status of which is yet unclear.

A Robot Equipped with a High-Speed LSPR Gas Sensor Module for Collecting Spatial Odor Information from On-Ground Invisible Odor Sources.

PubMed

Yang, Zhongyuan; Sassa, Fumihiro; Hayashi, Kenshi

2018-06-22

Improving the efficiency of detecting the spatial distribution of gas information with a mobile robot is a great challenge that requires rapid sample collection, which is basically determined by the speed of operation of gas sensors. The present work developed a robot equipped with a high-speed gas sensor module based on localized surface plasmon resonance. The sensor module is designed to sample gases from an on-ground odor source, such as a footprint material or artificial odor marker, via a fine sampling tubing. The tip of the sampling tubing was placed close to the ground to reduce the sampling time and the effect of natural gas diffusion. On-ground ethanol odor sources were detected by the robot at high resolution (i.e., 2.5 cm when the robot moved at 10 cm/s), and the reading of gas information was demonstrated experimentally. This work may help in the development of environmental sensing robots, such as the development of odor source mapping and multirobot systems with pheromone tracing.

Analysis on the Spatial Difference of Bacterial Community Structure in Micro-pressure Air-lift Loop Reactor

NASA Astrophysics Data System (ADS)

Wan, L. G.; Lin, Q.; Bian, D. J.; Ren, Q. K.; Xiao, Y. B.; Lu, W. X.

2018-02-01

In order to reveal the spatial difference of the bacterial community structure in the Micro-pressure Air-lift Loop Reactor, the activated sludge bacterial at five different representative sites in the reactor were studied by denaturing gradient gel electrophoresis (DGGE). The results of DGGE showed that the difference of environmental conditions (such as substrate concentration, dissolved oxygen and PH, etc.) resulted in different diversity and similarity of microbial flora in different spatial locations. The Shannon-Wiener diversity index of the total bacterial samples from five sludge samples varied from 0.92 to 1.28, the biodiversity index was the smallest at point 5, and the biodiversity index was the highest at point 2. The similarity of the flora between the point 2, 3 and 4 was 80% or more, respectively. The similarity of the flora between the point 5 and the other samples was below 70%, and the similarity of point 2 was only 59.2%. Due to the different contribution of different strains to the removal of pollutants, it can give full play to the synergistic effect of bacterial degradation of pollutants, and further improve the efficiency of sewage treatment.

On spatial coalescents with multiple mergers in two dimensions.

PubMed

Heuer, Benjamin; Sturm, Anja

2013-08-01

We consider the genealogy of a sample of individuals taken from a spatially structured population when the variance of the offspring distribution is relatively large. The space is structured into discrete sites of a graph G. If the population size at each site is large, spatial coalescents with multiple mergers, so called spatial Λ-coalescents, for which ancestral lines migrate in space and coalesce according to some Λ-coalescent mechanism, are shown to be appropriate approximations to the genealogy of a sample of individuals. We then consider as the graph G the two dimensional torus with side length 2L+1 and show that as L tends to infinity, and time is rescaled appropriately, the partition structure of spatial Λ-coalescents of individuals sampled far enough apart converges to the partition structure of a non-spatial Kingman coalescent. From a biological point of view this means that in certain circumstances both the spatial structure as well as larger variances of the underlying offspring distribution are harder to detect from the sample. However, supplemental simulations show that for moderately large L the different structure is still evident. Copyright © 2012 Elsevier Inc. All rights reserved.

Quantifying the effect of 3D spatial resolution on the accuracy of microstructural distributions

NASA Astrophysics Data System (ADS)

Loughnane, Gregory; Groeber, Michael; Uchic, Michael; Riley, Matthew; Shah, Megna; Srinivasan, Raghavan; Grandhi, Ramana

The choice of spatial resolution for experimentally-collected 3D microstructural data is often governed by general rules of thumb. For example, serial section experiments often strive to collect at least ten sections through the average feature-of-interest. However, the desire to collect high resolution data in 3D is greatly tempered by the exponential growth in collection times and data storage requirements. This paper explores the use of systematic down-sampling of synthetically-generated grain microstructures to examine the effect of resolution on the calculated distributions of microstructural descriptors such as grain size, number of nearest neighbors, aspect ratio, and Ω3.

Sports training enhances visuo-spatial cognition regardless of open-closed typology

PubMed Central

Hsieh, Shu-Shih; Chen, Kuan-Fu; Chang, Yu-Kai

2017-01-01

The aim of this study was to investigate the effects of open and closed sport participation on visuo-spatial attention and memory performance among young adults. Forty-eight young adults—16 open-skill athletes, 16 closed-skill athletes, and 16 non-athletes controls—were recruited for the study. Both behavioral performance and event-related potential (ERP) measurement were assessed when participants performed non-delayed and delayed match-to-sample task that tested visuo-spatial attention and memory processing. Results demonstrated that regardless of training typology, the athlete groups exhibited shorter reaction times in both the visuo-spatial attention and memory conditions than the control group with no existence of speed-accuracy trade-off. Similarly, a larger P3 amplitudes were observed in both athlete groups than in the control group for the visuo-spatial memory condition. These findings suggest that sports training, regardless of typology, are associated with superior visuo-spatial attention and memory performance, and more efficient neural resource allocation in memory processing. PMID:28560098

A simple homogeneous model for regular and irregular metallic wire media samples

NASA Astrophysics Data System (ADS)

Kosulnikov, S. Y.; Mirmoosa, M. S.; Simovski, C. R.

2018-02-01

To simplify the solution of electromagnetic problems with wire media samples, it is reasonable to treat them as the samples of a homogeneous material without spatial dispersion. The account of spatial dispersion implies additional boundary conditions and makes the solution of boundary problems difficult especially if the sample is not an infinitely extended layer. Moreover, for a novel type of wire media - arrays of randomly tilted wires - a spatially dispersive model has not been developed. Here, we introduce a simplistic heuristic model of wire media samples shaped as bricks. Our model covers WM of both regularly and irregularly stretched wires.

Image reconstructions from super-sampled data sets with resolution modeling in PET imaging.

PubMed

Li, Yusheng; Matej, Samuel; Metzler, Scott D

2014-12-01

Spatial resolution in positron emission tomography (PET) is still a limiting factor in many imaging applications. To improve the spatial resolution for an existing scanner with fixed crystal sizes, mechanical movements such as scanner wobbling and object shifting have been considered for PET systems. Multiple acquisitions from different positions can provide complementary information and increased spatial sampling. The objective of this paper is to explore an efficient and useful reconstruction framework to reconstruct super-resolution images from super-sampled low-resolution data sets. The authors introduce a super-sampling data acquisition model based on the physical processes with tomographic, downsampling, and shifting matrices as its building blocks. Based on the model, we extend the MLEM and Landweber algorithms to reconstruct images from super-sampled data sets. The authors also derive a backprojection-filtration-like (BPF-like) method for the super-sampling reconstruction. Furthermore, they explore variant methods for super-sampling reconstructions: the separate super-sampling resolution-modeling reconstruction and the reconstruction without downsampling to further improve image quality at the cost of more computation. The authors use simulated reconstruction of a resolution phantom to evaluate the three types of algorithms with different super-samplings at different count levels. Contrast recovery coefficient (CRC) versus background variability, as an image-quality metric, is calculated at each iteration for all reconstructions. The authors observe that all three algorithms can significantly and consistently achieve increased CRCs at fixed background variability and reduce background artifacts with super-sampled data sets at the same count levels. For the same super-sampled data sets, the MLEM method achieves better image quality than the Landweber method, which in turn achieves better image quality than the BPF-like method. The authors also demonstrate that the reconstructions from super-sampled data sets using a fine system matrix yield improved image quality compared to the reconstructions using a coarse system matrix. Super-sampling reconstructions with different count levels showed that the more spatial-resolution improvement can be obtained with higher count at a larger iteration number. The authors developed a super-sampling reconstruction framework that can reconstruct super-resolution images using the super-sampling data sets simultaneously with known acquisition motion. The super-sampling PET acquisition using the proposed algorithms provides an effective and economic way to improve image quality for PET imaging, which has an important implication in preclinical and clinical region-of-interest PET imaging applications.

Sampling benthic macroinvertebrates in a large flood-plain river: Considerations of study design, sample size, and cost

USGS Publications Warehouse

Bartsch, L.A.; Richardson, W.B.; Naimo, T.J.

1998-01-01

Estimation of benthic macroinvertebrate populations over large spatial scales is difficult due to the high variability in abundance and the cost of sample processing and taxonomic analysis. To determine a cost-effective, statistically powerful sample design, we conducted an exploratory study of the spatial variation of benthic macroinvertebrates in a 37 km reach of the Upper Mississippi River. We sampled benthos at 36 sites within each of two strata, contiguous backwater and channel border. Three standard ponar (525 cm(2)) grab samples were obtained at each site ('Original Design'). Analysis of variance and sampling cost of strata-wide estimates for abundance of Oligochaeta, Chironomidae, and total invertebrates showed that only one ponar sample per site ('Reduced Design') yielded essentially the same abundance estimates as the Original Design, while reducing the overall cost by 63%. A posteriori statistical power analysis (alpha = 0.05, beta = 0.20) on the Reduced Design estimated that at least 18 sites per stratum were needed to detect differences in mean abundance between contiguous backwater and channel border areas for Oligochaeta, Chironomidae, and total invertebrates. Statistical power was nearly identical for the three taxonomic groups. The abundances of several taxa of concern (e.g., Hexagenia mayflies and Musculium fingernail clams) were too spatially variable to estimate power with our method. Resampling simulations indicated that to achieve adequate sampling precision for Oligochaeta, at least 36 sample sites per stratum would be required, whereas a sampling precision of 0.2 would not be attained with any sample size for Hexagenia in channel border areas, or Chironomidae and Musculium in both strata given the variance structure of the original samples. Community-wide diversity indices (Brillouin and 1-Simpsons) increased as sample area per site increased. The backwater area had higher diversity than the channel border area. The number of sampling sites required to sample benthic macroinvertebrates during our sampling period depended on the study objective and ranged from 18 to more than 40 sites per stratum. No single sampling regime would efficiently and adequately sample all components of the macroinvertebrate community.

Electronic and Morphological Inhomogeneities in Pristine and Deteriorated Perovskite Photovoltaic Films

DOE PAGES

Berweger, Samuel; MacDonald, Gordon A.; Yang, Mengjin; ...

2017-02-02

We perform scanning microwave microscopy (SMM) to study the spatially varying electronic properties and related morphology of pristine and degraded methylammonium lead-halide (MAPI) perovskite films fabricated under different ambient humidity. Here, we find that higher processing humidity leads to the emergence of increased conductivity at the grain boundaries but also correlates with the appearance of resistive grains that contain PbI 2. Deteriorated films show larger and increasingly insulating grain boundaries as well as spatially localized regions of reduced conductivity within grains. These results suggest that while humidity during film fabrication primarily benefits device properties due to the passivation of trapsmore » at the grain boundaries and self-doping, it also results in the emergence of PbI 2-containing grains. We further establish that MAPI film deterioration under ambient conditions proceeds via the spatially localized breakdown of film conductivity, both at grain boundaries and within grains, due to local variations in susceptibility to deterioration. These results confirm that PbI 2 has both beneficial and adverse effects on device performance and provide new means for device optimization by revealing spatial variations in sample conductivity as well as morphological differences in resistance to sample deterioration.« less

Nitrogen Fertilization Elevated Spatial Heterogeneity of Soil Microbial Biomass Carbon and Nitrogen in Switchgrass and Gamagrass Croplands

NASA Astrophysics Data System (ADS)

Jian, S.; Li, J.; Guo, C.; Hui, D.; Deng, Q.; Yu, C. L.; Dzantor, K. E.; Lane, C.

2017-12-01

Nitrogen (N) fertilizers are widely used to increase bioenergy crop yield but intensive fertilizations on spatial distributions of soil microbial processes in bioenergy croplands remains unknown. To quantify N fertilization effect on spatial heterogeneity of soil microbial biomass carbon (MBC) and N (MBN), we sampled top mineral horizon soils (0-15cm) using a spatially explicit design within two 15-m2 plots under three fertilization treatments in two bioenergy croplands in a three-year long fertilization experiment in Middle Tennessee, USA. The three fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha-1 in urea) and high N input (HN: 168 kg N ha-1 in urea). The two crops were switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.). Results showed that N fertilizations little altered central tendencies of microbial variables but relative to LN, HN significantly increased MBC and MBC:MBN (GG only). HN possessed the greatest within-plot variances except for MBN (GG only). Spatial patterns were generally evident under HN and LN plots and much less so under NN plots. Substantially contrasting spatial variations were also identified between croplands (GG>SG) and among variables (MBN, MBC:MBN > MBC). No significant correlations were identified between soil pH and microbial variables. This study demonstrated that spatial heterogeneity is elevated in microbial biomass of fertilized soils likely by uneven fertilizer application, the nature of soil microbial communities and bioenergy crops. Future researchers should better match sample sizes with the heterogeneity of soil microbial property (i.e. MBN) in bioenergy croplands.

Spatial distribution of nematodes in soil cultivated with sugarcane under different uses

NASA Astrophysics Data System (ADS)

Cardoso, M. O.; Pedrosa, E. M. R.; Vicente, T. F. S.; Siqueira, G. M.; Montenegro, A. A. A.

2012-04-01

Sugarcane is a crop of major importance within the Brazilian economy, being an activity that generates energy and with high capacity to develop various economic sectors. Currently the greatest challenge is to maximize productivity and minimize environmental impacts. The plant-parasites nematodes have great expression, because influence directly the productive potential of sugarcane crops. Accordingly, little research has been devoted to the study of spatial variability of nematodes. Thus, the purpose of this work is to analyze the spatial distribution of nematodes in a soil cultivated with sugarcane in areas with and without irrigation, with distinct spacing of sampling to determine the differences between the sampling scales. The study area is located in the municipality of Goiana (Pernambuco State, Brazil). The experiment was conducted in two areas with 40 hectares each, being collected 90 samples at different spacing: 18 samples with spacing of 200.00 x 200.00 m, 36 samples with spacing of 20.00 m x 20.00 m and 36 samples with spacing of 2.00 m x 2.00 m. Soil samples were collected at deep of 0.00-0.20 m and nematodes were extracted per 300 cm3 of soil through centrifugal flotation in sucrose being quantified, classified according trophic habit (plant-parasites, fungivores, bacterivores, omnivores and predators) and identified in level of genus or family. In irrigated area the amount of water applied was determined considering the evapotranspiration of culture. The data were analyzed using classical statistics and geostatistics. The results demonstrated that the data showed high values of coefficient of variation in both study areas. All attributes studied showed log normal frequency distribution. The area B (irrigated) has a population of nematodes more stable than the area A (non-irrigated), a fact confirmed by its mean value of the total population of nematodes (282.45 individuals). The use of geostatistics not allowed to assess the spatial distribution of populations of nematodes even with the data being collected at different scales, describing the spatial variability of groups of nematodes present in the areas evaluated is smaller than the smallest spacing used. Even with the data showing pure nugget effect was possible to verify the semivariogram for the groups of nematodes in the area A, where pairs of semivariance showed great dispersion.

Spatial variability of organic layer thickness and carbon stocks in mature boreal forest stands--implications and suggestions for sampling designs.

PubMed

Kristensen, Terje; Ohlson, Mikael; Bolstad, Paul; Nagy, Zoltan

2015-08-01

Accurate field measurements from inventories across fine spatial scales are critical to improve sampling designs and to increase the precision of forest C cycling modeling. By studying soils undisturbed from active forest management, this paper gives a unique insight in the naturally occurring variability of organic layer C and provides valuable references against which subsequent and future sampling schemes can be evaluated. We found that the organic layer C stocks displayed great short-range variability with spatial autocorrelation distances ranging from 0.86 up to 2.85 m. When spatial autocorrelations are known, we show that a minimum of 20 inventory samples separated by ∼5 m is needed to determine the organic layer C stock with a precision of ±0.5 kg C m(-2). Our data also demonstrates a strong relationship between the organic layer C stock and horizon thickness (R (2) ranging from 0.58 to 0.82). This relationship suggests that relatively inexpensive measurements of horizon thickness can supplement soil C sampling, by reducing the number of soil samples collected, or to enhance the spatial resolution of organic layer C mapping.

The study of combining Latin Hypercube Sampling method and LU decomposition method (LULHS method) for constructing spatial random field

NASA Astrophysics Data System (ADS)

WANG, P. T.

2015-12-01

Groundwater modeling requires to assign hydrogeological properties to every numerical grid. Due to the lack of detailed information and the inherent spatial heterogeneity, geological properties can be treated as random variables. Hydrogeological property is assumed to be a multivariate distribution with spatial correlations. By sampling random numbers from a given statistical distribution and assigning a value to each grid, a random field for modeling can be completed. Therefore, statistics sampling plays an important role in the efficiency of modeling procedure. Latin Hypercube Sampling (LHS) is a stratified random sampling procedure that provides an efficient way to sample variables from their multivariate distributions. This study combines the the stratified random procedure from LHS and the simulation by using LU decomposition to form LULHS. Both conditional and unconditional simulations of LULHS were develpoed. The simulation efficiency and spatial correlation of LULHS are compared to the other three different simulation methods. The results show that for the conditional simulation and unconditional simulation, LULHS method is more efficient in terms of computational effort. Less realizations are required to achieve the required statistical accuracy and spatial correlation.

Spatial and temporal patterns of chronic wasting disease: Fine-scale mapping of a wildlife epidemic in Wisconsin

USGS Publications Warehouse

Osnas, E.E.; Heisey, D.M.; Rolley, R.E.; Samuel, M.D.

2009-01-01

Emerging infectious diseases threaten wildlife populations and human health. Understanding the spatial distributions of these new diseases is important for disease management and policy makers; however, the data are complicated by heterogeneities across host classes, sampling variance, sampling biases, and the space-time epidemic process. Ignoring these issues can lead to false conclusions or obscure important patterns in the data, such as spatial variation in disease prevalence. Here, we applied hierarchical Bayesian disease mapping methods to account for risk factors and to estimate spatial and temporal patterns of infection by chronic wasting disease (CWD) in white-tailed deer (Odocoileus virginianus) of Wisconsin, USA. We found significant heterogeneities for infection due to age, sex, and spatial location. Infection probability increased with age for all young deer, increased with age faster for young males, and then declined for some older animals, as expected from disease-associated mortality and age-related changes in infection risk. We found that disease prevalence was clustered in a central location, as expected under a simple spatial epidemic process where disease prevalence should increase with time and expand spatially. However, we could not detect any consistent temporal or spatiotemporal trends in CWD prevalence. Estimates of the temporal trend indicated that prevalence may have decreased or increased with nearly equal posterior probability, and the model without temporal or spatiotemporal effects was nearly equivalent to models with these effects based on deviance information criteria. For maximum interpretability of the role of location as a disease risk factor, we used the technique of direct standardization for prevalence mapping, which we develop and describe. These mapping results allow disease management actions to be employed with reference to the estimated spatial distribution of the disease and to those host classes most at risk. Future wildlife epidemiology studies should employ hierarchical Bayesian methods to smooth estimated quantities across space and time, account for heterogeneities, and then report disease rates based on an appropriate standardization. ?? 2009 by the Ecological Society of America.

Spatial distribution of Batrachochytrium dendrobatidis in South American caecilians.

PubMed

Lambertini, Carolina; Becker, C Guilherme; Bardier, Cecilia; da Silva Leite, Domingos; Toledo, Luís Felipe

2017-04-20

The amphibian-killing fungus Batrachochytrium dendrobatidis (Bd) is linked to population declines in anurans and salamanders globally. To date, however, few studies have attempted to screen Bd in live caecilians; Bd-positive caecilians have only been reported in Africa and French Guiana. Here, we performed a retrospective survey of museum preserved specimens to (1) describe spatial patterns of Bd infection in Gymnophiona across South America and (2) test whether areas of low climatic suitability for Bd in anurans predict Bd spatial epidemiology in caecilians. We used quantitative PCR to detect Bd in preserved caecilians collected over a 109 yr period, and performed autologistic regressions to test the effect of bioclimatic metrics of temperature and precipitation, vegetation density, and elevation on the likelihood of Bd occurrence. We detected an overall Bd prevalence of 12.4%, with positive samples spanning the Uruguayan savanna, Brazil's Atlantic Forest, and the Amazon basin. Our autologistic models detected a strong effect of macroclimate, a weaker effect of vegetation density, and no effect of elevation on the likelihood of Bd occurrence. Although most of our Bd-positive records overlapped with reported areas of high climatic suitability for the fungus in the Neotropics, many of our new Bd-positive samples extend far into areas of poor suitability for Bd in anurans. Our results highlight an important gap in the study of amphibian chytridiomycosis: the potential negative impact of Bd on Neotropical caecilians and the hypothetical role of caecilians as Bd reservoirs.

Modeling unobserved sources of heterogeneity in animal abundance using a Dirichlet process prior

USGS Publications Warehouse

Dorazio, R.M.; Mukherjee, B.; Zhang, L.; Ghosh, M.; Jelks, H.L.; Jordan, F.

2008-01-01

In surveys of natural populations of animals, a sampling protocol is often spatially replicated to collect a representative sample of the population. In these surveys, differences in abundance of animals among sample locations may induce spatial heterogeneity in the counts associated with a particular sampling protocol. For some species, the sources of heterogeneity in abundance may be unknown or unmeasurable, leading one to specify the variation in abundance among sample locations stochastically. However, choosing a parametric model for the distribution of unmeasured heterogeneity is potentially subject to error and can have profound effects on predictions of abundance at unsampled locations. In this article, we develop an alternative approach wherein a Dirichlet process prior is assumed for the distribution of latent abundances. This approach allows for uncertainty in model specification and for natural clustering in the distribution of abundances in a data-adaptive way. We apply this approach in an analysis of counts based on removal samples of an endangered fish species, the Okaloosa darter. Results of our data analysis and simulation studies suggest that our implementation of the Dirichlet process prior has several attractive features not shared by conventional, fully parametric alternatives. ?? 2008, The International Biometric Society.

An Intrinsic Algorithm for Parallel Poisson Disk Sampling on Arbitrary Surfaces.

PubMed

Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying

2013-03-08

Poisson disk sampling plays an important role in a variety of visual computing, due to its useful statistical property in distribution and the absence of aliasing artifacts. While many effective techniques have been proposed to generate Poisson disk distribution in Euclidean space, relatively few work has been reported to the surface counterpart. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. We propose a new technique for parallelizing the dart throwing. Rather than the conventional approaches that explicitly partition the spatial domain to generate the samples in parallel, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. It is worth noting that our algorithm is accurate as the generated Poisson disks are uniformly and randomly distributed without bias. Our method is intrinsic in that all the computations are based on the intrinsic metric and are independent of the embedding space. This intrinsic feature allows us to generate Poisson disk distributions on arbitrary surfaces. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.

Optimization of Sampling Design to Determine the Spatial Distributions of Emerging Contaminants in Estuaries

EPA Science Inventory

Narragansett Bay (NB) has been extensively sampled over the last 50 years by various government agencies, academic institutions, and private groups. To date, most spatial research conducted within the estuary has employed deterministic sampling designs. Several studies have used ...

The amusic brain: lost in music, but not in space.

PubMed

Tillmann, Barbara; Jolicoeur, Pierre; Ishihara, Masami; Gosselin, Nathalie; Bertrand, Olivier; Rossetti, Yves; Peretz, Isabelle

2010-04-21

Congenital amusia is a neurogenetic disorder of music processing that is currently ascribed to a deficit in pitch processing. A recent study challenges this view and claims the disorder might arise as a consequence of a general spatial-processing deficit. Here, we assessed spatial processing abilities in two independent samples of individuals with congenital amusia by using line bisection tasks (Experiment 1) and a mental rotation task (Experiment 2). Both amusics and controls showed the classical spatial effects on bisection performance and on mental rotation performance, and amusics and controls did not differ from each other. These results indicate that the neurocognitive impairment of congenital amusia does not affect the processing of space.

Measurement of in situ sulfur isotopes by laser ablation multi-collector ICPMS: opening Pandora’s Box

USGS Publications Warehouse

Ridley, William I.; Pribil, Michael; Koenig, Alan E.; Slack, John F.

2015-01-01

Laser ablation multi-collector ICPMS is a modern tool for in situ measurement of S isotopes. Advantages of the technique are speed of analysis and relatively minor matrix effects combined with spatial resolution sufficient for many applications. The main disadvantage is a more destructive sampling mechanism relative to the ion microprobe technique. Recent advances in instrumentation allow precise measurement with spatial resolutions down to 25 microns. We describe specific examples from economic geology where increased spatial resolution has greatly expanded insights into the sources and evolution of fluids that cause mineralization and illuminated genetic relations between individual deposits in single mineral districts.

The Geography of Economics and Happiness: Spatial Patterns in the Effects of Economic Conditions on Well-Being

ERIC Educational Resources Information Center

Stanca, Luca

2010-01-01

This paper investigates the cross-country distribution of the relationship between economic conditions and well-being. Using a large sample of individuals from 94 countries worldwide, we find that the effect of income on well-being is larger in countries with lower GDP per capita, while the negative effect of being unemployed is stronger in…

Visual sensitivity to spatially sampled modulation in human observers

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.; Macleod, Donald I. A.

1991-01-01

Thresholds were measured for detecting spatial luminance modulation in regular lattices of visually discrete dots. Thresholds for modulation of a lattice are generally higher than the corresponding threshold for modulation of a continuous field, and the size of the threshold elevation, which depends on the spacing of the lattice elements, can be as large as a one log unit. The largest threshold elevations are seen when the sample spacing is 12 min arc or greater. Theories based on response compression cannot explain the further observation that the threshold elevations due to spatial sampling are also dependent on modulation frequency: the greatest elevations occur with higher modulation frequencies. The idea that this is due to masking of the modulation frequency by the spatial frequencies in the sampling lattice is considered.

Evaluation of spatial variability of soil arsenic adjacent to a disused cattle-dip site, using model-based geostatistics.

PubMed

Niazi, Nabeel K; Bishop, Thomas F A; Singh, Balwant

2011-12-15

This study investigated the spatial variability of total and phosphate-extractable arsenic (As) concentrations in soil adjacent to a cattle-dip site, employing a linear mixed model-based geostatistical approach. The soil samples in the study area (n = 102 in 8.1 m(2)) were taken at the nodes of a 0.30 × 0.35 m grid. The results showed that total As concentration (0-0.2 m depth) and phosphate-extractable As concentration (at depths of 0-0.2, 0.2-0.4, and 0.4-0.6 m) in soil adjacent to the dip varied greatly. Both total and phosphate-extractable soil As concentrations significantly (p = 0.004-0.048) increased toward the cattle-dip. Using the linear mixed model, we suggest that 5 samples are sufficient to assess a dip site for soil (As) contamination (95% confidence interval of ±475.9 mg kg(-1)), but 15 samples (95% confidence interval of ±212.3 mg kg(-1)) is desirable baseline when the ultimate goal is to evaluate the effects of phytoremediation. Such guidelines on sampling requirements are crucial for the assessment of As contamination levels at other cattle-dip sites, and to determine the effect of phytoremediation on soil As.

Analysis of Genetic Algorithm for Rule-Set Production (GARP) modeling approach for predicting distributions of fleas implicated as vectors of plague, Yersinia pestis, in California.

PubMed

Adjemian, Jennifer C Z; Girvetz, Evan H; Beckett, Laurel; Foley, Janet E

2006-01-01

More than 20 species of fleas in California are implicated as potential vectors of Yersinia pestis. Extremely limited spatial data exist for plague vectors-a key component to understanding where the greatest risks for human, domestic animal, and wildlife health exist. This study increases the spatial data available for 13 potential plague vectors by using the ecological niche modeling system Genetic Algorithm for Rule-Set Production (GARP) to predict their respective distributions. Because the available sample sizes in our data set varied greatly from one species to another, we also performed an analysis of the robustness of GARP by using the data available for flea Oropsylla montana (Baker) to quantify the effects that sample size and the chosen explanatory variables have on the final species distribution map. GARP effectively modeled the distributions of 13 vector species. Furthermore, our analyses show that all of these modeled ranges are robust, with a sample size of six fleas or greater not significantly impacting the percentage of the in-state area where the flea was predicted to be found, or the testing accuracy of the model. The results of this study will help guide the sampling efforts of future studies focusing on plague vectors.

The New Bedford Harbor Superfund Site Long Term ...

EPA Pesticide Factsheets

Background. New Bedford Harbor (NBH), located in southeastern Massachusetts, was designated as a marine Superfund site in 1983 due to sediment contamination by polychlorinated biphenyls (PCBs). Based on risks to human health and the environment, the first two phases of the site cleanup involved dredging PCB-contaminated sediments from the harbor. Therefore, a long-term monitoring program (LTM) was developed to measure spatial and temporal chemical and biological changes in sediment, water, and biota to assess the effects and effectiveness of the remedial activities. Approach. A systematic, probabilistic sampling design was used to select approximately 70 sediment sampling stations. Sediment was collected at each station and chemical (e.g., PCBs, metals), physical (e.g., grain size), and biological (e.g., benthic community) measurements were conducted on all samples. There have been six sample collections to date: 1993-baseline, 1995-post hot spot removal, 1999-prior to full scale dredging, and then at 5 year intervals: 2004, 2009, and 2014. Mussel (Mytilus edulis) bioaccumulation has also been measured twice yearly. Results. There is a decreasing spatial gradient in sediment PCB concentrations from the northern boundary (upper harbor) to the southern boundary (outer harbor) of the site. Along this same transect, there is an increase in biological condition (e.g., benthic community diversity). Temporally, the contaminant and biological gradients have been

Preferential sampling and Bayesian geostatistics: Statistical modeling and examples.

PubMed

Cecconi, Lorenzo; Grisotto, Laura; Catelan, Dolores; Lagazio, Corrado; Berrocal, Veronica; Biggeri, Annibale

2016-08-01

Preferential sampling refers to any situation in which the spatial process and the sampling locations are not stochastically independent. In this paper, we present two examples of geostatistical analysis in which the usual assumption of stochastic independence between the point process and the measurement process is violated. To account for preferential sampling, we specify a flexible and general Bayesian geostatistical model that includes a shared spatial random component. We apply the proposed model to two different case studies that allow us to highlight three different modeling and inferential aspects of geostatistical modeling under preferential sampling: (1) continuous or finite spatial sampling frame; (2) underlying causal model and relevant covariates; and (3) inferential goals related to mean prediction surface or prediction uncertainty. © The Author(s) 2016.

Simple Approaches for Measuring Dry Atmospheric Nitrogen Deposition to Watersheds

EPA Science Inventory

Assessing the effects of atmospheric nitrogen (N) deposition on surface water quality requires accurate accounts of total N deposition (wet, dry, and cloud vapor); however, dry deposition is difficult to measure and is often spatially variable. Affordable passive sampling methods...

BAYESIAN ENTROPY FOR SPATIAL SAMPLING DESIGN OF ENVIRONMENTAL DATA

EPA Science Inventory

Particulate Matter (PM) has been linked to widespread public health effects, including a range of serious respiratory and cardiovascular problems, and to reduced visibility in may parts of the United States, see the Environmental Protection Agency (EPA) report (2004) and relevant...

Spatial distribution, enrichment, and source of environmentally important elements in Batticaloa lagoon, Sri Lanka.

PubMed

Adikaram, Madurya; Pitawala, Amarasooriya; Ishiga, Hiroaki; Jayawardana, Daham

2017-01-01

The present paper is the first documentation of distribution and contamination status of environmentally important elements of superficial sediments in the Batticaloa lagoon that is connected to the largest bay of the world. Surface sediment samples were collected from 34 sites covering all over the lagoon. Concentrations of elements such as As, Cr, Cu, Fe, Nb, Ni, Pb, Sc, Sr, Th, V, Y, Zn, and Zr were measured by X-ray florescence analysis. Geochemically, the lagoon has three different zones that were influenced mainly by fresh water sources, marine fronts, and intermediate mixing zones. The marine sediment quality standards indicate that Zr and Th values are exceeded throughout the lagoon. According to the freshwater sediment quality standards, Cr levels of all sampling sites exceed the threshold effect level (TEL) and 17 % of them are even above the probable effect level (PEL). Most sampling sites of the channel discharging areas show minor enrichment of Cu, Ni, and Zn with respect to the TEL. Contamination indices show that the lagoon mouth area is enriched with As. Statistical analysis implies that discharges from agricultural channel and marine fluxes of the lagoon effects on the spatial distribution of measured elements. Further research is required to understand the rate of contamination in the studied marine system.

Trap configuration and spacing influences parameter estimates in spatial capture-recapture models

USGS Publications Warehouse

Sun, Catherine C.; Fuller, Angela K.; Royle, J. Andrew

2014-01-01

An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus) populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation). We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.

Spatio-Temporal Variability of Groundwater Storage in India

NASA Technical Reports Server (NTRS)

Bhanja, Soumendra; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2016-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Ground water storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent).In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Spatio-temporal variability of groundwater storage in India.

