Spatial and temporal coherence in perceptual binding

PubMed Central

Blake, Randolph; Yang, Yuede

1997-01-01

Component visual features of objects are registered by distributed patterns of activity among neurons comprising multiple pathways and visual areas. How these distributed patterns of activity give rise to unified representations of objects remains unresolved, although one recent, controversial view posits temporal coherence of neural activity as a binding agent. Motivated by the possible role of temporal coherence in feature binding, we devised a novel psychophysical task that requires the detection of temporal coherence among features comprising complex visual images. Results show that human observers can more easily detect synchronized patterns of temporal contrast modulation within hybrid visual images composed of two components when those components are drawn from the same original picture. Evidently, time-varying changes within spatially coherent features produce more salient neural signals. PMID:9192701

The impact of half-a-degree Celsius upon the spatial pattern of future sea-level change.

NASA Astrophysics Data System (ADS)

Jackson, Luke

2017-04-01

It has been shown that the global thermal expansion of sea level and ocean dynamics are linearly related to global temperature change. On this basis one can estimate the difference in local sea-level change between a 1.5°C and 2.0°C world. The mitigation scenario RCP 2.6 shows an end-of-century global temperature range of 0.9 to 2.3°C (median 1.6°C). Additional sea-level components, such as mass changes in ice sheets, glaciers and land-water storage have unique spatial patterns that contribute to sea-level change and will be indirectly affected by global temperature change. We project local sea-level change for RCP 2.6 using sub-sets of models in the CMIP5 archive that follow different global temperature pathways. The method used to calculate local sea-level change is probabilistic and combines the normalised spatial patterns of sea-level components with global average projections of individual sea-level components.

Spatial and seasonal patterns in water quality in an embayment-mainstem reach of the tidal freshwater Potomac River, USA: a multiyear study.

PubMed

Jones, R Christian; Kelso, Donald P; Schaeffer, Elaine

2008-12-01

Spatial and temporal patterns in water quality were studied for seven years within an embayment-river mainstem area of the tidal freshwater Potomac River. The purpose of this paper is to determine the important components of spatial and temporal variation in water quality in this study area to facilitate an understanding of management impacts and allow the most effective use of future monitoring resources. The study area received treated sewage effluent and freshwater inflow from direct tributary inputs into the shallow embayment as well as upriver sources in the mainstem. Depth variations were determined to be detectable, but minimal due mainly to the influence of tidal mixing. Results of principal component analysis of two independent water quality datasets revealed clear spatial and seasonal patterns. Interannual variation was generally minimal despite substantial variations in tributary and mainstem discharge among years. Since both spatial and seasonal components were important, data were segmented by season to best determine the spatial pattern. A clear difference was found between a set of stations located within one embayment (Gunston Cove) and a second set in the nearby Potomac mainstem. Parameters most highly correlated with differences were those typically associated with higher densities of phytoplankton: chlorophyll a, photosynthetic rate, pH, dissolved oxygen, BOD, total phosphorus and Secchi depth. These differences and their consistency indicated two distinct water masses: one in the cove harboring higher algal density and activity and a second in the river with lower phytoplankton activity. A second embayment not receiving sewage effluent generally had an intermediate position. While this was the most consistent spatial pattern, there were two others of a secondary nature. Stations closer to the effluent inputs in the embayment sometimes grouped separately due to elevated ammonia and chloride. Stations closer to tributary inflows into the embayment sometimes grouped separately due to dilution with freshwater runoff. Segmenting the datasets by spatial region resulted in a clarification of seasonal patterns with similar factors relating to algal activity being the major correlates of the seasonal pattern. A basic seasonal pattern of lower scores in the spring increasing steadily to a peak in July and August followed by a steady decline through the fall was observed in the cove. In the river, the pattern of increases tended to be delayed slightly in the spring. Results indicate that the study area can be effectively monitored with fewer study sites provided that at least one is located in each of the spatial regions.

Joint modelling of potentially avoidable hospitalisation for five diseases accounting for spatiotemporal effects: A case study in New South Wales, Australia.

PubMed

Baker, Jannah; White, Nicole; Mengersen, Kerrie; Rolfe, Margaret; Morgan, Geoffrey G

2017-01-01

Three variant formulations of a spatiotemporal shared component model are proposed that allow examination of changes in shared underlying factors over time. Models are evaluated within the context of a case study examining hospitalisation rates for five chronic diseases for residents of a regional area in New South Wales: type II diabetes mellitus (DMII), chronic obstructive pulmonary disease (COPD), coronary arterial disease (CAD), hypertension (HT) and congestive heart failure (CHF) between 2001-2006. These represent ambulatory care sensitive (ACS) conditions, often used as a proxy for avoidable hospitalisations. Using a selected model, the effects of socio-economic status (SES) as a shared component are estimated and temporal patterns in the influence of the residual shared spatial component are examined. Choice of model depends upon the application. In the featured application, a model allowing for changing influence of the shared spatial component over time was found to have the best fit and was selected for further analyses. Hospitalisation rates were found to be increasing for COPD and DMII, decreasing for CHF and stable for CAD and HT. SES was substantively associated with hospitalisation rates, with differing degrees of influence for each disease. In general, most of the spatial variation in hospitalisation rates was explained by disease-specific spatial components, followed by the residual shared spatial component. Appropriate selection of a joint disease model allows for the examination of temporal patterns of disease outcomes and shared underlying spatial factors, and distinction between different shared spatial factors.

A Familiar Pattern? Semantic Memory Contributes to the Enhancement of Visuo-Spatial Memories

ERIC Educational Resources Information Center

Riby, Leigh M.; Orme, Elizabeth

2013-01-01

In this study we quantify for the first time electrophysiological components associated with incorporating long-term semantic knowledge with visuo-spatial information using two variants of a traditional matrix patterns task. Results indicated that the matrix task with greater semantic content was associated with enhanced accuracy and RTs in a…

Component pattern analysis of chemicals using multispectral THz imaging system

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuki

2004-04-01

We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

The Spatial Behaviour of Animals and Men

ERIC Educational Resources Information Center

Brindley, T. S.

1973-01-01

Describes some common patterns of animal spatial behavior, and discusses spatial relationships that can be observed as an important component of human social behavior. Reports the results of a study relating to the interpersonal distances of people in bus queues in Britain. (JR)

Implications of recurrent disturbance for genetic diversity.

PubMed

Davies, Ian D; Cary, Geoffrey J; Landguth, Erin L; Lindenmayer, David B; Banks, Sam C

2016-02-01

Exploring interactions between ecological disturbance, species' abundances and community composition provides critical insights for ecological dynamics. While disturbance is also potentially an important driver of landscape genetic patterns, the mechanisms by which these patterns may arise by selective and neutral processes are not well-understood. We used simulation to evaluate the relative importance of disturbance regime components, and their interaction with demographic and dispersal processes, on the distribution of genetic diversity across landscapes. We investigated genetic impacts of variation in key components of disturbance regimes and spatial patterns that are likely to respond to climate change and land management, including disturbance size, frequency, and severity. The influence of disturbance was mediated by dispersal distance and, to a limited extent, by birth rate. Nevertheless, all three disturbance regime components strongly influenced spatial and temporal patterns of genetic diversity within subpopulations, and were associated with changes in genetic structure. Furthermore, disturbance-induced changes in temporal population dynamics and the spatial distribution of populations across the landscape resulted in disrupted isolation by distance patterns among populations. Our results show that forecast changes in disturbance regimes have the potential to cause major changes to the distribution of genetic diversity within and among populations. We highlight likely scenarios under which future changes to disturbance size, severity, or frequency will have the strongest impacts on population genetic patterns. In addition, our results have implications for the inference of biological processes from genetic data, because the effects of dispersal on genetic patterns were strongly mediated by disturbance regimes.

[Effects of sub-watershed landscape patterns at the upper reaches of Minjiang River on soil erosion].

PubMed

Yang, Meng; Li, Xiu-zhen; Yang, Zhao-ping; Hu, Yuan-man; Wen, Qing-chun

2007-11-01

Based on GIS, the spatial distribution of soil loss and sediment yield in Heishui and Zhenjiangguan sub-watersheds at the upper reaches of Minjiang River was simulated by using sediment delivery-distribution (SEDD) model, and the effects of land use/cover types on soil erosion and sediment yield were discussed, based on the simulated results and related land use maps. A landscape index named location-weighted landscape contrast index (LCI) was calculated to evaluate the effects of landscape components' spatial distribution, weight, and structure of land use/cover on soil erosion. The results showed the soil erosion modulus varied with land use pattern, and decreased in the order of bare rock > urban/village > rangeland > farmland > shrub > forest. There were no significant differences in sediment yield modules among different land use/covers. In the two sub-watersheds, the spatial distribution of land use/covers on slope tended to decrease the final sediment load at watershed outlet, hut as related to relative elevation, relative distance, and flow length, the spatial distribution tended to increase sediment yield. The two sub-watersheds had different advantages as related to landscape components' spatial distribution, but, when the land use/cover weight was considered, the advantages of Zhenjiangguan sub-watershed increased. If the land use/cover structure was considered in addition, the landscape pattern of Zhenjiangguan subwatershed was better. Therefore, only the three elements, i.e., landscape components' spatial distribution, land use/cover weight, and land use/cover structure, were considered comprehensively, can we get an overall evaluation on the effects of landscape pattern on soil erosion. The calculation of LCI related to slope suggested that this index couldn' t accurately reflect the effects of land use/cover weight and structure on soil erosion, and thus, needed to be modified.

The Ability of Atmospheric Data to Reduce Disagreements in Wetland Methane Flux Estimates over North America

NASA Astrophysics Data System (ADS)

Miller, S. M.; Andrews, A. E.; Benmergui, J. S.; Commane, R.; Dlugokencky, E. J.; Janssens-Maenhout, G.; Melton, J. R.; Michalak, A. M.; Sweeney, C.; Worthy, D. E. J.