PubMed

Bhanja, Soumendra N; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2017-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Groundwater storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent). In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Strong Spatial Influence on Colonization Rates in a Pioneer Zooplankton Metacommunity

PubMed Central

Frisch, Dagmar; Cottenie, Karl; Badosa, Anna; Green, Andy J.

2012-01-01

The magnitude of community-wide dispersal is central to metacommunity models, yet dispersal is notoriously difficult to quantify in passive and cryptic dispersers such as many freshwater invertebrates. By overcoming the problem of quantifying dispersal rates, colonization rates into new habitats can provide a useful estimate of the magnitude of effective dispersal. Here we study the influence of spatial and local processes on colonization rates into new ponds that indicate differential dispersal limitation of major zooplankton taxa, with important implications for metacommunity dynamics. We identify regional and local factors that affect zooplankton colonization rates and spatial patterns in a large-scale experimental system. Our study differs from others in the unique setup of the experimental pond area by which we were able to test spatial and environmental variables at a large spatial scale. We quantified colonization rates separately for the Copepoda, Cladocera and Rotifera from samples collected over a period of 21 months in 48 newly constructed temporary ponds of 0.18–2.95 ha distributed in a restored wetland area of 2,700 ha in Doñana National Park, Southern Spain. Species richness upon initial sampling of new ponds was about one third of that in reference ponds, although the rate of detection of new species from thereon were not significantly different, probably owing to high turnover in the dynamic, temporary reference ponds. Environmental heterogeneity had no detectable effect on colonization rates in new ponds. In contrast, connectivity, space (based on latitude and longitude) and surface area were key determinants of colonization rates for copepods and cladocerans. This suggests dispersal limitation in cladocerans and copepods, but not in rotifers, possibly due to differences in propagule size and abundance. PMID:22792241

Strong spatial influence on colonization rates in a pioneer zooplankton metacommunity.

PubMed

Frisch, Dagmar; Cottenie, Karl; Badosa, Anna; Green, Andy J

2012-01-01

The magnitude of community-wide dispersal is central to metacommunity models, yet dispersal is notoriously difficult to quantify in passive and cryptic dispersers such as many freshwater invertebrates. By overcoming the problem of quantifying dispersal rates, colonization rates into new habitats can provide a useful estimate of the magnitude of effective dispersal. Here we study the influence of spatial and local processes on colonization rates into new ponds that indicate differential dispersal limitation of major zooplankton taxa, with important implications for metacommunity dynamics. We identify regional and local factors that affect zooplankton colonization rates and spatial patterns in a large-scale experimental system. Our study differs from others in the unique setup of the experimental pond area by which we were able to test spatial and environmental variables at a large spatial scale. We quantified colonization rates separately for the Copepoda, Cladocera and Rotifera from samples collected over a period of 21 months in 48 newly constructed temporary ponds of 0.18-2.95 ha distributed in a restored wetland area of 2,700 ha in Doñana National Park, Southern Spain. Species richness upon initial sampling of new ponds was about one third of that in reference ponds, although the rate of detection of new species from thereon were not significantly different, probably owing to high turnover in the dynamic, temporary reference ponds. Environmental heterogeneity had no detectable effect on colonization rates in new ponds. In contrast, connectivity, space (based on latitude and longitude) and surface area were key determinants of colonization rates for copepods and cladocerans. This suggests dispersal limitation in cladocerans and copepods, but not in rotifers, possibly due to differences in propagule size and abundance.

Scale-Dependence of Processes Structuring Dung Beetle Metacommunities Using Functional Diversity and Community Deconstruction Approaches

PubMed Central

da Silva, Pedro Giovâni; Hernández, Malva Isabel Medina

2015-01-01

Community structure is driven by mechanisms linked to environmental, spatial and temporal processes, which have been successfully addressed using metacommunity framework. The relative importance of processes shaping community structure can be identified using several different approaches. Two approaches that are increasingly being used are functional diversity and community deconstruction. Functional diversity is measured using various indices that incorporate distinct community attributes. Community deconstruction is a way to disentangle species responses to ecological processes by grouping species with similar traits. We used these two approaches to determine whether they are improvements over traditional measures (e.g., species composition, abundance, biomass) for identification of the main processes driving dung beetle (Scarabaeinae) community structure in a fragmented mainland-island landscape in southern Brazilian Atlantic Forest. We sampled five sites in each of four large forest areas, two on the mainland and two on the island. Sampling was performed in 2012 and 2013. We collected abundance and biomass data from 100 sampling points distributed over 20 sampling sites. We studied environmental, spatial and temporal effects on dung beetle community across three spatial scales, i.e., between sites, between areas and mainland-island. The γ-diversity based on species abundance was mainly attributed to β-diversity as a consequence of the increase in mean α- and β-diversity between areas. Variation partitioning on abundance, biomass and functional diversity showed scale-dependence of processes structuring dung beetle metacommunities. We identified two major groups of responses among 17 functional groups. In general, environmental filters were important at both local and regional scales. Spatial factors were important at the intermediate scale. Our study supports the notion of scale-dependence of environmental, spatial and temporal processes in the distribution and functional organization of Scarabaeinae beetles. We conclude that functional diversity may be used as a complementary approach to traditional measures, and that community deconstruction allows sufficient disentangling of responses of different trait-based groups. PMID:25822150

Assessing temporally and spatially resolved PM 2.5 exposures for epidemiological studies using satellite aerosol optical depth measurements

NASA Astrophysics Data System (ADS)

Kloog, Itai; Koutrakis, Petros; Coull, Brent A.; Lee, Hyung Joo; Schwartz, Joel

2011-11-01

Land use regression (LUR) models provide good estimates of spatially resolved long-term exposures, but are poor at capturing short term exposures. Satellite-derived Aerosol Optical Depth (AOD) measurements have the potential to provide spatio-temporally resolved predictions of both long and short term exposures, but previous studies have generally showed relatively low predictive power. Our objective was to extend our previous work on day-specific calibrations of AOD data using ground PM 2.5 measurements by incorporating commonly used LUR variables and meteorological variables, thus benefiting from both the spatial resolution from the LUR models and the spatio-temporal resolution from the satellite models. Later we use spatial smoothing to predict PM 2.5 concentrations for day/locations with missing AOD measures. We used mixed models with random slopes for day to calibrate AOD data for 2000-2008 across New-England with monitored PM 2.5 measurements. We then used a generalized additive mixed model with spatial smoothing to estimate PM 2.5 in location-day pairs with missing AOD, using regional measured PM 2.5, AOD values in neighboring cells, and land use. Finally, local (100 m) land use terms were used to model the difference between grid cell prediction and monitored value to capture very local traffic particles. Out-of-sample ten-fold cross-validation was used to quantify the accuracy of our predictions. For days with available AOD data we found high out-of-sample R2 (mean out-of-sample R2 = 0.830, year to year variation 0.725-0.904). For days without AOD values, our model performance was also excellent (mean out-of-sample R2 = 0.810, year to year variation 0.692-0.887). Importantly, these R2 are for daily, rather than monthly or yearly, values. Our model allows one to assess short term and long-term human exposures in order to investigate both the acute and chronic effects of ambient particles, respectively.

Spatial Variation in Soil Properties among North American Ecosystems and Guidelines for Sampling Designs

PubMed Central

Loescher, Henry; Ayres, Edward; Duffy, Paul; Luo, Hongyan; Brunke, Max

2014-01-01

Soils are highly variable at many spatial scales, which makes designing studies to accurately estimate the mean value of soil properties across space challenging. The spatial correlation structure is critical to develop robust sampling strategies (e.g., sample size and sample spacing). Current guidelines for designing studies recommend conducting preliminary investigation(s) to characterize this structure, but are rarely followed and sampling designs are often defined by logistics rather than quantitative considerations. The spatial variability of soils was assessed across ∼1 ha at 60 sites. Sites were chosen to represent key US ecosystems as part of a scaling strategy deployed by the National Ecological Observatory Network. We measured soil temperature (Ts) and water content (SWC) because these properties mediate biological/biogeochemical processes below- and above-ground, and quantified spatial variability using semivariograms to estimate spatial correlation. We developed quantitative guidelines to inform sample size and sample spacing for future soil studies, e.g., 20 samples were sufficient to measure Ts to within 10% of the mean with 90% confidence at every temperate and sub-tropical site during the growing season, whereas an order of magnitude more samples were needed to meet this accuracy at some high-latitude sites. SWC was significantly more variable than Ts at most sites, resulting in at least 10× more SWC samples needed to meet the same accuracy requirement. Previous studies investigated the relationship between the mean and variability (i.e., sill) of SWC across space at individual sites across time and have often (but not always) observed the variance or standard deviation peaking at intermediate values of SWC and decreasing at low and high SWC. Finally, we quantified how far apart samples must be spaced to be statistically independent. Semivariance structures from 10 of the 12-dominant soil orders across the US were estimated, advancing our continental-scale understanding of soil behavior. PMID:24465377

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Nagarajaiah, Satish; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-03-01

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30-60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. The proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

The effects of biome and spatial scale on the Co-occurrence patterns of a group of Namibian beetles

NASA Astrophysics Data System (ADS)

Pitzalis, Monica; Montalto, Francesca; Amore, Valentina; Luiselli, Luca; Bologna, Marco A.

2017-08-01

Co-occurrence patterns (studied by C-score, number of checkerboard units, number of species combinations, and V-ratio, and by an empirical Bayes approach developed by Gotelli and Ulrich, 2010) are crucial elements in order to understand assembly rules in ecological communities at both local and spatial scales. In order to explore general assembly rules and the effects of biome and spatial scale on such rules, here we studied a group of beetles (Coleoptera, Meloidae), using Namibia as a case of study. Data were gathered from 186 sampling sites, which allowed collection of 74 different species. We analyzed data at the level of (i) all sampled sites, (ii) all sites stratified by biome (Savannah, Succulent Karoo, Nama Karoo, Desert), and (iii) three randomly selected nested areas with three spatial scales each. Three competing algorithms were used for all analyses: (i) Fixed-Equiprobable, (ii) Fixed-Fixed, and (iii) Fixed-Proportional. In most of the null models we created, co-occurrence indicators revealed a non-random structure in meloid beetle assemblages at the global scale and at the scale of biomes, with species aggregation being much more important than species segregation in determining this non-randomness. At the level of biome, the same non-random organization was uncovered in assemblages from Savannah (where the aggregation pattern was particularly strong) and Succulent Karoo, but not in Desert and Nama Karoo. We conclude that species facilitation and similar niche in endemic species pairs may be particularly important as community drivers in our case of study. This pattern is also consistent with the evidence of a higher species diversity (normalized according to biome surface area) in the two former biomes. Historical patterns were perhaps also important for Succulent Karoo assemblages. Spatial scale had a reduced effect on patterning our data. This is consistent with the general homogeneity of environmental conditions over wide areas in Namibia.

Functional Nonlinear Mixed Effects Models For Longitudinal Image Data

PubMed Central

Luo, Xinchao; Zhu, Lixing; Kong, Linglong; Zhu, Hongtu

2015-01-01

Motivated by studying large-scale longitudinal image data, we propose a novel functional nonlinear mixed effects modeling (FN-MEM) framework to model the nonlinear spatial-temporal growth patterns of brain structure and function and their association with covariates of interest (e.g., time or diagnostic status). Our FNMEM explicitly quantifies a random nonlinear association map of individual trajectories. We develop an efficient estimation method to estimate the nonlinear growth function and the covariance operator of the spatial-temporal process. We propose a global test and a simultaneous confidence band for some specific growth patterns. We conduct Monte Carlo simulation to examine the finite-sample performance of the proposed procedures. We apply FNMEM to investigate the spatial-temporal dynamics of white-matter fiber skeletons in a national database for autism research. Our FNMEM may provide a valuable tool for charting the developmental trajectories of various neuropsychiatric and neurodegenerative disorders. PMID:26213453

Improved Spatial Differencing Scheme for 2-D DOA Estimation of Coherent Signals with Uniform Rectangular Arrays.

PubMed

Shi, Junpeng; Hu, Guoping; Sun, Fenggang; Zong, Binfeng; Wang, Xin

2017-08-24

This paper proposes an improved spatial differencing (ISD) scheme for two-dimensional direction of arrival (2-D DOA) estimation of coherent signals with uniform rectangular arrays (URAs). We first divide the URA into a number of row rectangular subarrays. Then, by extracting all the data information of each subarray, we only perform difference-operation on the auto-correlations, while the cross-correlations are kept unchanged. Using the reconstructed submatrices, both the forward only ISD (FO-ISD) and forward backward ISD (FB-ISD) methods are developed under the proposed scheme. Compared with the existing spatial smoothing techniques, the proposed scheme can use more data information of the sample covariance matrix and also suppress the effect of additive noise more effectively. Simulation results show that both FO-ISD and FB-ISD can improve the estimation performance largely as compared to the others, in white or colored noise conditions.

Improved Spatial Differencing Scheme for 2-D DOA Estimation of Coherent Signals with Uniform Rectangular Arrays

PubMed Central

Hu, Guoping; Zong, Binfeng; Wang, Xin

2017-01-01

This paper proposes an improved spatial differencing (ISD) scheme for two-dimensional direction of arrival (2-D DOA) estimation of coherent signals with uniform rectangular arrays (URAs). We first divide the URA into a number of row rectangular subarrays. Then, by extracting all the data information of each subarray, we only perform difference-operation on the auto-correlations, while the cross-correlations are kept unchanged. Using the reconstructed submatrices, both the forward only ISD (FO-ISD) and forward backward ISD (FB-ISD) methods are developed under the proposed scheme. Compared with the existing spatial smoothing techniques, the proposed scheme can use more data information of the sample covariance matrix and also suppress the effect of additive noise more effectively. Simulation results show that both FO-ISD and FB-ISD can improve the estimation performance largely as compared to the others, in white or colored noise conditions. PMID:28837115

On the importance of image formation optics in the design of infrared spectroscopic imaging systems

PubMed Central

Mayerich, David; van Dijk, Thomas; Walsh, Michael; Schulmerich, Matthew; Carney, P. Scott

2014-01-01

Infrared spectroscopic imaging provides micron-scale spatial resolution with molecular contrast. While recent work demonstrates that sample morphology affects the recorded spectrum, considerably less attention has been focused on the effects of the optics, including the condenser and objective. This analysis is extremely important, since it will be possible to understand effects on recorded data and provides insight for reducing optical effects through rigorous microscope design. Here, we present a theoretical description and experimental results that demonstrate the effects of commonly-employed cassegranian optics on recorded spectra. We first combine an explicit model of image formation and a method for quantifying and visualizing the deviations in recorded spectra as a function of microscope optics. We then verify these simulations with measurements obtained from spatially heterogeneous samples. The deviation of the computed spectrum from the ideal case is quantified via a map which we call a deviation map. The deviation map is obtained as a function of optical elements by systematic simulations. Examination of deviation maps demonstrates that the optimal optical configuration for minimal deviation is contrary to prevailing practice in which throughput is maximized for an instrument without a sample. This report should be helpful for understanding recorded spectra as a function of the optics, the analytical limits of recorded data determined by the optical design, and potential routes for optimization of imaging systems. PMID:24936526

On the importance of image formation optics in the design of infrared spectroscopic imaging systems.

PubMed

Mayerich, David; van Dijk, Thomas; Walsh, Michael J; Schulmerich, Matthew V; Carney, P Scott; Bhargava, Rohit

2014-08-21

Infrared spectroscopic imaging provides micron-scale spatial resolution with molecular contrast. While recent work demonstrates that sample morphology affects the recorded spectrum, considerably less attention has been focused on the effects of the optics, including the condenser and objective. This analysis is extremely important, since it will be possible to understand effects on recorded data and provides insight for reducing optical effects through rigorous microscope design. Here, we present a theoretical description and experimental results that demonstrate the effects of commonly-employed cassegranian optics on recorded spectra. We first combine an explicit model of image formation and a method for quantifying and visualizing the deviations in recorded spectra as a function of microscope optics. We then verify these simulations with measurements obtained from spatially heterogeneous samples. The deviation of the computed spectrum from the ideal case is quantified via a map which we call a deviation map. The deviation map is obtained as a function of optical elements by systematic simulations. Examination of deviation maps demonstrates that the optimal optical configuration for minimal deviation is contrary to prevailing practice in which throughput is maximized for an instrument without a sample. This report should be helpful for understanding recorded spectra as a function of the optics, the analytical limits of recorded data determined by the optical design, and potential routes for optimization of imaging systems.

Effect of species rarity on the accuracy of species distribution models for reptiles and amphibians in southern California

USGS Publications Warehouse

Franklin, J.; Wejnert, K.E.; Hathaway, S.A.; Rochester, C.J.; Fisher, R.N.

2009-01-01

Aim: Several studies have found that more accurate predictive models of species' occurrences can be developed for rarer species; however, one recent study found the relationship between range size and model performance to be an artefact of sample prevalence, that is, the proportion of presence versus absence observations in the data used to train the model. We examined the effect of model type, species rarity class, species' survey frequency, detectability and manipulated sample prevalence on the accuracy of distribution models developed for 30 reptile and amphibian species. Location: Coastal southern California, USA. Methods: Classification trees, generalized additive models and generalized linear models were developed using species presence and absence data from 420 locations. Model performance was measured using sensitivity, specificity and the area under the curve (AUC) of the receiver-operating characteristic (ROC) plot based on twofold cross-validation, or on bootstrapping. Predictors included climate, terrain, soil and vegetation variables. Species were assigned to rarity classes by experts. The data were sampled to generate subsets with varying ratios of presences and absences to test for the effect of sample prevalence. Join count statistics were used to characterize spatial dependence in the prediction errors. Results: Species in classes with higher rarity were more accurately predicted than common species, and this effect was independent of sample prevalence. Although positive spatial autocorrelation remained in the prediction errors, it was weaker than was observed in the species occurrence data. The differences in accuracy among model types were slight. Main conclusions: Using a variety of modelling methods, more accurate species distribution models were developed for rarer than for more common species. This was presumably because it is difficult to discriminate suitable from unsuitable habitat for habitat generalists, and not as an artefact of the effect of sample prevalence on model estimation. ?? 2008 The Authors.

Chagas disease vector control and Taylor's law

PubMed Central

Rodríguez-Planes, Lucía I.; Gaspe, María S.; Cecere, María C.; Cardinal, Marta V.

2017-01-01

Background Large spatial and temporal fluctuations in the population density of living organisms have profound consequences for biodiversity conservation, food production, pest control and disease control, especially vector-borne disease control. Chagas disease vector control based on insecticide spraying could benefit from improved concepts and methods to deal with spatial variations in vector population density. Methodology/Principal findings We show that Taylor's law (TL) of fluctuation scaling describes accurately the mean and variance over space of relative abundance, by habitat, of four insect vectors of Chagas disease (Triatoma infestans, Triatoma guasayana, Triatoma garciabesi and Triatoma sordida) in 33,908 searches of people's dwellings and associated habitats in 79 field surveys in four districts in the Argentine Chaco region, before and after insecticide spraying. As TL predicts, the logarithm of the sample variance of bug relative abundance closely approximates a linear function of the logarithm of the sample mean of abundance in different habitats. Slopes of TL indicate spatial aggregation or variation in habitat suitability. Predictions of new mathematical models of the effect of vector control measures on TL agree overall with field data before and after community-wide spraying of insecticide. Conclusions/Significance A spatial Taylor's law identifies key habitats with high average infestation and spatially highly variable infestation, providing a new instrument for the control and elimination of the vectors of a major human disease. PMID:29190728

Roles of Spatial Scale and Rarity on the Relationship between Butterfly Species Richness and Human Density in South Africa

PubMed Central

Mecenero, Silvia; Altwegg, Res; Colville, Jonathan F.; Beale, Colin M.

2015-01-01

Wildlife and humans tend to prefer the same productive environments, yet high human densities often lead to reduced biodiversity. Species richness is often positively correlated with human population density at broad scales, but this correlation could also be caused by unequal sampling effort leading to higher species tallies in areas of dense human activity. We examined the relationships between butterfly species richness and human population density at five spatial resolutions ranging from 2' to 60' across South Africa. We used atlas-type data and spatial interpolation techniques aimed at reducing the effect of unequal spatial sampling. Our results confirm the general positive correlation between total species richness and human population density. Contrary to our expectations, the strength of this positive correlation did not weaken at finer spatial resolutions. The patterns observed using total species richness were driven mostly by common species. The richness of threatened and restricted range species was not correlated to human population density. None of the correlations we examined were particularly strong, with much unexplained variance remaining, suggesting that the overlap between butterflies and humans is not strong compared to other factors not accounted for in our analyses. Special consideration needs to be made regarding conservation goals and variables used when investigating the overlap between species and humans for biodiversity conservation. PMID:25915899

Roles of Spatial Scale and Rarity on the Relationship between Butterfly Species Richness and Human Density in South Africa.

PubMed

Mecenero, Silvia; Altwegg, Res; Colville, Jonathan F; Beale, Colin M

2015-01-01

Wildlife and humans tend to prefer the same productive environments, yet high human densities often lead to reduced biodiversity. Species richness is often positively correlated with human population density at broad scales, but this correlation could also be caused by unequal sampling effort leading to higher species tallies in areas of dense human activity. We examined the relationships between butterfly species richness and human population density at five spatial resolutions ranging from 2' to 60' across South Africa. We used atlas-type data and spatial interpolation techniques aimed at reducing the effect of unequal spatial sampling. Our results confirm the general positive correlation between total species richness and human population density. Contrary to our expectations, the strength of this positive correlation did not weaken at finer spatial resolutions. The patterns observed using total species richness were driven mostly by common species. The richness of threatened and restricted range species was not correlated to human population density. None of the correlations we examined were particularly strong, with much unexplained variance remaining, suggesting that the overlap between butterflies and humans is not strong compared to other factors not accounted for in our analyses. Special consideration needs to be made regarding conservation goals and variables used when investigating the overlap between species and humans for biodiversity conservation.

Fine-scale landscape genetics of the American badger (Taxidea taxus): disentangling landscape effects and sampling artifacts in a poorly understood species

PubMed Central

Kierepka, E M; Latch, E K

2016-01-01

Landscape genetics is a powerful tool for conservation because it identifies landscape features that are important for maintaining genetic connectivity between populations within heterogeneous landscapes. However, using landscape genetics in poorly understood species presents a number of challenges, namely, limited life history information for the focal population and spatially biased sampling. Both obstacles can reduce power in statistics, particularly in individual-based studies. In this study, we genotyped 233 American badgers in Wisconsin at 12 microsatellite loci to identify alternative statistical approaches that can be applied to poorly understood species in an individual-based framework. Badgers are protected in Wisconsin owing to an overall lack in life history information, so our study utilized partial redundancy analysis (RDA) and spatially lagged regressions to quantify how three landscape factors (Wisconsin River, Ecoregions and land cover) impacted gene flow. We also performed simulations to quantify errors created by spatially biased sampling. Statistical analyses first found that geographic distance was an important influence on gene flow, mainly driven by fine-scale positive spatial autocorrelations. After controlling for geographic distance, both RDA and regressions found that Wisconsin River and Agriculture were correlated with genetic differentiation. However, only Agriculture had an acceptable type I error rate (3–5%) to be considered biologically relevant. Collectively, this study highlights the benefits of combining robust statistics and error assessment via simulations and provides a method for hypothesis testing in individual-based landscape genetics. PMID:26243136

Spatial Normalization of Reverse Phase Protein Array Data

PubMed Central

Kaushik, Poorvi; Molinelli, Evan J.; Miller, Martin L.; Wang, Weiqing; Korkut, Anil; Liu, Wenbin; Ju, Zhenlin; Lu, Yiling; Mills, Gordon; Sander, Chris

2014-01-01

Reverse phase protein arrays (RPPA) are an efficient, high-throughput, cost-effective method for the quantification of specific proteins in complex biological samples. The quality of RPPA data may be affected by various sources of error. One of these, spatial variation, is caused by uneven exposure of different parts of an RPPA slide to the reagents used in protein detection. We present a method for the determination and correction of systematic spatial variation in RPPA slides using positive control spots printed on each slide. The method uses a simple bi-linear interpolation technique to obtain a surface representing the spatial variation occurring across the dimensions of a slide. This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide. The adoption of the method results in increased agreement between technical and biological replicates of various tumor and cell-line derived samples. Further, in data from a study of the melanoma cell-line SKMEL-133, several slides that had previously been rejected because they had a coefficient of variation (CV) greater than 15%, are rescued by reduction of CV below this threshold in each case. The method is implemented in the R statistical programing language. It is compatible with MicroVigene and SuperCurve, packages commonly used in RPPA data analysis. The method is made available, along with suggestions for implementation, at http://bitbucket.org/rppa_preprocess/rppa_preprocess/src. PMID:25501559

Neighborhoods and Adolescent Health-Risk Behavior: An Ecological Network Approach1

PubMed Central

Browning, Christopher R.; Soller, Brian; Jackson, Aubrey L.

2014-01-01

This study integrates insights from social network analysis, activity space perspectives, and theories of urban and spatial processes to present an innovative approach to neighborhood effects on health-risk behavior among youth. We suggest spatial patterns of neighborhood residents’ non-home routine activities may be conceptualized as ecological, or “eco”-networks, which are two-mode networks that indirectly link residents through socio-spatial overlap in routine activities. We further argue structural configurations of eco-networks are consequential for youth’s behavioral health. In this study we focus on a key structural feature of eco-networks—the neighborhood-level extent to which households share two or more activity locations, or eco-network reinforcement—and its association with two dimensions of health-risk behavior, substance use and delinquency/sexual activity. Using geographic data on non-home routine activity locations among respondents from the Los Angeles Family and Neighborhood Survey (L.A.FANS), we constructed neighborhood-specific eco-networks by connecting sampled households to “activity clusters,” which are sets of spatially-proximate activity locations. We then measured eco-network reinforcement and examined its association with adolescent dimensions of health risk behavior employing a sample of 830 youth ages 12-17 nested in 65 census tracts. We also examined whether neighborhood-level social processes (collective efficacy and intergenerational closure) mediate the association between eco-network reinforcement and the outcomes considered. Results indicated eco-network reinforcement exhibits robust negative associations with both substance use and delinquency/sexual activity scales. Eco-network reinforcement effects were not explained by potential mediating variables. In addition to introducing a novel theoretical and empirical approach to neighborhood effects on youth, our findings highlight the importance of eco-network reinforcement for adolescent behavioral health. PMID:25011958

The space-math link in preschool boys and girls: Importance of mental transformation, targeting accuracy, and spatial anxiety.

PubMed

Wong, Wang I

2017-06-01

Spatial abilities are pertinent to mathematical competence, but evidence of the space-math link has largely been confined to older samples and intrinsic spatial abilities (e.g., mental transformation). The roles of gender and affective factors are also unclear. This study examined the correlations between counting ability, mental transformation, and targeting accuracy in 182 Hong Kong preschoolers, and whether these relationships were weaker at higher spatial anxiety levels. Both spatial abilities related with counting similarly for boys and girls. Targeting accuracy also mediated the male advantage in counting. Interestingly, spatial anxiety moderated the space-math links, but differently for boys and girls. For boys, spatial abilities were irrelevant to counting at high anxiety levels; for girls, the role of anxiety on the space-math link is less clear. Results extend the evidence base of the space-math link to include an extrinsic spatial ability (targeting accuracy) and have implications for intervention programmes. Statement of contribution What is already known on this subject? Much evidence of a space-math link in adolescent and adult samples and for intrinsic spatial abilities. What does this study add? Extended the space-math link to include both intrinsic and extrinsic spatial abilities in a preschool sample. Showed how spatial anxiety moderated the space-math link differently for boys and girls. © 2016 The British Psychological Society.

Indications of a spatial variation of the fine structure constant.

PubMed

Webb, J K; King, J A; Murphy, M T; Flambaum, V V; Carswell, R F; Bainbridge, M B

2011-11-04

We previously reported Keck telescope observations suggesting a smaller value of the fine structure constant α at high redshift. New Very Large Telescope (VLT) data, probing a different direction in the Universe, shows an inverse evolution; α increases at high redshift. Although the pattern could be due to as yet undetected systematic effects, with the systematics as presently understood the combined data set fits a spatial dipole, significant at the 4.2 σ level, in the direction right ascension 17.5 ± 0.9 h, declination -58 ± 9 deg. The independent VLT and Keck samples give consistent dipole directions and amplitudes, as do high and low redshift samples. A search for systematics, using observations duplicated at both telescopes, reveals none so far which emulate this result.

Time-Lapse Electrical Geophysical Monitoring of Amendment-Based Biostimulation

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

Johnson, Timothy C.; Versteeg, Roelof; Day-Lewis, Frederick D.

Biostimulation is increasingly used to accelerate microbial remediation of recalcitrant groundwater contaminants. Effective application of biostimulation requires successful emplacement of amendment in the contaminant target zone. Verification of remediation performance requires postemplacement assessment and contaminant monitoring. Sampling based approaches are expensive and provide low-density spatial and temporal information. Time-lapse electrical resistivity tomography (ERT) is an effective geophysical method for determining temporal changes in subsurface electrical conductivity. Because remedial amendments and biostimulation-related biogeochemical processes often change subsurface electrical conductivity, ERT can complement and enhance sampling-based approaches for assessing emplacement and monitoring biostimulation-based remediation. Field studies demonstrating the ability of time-lapse ERTmore » to monitor amendment emplacement and behavior were performed during a biostimulation remediation effort conducted at the Department of Defense Reutilization and Marketing Office (DRMO) Yard, in Brandywine, Maryland, United States. Geochemical fluid sampling was used to calibrate a petrophysical relation in order to predict groundwater indicators of amendment distribution. The petrophysical relations were field validated by comparing predictions to sequestered fluid sample results, thus demonstrating the potential of electrical geophysics for quantitative assessment of amendment-related geochemical properties. Crosshole radar zero-offset profile and borehole geophysical logging were also performed to augment the data set and validate interpretation. In addition to delineating amendment transport in the first 10 months after emplacement, the time-lapse ERT results show later changes in bulk electrical properties interpreted as mineral precipitation. Results support the use of more cost-effective surfacebased ERT in conjunction with limited field sampling to improve spatial and temporal monitoring of amendment emplacement and remediation performance.« less

Time-lapse electrical geophysical monitoring of amendment-based biostimulation

USGS Publications Warehouse

Johnson, Timothy C.; Versteeg, Roelof J.; Day-Lewis, Frederick D.; Major, William; Lane, John W.

2015-01-01

Biostimulation is increasingly used to accelerate microbial remediation of recalcitrant groundwater contaminants. Effective application of biostimulation requires successful emplacement of amendment in the contaminant target zone. Verification of remediation performance requires postemplacement assessment and contaminant monitoring. Sampling-based approaches are expensive and provide low-density spatial and temporal information. Time-lapse electrical resistivity tomography (ERT) is an effective geophysical method for determining temporal changes in subsurface electrical conductivity. Because remedial amendments and biostimulation-related biogeochemical processes often change subsurface electrical conductivity, ERT can complement and enhance sampling-based approaches for assessing emplacement and monitoring biostimulation-based remediation.Field studies demonstrating the ability of time-lapse ERT to monitor amendment emplacement and behavior were performed during a biostimulation remediation effort conducted at the Department of Defense Reutilization and Marketing Office (DRMO) Yard, in Brandywine, Maryland, United States. Geochemical fluid sampling was used to calibrate a petrophysical relation in order to predict groundwater indicators of amendment distribution. The petrophysical relations were field validated by comparing predictions to sequestered fluid sample results, thus demonstrating the potential of electrical geophysics for quantitative assessment of amendment-related geochemical properties. Crosshole radar zero-offset profile and borehole geophysical logging were also performed to augment the data set and validate interpretation.In addition to delineating amendment transport in the first 10 months after emplacement, the time-lapse ERT results show later changes in bulk electrical properties interpreted as mineral precipitation. Results support the use of more cost-effective surface-based ERT in conjunction with limited field sampling to improve spatial and temporal monitoring of amendment emplacement and remediation performance.

Spatial capture-recapture

USGS Publications Warehouse

Royle, J. Andrew; Chandler, Richard B.; Sollmann, Rahel; Gardner, Beth

2013-01-01

Spatial Capture-Recapture provides a revolutionary extension of traditional capture-recapture methods for studying animal populations using data from live trapping, camera trapping, DNA sampling, acoustic sampling, and related field methods. This book is a conceptual and methodological synthesis of spatial capture-recapture modeling. As a comprehensive how-to manual, this reference contains detailed examples of a wide range of relevant spatial capture-recapture models for inference about population size and spatial and temporal variation in demographic parameters. Practicing field biologists studying animal populations will find this book to be a useful resource, as will graduate students and professionals in ecology, conservation biology, and fisheries and wildlife management.

DOWN-STREAM SPATIAL DISTRIBUTION OF ANTIBIOTIC RESISTANCE TRAITS ALONG METAL CONTAMINATED STREAM REACHES

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

Tuckfield, C; J V Mcarthur

2007-04-16

Sediment bacteria samples were collected from three streams in South Carolina, two contaminated with multiple metals (Four Mile Creek and Castor Creek), one uncontaminated (Meyers Branch), and another metal contaminated stream (Lampert Creek) in northern Washington State. Growth plates inoculated with Four Mile Creek sample extracts show bacteria colony growth after incubation on plates containing either one of two aminoglycosides (kanamycin or streptomycin), tetracycline or chloramphenocol. This study analyzes the spatial pattern of antibiotic resistance in culturable sediment bacteria in all four streams that may be due to metal contamination. We summarize the two aminoglycoside resistance measures and the 10more » metals concentrations by Principal Components Analysis. Respectively, 63% and 58% of the variability was explained in the 1st principal component of each variable set. We used the respective multivariate summary metrics (i.e. 1st principal component scores) as input measures for exploring the spatial correlation between antibiotic resistance and metal concentration for each stream reach sampled. Results show a significant and negative correlation between metals scores versus aminoglycoside resistance scores and suggest that selection for metal tolerance among sediment bacteria may influence selection for antibiotic resistance differently than previously supposed.. In addition, we borrow a method from geostatistics (variography) wherein a spatial cross-correlation analysis shows that decreasing metal concentrations scores are associated with increasing aminoglycoside resistance scores as the separation distance between sediment samples decreases, but for contaminated streams only. Since these results were counter to our initial expectation and to other experimental evidence for water column bacteria, we suspect our field results are influenced by metal bioavailability in the sediments and by a contaminant promoted interaction or ''cocktail effect'' from complex combinations of pollution mediated selection agents.« less

Improving working memory in children with low language abilities

PubMed Central

Holmes, Joni; Butterfield, Sally; Cormack, Francesca; van Loenhoud, Anita; Ruggero, Leanne; Kashikar, Linda; Gathercole, Susan

2015-01-01

This study investigated whether working memory training is effective in enhancing verbal memory in children with low language abilities (LLA). Cogmed Working Memory Training was completed by a community sample of children aged 8–11 years with LLA and a comparison group with matched non-verbal abilities and age-typical language performance. Short-term memory (STM), working memory, language, and IQ were assessed before and after training. Significant and equivalent post-training gains were found in visuo-spatial short-term memory in both groups. Exploratory analyses across the sample established that low verbal IQ scores were strongly and highly specifically associated with greater gains in verbal STM, and that children with higher verbal IQs made greater gains in visuo-spatial short-term memory following training. This provides preliminary evidence that intensive working memory training may be effective for enhancing the weakest aspects of STM in children with low verbal abilities, and may also be of value in developing compensatory strategies. PMID:25983703

Maternal working memory and reactive negativity in parenting.

PubMed

Deater-Deckard, Kirby; Sewell, Michael D; Petrill, Stephen A; Thompson, Lee A

2010-01-01

We examined the role of working memory in observed reactive parenting in a sample of 216 mothers and their same-sex twin children. The mothers and their children were observed completing two frustrating cooperation tasks during a visit to the home. The mothers worked one-on-one with each child separately. Mothers completed the Vocabulary (verbal), Block Design (spatial), and Digit Span (working memory) subtests of the Wechsler Adult Intelligence Scale-Third Edition. We used a within-family quasi-experimental design to estimate the magnitude of the association between sibling differences in observed challenging behaviors (i.e., opposition and distractibility) and the difference in the mother's negativity toward each child. As hypothesized, reactive negativity was evident only among mothers with poorer working memory. Verbal and spatial ability did not show this moderating effect. The effect was replicated in a post hoc secondary data analysis of a sample of adoptive mothers and sibling children. Results implicate working memory in the etiology of harsh reactive parenting.

A temporal and spatial assessment of TBT concentrations at dredged material disposal sites around the coast of England and Wales.

PubMed

Bolam, Thi; Barry, Jon; Law, Robin J; James, David; Thomas, Boby; Bolam, Stefan G

2014-02-15

Despite legislative interventions since the 1980s, contemporary concentrations of organotin compounds in marine sediments still impose restrictions on the disposal of dredged material in the UK. Here, we analyse temporal and spatial data to assess the effectiveness of the ban on the use of TBT paints in reducing concentrations at disposal sites. At a national scale, there was a statistically significant increase in the proportion of samples in which the concentration was below the limit of detection (LOD) from 1998 to 2010. This was observed for sediments both inside and outside the disposal sites. However, this temporal decline in organotin concentration is disposal site-specific. Of the four sites studied in detail, two displayed significant increases in proportion of samples below LOD over time. We argue that site-specificity in the effectiveness of the TBT ban results from variations in historical practices at source and unique environmental characteristics of each site. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

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.

OpenMSI Arrayed Analysis Tools v2.0

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

BOWEN, BENJAMIN; RUEBEL, OLIVER; DE ROND, TRISTAN

2017-02-07

Mass spectrometry imaging (MSI) enables high-resolution spatial mapping of biomolecules in samples and is a valuable tool for the analysis of tissues from plants and animals, microbial interactions, high-throughput screening, drug metabolism, and a host of other applications. This is accomplished by desorbing molecules from the surface on spatially defined locations, using a laser or ion beam. These ions are analyzed by a mass spectrometry and collected into a MSI 'image', a dataset containing unique mass spectra from the sampled spatial locations. MSI is used in a diverse and increasing number of biological applications. The OpenMSI Arrayed Analysis Tool (OMAAT)more » is a new software method that addresses the challenges of analyzing spatially defined samples in large MSI datasets, by providing support for automatic sample position optimization and ion selection.« less

Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome.

PubMed

Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

2015-01-01

Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate "wall-to-wall" remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution.

Improving the accuracy of livestock distribution estimates through spatial interpolation.

PubMed

Bryssinckx, Ward; Ducheyne, Els; Muhwezi, Bernard; Godfrey, Sunday; Mintiens, Koen; Leirs, Herwig; Hendrickx, Guy

2012-11-01

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P <0.009 based on a sample of 2,077 parishes using one-stage stratified samples). During aggregation, area-weighted mean values were assigned to higher administrative unit levels. However, when this step is preceded by a spatial interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level). Whether the same observations apply on a lower spatial scale should be further investigated.

Pulsed field gradients in simulations of one- and two-dimensional NMR spectra.

PubMed

Meresi, G H; Cuperlovic, M; Palke, W E; Gerig, J T

1999-03-01

A method for the inclusion of the effects of z-axis pulsed field gradients in computer simulations of an arbitrary pulsed NMR experiment with spin (1/2) nuclei is described. Recognizing that the phase acquired by a coherence following the application of a z-axis pulsed field gradient bears a fixed relation to its order and the spatial position of the spins in the sample tube, the sample is regarded as a collection of volume elements, each phase-encoded by a characteristic, spatially dependent precession frequency. The evolution of the sample's density matrix is thus obtained by computing the evolution of the density matrix for each volume element. Following the last gradient pulse, these density matrices are combined to form a composite density matrix which evolves through the rest of the experiment to yield the observable signal. This approach is implemented in a program which includes capabilities for rigorous inclusion of spin relaxation by dipole-dipole, chemical shift anisotropy, and random field mechanisms, plus the effects of arbitrary RF fields. Mathematical procedures for accelerating these calculations are described. The approach is illustrated by simulations of representative one- and two-dimensional NMR experiments. Copyright 1999 Academic Press.

Spatial resolution enhancement of terrestrial features using deconvolved SSM/I microwave brightness temperatures

NASA Technical Reports Server (NTRS)

Farrar, Michael R.; Smith, Eric A.

1992-01-01

A method for enhancing the 19, 22, and 37 GHz measurements of the SSM/I (Special Sensor Microwave/Imager) to the spatial resolution and sampling density of the high resolution 85-GHz channel is presented. An objective technique for specifying the tuning parameter, which balances the tradeoff between resolution and noise, is developed in terms of maximizing cross-channel correlations. Various validation procedures are performed to demonstrate the effectiveness of the method, which hopefully will provide researchers with a valuable tool in multispectral applications of satellite radiometer data.

Relationship of Pupils' Spatial Perception and Ability with Their Performance in Geography

ERIC Educational Resources Information Center

Likouri, Anna-Aikaterini; Klonari, Aikaterini; Flouris, George

2017-01-01

The aim of this study was to investigate the correlation between pupils' spatial perception and abilities and their performance in geography. The sample was 600 6th-grade pupils from various areas of Greece selected by the cluster sampling method. The study results showed that: a) the vast majority of pupils showed low spatial ability; b) there…

Observation and studies of double J / ψ production at the Tevatron

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

Abazov, V. M.; Abbott, B.; Acharya, B. S.

2014-12-01

We present the observation of doubly-producedmore » $$J/\\psi$$ mesons with the D0 detector at Fermilab in $$p\\bar{p}$$ collisions at $$\\sqrt{s}=1.96$$ TeV. The production cross section for both singly and doubly-produced $$J/\\psi$$ mesons is measured using a sample with an integrated luminosity of 8.1fb$$^{-1}$$. For the first time, the double $$J/\\psi$$ production cross section is separated into contributions due to single and double parton scatterings. Using these measurements, we determine the effective cross section $$\\sigma_{eff}$$, a parameter characterizing an effective spatial area of the parton-parton interactions and related to the parton spatial density inside the nucleon.« less

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

Kirtley, John R., E-mail: jkirtley@stanford.edu; Rosenberg, Aaron J.; Palmstrom, Johanna C.

Superconducting QUantum Interference Device (SQUID) microscopy has excellent magnetic field sensitivity, but suffers from modest spatial resolution when compared with other scanning probes. This spatial resolution is determined by both the size of the field sensitive area and the spacing between this area and the sample surface. In this paper we describe scanning SQUID susceptometers that achieve sub-micron spatial resolution while retaining a white noise floor flux sensitivity of ≈2μΦ{sub 0}/Hz{sup 1/2}. This high spatial resolution is accomplished by deep sub-micron feature sizes, well shielded pickup loops fabricated using a planarized process, and a deep etch step that minimizes themore » spacing between the sample surface and the SQUID pickup loop. We describe the design, modeling, fabrication, and testing of these sensors. Although sub-micron spatial resolution has been achieved previously in scanning SQUID sensors, our sensors not only achieve high spatial resolution but also have integrated modulation coils for flux feedback, integrated field coils for susceptibility measurements, and batch processing. They are therefore a generally applicable tool for imaging sample magnetization, currents, and susceptibilities with higher spatial resolution than previous susceptometers.« less

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression.

PubMed

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson's statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran's index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China's regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test.

Long-term spatial and temporal microbial community dynamics in a large-scale drinking water distribution system with multiple disinfectant regimes.

PubMed

Potgieter, Sarah; Pinto, Ameet; Sigudu, Makhosazana; du Preez, Hein; Ncube, Esper; Venter, Stephanus

2018-08-01

Long-term spatial-temporal investigations of microbial dynamics in full-scale drinking water distribution systems are scarce. These investigations can reveal the process, infrastructure, and environmental factors that influence the microbial community, offering opportunities to re-think microbial management in drinking water systems. Often, these insights are missed or are unreliable in short-term studies, which are impacted by stochastic variabilities inherent to large full-scale systems. In this two-year study, we investigated the spatial and temporal dynamics of the microbial community in a large, full scale South African drinking water distribution system that uses three successive disinfection strategies (i.e. chlorination, chloramination and hypochlorination). Monthly bulk water samples were collected from the outlet of the treatment plant and from 17 points in the distribution system spanning nearly 150 km and the bacterial community composition was characterised by Illumina MiSeq sequencing of the V4 hypervariable region of the 16S rRNA gene. Like previous studies, Alpha- and Betaproteobacteria dominated the drinking water bacterial communities, with an increase in Betaproteobacteria post-chloramination. In contrast with previous reports, the observed richness, diversity, and evenness of the bacterial communities were higher in the winter months as opposed to the summer months in this study. In addition to temperature effects, the seasonal variations were also likely to be influenced by changes in average water age in the distribution system and corresponding changes in disinfectant residual concentrations. Spatial dynamics of the bacterial communities indicated distance decay, with bacterial communities becoming increasingly dissimilar with increasing distance between sampling locations. These spatial effects dampened the temporal changes in the bulk water community and were the dominant factor when considering the entire distribution system. However, temporal variations were consistently stronger as compared to spatial changes at individual sampling locations and demonstrated seasonality. This study emphasises the need for long-term studies to comprehensively understand the temporal patterns that would otherwise be missed in short-term investigations. Furthermore, systematic long-term investigations are particularly critical towards determining the impact of changes in source water quality, environmental conditions, and process operations on the changes in microbial community composition in the drinking water distribution system. Copyright © 2018 Elsevier Ltd. All rights reserved.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters).

PubMed

Sisniega, A; Zbijewski, W; Stayman, J W; Xu, J; Taguchi, K; Fredenberg, E; Lundqvist, Mats; Siewerdsen, J H

2016-01-07

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm  ×  25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8  ×  higher CNR (at matched spatial resolution) compared to the constant penalty. The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters)

NASA Astrophysics Data System (ADS)

Sisniega, A.; Zbijewski, W.; Stayman, J. W.; Xu, J.; Taguchi, K.; Fredenberg, E.; Lundqvist, Mats; Siewerdsen, J. H.

2016-01-01

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm  ×  25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8  ×  higher CNR (at matched spatial resolution) compared to the constant penalty. The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters)

PubMed Central

Sisniega, A; Zbijewski, W; Stayman, J W; Xu, J; Taguchi, K; Fredenberg, E; Lundqvist, Mats; Siewerdsen, J H

2016-01-01

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm × 25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8 × higher CNR (at matched spatial resolution) compared to the constant penalty. The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging. PMID:26611740

Within-field spatial distribution of Megacopta cribraria (Hemiptera: Plataspidae) in soybean (Fabales: Fabaceae).

PubMed

Seiter, Nicholas J; Reay-Jones, Francis P F; Greene, Jeremy K

2013-12-01

The recently introduced plataspid Megacopta cribraria (F.) can infest fields of soybean (Glycine max (L.) Merrill) in the southeastern United States. Grid sampling in four soybean fields was conducted in 2011 and 2012 to study the spatial distribution of M. cribraria adults, nymphs, and egg masses. Peak oviposition typically occurred in early August, while peak levels of adults occurred in mid-late September. The overall sex ratio was slightly biased at 53.1 ± 0.2% (SEM) male. Sweep samples of nymphs were biased toward late instars. All three life stages exhibited a generally aggregated spatial distribution based on Taylor's power law, Iwao's patchiness regression, and spatial analysis by distance indices (SADIE). Interpolation maps of local SADIE aggregation indices showed clusters of adults and nymphs located at field edges, and mean densities of adults were higher in samples taken from field edges than in those taken from field interiors. Adults and nymphs were often spatially associated based on SADIE, indicating spatial stability across life stages.

Maintenance of tactile short-term memory for locations is mediated by spatial attention.

PubMed

Katus, Tobias; Andersen, Søren K; Müller, Matthias M

2012-01-01

According to the attention-based rehearsal hypothesis, maintenance of spatial information is mediated by covert orienting towards memorized locations. In a somatosensory memory task, participants simultaneously received bilateral pairs of mechanical sample pulses. For each hand, sample stimuli were randomly assigned to one of three locations (fingers). A subsequent visual retro-cue determined whether the left or right hand sample was to be memorized. The retro-cue elicited lateralized activity reflecting the location of the relevant sample stimulus. Sensory processing during the retention period was probed by task-irrelevant pulses randomized to locations at the cued and uncued hand. The somatosensory N140 was enhanced for probes delivered to the cued hand, relative to uncued. Probes presented shortly after the retro-cue showed greatest attentional modulations. This suggests that transient contributions from retrospective selection overlapped with the sustained effect of attention-based rehearsal. In conclusion, focal attention shifts within tactile mnemonic content occurred after retro-cues and guided sensory processing during retention. Copyright © 2011 Elsevier B.V. All rights reserved.

A Bayesian method for assessing multiscalespecies-habitat relationships

USGS Publications Warehouse

Stuber, Erica F.; Gruber, Lutz F.; Fontaine, Joseph J.

2017-01-01

ContextScientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multi-scale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large.ObjectivesOur objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance.MethodsWe introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA.ResultsOur method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%.ConclusionsGiven the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.

Spatial Evaluation of Heavy Metals Concentrations in the Surface Sediment of Taihu Lake.

PubMed

Niu, Yong; Jiao, Wei; Yu, Hui; Niu, Yuan; Pang, Yong; Xu, Xiangyang; Guo, Xiaochun

2015-11-27

With regard to the size of China's freshwater lakes, Taihu Lake ranks third and it plays an important role in the supply of drinking water, flood prevention, farming and navigation, as well as in the travelling industry. The problem of environmental pollution has attracted widespread attention in recent years. In order to understand the levels, distribution and sources of heavy metals in sediments of Taihu Lake, random selection was carried out to obtain 59 samples of surface sediment from the entire lake and study the concentrations of Pb, Cd, Cu, Zn, Cr and Ni. Toxic units were also calculated to normalize the toxicities caused by various heavy metals. As a result, Cd and Cu in sediment were considered lower than the effect range low (ERL) at all regions where samples were gathered, while Pb and Ni were categorized into ERL-effect range median (ERM) at over 22% of the regions where samples were obtained. Nevertheless, all average concentrations of the samples were below the level of potential effect. According to the findings of this research, significant spatial heterogeneity existed in the above heavy metals. In conclusion, the distribution areas of heavy metals with higher concentrations were mainly the north bays, namely Zhushan Bay, Meiliang Bay as well as Gonghu Bay. The distribution areas of Cu, Zn, Cr and Ni with higher concentration also included the lake's central region, whereas the uniform distribution areas of those with lower concentrations were the lake's southeast region. In addition, it was most probable that the spatial distribution of heavy metals was determined by river inputs, whereas atmospheric precipitation caused by urban and traffic contamination also exerted considerable effects on the higher concentrations of Pb and Cd. Through evaluating the total amount of toxic units (ΣTU), it was found that higher toxicity existed primarily in the north bays and central region of the lake. If the heavy metals were sorted by the reduction of mean heavy metal toxic units in Taihu Lake in descending order, it would be Pb, Cr, Ni, Cd, Zn and Cu. Generally speaking, these result of analyses are conducive to alleviating the contamination of heavy metals in Taihu Lake.

Linear multivariate evaluation models for spatial perception of soundscape.

PubMed

Deng, Zhiyong; Kang, Jian; Wang, Daiwei; Liu, Aili; Kang, Joe Zhengyu

2015-11-01

Soundscape is a sound environment that emphasizes the awareness of auditory perception and social or cultural understandings. The case of spatial perception is significant to soundscape. However, previous studies on the auditory spatial perception of the soundscape environment have been limited. Based on 21 native binaural-recorded soundscape samples and a set of auditory experiments for subjective spatial perception (SSP), a study of the analysis among semantic parameters, the inter-aural-cross-correlation coefficient (IACC), A-weighted-equal sound-pressure-level (L(eq)), dynamic (D), and SSP is introduced to verify the independent effect of each parameter and to re-determine some of their possible relationships. The results show that the more noisiness the audience perceived, the worse spatial awareness they received, while the closer and more directional the sound source image variations, dynamics, and numbers of sound sources in the soundscape are, the better the spatial awareness would be. Thus, the sensations of roughness, sound intensity, transient dynamic, and the values of Leq and IACC have a suitable range for better spatial perception. A better spatial awareness seems to promote the preference slightly for the audience. Finally, setting SSPs as functions of the semantic parameters and Leq-D-IACC, two linear multivariate evaluation models of subjective spatial perception are proposed.

Distributed encoding of spatial and object categories in primate hippocampal microcircuits

PubMed Central

Opris, Ioan; Santos, Lucas M.; Gerhardt, Greg A.; Song, Dong; Berger, Theodore W.; Hampson, Robert E.; Deadwyler, Sam A.

2015-01-01

The primate hippocampus plays critical roles in the encoding, representation, categorization and retrieval of cognitive information. Such cognitive abilities may use the transformational input-output properties of hippocampal laminar microcircuitry to generate spatial representations and to categorize features of objects, images, and their numeric characteristics. Four nonhuman primates were trained in a delayed-match-to-sample (DMS) task while multi-neuron activity was simultaneously recorded from the CA1 and CA3 hippocampal cell fields. The results show differential encoding of spatial location and categorization of images presented as relevant stimuli in the task. Individual hippocampal cells encoded visual stimuli only on specific types of trials in which retention of either, the Sample image, or the spatial position of the Sample image indicated at the beginning of the trial, was required. Consistent with such encoding, it was shown that patterned microstimulation applied during Sample image presentation facilitated selection of either Sample image spatial locations or types of images, during the Match phase of the task. These findings support the existence of specific codes for spatial and numeric object representations in primate hippocampus which can be applied on differentially signaled trials. Moreover, the transformational properties of hippocampal microcircuitry, together with the patterned microstimulation are supporting the practical importance of this approach for cognitive enhancement and rehabilitation, needed for memory neuroprosthetics. PMID:26500473

STAR FORMATION LAWS: THE EFFECTS OF GAS CLOUD SAMPLING

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

Calzetti, D.; Liu, G.; Koda, J., E-mail: calzetti@astro.umass.edu

Recent observational results indicate that the functional shape of the spatially resolved star formation-molecular gas density relation depends on the spatial scale considered. These results may indicate a fundamental role of sampling effects on scales that are typically only a few times larger than those of the largest molecular clouds. To investigate the impact of this effect, we construct simple models for the distribution of molecular clouds in a typical star-forming spiral galaxy and, assuming a power-law relation between star formation rate (SFR) and cloud mass, explore a range of input parameters. We confirm that the slope and the scattermore » of the simulated SFR-molecular gas surface density relation depend on the size of the sub-galactic region considered, due to stochastic sampling of the molecular cloud mass function, and the effect is larger for steeper relations between SFR and molecular gas. There is a general trend for all slope values to tend to {approx}unity for region sizes larger than 1-2 kpc, irrespective of the input SFR-cloud relation. The region size of 1-2 kpc corresponds to the area where the cloud mass function becomes fully sampled. We quantify the effects of selection biases in data tracing the SFR, either as thresholds (i.e., clouds smaller than a given mass value do not form stars) or as backgrounds (e.g., diffuse emission unrelated to current star formation is counted toward the SFR). Apparently discordant observational results are brought into agreement via this simple model, and the comparison of our simulations with data for a few galaxies supports a steep (>1) power-law index between SFR and molecular gas.« less

Three-gene identity coefficients demonstrate that clonal reproduction promotes inbreeding and spatial relatedness in yellow-cedar, Callitropsis nootkatensis.

PubMed

Thompson, Stacey Lee; Bérubé, Yanik; Bruneau, Anne; Ritland, Kermit

2008-10-01

Asexual reproduction has the potential to promote population structuring through matings between clones as well as through limited dispersal of related progeny. Here we present an application of three-gene identity coefficients that tests whether clonal reproduction promotes inbreeding and spatial relatedness within populations. With this method, the first two genes are sampled to estimate pairwise relatedness or inbreeding, whereas the third gene is sampled from either a clone or a sexually derived individual. If three-gene coefficients are significantly greater for clones than nonclones, then clonality contributes excessively to genetic structure. First, we describe an estimator of three-gene identity and briefly evaluate its properties. We then use this estimator to test the effect of clonality on the genetic structure within populations of yellow-cedar (Callitropsis nootkatensis) using a molecular marker survey. Five microsatellite loci were genotyped for 485 trees sampled from nine populations. Our three-gene analyses show that clonal ramets promote inbreeding and spatial structure in most populations. Among-population correlations between clonal extent and genetic structure generally support these trends, yet with less statistical significance. Clones appear to contribute to genetic structure through the limited dispersal of offspring from replicated ramets of the same clonal genet, whereas this structure is likely maintained by mating among these relatives.

Impact of Satellite Viewing-Swath Width on Global and Regional Aerosol Optical Thickness Statistics and Trends

NASA Technical Reports Server (NTRS)

Colarco, P. R.; Kahn, R. A.; Remer, L. A.; Levy, R. C.

2014-01-01

We use the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite aerosol optical thickness (AOT) product to assess the impact of reduced swath width on global and regional AOT statistics and trends. Alongtrack and across-track sampling strategies are employed, in which the full MODIS data set is sub-sampled with various narrow-swath (approximately 400-800 km) and single pixel width (approximately 10 km) configurations. Although view-angle artifacts in the MODIS AOT retrieval confound direct comparisons between averages derived from different sub-samples, careful analysis shows that with many portions of the Earth essentially unobserved, spatial sampling introduces uncertainty in the derived seasonal-regional mean AOT. These AOT spatial sampling artifacts comprise up to 60%of the full-swath AOT value under moderate aerosol loading, and can be as large as 0.1 in some regions under high aerosol loading. Compared to full-swath observations, narrower swath and single pixel width sampling exhibits a reduced ability to detect AOT trends with statistical significance. On the other hand, estimates of the global, annual mean AOT do not vary significantly from the full-swath values as spatial sampling is reduced. Aggregation of the MODIS data at coarse grid scales (10 deg) shows consistency in the aerosol trends across sampling strategies, with increased statistical confidence, but quantitative errors in the derived trends are found even for the full-swath data when compared to high spatial resolution (0.5 deg) aggregations. Using results of a model-derived aerosol reanalysis, we find consistency in our conclusions about a seasonal-regional spatial sampling artifact in AOT Furthermore, the model shows that reduced spatial sampling can amount to uncertainty in computed shortwave top-ofatmosphere aerosol radiative forcing of 2-3 W m(sup-2). These artifacts are lower bounds, as possibly other unconsidered sampling strategies would perform less well. These results suggest that future aerosol satellite missions having significantly less than full-swath viewing are unlikely to sample the true AOT distribution well enough to obtain the statistics needed to reduce uncertainty in aerosol direct forcing of climate.

A New Stratified Sampling Procedure which Decreases Error Estimation of Varroa Mite Number on Sticky Boards.

PubMed

Kretzschmar, A; Durand, E; Maisonnasse, A; Vallon, J; Le Conte, Y

2015-06-01

A new procedure of stratified sampling is proposed in order to establish an accurate estimation of Varroa destructor populations on sticky bottom boards of the hive. It is based on the spatial sampling theory that recommends using regular grid stratification in the case of spatially structured process. The distribution of varroa mites on sticky board being observed as spatially structured, we designed a sampling scheme based on a regular grid with circles centered on each grid element. This new procedure is then compared with a former method using partially random sampling. Relative error improvements are exposed on the basis of a large sample of simulated sticky boards (n=20,000) which provides a complete range of spatial structures, from a random structure to a highly frame driven structure. The improvement of varroa mite number estimation is then measured by the percentage of counts with an error greater than a given level. © 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.

Spatial variation of dissolved organic matter composition and characteristics in an urbanized watershed

NASA Astrophysics Data System (ADS)

Hsieh, C.; Li, M.

2013-12-01

Dissolved organic matter (DOM) is a chemically complex mixture of organic polymers that plays an important role in river ecosystems and originates from various sources. Some DOMs are autochthonous originating through phytoplankton and microbial activity in situ. On the other hand, some DOMs are allochthonous which are transported to river from the surrounding watershed by natural or anthropogenic activities. The studies of DOM in river are usually conducted at the watershed scale; however, factors of local spatial scale affecting DOM composition also need to take into consideration for the study of DOM in an urbanized watershed. Through increasing urbanization, changes in a watershed occur not only in land use patterns but also in river channel characteristics. The objective of this study is to investigate effects of different river channel characteristics and patterns on changes in DOM source and composition. In this study, we chose three tributaries of Tamsui river in Taiwan according to its land use pattern and river channel characteristics. At each sub-basin, river water samples were sampled from three study sites. River water DOM was measured by using optical measurements of UV absorption and fluorescence spectroscopy. Water samples were also collected for laboratory analysis of different water quality parameters. From our study sites, they are from three sub-basins which are in the similar physical environments but with different river channel types: the highly channelized Keelung river, the less channelized Xindian river, and less channelized Dahan river with five human-made wetlands. From the upstream to the urbanized downstream, composition of DOM showed variation among different sampled sites. In all three sub-basins, the trends of 5-day biochemical oxygen demand (BOD5) and suspended solids (SS) are also different. The changes in DOM source and composition as well as different water quality parmaters occur at the local spatial-scale depended on their river channel characters in urbanized watersheds. Based on our result, it indicates river channel characters which can have effects on biogeochemical processes of DOM. This knowledge can help us in understanding biogeochemical processes controlled or manipulated by anthropogenic activities at different spatial scales, and help us to make an integrative river health management in a watershed.

Quantifying tap-to-household water quality deterioration in urban communities in Vellore, India: The impact of spatial assumptions.

PubMed

Alarcon Falconi, Tania M; Kulinkina, Alexandra V; Mohan, Venkata Raghava; Francis, Mark R; Kattula, Deepthi; Sarkar, Rajiv; Ward, Honorine; Kang, Gagandeep; Balraj, Vinohar; Naumova, Elena N

2017-01-01

Municipal water sources in India have been found to be highly contaminated, with further water quality deterioration occurring during household storage. Quantifying water quality deterioration requires knowledge about the exact source tap and length of water storage at the household, which is not usually known. This study presents a methodology to link source and household stored water, and explores the effects of spatial assumptions on the association between tap-to-household water quality deterioration and enteric infections in two semi-urban slums of Vellore, India. To determine a possible water source for each household sample, we paired household and tap samples collected on the same day using three spatial approaches implemented in GIS: minimum Euclidean distance; minimum network distance; and inverse network-distance weighted average. Logistic and Poisson regression models were used to determine associations between water quality deterioration and household-level characteristics, and between diarrheal cases and water quality deterioration. On average, 60% of households had higher fecal coliform concentrations in household samples than at source taps. Only the weighted average approach detected a higher risk of water quality deterioration for households that do not purify water and that have animals in the home (RR=1.50 [1.03, 2.18], p=0.033); and showed that households with water quality deterioration were more likely to report diarrheal cases (OR=3.08 [1.21, 8.18], p=0.02). Studies to assess contamination between source and household are rare due to methodological challenges and high costs associated with collecting paired samples. Our study demonstrated it is possible to derive useful spatial links between samples post hoc; and that the pairing approach affects the conclusions related to associations between enteric infections and water quality deterioration. Copyright © 2016 Elsevier GmbH. All rights reserved.

MaNGA: Target selection and Optimization

NASA Astrophysics Data System (ADS)

Wake, David

2015-01-01

The 6-year SDSS-IV MaNGA survey will measure spatially resolved spectroscopy for 10,000 nearby galaxies using the Sloan 2.5m telescope and the BOSS spectrographs with a new fiber arrangement consisting of 17 individually deployable IFUs. We present the simultaneous design of the target selection and IFU size distribution to optimally meet our targeting requirements. The requirements for the main samples were to use simple cuts in redshift and magnitude to produce an approximately flat number density of targets as a function of stellar mass, ranging from 1x109 to 1x1011 M⊙, and radial coverage to either 1.5 (Primary sample) or 2.5 (Secondary sample) effective radii, while maximizing S/N and spatial resolution. In addition we constructed a 'Color-Enhanced' sample where we required 25% of the targets to have an approximately flat number density in the color and mass plane. We show how these requirements are met using simple absolute magnitude (and color) dependent redshift cuts applied to an extended version of the NASA Sloan Atlas (NSA), how this determines the distribution of IFU sizes and the resulting properties of the MaNGA sample.

MaNGA: Target selection and Optimization

NASA Astrophysics Data System (ADS)

Wake, David

2016-01-01

The 6-year SDSS-IV MaNGA survey will measure spatially resolved spectroscopy for 10,000 nearby galaxies using the Sloan 2.5m telescope and the BOSS spectrographs with a new fiber arrangement consisting of 17 individually deployable IFUs. We present the simultaneous design of the target selection and IFU size distribution to optimally meet our targeting requirements. The requirements for the main samples were to use simple cuts in redshift and magnitude to produce an approximately flat number density of targets as a function of stellar mass, ranging from 1x109 to 1x1011 M⊙, and radial coverage to either 1.5 (Primary sample) or 2.5 (Secondary sample) effective radii, while maximizing S/N and spatial resolution. In addition we constructed a "Color-Enhanced" sample where we required 25% of the targets to have an approximately flat number density in the color and mass plane. We show how these requirements are met using simple absolute magnitude (and color) dependent redshift cuts applied to an extended version of the NASA Sloan Atlas (NSA), how this determines the distribution of IFU sizes and the resulting properties of the MaNGA sample.