2015-12-01

Existing estimates of methane fluxes from wetlands differ in both magnitude and distribution across North America. We discuss seven different bottom-up methane estimates in the context of atmospheric methane data collected across the US and Canada. In the first component of this study, we explore whether the observation network can even detect a methane pattern from wetlands. We find that the observation network can identify a methane pattern from Canadian wetlands but not reliably from US wetlands. Over Canada, the network can even identify spatial patterns at multi-provence scales. Over the US, by contrast, anthropogenic emissions and modeling errors obscure atmospheric patterns from wetland fluxes. In the second component of the study, we then use these observations to reconcile disagreements in the magnitude, seasonal cycle, and spatial distribution of existing estimates. Most existing estimates predict fluxes that are too large with a seasonal cycle that is too narrow. A model known as LPJ-Bern has a spatial distribution most consistent with atmospheric observations. By contrast, a spatially-constant model outperforms the distribution of most existing flux estimates across Canada. The results presented here provide several pathways to reduce disagreements among existing wetland flux estimates across North America.

[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.

Relative influence of the components of timber harvest strategies on landscape pattern

Treesearch

Eric J. Gustafson

2007-01-01

Forest managers seek to produce healthy landscape patterns by implementing harvest strategies that are composed of multiple management components such as cutblock size, rotation length, even-aged or uneven-aged residual stand structure, conversion to plantations, and the spatial dispersion of harvest units. With use of the HARVEST model and neutral landscapes, a...

Climate and Human Pressure Constraints Co-Explain Regional Plant Invasion at Different Spatial Scales

PubMed Central

García-Baquero, Gonzalo; Caño, Lidia; Biurrun, Idoia; García-Mijangos, Itziar; Loidi, Javier; Herrera, Mercedes

2016-01-01

Alien species invasion represents a global threat to biodiversity and ecosystems. Explaining invasion patterns in terms of environmental constraints will help us to assess invasion risks and plan control strategies. We aim to identify plant invasion patterns in the Basque Country (Spain), and to determine the effects of climate and human pressure on that pattern. We modeled the regional distribution of 89 invasive plant species using two approaches. First, distance-based Moran’s eigenvector maps were used to partition variation in the invasive species richness, S, into spatial components at broad and fine scales; redundancy analysis was then used to explain those components on the basis of climate and human pressure descriptors. Second, we used generalized additive mixed modeling to fit species-specific responses to the same descriptors. Climate and human pressure descriptors have different effects on S at different spatial scales. Broad-scale spatially structured temperature and precipitation, and fine-scale spatially structured human population density and percentage of natural and semi-natural areas, explained altogether 38.7% of the total variance. The distribution of 84% of the individually tested species was related to either temperature, precipitation or both, and 68% was related to either population density or natural and semi-natural areas, displaying similar responses. The spatial pattern of the invasive species richness is strongly environmentally forced, mainly by climate factors. Since individual species responses were proved to be both similarly constrained in shape and explained variance by the same environmental factors, we conclude that the pattern of invasive species richness results from individual species’ environmental preferences. PMID:27741276

Age-associated patterns in gray matter volume, cerebral perfusion and BOLD oscillations in children and adolescents.

PubMed

Bray, Signe

2017-05-01

Healthy brain development involves changes in brain structure and function that are believed to support cognitive maturation. However, understanding how structural changes such as grey matter thinning relate to functional changes is challenging. To gain insight into structure-function relationships in development, the present study took a data driven approach to define age-related patterns of variation in gray matter volume (GMV), cerebral blood flow (CBF) and blood-oxygen level dependent (BOLD) signal variation (fractional amplitude of low-frequency fluctuations; fALFF) in 59 healthy children aged 7-18 years, and examined relationships between modalities. Principal components analysis (PCA) was applied to each modality in parallel, and participant scores for the top components were assessed for age associations. We found that decompositions of CBF, GMV and fALFF all included components for which scores were significantly associated with age. The dominant patterns in GMV and CBF showed significant (GMV) or trend level (CBF) associations with age and a strong spatial overlap, driven by increased signal intensity in default mode network (DMN) regions. GMV, CBF and fALFF additionally showed components accounting for 3-5% of variability with significant age associations. However, these patterns were relatively spatially independent, with small-to-moderate overlap between modalities. Independence of age effects was further demonstrated by correlating individual subject maps between modalities: CBF was significantly less correlated with GMV and fALFF in older children relative to younger. These spatially independent effects of age suggest that the parallel decline observed in global GMV and CBF may not reflect spatially synchronized processes. Hum Brain Mapp 38:2398-2407, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Detecting defective electrical components in heterogeneous infra-red images by spatial control charts

NASA Astrophysics Data System (ADS)

Jamshidieini, Bahman; Fazaee, Reza

2016-05-01

Distribution network components connect machines and other loads to electrical sources. If resistance or current of any component is more than specified range, its temperature may exceed the operational limit which can cause major problems. Therefore, these defects should be found and eliminated according to their severity. Although infra-red cameras have been used for inspection of electrical components, maintenance prioritization of distribution cubicles is mostly based on personal perception and lack of training data prevents engineers from developing image processing methods. New research on the spatial control chart encouraged us to use statistical approaches instead of the pattern recognition for the image processing. In the present study, a new scanning pattern which can tolerate heavy autocorrelation among adjacent pixels within infra-red image was developed and for the first time combination of kernel smoothing, spatial control charts and local robust regression were used for finding defects within heterogeneous infra-red images of old distribution cubicles. This method does not need training data and this advantage is crucially important when the training data is not available.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

A familiar pattern? Semantic memory contributes to the enhancement of visuo-spatial memories.

PubMed

Riby, Leigh M; Orme, Elizabeth

2013-03-01

In this study we quantify for the first time electrophysiological components associated with incorporating long-term semantic knowledge with visuo-spatial information using two variants of a traditional matrix patterns task. Results indicated that the matrix task with greater semantic content was associated with enhanced accuracy and RTs in a change-detection paradigm; this was also associated with increased P300 and N400 components as well as a sustained negative slow wave (NSW). In contrast, processing of the low semantic stimuli was associated with an increased N200 and a reduction in the P300. These findings suggest that semantic content can aid in reducing early visual processing of information and subsequent memory load by unitizing complex patterns into familiar forms. The N400/NSW may be associated with the requirements for maintaining visuo-spatial information about semantic forms such as orientation and relative location. Evidence for individual differences in semantic elaboration strategies used by participants is also discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

Spatial and temporal characterizations of water quality in Kuwait Bay.

PubMed

Al-Mutairi, N; Abahussain, A; El-Battay, A

2014-06-15

The spatial and temporal patterns of water quality in Kuwait Bay have been investigated using data from six stations between 2009 and 2011. The results showed that most of water quality parameters such as phosphorus (PO4), nitrate (NO3), dissolved oxygen (DO), and Total Suspended Solids (TSS) fluctuated over time and space. Based on Water Quality Index (WQI) data, six stations were significantly clustered into two main classes using cluster analysis, one group located in western side of the Bay, and other in eastern side. Three principal components are responsible for water quality variations in the Bay. The first component included DO and pH. The second included PO4, TSS and NO3, and the last component contained seawater temperature and turbidity. The spatial and temporal patterns of water quality in Kuwait Bay are mainly controlled by seasonal variations and discharges from point sources of pollution along Kuwait Bay's coast as well as from Shatt Al-Arab River. Copyright © 2014 Elsevier Ltd. All rights reserved.

Geostatistics, remote sensing and precision farming.

PubMed

Mulla, D J

1997-01-01

Precision farming is possible today because of advances in farming technology, procedures for mapping and interpolating spatial patterns, and geographic information systems for overlaying and interpreting several soil, landscape and crop attributes. The key component of precision farming is the map showing spatial patterns in field characteristics. Obtaining information for this map is often achieved by soil sampling. This approach, however, can be cost-prohibitive for grain crops. Soil sampling strategies can be simplified by use of auxiliary data provided by satellite or aerial photo imagery. This paper describes geostatistical methods for estimating spatial patterns in soil organic matter, soil test phosphorus and wheat grain yield from a combination of Thematic Mapper imaging and soil sampling.

[Research on the methods for multi-class kernel CSP-based feature extraction].

PubMed

Wang, Jinjia; Zhang, Lingzhi; Hu, Bei

2012-04-01

To relax the presumption of strictly linear patterns in the common spatial patterns (CSP), we studied the kernel CSP (KCSP). A new multi-class KCSP (MKCSP) approach was proposed in this paper, which combines the kernel approach with multi-class CSP technique. In this approach, we used kernel spatial patterns for each class against all others, and extracted signal components specific to one condition from EEG data sets of multiple conditions. Then we performed classification using the Logistic linear classifier. Brain computer interface (BCI) competition III_3a was used in the experiment. Through the experiment, it can be proved that this approach could decompose the raw EEG singles into spatial patterns extracted from multi-class of single trial EEG, and could obtain good classification results.

Visual and spatial working memory are not that dissociated after all: a time-based resource-sharing account.

PubMed

Vergauwe, Evie; Barrouillet, Pierre; Camos, Valérie

2009-07-01

Examinations of interference between visual and spatial materials in working memory have suggested domain- and process-based fractionations of visuo-spatial working memory. The present study examined the role of central time-based resource sharing in visuo-spatial working memory and assessed its role in obtained interference patterns. Visual and spatial storage were combined with both visual and spatial on-line processing components in computer-paced working memory span tasks (Experiment 1) and in a selective interference paradigm (Experiment 2). The cognitive load of the processing components was manipulated to investigate its impact on concurrent maintenance for both within-domain and between-domain combinations of processing and storage components. In contrast to both domain- and process-based fractionations of visuo-spatial working memory, the results revealed that recall performance was determined by the cognitive load induced by the processing of items, rather than by the domain to which those items pertained. These findings are interpreted as evidence for a time-based resource-sharing mechanism in visuo-spatial working memory.

Patterns of white matter damage are non-random and associated with cognitive function in secondary progressive multiple sclerosis.

PubMed

Meijer, K A; Cercignani, M; Muhlert, N; Sethi, V; Chard, D; Geurts, J J G; Ciccarelli, O

2016-01-01

In multiple sclerosis (MS), white matter damage is thought to contribute to cognitive dysfunction, which is especially prominent in secondary progressive MS (SPMS). While studies in healthy subjects have revealed patterns of correlated fractional anisotropy (FA) across white matter tracts, little is known about the underlying patterns of white matter damage in MS. In the present study, we aimed to map the SPMS-related covariance patterns of microstructural white matter changes, and investigated whether or not these patterns were associated with cognitive dysfunction. Diffusion MRI was acquired from 30 SPMS patients and 32 healthy controls (HC). A tensor model was fitted and FA maps were processed using tract-based spatial statistics (TBSS) in order to obtain a skeletonised map for each subject. The skeletonised FA maps of patients only were decomposed into 18 spatially independent components (ICs) using independent component analysis. Comprehensive cognitive assessment was conducted to evaluate five cognitive domains. Correlations between cognitive performance and (1) severity of FA abnormalities of the extracted ICs (i.e. z-scores relative to FA values of HC) and (2) IC load (i.e. FA covariance of a particular IC) were examined. SPMS patients showed lower FA values of all examined patterns of correlated FA (i.e. spatially independent components) than HC (p < 0.01). Tracts visually assigned to the supratentorial commissural class were most severely damaged (z = - 3.54; p < 0.001). Reduced FA was significantly correlated with reduced IC load (i.e. FA covariance) (r = 0.441; p < 0.05). Lower mean FA and component load of the supratentorial projection tracts and limbic association tracts classes were associated with worse cognitive function, including executive function, working memory and verbal memory. Despite the presence of white matter damage, it was possible to reveal patterns of FA covariance across SPMS patients. This could indicate that white matter tracts belonging to the same cluster, and thus with similar characteristics, tend to follow similar trends during neurodegeneration. Furthermore, these underlying FA patterns might help to explain cognitive dysfunction in SPMS.

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

Single-shot color fringe projection for three-dimensional shape measurement of objects with discontinuities.

PubMed

Dai, Meiling; Yang, Fujun; He, Xiaoyuan

2012-04-20

A simple but effective fringe projection profilometry is proposed to measure 3D shape by using one snapshot color sinusoidal fringe pattern. One color fringe pattern encoded with a sinusoidal fringe (as red component) and one uniform intensity pattern (as blue component) is projected by a digital video projector, and the deformed fringe pattern is recorded by a color CCD camera. The captured color fringe pattern is separated into its RGB components and division operation is applied to red and blue channels to reduce the variable reflection intensity. Shape information of the tested object is decoded by applying an arcsine algorithm on the normalized fringe pattern with subpixel resolution. In the case of fringe discontinuities caused by height steps, or spatially isolated surfaces, the separated blue component is binarized and used for correcting the phase demodulation. A simple and robust method is also introduced to compensate for nonlinear intensity response of the digital video projector. The experimental results demonstrate the validity of the proposed method.

Scanning digital lithography providing high speed large area patterning with diffraction limited sub-micron resolution

NASA Astrophysics Data System (ADS)

Wen, Sy-Bor; Bhaskar, Arun; Zhang, Hongjie

2018-07-01

A scanning digital lithography system using computer controlled digital spatial light modulator, spatial filter, infinity correct optical microscope and high precision translation stage is proposed and examined. Through utilizing the spatial filter to limit orders of diffraction modes for light delivered from the spatial light modulator, we are able to achieve diffraction limited deep submicron spatial resolution with the scanning digital lithography system by using standard one inch level optical components with reasonable prices. Raster scanning of this scanning digital lithography system using a high speed high precision x-y translation stage and piezo mount to real time adjust the focal position of objective lens allows us to achieve large area sub-micron resolved patterning with high speed (compared with e-beam lithography). It is determined in this study that to achieve high quality stitching of lithography patterns with raster scanning, a high-resolution rotation stage will be required to ensure the x and y directions of the projected pattern are in the same x and y translation directions of the nanometer precision x-y translation stage.

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

USGS Publications Warehouse

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

2006-01-01

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

Spatial noise in microdisplays for near-to-eye applications

NASA Astrophysics Data System (ADS)

Hastings, Arthur R., Jr.; Draper, Russell S.; Wood, Michael V.; Fellowes, David A.

2011-06-01

Spatial noise in imaging systems has been characterized and its impact on image quality metrics has been addressed primarily with respect to the introduction of this noise at the sensor component. However, sensor fixed pattern noise is not the only source of fixed pattern noise in an imaging system. Display fixed pattern noise cannot be easily mitigated in processing and, therefore, must be addressed. In this paper, a thorough examination of the amount and the effect of display fixed pattern noise is presented. The specific manifestation of display fixed pattern noise is dependent upon the display technology. Utilizing a calibrated camera, US Army RDECOM CERDEC NVESD has developed a microdisplay (μdisplay) spatial noise data collection capability. Noise and signal power spectra were used to characterize the display signal to noise ratio (SNR) as a function of spatial frequency analogous to the minimum resolvable temperature difference (MRTD) of a thermal sensor. The goal of this study is to establish a measurement technique to characterize μdisplay limiting performance to assist in proper imaging system specification.

Seasonal changes in spatial patterns of two annual plants in the Chihuahuan Desert, USA

USGS Publications Warehouse

Yin, Z.-Y.; Guo, Q.; Ren, H.; Peng, S.-L.

2005-01-01

Spatial pattern of a biotic population may change over time as its component individuals grow or die out, but whether this is the case for desert annual plants is largely unknown. Here we examined seasonal changes in spatial patterns of two annuals, Eriogonum abertianum and Haplopappus gracilis, in initial (winter) and final (summer) densities. The density was measured as the number of individuals from 384 permanent quadrats (each 0.5 m × 0.5 m) in the Chihuahuan Desert near Portal, Arizona, USA. We used three probability distributions (binomial, Poisson, and negative binomial or NB) that represent three basic spatial patterns (regular, random, and clumped) to fit the observed frequency distributions of densities of the two annuals. Both species showed clear clumped patterns as characterized by the NB and had similar inverse J-shaped frequency distribution curves in two density categories. Also, both species displayed a reduced degree of aggregation from winter to summer after the spring drought (massive die-off), as indicated by the increased k-parameter of the NB and decreased values of another NB parameter p, variance/mean ratio, Lloyd’s Index of Patchiness, and David and Moore’s Index of Clumping. Further, we hypothesized that while the NB (i.e., Poisson-logarithmic) well fits the distribution of individuals per quadrat, its components, the Poisson and logarithmic, may describe the distributions of clumps per quadrat and of individuals per clump, respectively. We thus obtained the means and variances for (1) individuals per quadrat, (2) clumps per quadrat, and (3) individuals per clump. The results showed that the decrease of the density from winter to summer for each plant resulted from the decrease of individuals per clump, rather than from the decrease of clumps per quadrat. The great similarities between the two annuals indicate that our observed temporal changes in spatial patterns may be common among desert annual plants.

Spatial eigenmodes and synchronous oscillation: co-incidence detection in simulated cerebral cortex.

PubMed

Chapman, Clare L; Wright, James J; Bourke, Paul D

2002-07-01

Zero-lag synchronisation arises between points on the cerebral cortex receiving concurrent independent inputs; an observation generally ascribed to nonlinear mechanisms. Using simulations of cerebral cortex and Principal Component Analysis (PCA) we show patterns of zero-lag synchronisation (associated with empirically realistic spectral content) can arise from both linear and nonlinear mechanisms. For low levels of activation, we show the synchronous field is described by the eigenmodes of the resultant damped wave activity. The first and second spatial eigenmodes (which capture most of the signal variance) arise from the even and odd components of the independent input signals. The pattern of zero-lag synchronisation can be accounted for by the relative dominance of the first mode over the second, in the near-field of the inputs. The simulated cortical surface can act as a few millisecond response coincidence detector for concurrent, but uncorrelated, inputs. As cortical activation levels are increased, local damped oscillations in the gamma band undergo a transition to highly nonlinear undamped activity with 40 Hz dominant frequency. This is associated with "locking" between active sites and spatially segregated phase patterns. The damped wave synchronisation and the locked nonlinear oscillations may combine to permit fast representation of multiple patterns of activity within the same field of neurons.

Assessment of Change in Green Infrastructure Components Using Morphological Spatial Pattern Analysis for the Conterminous United States

EPA Science Inventory

Green infrastructure is a widely used framework for conservation planning in the United States and elsewhere. The main components of green infrastructure are hubs and corridors. Hubs are large areas of natural vegetation, and corridors are linear features that connect hubs. W...

Investigating univariate temporal patterns for intrinsic connectivity networks based on complexity and low-frequency oscillation: a test-retest reliability study.

PubMed

Wang, X; Jiao, Y; Tang, T; Wang, H; Lu, Z

2013-12-19

Intrinsic connectivity networks (ICNs) are composed of spatial components and time courses. The spatial components of ICNs were discovered with moderate-to-high reliability. So far as we know, few studies focused on the reliability of the temporal patterns for ICNs based their individual time courses. The goals of this study were twofold: to investigate the test-retest reliability of temporal patterns for ICNs, and to analyze these informative univariate metrics. Additionally, a correlation analysis was performed to enhance interpretability. Our study included three datasets: (a) short- and long-term scans, (b) multi-band echo-planar imaging (mEPI), and (c) eyes open or closed. Using dual regression, we obtained the time courses of ICNs for each subject. To produce temporal patterns for ICNs, we applied two categories of univariate metrics: network-wise complexity and network-wise low-frequency oscillation. Furthermore, we validated the test-retest reliability for each metric. The network-wise temporal patterns for most ICNs (especially for default mode network, DMN) exhibited moderate-to-high reliability and reproducibility under different scan conditions. Network-wise complexity for DMN exhibited fair reliability (ICC<0.5) based on eyes-closed sessions. Specially, our results supported that mEPI could be a useful method with high reliability and reproducibility. In addition, these temporal patterns were with physiological meanings, and certain temporal patterns were correlated to the node strength of the corresponding ICN. Overall, network-wise temporal patterns of ICNs were reliable and informative and could be complementary to spatial patterns of ICNs for further study. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Method and apparatus for fiber optic multiple scattering suppression

NASA Technical Reports Server (NTRS)

Ackerson, Bruce J. (Inventor)

2000-01-01

The instant invention provides a method and apparatus for use in laser induced dynamic light scattering which attenuates the multiple scattering component in favor of the single scattering component. The preferred apparatus utilizes two light detectors that are spatially and/or angularly separated and which simultaneously record the speckle pattern from a single sample. The recorded patterns from the two detectors are then cross correlated in time to produce one point on a composite single/multiple scattering function curve. By collecting and analyzing cross correlation measurements that have been taken at a plurality of different spatial/angular positions, the signal representative of single scattering may be differentiated from the signal representative of multiple scattering, and a near optimum detector separation angle for use in taking future measurements may be determined.