Coil Compression for Accelerated Imaging with Cartesian Sampling

PubMed Central

Zhang, Tao; Pauly, John M.; Vasanawala, Shreyas S.; Lustig, Michael

2012-01-01

MRI using receiver arrays with many coil elements can provide high signal-to-noise ratio and increase parallel imaging acceleration. At the same time, the growing number of elements results in larger datasets and more computation in the reconstruction. This is of particular concern in 3D acquisitions and in iterative reconstructions. Coil compression algorithms are effective in mitigating this problem by compressing data from many channels into fewer virtual coils. In Cartesian sampling there often are fully sampled k-space dimensions. In this work, a new coil compression technique for Cartesian sampling is presented that exploits the spatially varying coil sensitivities in these non-subsampled dimensions for better compression and computation reduction. Instead of directly compressing in k-space, coil compression is performed separately for each spatial location along the fully-sampled directions, followed by an additional alignment process that guarantees the smoothness of the virtual coil sensitivities. This important step provides compatibility with autocalibrating parallel imaging techniques. Its performance is not susceptible to artifacts caused by a tight imaging fieldof-view. High quality compression of in-vivo 3D data from a 32 channel pediatric coil into 6 virtual coils is demonstrated. PMID:22488589

Invasive plants have scale-dependent effects on diversity by altering species-area relationships.

PubMed

Powell, Kristin I; Chase, Jonathan M; Knight, Tiffany M

2013-01-18

Although invasive plant species often reduce diversity, they rarely cause plant extinctions. We surveyed paired invaded and uninvaded plant communities from three biomes. We reconcile the discrepancy in diversity loss from invaders by showing that invaded communities have lower local richness but steeper species accumulation with area than that of uninvaded communities, leading to proportionately fewer species loss at broader spatial scales. We show that invaders drive scale-dependent biodiversity loss through strong neutral sampling effects on the number of individuals in a community. We also show that nonneutral species extirpations are due to a proportionately larger effect of invaders on common species, suggesting that rare species are buffered against extinction. Our study provides a synthetic perspective on the threat of invasions to biodiversity loss across spatial scales.

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.

Uncertainties in Coastal Ocean Color Products: Impacts of Spatial Sampling

NASA Technical Reports Server (NTRS)

Pahlevan, Nima; Sarkar, Sudipta; Franz, Bryan A.

2016-01-01

With increasing demands for ocean color (OC) products with improved accuracy and well characterized, per-retrieval uncertainty budgets, it is vital to decompose overall estimated errors into their primary components. Amongst various contributing elements (e.g., instrument calibration, atmospheric correction, inversion algorithms) in the uncertainty of an OC observation, less attention has been paid to uncertainties associated with spatial sampling. In this paper, we simulate MODIS (aboard both Aqua and Terra) and VIIRS OC products using 30 m resolution OC products derived from the Operational Land Imager (OLI) aboard Landsat-8, to examine impacts of spatial sampling on both cross-sensor product intercomparisons and in-situ validations of R(sub rs) products in coastal waters. Various OLI OC products representing different productivity levels and in-water spatial features were scanned for one full orbital-repeat cycle of each ocean color satellite. While some view-angle dependent differences in simulated Aqua-MODIS and VIIRS were observed, the average uncertainties (absolute) in product intercomparisons (due to differences in spatial sampling) at regional scales are found to be 1.8%, 1.9%, 2.4%, 4.3%, 2.7%, 1.8%, and 4% for the R(sub rs)(443), R(sub rs)(482), R(sub rs)(561), R(sub rs)(655), Chla, K(sub d)(482), and b(sub bp)(655) products, respectively. It is also found that, depending on in-water spatial variability and the sensor's footprint size, the errors for an in-situ validation station in coastal areas can reach as high as +/- 18%. We conclude that a) expected biases induced by the spatial sampling in product intercomparisons are mitigated when products are averaged over at least 7 km × 7 km areas, b) VIIRS observations, with improved consistency in cross-track spatial sampling, yield more precise calibration/validation statistics than that of MODIS, and c) use of a single pixel centered on in-situ coastal stations provides an optimal sampling size for validation efforts. These findings will have implications for enhancing our understanding of uncertainties in ocean color retrievals and for planning of future ocean color missions and the associated calibration/validation exercises.

Spatial Distribution and Site-Specific Spraying of Main Sucking Pests of Elm Trees.

PubMed

Karimzadeh, R; Iranipour, S

2017-06-01

Elm trees are important landscape trees and sucking insects weaken the elm trees and produce large amounts of honeydew. The main objectives of this study were to identify main honeydew-producing pests of elm trees and do site-specific spraying against these pests. To map the spatial distribution of the sucking pests in the large scale, the study area was divided into 40 × 40 m grids and one tree was chosen randomly from each grid (a total of 55 trees). These trees were sampled twice a year in 2011 and 2012. Each sample was a 30-cm branch terminal. Eight samples were taken from each tree in four cardinal directions and two canopy levels. The number of sucking insects and leaves of each sample were counted and recorded. Spatial analysis of the data was carried out using geostatistics. Kriging was used for producing prediction maps. Insecticide application was restricted to the regions with populations higher than threshold. To identify within-tree distribution of the honeydew-producing pests, six and four elm trees were chosen in 2011 and 2012 respectively, and sampled weekly. These trees were sampled as described previously. European elm scale (EES), Gossyparia spuria (Modeer) and two species of aphids were the dominant honeydew-producing pests. The results revealed that the effects of direction, canopy level and their interactions on insect populations were not statistically significant (P < 0.05). Site-specific spraying decreased the amount of insecticides used by ca. 20%, while satisfactory control of the sucking pests and honeydew excretion was obtained. Considering the environmental and economic benefits of site-specific spraying, it is worth doing more complementary works in this area.

Raman-spectroscopy-based chemical contaminant detection in milk powder

NASA Astrophysics Data System (ADS)

Dhakal, Sagar; Chao, Kuanglin; Qin, Jianwei; Kim, Moon S.

2015-05-01

Addition of edible and inedible chemical contaminants in food powders for purposes of economic benefit has become a recurring trend. In recent years, severe health issues have been reported due to consumption of food powders contaminated with chemical substances. This study examines the effect of spatial resolution used during spectral collection to select the optimal spatial resolution for detecting melamine in milk powder. Sample depth of 2mm, laser intensity of 200mw, and exposure time of 0.1s were previously determined as optimal experimental parameters for Raman imaging. Spatial resolution of 0.25mm was determined as the optimal resolution for acquiring spectral signal of melamine particles from a milk-melamine mixture sample. Using the optimal resolution of 0.25mm, sample depth of 2mm and laser intensity of 200mw obtained from previous study, spectral signal from 5 different concentration of milk-melamine mixture (1%, 0.5%, 0.1%, 0.05%, and 0.025%) were acquired to study the relationship between number of detected melamine pixels and corresponding sample concentration. The result shows that melamine concentration has a linear relation with detected number of melamine pixels with correlation coefficient of 0.99. It can be concluded that the quantitative analysis of powder mixture is dependent on many factors including physical characteristics of mixture, experimental parameters, and sample depth. The results obtained in this study are promising. We plan to apply the result obtained from this study to develop quantitative detection model for rapid screening of melamine in milk powder. This methodology can also be used for detection of other chemical contaminants in milk powders.

The timecourse of space- and object-based attentional prioritization with varying degrees of certainty

PubMed Central

Drummond, Leslie; Shomstein, Sarah

2013-01-01

The relative contributions of objects (i.e., object-based) and underlying spatial (i.e., space-based representations) to attentional prioritization and selection remain unclear. In most experimental circumstances, the two representations overlap thus their respective contributions cannot be evaluated. Here, a dynamic version of the two-rectangle paradigm allowed for a successful de-coupling of spatial and object representations. Space-based (cued spatial location), cued end of the object, and object-based (locations within the cued object) effects were sampled at several timepoints following the cue with high or low certainty as to target location. In the high uncertainty condition spatial benefits prevailed throughout most of the timecourse, as evidenced by facilitatory and inhibitory effects. Additionally, the cued end of the object, rather than a whole object, received the attentional benefit. When target location was predictable (low uncertainty manipulation), only probabilities guided selection (i.e., evidence by a benefit for the statistically biased location). These results suggest that with high spatial uncertainty, all available information present within the stimulus display is used for the purposes of attentional selection (e.g., spatial locations, cued end of the object) albeit to varying degrees and at different time points. However, as certainty increases, only spatial certainty guides selection (i.e., object ends and whole objects are filtered out). Taken together, these results further elucidate the contributing role of space- and object-representations to attentional guidance. PMID:24367302

Impact factors identification of spatial heterogeneity of herbaceous plant diversity on five southern islands of Miaodao Archipelago in North China

NASA Astrophysics Data System (ADS)

Chi, Yuan; Shi, Honghua; Wang, Xiaoli; Qin, Xuebo; Zheng, Wei; Peng, Shitao

2016-09-01

Herbaceous plants are widely distributed on islands and where they exhibit spatial heterogeneity. Accurately identifying the impact factors that drive spatial heterogeneity can reveal typical island biodiversity patterns. Five southern islands in the Miaodao Archipelago, North China were studied herein. The spatial distribution of herbaceous plant diversity on these islands was analyzed, and the impact factors and their degree of impact on spatial heterogeneity were identified using CCA ordination and ANOVA. The results reveal 114 herbaceous plant species, belonging to 94 genera from 34 families in the 50 plots sampled. The total species numbers on different islands were significantly positively correlated with island area, and the average α diversity was correlated with human activities, while the β diversity among islands was more affected by island area than mutual distances. Spatial heterogeneity within islands indicated that the diversities were generally high in areas with higher altitude, slope, total nitrogen, total carbon, and canopy density, and lower moisture content, pH, total phosphorus, total potassium, and aspect. Among the environmental factors, pH, canopy density, total K, total P, moisture content, altitude, and slope had significant gross effects, but only canopy density exhibited a significant net effect. Terrain affected diversity by restricting plantation, plantation in turn influenced soil properties and the two together affected diversity. Therefore, plantation was ultimately the fundamental driving factor for spatial heterogeneity in herbaceous plant diversity on the five islands.

The scale dependence of optical diversity in a prairie ecosystem

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Wang, R.; Stilwell, A.; Zygielbaum, A. I.; Cavender-Bares, J.; Townsend, P. A.

2015-12-01

Biodiversity loss, one of the most crucial challenges of our time, endangers ecosystem services that maintain human wellbeing. Traditional methods of measuring biodiversity require extensive and costly field sampling by biologists with extensive experience in species identification. Remote sensing can be used for such assessment based upon patterns of optical variation. This provides efficient and cost-effective means to determine ecosystem diversity at different scales and over large areas. Sampling scale has been described as a "fundamental conceptual problem" in ecology, and is an important practical consideration in both remote sensing and traditional biodiversity studies. On the one hand, with decreasing spatial and spectral resolution, the differences among different optical types may become weak or even disappear. Alternately, high spatial and/or spectral resolution may introduce redundant or contradictory information. For example, at high resolution, the variation within optical types (e.g., between leaves on a single plant canopy) may add complexity unrelated to specie richness. We studied the scale-dependence of optical diversity in a prairie ecosystem at Cedar Creek Ecosystem Science Reserve, Minnesota, USA using a variety of spectrometers from several platforms on the ground and in the air. Using the coefficient of variation (CV) of spectra as an indicator of optical diversity, we found that high richness plots generally have a higher coefficient of variation. High resolution imaging spectrometer data (1 mm pixels) showed the highest sensitivity to richness level. With decreasing spatial resolution, the difference in CV between richness levels decreased, but remained significant. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods.

Exploring the Potential of a Global Emerging Contaminant Early Warning Network through the Use of Retrospective Suspect Screening with High-Resolution Mass Spectrometry.

PubMed

Alygizakis, Nikiforos A; Samanipour, Saer; Hollender, Juliane; Ibáñez, María; Kaserzon, Sarit; Kokkali, Varvara; van Leerdam, Jan A; Mueller, Jochen F; Pijnappels, Martijn; Reid, Malcolm J; Schymanski, Emma L; Slobodnik, Jaroslav; Thomaidis, Nikolaos S; Thomas, Kevin V

2018-05-01

A key challenge in the environmental and exposure sciences is to establish experimental evidence of the role of chemical exposure in human and environmental systems. High resolution and accurate tandem mass spectrometry (HRMS) is increasingly being used for the analysis of environmental samples. One lauded benefit of HRMS is the possibility to retrospectively process data for (previously omitted) compounds that has led to the archiving of HRMS data. Archived HRMS data affords the possibility of exploiting historical data to rapidly and effectively establish the temporal and spatial occurrence of newly identified contaminants through retrospective suspect screening. We propose to establish a global emerging contaminant early warning network to rapidly assess the spatial and temporal distribution of contaminants of emerging concern in environmental samples through performing retrospective analysis on HRMS data. The effectiveness of such a network is demonstrated through a pilot study, where eight reference laboratories with available archived HRMS data retrospectively screened data acquired from aqueous environmental samples collected in 14 countries on 3 different continents. The widespread spatial occurrence of several surfactants (e.g., polyethylene glycols ( PEGs ) and C12AEO-PEGs ), transformation products of selected drugs (e.g., gabapentin-lactam, metoprolol-acid, carbamazepine-10-hydroxy, omeprazole-4-hydroxy-sulfide, and 2-benzothiazole-sulfonic-acid), and industrial chemicals (3-nitrobenzenesulfonate and bisphenol-S) was revealed. Obtaining identifications of increased reliability through retrospective suspect screening is challenging, and recommendations for dealing with issues such as broad chromatographic peaks, data acquisition, and sensitivity are provided.

Feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory.

PubMed

Wang, Haoyu; Miao, Yanwei; Zhou, Kun; Yu, Yanming; Bao, Shanglian; He, Qiang; Dai, Yongming; Xuan, Stephanie Y; Tarabishy, Bisher; Ye, Yongquan; Hu, Jiani

2010-09-01

To investigate the feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory. Two experiments were designed to investigate the feasibility of using reference image based compressed sensing (RICS) technique in DCE-MRI of the breast. The first experiment examined the capability of RICS to faithfully reconstruct uptake curves using undersampled data sets extracted from fully sampled clinical breast DCE-MRI data. An average approach and an approach using motion estimation and motion compensation (ME/MC) were implemented to obtain reference images and to evaluate their efficacy in reducing motion related effects. The second experiment, an in vitro phantom study, tested the feasibility of RICS for improving temporal resolution without degrading the spatial resolution. For the uptake-curve reconstruction experiment, there was a high correlation between uptake curves reconstructed from fully sampled data by Fourier transform and from undersampled data by RICS, indicating high similarity between them. The mean Pearson correlation coefficients for RICS with the ME/MC approach and RICS with the average approach were 0.977 +/- 0.023 and 0.953 +/- 0.031, respectively. The comparisons of final reconstruction results between RICS with the average approach and RICS with the ME/MC approach suggested that the latter was superior to the former in reducing motion related effects. For the in vitro experiment, compared to the fully sampled method, RICS improved the temporal resolution by an acceleration factor of 10 without degrading the spatial resolution. The preliminary study demonstrates the feasibility of RICS for faithfully reconstructing uptake curves and improving temporal resolution of breast DCE-MRI without degrading the spatial resolution.

Analysis of the spatio-temporal distribution of Eurygaster integriceps (Hemiptera: Scutelleridae) by using spatial analysis by distance indices and geostatistics.

PubMed

Karimzadeh, R; Hejazi, M J; Helali, H; Iranipour, S; Mohammadi, S A

2011-10-01

Eurygaster integriceps Puton (Hemiptera: Scutelleridae) is the most serious insect pest of wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) in Iran. In this study, spatio-temporal distribution of this pest was determined in wheat by using spatial analysis by distance indices (SADIE) and geostatistics. Global positioning and geographic information systems were used for spatial sampling and mapping the distribution of this insect. The study was conducted for three growing seasons in Gharamalek, an agricultural region to the west of Tabriz, Iran. Weekly sampling began when E. integriceps adults migrated to wheat fields from overwintering sites and ended when the new generation adults appeared at the end of season. The adults were sampled using 1- by 1-m quadrat and distance-walk methods. A sweep net was used for sampling the nymphs, and five 180° sweeps were considered as the sampling unit. The results of spatial analyses by using geostatistics and SADIE indicated that E. integriceps adults were clumped after migration to fields and had significant spatial dependency. The second- and third-instar nymphs showed aggregated spatial structure in the middle of growing season. At the end of the season, population distribution changed toward random or regular patterns; and fourth and fifth instars had weaker spatial structure compared with younger nymphs. In Iran, management measures for E. integriceps in wheat fields are mainly applied against overwintering adults, as well as second and third instars. Because of the aggregated distribution of these life stages, site-specific spraying of chemicals is feasible in managing E. integriceps.

TEMPORAL-SPATIAL ANALYSIS OF U.S.- MEXICO BORDER ENVIRONMENTAL FINE AND COARSE PM AIR SAMPLE EXTRACT ACTIVITY IN HUMAN BRONCHIAL EPITHELIAL CELLS

PubMed Central

Lauer, Fredine T.; Mitchell, Leah A.; Bedrick, Edward; McDonald, Jacob D.; Lee, Wen-Yee; Li, Wen-Whai; Olvera, Hector; Amaya, Maria A.; Berwick, Marianne; Gonzales, Melissa; Currey, Robert; Pingitore, Nicholas E.; Burchiel, Scott W.

2009-01-01

Particulate matter less than 10 μm (PM10) has been shown to be associated with aggravation of asthma and respiratory and cardiopulmonary morbidity. There is also great interest in the potential health effects of PM 2.5. Particulate matter (PM) varies in composition both spatially and temporally depending on the source, location and seasonal condition. El Paso County which lies in the Paso del Norte airshed is a unique location to study ambient air pollution due to three major points: the geological land formation, the relatively large population and the various sources of PM. In this study, dichotomous filters were collected from various sites in El Paso County every seven days for a period of one year. The sampling sites were both distant and near border crossings, which are near heavily populated areas with high traffic volume. Fine (PM2.5) and Coarse (PM10-2.5) PM filter samples were extracted using dichloromethane and were assessed for biologic activity and polycyclic aromatic (PAH) content. Three sets of marker genes human BEAS2B bronchial epithelial cells were utilized to assess the effects of airborne PAHs on biologic activities associated with specific biological pathways associated with airway diseases. These pathways included in inflammatory cytokine production (IL-6, IL-8), oxidative stress (HMOX-1, NQO-1, ALDH3A1, AKR1C1), and aryl hydrocarbon receptor (AhR)-dependent signaling (CYP1A1). Results demonstrated interesting temporal and spatial patterns of gene induction for all pathways, particularly those associated with oxidative stress, and significant differences in the PAHs detected in the PM10-2.5 and PM 2.5 fractions. Temporally, the greatest effects on gene induction were observed in winter months, which appeared to correlate with inversions that are common in the air basin. Spatially, the greatest gene expression increases were seen in extracts collected from the central most areas of El Paso which are also closest to highways and border crossings. PMID:19410595

Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

PubMed

Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

2014-05-01

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

[Correlativity study of the distribution of soil magnetic susceptibility and the heavy metal contents in Xi'an City].

PubMed

Chen, Xiu-Duan; Lu, Xin-Wei; Yang, Guang

2013-03-01

The magnetic susceptibility and the concentrations of Co, Cr, Cu, Pb, Sn, Sr and Ba in topsoil samples from Xi'an City were measured to study their spatial distribution and their correlation in this study. The results show that the concentrations of all measured heavy metals are higher than their background values in Cinnamon topsoil, which is the main soil type of Xi'an City. The heavy metals concentrations and the magnetic susceptibility of the studied samples display moderate variance. Co, Cr, Cu, Pb, Sn, Sr and Ba are significantly positively correlated with low-frequency magnetic susceptibility, while are significantly negatively correlated with frequency susceptibility. The spatial distribution of low-frequency magnetic susceptibility is identical with the concentrations of Pb and Cu. However, the spatial variation of frequency magnetic susceptibility is different from the concentrations of Co, Cr and Ba. The pollution assessment results show that the heavy metal pollution in topsoil of Xi'an City is moderate. The spatial contribution of the pollution load index was significantly correlated with the magnetic susceptibility of topsoil in Xi'an City. Therefore, soil magnetic susceptibility can be used as an effective monitoring means for heavy metal pollution in urban soil.

Evaluation of Satellite Remote Sensing Albedo Retrievals over the Ablation Area of the Southwestern Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Moustafa, Samiah E.; Rennermalm, Asa K.; Roman, Miguel O.; Wang, Zhuosen; Schaaf, Crystal B.; Smith, Laurence C.; Koenig, Lora S.; Erb, Angela

2017-01-01

MODerate resolution Imaging Spectroradiometer (MODIS) albedo products have been validated over spatially uniform, snow-covered areas of the Greenland ice sheet (GrIS) using the so-called single 'point-to-pixel' method. This study expands on this methodology by applying a 'multiple-point-to-pixel' method and examination of spatial autocorrelation (here using semivariogram analysis) by using in situ observations, high-resolution World- View-2 (WV-2) surface reflectances, and MODIS Collection V006 daily blue-sky albedo over a spatially heterogeneous surfaces in the lower ablation zone in southwest Greenland. Our results using 232 ground-based samples within two MODIS pixels, one being more spatial heterogeneous than the other, show little difference in accuracy among narrow and broad band albedos (except for Band 2). Within the more homogenous pixel area, in situ and MODIS albedos were very close (error varied from -4% to +7%) and within the range of ASD standard errors. The semivariogram analysis revealed that the minimum observational footprint needed for a spatially representative sample is 30 m. In contrast, over the more spatially heterogeneous surface pixel, a minimum footprint size was not quantifiable due to spatial autocorrelation, and far exceeds the effective resolution of the MODIS retrievals. Over the high spatial heterogeneity surface pixel, MODIS is lower than ground measurements by 4-7%, partly due to a known in situ undersampling of darker surfaces that often are impassable by foot (e.g., meltwater features and shadowing effects over crevasses). Despite the sampling issue, our analysis errors are very close to the stated general accuracy of the MODIS product of 5%. Thus, our study suggests that the MODIS albedo product performs well in a very heterogeneous, low-albedo, area of the ice sheet ablation zone. Furthermore, we demonstrate that single 'point-to-pixel' methods alone are insufficient in characterizing and validating the variation of surface albedo displayed in the lower ablation area. This is true because the distribution of in situ data deviations from MODIS albedo show a substantial range, with the average values for the 10th and 90th percentiles being -0.30 and 0.43 across all bands. Thus, if only single point is taken for ground validation, and is randomly selected from either distribution tails, the error would appear to be considerable. Given the need for multiple in-situ points, concurrent albedo measurements derived from existing AWSs, (low-flying vehicles (airborne or unmanned) and high-resolution imagery (WV-2)) are needed to resolve high sub-pixel variability in the ablation zone, and thus, further improve our characterization of Greenland's surface albedo.

Spatially explicit models for inference about density in unmarked or partially marked populations

USGS Publications Warehouse

Chandler, Richard B.; Royle, J. Andrew

2013-01-01

Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating that neither spatial independence nor individual recognition is needed to estimate population density—rather, spatial dependence can be informative about individual distribution and density.

Spatial Variability of the Topsoil Organic Carbon in the Moso Bamboo Forests of Southern China in Association with Soil Properties

PubMed Central

Zhang, Houxi; Zhuang, Shunyao; Qian, Haiyan; Wang, Feng; Ji, Haibao

2015-01-01

Understanding the spatial variability of soil organic carbon (SOC) must be enhanced to improve sampling design and to develop soil management strategies in terrestrial ecosystems. Moso bamboo (Phyllostachys pubescens Mazel ex Houz.) forests have a high SOC storage potential; however, they also vary significantly spatially. This study investigated the spatial variability of SOC (0-20 cm) in association with other soil properties and with spatial variables in the Moso bamboo forests of Jian’ou City, which is a typical bamboo hometown in China. 209 soil samples were collected from Moso bamboo stands and then analyzed for SOC, bulk density (BD), pH, cation exchange capacity (CEC), and gravel content (GC) based on spatial distribution. The spatial variability of SOC was then examined using geostatistics. A Kriging map was produced through ordinary interpolation and required sample numbers were calculated by classical and Kriging methods. An aggregated boosted tree (ABT) analysis was also conducted. A semivariogram analysis indicated that ln(SOC) was best fitted with an exponential model and that it exhibited moderate spatial dependence, with a nugget/sill ratio of 0.462. SOC was significantly and linearly correlated with BD (r = −0.373**), pH (r = −0.429**), GC (r = −0.163*), CEC (r = 0.263**), and elevation (r = 0.192**). Moreover, the Kriging method requires fewer samples than the classical method given an expected standard error level as per a variance analysis. ABT analysis indicated that the physicochemical variables of soil affected SOC variation more significantly than spatial variables did, thus suggesting that the SOC in Moso bamboo forests can be strongly influenced by management practices. Thus, this study provides valuable information in relation to sampling strategy and insight into the potential of adjustments in agronomic measure, such as in fertilization for Moso bamboo production. PMID:25789615

Multiplexed immunosensing and kinetics monitoring in nanofluidic devices with highly enhanced target capture efficiency

PubMed Central

Lin, Yii-Lih; Huang, Yen-Jun; Teerapanich, Pattamon; Leïchlé, Thierry

2016-01-01

Nanofluidic devices promise high reaction efficiency and fast kinetic responses due to the spatial constriction of transported biomolecules with confined molecular diffusion. However, parallel detection of multiple biomolecules, particularly proteins, in highly confined space remains challenging. This study integrates extended nanofluidics with embedded protein microarray to achieve multiplexed real-time biosensing and kinetics monitoring. Implementation of embedded standard-sized antibody microarray is attained by epoxy-silane surface modification and a room-temperature low-aspect-ratio bonding technique. An effective sample transport is achieved by electrokinetic pumping via electroosmotic flow. Through the nanoslit-based spatial confinement, the antigen-antibody binding reaction is enhanced with ∼100% efficiency and may be directly observed with fluorescence microscopy without the requirement of intermediate washing steps. The image-based data provide numerous spatially distributed reaction kinetic curves and are collectively modeled using a simple one-dimensional convection-reaction model. This study represents an integrated nanofluidic solution for real-time multiplexed immunosensing and kinetics monitoring, starting from device fabrication, protein immobilization, device bonding, sample transport, to data analysis at Péclet number less than 1. PMID:27375819

Enhanced Sensitivity for High Spatial Resolution Lipid Analysis by Negative Ion Mode MALDI Imaging Mass Spectrometry

PubMed Central

Angel, Peggi M.; Spraggins, Jeffrey M.; Baldwin, H. Scott; Caprioli, Richard

2012-01-01

We have achieved enhanced lipid imaging to a ~10 μm spatial resolution using negative ion mode matrix assisted laser desorption ionization (MALDI) imaging mass spectrometry, sublimation of 2,5-dihydroxybenzoic acid as the MALDI matrix and a sample preparation protocol that uses aqueous washes. We report on the effect of treating tissue sections by washing with volatile buffers at different pHs prior to negative ion mode lipid imaging. The results show that washing with ammonium formate, pH 6.4, or ammonium acetate, pH 6.7, significantly increases signal intensity and number of analytes recorded from adult mouse brain tissue sections. Major lipid species measured were glycerophosphoinositols, glycerophosphates, glycerolphosphoglycerols, glycerophosphoethanolamines, glycerophospho-serines, sulfatides, and gangliosides. Ion images from adult mouse brain sections that compare washed and unwashed sections are presented and show up to fivefold increases in ion intensity for washed tissue. The sample preparation protocol has been found to be applicable across numerous organ types and significantly expands the number of lipid species detectable by imaging mass spectrometry at high spatial resolution. PMID:22243218

On the ecological relevance of landscape mapping and its application in the spatial planning of very large marine protected areas.

PubMed

Hogg, Oliver T; Huvenne, Veerle A I; Griffiths, Huw J; Linse, Katrin

2018-06-01

In recent years very large marine protected areas (VLMPAs) have become the dominant form of spatial protection in the marine environment. Whilst seen as a holistic and geopolitically achievable approach to conservation, there is currently a mismatch between the size of VLMPAs, and the data available to underpin their establishment and inform on their management. Habitat mapping has increasingly been adopted as a means of addressing paucity in biological data, through use of environmental proxies to estimate species and community distribution. Small-scale studies have demonstrated environmental-biological links in marine systems. Such links, however, are rarely demonstrated across larger spatial scales in the benthic environment. As such, the utility of habitat mapping as an effective approach to the ecosystem-based management of VLMPAs remains, thus far, largely undetermined. The aim of this study was to assess the ecological relevance of broadscale landscape mapping. Specifically we test the relationship between broad-scale marine landscapes and the structure of their benthic faunal communities. We focussed our work at the sub-Antarctic island of South Georgia, site of one of the largest MPAs in the world. We demonstrate a statistically significant relationship between environmentally derived landscape mapping clusters, and the composition of presence-only species data from the region. To demonstrate this relationship required specific re-sampling of historical species occurrence data to balance biological rarity, biological cosmopolitism, range-restricted sampling and fine-scale heterogeneity between sampling stations. The relationship reveals a distinct biological signature in the faunal composition of individual landscapes, attributing ecological relevance to South Georgia's environmentally derived marine landscape map. We argue therefore, that landscape mapping represents an effective framework for ensuring representative protection of habitats in management plans. Such scientific underpinning of marine spatial planning is critical in balancing the needs of multiple stakeholders whilst maximising conservation payoff. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

The Grism Lens-Amplified Survey from Space (GLASS). II. Gas-Phase Metallicity and Radial Gradients in an Interacting System At Z ≃ 2

NASA Astrophysics Data System (ADS)

Jones, T.; Wang, X.; Schmidt, K. B.; Treu, T.; Brammer, G. B.; Bradač, M.; Dressler, A.; Henry, A. L.; Malkan, M. A.; Pentericci, L.; Trenti, M.

2015-03-01

We present spatially resolved gas-phase metallicity for a system of three galaxies at z = 1.85 detected in the Grism Lens-Amplified Survey from Space (GLASS). The combination of Hubble Space Telescope (HST’s) diffraction limit and strong gravitational lensing by the cluster MACS J0717+3745 results in a spatial resolution of ≃200-300 pc, enabling good spatial sampling despite the intrinsically small galaxy sizes. The galaxies in this system are separated by ≃50-200 kpc in projection and are likely in an early stage of interaction, evidenced by relatively high specific star formation rates. Their gas-phase metallicities are consistent with larger samples at similar redshift, star formation rate (SFR), and stellar mass. We obtain a precise measurement of the metallicity gradient for one galaxy and find a shallow slope compared to isolated galaxies at high redshift, consistent with a flattening of the gradient due to gravitational interaction. An alternative explanation for the shallow metallicity gradient and elevated SFR is rapid recycling of metal-enriched gas, but we find no evidence for enhanced gas-phase metallicities which should result from this effect. Notably, the measured stellar masses log {{M}*}/{{M}} = 7.2-9.1 probe to an order of magnitude below previous mass-metallicity studies at this redshift. The lowest mass galaxy has properties similar to those expected for Fornax at this redshift, indicating that GLASS is able to directly study the progenitors of local group dwarf galaxies on spatially resolved scales. Larger samples from the full GLASS survey will be ideal for studying the effects of feedback, and the time evolution of metallicity gradients. These initial results demonstrate the utility of HST spectroscopy combined with gravitational lensing for characterizing resolved physical properties of galaxies at high redshift.

Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river

USGS Publications Warehouse

Smith, D.R.; Rogala, J.T.; Gray, B.R.; Zigler, S.J.; Newton, T.J.

2011-01-01

Reliable estimates of abundance are needed to assess consequences of proposed habitat restoration and enhancement projects on freshwater mussels in the Upper Mississippi River (UMR). Although there is general guidance on sampling techniques for population assessment of freshwater mussels, the actual performance of sampling designs can depend critically on the population density and spatial distribution at the project site. To evaluate various sampling designs, we simulated sampling of populations, which varied in density and degree of spatial clustering. Because of logistics and costs of large river sampling and spatial clustering of freshwater mussels, we focused on adaptive and non-adaptive versions of single and two-stage sampling. The candidate designs performed similarly in terms of precision (CV) and probability of species detection for fixed sample size. Both CV and species detection were determined largely by density, spatial distribution and sample size. However, designs did differ in the rate that occupied quadrats were encountered. Occupied units had a higher probability of selection using adaptive designs than conventional designs. We used two measures of cost: sample size (i.e. number of quadrats) and distance travelled between the quadrats. Adaptive and two-stage designs tended to reduce distance between sampling units, and thus performed better when distance travelled was considered. Based on the comparisons, we provide general recommendations on the sampling designs for the freshwater mussels in the UMR, and presumably other large rivers.

An Active Learning Framework for Hyperspectral Image Classification Using Hierarchical Segmentation

NASA Technical Reports Server (NTRS)

Zhang, Zhou; Pasolli, Edoardo; Crawford, Melba M.; Tilton, James C.

2015-01-01

Augmenting spectral data with spatial information for image classification has recently gained significant attention, as classification accuracy can often be improved by extracting spatial information from neighboring pixels. In this paper, we propose a new framework in which active learning (AL) and hierarchical segmentation (HSeg) are combined for spectral-spatial classification of hyperspectral images. The spatial information is extracted from a best segmentation obtained by pruning the HSeg tree using a new supervised strategy. The best segmentation is updated at each iteration of the AL process, thus taking advantage of informative labeled samples provided by the user. The proposed strategy incorporates spatial information in two ways: 1) concatenating the extracted spatial features and the original spectral features into a stacked vector and 2) extending the training set using a self-learning-based semi-supervised learning (SSL) approach. Finally, the two strategies are combined within an AL framework. The proposed framework is validated with two benchmark hyperspectral datasets. Higher classification accuracies are obtained by the proposed framework with respect to five other state-of-the-art spectral-spatial classification approaches. Moreover, the effectiveness of the proposed pruning strategy is also demonstrated relative to the approaches based on a fixed segmentation.