Optical processing for landmark identification

NASA Technical Reports Server (NTRS)

Casasent, D.; Luu, T. K.

1981-01-01

A study of optical pattern recognition techniques, available components and airborne optical systems for use in landmark identification was conducted. A data base of imagery exhibiting multisensor, seasonal, snow and fog cover, exposure, and other differences was assembled. These were successfully processed in a scaling optical correlator using weighted matched spatial filter synthesis. Distinctive data classes were defined and a description of the data (with considerable input information and content information) emerged from this study. It has considerable merit with regard to the preprocessing needed and the image difference categories advanced. A optical pattern recognition airborne applications was developed, assembled and demontrated. It employed a laser diode light source and holographic optical elements in a new lensless matched spatial filter architecture with greatly reduced size and weight, as well as component positioning toleranced.

Spatial Factors Play a Major Role as Determinants of Endemic Ground Beetle Beta Diversity of Madeira Island Laurisilva

PubMed Central

Boieiro, Mário; Carvalho, José C.; Cardoso, Pedro; Aguiar, Carlos A. S.; Rego, Carla; de Faria e Silva, Israel; Amorim, Isabel R.; Pereira, Fernando; Azevedo, Eduardo B.; Borges, Paulo A. V.; Serrano, Artur R. M.

2013-01-01

The development in recent years of new beta diversity analytical approaches highlighted valuable information on the different processes structuring ecological communities. A crucial development for the understanding of beta diversity patterns was also its differentiation in two components: species turnover and richness differences. In this study, we evaluate beta diversity patterns of ground beetles from 26 sites in Madeira Island distributed throughout Laurisilva – a relict forest restricted to the Macaronesian archipelagos. We assess how the two components of ground beetle beta diversity (βrepl – species turnover and βrich - species richness differences) relate with differences in climate, geography, landscape composition matrix, woody plant species richness and soil characteristics and the relative importance of the effects of these variables at different spatial scales. We sampled 1025 specimens from 31 species, most of which are endemic to Madeira Island. A spatially explicit analysis was used to evaluate the contribution of pure environmental, pure spatial and environmental spatially structured effects on variation in ground beetle species richness and composition. Variation partitioning showed that 31.9% of species turnover (βrepl) and 40.7% of species richness variation (βrich) could be explained by the environmental and spatial variables. However, different environmental variables controlled the two types of beta diversity: βrepl was influenced by climate, disturbance and soil organic matter content whilst βrich was controlled by altitude and slope. Furthermore, spatial variables, represented through Moran’s eigenvector maps, played a significant role in explaining both βrepl and βrich, suggesting that both dispersal ability and Madeira Island complex orography are crucial for the understanding of beta diversity patterns in this group of beetles. PMID:23724065

Increasing the space-time product of super-resolution structured illumination microscopy by means of two-pattern illumination

NASA Astrophysics Data System (ADS)

Inochkin, F. M.; Pozzi, P.; Bezzubik, V. V.; Belashenkov, N. R.

2017-06-01

Superresolution image reconstruction method based on the structured illumination microscopy (SIM) principle with reduced and simplified pattern set is presented. The method described needs only 2 sinusoidal patterns shifted by half a period for each spatial direction of reconstruction, instead of the minimum of 3 for the previously known methods. The method is based on estimating redundant frequency components in the acquired set of modulated images. Digital processing is based on linear operations. When applied to several spatial orientations, the image set can be further reduced to a single pattern for each spatial orientation, complemented by a single non-modulated image for all the orientations. By utilizing this method for the case of two spatial orientations, the total input image set is reduced up to 3 images, providing up to 2-fold improvement in data acquisition time compared to the conventional 3-pattern SIM method. Using the simplified pattern design, the field of view can be doubled with the same number of spatial light modulator raster elements, resulting in a total 4-fold increase in the space-time product. The method requires precise knowledge of the optical transfer function (OTF). The key limitation is the thickness of object layer that scatters or emits light, which requires to be sufficiently small relatively to the lens depth of field. Numerical simulations and experimental results are presented. Experimental results are obtained on the SIM setup with the spatial light modulator based on the 1920x1080 digital micromirror device.

Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations

PubMed Central

Gurunathan, Rajalakshmi; Van Emden, Bernard; Panchanathan, Sethuraman; Kumar, Sudhir

2004-01-01

Background Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns. Results The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches. Conclusions We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns. PMID:15603586

Influence of Different Factors on Relative Air Humidity in Zaragoza, Spain

NASA Astrophysics Data System (ADS)

Cuadrat, José M.

2015-03-01

In this study, the spatial patterns of relative air humidity and its relation to urban, geographical and meteorological factors in the city of Zaragoza (Spain) is discussed. We created a relative humidity database by means of 32 urban transects. Data were taken on different days and with different weather types. This data set was used to map the mean spatial distribution of urban dry island (UDI). Using stepwise multiple regression analysis and Landsat ETM+ images the relationships between mean UDI and the main geographic-urban factors: topography, land cover and surface reflectivity, have been analyzed. Different spatial patterns of UDI were determined using Principal Component Analysis (Varimax rotation). The three components extracted accounted for 91% of the total variance. PC1 accounted for the most general patterns (similar to mean UDI); PC2 showed a shift of dry areas to the SE and PC3 a shift to NW. Using data on wind direction in Zaragoza, we have found that the displacement of dry areas to the SE (PC 2) was greater during NW winds while the shift to the NW (PC 3) was produced mainly by SE winds.

Electrode channel selection based on backtracking search optimization in motor imagery brain-computer interfaces.

PubMed

Dai, Shengfa; Wei, Qingguo

2017-01-01

Common spatial pattern algorithm is widely used to estimate spatial filters in motor imagery based brain-computer interfaces. However, use of a large number of channels will make common spatial pattern tend to over-fitting and the classification of electroencephalographic signals time-consuming. To overcome these problems, it is necessary to choose an optimal subset of the whole channels to save computational time and improve the classification accuracy. In this paper, a novel method named backtracking search optimization algorithm is proposed to automatically select the optimal channel set for common spatial pattern. Each individual in the population is a N-dimensional vector, with each component representing one channel. A population of binary codes generate randomly in the beginning, and then channels are selected according to the evolution of these codes. The number and positions of 1's in the code denote the number and positions of chosen channels. The objective function of backtracking search optimization algorithm is defined as the combination of classification error rate and relative number of channels. Experimental results suggest that higher classification accuracy can be achieved with much fewer channels compared to standard common spatial pattern with whole channels.

Inferring Processes from Spatial Patterns: The Role of Directional and Non–Directional Forces in Shaping Fish Larvae Distribution in a Freshwater Lake System

PubMed Central

Bertolo, Andrea; Blanchet, F. Guillaume; Magnan, Pierre; Brodeur, Philippe; Mingelbier, Marc; Legendre, Pierre

2012-01-01

Larval dispersal is a crucial factor for fish recruitment. For fishes with relatively small-bodied larvae, drift has the potential to play a more important role than active habitat selection in determining larval dispersal; therefore, we expect small-bodied fish larvae to be poorly associated with habitat characteristics. To test this hypothesis, we used as model yellow perch (Perca flavescens), whose larvae are among the smallest among freshwater temperate fishes. Thus, we analysed the habitat association of yellow perch larvae at multiple spatial scales in a large shallow fluvial lake by explicitly modelling directional (e.g. due to water currents) and non-directional (e.g. due to aggregation) spatial patterns. This allowed us to indirectly assess the relative roles of drift (directional process) and potential habitat choice on larval dispersal. Our results give weak support to the drift hypothesis, whereas yellow perch show a strong habitat association at unexpectedly small sizes, when compared to other systems. We found consistent non-directional patterns in larvae distributions at both broad and medium spatial scales but only few significant directional components. The environmental variables alone (e.g. vegetation) generally explained a significant and biologically relevant fraction of the variation in fish larvae distribution data. These results suggest that (i) drift plays a minor role in this shallow system, (ii) larvae display spatial patterns that only partially covary with environmental variables, and (iii) larvae are associated to specific habitats. By suggesting that habitat association potentially includes an active choice component for yellow perch larvae, our results shed new light on the ecology of freshwater fish larvae and should help in building more realistic recruitment models. PMID:23185585

Distribution patterns of the crab Ucides cordatus (Brachyura, Ucididae) at different spatial scales in subtropical mangroves of Paranaguá Bay (southern Brazil)

NASA Astrophysics Data System (ADS)

Sandrini-Neto, L.; Lana, P. C.

2012-06-01

Heterogeneity in the distribution of organisms occurs at a range of spatial scales, which may vary from few centimeters to hundreds of kilometers. The exclusion of small-scale variability from routine sampling designs may confound comparisons at larger scales and lead to inconsistent interpretation of data. Despite its ecological and social-economic importance, little is known about the spatial structure of the mangrove crab Ucides cordatus in the southwest Atlantic. Previous studies have commonly compared densities at relatively broad scales, relying on alleged distribution patterns (e.g., mangroves of distinct composition and structure). We have assessed variability patterns of U. cordatus in mangroves of Paranaguá Bay at four levels of spatial hierarchy (10 s km, km, 10 s m and m) using a nested ANOVA and variance components measures. The potential role of sediment parameters, pneumatophore density, and organic matter content in regulating observed patterns was assessed by multiple regression models. Densities of total and non-commercial size crabs varied mostly at 10 s m to km scales. Densities of commercial size crabs differed at the scales of 10 s m and 10 s km. Variance components indicated that small-scale variation was the most important, contributing up to 70% of the crab density variability. Multiple regression models could not explain the observed variations. Processes driving differences in crab abundance were not related to the measured variables. Small-scale patchy distribution has direct implications to current management practices of U. cordatus. Future studies should consider processes operating at smaller scales, which are responsible for a complex mosaic of patches within previously described patterns.

Revealing Beta-Diversity Patterns of Breeding Bird and Lizard Communities on Inundated Land-Bridge Islands by Separating the Turnover and Nestedness Components

PubMed Central

Si, Xingfeng; Baselga, Andrés; Ding, Ping

2015-01-01

Beta diversity describes changes in species composition among sites in a region and has particular relevance for explaining ecological patterns in fragmented habitats. However, it is difficult to reveal the mechanisms if broad sense beta-diversity indices (i.e. yielding identical values under nestedness and species replacement) are used. Partitioning beta diversity into turnover (caused by species replacement from site to site) and nestedness-resultant components (caused by nested species losses) could provide a unique way to understand the variation of species composition in fragmented habitats. Here, we collected occupancy data of breeding birds and lizards on land-bridge islands in an inundated lake in eastern China. We decomposed beta diversity of breeding bird and lizard communities into spatial turnover and nestedness-resultant components to assess their relative contributions and respective relationships to differences in island area, isolation, and habitat richness. Our results showed that spatial turnover contributed more to beta diversity than the nestedness-resultant component. The degree of isolation had no significant effect on overall beta diversity or its components, neither for breeding birds nor for lizards. In turn, in both groups the nestedness-resultant component increased with larger differences in island area and habitat richness, respectively, while turnover component decreased with them. The major difference among birds and lizards was a higher relevance of nestedness-resultant dissimilarity in lizards, suggesting that they are more prone to local extinctions derived from habitat fragmentation. The dominance of the spatial turnover component of beta diversity suggests that all islands have potential conservation value for breeding bird and lizard communities. PMID:25992559

Fluorescent components and spatial patterns of chromophoric dissolved organic matters in Lake Taihu, a large shallow eutrophic lake in China.

PubMed

Yao, Bo; Hu, Chunming; Liu, Qingquan

2016-11-01

Water samples at both surface and bottom layers were taken from 102 sites in Lake Taihu to study the fluorescent components and spatial patterns of chromophoric dissolved organic matters (CDOM). Three-dimensional excitation-emission matrix data obtained from the samples were analyzed by parallel factor approach in which four humic-like and two protein-like fluorescent components (named C1-C6) were identified. The results showed that fluorescence intensities were higher in the northern and western lake regions, and notable declines of fluorescence maxima (F max ) were observed from the northwest to the center and then to the southeast of the lake. Calculated biological index (BIX) values ranged from 0.88 to 1.44 and humification index (HIX) values from 0.64 to 3.37 for all the samples. The spatial variations of BIX and HIX values suggested stronger allochthonous CDOM characteristics in Zhushan Bay and the western area and autochthonous characteristics in the southern and eastern areas. Vertically, the average F max value of the surface samples was about 6 % less than that of the bottom samples, but noticeable variations existed among different sampling sites and components. These distribution characteristics of CDOM were mainly attributed to the spatial heterogeneity of sources and wind-induced transportation process. Interestingly, the C6 component (Ex max /Em max  = 250/455 nm) seemed to be unique in samples from Zhushan Bay and probably resulted from the discharge of the Taige River. Therefore, it could be used as an indicator of point-source discharge and a tracer to study the fate of CDOM in the lake.

The spatial pattern of suicide in the US in relation to deprivation, fragmentation and rurality.

PubMed

Congdon, Peter

2011-01-01

Analysis of geographical patterns of suicide and psychiatric morbidity has demonstrated the impact of latent ecological variables (such as deprivation, rurality). Such latent variables may be derived by conventional multivariate techniques from sets of observed indices (for example, by principal components), by composite variable methods or by methods which explicitly consider the spatial framework of areas and, in particular, the spatial clustering of latent risks and outcomes. This article considers a latent random variable approach to explaining geographical contrasts in suicide in the US; and it develops a spatial structural equation model incorporating deprivation, social fragmentation and rurality. The approach allows for such latent spatial constructs to be correlated both within and between areas. Potential effects of area ethnic mix are also included. The model is applied to male and female suicide deaths over 2002–06 in 3142 US counties.

Climatic and Landscape Influences on Fire Regimes from 1984 to 2010 in the Western United States

PubMed Central

Liu, Zhihua; Wimberly, Michael C.

2015-01-01

An improved understanding of the relative influences of climatic and landscape controls on multiple fire regime components is needed to enhance our understanding of modern fire regimes and how they will respond to future environmental change. To address this need, we analyzed the spatio-temporal patterns of fire occurrence, size, and severity of large fires (> 405 ha) in the western United States from 1984–2010. We assessed the associations of these fire regime components with environmental variables, including short-term climate anomalies, vegetation type, topography, and human influences, using boosted regression tree analysis. Results showed that large fire occurrence, size, and severity each exhibited distinctive spatial and spatio-temporal patterns, which were controlled by different sets of climate and landscape factors. Antecedent climate anomalies had the strongest influences on fire occurrence, resulting in the highest spatial synchrony. In contrast, climatic variability had weaker influences on fire size and severity and vegetation types were the most important environmental determinants of these fire regime components. Topography had moderately strong effects on both fire occurrence and severity, and human influence variables were most strongly associated with fire size. These results suggest a potential for the emergence of novel fire regimes due to the responses of fire regime components to multiple drivers at different spatial and temporal scales. Next-generation approaches for projecting future fire regimes should incorporate indirect climate effects on vegetation type changes as well as other landscape effects on multiple components of fire regimes. PMID:26465959

Estimating spatially distributed soil texture using time series of thermal remote sensing - a case study in central Europe

NASA Astrophysics Data System (ADS)

Müller, Benjamin; Bernhardt, Matthias; Jackisch, Conrad; Schulz, Karsten

2016-09-01

For understanding water and solute transport processes, knowledge about the respective hydraulic properties is necessary. Commonly, hydraulic parameters are estimated via pedo-transfer functions using soil texture data to avoid cost-intensive measurements of hydraulic parameters in the laboratory. Therefore, current soil texture information is only available at a coarse spatial resolution of 250 to 1000 m. Here, a method is presented to derive high-resolution (15 m) spatial topsoil texture patterns for the meso-scale Attert catchment (Luxembourg, 288 km2) from 28 images of ASTER (advanced spaceborne thermal emission and reflection radiometer) thermal remote sensing. A principle component analysis of the images reveals the most dominant thermal patterns (principle components, PCs) that are related to 212 fractional soil texture samples. Within a multiple linear regression framework, distributed soil texture information is estimated and related uncertainties are assessed. An overall root mean squared error (RMSE) of 12.7 percentage points (pp) lies well within and even below the range of recent studies on soil texture estimation, while requiring sparser sample setups and a less diverse set of basic spatial input. This approach will improve the generation of spatially distributed topsoil maps, particularly for hydrologic modeling purposes, and will expand the usage of thermal remote sensing products.

Obstacle detection by recognizing binary expansion patterns

NASA Technical Reports Server (NTRS)

Baram, Yoram; Barniv, Yair

1993-01-01

This paper describes a technique for obstacle detection, based on the expansion of the image-plane projection of a textured object, as its distance from the sensor decreases. Information is conveyed by vectors whose components represent first-order temporal and spatial derivatives of the image intensity, which are related to the time to collision through the local divergence. Such vectors may be characterized as patterns corresponding to 'safe' or 'dangerous' situations. We show that essential information is conveyed by single-bit vector components, representing the signs of the relevant derivatives. We use two recently developed, high capacity classifiers, employing neural learning techniques, to recognize the imminence of collision from such patterns.

Components of spatial and temporal soil variation at Canyonlands National Park: Implications for P dynamics and cheatgrass (Bromus tectorum) performance

Treesearch

Mark Miller; Jayne Belnap; Susan Beatty; Bruce Webb

2001-01-01

From January 1997 through October 1998, research was conducted at Canyonlands National Park to investigate soil traits responsible for distinct spatial patterns of cheatgrass (Bromus tectorum) occurrence. Field experiments were conducted at sites representing a broad range of soil conditions and cheatgrass abundances. Standard physicochemical soil measures in...

Spatial patterns of soil moisture connected to monthly-seasonal precipitation variability in a monsoon region

Treesearch

Yongqiang Liu

2003-01-01

The relations between monthly-seasonal soil moisture and precipitation variability are investigated by identifying the coupled patterns of the two hydrological fields using singular value decomposition (SVD). SVD is a technique of principal component analysis similar to empirical orthogonal knctions (EOF). However, it is applied to two variables simultaneously and is...

Generation mechanisms of fundamental rogue wave spatial-temporal structure.

PubMed

Ling, Liming; Zhao, Li-Chen; Yang, Zhan-Ying; Guo, Boling

2017-08-01

We discuss the generation mechanism of fundamental rogue wave structures in N-component coupled systems, based on analytical solutions of the nonlinear Schrödinger equation and modulational instability analysis. Our analysis discloses that the pattern of a fundamental rogue wave is determined by the evolution energy and growth rate of the resonant perturbation that is responsible for forming the rogue wave. This finding allows one to predict the rogue wave pattern without the need to solve the N-component coupled nonlinear Schrödinger equation. Furthermore, our results show that N-component coupled nonlinear Schrödinger systems may possess N different fundamental rogue wave patterns at most. These results can be extended to evaluate the type and number of fundamental rogue wave structure in other coupled nonlinear systems.

Self-aligned spatial filtering using laser optical tweezers.

PubMed

Birkbeck, Aaron L; Zlatanovic, Sanja; Esener, Sadik C

2006-09-01

We present an optical spatial filtering device that has been integrated into a microfluidic system and whose motion and alignment is controlled using a laser optical tweezer. The lithographically patterned micro-optical spatial filter device filters out higher frequency additive noise components by automatically aligning itself in three dimensions to the focus of the laser beam. This self-alignment capability is achieved through the attachment of a refractive optical element directly over the circular aperture or pinhole of the spatial filter. A discussion of two different spatial filter designs is presented along with experimental results that demonstrate the effectiveness of the self-aligned micro-optic spatial filter.