Influence of the limited detector size on spatial variations of the reconstruction accuracy in holographic tomography

NASA Astrophysics Data System (ADS)

Kostencka, Julianna; Kozacki, Tomasz; Hennelly, Bryan; Sheridan, John T.

2017-06-01

Holographic tomography (HT) allows noninvasive, quantitative, 3D imaging of transparent microobjects, such as living biological cells and fiber optics elements. The technique is based on acquisition of multiple scattered fields for various sample perspectives using digital holographic microscopy. Then, the captured data is processed with one of the tomographic reconstruction algorithms, which enables 3D reconstruction of refractive index distribution. In our recent works we addressed the issue of spatially variant accuracy of the HT reconstructions, which results from the insufficient model of diffraction that is applied in the widely-used tomographic reconstruction algorithms basing on the Rytov approximation. In the present study, we continue investigating the spatially variant properties of the HT imaging, however, we are now focusing on the limited spatial size of holograms as a source of this problem. Using the Wigner distribution representation and the Ewald sphere approach, we show that the limited size of the holograms results in a decreased quality of tomographic imaging in off-center regions of the HT reconstructions. This is because the finite detector extent becomes a limiting aperture that prohibits acquisition of full information about diffracted fields coming from the out-of-focus structures of a sample. The incompleteness of the data results in an effective truncation of the tomographic transfer function for the out-of-center regions of the tomographic image. In this paper, the described effect is quantitatively characterized for three types of the tomographic systems: the configuration with 1) object rotation, 2) scanning of the illumination direction, 3) the hybrid HT solution combing both previous approaches.

Effects of Landscape Conditions and Management Practices ...

EPA Pesticide Factsheets

Lakes continue to face escalating pressures associated with land cover change and growing human populations. The U.S. EPA National Lakes Assessment, which sampled 1,028 lakes during the summer of 2007 using a probabilistic survey, was the first large scale effort to determine the condition of lakes across the country. In addition to broad trends, these data offer an abundance of new opportunities to examine biodiversity patterns, drivers of ecosystem change, and effectiveness of management practices that aim to reduce adverse effects of land cover change. Here, we use 2006 National Land Cover Data and sediment diatom samples collected from the tops of cores to examine how land cover at different spatial extents affects the habitat and diatom communities of lakes. We are examining the effects of land cover in basins, buffers in upstream networks, and buffers adjacent to 188 lakes in regions extending from the Mid-Atlantic to New England. Identifying relationships of diatom communities with land cover and physico-chemical parameters, along with generating stressor-response curves, will help with (1) developing diatom indicators responsive to anthropogenic impacts, (2) identifying how spatial locations of land cover affect lake conditions and diatoms, (3) informing future assessments and management efforts, and (4) characterizing potentially different patterns across regions and the effects of natural variation. Comparisons of study lakes to reference lake conditio

Extracting Hydrologic Understanding from the Unique Space-time Sampling of the Surface Water and Ocean Topography (SWOT) Mission

NASA Astrophysics Data System (ADS)

Nickles, C.; Zhao, Y.; Beighley, E.; Durand, M. T.; David, C. H.; Lee, H.

2017-12-01

The Surface Water and Ocean Topography (SWOT) satellite mission is jointly developed by NASA, the French space agency (CNES), with participation from the Canadian and UK space agencies to serve both the hydrology and oceanography communities. The SWOT mission will sample global surface water extents and elevations (lakes/reservoirs, rivers, estuaries, oceans, sea and land ice) at a finer spatial resolution than is currently possible enabling hydrologic discovery, model advancements and new applications that are not currently possible or likely even conceivable. Although the mission will provide global cover, analysis and interpolation of the data generated from the irregular space/time sampling represents a significant challenge. In this study, we explore the applicability of the unique space/time sampling for understanding river discharge dynamics throughout the Ohio River Basin. River network topology, SWOT sampling (i.e., orbit and identified SWOT river reaches) and spatial interpolation concepts are used to quantify the fraction of effective sampling of river reaches each day of the three-year mission. Streamflow statistics for SWOT generated river discharge time series are compared to continuous daily river discharge series. Relationships are presented to transform SWOT generated streamflow statistics to equivalent continuous daily discharge time series statistics intended to support hydrologic applications using low-flow and annual flow duration statistics.

Spatially resolved δ13C analysis using laser ablation isotope ratio mass spectrometry

NASA Astrophysics Data System (ADS)

Moran, J.; Riha, K. M.; Nims, M. K.; Linley, T. J.; Hess, N. J.; Nico, P. S.

2014-12-01

Inherent geochemical, organic matter, and microbial heterogeneity over small spatial scales can complicate studies of carbon dynamics through soils. Stable isotope analysis has a strong history of helping track substrate turnover, delineate rhizosphere activity zones, and identifying transitions in vegetation cover, but most traditional isotope approaches are limited in spatial resolution by a combination of physical separation techniques (manual dissection) and IRMS instrument sensitivity. We coupled laser ablation sampling with isotope measurement via IRMS to enable spatially resolved analysis over solid surfaces. Once a targeted sample region is ablated the resulting particulates are entrained in a helium carrier gas and passed through a combustion reactor where carbon is converted to CO2. Cyrotrapping of the resulting CO2 enables a reduction in carrier gas flow which improves overall measurement sensitivity versus traditional, high flow sample introduction. Currently we are performing sample analysis at 50 μm resolution, require 65 ng C per analysis, and achieve measurement precision consistent with other continuous flow techniques. We will discuss applications of the laser ablation IRMS (LA-IRMS) system to microbial communities and fish ecology studies to demonstrate the merits of this technique and how similar analytical approaches can be transitioned to soil systems. Preliminary efforts at analyzing soil samples will be used to highlight strengths and limitations of the LA-IRMS approach, paying particular attention to sample preparation requirements, spatial resolution, sample analysis time, and the types of questions most conducive to analysis via LA-IRMS.

Gender Differences in Spatial Ability: "Relationship to Spatial Experience among Chinese Gifted Students in Hong Kong"

ERIC Educational Resources Information Center

Chan, David W.

2007-01-01

Spatial ability based on measures of mental rotation, and spatial experience based on self-reported participation in visual-arts as well as spatial-orientation activities were assessed in a sample of 337 Chinese, gifted students. Consistent with past findings for the general population, there were gender differences in spatial ability favoring…

Use of LANDSAT imagery for wildlife habitat mapping in northeast and eastcentral Alaska

NASA Technical Reports Server (NTRS)

Lent, P. C. (Principal Investigator)

1976-01-01

The author has identified the following significant results. There is strong indication that spatially rare feature classes may be missed in clustering classifications based on 2% random sampling. Therefore, it seems advisable to augment random sampling for cluster analysis with directed sampling of any spatially rare features which are relevant to the analysis.

Effects of climate and sewer condition on virus transport to groundwater

USDA-ARS?s Scientific Manuscript database

Pathogen contamination from leaky sanitary sewers poses a threat to groundwater quality in urban areas, yet the spatial and temporal dimensions of this contamination are not well understood. In this study, 16 monitoring wells and six municipal wells were repeatedly sampled for human enteric viruses....

Acousto-Optic Tunable Filter Hyperspectral Microscope Imaging Method for Characterizing Spectra from Foodborne Pathogens.

USDA-ARS?s Scientific Manuscript database

Hyperspectral microscope imaging (HMI) method, which provides both spatial and spectral characteristics of samples, can be effective for foodborne pathogen detection. The acousto-optic tunable filter (AOTF)-based HMI method can be used to characterize spectral properties of biofilms formed by Salmon...

Two sampling methods yield distinct microbial signatures in the nasopharynges of asthmatic children.

PubMed

Pérez-Losada, Marcos; Crandall, Keith A; Freishtat, Robert J

2016-06-16

The nasopharynx is a reservoir for pathogens associated with respiratory illnesses, such as asthma. Next-generation sequencing (NGS) has been used to characterize the nasopharyngeal microbiome during health and disease. Most studies so far have surveyed the nasopharynx as a whole; however, less is known about spatial variation (biogeography) in nasal microenvironments and how sampling techniques may capture that microbial diversity. We used targeted 16S rRNA MiSeq sequencing and two different sampling strategies [nasal washes (NW) and nasal brushes (NB)] to characterize the nasopharyngeal microbiota in 30 asthmatic children. Nasal brushing is more abrasive than nasal washing and targeted the inner portion of the inferior turbinate. This region is expected to be different from other nasal microenvironments. Nasal washing is not spatially specific. Our 30 × 2 nasal microbiomes generated 1,474,497 sequences, from which we identified an average of 157 and 186 OTUs per sample in the NW and NB groups, respectively. Microbiotas from NB showed significantly higher alpha-diversity than microbiotas from NW. Similarly, both nasal microbiotas were distinct from each other (PCoA) and significantly differed in their community composition and abundance in at least 9 genera (effective size ≥1 %). Nasopharyngeal microenvironments in asthmatic children contain microbiotas with different diversity and structure. Nasal washes and brushes capture that diversity differently. Future microbial studies of the nasopharynx need to be aware of potential spatial variation (biogeography).

Wavefront sensor based on the Talbot effect with the precorrected holographic grating.

PubMed

Podanchuk, Dmytro; Kurashov, Vitalij; Goloborodko, Andrey; Dan'ko, Volodymyr; Kotov, Myhaylo; Goloborodko, Natalya

2012-04-01

A holographic wavefront sensor based on the Talbot effect is proposed. Optical wavefronts are measured by sampling the light amplitude distribution with a two-dimensional (2D) precorrected holographic grating. The factors that allow changing an angular measurement range and a spatial resolution of the sensor are discussed. A comparative analysis with the Shack-Hartmann sensor is illustrated with some experimental results.

Near-Field Scanning Optical Microscopy of Soft, Biological, or Rough Objects in Aqueous Environment: Challenges and some Remedies to Circumvent

NASA Technical Reports Server (NTRS)

Vikram, C. S.; Witherow, W. K.

1999-01-01

Near-field scanning optical microscopy is an established technique for sub-wavelength spatial resolution in imaging, spectroscopy, material science, surface chemistry, polarimetry, etc. A significant amount of confidence has been established for thin hard specimens in air. However when soft, biological, rough, in aqueous environment object, or a combination is involved, the progress has been slow. The tip-sample mechanical interaction, heat effects to sample, drag effects to the probe, difficulty in controlling tip-sample separation in case of rough objects, light scattering from sample thickness, etc. create problems. Although these problems are not even fully understood, there have been attempts to study them with the aim of performing reliable operations. In this review we describe these attempts. Starting with general problems encountered, various effects like polarization, thermal, and media are covered. The roles of independent tip-sample distance control tools in the relevant situations are then described. Finally progress in fluid cell aspect has been summarized.

Sampling scales define occupancy and underlying occupancy-abundance relationships in animals.

PubMed

Steenweg, Robin; Hebblewhite, Mark; Whittington, Jesse; Lukacs, Paul; McKelvey, Kevin

2018-01-01

Occupancy-abundance (OA) relationships are a foundational ecological phenomenon and field of study, and occupancy models are increasingly used to track population trends and understand ecological interactions. However, these two fields of ecological inquiry remain largely isolated, despite growing appreciation of the importance of integration. For example, using occupancy models to infer trends in abundance is predicated on positive OA relationships. Many occupancy studies collect data that violate geographical closure assumptions due to the choice of sampling scales and application to mobile organisms, which may change how occupancy and abundance are related. Little research, however, has explored how different occupancy sampling designs affect OA relationships. We develop a conceptual framework for understanding how sampling scales affect the definition of occupancy for mobile organisms, which drives OA relationships. We explore how spatial and temporal sampling scales, and the choice of sampling unit (areal vs. point sampling), affect OA relationships. We develop predictions using simulations, and test them using empirical occupancy data from remote cameras on 11 medium-large mammals. Surprisingly, our simulations demonstrate that when using point sampling, OA relationships are unaffected by spatial sampling grain (i.e., cell size). In contrast, when using areal sampling (e.g., species atlas data), OA relationships are affected by spatial grain. Furthermore, OA relationships are also affected by temporal sampling scales, where the curvature of the OA relationship increases with temporal sampling duration. Our empirical results support these predictions, showing that at any given abundance, the spatial grain of point sampling does not affect occupancy estimates, but longer surveys do increase occupancy estimates. For rare species (low occupancy), estimates of occupancy will quickly increase with longer surveys, even while abundance remains constant. Our results also clearly demonstrate that occupancy for mobile species without geographical closure is not true occupancy. The independence of occupancy estimates from spatial sampling grain depends on the sampling unit. Point-sampling surveys can, however, provide unbiased estimates of occupancy for multiple species simultaneously, irrespective of home-range size. The use of occupancy for trend monitoring needs to explicitly articulate how the chosen sampling scales define occupancy and affect the occupancy-abundance relationship. © 2017 by the Ecological Society of America.

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.

Aggregating pixel-level basal area predictions derived from LiDAR data to industrial forest stands in North-Central Idaho

Treesearch

Andrew T. Hudak; Jeffrey S. Evans; Nicholas L. Crookston; Michael J. Falkowski; Brant K. Steigers; Rob Taylor; Halli Hemingway

2008-01-01

Stand exams are the principal means by which timber companies monitor and manage their forested lands. Airborne LiDAR surveys sample forest stands at much finer spatial resolution and broader spatial extent than is practical on the ground. In this paper, we developed models that leverage spatially intensive and extensive LiDAR data and a stratified random sample of...

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.

Analysis of axial spatial resolution in a variable resolution x-ray cone beam CT (VRX-CBCT) system

NASA Astrophysics Data System (ADS)

Dahi, Bahram; Keyes, Gary S.; Rendon, David A.; DiBianca, Frank A.

2008-03-01

The Variable Resolution X-ray (VRX) technique has been successfully used in a Cone-Beam CT (CBCT) system to increase the spatial resolution of CT images in the transverse plane. This was achieved by tilting the Flat Panel Detector (FPD) to smaller vrx y angles in a VRX Cone Beam CT (VRX-CBCT) system. In this paper, the effect on the axial spatial resolution of CT images created by the VRX-CBCT system is examined at different vrx x angles, where vrx x is the tilting angle of the FPD about its x-axis. An amorphous silicon FPD with a CsI scintillator is coupled with a micro-focus x-ray tube to form a CBCT. The FPD is installed on a rotating frame that allows rotation of up to 90° about x and y axes of the FPD. There is no rotation about the z-axis (i.e. normal to the imaging surface). Tilting the FPD about its x-axis (i.e. decreasing the vrx x angle) reduces both the width of the line-spread function and the sampling distance by a factor of sin vrx x, thereby increasing the theoretical detector pre-sampling spatial resolution proportionately. This results in thinner CT slices that in turn help increase the axial spatial resolution of the CT images. An in-house phantom is used to measure the MTF of the reconstructed CT images at different vrx x angles.

High spatial variation in population size and symbiotic performance of Rhizobium leguminosarum bv. trifolii with white clover in New Zealand pasture soils.

PubMed

Wakelin, Steven; Tillard, Guyléne; van Ham, Robert; Ballard, Ross; Farquharson, Elizabeth; Gerard, Emily; Geurts, Rene; Brown, Matthew; Ridgway, Hayley; O'Callaghan, Maureen

2018-01-01

Biological nitrogen fixation through the legume-rhizobia symbiosis is important for sustainable pastoral production. In New Zealand, the most widespread and valuable symbiosis occurs between white clover (Trifolium repens L.) and Rhizobium leguminosarum bv. trifolii (Rlt). As variation in the population size (determined by most probable number assays; MPN) and effectiveness of N-fixation (symbiotic potential; SP) of Rlt in soils may affect white clover performance, the extent in variation in these properties was examined at three different spatial scales: (1) From 26 sites across New Zealand, (2) at farm-wide scale, and (3) within single fields. Overall, Rlt populations ranged from 95 to >1 x 108 per g soil, with variation similar at the three spatial scales assessed. For almost all samples, there was no relationship between rhizobia population size and ability of the population to fix N during legume symbiosis (SP). When compared with the commercial inoculant strain, the SP of soils ranged between 14 to 143% efficacy. The N-fixing ability of rhizobia populations varied more between samples collected from within a single hill country field (0.8 ha) than between 26 samples collected from diverse locations across New Zealand. Correlations between SP and calcium and aluminium content were found in all sites, except within a dairy farm field. Given the general lack of association between SP and MPN, and high spatial variability of SP at single field scale, provision of advice for treating legume seed with rhizobia based on field-average MPN counts needs to be carefully considered.

High spatial variation in population size and symbiotic performance of Rhizobium leguminosarum bv. trifolii with white clover in New Zealand pasture soils

PubMed Central

Tillard, Guyléne; van Ham, Robert; Ballard, Ross; Farquharson, Elizabeth; Gerard, Emily; Geurts, Rene; Brown, Matthew; Ridgway, Hayley; O’Callaghan, Maureen

2018-01-01

Biological nitrogen fixation through the legume-rhizobia symbiosis is important for sustainable pastoral production. In New Zealand, the most widespread and valuable symbiosis occurs between white clover (Trifolium repens L.) and Rhizobium leguminosarum bv. trifolii (Rlt). As variation in the population size (determined by most probable number assays; MPN) and effectiveness of N-fixation (symbiotic potential; SP) of Rlt in soils may affect white clover performance, the extent in variation in these properties was examined at three different spatial scales: (1) From 26 sites across New Zealand, (2) at farm-wide scale, and (3) within single fields. Overall, Rlt populations ranged from 95 to >1 x 108 per g soil, with variation similar at the three spatial scales assessed. For almost all samples, there was no relationship between rhizobia population size and ability of the population to fix N during legume symbiosis (SP). When compared with the commercial inoculant strain, the SP of soils ranged between 14 to 143% efficacy. The N-fixing ability of rhizobia populations varied more between samples collected from within a single hill country field (0.8 ha) than between 26 samples collected from diverse locations across New Zealand. Correlations between SP and calcium and aluminium content were found in all sites, except within a dairy farm field. Given the general lack of association between SP and MPN, and high spatial variability of SP at single field scale, provision of advice for treating legume seed with rhizobia based on field-average MPN counts needs to be carefully considered. PMID:29489845

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression

PubMed Central

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson’s statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran’s index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China’s regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test. PMID:26800271

Spatially balanced survey designs for natural resources

EPA Science Inventory

Ecological resource monitoring programs typically require the use of a probability survey design to select locations or entities to be physically sampled in the field. The ecological resource of interest, the target population, occurs over a spatial domain and the sample selecte...

Time-Lapse Electrical Geophysical Monitoring of Amendment-Based Biostimulation.

PubMed

Johnson, Timothy C; Versteeg, Roelof J; Day-Lewis, Frederick D; Major, William; Lane, John W

2015-01-01

Biostimulation is increasingly used to accelerate microbial remediation of recalcitrant groundwater contaminants. Effective application of biostimulation requires successful emplacement of amendment in the contaminant target zone. Verification of remediation performance requires postemplacement assessment and contaminant monitoring. Sampling-based approaches are expensive and provide low-density spatial and temporal information. Time-lapse electrical resistivity tomography (ERT) is an effective geophysical method for determining temporal changes in subsurface electrical conductivity. Because remedial amendments and biostimulation-related biogeochemical processes often change subsurface electrical conductivity, ERT can complement and enhance sampling-based approaches for assessing emplacement and monitoring biostimulation-based remediation. Field studies demonstrating the ability of time-lapse ERT to monitor amendment emplacement and behavior were performed during a biostimulation remediation effort conducted at the Department of Defense Reutilization and Marketing Office (DRMO) Yard, in Brandywine, Maryland, United States. Geochemical fluid sampling was used to calibrate a petrophysical relation in order to predict groundwater indicators of amendment distribution. The petrophysical relations were field validated by comparing predictions to sequestered fluid sample results, thus demonstrating the potential of electrical geophysics for quantitative assessment of amendment-related geochemical properties. Crosshole radar zero-offset profile and borehole geophysical logging were also performed to augment the data set and validate interpretation. In addition to delineating amendment transport in the first 10 months after emplacement, the time-lapse ERT results show later changes in bulk electrical properties interpreted as mineral precipitation. Results support the use of more cost-effective surface-based ERT in conjunction with limited field sampling to improve spatial and temporal monitoring of amendment emplacement and remediation performance. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Geometrical superresolved imaging using nonperiodic spatial masking.

PubMed

Borkowski, Amikam; Zalevsky, Zeev; Javidi, Bahram

2009-03-01

The resolution of every imaging system is limited either by the F-number of its optics or by the geometry of its detection array. The geometrical limitation is caused by lack of spatial sampling points as well as by the shape of every sampling pixel that generates spectral low-pass filtering. We present a novel approach to overcome the low-pass filtering that is due to the shape of the sampling pixels. The approach combines special algorithms together with spatial masking placed in the intermediate image plane and eventually allows geometrical superresolved imaging without relation to the actual shape of the pixels.

Truck crash severity in New York city: An investigation of the spatial and the time of day effects.

PubMed

Zou, Wei; Wang, Xiaokun; Zhang, Dapeng

2017-02-01

This paper investigates the differences between single-vehicle and multi-vehicle truck crashes in New York City. The random parameter models take into account the time of day effect, the heterogeneous truck weight effect and other influencing factors such as crash characteristics, driver and vehicle characteristics, built environment factors and traffic volume attributes. Based on the results from the co-location quotient analysis, a spatial generalized ordered probit model is further developed to investigate the potential spatial dependency among single-vehicle truck crashes. The sample is drawn from the state maintained incident data, the publicly available Smart Location Data, and the BEST Practices Model (BPM) data from 2008 to 2012. The result shows that there exists a substantial difference between factors influencing single-vehicle and multi-vehicle truck crash severity. It also suggests that heterogeneity does exist in the truck weight, and it behaves differently in single-vehicle and multi-vehicle truck crashes. Furthermore, individual truck crashes are proved to be spatially dependent events for both single and multi-vehicle crashes. Last but not least, significant time of day effects were found for PM and night time slots, crashes that occurred in the afternoons and at nights were less severe in single-vehicle crashes, but more severe in multi-vehicle crashes. Copyright © 2016. Published by Elsevier Ltd.

A Scalable Field Study Protocol and Rationale for Passive Ambient Air Sampling: A Spatial Phytosampling for Leaf Data Collection

PubMed Central

Oyana, Tonny J.; Lomnicki, Slawomir M.; Guo, Chuqi; Cormier, Stephania A.

2018-01-01

Stable, bioreactive, radicals known as environmentally persistent free radicals (EPFRs) have been found to exist on the surface of airborne PM2.5. These EPFRs have been found to form during many combustion processes, are present in vehicular exhaust, and persist in the environment for weeks and biological systems for up to 12 h. To measure EPFRs in PM samples, high volume samplers are required and measurements are less representative of community exposure; therefore, we developed a novel spatial phytosampling methodology to study the spatial patterns of EPFR concentrations using plants. Leaf samples for laboratory PM analysis were collected from 188 randomly drawn sampling sites within a 500-m buffer zone of pollution sources across a sampling grid measuring 32.9 × 28.4 km in Memphis, Tennessee. PM was isolated from the intact leaves and size fractionated, and EPFRs on PM quantified by electron paramagnetic resonance spectroscopy. The radical concentration was found to positively correlate with the EPFR g-value, thus indicating cumulative content of oxygen centered radicals in PM with higher EPFR load. Our spatial phytosampling approach reveals spatial variations and potential “hotspots” risk due to EPFR exposure across Memphis and provides valuable insights for identifying exposure and demographic differences for health studies. PMID:28805054

Spatial analysis of the distribution of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) and losses in maize crop productivity using geostatistics.

PubMed

Farias, Paulo R S; Barbosa, José C; Busoli, Antonio C; Overal, William L; Miranda, Vicente S; Ribeiro, Susane M

2008-01-01

The fall armyworm, Spodoptera frugiperda (J.E. Smith), is one of the chief pests of maize in the Americas. The study of its spatial distribution is fundamental for designing correct control strategies, improving sampling methods, determining actual and potential crop losses, and adopting precise agricultural techniques. In São Paulo state, Brazil, a maize field was sampled at weekly intervals, from germination through harvest, for caterpillar densities, using quadrates. In each of 200 quadrates, 10 plants were sampled per week. Harvest weights were obtained in the field for each quadrate, and ear diameters and lengths were also sampled (15 ears per quadrate) and used to estimate potential productivity of the quadrate. Geostatistical analyses of caterpillar densities showed greatest ranges for small caterpillars when semivariograms were adjusted for a spherical model that showed greatest fit. As the caterpillars developed in the field, their spatial distribution became increasingly random, as shown by a model adjusted to a straight line, indicating a lack of spatial dependence among samples. Harvest weight and ear length followed the spherical model, indicating the existence of spatial variability of the production parameters in the maize field. Geostatistics shows promise for the application of precise methods in the integrated control of pests.

Generalized estimators of avian abundance from count survey data

USGS Publications Warehouse

Royle, J. Andrew

2004-01-01

I consider modeling avian abundance from spatially referenced bird count data collected according to common protocols such as capture?recapture, multiple observer, removal sampling and simple point counts. Small sample sizes and large numbers of parameters have motivated many analyses that disregard the spatial indexing of the data, and thus do not provide an adequate treatment of spatial structure. I describe a general framework for modeling spatially replicated data that regards local abundance as a random process, motivated by the view that the set of spatially referenced local populations (at the sample locations) constitute a metapopulation. Under this view, attention can be focused on developing a model for the variation in local abundance independent of the sampling protocol being considered. The metapopulation model structure, when combined with the data generating model, define a simple hierarchical model that can be analyzed using conventional methods. The proposed modeling framework is completely general in the sense that broad classes of metapopulation models may be considered, site level covariates on detection and abundance may be considered, and estimates of abundance and related quantities may be obtained for sample locations, groups of locations, unsampled locations. Two brief examples are given, the first involving simple point counts, and the second based on temporary removal counts. Extension of these models to open systems is briefly discussed.

A Scalable Field Study Protocol and Rationale for Passive Ambient Air Sampling: A Spatial Phytosampling for Leaf Data Collection.

PubMed

Oyana, Tonny J; Lomnicki, Slawomir M; Guo, Chuqi; Cormier, Stephania A

2017-09-19

Stable, bioreactive, radicals known as environmentally persistent free radicals (EPFRs) have been found to exist on the surface of airborne PM 2.5 . These EPFRs have been found to form during many combustion processes, are present in vehicular exhaust, and persist in the environment for weeks and biological systems for up to 12 h. To measure EPFRs in PM samples, high volume samplers are required and measurements are less representative of community exposure; therefore, we developed a novel spatial phytosampling methodology to study the spatial patterns of EPFR concentrations using plants. Leaf samples for laboratory PM analysis were collected from 188 randomly drawn sampling sites within a 500-m buffer zone of pollution sources across a sampling grid measuring 32.9 × 28.4 km in Memphis, Tennessee. PM was isolated from the intact leaves and size fractionated, and EPFRs on PM quantified by electron paramagnetic resonance spectroscopy. The radical concentration was found to positively correlate with the EPFR g-value, thus indicating cumulative content of oxygen centered radicals in PM with higher EPFR load. Our spatial phytosampling approach reveals spatial variations and potential "hotspots" risk due to EPFR exposure across Memphis and provides valuable insights for identifying exposure and demographic differences for health studies.

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data

PubMed Central

Broekhuis, Femke; Gopalaswamy, Arjun M.

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed ‘hotspots’ of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species. PMID:27135614

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data.

PubMed

Broekhuis, Femke; Gopalaswamy, Arjun M

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

Spatial patterns of throughfall isotopic composition at the event and seasonal timescales

NASA Astrophysics Data System (ADS)

Allen, Scott T.; Keim, Richard F.; McDonnell, Jeffrey J.

2015-03-01

Spatial variability of throughfall isotopic composition in forests is indicative of complex processes occurring in the canopy and remains insufficiently understood to properly characterize precipitation inputs to the catchment water balance. Here we investigate variability of throughfall isotopic composition with the objectives: (1) to quantify the spatial variability in event-scale samples, (2) to determine if there are persistent controls over the variability and how these affect variability of seasonally accumulated throughfall, and (3) to analyze the distribution of measured throughfall isotopic composition associated with varying sampling regimes. We measured throughfall over two, three-month periods in western Oregon, USA under a Douglas-fir canopy. The mean spatial range of δ18O for each event was 1.6‰ and 1.2‰ through Fall 2009 (11 events) and Spring 2010 (7 events), respectively. However, the spatial pattern of isotopic composition was not temporally stable causing season-total throughfall to be less variable than event throughfall (1.0‰; range of cumulative δ18O for Fall 2009). Isotopic composition was not spatially autocorrelated and not explained by location relative to tree stems. Sampling error analysis for both field measurements and Monte-Carlo simulated datasets representing different sampling schemes revealed the standard deviation of differences from the true mean as high as 0.45‰ (δ18O) and 1.29‰ (d-excess). The magnitude of this isotopic variation suggests that small sample sizes are a source of substantial experimental error.

Device for high spatial resolution chemical analysis of a sample and method of high spatial resolution chemical analysis

DOEpatents

Van Berkel, Gary J.

2015-10-06

A system and method for analyzing a chemical composition of a specimen are described. The system can include at least one pin; a sampling device configured to contact a liquid with a specimen on the at least one pin to form a testing solution; and a stepper mechanism configured to move the at least one pin and the sampling device relative to one another. The system can also include an analytical instrument for determining a chemical composition of the specimen from the testing solution. In particular, the systems and methods described herein enable chemical analysis of specimens, such as tissue, to be evaluated in a manner that the spatial-resolution is limited by the size of the pins used to obtain tissue samples, not the size of the sampling device used to solubilize the samples coupled to the pins.

Clinal patterns of human Y chromosomal diversity in continental Italy and Greece are dominated by drift and founder effects.

PubMed

Di Giacomo, F; Luca, F; Anagnou, N; Ciavarella, G; Corbo, R M; Cresta, M; Cucci, F; Di Stasi, L; Agostiano, V; Giparaki, M; Loutradis, A; Mammi', C; Michalodimitrakis, E N; Papola, F; Pedicini, G; Plata, E; Terrenato, L; Tofanelli, S; Malaspina, P; Novelletto, A

2003-09-01

We explored the spatial distribution of human Y chromosomal diversity on a microgeographic scale, by typing 30 population samples from closely spaced locations in Italy and Greece for 9 haplogroups and their internal microsatellite variation. We confirm a significant difference in the composition of the Y chromosomal gene pools of the two countries. However, within each country, heterogeneity is not organized along the lines of clinal variation deduced from studies on larger spatial scales. Microsatellite data indicate that local increases of haplogroup frequencies can be often explained by a limited number of founders. We conclude that local founder or drift effects are the main determinants in shaping the microgeographic Y chromosomal diversity.

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

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

Yang, Yongchao; Dorn, Charles; Mancini, Tyler

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

DOE PAGES

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; ...

2016-12-05

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

Integration of electromagnetic induction sensor data in soil sampling scheme optimization using simulated annealing.

PubMed

Barca, E; Castrignanò, A; Buttafuoco, G; De Benedetto, D; Passarella, G

2015-07-01

Soil survey is generally time-consuming, labor-intensive, and costly. Optimization of sampling scheme allows one to reduce the number of sampling points without decreasing or even increasing the accuracy of investigated attribute. Maps of bulk soil electrical conductivity (EC a ) recorded with electromagnetic induction (EMI) sensors could be effectively used to direct soil sampling design for assessing spatial variability of soil moisture. A protocol, using a field-scale bulk EC a survey, has been applied in an agricultural field in Apulia region (southeastern Italy). Spatial simulated annealing was used as a method to optimize spatial soil sampling scheme taking into account sampling constraints, field boundaries, and preliminary observations. Three optimization criteria were used. the first criterion (minimization of mean of the shortest distances, MMSD) optimizes the spreading of the point observations over the entire field by minimizing the expectation of the distance between an arbitrarily chosen point and its nearest observation; the second criterion (minimization of weighted mean of the shortest distances, MWMSD) is a weighted version of the MMSD, which uses the digital gradient of the grid EC a data as weighting function; and the third criterion (mean of average ordinary kriging variance, MAOKV) minimizes mean kriging estimation variance of the target variable. The last criterion utilizes the variogram model of soil water content estimated in a previous trial. The procedures, or a combination of them, were tested and compared in a real case. Simulated annealing was implemented by the software MSANOS able to define or redesign any sampling scheme by increasing or decreasing the original sampling locations. The output consists of the computed sampling scheme, the convergence time, and the cooling law, which can be an invaluable support to the process of sampling design. The proposed approach has found the optimal solution in a reasonable computation time. The use of bulk EC a gradient as an exhaustive variable, known at any node of an interpolation grid, has allowed the optimization of the sampling scheme, distinguishing among areas with different priority levels.