An analysis of tree mortality using high resolution remotely-sensed data for mixed-conifer forests in San Diego county

NASA Astrophysics Data System (ADS)

Freeman, Mary Pyott

ABSTRACT An Analysis of Tree Mortality Using High Resolution Remotely-Sensed Data for Mixed-Conifer Forests in San Diego County by Mary Pyott Freeman The montane mixed-conifer forests of San Diego County are currently experiencing extensive tree mortality, which is defined as dieback where whole stands are affected. This mortality is likely the result of the complex interaction of many variables, such as altered fire regimes, climatic conditions such as drought, as well as forest pathogens and past management strategies. Conifer tree mortality and its spatial pattern and change over time were examined in three components. In component 1, two remote sensing approaches were compared for their effectiveness in delineating dead trees, a spatial contextual approach and an OBIA (object based image analysis) approach, utilizing various dates and spatial resolutions of airborne image data. For each approach transforms and masking techniques were explored, which were found to improve classifications, and an object-based assessment approach was tested. In component 2, dead tree maps produced by the most effective techniques derived from component 1 were utilized for point pattern and vector analyses to further understand spatio-temporal changes in tree mortality for the years 1997, 2000, 2002, and 2005 for three study areas: Palomar, Volcan and Laguna mountains. Plot-based fieldwork was conducted to further assess mortality patterns. Results indicate that conifer mortality was significantly clustered, increased substantially between 2002 and 2005, and was non-random with respect to tree species and diameter class sizes. In component 3, multiple environmental variables were used in Generalized Linear Model (GLM-logistic regression) and decision tree classifier model development, revealing the importance of climate and topographic factors such as precipitation and elevation, in being able to predict areas of high risk for tree mortality. The results from this study highlight the importance of multi-scale spatial as well as temporal analyses, in order to understand mixed-conifer forest structure, dynamics, and processes of decline, which can lead to more sustainable management of forests with continued natural and anthropogenic disturbance.

Regionalization of precipitation characteristics in Iran's Lake Urmia basin

NASA Astrophysics Data System (ADS)

Fazel, Nasim; Berndtsson, Ronny; Uvo, Cintia Bertacchi; Madani, Kaveh; Kløve, Bjørn

2018-04-01

Lake Urmia in northwest Iran, once one of the largest hypersaline lakes in the world, has shrunk by almost 90% in area and 80% in volume during the last four decades. To improve the understanding of regional differences in water availability throughout the region and to refine the existing information on precipitation variability, this study investigated the spatial pattern of precipitation for the Lake Urmia basin. Daily rainfall time series from 122 precipitation stations with different record lengths were used to extract 15 statistical descriptors comprising 25th percentile, 75th percentile, and coefficient of variation for annual and seasonal total precipitation. Principal component analysis in association with cluster analysis identified three main homogeneous precipitation groups in the lake basin. The first sub-region (group 1) includes stations located in the center and southeast; the second sub-region (group 2) covers mostly northern and northeastern part of the basin, and the third sub-region (group 3) covers the western and southern edges of the basin. Results of principal component (PC) and clustering analyses showed that seasonal precipitation variation is the most important feature controlling the spatial pattern of precipitation in the lake basin. The 25th and 75th percentiles of winter and autumn are the most important variables controlling the spatial pattern of the first rotated principal component explaining about 32% of the total variance. Summer and spring precipitation variations are the most important variables in the second and third rotated principal components, respectively. Seasonal variation in precipitation amount and seasonality are explained by topography and influenced by the lake and westerly winds that are related to the strength of the North Atlantic Oscillation. Despite using incomplete time series with different lengths, the identified sub-regions are physically meaningful.

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

PubMed

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

2017-09-01

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

Free-standing carbon nanotube composite sensing skin for distributed strain sensing in structures

NASA Astrophysics Data System (ADS)

Burton, Andrew R.; Minegishi, Kaede; Kurata, Masahiro; Lynch, Jerome P.

2014-04-01

The technical challenges of managing the health of critical infrastructure systems necessitate greater structural sensing capabilities. Among these needs is the ability for quantitative, spatial damage detection on critical structural components. Advances in material science have now opened the door for novel and cost-effective spatial sensing solutions specially tailored for damage detection in structures. However, challenges remain before spatial damage detection can be realized. Some of the technical challenges include sensor installations and extensive signal processing requirements. This work addresses these challenges by developing a patterned carbon nanotube composite thin film sensor whose pattern has been optimized for measuring the spatial distribution of strain. The carbon nanotube-polymer nanocomposite sensing material is fabricated on a flexible polyimide substrate using a layer-by-layer deposition process. The thin film sensors are then patterned into sensing elements using optical lithography processes common to microelectromechanical systems (MEMS) technologies. The sensor array is designed as a series of sensing elements with varying width to provide insight on the limitations of such patterning and implications of pattern geometry on sensing signals. Once fabrication is complete, the substrate and attached sensor are epoxy bonded to a poly vinyl composite (PVC) bar that is then tested with a uniaxial, cyclic load pattern and mechanical response is characterized. The fabrication processes are then utilized on a larger-scale to develop and instrument a component-specific sensing skin in order to observe the strain distribution on the web of a steel beam. The instrumented beam is part of a larger steel beam-column connection with a concrete slab in composite action. The beam-column subassembly is laterally loaded and strain trends in the web are observed using the carbon nanotube composite sensing skin. The results are discussed in the context of understanding the properties of the thin film sensor and how it may be advanced toward structural sensing applications.

Enhanced dual-frequency pattern scheme based on spatial-temporal fringes method

NASA Astrophysics Data System (ADS)

Wang, Minmin; Zhou, Canlin; Si, Shuchun; Lei, Zhenkun; Li, Xiaolei; Li, Hui; Li, YanJie

2018-07-01

One of the major challenges of employing a dual-frequency phase-shifting algorithm for phase retrieval is its sensitivity to noise. Yun et al proposed a dual-frequency method based on the Fourier transform profilometry, yet the low-frequency lobes are close to each other for accurate band-pass filtering. In the light of this problem, a novel dual-frequency pattern based on the spatial-temporal fringes (STF) method is developed in this paper. Three fringe patterns with two different frequencies are required. The low-frequency phase is obtained from two low-frequency fringe patterns by the STF method, so the signal lobes can be extracted accurately as they are far away from each other. The high-frequency phase is retrieved from another fringe pattern without the impact of the DC component. Simulations and experiments are conducted to demonstrate the excellent precision of the proposed method.

Patterns of fish community composition along a river affected by agricultural and urban disturbance in south-central Chile

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

Orrego, Rodrigo; Barra, Ricardo; Chiang, Gustavo

2008-03-01

Patterns of fish community composition in a south-central Chile river were investigated along the altitudinal-spatial and environmental gradient and as a function of anthropogenic factors. The spatial pattern of fish communities in different biocoenotic zones of the Chillan River is influenced by both natural factors such a hydrologic features, habitat, and feeding types, and also by water quality variables which can reduce the diversity and abundance of sensitive species. A principal component analysis incorporating both water quality parameters and biomarker responses of representative fish species was used to evaluate the status of fish communities along the spatial gradient of themore » stream. The abundance and diversity of the fish community changed from a low in the upper reaches where the low pollution-tolerant species such as salmonid dominated, to a reduced diversity in the lower reaches of the river where tolerant browser species such as cypriniformes dominated. Even though the spatial pattern of fish community structure is similar to that found for the Chilean Rivers, the structure of these communities is highly influenced by human disturbance, particularly along the lower reaches of the river.« less

A hierarchical approach to forest landscape pattern characterization.

PubMed

Wang, Jialing; Yang, Xiaojun

2012-01-01

Landscape spatial patterns have increasingly been considered to be essential for environmental planning and resources management. In this study, we proposed a hierarchical approach for landscape classification and evaluation by characterizing landscape spatial patterns across different hierarchical levels. The case study site is the Red Hills region of northern Florida and southwestern Georgia, well known for its biodiversity, historic resources, and scenic beauty. We used one Landsat Enhanced Thematic Mapper image to extract land-use/-cover information. Then, we employed principal-component analysis to help identify key class-level landscape metrics for forests at different hierarchical levels, namely, open pine, upland pine, and forest as a whole. We found that the key class-level landscape metrics varied across different hierarchical levels. Compared with forest as a whole, open pine forest is much more fragmented. The landscape metric, such as CONTIG_MN, which measures whether pine patches are contiguous or not, is more important to characterize the spatial pattern of pine forest than to forest as a whole. This suggests that different metric sets should be used to characterize landscape patterns at different hierarchical levels. We further used these key metrics, along with the total class area, to classify and evaluate subwatersheds through cluster analysis. This study demonstrates a promising approach that can be used to integrate spatial patterns and processes for hierarchical forest landscape planning and management.

Pattern classification of fMRI data: applications for analysis of spatially distributed cortical networks.

PubMed

Yourganov, Grigori; Schmah, Tanya; Churchill, Nathan W; Berman, Marc G; Grady, Cheryl L; Strother, Stephen C

2014-08-01

The field of fMRI data analysis is rapidly growing in sophistication, particularly in the domain of multivariate pattern classification. However, the interaction between the properties of the analytical model and the parameters of the BOLD signal (e.g. signal magnitude, temporal variance and functional connectivity) is still an open problem. We addressed this problem by evaluating a set of pattern classification algorithms on simulated and experimental block-design fMRI data. The set of classifiers consisted of linear and quadratic discriminants, linear support vector machine, and linear and nonlinear Gaussian naive Bayes classifiers. For linear discriminant, we used two methods of regularization: principal component analysis, and ridge regularization. The classifiers were used (1) to classify the volumes according to the behavioral task that was performed by the subject, and (2) to construct spatial maps that indicated the relative contribution of each voxel to classification. Our evaluation metrics were: (1) accuracy of out-of-sample classification and (2) reproducibility of spatial maps. In simulated data sets, we performed an additional evaluation of spatial maps with ROC analysis. We varied the magnitude, temporal variance and connectivity of simulated fMRI signal and identified the optimal classifier for each simulated environment. Overall, the best performers were linear and quadratic discriminants (operating on principal components of the data matrix) and, in some rare situations, a nonlinear Gaussian naïve Bayes classifier. The results from the simulated data were supported by within-subject analysis of experimental fMRI data, collected in a study of aging. This is the first study that systematically characterizes interactions between analysis model and signal parameters (such as magnitude, variance and correlation) on the performance of pattern classifiers for fMRI. Copyright © 2014 Elsevier Inc. All rights reserved.