Detecting spatial structures in throughfall data: The effect of extent, sample size, sampling design, and variogram estimation method

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-09-01

In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous throughfall studies relied on method-of-moments variogram estimation and sample sizes ≪200, currently available data are prone to large uncertainties.

An examination of gender bias on the eighth-grade MEAP science test as it relates to the Hunter Gatherer Theory of Spatial Sex Differences

NASA Astrophysics Data System (ADS)

Armstrong-Hall, Judy Gail

The purpose of this study was to apply the Hunter-Gatherer Theory of sex spatial skills to responses to individual questions by eighth grade students on the Science component of the Michigan Educational Assessment Program (MEAP) to determine if sex bias was inherent in the test. The Hunter-Gatherer Theory on Spatial Sex Differences, an original theory, that suggested a spatial dimorphism concept with female spatial skill of pattern recall of unconnected items and male spatial skills requiring mental movement. This is the first attempt to apply the Hunter-Gatherer Theory on Spatial Sex Differences to a standardized test. An overall hypothesis suggested that the Hunter-Gatherer Theory of Spatial Sex Differences could predict that males would perform better on problems involving mental movement and females would do better on problems involving the pattern recall of unconnected items. Responses to questions on the 1994-95 MEAP requiring the use of male spatial skills and female spatial skills were analyzed for 5,155 eighth grade students. A panel composed of five educators and a theory developer determined which test items involved the use of male and female spatial skills. A MANOVA, using a random sample of 20% of the 5,155 students to compare male and female correct scores, was statistically significant, with males having higher scores on male spatial skills items and females having higher scores on female spatial skills items. Pearson product moment correlation analyses produced a positive correlation for both male and female performance on both types of spatial skills. The Hunter-Gatherer Theory of Spatial Sex Differences appears to be able to predict that males could perform better on the problems involving mental movement and females could perform better on problems involving the pattern recall of unconnected items. Recommendations for further research included: examination of male/female spatial skill differences at early elementary and high school levels to determine impact of gender on difficulties in solving spatial problems; investigation of the relationship between dominant female spatial skills for students diagnosed with ADHD; study effects of teaching male spatial skills to female students starting in early elementary school to determine the effect on standardized testing.

Spectral refractive index assessment of turbid samples by combining spatial frequency near-infrared spectroscopy with Kramers-Kronig analysis

NASA Astrophysics Data System (ADS)

Meitav, Omri; Shaul, Oren; Abookasis, David

2018-03-01

A practical algorithm for estimating the wavelength-dependent refractive index (RI) of a turbid sample in the spatial frequency domain with the aid of Kramers-Kronig (KK) relations is presented. In it, phase-shifted sinusoidal patterns (structured illumination) are serially projected at a high spatial frequency onto the sample surface (mouse scalp) at different near-infrared wavelengths while a camera mounted normally to the sample surface captures the reflected diffuse light. In the offline analysis pipeline, recorded images at each wavelength are converted to spatial absorption maps by logarithmic function, and once the absorption coefficient information is obtained, the imaginary part (k) of the complex RI (CRI), based on Maxell's equations, can be calculated. Using the data represented by k, the real part of the CRI (n) is then resolved by KK analysis. The wavelength dependence of n ( λ ) is then fitted separately using four standard dispersion models: Cornu, Cauchy, Conrady, and Sellmeier. In addition, three-dimensional surface-profile distribution of n is provided based on phase profilometry principles and a phase-unwrapping-based phase-derivative-variance algorithm. Experimental results demonstrate the capability of the proposed idea for sample's determination of a biological sample's RI value.

Optical pendulum effect in one-dimensional diffraction-thick porous silicon based photonic crystals

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

Novikov, V. B., E-mail: vb.novikov@physics.msu.ru; Svyakhovskiy, S. E.; Maydykovskiy, A. I.

We present the realization of the multiperiodic optical pendulum effect in 1D porous silicon photonic crystals (PhCs) under dynamical Bragg diffraction in the Laue scheme. The diffraction-thick PhC contained 360 spatial periods with a large variation of the refractive index of adjacent layers of 0.4. The experiments reveal switching of the light leaving the PhC between the two spatial directions, which correspond to Laue diffraction maxima, as the fundamental wavelength or polarization of the incident light is varied. A similar effect can be achieved when the temperature of the sample or the intensity of the additional laser beam illuminating themore » crystal are changed. We show that in our PhC structures, the spectral period of the pendulum effect is down to 5 nm, while the thermal period is about 10 °C.« less

The micron- to kilometer-scale Moon: linking samples to orbital observations, Apollo to LRO

NASA Astrophysics Data System (ADS)

Crites, S.; Lucey, P. G.; Taylor, J.; Martel, L.; Sun, L.; Honniball, C.; Lemelin, M.

2017-12-01

The Apollo missions have shaped the field of lunar science and our understanding of the Moon, from global-scale revelations like the magma ocean hypothesis, to providing ground truth for compositional remote sensing and absolute ages to anchor cratering chronologies. While lunar meteorite samples can provide a global- to regional-level view of the Moon, samples returned from known locations are needed to directly link orbital-scale observations with laboratory measurements-a link that can be brought to full fruition with today's extremely high spatial resolution observations from Lunar Reconnaissance Orbiter and other recent missions. Korotev et al. (2005) described a scenario of the Moon without Apollo to speculate about our understanding of the Moon if our data were confined to lunar meteorites and remote sensing. I will review some of the major points discussed by Korotev et al. (2005), and focus on some of the ways in which spectroscopic remote sensing in particular has benefited from the Apollo samples. For example, could the causes and effects of lunar-style space weathering have been unraveled without the Apollo samples? What would be the limitations on remote sensing compositional measurements that rely on Apollo samples for calibration and validation? And what new opportunities to bring together orbital and sample analyses now exist, in light of today's high spatial and spectral resolution remote sensing datasets?

Electron Paramagnetic Resonance Imaging of the Spatial Distribution of Free Radicals in PMR-15 Polyimide Resins

NASA Technical Reports Server (NTRS)

Ahn, Myong K.; Eaton, Sandra S.; Eaton, Gareth R.; Meador, Mary Ann B.

1997-01-01

Prior studies have shown that free radicals generated by heating polyimides above 300 C are stable at room temperature and are involved in thermo-oxidative degradation in the presence of oxygen gas. Electron paramagnetic resonance imaging (EPRI) is a technique to determine the spatial distribution of free radicals. X-band (9.5 GHz) EPR images of PMR-15 polyimide were obtained with a spatial resolution of approximately 0.18 mm along a 2-mm dimension of the sample. In a polyimide sample that was not thermocycled, the radical distribution was uniform along the 2-mm dimension of the sample. For a polyimide sample that was exposed to thermocycling in air for 300 1-h cycles at 335 C, one-dimensional EPRI showed a higher concentration of free radicals in the surface layers than in the bulk sample. A spectral-spatial two-dimensional image showed that the EPR lineshape of the surface layer remained the same as that of the bulk. These EPRI results suggest that the thermo-oxidative degradation of PMR-15 resin involves free radicals present in the oxygen-rich surface layer.

Electron Paramagnetic Resonance Imaging of the Spatial Distribution of Free Radicals in PMR-15 Polyimide Resins

NASA Technical Reports Server (NTRS)

Ahn, Myong K.; Eaton, Sandra S.; Eaton, Gareth R.; Meador, Mary Ann B.

1997-01-01

Prior studies have shown that free radicals generated by heating polyimides above 300 C are stable at room temperature and are involved in thermo-oxidative degradation in the presence of oxygen gas. Electron Paramagnetic Resonance Imaging (EPRI) is a technique to determine the spatial distribution of free radicals. X-band (9.5 GHz) EPR images of PMR-15 polyimide were obtained with a spatial resolution of about 0.18 mm along a 2 mm dimension of the sample. In a polyimide sample that was not thermocycled, the radical distribution was uniform along the 2 mm dimension of the sample. For a polyimide sample that was exposed to thermocycling in air for 300 one-hour cycles at 335 C, one-dimensional EPRI showed a higher concentration of free radicals in the surface layers than in the bulk sample. A spectral-spatial two-dimensional image showed that the EPR lineshape of the surface layer remained the same as that of the bulk. These EPRI results suggest that the thermo-oxidative degradation of PMR-15 resin involves free radicals present in the oxygen-rich surface layer.

[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.

Resolution modeling of dispersive imaging spectrometers

NASA Astrophysics Data System (ADS)

Silny, John F.

2017-08-01

This paper presents best practices for modeling the resolution of dispersive imaging spectrometers. The differences between sampling, width, and resolution are discussed. It is proposed that the spectral imaging community adopt a standard definition for resolution as the full-width at half maximum of the total line spread function. Resolution should be computed for each of the spectral, cross-scan spatial, and along-scan spatial/temporal dimensions separately. A physical optics resolution model is presented that incorporates the effects of slit diffraction and partial coherence, the result of which is a narrower slit image width and reduced radiometric throughput.

VARIANCE ESTIMATION FOR SPATIALLY BALANCED SAMPLES OF ENVIRONMENTAL RESOURCES

EPA Science Inventory

The spatial distribution of a natural resource is an important consideration in designing an efficient survey or monitoring program for the resource. We review a unified strategy for designing probability samples of discrete, finite resource populations, such as lakes within som...

Modeling of surface dust concentration in snow cover at industrial area using neural networks and kriging

NASA Astrophysics Data System (ADS)

Sergeev, A. P.; Tarasov, D. A.; Buevich, A. G.; Shichkin, A. V.; Tyagunov, A. G.; Medvedev, A. N.

2017-06-01

Modeling of spatial distribution of pollutants in the urbanized territories is difficult, especially if there are multiple emission sources. When monitoring such territories, it is often impossible to arrange the necessary detailed sampling. Because of this, the usual methods of analysis and forecasting based on geostatistics are often less effective. Approaches based on artificial neural networks (ANNs) demonstrate the best results under these circumstances. This study compares two models based on ANNs, which are multilayer perceptron (MLP) and generalized regression neural networks (GRNNs) with the base geostatistical method - kriging. Models of the spatial dust distribution in the snow cover around the existing copper quarry and in the area of emissions of a nickel factory were created. To assess the effectiveness of the models three indices were used: the mean absolute error (MAE), the root-mean-square error (RMSE), and the relative root-mean-square error (RRMSE). Taking into account all indices the model of GRNN proved to be the most accurate which included coordinates of the sampling points and the distance to the likely emission source as input parameters for the modeling. Maps of spatial dust distribution in the snow cover were created in the study area. It has been shown that the models based on ANNs were more accurate than the kriging, particularly in the context of a limited data set.

Spatial prediction of near surface soil water retention functions using hydrogeophysics and empirical orthogonal functions

NASA Astrophysics Data System (ADS)

Gibson, Justin; Franz, Trenton E.

2018-06-01

The hydrological community often turns to widely available spatial datasets such as the NRCS Soil Survey Geographic database (SSURGO) to characterize the spatial variability of soil properties. When used to spatially characterize and parameterize watershed models, this has served as a reasonable first approximation when lacking localized or incomplete soil data. Within agriculture, soil data has been left relatively coarse when compared to numerous other data sources measured. This is because localized soil sampling is both expensive and time intense, thus a need exists in better connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, non-invasive, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with spatially exhaustive datasets. In this work, we utilize two common near surface geophysical methods, cosmic-ray neutron probe and electromagnetic induction, to identify temporally stable spatial patterns of measured geophysical properties in three 65 ha agricultural fields in western Nebraska. This is achieved by repeat geophysical observations of the same study area across a range of wet to dry field conditions in order to evaluate with an empirical orthogonal function. Shallow cores were then extracted within each identified zone and water retention functions were generated in the laboratory. Using EOF patterns as a covariate, we quantify the predictive skill of estimating soil hydraulic properties in areas without measurement using a bootstrap validation analysis. Results indicate that sampling locations informed via repeat hydrogeophysical surveys, required only five cores to reduce the cross-validation root mean squared error by an average of 64% as compared to soil parameters predicted by a commonly used benchmark, SSURGO and ROSETTA. The reduction to five strategically located samples within the 65 ha fields reduces sampling efforts by up to ∼90% as compared to the common practice of soil grid sampling every 1 ha.

Future VIIRS enhancements for the integrated polar-orbiting environmental satellite system

NASA Astrophysics Data System (ADS)

Puschell, Jeffery J.; Silny, John; Cook, Lacy; Kim, Eugene

2010-08-01

The Visible/Infrared Imager Radiometer Suite (VIIRS) is the next-generation imaging spectroradiometer for the future operational polar-orbiting environmental satellite system. A successful Flight Unit 1 has been delivered and integrated onto the NPP spacecraft. The flexible VIIRS architecture can be adapted and enhanced to respond to a wide range of requirements and to incorporate new technology as it becomes available. This paper reports on recent design studies to evaluate building a MW-VLWIR dispersive hyperspectral module with active cooling into the existing VIIRS architecture. Performance of a two-grating VIIRS hyperspectral module was studied across a broad trade space defined primarily by spatial sampling, spectral range, spectral sampling interval, along-track field of view and integration time. The hyperspectral module studied here provides contiguous coverage across 3.9 - 15.5 μm with a spectral sampling interval of 10 nm or better, thereby extending VIIRS spectral range to the shortwave side of the 15.5 μm CO2 band and encompassing the 6.7 μm H2O band. Spatial sampling occurs at VIIRS I-band (~0.4 km at nadir) spatial resolution with aggregation to M-band (~0.8 km) and larger pixel sizes to improve sensitivity. Radiometric sensitivity (NEdT) at a spatial resolution of ~4 km is ~0.1 K or better for a 250 K scene across a wavelength range of 4.5 μm to 15.5 μm. The large number of high spectral and spatial resolution FOVs in this instrument improves chances for retrievals of information on the physical state and composition of the atmosphere all the way to the surface in cloudy regions relative to current systems. Spectral aggregation of spatial resolution measurements to MODIS and VIIRS multispectral bands would continue legacy measurements with better sensitivity in nearly all bands. Additional work is needed to optimize spatial sampling, spectral range and spectral sampling approaches for the hyperspectral module and to further refine this powerful imager concept.

Spatial acoustic radiation of respiratory sounds for sleep evaluation.

PubMed

Shabtai, Noam R; Zigel, Yaniv

2017-09-01

Body posture has an effect on sleeping quality and breathing disorders and therefore it is important to be recognized for the completion of the sleep evaluation process. Since humans have a directional acoustic radiation pattern, it is hypothesized that microphone arrays can be used to recognize different body postures, which is highly practical for sleep evaluation applications that already measure respiratory sounds using distant microphones. Furthermore, body posture may have an effect on distant microphone measurement; hence, the measurement can be compensated if the body posture is correctly recognized. A spherical harmonics decomposition approach to the spatial acoustic radiation is presented, assuming an array of eight microphones in a medium-sized audiology booth. The spatial sampling and reconstruction of the radiation pattern is discussed, and a final setup for the microphone array is recommended. A case study is shown using recorded segments of snoring and breathing sounds of three human subjects in three body postures in a silent but not anechoic audiology booth.

The value of remote sensing techniques in supporting effective extrapolation across multiple marine spatial scales.

PubMed

Strong, James Asa; Elliott, Michael

2017-03-15

The reporting of ecological phenomena and environmental status routinely required point observations, collected with traditional sampling approaches to be extrapolated to larger reporting scales. This process encompasses difficulties that can quickly entrain significant errors. Remote sensing techniques offer insights and exceptional spatial coverage for observing the marine environment. This review provides guidance on (i) the structures and discontinuities inherent within the extrapolative process, (ii) how to extrapolate effectively across multiple spatial scales, and (iii) remote sensing techniques and data sets that can facilitate this process. This evaluation illustrates that remote sensing techniques are a critical component in extrapolation and likely to underpin the production of high-quality assessments of ecological phenomena and the regional reporting of environmental status. Ultimately, is it hoped that this guidance will aid the production of robust and consistent extrapolations that also make full use of the techniques and data sets that expedite this process. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment of the effects of different sample perfusion procedures on phase-contrast tomographic images of mouse spinal cord

NASA Astrophysics Data System (ADS)

Stefanutti, E.; Sierra, A.; Miocchi, P.; Massimi, L.; Brun, F.; Maugeri, L.; Bukreeva, I.; Nurmi, A.; Begani Provinciali, G.; Tromba, G.; Gröhn, O.; Giove, F.; Cedola, A.; Fratini, M.

2018-03-01

Synchrotron X-ray Phase Contrast micro-Tomography (SXrPCμT) is a powerful tool in the investigation of biological tissues, including the central nervous system (CNS), and it allows to simultaneously detect the vascular and neuronal network avoiding contrast agents or destructive sample preparations. However, specific sample preparation procedures aimed to optimize the achievable contrast- and signal-to-noise ratio (CNR and SNR, respectively) are required. Here we report and discuss the effects of perfusion with two different fixative agents (ethanol and paraformaldehyde) and with a widely used contrast medium (MICROFIL®) on mouse spinal cord. As a main result, we found that ethanol enhances contrast at the grey/white matter interface and increases the contrast in correspondence of vascular features and fibres, thus providing an adequate spatial resolution to visualise the vascular network at the microscale. On the other hand, ethanol is known to induce tissue dehydration, likely reducing cell dimensions below the spatial resolution limit imposed by the experimental technique. Nonetheless, neurons remain well visible using either perfused paraformaldehyde or MICROFIL® compound, as these latter media do not affect tissues with dehydration effects. Paraformaldehyde appears as the best compromise: it is not a contrast agent, like MICROFIL®, but it is less invasive than ethanol and permits to visualise well both cells and blood vessels. However, a quantitative estimation of the relative grey matter volume of each sample has led us to conclude that no significant alterations in the grey matter extension compared to the white matter occur as a consequence of the perfusion procedures tested in this study.

Raman hyperspectral imaging as an effective and highly informative tool to study the diagenetic alteration of fossil bones.

PubMed

Dal Sasso, Gregorio; Angelini, Ivana; Maritan, Lara; Artioli, Gilberto

2018-03-01

Retrieving the pristine chemical or isotopic composition of archaeological bones is of great interest for many studies aiming to reconstruct the past life of ancient populations (i.e. diet, mobility, palaeoenvironment, age). However, from the death of the individual onwards, bones undergo several taphonomic and diagenetic processes that cause the alteration of their microstructure and composition. A detailed study on bone diagenesis has the double purpose to assess the preservation state of archaeological bones and to understand the alteration pathways, thus providing evidence that may contribute to evaluate the reliability of the retrieved information. On these bases, this research aims to explore the effectiveness of Raman hyperspectral imaging to detect types, extent and spatial distribution of diagenetic alteration at the micro-scale level. An early-Holocene bone sample from the Al Khiday cemetery (Khartoum, Sudan) was here analysed. Parameters related to the collagen content, bioapatite crystallinity and structural carbonate content, and to the occurrence of secondary mineral phases were calculated from Raman spectra. The acquired data provided spatially-resolved information on both the preservation state of bone constituents and the diagenetic processes occurring during burial. Given the minimal sample preparation, the easy and fast data acquisition and the improvement of system configurations, micro-Raman spectroscopy can be extensively applied as a screening method on a large set of samples in order to characterise the preservation state of archaeological bones. This technique can be effectively applied to identify suitable and well preserved portions of the analysed sample on which perform further analyses. Copyright © 2017 Elsevier B.V. All rights reserved.

Effect of selective logging on genetic diversity and gene flow in Cariniana legalis sampled from a cacao agroforestry system.

PubMed

Leal, J B; Santos, R P; Gaiotto, F A

2014-01-28

The fragments of the Atlantic Forest of southern Bahia have a long history of intense logging and selective cutting. Some tree species, such as jequitibá rosa (Cariniana legalis), have experienced a reduction in their populations with respect to both area and density. To evaluate the possible effects of selective logging on genetic diversity, gene flow, and spatial genetic structure, 51 C. legalis individuals were sampled, representing the total remaining population from the cacao agroforestry system. A total of 120 alleles were observed from the 11 microsatellite loci analyzed. The average observed heterozygosity (0.486) was less than the expected heterozygosity (0.721), indicating a loss of genetic diversity in this population. A high fixation index (FIS = 0.325) was found, which is possibly due to a reduction in population size, resulting in increased mating among relatives. The maximum (1055 m) and minimum (0.095 m) distances traveled by pollen or seeds were inferred based on paternity tests. We found 36.84% of unique parents among all sampled seedlings. The progenitors of the remaining seedlings (63.16%) were most likely out of the sampled area. Positive and significant spatial genetic structure was identified in this population among classes 10 to 30 m away with an average coancestry coefficient between pairs of individuals of 0.12. These results suggest that the agroforestry system of cacao cultivation is contributing to maintaining levels of diversity and gene flow in the studied population, thus minimizing the effects of selective logging.

Study of a MEMS-based Shack-Hartmann wavefront sensor with adjustable pupil sampling for astronomical adaptive optics.

PubMed

Baranec, Christoph; Dekany, Richard

2008-10-01

We introduce a Shack-Hartmann wavefront sensor for adaptive optics that enables dynamic control of the spatial sampling of an incoming wavefront using a segmented mirror microelectrical mechanical systems (MEMS) device. Unlike a conventional lenslet array, subapertures are defined by either segments or groups of segments of a mirror array, with the ability to change spatial pupil sampling arbitrarily by redefining the segment grouping. Control over the spatial sampling of the wavefront allows for the minimization of wavefront reconstruction error for different intensities of guide source and different atmospheric conditions, which in turn maximizes an adaptive optics system's delivered Strehl ratio. Requirements for the MEMS devices needed in this Shack-Hartmann wavefront sensor are also presented.

Individual differences in spatial relation processing: effects of strategy, ability, and gender

PubMed Central

van der Ham, Ineke J. M.; Borst, Gregoire

2011-01-01

Numerous studies have focused on the distinction between categorical and coordinate spatial relations. Categorical relations are propositional and abstract, and often related to a left hemisphere advantage. Coordinate relations specify the metric information of the relative locations of objects, and can be linked to right hemisphere processing. Yet, not all studies have reported such a clear double dissociation; in particular the categorical left hemisphere advantage is not always reported. In the current study we investigated whether verbal and spatial strategies, verbal and spatial cognitive abilities, and gender could account for the discrepancies observed in hemispheric lateralization of spatial relations. Seventy-five participants performed two visual half field, match-to-sample tasks (Van der Ham et al., 2007; 2009) to study the lateralization of categorical and coordinate relation processing. For each participant we determined the strategy they used in each of the two tasks. Consistent with previous findings, we found an overall categorical left hemisphere advantage and coordinate right hemisphere advantage. The lateralization pattern was affected selectively by the degree to which participants used a spatial strategy and by none of the other variables (i.e., verbal strategy, cognitive abilities, and gender). Critically, the categorical left hemisphere advantage was observed only for participants that relied strongly on a spatial strategy. This result is another piece of evidence that categorical spatial relation processing relies on spatial and not verbal processes. PMID:21353361

When time affects space: Dispersal ability and extreme weather events determine metacommunity organization in marine sediments.

PubMed

Corte, Guilherme N; Gonçalves-Souza, Thiago; Checon, Helio H; Siegle, Eduardo; Coleman, Ross A; Amaral, A Cecília Z

2018-05-01

Community ecology has traditionally assumed that the distribution of species is mainly influenced by environmental processes. There is, however, growing evidence that environmental (habitat characteristics and biotic interactions) and spatial processes (factors that affect a local assemblage regardless of environmental conditions - typically related to dispersal and movement of species) interactively shape biological assemblages. A metacommunity, which is a set of local assemblages connected by dispersal of individuals, is spatial in nature and can be used as a straightforward approach for investigating the interactive and independent effects of both environmental and spatial processes. Here, we examined (i) how environmental and spatial processes affect the metacommunity organization of marine macroinvertebrates inhabiting the intertidal sediments of a biodiverse coastal ecosystem; (ii) whether the influence of these processes is constant through time or is affected by extreme weather events (storms); and (iii) whether the relative importance of these processes depends on the dispersal abilities of organisms. We found that macrobenthic assemblages are influenced by each of environmental and spatial variables; however, spatial processes exerted a stronger role. We also found that this influence changes through time and is modified by storms. Moreover, we observed that the influence of environmental and spatial processes varies according to the dispersal capabilities of organisms. More effective dispersers (i.e., species with planktonic larvae) are more affected by spatial processes whereas environmental variables had a stronger effect on weaker dispersers (i.e. species with low motility in larval and adult stages). These findings highlight that accounting for spatial processes and differences in species life histories is essential to improve our understanding of species distribution and coexistence patterns in intertidal soft-sediments. Furthermore, it shows that storms modify the structure of coastal assemblages. Given that the influence of spatial and environmental processes is not consistent through time, it is of utmost importance that future studies replicate sampling over different periods so the influence of temporal and stochastic factors on macrobenthic metacommunities can be better understood. Copyright © 2018 Elsevier Ltd. All rights reserved.

Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization.

PubMed

Glaser, Joshua I; Zamft, Bradley M; Church, George M; Kording, Konrad P

2015-01-01

Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, "puzzle imaging," that allows imaging a spatially scrambled sample. This technique takes many spatially disordered samples, and then pieces them back together using local properties embedded within the sample. We show that puzzle imaging can efficiently produce high-resolution images using dimensionality reduction algorithms. We demonstrate the theoretical capabilities of puzzle imaging in three biological scenarios, showing that (1) relatively precise 3-dimensional brain imaging is possible; (2) the physical structure of a neural network can often be recovered based only on the neural connectivity matrix; and (3) a chemical map could be reproduced using bacteria with chemosensitive DNA and conjugative transfer. The ability to reconstruct scrambled images promises to enable imaging based on DNA sequencing of homogenized tissue samples.

Spatial variability of heavy metals in the coastal soils under long-term reclamation

NASA Astrophysics Data System (ADS)

Wang, Lin; Coles, Neil A.; Wu, Chunfa; Wu, Jiaping

2014-12-01

The coastal plain of Cixi City, China, has experienced over 1000 years of reclamation. With the rapid development of agriculture and industry after reclamation, successive inputs into agricultural soils have drastically modified the soil environment. To determine the spatial distribution of heavy metals and to evaluate the influence of anthropogenic activities, a total of 329 top soil samples were taken along a transect on the coastal plain. The samples collected across 11 sea dikes, were selected by a nested sampling methodology. Total Cu, Fe, Mn, Ni, Pb, and Zn concentrations, as well as their diethylenetriamine penta-acetic acid (DTPA) extractable (available) concentrations were determined. Results indicated that except for Zn concentrations, there was neither heavy metals pollution nor mineral deficiency in the soils. Heavy metals exhibited considerable spatial variability, obvious spatial dependence, and close relationships on the reclaimed land. For most metals, the reclamation history was the main influencing factor. Metals concentrations generally showed discontinuities around the position of sea dikes, and the longer reclamation histories tended to have higher metals concentrations than the recently reclaimed sectors. As for Cu and Zn total concentrations, stochastic factors, like industrial waste discharge, fertilization and pesticide application, probably led to the high nugget effect and altered this relationship. The 6th and 10th zones generally had the highest total metals concentrations, due to the concentration of household appliance manufacturers in these reclaimed areas. The first two zones were characterized by high available metals concentrations, probably due to the alternant flooding and emergence, low pH values and high organic matter contents in these paddy field soils. From the 3rd to 7th zones with the same land use history and soil type, metals concentrations, especially available concentrations, showed homogeneity. The nested sampling method adopted demonstrated that the 500-m interval was enough to capture the spatial variation of the metals. These results were useful in evaluating the variation in the environment quality of the soils under long-term reclamation and to formulate plans for future reclamation projects.

Effect of Hurricane Hugo on molluscan skeletal distributions,Salt River Bay, St. Croix, U.S. Virgin Islands

NASA Astrophysics Data System (ADS)

Miller, Arnold I.; Llewellyn, Ghislaine; Parsons, Karla M.; Cummins, Hays; Boardman, Mark R.; Greenstein, Benjamin J.; Jacobs, David K.

1992-01-01

Just prior to the passage of Hurricane Hugo over St. Croix, U.S. Virgin Islands, 35 molluscan skeletal samples were collected at 30 m intervals along a sampling transect in Salt River Bay, on the north-central coast. Three months after the hurricane, the transect was resampled to permit direct assessment of storm effects on skeletal distributions. Results indicate that spatial zonation of molluscan accumulations, associated with environmental transitions along the transect, was maintained in the wake of the hurricane. However, limited transport was diagnosed by comparing the compositions of prestorm and poststorm samples from the deepest, mud-rich subenvironment on the transect. In aggregate, the species richness of samples from the southern half of this zone increased from 16 to 40, and the abundance of species that were not among the characteristic molluscs of this subenvironment increased from 11% to 26%. These storm effects could probably not have been recognized, and attributed directly to Hugo, had there been no prestorm samples with which to compare directly the poststorm samples.

Quantum state atomic force microscopy

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

Passian, Ali; Siopsis, George

New classical modalities of atomic force microscopy continue to emerge to achieve higher spatial, spectral, and temporal resolution for nanometrology of materials. Here, we introduce the concept of a quantum mechanical modality that capitalizes on squeezed states of probe displacement. We show that such squeezing is enabled nanomechanically when the probe enters the van der Waals regime of interaction with a sample. The effect is studied in the non-contact mode, where we consider the parameter domains characterizing the attractive regime of the probe-sample interaction force.

Quantum state atomic force microscopy

DOE PAGES

Passian, Ali; Siopsis, George

2017-04-10

New classical modalities of atomic force microscopy continue to emerge to achieve higher spatial, spectral, and temporal resolution for nanometrology of materials. Here, we introduce the concept of a quantum mechanical modality that capitalizes on squeezed states of probe displacement. We show that such squeezing is enabled nanomechanically when the probe enters the van der Waals regime of interaction with a sample. The effect is studied in the non-contact mode, where we consider the parameter domains characterizing the attractive regime of the probe-sample interaction force.

Assessment of sediment toxicity and chemical concentrations in the San Diego Bay region, California, USA

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

Fairey, R.; Roberts, C.; Jacobi, M.

1998-08-01

Sediment quality within San Diego Bay, Mission Bay, and the Tijuana River Estuary of California was investigated as part of an ongoing statewide monitoring effort (Bay Protection and Toxic Cleanup Program). Study objectives were to determine the incidence, spatial patterns, and spatial extent of toxicity in sediments and porewater; the concentration and distribution of potentially toxic anthropogenic chemicals; and the relationships between toxicity and chemical concentrations. Rhepoxynius abronius survival bioassays, grain size, and total organic carbon analyses were performed on 350 sediment samples. Strongylocentrotus purpuratus development bioassays were performed on 164 pore-water samples. Toxicity was demonstrated throughout the San Diegomore » Bay region, with increased incidence and concordance occurring in areas of industrial and shipping activity. Trace metal and trace synthetic organic analyses were performed on 229 samples. Copper, zinc, mercury, polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and chlordane were found to exceed ERM (effects range median) or PEL (probable effects level) sediment quality guidelines and were considered the six major chemicals or chemical groups of concern. Statistical analysis of the relationships between amphipod toxicity, bulk phase sediment chemistry, and physical parameters demonstrated few significant linear relationships. Significant differences in chemical levels were found between toxic and nontoxic responses using multivariate and univariate statistics. Potential sources of anthropogenic chemicals were discussed.« less

Community structure of aquatic insects in the Esparza River, Costa Rica.

PubMed

Herrera-Vásquez, Jonathan

2009-01-01

This study focused on the structure of the aquatic insect community in spatial and temporal scales in the Esparza River. The river was sampled for one full year throughout 2007. During the dry season low flow months, five sampling points were selected in two different habitats (currents and pools), with five replicates per sample site. During the wet season with peak rain, only the data in the "current habitat" were sampled at each site. Specimens present in the different substrates were collected and preserved in situ. A nested ANOVA was then applied to the data to determine richness and density as the response variables. The variations in temporal and spatial scales were analyzed using width, depth and discharge of the river, and then analyzed using a nested ANOVA. Only a correlation of 51% similarity in richness was found, while in spatial scale, richness showed significant variation between sampling sites, but not between habitats. However, the temporal scale showed significant differences between habitats. Density showed differences between sites and habitats during the dry season in the spatial scale, while in the temporal scale significant variation was found between sampling sites. Width varied between habitats during the dry season, but not between sampling points. Depth showed differences between sampling sites and season. This work studies the importance of community structure of aquatic insects in rivers, and its relevance for the quality of water in rivers and streams.

Grain-dependent responses of mammalian diversity to land use and the implications for conservation set-aside.

PubMed

Wearn, Oliver R; Carbone, Chris; Rowcliffe, J Marcus; Bernard, Henry; Ewers, Robert M

2016-07-01

Diversity responses to land-use change are poorly understood at local scales, hindering our ability to make forecasts and management recommendations at scales which are of practical relevance. A key barrier in this has been the underappreciation of grain-dependent diversity responses and the role that β-diversity (variation in community composition across space) plays in this. Decisions about the most effective spatial arrangement of conservation set-aside, for example high conservation value areas, have also neglected β-diversity, despite its role in determining the complementarity of sites. We examined local-scale mammalian species richness and β-diversity across old-growth forest, logged forest, and oil palm plantations in Borneo, using intensive camera- and live-trapping. For the first time, we were able to investigate diversity responses, as well as β-diversity, at multiple spatial grains, and across the whole terrestrial mammal community (large and small mammals); β-diversity was quantified by comparing observed β-diversity with that obtained under a null model, in order to control for sampling effects, and we refer to this as the β-diversity signal. Community responses to land use were grain dependent, with large mammals showing reduced richness in logged forest compared to old-growth forest at the grain of individual sampling points, but no change at the overall land-use level. Responses varied with species group, however, with small mammals increasing in richness at all grains in logged forest compared to old-growth forest. Both species groups were significantly depauperate in oil palm. Large mammal communities in old-growth forest became more heterogeneous at coarser spatial grains and small mammal communities became more homogeneous, while this pattern was reversed in logged forest. Both groups, however, showed a significant β-diversity signal at the finest grain in logged forest, likely due to logging-induced environmental heterogeneity. The β-diversity signal in oil palm was weak, but heterogeneity at the coarsest spatial grain was still evident, likely due to variation in landscape forest cover. Our findings suggest that the most effective spatial arrangement of set-aside will involve trade-offs between conserving large and small mammals. Greater consideration in the conservation and management of tropical landscapes needs to be given to β-diversity at a range of spatial grains. © 2016 by the Ecological Society of America.

Spatial adaptive sampling in multiscale simulation

NASA Astrophysics Data System (ADS)

Rouet-Leduc, Bertrand; Barros, Kipton; Cieren, Emmanuel; Elango, Venmugil; Junghans, Christoph; Lookman, Turab; Mohd-Yusof, Jamaludin; Pavel, Robert S.; Rivera, Axel Y.; Roehm, Dominic; McPherson, Allen L.; Germann, Timothy C.

2014-07-01

In a common approach to multiscale simulation, an incomplete set of macroscale equations must be supplemented with constitutive data provided by fine-scale simulation. Collecting statistics from these fine-scale simulations is typically the overwhelming computational cost. We reduce this cost by interpolating the results of fine-scale simulation over the spatial domain of the macro-solver. Unlike previous adaptive sampling strategies, we do not interpolate on the potentially very high dimensional space of inputs to the fine-scale simulation. Our approach is local in space and time, avoids the need for a central database, and is designed to parallelize well on large computer clusters. To demonstrate our method, we simulate one-dimensional elastodynamic shock propagation using the Heterogeneous Multiscale Method (HMM); we find that spatial adaptive sampling requires only ≈ 50 ×N0.14 fine-scale simulations to reconstruct the stress field at all N grid points. Related multiscale approaches, such as Equation Free methods, may also benefit from spatial adaptive sampling.

Effectiveness of timber harvesting BMPs: monitoring spatial and temporal dynamics of dissolved oxygen, nitrogen, and phosphorus in a low-gradient watershed, Louisiana

Treesearch

Abram DaSilva; Y. Jun Xu; George Ice; John Beebe; Richard Stich

2012-01-01

To test effectiveness of Louisiana’s voluntary best management practices (BMPs) at preventing water quality degradation from timber harvesting activities, a study with BACI design was conducted from 2006 through 2010 in the Flat Creek Watershed, north-central Louisiana. Water samples for nutrient analyses and measurements of stream flow and of in-stream dissolved...

The Analytical Limits of Modeling Short Diffusion Timescales

NASA Astrophysics Data System (ADS)

Bradshaw, R. W.; Kent, A. J.

2016-12-01

Chemical and isotopic zoning in minerals is widely used to constrain the timescales of magmatic processes such as magma mixing and crystal residence, etc. via diffusion modeling. Forward modeling of diffusion relies on fitting diffusion profiles to measured compositional gradients. However, an individual measurement is essentially an average composition for a segment of the gradient defined by the spatial resolution of the analysis. Thus there is the potential for the analytical spatial resolution to limit the timescales that can be determined for an element of given diffusivity, particularly where the scale of the gradient approaches that of the measurement. Here we use a probabilistic modeling approach to investigate the effect of analytical spatial resolution on estimated timescales from diffusion modeling. Our method investigates how accurately the age of a synthetic diffusion profile can be obtained by modeling an "unknown" profile derived from discrete sampling of the synthetic compositional gradient at a given spatial resolution. We also include the effects of analytical uncertainty and the position of measurements relative to the diffusion gradient. We apply this method to the spatial resolutions of common microanalytical techniques (LA-ICP-MS, SIMS, EMP, NanoSIMS). Our results confirm that for a given diffusivity, higher spatial resolution gives access to shorter timescales, and that each analytical spacing has a minimum timescale, below which it overestimates the timescale. For example, for Ba diffusion in plagioclase at 750 °C timescales are accurate (within 20%) above 10, 100, 2,600, and 71,000 years at 0.3, 1, 5, and 25 mm spatial resolution, respectively. For Sr diffusion in plagioclase at 750 °C, timescales are accurate above 0.02, 0.2, 4, and 120 years at the same spatial resolutions. Our results highlight the importance of selecting appropriate analytical techniques to estimate accurate diffusion-based timescales.

Examination of the Effect of Drama Education on Multiple Intelligence Areas of Children

ERIC Educational Resources Information Center

Köksal Akyol, Aysel

2018-01-01

This study was conducted to determine whether or not drama education causes any difference in the verbal-linguistic, mathematical-logical, visual-spatial, musical-rhythmic, bodily-kinaesthetic, intrapersonal and interpersonal intelligences of children. The sample group of the study consisted of 46 children (23 children in the experimental group…

Spatially-explicit estimation of Wright's neighborhood size in continuous populations

Treesearch

Andrew J. Shirk; Samuel A. Cushman

2014-01-01

Effective population size (Ne) is an important parameter in conservation genetics because it quantifies a population's capacity to resist loss of genetic diversity due to inbreeding and drift. The classical approach to estimate Ne from genetic data involves grouping sampled individuals into discretely defined subpopulations assumed to be panmictic. Importantly,...

Effects of spatial allocation and parameter variability on lakewide estimates from surveys of Lake Superior, North America’s largest lake

EPA Science Inventory

Lake Superior was sampled in 2011 using a Generalized Random Tessellation Stratified design (n=54 sites) to characterize biological and chemical properties of this huge aquatic resource, with statistical confidence. The lake was divided into two strata (inshore <100m and offsh...

Spatial and temporal dynamics of root exudation: how important is heterogeneity in allelopathic interactions?

PubMed

Weidenhamer, Jeffrey D; Mohney, Brian K; Shihada, Nader; Rupasinghe, Maduka

2014-08-01

Understanding allelopathy has been hindered by the lack of methods available to monitor the dynamics of allelochemicals in the soil. Previous work has demonstrated the feasibility of using polydimethylsiloxane (PDMS) microtubing (silicone tubing microextraction, or STME) to construct sampling devices to monitor the release of lipophilic allelochemicals from plant roots. The objective of this study was to use such sampling devices to intensively monitor thiophene fluxes beneath marigolds over several weeks to gain insight into the magnitude of temporal and spatial heterogeneity in these fluxes. Marigolds were grown in rhizoboxes (20.5 x 20.5 x 3.0 cm) with 16 individual STME samplers per box. Thiophene sampling and HPLC analysis began 45 days after planting. At the end of the study, roots around each sampler were analyzed by HPLC. Results confirmed the tremendous spatial and temporal heterogeneity in thiophene production seen in our previous studies. STME probes show that thiophene concentrations generally increase over time; however, these effects were sampling-port specific. When sampling ports were monitored at 12 h intervals, fluxes at each port ranged from 0 to 2,510 ng day(-1). Fluxes measured over daylight hr averaged 29 % higher than those measured overnight. Fluxes were less than 1 % on average of the total thiophene content of surrounding roots. While the importance of such heterogeneity, or "patchiness", in the root zone has been recognized for soil nutrients, the potential importance in allelopathic interactions has seldom been considered. The reasons for this variability are unclear, but are being investigated. Our results demonstrate that STME can be used as a tool to provide a more finely-resolved picture of allelochemical dynamics in the root zone than has previously been available.

Single-step collision-free trajectory planning of biped climbing robots in spatial trusses.

PubMed

Zhu, Haifei; Guan, Yisheng; Chen, Shengjun; Su, Manjia; Zhang, Hong

For a biped climbing robot with dual grippers to climb poles, trusses or trees, feasible collision-free climbing motion is inevitable and essential. In this paper, we utilize the sampling-based algorithm, Bi-RRT, to plan single-step collision-free motion for biped climbing robots in spatial trusses. To deal with the orientation limit of a 5-DoF biped climbing robot, a new state representation along with corresponding operations including sampling, metric calculation and interpolation is presented. A simple but effective model of a biped climbing robot in trusses is proposed, through which the motion planning of one climbing cycle is transformed to that of a manipulator. In addition, the pre- and post-processes are introduced to expedite the convergence of the Bi-RRT algorithm and to ensure the safe motion of the climbing robot near poles as well. The piecewise linear paths are smoothed by utilizing cubic B-spline curve fitting. The effectiveness and efficiency of the presented Bi-RRT algorithm for climbing motion planning are verified by simulations.

[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.

Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome

PubMed Central

Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

2015-01-01

Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate “wall-to-wall” remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution. PMID:26402522

General constraints on sampling wildlife on FIA plots

USGS Publications Warehouse

Bailey, L.L.; Sauer, J.R.; Nichols, J.D.; Geissler, P.H.; McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H.; Cieszewski, Chris J.

2005-01-01

This paper reviews the constraints to sampling wildlife populations at FIA points. Wildlife sampling programs must have well-defined goals and provide information adequate to meet those goals. Investigators should choose a State variable based on information needs and the spatial sampling scale. We discuss estimation-based methods for three State variables: species richness, abundance, and patch occupancy. All methods incorporate two essential sources of variation: detectability estimation and spatial variation. FIA sampling imposes specific space and time criteria that may need to be adjusted to meet local wildlife objectives.

Spatial analysis of NDVI readings with difference sampling density

USDA-ARS?s Scientific Manuscript database

Advanced remote sensing technologies provide research an innovative way of collecting spatial data for use in precision agriculture. Sensor information and spatial analysis together allow for a complete understanding of the spatial complexity of a field and its crop. The objective of the study was...

A technique for evaluating the influence of spatial sampling on the determination of global mean total columnar ozone

NASA Technical Reports Server (NTRS)

Tolson, R. H.

1981-01-01

A technique is described for providing a means of evaluating the influence of spatial sampling on the determination of global mean total columnar ozone. A finite number of coefficients in the expansion are determined, and the truncated part of the expansion is shown to contribute an error to the estimate, which depends strongly on the spatial sampling and is relatively insensitive to data noise. First and second order statistics are derived for each term in a spherical harmonic expansion which represents the ozone field, and the statistics are used to estimate systematic and random errors in the estimates of total ozone.

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir

PubMed Central

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-01-01

Background: 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. Methods: 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. Results: 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. Conclusion: 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. PMID:26404350

Intensity of Territorial Marking Predicts Wolf Reproduction: Implications for Wolf Monitoring

PubMed Central

García, Emilio J.

2014-01-01

Background The implementation of intensive and complex approaches to monitor large carnivores is resource demanding, restricted to endangered species, small populations, or small distribution ranges. Wolf monitoring over large spatial scales is difficult, but the management of such contentious species requires regular estimations of abundance to guide decision-makers. The integration of wolf marking behaviour with simple sign counts may offer a cost-effective alternative to monitor the status of wolf populations over large spatial scales. Methodology/Principal Findings We used a multi-sampling approach, based on the collection of visual and scent wolf marks (faeces and ground scratching) and the assessment of wolf reproduction using howling and observation points, to test whether the intensity of marking behaviour around the pup-rearing period (summer-autumn) could reflect wolf reproduction. Between 1994 and 2007 we collected 1,964 wolf marks in a total of 1,877 km surveyed and we searched for the pups' presence (1,497 howling and 307 observations points) in 42 sampling sites with a regular presence of wolves (120 sampling sites/year). The number of wolf marks was ca. 3 times higher in sites with a confirmed presence of pups (20.3 vs. 7.2 marks). We found a significant relationship between the number of wolf marks (mean and maximum relative abundance index) and the probability of wolf reproduction. Conclusions/Significance This research establishes a real-time relationship between the intensity of wolf marking behaviour and wolf reproduction. We suggest a conservative cutting point of 0.60 for the probability of wolf reproduction to monitor wolves on a regional scale combined with the use of the mean relative abundance index of wolf marks in a given area. We show how the integration of wolf behaviour with simple sampling procedures permit rapid, real-time, and cost-effective assessments of the breeding status of wolf packs with substantial implications to monitor wolves at large spatial scales. PMID:24663068

High cognitive reserve is associated with a reduced age-related deficit in spatial conflict resolution

PubMed Central

Puccioni, Olga; Vallesi, Antonino

2012-01-01

Several studies support the existence of a specific age-related difficulty in suppressing potentially distracting information. The aim of the present study is to investigate whether spatial conflict resolution is selectively affected by aging. The way aging affects individuals could be modulated by many factors determined by the socieconomic status: we investigated whether factors such as cognitive reserve (CR) and years of education may play a compensatory role against age-related deficits in the spatial domain. A spatial Stroop task with no feature repetitions was administered to a sample of 17 non-demented older adults (69–79 years-old) and 18 younger controls (18–34 years-old) matched for gender and years of education. The two age groups were also administered with measures of intelligence and CR. The overall spatial Stroop effect did not differ according to age, neither for speed nor for accuracy. The two age groups equally showed sequential effects for congruent trials: reduced response times (RTs) if another congruent trial preceded them, and accuracy at ceiling. For incongruent trials, older adults, but not younger controls, were influenced by congruency of trialn−1, since RTs increased with preceding congruent trials. Interestingly, such an age-related modulation negatively correlated with CR. These findings suggest that spatial conflict resolution in aging is predominantly affected by general slowing, rather than by a more specific deficit. However, a high level of CR seems to play a compensatory role for both factors. PMID:23248595

[Using sequential indicator simulation method to define risk areas of soil heavy metals in farmland.

PubMed

Yang, Hao; Song, Ying Qiang; Hu, Yue Ming; Chen, Fei Xiang; Zhang, Rui

2018-05-01

The heavy metals in soil have serious impacts on safety, ecological environment and human health due to their toxicity and accumulation. It is necessary to efficiently identify the risk area of heavy metals in farmland soil, which is of important significance for environment protection, pollution warning and farmland risk control. We collected 204 samples and analyzed the contents of seven kinds of heavy metals (Cu, Zn, Pb, Cd, Cr, As, Hg) in Zengcheng District of Guangzhou, China. In order to overcame the problems of the data, including the limitation of abnormal values and skewness distribution and the smooth effect with the traditional kriging methods, we used sequential indicator simulation method (SISIM) to define the spatial distribution of heavy metals, and combined Hakanson index method to identify potential ecological risk area of heavy metals in farmland. The results showed that: (1) Based on the similar accuracy of spatial prediction of soil heavy metals, the SISIM had a better expression of detail rebuild than ordinary kriging in small scale area. Compared to indicator kriging, the SISIM had less error rate (4.9%-17.1%) in uncertainty evaluation of heavy-metal risk identification. The SISIM had less smooth effect and was more applicable to simulate the spatial uncertainty assessment of soil heavy metals and risk identification. (2) There was no pollution in Zengcheng's farmland. Moderate potential ecological risk was found in the southern part of study area due to enterprise production, human activities, and river sediments. This study combined the sequential indicator simulation with Hakanson risk index method, and effectively overcame the outlier information loss and smooth effect of traditional kriging method. It provided a new way to identify the soil heavy metal risk area of farmland in uneven sampling.

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

PubMed

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

Detection of forest stand-level spatial structure in ectomycorrhizal fungal communities.

PubMed

Lilleskov, Erik A; Bruns, Thomas D; Horton, Thomas R; Taylor, D; Grogan, Paul

2004-08-01

Ectomycorrhizal fungal (EMF) communities are highly diverse at the stand level. To begin to understand what might lead to such diversity, and to improve sampling designs, we investigated the spatial structure of these communities. We used EMF community data from a number of studies carried out in seven mature and one recently fire-initiated forest stand. We applied various measures of spatial pattern to characterize distributions at EMF community and species levels: Mantel tests, Mantel correlograms, variance/mean and standardized variograms. Mantel tests indicated that in four of eight sites community similarity decreased with distance, whereas Mantel correlograms also found spatial autocorrelation in those four plus two additional sites. In all but one of these sites elevated similarity was evident only at relatively small spatial scales (< 2.6 m), whereas one exhibited a larger scale pattern ( approximately 25 m). Evenness of biomass distribution among cores varied widely among taxa. Standardized variograms indicated that most of the dominant taxa showed patchiness at a scale of less than 3 m, with a range from 0 to < or =17 m. These results have implications for both sampling scale and intensity to achieve maximum efficiency of community sampling. In the systems we examined, cores should be at least 3 m apart to achieve the greatest sampling efficiency for stand-level community analysis. In some cases even this spacing may result in reduced sampling efficiency arising from patterns of spatial autocorrelation. Interpretation of the causes and significance of these patterns requires information on the genetic identity of individuals in the communities.

RAPID SPATIAL MAPPING OF CHEMICALS DISPERSED ACROSS SURFACES USING AN AUTOSAMPLER/DART/TOFMS

EPA Science Inventory

Rapid identification and semi-quantitation of chemicals spatially dispersed and

deposited on surfaces by accidental, deliberate, or weather-related events requires analysis of

hundreds of samples, usually obtained by sampling with wipes. Hand-held devices used on-si...

Digital Fresnel reflection holography for high-resolution 3D near-wall flow measurement.

PubMed

Kumar, S Santosh; Hong, Jiarong

2018-05-14

We propose a novel backscatter holographic imaging system, as a compact and effective tool for 3D near-wall flow diagnostics at high resolutions, utilizing light reflected at the solid-liquid interface as a reference beam. The technique is fully calibrated, and is demonstrated in a densely seeded channel to achieve a spatial resolution of near-wall flows equivalent to or exceeding prior digital inline holographic measurements using local tracer seeding technique. Additionally, we examined the effects of seeding concentration and laser coherence on the measurement resolution and sample volume resolved, demonstrating the potential to manipulate sample domain by tuning the laser coherence profile.

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

Decreased Leftward ‘Aiming’ Motor-Intentional Spatial Cuing in Traumatic Brain Injury

PubMed Central

Wagner, Daymond; Eslinger, Paul J.; Barrett, A. M.

2016-01-01

Objective To characterize the mediation of attention and action in space following traumatic brain injury (TBI). Method Two exploratory analyses were performed to determine the influence of spatial ‘Aiming’ motor versus spatial ‘Where’ bias on line bisection in TBI participants. The first experiment compared performance according to severity and location of injury in TBI. The second experiment examined bisection performance in a larger TBI sample against a matched control group. In both experiments, participants bisected lines in near and far space using an apparatus that allowed for the fractionation of spatial Aiming versus Where error components. Results In the first experiment, participants with severe injuries tended to incur rightward error when starting from the right in far space, compared with participants with mild injuries. In the second experiment, when performance was examined at the individual level, more participants with TBI tended to incur rightward motor error compared to controls. Conclusions TBI may cause frontal-subcortical cognitive dysfunction and asymmetric motor perseveration, affecting spatial Aiming bias on line bisection. Potential effects on real-world function need further investigation. PMID:27571220

Breast cancer mitosis detection in histopathological images with spatial feature extraction

NASA Astrophysics Data System (ADS)

Albayrak, Abdülkadir; Bilgin, Gökhan

2013-12-01

In this work, cellular mitosis detection in histopathological images has been investigated. Mitosis detection is very expensive and time consuming process. Development of digital imaging in pathology has enabled reasonable and effective solution to this problem. Segmentation of digital images provides easier analysis of cell structures in histopathological data. To differentiate normal and mitotic cells in histopathological images, feature extraction step is very crucial step for the system accuracy. A mitotic cell has more distinctive textural dissimilarities than the other normal cells. Hence, it is important to incorporate spatial information in feature extraction or in post-processing steps. As a main part of this study, Haralick texture descriptor has been proposed with different spatial window sizes in RGB and La*b* color spaces. So, spatial dependencies of normal and mitotic cellular pixels can be evaluated within different pixel neighborhoods. Extracted features are compared with various sample sizes by Support Vector Machines using k-fold cross validation method. According to the represented results, it has been shown that separation accuracy on mitotic and non-mitotic cellular pixels gets better with the increasing size of spatial window.

Examining the occupancy–density relationship for a low-density carnivore

USGS Publications Warehouse

Linden, Daniel W.; Fuller, Angela K.; Royle, J. Andrew; Hare, Matthew P.

2017-01-01

The challenges associated with monitoring low-density carnivores across large landscapes have limited the ability to implement and evaluate conservation and management strategies for such species. Non-invasive sampling techniques and advanced statistical approaches have alleviated some of these challenges and can even allow for spatially explicit estimates of density, one of the most valuable wildlife monitoring tools.For some species, individual identification comes at no cost when unique attributes (e.g. pelage patterns) can be discerned with remote cameras, while other species require viable genetic material and expensive laboratory processing for individual assignment. Prohibitive costs may still force monitoring efforts to use species distribution or occupancy as a surrogate for density, which may not be appropriate under many conditions.Here, we used a large-scale monitoring study of fisher Pekania pennanti to evaluate the effectiveness of occupancy as an approximation to density, particularly for informing harvest management decisions. We combined remote cameras with baited hair snares during 2013–2015 to sample across a 70 096-km2 region of western New York, USA. We fit occupancy and Royle–Nichols models to species detection–non-detection data collected by cameras, and spatial capture–recapture (SCR) models to individual encounter data obtained by genotyped hair samples. Variation in the state variables within 15-km2 grid cells was modelled as a function of landscape attributes known to influence fisher distribution.We found a close relationship between grid cell estimates of fisher state variables from the models using detection–non-detection data and those from the SCR model, likely due to informative spatial covariates across a large landscape extent and a grid cell resolution that worked well with the movement ecology of the species. Fisher occupancy and density were both positively associated with the proportion of coniferous-mixed forest and negatively associated with road density. As a result, spatially explicit management recommendations for fisher were similar across models, though relative variation was dampened for the detection–non-detection data.Synthesis and applications. Our work provides empirical evidence that models using detection–non-detection data can make similar inferences regarding relative spatial variation of the focal population to models using more expensive individual encounters when the selected spatial grain approximates or is marginally smaller than home range size. When occupancy alone is chosen as a cost-effective state variable for monitoring, simulation and sensitivity analyses should be used to understand how inferences from detection–non-detection data will be affected by aspects of study design and species ecology.

'spup' - an R package for uncertainty propagation in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2016-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability, including case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected static and interactive visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

'spup' - an R package for uncertainty propagation analysis in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2017-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability and being able to deal with case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

Testing aggregation hypotheses among Neotropical trees and shrubs: results from a 50-ha plot over 20 years of sampling.

PubMed

Myster, Randall W; Malahy, Michael P

2012-09-01

Spatial patterns of tropical trees and shrubs are important to understanding their interaction and the resultant structure of tropical rainforests. To assess this issue, we took advantage of previously collected data, on Neotropical tree and shrub stem identified to species and mapped for spatial coordinates in a 50ha plot, with a frequency of every five years and over a 20 year period. These stems data were first placed into four groups, regardless of species, depending on their location in the vertical strata of the rainforest (shrubs, understory trees, mid-sized trees, tall trees) and then used to generate aggregation patterns for each sampling year. We found shrubs and understory trees clumped at small spatial scales of a few meters for several of the years sampled. Alternatively, mid-sized trees and tall trees did not clump, nor did they show uniform (regular) patterns, during any sampling period. In general (1) groups found higher in the canopy did not show aggregation on the ground and (2) the spatial patterns of all four groups showed similarity among different sampling years, thereby supporting a "shifting mosaic" view of plant communities over large areas. Spatial analysis, such as this one, are critical to understanding and predicting tree spaces, tree-tree replacements and the Neotropical forest patterns, such as biodiversity and those needed for sustainability efforts, they produce.

Global patterns and predictors of fish species richness in estuaries.

PubMed

Vasconcelos, Rita P; Henriques, Sofia; França, Susana; Pasquaud, Stéphanie; Cardoso, Inês; Laborde, Marina; Cabral, Henrique N

2015-09-01

1. Knowledge of global patterns of biodiversity and regulating variables is indispensable to develop predictive models. 2. The present study used predictive modelling approaches to investigate hypotheses that explain the variation in fish species richness between estuaries over a worldwide spatial extent. Ultimately, such models will allow assessment of future changes in ecosystem structure and function as a result of environmental changes. 3. A comprehensive worldwide data base was compiled of the fish assemblage composition and environmental characteristics of estuaries. Generalized Linear Models were used to quantify how variation in species richness among estuaries is related to historical events, energy dynamics and ecosystem characteristics, while controlling for sampling effects. 4. At the global extent, species richness differed among marine biogeographic realms and continents and increased with mean sea surface temperature, terrestrial net primary productivity and the stability of connectivity with a marine ecosystem (open vs. temporarily open estuaries). At a smaller extent (within a marine biogeographic realm or continent), other characteristics were also important in predicting variation in species richness, with species richness increasing with estuary area and continental shelf width. 5. The results suggest that species richness in an estuary is defined by predictors that are spatially hierarchical. Over the largest spatial extents, species richness is influenced by the broader distributions and habitat use patterns of marine and freshwater species that can colonize estuaries, which are in turn governed by history contingency, energy dynamics and productivity variables. Species richness is also influenced by more regional and local parameters that can further affect the process of community colonization in an estuary including the connectivity of the estuary with the adjacent marine habitat, and, over smaller spatial extents, the size of these habitats. In summary, patterns of species richness in estuaries across large spatial extents seem to reflect from global to local processes acting on community colonization. The importance of considering spatial extent, sampling effects and of combining history and contemporary environmental characteristics when exploring biodiversity is highlighted. © 2015 The Authors. Journal of Animal Ecology published by John Wiley & Sons on behalf of the British Ecological Society.

Meteorology-induced variations in the spatial behavior of summer ozone pollution in Central California

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

Jin, Ling; Harley, Robert A.; Brown, Nancy J.

Cluster analysis was applied to daily 8 h ozone maxima modeled for a summer season to characterize meteorology-induced variations in the spatial distribution of ozone. Principal component analysis is employed to form a reduced dimension set to describe and interpret ozone spatial patterns. The first three principal components (PCs) capture {approx}85% of total variance, with PC1 describing a general spatial trend, and PC2 and PC3 each describing a spatial contrast. Six clusters were identified for California's San Joaquin Valley (SJV) with two low, three moderate, and one high-ozone cluster. The moderate ozone clusters are distinguished by elevated ozone levels inmore » different parts of the valley: northern, western, and eastern, respectively. The SJV ozone clusters have stronger coupling with the San Francisco Bay area (SFB) than with the Sacramento Valley (SV). Variations in ozone spatial distributions induced by anthropogenic emission changes are small relative to the overall variations in ozone amomalies observed for the whole summer. Ozone regimes identified here are mostly determined by the direct and indirect meteorological effects. Existing measurement sites are sufficiently representative to capture ozone spatial patterns in the SFB and SV, but the western side of the SJV is under-sampled.« less

Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part I): Earths Radiation Budget

NASA Technical Reports Server (NTRS)

Holdaway, Daniel; Yang, Yuekui

2016-01-01

Satellites always sample the Earth-atmosphere system in a finite temporal resolution. This study investigates the effect of sampling frequency on the satellite-derived Earth radiation budget, with the Deep Space Climate Observatory (DSCOVR) as an example. The output from NASA's Goddard Earth Observing System Version 5 (GEOS-5) Nature Run is used as the truth. The Nature Run is a high spatial and temporal resolution atmospheric simulation spanning a two-year period. The effect of temporal resolution on potential DSCOVR observations is assessed by sampling the full Nature Run data with 1-h to 24-h frequencies. The uncertainty associated with a given sampling frequency is measured by computing means over daily, monthly, seasonal and annual intervals and determining the spread across different possible starting points. The skill with which a particular sampling frequency captures the structure of the full time series is measured using correlations and normalized errors. Results show that higher sampling frequency gives more information and less uncertainty in the derived radiation budget. A sampling frequency coarser than every 4 h results in significant error. Correlations between true and sampled time series also decrease more rapidly for a sampling frequency less than 4 h.

REACTT: an algorithm for solving spatial equilibrium problems.

Treesearch

D.J. Brooks; J. Kincaid

1987-01-01

The problem of determining equilibrium prices and quantities in spatially separated markets is reviewed. Algorithms that compute spatial equilibria are discussed. A computer program using the reactive programming algorithm for solving spatial equilibrium problems that involve multiple commodities is presented, along with detailed documentation. A sample data set,...

Cost-effective sampling of ¹³⁷Cs-derived net soil redistribution: part 1--estimating the spatial mean across scales of variation.

PubMed

Li, Y; Chappell, A; Nyamdavaa, B; Yu, H; Davaasuren, D; Zoljargal, K

2015-03-01

The (137)Cs technique for estimating net time-integrated soil redistribution is valuable for understanding the factors controlling soil redistribution by all processes. The literature on this technique is dominated by studies of individual fields and describes its typically time-consuming nature. We contend that the community making these studies has inappropriately assumed that many (137)Cs measurements are required and hence estimates of net soil redistribution can only be made at the field scale. Here, we support future studies of (137)Cs-derived net soil redistribution to apply their often limited resources across scales of variation (field, catchment, region etc.) without compromising the quality of the estimates at any scale. We describe a hybrid, design-based and model-based, stratified random sampling design with composites to estimate the sampling variance and a cost model for fieldwork and laboratory measurements. Geostatistical mapping of net (1954-2012) soil redistribution as a case study on the Chinese Loess Plateau is compared with estimates for several other sampling designs popular in the literature. We demonstrate the cost-effectiveness of the hybrid design for spatial estimation of net soil redistribution. To demonstrate the limitations of current sampling approaches to cut across scales of variation, we extrapolate our estimate of net soil redistribution across the region, show that for the same resources, estimates from many fields could have been provided and would elucidate the cause of differences within and between regional estimates. We recommend that future studies evaluate carefully the sampling design to consider the opportunity to investigate (137)Cs-derived net soil redistribution across scales of variation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sample Preparation of Corn Seed Tissue to Prevent Analyte Relocations for Mass Spectrometry Imaging

NASA Astrophysics Data System (ADS)

Kim, Shin Hye; Kim, Jeongkwon; Lee, Young Jin; Lee, Tae Geol; Yoon, Sohee

2017-08-01

Corn seed tissue sections were prepared by the tape support method using an adhesive tape, and mass spectrometry imaging (MSI) was performed. The effect of heat generated during sample preparation was investigated by time-of-flight secondary mass spectrometry (TOF-SIMS) imaging of corn seed tissue prepared by the tape support and the thaw-mounted methods. Unlike thaw-mounted sample preparation, the tape support method does not cause imaging distortion because of the absence of heat, which can cause migration of the analytes on the sample. By applying the tape-support method, the corn seed tissue was prepared without structural damage and MSI with accurate spatial information of analytes was successfully performed.

Spatial Prediction and Optimized Sampling Design for Sodium Concentration in Groundwater

PubMed Central

Shabbir, Javid; M. AbdEl-Salam, Nasser; Hussain, Tajammal

2016-01-01

Sodium is an integral part of water, and its excessive amount in drinking water causes high blood pressure and hypertension. In the present paper, spatial distribution of sodium concentration in drinking water is modeled and optimized sampling designs for selecting sampling locations is calculated for three divisions in Punjab, Pakistan. Universal kriging and Bayesian universal kriging are used to predict the sodium concentrations. Spatial simulated annealing is used to generate optimized sampling designs. Different estimation methods (i.e., maximum likelihood, restricted maximum likelihood, ordinary least squares, and weighted least squares) are used to estimate the parameters of the variogram model (i.e, exponential, Gaussian, spherical and cubic). It is concluded that Bayesian universal kriging fits better than universal kriging. It is also observed that the universal kriging predictor provides minimum mean universal kriging variance for both adding and deleting locations during sampling design. PMID:27683016

Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization

PubMed Central

Glaser, Joshua I.; Zamft, Bradley M.; Church, George M.; Kording, Konrad P.

2015-01-01

Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, “puzzle imaging,” that allows imaging a spatially scrambled sample. This technique takes many spatially disordered samples, and then pieces them back together using local properties embedded within the sample. We show that puzzle imaging can efficiently produce high-resolution images using dimensionality reduction algorithms. We demonstrate the theoretical capabilities of puzzle imaging in three biological scenarios, showing that (1) relatively precise 3-dimensional brain imaging is possible; (2) the physical structure of a neural network can often be recovered based only on the neural connectivity matrix; and (3) a chemical map could be reproduced using bacteria with chemosensitive DNA and conjugative transfer. The ability to reconstruct scrambled images promises to enable imaging based on DNA sequencing of homogenized tissue samples. PMID:26192446

X-ray simulations method for the large field of view

NASA Astrophysics Data System (ADS)

Schelokov, I. A.; Grigoriev, M. V.; Chukalina, M. V.; Asadchikov, V. E.