Spatial distribution of ammonia-oxidizing bacteria and archaea across a 44-hectare farm related to ecosystem functioning

PubMed Central

Wessén, Ella; Söderström, Mats; Stenberg, Maria; Bru, David; Hellman, Maria; Welsh, Allana; Thomsen, Frida; Klemedtson, Leif; Philippot, Laurent; Hallin, Sara

2011-01-01

Characterization of spatial patterns of functional microbial communities could facilitate the understanding of the relationships between the ecology of microbial communities, the biogeochemical processes they perform and the corresponding ecosystem functions. Because of the important role the ammonia-oxidizing bacteria (AOB) and archaea (AOA) have in nitrogen cycling and nitrate leaching, we explored the spatial distribution of their activity, abundance and community composition across a 44-ha large farm divided into an organic and an integrated farming system. The spatial patterns were mapped by geostatistical modeling and correlations to soil properties and ecosystem functioning in terms of nitrate leaching were determined. All measured community components for both AOB and AOA exhibited spatial patterns at the hectare scale. The patchy patterns of community structures did not reflect the farming systems, but the AOB community was weakly related to differences in soil pH and moisture, whereas the AOA community to differences in soil pH and clay content. Soil properties related differently to the size of the communities, with soil organic carbon and total nitrogen correlating positively to AOB abundance, while clay content and pH showed a negative correlation to AOA abundance. Contrasting spatial patterns were observed for the abundance distributions of the two groups indicating that the AOB and AOA may occupy different niches in agro-ecosystems. In addition, the two communities correlated differently to community and ecosystem functions. Our results suggest that the AOA, not the AOB, were contributing to nitrate leaching at the site by providing substrate for the nitrite oxidizers. PMID:21228891

Two-component vector solitons in defocusing Kerr-type media with spatially modulated nonlinearity

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

Zhong, Wei-Ping, E-mail: zhongwp6@126.com; Texas A and M University at Qatar, P.O. Box 23874 Doha; Belić, Milivoj

2014-12-15

We present a class of exact solutions to the coupled (2+1)-dimensional nonlinear Schrödinger equation with spatially modulated nonlinearity and a special external potential, which describe the evolution of two-component vector solitons in defocusing Kerr-type media. We find a robust soliton solution, constructed with the help of Whittaker functions. For specific choices of the topological charge, the radial mode number and the modulation depth, the solitons may exist in various forms, such as the half-moon, necklace-ring, and sawtooth vortex-ring patterns. Our results show that the profile of such solitons can be effectively controlled by the topological charge, the radial mode number,more » and the modulation depth. - Highlights: • Two-component vector soliton clusters in defocusing Kerr-type media are reported. • These soliton clusters are constructed with the help of Whittaker functions. • The half-moon, necklace-ring and vortex-ring patterns are found. • The profile of these solitons can be effectively controlled by three soliton parameters.« less

Reactivation of Rate Remapping in CA3.

PubMed

Schwindel, C Daniela; Navratilova, Zaneta; Ali, Karim; Tatsuno, Masami; McNaughton, Bruce L

2016-09-07

The hippocampus is thought to contribute to episodic memory by creating, storing, and reactivating patterns that are unique to each experience, including different experiences that happen at the same location. Hippocampus can combine spatial and contextual/episodic information using a dual coding scheme known as "global" and "rate" remapping. Global remapping selects which set of neurons can activate at a given location. Rate remapping readjusts the firing rates of this set depending on current experience, thus expressing experience-unique patterns at each location. But can the experience-unique component be retrieved spontaneously? Whereas reactivation of recent, spatially selective patterns in hippocampus is well established, it is never perfect, raising the issue of whether the experiential component might be absent. This question is key to the hypothesis that hippocampus can assist memory consolidation by reactivating and broadcasting experience-specific "index codes" to neocortex. In CA3, global remapping exhibits attractor-like dynamics, whereas rate remapping apparently does not, leading to the hypothesis that only the former can be retrieved associatively and casting doubt on the general consolidation hypothesis. Therefore, we studied whether the rate component is reactivated spontaneously during sleep. We conducted neural ensemble recordings from CA3 while rats ran on a circular track in different directions (in different sessions) and while they slept. It was shown previously that the two directions of running result in strong rate remapping. During sleep, the most recent rate distribution was reactivated preferentially. Therefore, CA3 can retrieve patterns spontaneously that are unique to both the location and the content of recent experience. The hippocampus is required for memory of events and their spatial contexts. The primary correlate of hippocampal activity is location in space, but multiple memories can occur in the same location. To be useful for distinguishing these memories, the hippocampus must be able, not only to express, but also to retrieve both spatial and nonspatial information about events. Whether it can retrieve nonspatial information has been challenged recently. We exposed rats to two different experiences (running in different directions) in the same locations and showed that even the nonspatial components of hippocampal cell firing are reactivated spontaneously during sleep, supporting the conclusion that both types of information about a recent experience can be retrieved. Copyright © 2016 the authors 0270-6474/16/369342-09$15.00/0.

Differential effects of exogenous and endogenous attention on second-order texture contrast sensitivity

PubMed Central

Barbot, Antoine; Landy, Michael S.; Carrasco, Marisa

2012-01-01

The visual system can use a rich variety of contours to segment visual scenes into distinct perceptually coherent regions. However, successfully segmenting an image is a computationally expensive process. Previously we have shown that exogenous attention—the more automatic, stimulus-driven component of spatial attention—helps extract contours by enhancing contrast sensitivity for second-order, texture-defined patterns at the attended location, while reducing sensitivity at unattended locations, relative to a neutral condition. Interestingly, the effects of exogenous attention depended on the second-order spatial frequency of the stimulus. At parafoveal locations, attention enhanced second-order contrast sensitivity to relatively high, but not to low second-order spatial frequencies. In the present study we investigated whether endogenous attention—the more voluntary, conceptually-driven component of spatial attention—affects second-order contrast sensitivity, and if so, whether its effects are similar to those of exogenous attention. To that end, we compared the effects of exogenous and endogenous attention on the sensitivity to second-order, orientation-defined, texture patterns of either high or low second-order spatial frequencies. The results show that, like exogenous attention, endogenous attention enhances second-order contrast sensitivity at the attended location and reduces it at unattended locations. However, whereas the effects of exogenous attention are a function of the second-order spatial frequency content, endogenous attention affected second-order contrast sensitivity independent of the second-order spatial frequency content. This finding supports the notion that both exogenous and endogenous attention can affect second-order contrast sensitivity, but that endogenous attention is more flexible, benefitting performance under different conditions. PMID:22895879

Spatial distribution and implications to sources of halogenated flame retardants in riverine sediments of Taizhou, an intense e-waste recycling area in eastern China.

PubMed

Zhou, Shanshan; Fu, Jie; He, Huan; Fu, Jianjie; Tang, Qiaozhi; Dong, Minfeng; Pan, Yongqiang; Li, An; Liu, Weiping; Zhang, Limin

2017-10-01

Concentrations and spatial distribution pattern of organohalogen flame retardants were investigated in the riverine surface sediments from Taizhou, an intensive e-waste recycling region in China. The analytes were syn- and anti- Dechlorane Plus (DP), Dechloranes 602, 603, and 604, a DP monoadduct, two dechlorinated DPs and 8 congeners of polybrominated diphenyl ethers (PBDEs). The concentrations of Σ 8 PBDEs, ΣDP, ΣDec600s, and ΣDP-degradates ranged from <100 to 172,000, 100 to 55,000, not detectable (nd) to 1600, and nd to 2800 pg/g dry weight, respectively. BDE-209 and DP, both have been manufactured in China, had similar spatial distribution patterns in the study area, featured by distinctly recognizable hotspots some of which are in proximity to known e-waste dumping or metal recycling facilities. Such patterns were largely shared by Dec602 and dechlorinated DP, although their concentration levels were much lower. These major flame retardants significantly correlate with each other, and cluster together in the loading plot of principle component analysis. In contrast, most non-deca PBDE congeners do not correlate with DPs. Dec604 stood out having distinctly different spatial distribution pattern, which could be linked to historical use of mirex. Organic matter content of the sediment was not the dominant factor in determining the spatial pattern of pollution by halogenated flame retardants in the rivers of this study. Copyright © 2017 Elsevier Ltd. All rights reserved.

Biodiversity, molecular ecology and phylogeography of marine sponges: patterns, implications and outlooks.

PubMed

Wörheide, Gert; Solé-Cava, Antonio M; Hooper, John N A

2005-04-01

Marine sponges are an ecologically important and highly diverse component of marine benthic communities, found in all the world's oceans, at all depths. Although their commercial potential and evolutionary importance is increasingly recognized, many pivotal aspects of their basic biology remain enigmatic. Knowledge of historical biogeographic affinities and biodiversity patterns is rudimentary, and there are still few data about genetic variation among sponge populations and spatial patterns of this variation. Biodiversity analyses of tropical Australasian sponges revealed spatial trends not universally reflected in the distributions of other marine phyla within the Indo-West Pacific region. At smaller spatial scales sponges frequently form heterogeneous, spatially patchy assemblages, with some empirical evidence suggesting that environmental variables such as light and/or turbidity strongly contribute to local distributions. There are no apparent latitudinal diversity gradients at larger spatial scales but stochastic processes, such as changing current patterns, the presence or absence of major carbonate platforms and historical biogeography, may determine modern day distributions. Studies on Caribbean oceanic reefs have revealed similar patterns, only weakly correlated with environmental factors. However, several questions remain where molecular approaches promise great potential, e.g., concerning connectivity and biogeographic relationships. Studies to date have helped to reveal that sponge populations are genetically highly structured and that historical processes might play an important role in determining such structure. Increasingly sophisticated molecular tools are now being applied, with results contributing significantly to a better understanding of poriferan microevolutionary processes and molecular ecology.

Spatial and temporal air quality pattern recognition using environmetric techniques: a case study in Malaysia.

PubMed

Syed Abdul Mutalib, Sharifah Norsukhairin; Juahir, Hafizan; Azid, Azman; Mohd Sharif, Sharifah; Latif, Mohd Talib; Aris, Ahmad Zaharin; Zain, Sharifuddin M; Dominick, Doreena

2013-09-01

The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

Spatiotemporal Filtering Using Principal Component Analysis and Karhunen-Loeve Expansion Approaches for Regional GPS Network Analysis

NASA Technical Reports Server (NTRS)

Dong, D.; Fang, P.; Bock, F.; Webb, F.; Prawirondirdjo, L.; Kedar, S.; Jamason, P.