2018-03-01

In the standard approach, X-ray simulation is usually limited to the step of spatial sampling to calculate the convolution of integrals of the Fresnel type. Explicitly the sampling step is determined by the size of the last Fresnel zone in the beam aperture. In other words, the spatial sampling is determined by the precision of integral convolution calculations and is not connected with the space resolution of an optical scheme. In the developed approach the convolution in the normal space is replaced by computations of the shear strain of ambiguity function in the phase space. The spatial sampling is then determined by the space resolution of an optical scheme. The sampling step can differ in various directions because of the source anisotropy. The approach was used to simulate original images in the X-ray Talbot interferometry and showed that the simulation can be applied to optimize the methods of postprocessing.

Determining biological tissue optical properties via integrating sphere spatial measurements

DOEpatents

Baba, Justin S [Knoxville, TN; Letzen, Brian S [Coral Springs, FL

2011-01-11

An optical sample is mounted on a spatial-acquisition apparatus that is placed in or on an enclosure. An incident beam is irradiated on a surface of the sample and the specular reflection is allowed to escape from the enclosure through an opening. The spatial-acquisition apparatus is provided with a light-occluding slider that moves in front of the sample to block portions of diffuse scattering from the sample. As the light-occluding slider moves across the front of the sample, diffuse light scattered into the area of the backside of the light-occluding slider is absorbed by back side surface of the light-occluding slider. By measuring a baseline diffuse reflectance without a light-occluding slider and subtracting measured diffuse reflectance with a light-occluding slider therefrom, diffuse reflectance for the area blocked by the light-occluding slider can be calculated.

Soft-tissue imaging with C-arm cone-beam CT using statistical reconstruction

NASA Astrophysics Data System (ADS)

Wang, Adam S.; Webster Stayman, J.; Otake, Yoshito; Kleinszig, Gerhard; Vogt, Sebastian; Gallia, Gary L.; Khanna, A. Jay; Siewerdsen, Jeffrey H.

2014-02-01

The potential for statistical image reconstruction methods such as penalized-likelihood (PL) to improve C-arm cone-beam CT (CBCT) soft-tissue visualization for intraoperative imaging over conventional filtered backprojection (FBP) is assessed in this work by making a fair comparison in relation to soft-tissue performance. A prototype mobile C-arm was used to scan anthropomorphic head and abdomen phantoms as well as a cadaveric torso at doses substantially lower than typical values in diagnostic CT, and the effects of dose reduction via tube current reduction and sparse sampling were also compared. Matched spatial resolution between PL and FBP was determined by the edge spread function of low-contrast (˜40-80 HU) spheres in the phantoms, which were representative of soft-tissue imaging tasks. PL using the non-quadratic Huber penalty was found to substantially reduce noise relative to FBP, especially at lower spatial resolution where PL provides a contrast-to-noise ratio increase up to 1.4-2.2× over FBP at 50% dose reduction across all objects. Comparison of sampling strategies indicates that soft-tissue imaging benefits from fully sampled acquisitions at dose above ˜1.7 mGy and benefits from 50% sparsity at dose below ˜1.0 mGy. Therefore, an appropriate sampling strategy along with the improved low-contrast visualization offered by statistical reconstruction demonstrates the potential for extending intraoperative C-arm CBCT to applications in soft-tissue interventions in neurosurgery as well as thoracic and abdominal surgeries by overcoming conventional tradeoffs in noise, spatial resolution, and dose.

Spatial heterogeneity study of vegetation coverage at Heihe River Basin

NASA Astrophysics Data System (ADS)

Wu, Lijuan; Zhong, Bo; Guo, Liyu; Zhao, Xiangwei

2014-11-01

Spatial heterogeneity of the animal-landscape system has three major components: heterogeneity of resource distributions in the physical environment, heterogeneity of plant tissue chemistry, heterogeneity of movement modes by the animal. Furthermore, all three different types of heterogeneity interact each other and can either reinforce or offset one another, thereby affecting system stability and dynamics. In previous studies, the study areas are investigated by field sampling, which costs a large amount of manpower. In addition, uncertain in sampling affects the quality of field data, which leads to unsatisfactory results during the entire study. In this study, remote sensing data is used to guide the sampling for research on heterogeneity of vegetation coverage to avoid errors caused by randomness of field sampling. Semi-variance and fractal dimension analysis are used to analyze the spatial heterogeneity of vegetation coverage at Heihe River Basin. The spherical model with nugget is used to fit the semivariogram of vegetation coverage. Based on the experiment above, it is found, (1)there is a strong correlation between vegetation coverage and distance of vegetation populations within the range of 0-28051.3188m at Heihe River Basin, but the correlation loses suddenly when the distance greater than 28051.3188m. (2)The degree of spatial heterogeneity of vegetation coverage at Heihe River Basin is medium. (3)Spatial distribution variability of vegetation occurs mainly on small scales. (4)The degree of spatial autocorrelation is 72.29% between 25% and 75%, which means that spatial correlation of vegetation coverage at Heihe River Basin is medium high.

SPATIALLY-BALANCED SAMPLING OF NATURAL RESOURCES IN THE PRESENCE OF FRAME IMPERFECTIONS

EPA Science Inventory

The spatial distribution of a natural resource is an important consideration in designing an efficient survey or monitoring program for the resource. Generally, samples that are more or less evenly dispersed over the extent of the resource will be more efficient than simple rando...

Spatial averaging for small molecule diffusion in condensed phase environments

NASA Astrophysics Data System (ADS)

Plattner, Nuria; Doll, J. D.; Meuwly, Markus

2010-07-01

Spatial averaging is a new approach for sampling rare-event problems. The approach modifies the importance function which improves the sampling efficiency while keeping a defined relation to the original statistical distribution. In this work, spatial averaging is applied to multidimensional systems for typical problems arising in physical chemistry. They include (I) a CO molecule diffusing on an amorphous ice surface, (II) a hydrogen molecule probing favorable positions in amorphous ice, and (III) CO migration in myoglobin. The systems encompass a wide range of energy barriers and for all of them spatial averaging is found to outperform conventional Metropolis Monte Carlo. It is also found that optimal simulation parameters are surprisingly similar for the different systems studied, in particular, the radius of the point cloud over which the potential energy function is averaged. For H2 diffusing in amorphous ice it is found that facile migration is possible which is in agreement with previous suggestions from experiment. The free energy barriers involved are typically lower than 1 kcal/mol. Spatial averaging simulations for CO in myoglobin are able to locate all currently characterized metastable states. Overall, it is found that spatial averaging considerably improves the sampling of configurational space.

Geotechnical parameter spatial distribution stochastic analysis based on multi-precision information assimilation

NASA Astrophysics Data System (ADS)

Wang, C.; Rubin, Y.

2014-12-01

Spatial distribution of important geotechnical parameter named compression modulus Es contributes considerably to the understanding of the underlying geological processes and the adequate assessment of the Es mechanics effects for differential settlement of large continuous structure foundation. These analyses should be derived using an assimilating approach that combines in-situ static cone penetration test (CPT) with borehole experiments. To achieve such a task, the Es distribution of stratum of silty clay in region A of China Expo Center (Shanghai) is studied using the Bayesian-maximum entropy method. This method integrates rigorously and efficiently multi-precision of different geotechnical investigations and sources of uncertainty. Single CPT samplings were modeled as a rational probability density curve by maximum entropy theory. Spatial prior multivariate probability density function (PDF) and likelihood PDF of the CPT positions were built by borehole experiments and the potential value of the prediction point, then, preceding numerical integration on the CPT probability density curves, the posterior probability density curve of the prediction point would be calculated by the Bayesian reverse interpolation framework. The results were compared between Gaussian Sequential Stochastic Simulation and Bayesian methods. The differences were also discussed between single CPT samplings of normal distribution and simulated probability density curve based on maximum entropy theory. It is shown that the study of Es spatial distributions can be improved by properly incorporating CPT sampling variation into interpolation process, whereas more informative estimations are generated by considering CPT Uncertainty for the estimation points. Calculation illustrates the significance of stochastic Es characterization in a stratum, and identifies limitations associated with inadequate geostatistical interpolation techniques. This characterization results will provide a multi-precision information assimilation method of other geotechnical parameters.

Short-term spatial and temporal variability in greenhouse gas fluxes in riparian zones.

PubMed

Vidon, P; Marchese, S; Welsh, M; McMillan, S

2015-08-01

Recent research indicates that riparian zones have the potential to contribute significant amounts of greenhouse gases (GHG: N2O, CO2, CH4) to the atmosphere. Yet, the short-term spatial and temporal variability in GHG emission in these systems is poorly understood. Using two transects of three static chambers at two North Carolina agricultural riparian zones (one restored, one unrestored), we show that estimates of the average GHG flux at the site scale can vary by one order of magnitude depending on whether the mean or the median is used as a measure of central tendency. Because the median tends to mute the effect of outlier points (hot spots and hot moments), we propose that both must be reported or that other more advanced spatial averaging techniques (e.g., kriging, area-weighted average) should be used to estimate GHG fluxes at the site scale. Results also indicate that short-term temporal variability in GHG fluxes (a few days) under seemingly constant temperature and hydrological conditions can be as large as spatial variability at the site scale, suggesting that the scientific community should rethink sampling protocols for GHG at the soil-atmosphere interface to include repeated measures over short periods of time at select chambers to estimate GHG emissions in the field. Although recent advances in technology provide tools to address these challenges, their cost is often too high for widespread implementation. Until technology improves, sampling design strategies will need to be carefully considered to balance cost, time, and spatial and temporal representativeness of measurements.

Quantifying Rock Weakening Due to Decreasing Calcite Mineral Content by Numerical Simulations

PubMed Central

2018-01-01

The quantification of changes in geomechanical properties due to chemical reactions is of paramount importance for geological subsurface utilisation, since mineral dissolution generally reduces rock stiffness. In the present study, the effective elastic moduli of two digital rock samples, the Fontainebleau and Bentheim sandstones, are numerically determined based on micro-CT images. Reduction in rock stiffness due to the dissolution of 10% calcite cement by volume out of the pore network is quantified for three synthetic spatial calcite distributions (coating, partial filling and random) using representative sub-cubes derived from the digital rock samples. Due to the reduced calcite content, bulk and shear moduli decrease by 34% and 38% in maximum, respectively. Total porosity is clearly the dominant parameter, while spatial calcite distribution has a minor impact, except for a randomly chosen cement distribution within the pore network. Moreover, applying an initial stiffness reduced by 47% for the calcite cement results only in a slightly weaker mechanical behaviour. Using the quantitative approach introduced here substantially improves the accuracy of predictions in elastic rock properties compared to general analytical methods, and further enables quantification of uncertainties related to spatial variations in porosity and mineral distribution. PMID:29614776

Benthic macrofaunal structure and secondary production in tropical estuaries on the Eastern Marine Ecoregion of Brazil.

PubMed

Bissoli, Lorena B; Bernardino, Angelo F

2018-01-01

Tropical estuaries are highly productive and support diverse benthic assemblages within mangroves and tidal flats habitats. Determining differences and similarities of benthic assemblages within estuarine habitats and between regional ecosystems may provide scientific support for management of those ecosystems. Here we studied three tropical estuaries in the Eastern Marine Ecoregion of Brazil to assess the spatial variability of benthic assemblages from vegetated (mangroves) and unvegetated (tidal flats) habitats. A nested sampling design was used to determine spatial scales of variability in benthic macrofaunal density, biomass and secondary production. Habitat differences in benthic assemblage composition were evident, with mangrove forests being dominated by annelids (Oligochaeta and Capitellidae) whereas peracarid crustaceans were also abundant on tidal flats. Macrofaunal biomass, density and secondary production also differed between habitats and among estuaries. Those differences were related both to the composition of benthic assemblages and to random spatial variability, underscoring the importance of hierarchical sampling in estuarine ecological studies. Given variable levels of human impacts and predicted climate change effects on tropical estuarine assemblages in Eastern Brazil, our data support the use of benthic secondary production to address long-term changes and improved management of estuaries in Eastern Brazil.

Quantifying Rock Weakening Due to Decreasing Calcite Mineral Content by Numerical Simulations.

PubMed

Wetzel, Maria; Kempka, Thomas; Kühn, Michael

2018-04-01

The quantification of changes in geomechanical properties due to chemical reactions is of paramount importance for geological subsurface utilisation, since mineral dissolution generally reduces rock stiffness. In the present study, the effective elastic moduli of two digital rock samples, the Fontainebleau and Bentheim sandstones, are numerically determined based on micro-CT images. Reduction in rock stiffness due to the dissolution of 10% calcite cement by volume out of the pore network is quantified for three synthetic spatial calcite distributions (coating, partial filling and random) using representative sub-cubes derived from the digital rock samples. Due to the reduced calcite content, bulk and shear moduli decrease by 34% and 38% in maximum, respectively. Total porosity is clearly the dominant parameter, while spatial calcite distribution has a minor impact, except for a randomly chosen cement distribution within the pore network. Moreover, applying an initial stiffness reduced by 47% for the calcite cement results only in a slightly weaker mechanical behaviour. Using the quantitative approach introduced here substantially improves the accuracy of predictions in elastic rock properties compared to general analytical methods, and further enables quantification of uncertainties related to spatial variations in porosity and mineral distribution.

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

Yashchuk, V. V.; Fischer, P. J.; Chan, E. R.

We present a modulation transfer function (MTF) calibration method based on binary pseudo-random (BPR) one-dimensional sequences and two-dimensional arrays as an effective method for spectral characterization in the spatial frequency domain of a broad variety of metrology instrumentation, including interferometric microscopes, scatterometers, phase shifting Fizeau interferometers, scanning and transmission electron microscopes, and at this time, x-ray microscopes. The inherent power spectral density of BPR gratings and arrays, which has a deterministic white-noise-like character, allows a direct determination of the MTF with a uniform sensitivity over the entire spatial frequency range and field of view of an instrument. We demonstrate themore » MTF calibration and resolution characterization over the full field of a transmission soft x-ray microscope using a BPR multilayer (ML) test sample with 2.8 nm fundamental layer thickness. We show that beyond providing a direct measurement of the microscope's MTF, tests with the BPRML sample can be used to fine tune the instrument's focal distance. Finally, our results confirm the universality of the method that makes it applicable to a large variety of metrology instrumentation with spatial wavelength bandwidths from a few nanometers to hundreds of millimeters.« less

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

Yashchuk, V. V., E-mail: VVYashchuk@lbl.gov; Chan, E. R.; Lacey, I.

We present a modulation transfer function (MTF) calibration method based on binary pseudo-random (BPR) one-dimensional sequences and two-dimensional arrays as an effective method for spectral characterization in the spatial frequency domain of a broad variety of metrology instrumentation, including interferometric microscopes, scatterometers, phase shifting Fizeau interferometers, scanning and transmission electron microscopes, and at this time, x-ray microscopes. The inherent power spectral density of BPR gratings and arrays, which has a deterministic white-noise-like character, allows a direct determination of the MTF with a uniform sensitivity over the entire spatial frequency range and field of view of an instrument. We demonstrate themore » MTF calibration and resolution characterization over the full field of a transmission soft x-ray microscope using a BPR multilayer (ML) test sample with 2.8 nm fundamental layer thickness. We show that beyond providing a direct measurement of the microscope’s MTF, tests with the BPRML sample can be used to fine tune the instrument’s focal distance. Our results confirm the universality of the method that makes it applicable to a large variety of metrology instrumentation with spatial wavelength bandwidths from a few nanometers to hundreds of millimeters.« less

Acute and chronic ethanol intake: effects on spatial and non-spatial memory in rats.

PubMed

García-Moreno, Luis M; Cimadevilla, Jose M

2012-12-01

Abusive alcohol consumption produces neuronal damage and biochemical alterations in the mammal brain followed by cognitive disturbances. In this work rats receiving chronic and acute alcohol intake were evaluated in a spontaneous delayed non-matching to sample/position test. Chronic alcohol-treated rats had free access to an aqueous ethanol solution as the only available liquid source from the postnatal day 21 to the end of experiment (postnatal day 90). Acute alcoholic animals received an injection of 2 g/kg ethanol solution once per week. Subjects were evaluated in two tests (object recognition and spatial recognition) based on the spontaneous delayed non-matching to sample or to position paradigm using delays of 1 min, 15 min and 60 min. Results showed that chronic and acute alcohol intake impairs the rats' performance in both tests. Moreover, chronic alcohol-treated rats were more altered than acute treated animals in both tasks. Our results support the idea that chronic and acute alcohol administration during postnatal development caused widespread brain damage resulting in behavioral disturbances and learning disabilities. Copyright © 2012 Elsevier Inc. All rights reserved.

On edge-aware path-based color spatial sampling for Retinex: from Termite Retinex to Light Energy-driven Termite Retinex

NASA Astrophysics Data System (ADS)

Simone, Gabriele; Cordone, Roberto; Serapioni, Raul Paolo; Lecca, Michela

2017-05-01

Retinex theory estimates the human color sensation at any observed point by correcting its color based on the spatial arrangement of the colors in proximate regions. We revise two recent path-based, edge-aware Retinex implementations: Termite Retinex (TR) and Energy-driven Termite Retinex (ETR). As the original Retinex implementation, TR and ETR scan the neighborhood of any image pixel by paths and rescale their chromatic intensities by intensity levels computed by reworking the colors of the pixels on the paths. Our interest in TR and ETR is due to their unique, content-based scanning scheme, which uses the image edges to define the paths and exploits a swarm intelligence model for guiding the spatial exploration of the image. The exploration scheme of ETR has been showed to be particularly effective: its paths are local minima of an energy functional, designed to favor the sampling of image pixels highly relevant to color sensation. Nevertheless, since its computational complexity makes ETR poorly practicable, here we present a light version of it, named Light Energy-driven TR, and obtained from ETR by implementing a modified, optimized minimization procedure and by exploiting parallel computing.

Benthic macrofaunal structure and secondary production in tropical estuaries on the Eastern Marine Ecoregion of Brazil

PubMed Central

Bissoli, Lorena B.

2018-01-01

Tropical estuaries are highly productive and support diverse benthic assemblages within mangroves and tidal flats habitats. Determining differences and similarities of benthic assemblages within estuarine habitats and between regional ecosystems may provide scientific support for management of those ecosystems. Here we studied three tropical estuaries in the Eastern Marine Ecoregion of Brazil to assess the spatial variability of benthic assemblages from vegetated (mangroves) and unvegetated (tidal flats) habitats. A nested sampling design was used to determine spatial scales of variability in benthic macrofaunal density, biomass and secondary production. Habitat differences in benthic assemblage composition were evident, with mangrove forests being dominated by annelids (Oligochaeta and Capitellidae) whereas peracarid crustaceans were also abundant on tidal flats. Macrofaunal biomass, density and secondary production also differed between habitats and among estuaries. Those differences were related both to the composition of benthic assemblages and to random spatial variability, underscoring the importance of hierarchical sampling in estuarine ecological studies. Given variable levels of human impacts and predicted climate change effects on tropical estuarine assemblages in Eastern Brazil, our data support the use of benthic secondary production to address long-term changes and improved management of estuaries in Eastern Brazil. PMID:29507833

A Spatial Hedonic Analysis of the Effects of Wind Energy Facilities on Surrounding Property Values in the United States

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

Hoen, Ben; Wiser, Ryan; Cappers, Peter

2013-08-21

This report summarizes a new analysis, building on previously published research, about wind energy’s effects on residential property values. This study helps fill research gaps by collecting and analyzing data from 27 counties across nine U.S. states, related to 67 different wind facilities, and constructs a pooled model that investigates average effects near the turbines across the sample while controlling for local variables, such as sale prices of nearby homes.

Impact of spatial variability and sampling design on model performance

NASA Astrophysics Data System (ADS)

Schrape, Charlotte; Schneider, Anne-Kathrin; Schröder, Boris; van Schaik, Loes

2017-04-01

Many environmental physical and chemical parameters as well as species distributions display a spatial variability at different scales. In case measurements are very costly in labour time or money a choice has to be made between a high sampling resolution at small scales and a low spatial cover of the study area or a lower sampling resolution at the small scales resulting in local data uncertainties with a better spatial cover of the whole area. This dilemma is often faced in the design of field sampling campaigns for large scale studies. When the gathered field data are subsequently used for modelling purposes the choice of sampling design and resulting data quality influence the model performance criteria. We studied this influence with a virtual model study based on a large dataset of field information on spatial variation of earthworms at different scales. Therefore we built a virtual map of anecic earthworm distributions over the Weiherbach catchment (Baden-Württemberg in Germany). First of all the field scale abundance of earthworms was estimated using a catchment scale model based on 65 field measurements. Subsequently the high small scale variability was added using semi-variograms, based on five fields with a total of 430 measurements divided in a spatially nested sampling design over these fields, to estimate the nugget, range and standard deviation of measurements within the fields. With the produced maps, we performed virtual samplings of one up to 50 random points per field. We then used these data to rebuild the catchment scale models of anecic earthworm abundance with the same model parameters as in the work by Palm et al. (2013). The results of the models show clearly that a large part of the non-explained deviance of the models is due to the very high small scale variability in earthworm abundance: the models based on single virtual sampling points on average obtain an explained deviance of 0.20 and a correlation coefficient of 0.64. With increasing sampling points per field, we averaged the measured abundance of the sampling within each field to obtain a more representative value of the field average. Doubling the samplings per field strongly improved the model performance criteria (explained deviance 0.38 and correlation coefficient 0.73). With 50 sampling points per field the performance criteria were 0.91 and 0.97 respectively for explained deviance and correlation coefficient. The relationship between number of samplings and performance criteria can be described with a saturation curve. Beyond five samples per field the model improvement becomes rather small. With this contribution we wish to discuss the impact of data variability at sampling scale on model performance and the implications for sampling design and assessment of model results as well as ecological inferences.

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.

Using GIS to generate spatially balanced random survey designs for natural resource applications.

PubMed

Theobald, David M; Stevens, Don L; White, Denis; Urquhart, N Scott; Olsen, Anthony R; Norman, John B

2007-07-01

Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sample apply to the entire population. Probability survey designs should be used in natural resource and environmental management situations because they provide the mathematical foundation for statistical inference. Development of long-term monitoring designs demand survey designs that achieve statistical rigor and are efficient but remain flexible to inevitable logistical or practical constraints during field data collection. Here we describe an approach to probability-based survey design, called the Reversed Randomized Quadrant-Recursive Raster, based on the concept of spatially balanced sampling and implemented in a geographic information system. This provides environmental managers a practical tool to generate flexible and efficient survey designs for natural resource applications. Factors commonly used to modify sampling intensity, such as categories, gradients, or accessibility, can be readily incorporated into the spatially balanced sample design.

Nanoscale infrared spectroscopy as a non-destructive probe of extraterrestrial samples.

PubMed

Dominguez, Gerardo; Mcleod, A S; Gainsforth, Zack; Kelly, P; Bechtel, Hans A; Keilmann, Fritz; Westphal, Andrew; Thiemens, Mark; Basov, D N

2014-12-09

Advances in the spatial resolution of modern analytical techniques have tremendously augmented the scientific insight gained from the analysis of natural samples. Yet, while techniques for the elemental and structural characterization of samples have achieved sub-nanometre spatial resolution, infrared spectral mapping of geochemical samples at vibrational 'fingerprint' wavelengths has remained restricted to spatial scales >10 μm. Nevertheless, infrared spectroscopy remains an invaluable contactless probe of chemical structure, details of which offer clues to the formation history of minerals. Here we report on the successful implementation of infrared near-field imaging, spectroscopy and analysis techniques capable of sub-micron scale mineral identification within natural samples, including a chondrule from the Murchison meteorite and a cometary dust grain (Iris) from NASA's Stardust mission. Complementary to scanning electron microscopy, energy-dispersive X-ray spectroscopy and transmission electron microscopy probes, this work evidences a similarity between chondritic and cometary materials, and inaugurates a new era of infrared nano-spectroscopy applied to small and invaluable extraterrestrial samples.

Spatial Evaluation of Heavy Metals Concentrations in the Surface Sediment of Taihu Lake

PubMed Central

Niu, Yong; Jiao, Wei; Yu, Hui; Niu, Yuan; Pang, Yong; Xu, Xiangyang; Guo, Xiaochun

2015-01-01

With regard to the size of China’s freshwater lakes, Taihu Lake ranks third and it plays an important role in the supply of drinking water, flood prevention, farming and navigation, as well as in the travelling industry. The problem of environmental pollution has attracted widespread attention in recent years. In order to understand the levels, distribution and sources of heavy metals in sediments of Taihu Lake, random selection was carried out to obtain 59 samples of surface sediment from the entire lake and study the concentrations of Pb, Cd, Cu, Zn, Cr and Ni. Toxic units were also calculated to normalize the toxicities caused by various heavy metals. As a result, Cd and Cu in sediment were considered lower than the effect range low (ERL) at all regions where samples were gathered, while Pb and Ni were categorized into ERL-effect range median (ERM) at over 22% of the regions where samples were obtained. Nevertheless, all average concentrations of the samples were below the level of potential effect. According to the findings of this research, significant spatial heterogeneity existed in the above heavy metals. In conclusion, the distribution areas of heavy metals with higher concentrations were mainly the north bays, namely Zhushan Bay, Meiliang Bay as well as Gonghu Bay. The distribution areas of Cu, Zn, Cr and Ni with higher concentration also included the lake’s central region, whereas the uniform distribution areas of those with lower concentrations were the lake’s southeast region. In addition, it was most probable that the spatial distribution of heavy metals was determined by river inputs, whereas atmospheric precipitation caused by urban and traffic contamination also exerted considerable effects on the higher concentrations of Pb and Cd. Through evaluating the total amount of toxic units (ΣTU), it was found that higher toxicity existed primarily in the north bays and central region of the lake. If the heavy metals were sorted by the reduction of mean heavy metal toxic units in Taihu Lake in descending order, it would be Pb, Cr, Ni, Cd, Zn and Cu. Generally speaking, these result of analyses are conducive to alleviating the contamination of heavy metals in Taihu Lake. PMID:26633432

Individual differences in the dominance of interhemispheric connections predict cognitive ability beyond sex and brain size.

PubMed

Martínez, Kenia; Janssen, Joost; Pineda-Pardo, José Ángel; Carmona, Susanna; Román, Francisco Javier; Alemán-Gómez, Yasser; Garcia-Garcia, David; Escorial, Sergio; Quiroga, María Ángeles; Santarnecchi, Emiliano; Navas-Sánchez, Francisco Javier; Desco, Manuel; Arango, Celso; Colom, Roberto

2017-07-15

Global structural brain connectivity has been reported to be sex-dependent with women having increased interhemispheric connectivity (InterHc) and men having greater intrahemispheric connectivity (IntraHc). However, (a) smaller brains show greater InterHc, (b) larger brains show greater IntraHc, and (c) women have, on average, smaller brains than men. Therefore, sex differences in brain size may modulate sex differences in global brain connectivity. At the behavioural level, sex-dependent differences in connectivity are thought to contribute to men-women differences in spatial and verbal abilities. But this has never been tested at the individual level. The current study assessed whether individual differences in global structural connectome measures (InterHc, IntraHc and the ratio of InterHc relative to IntraHc) predict spatial and verbal ability while accounting for the effect of sex and brain size. The sample included forty men and forty women, who did neither differ in age nor in verbal and spatial latent components defined by a broad battery of tests and tasks. High-resolution T 1 -weighted and diffusion-weighted images were obtained for computing brain size and reconstructing the structural connectome. Results showed that men had higher IntraHc than women, while women had an increased ratio InterHc/IntraHc. However, these sex differences were modulated by brain size. Increased InterHc relative to IntraHc predicted higher spatial and verbal ability irrespective of sex and brain size. The positive correlations between the ratio InterHc/IntraHc and the spatial and verbal abilities were confirmed in 1000 random samples generated by bootstrapping. Therefore, sex differences in global structural connectome connectivity were modulated by brain size and did not underlie sex differences in verbal and spatial abilities. Rather, the level of dominance of InterHc over IntraHc may be associated with individual differences in verbal and spatial abilities in both men and women. Copyright © 2017 Elsevier Inc. All rights reserved.

Temporal and Spatial Diversity of Bacterial Communities in Coastal Waters of the South China Sea

PubMed Central

Du, Jikun; Xiao, Kai; Li, Li; Ding, Xian; Liu, Helu; Lu, Yongjun; Zhou, Shining

2013-01-01

Bacteria are recognized as important drivers of biogeochemical processes in all aquatic ecosystems. Temporal and geographical patterns in ocean bacterial communities have been observed in many studies, but the temporal and spatial patterns in the bacterial communities from the South China Sea remained unexplored. To determine the spatiotemporal patterns, we generated 16S rRNA datasets for 15 samples collected from the five regularly distributed sites of the South China Sea in three seasons (spring, summer, winter). A total of 491 representative sequences were analyzed by MOTHUR, yielding 282 operational taxonomic units (OTUs) grouped at 97% stringency. Significant temporal variations of bacterial diversity were observed. Richness and diversity indices indicated that summer samples were the most diverse. The main bacterial group in spring and summer samples was Alphaproteobacteria, followed by Cyanobacteria and Gammaproteobacteria, whereas Cyanobacteria dominated the winter samples. Spatial patterns in the samples were observed that samples collected from the coastal (D151, D221) waters and offshore (D157, D1512, D224) waters clustered separately, the coastal samples harbored more diverse bacterial communities. However, the temporal pattern of the coastal site D151 was contrary to that of the coastal site D221. The LIBSHUFF statistics revealed noticeable differences among the spring, summer and winter libraries collected at five sites. The UPGMA tree showed there were temporal and spatial heterogeneity of bacterial community composition in coastal waters of the South China Sea. The water salinity (P=0.001) contributed significantly to the bacteria-environment relationship. Our results revealed that bacterial community structures were influenced by environmental factors and community-level changes in 16S-based diversity were better explained by spatial patterns than by temporal patterns. PMID:23785512

A novel artificial immune algorithm for spatial clustering with obstacle constraint and its applications.

PubMed

Sun, Liping; Luo, Yonglong; Ding, Xintao; Zhang, Ji

2014-01-01

An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE) algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect.

Numerical Magnitude Representation in Children With Mathematical Difficulties With or Without Reading Difficulties.

PubMed

Tobia, Valentina; Fasola, Anna; Lupieri, Alice; Marzocchi, Gian Marco

2016-01-01

This study aimed to explore the spatial numerical association of response codes (SNARC), the flanker, and the numerical distance effects in children with mathematical difficulties. From a sample of 720 third, fourth, and fifth graders, 60 children were selected and divided into the following three groups: typically developing children (TD; n = 29), children with mathematical difficulties only (MD only; n = 21), and children with mathematical and reading difficulties (MD+RD; n = 10). Children were tested with a numerical Eriksen task that was built to assess SNARC, numerical distance, and flanker (first and second order congruency) effects. Children with MD only showed stronger SNARC and second order congruency effects than did TD children, whereas the numerical distance effects were similar across the three groups. Finally, the first order congruency effect was associated with reading difficulties. These results showed that children with mathematical difficulties with or without reading difficulties were globally more impaired when spatial incompatibilities were presented. © Hammill Institute on Disabilities 2014.

Spatial Neglect Hinders Success of Inpatient Rehabilitation in Individuals With Traumatic Brain Injury: A Retrospective Study.

PubMed

Chen, Peii; Ward, Irene; Khan, Ummais; Liu, Yan; Hreha, Kimberly

2016-06-01

Background Current knowledge about spatial neglect and its impact on rehabilitation mostly originates from stroke studies. Objective To examine the impact of spatial neglect on rehabilitation outcome in individuals with traumatic brain injury (TBI). Methods The retrospective study included 156 consecutive patients with TBI (73 women; median age = 69.5 years; interquartile range = 50-81 years) at an inpatient rehabilitation facility (IRF). We examined whether the presence of spatial neglect affected the Functional Independence Measure (FIM) scores, length of stay, or discharge disposition. Based on the available medical records, we also explored whether spatial neglect was associated with tactile sensation or muscle strength asymmetry in the extremities and whether specific brain injuries or lesions predicted spatial neglect. Results In all, 30.1% (47 of 156) of the sample had spatial neglect. Sex, age, severity of TBI, or time postinjury did not differ between patients with and without spatial neglect. In comparison to patients without spatial neglect, patients with the disorder stayed in IRF 5 days longer, had lower FIM scores at discharge, improved slower in both Cognitive and Motor FIM scores, and might have less likelihood of return home. In addition, left-sided neglect was associated with asymmetric strength in the lower extremities, specifically left weaker than the right. Finally, brain injury-induced mass effect predicted left-sided neglect. Conclusions Spatial neglect is common following TBI, impedes rehabilitation progress in both motor and cognitive domains, and prolongs length of stay. Future research is needed for linking specific traumatic injuries and lesioned networks to spatial neglect and related impairment. © The Author(s) 2015.