2006-01-01

Spatial filtering is an effective way to improve the precision of coordinate time series for regional GPS networks by reducing so-called common mode errors, thereby providing better resolution for detecting weak or transient deformation signals. The commonly used approach to regional filtering assumes that the common mode error is spatially uniform, which is a good approximation for networks of hundreds of kilometers extent, but breaks down as the spatial extent increases. A more rigorous approach should remove the assumption of spatially uniform distribution and let the data themselves reveal the spatial distribution of the common mode error. The principal component analysis (PCA) and the Karhunen-Loeve expansion (KLE) both decompose network time series into a set of temporally varying modes and their spatial responses. Therefore they provide a mathematical framework to perform spatiotemporal filtering.We apply the combination of PCA and KLE to daily station coordinate time series of the Southern California Integrated GPS Network (SCIGN) for the period 2000 to 2004. We demonstrate that spatially and temporally correlated common mode errors are the dominant error source in daily GPS solutions. The spatial characteristics of the common mode errors are close to uniform for all east, north, and vertical components, which implies a very long wavelength source for the common mode errors, compared to the spatial extent of the GPS network in southern California. Furthermore, the common mode errors exhibit temporally nonrandom patterns.

Component deficits of visual neglect: "Magnetic" attraction of attention vs. impaired spatial working memory.

PubMed

Toba, Monica N; Rabuffetti, Marco; Duret, Christophe; Pradat-Diehl, Pascale; Gainotti, Guido; Bartolomeo, Paolo

2018-01-31

Visual neglect is a disabling consequence of right hemisphere damage, whereby patients fail to detect left-sided objects. Its precise mechanisms are debated, but there is some consensus that distinct component deficits may variously associate and interact in different patients. Here we used a touch-screen based procedure to study two putative component deficits of neglect, rightward "magnetic" attraction of attention and impaired spatial working memory, in a group of 47 right brain-damaged patients, of whom 33 had signs of left neglect. Patients performed a visual search task on three distinct conditions, whereby touched targets could (1) be tagged, (2) disappear or (3) show no change. Magnetic attraction of attention was defined as more left neglect on the tag condition than on the disappear condition, where right-sided disappeared targets could not capture patients' attention. Impaired spatial working memory should instead produce more neglect on the no change condition, where no external cue indicated that a target had already been explored, than on the tag condition. Using a specifically developed analysis algorithm, we identified significant differences of performance between the critical conditions. Neglect patients as a group performed better on the disappear condition than on the no change condition and also better in the tag condition comparing with the no change condition. No difference was found between the tag condition and the disappear condition. Some of our neglect patients had dissociated patterns of performance, with predominant magnetic attraction or impaired spatial working memory. Anatomical results issued from both grey matter analysis and fiber tracking were consistent with the typical patterns of fronto-parietal and occipito-frontal disconnection in neglect, but did not identify lesional patterns specifically associated with one or another deficit, thus suggesting the possible co-localization of attentional and working memory processes in fronto-parietal networks. These findings give support to the hypothesis of the co-occurrence of distinct cognitive deficits in visual neglect and stress the necessity of multi-component models of visuospatial disorders. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial-frequency spectrum of patterns changes the visibility of spatial-phase differences

NASA Technical Reports Server (NTRS)

Lawton, T. B.

1985-01-01

It is shown that spatial-frequency components over a 4-octave range affected the visibility of spatial-phase differences. Contrast thresholds were measured for discrimination between two (+45- and -45-deg) spatial phases of a sinusoidal test grating added to a background grating. The background could contain one or several sinusoidal components, all in 0-deg phase. Phase differences between the test and the background were visible at lower contrasts when test and background frequencies were harmonically related than when they were not, when test and background frequencies were within 1 octave than when they were farther apart, when the fundamental frequency of the background was low than when it was high, and for some discriminations more than for others, after practice. The visibility of phase differences was not affected by additional components in the background if the fundamental and difference frequencies of the background remained unchanged. Observers' reports of their strategies gave information about the types of attentive processing that were used to discriminate phase differences. Attentive processing facilitated phase discrimination for multifrequency gratings spanning a much wider range of spatial frequencies than would be possible by using only local preattentive processing. These results were consistent with the visibility of phase differences being processed by some combination of even- and odd-symmetric simple cells tuned to a wide range of different spatial frequencies.

MRCK-1 drives apical constriction in C. elegans by linking developmental patterning to force generation

PubMed Central

Marston, Daniel J.; Higgins, Christopher D.; Peters, Kimberly A.; Cupp, Timothy D.; Dickinson, Daniel J.; Pani, Ariel M.; Moore, Regan P.; Cox, Amanda H.; Kiehart, Daniel P.; Goldstein, Bob

2016-01-01

Summary Apical constriction is a change in cell shape that drives key morphogenetic events including gastrulation and neural tube formation. Apical force-producing actomyosin networks drive apical constriction by contracting while connected to cell-cell junctions. The mechanisms by which developmental patterning regulates these actomyosin networks and associated junctions with spatial precision are not fully understood. Here, we identify a myosin light chain kinase MRCK-1 as a key regulator of C. elegans gastrulation that integrates spatial and developmental patterning information. We show that MRCK-1 is required for activation of contractile actomyosin dynamics and elevated cortical tension in the apical cell cortex of endodermal precursor cells. MRCK-1 is apically localized by active Cdc42 at the external, cell-cell contact-free surfaces of apically constricting cells, downstream of cell fate determination mechanisms. We establish that the junctional components α-catenin, β-catenin, and cadherin become highly enriched at the apical junctions of apically-constricting cells, and that MRCK-1 and myosin activity are required in vivo for this enrichment. Taken together, our results define mechanisms that position a myosin activator to a specific cell surface where it both locally increases cortical tension and locally enriches junctional components to facilitate apical constriction. These results reveal crucial links that can tie spatial information to local force generation to drive morphogenesis. PMID:27451898

Drought Patterns Forecasting using an Auto-Regressive Logistic Model

NASA Astrophysics Data System (ADS)

del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.

2014-12-01

Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

Principal component analysis of dynamic fluorescence images for diagnosis of diabetic vasculopathy

NASA Astrophysics Data System (ADS)

Seo, Jihye; An, Yuri; Lee, Jungsul; Ku, Taeyun; Kang, Yujung; Ahn, Chulwoo; Choi, Chulhee

2016-04-01

Indocyanine green (ICG) fluorescence imaging has been clinically used for noninvasive visualizations of vascular structures. We have previously developed a diagnostic system based on dynamic ICG fluorescence imaging for sensitive detection of vascular disorders. However, because high-dimensional raw data were used, the analysis of the ICG dynamics proved difficult. We used principal component analysis (PCA) in this study to extract important elements without significant loss of information. We examined ICG spatiotemporal profiles and identified critical features related to vascular disorders. PCA time courses of the first three components showed a distinct pattern in diabetic patients. Among the major components, the second principal component (PC2) represented arterial-like features. The explained variance of PC2 in diabetic patients was significantly lower than in normal controls. To visualize the spatial pattern of PCs, pixels were mapped with red, green, and blue channels. The PC2 score showed an inverse pattern between normal controls and diabetic patients. We propose that PC2 can be used as a representative bioimaging marker for the screening of vascular diseases. It may also be useful in simple extractions of arterial-like features.

Negative plant soil feedback explaining ring formation in clonal plants.

PubMed

Cartenì, Fabrizio; Marasco, Addolorata; Bonanomi, Giuliano; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco

2012-11-21

Ring shaped patches of clonal plants have been reported in different environments, but the mechanisms underlying such pattern formation are still poorly explained. Water depletion in the inner tussocks zone has been proposed as a possible cause, although ring patterns have been also observed in ecosystems without limiting water conditions. In this work, a spatially explicit model is presented in order to investigate the role of negative plant-soil feedback as an additional explanation for ring formation. The model describes the dynamics of the plant biomass in the presence of toxicity produced by the decomposition of accumulated litter in the soil. Our model qualitatively reproduces the emergence of ring patterns of a single clonal plant species during colonisation of a bare substrate. The model admits two homogeneous stationary solutions representing bare soil and uniform vegetation cover which depend only on the ratio between the biomass death and growth rates. Moreover, differently from other plant spatial patterns models, but in agreement with real field observations of vegetation dynamics, we demonstrated that the pattern dynamics always lead to spatially homogeneous vegetation covers without creation of stable Turing patterns. Analytical results show that ring formation is a function of two main components, the plant specific susceptibility to toxic compounds released in the soil by the accumulated litter and the decay rate of these same compounds, depending on environmental conditions. These components act at the same time and their respective intensities can give rise to the different ring structures observed in nature, ranging from slight reductions of biomass in patch centres, to the appearance of marked rings with bare inner zones, as well as the occurrence of ephemeral waves of plant cover. Our results highlight the potential role of plant-soil negative feedback depending on decomposition processes for the development of transient vegetation patterns. Copyright © 2012 Elsevier Ltd. All rights reserved.

Application of a global magnetospheric-ionospheric current model for dayside and terminator Pi2 pulsations

NASA Astrophysics Data System (ADS)

Imajo, S.; Yoshikawa, A.; Uozumi, T.; Ohtani, S.; Nakamizo, A.; Chi, P. J.

2017-12-01

Pi2 magnetic oscillations on the dayside are considered to be produced by the ionospheric current that is driven by Pi2-associated electric fields from the high-latitude region, but this idea has not been quantitatively tested. The present study numerically tested the magnetospheric-ionospheric current system for Pi2 consisting of field-aligned currents (FACs) localized in the nightside auroral region, the perpendicular magnetospheric current flowing in the azimuthal direction, and horizontal ionospheric currents driven by the FACs. We calculated the spatial distribution of the ground magnetic field produced by these currents using the Biot-Savart law in a stationary state. The calculated magnetic field reproduced the observational features reported by previous studies; (1) the sense of the H component does not change a wide range of local time sectors at low latitudes; (2) the amplitude of the H component on the dayside is enhanced at the equator; (3) The D component reverses its phase near the dawn and dusk terminators; (4) the meridian of the D-component phase reversal near the dusk terminator is shifted more sunward than that near the dawn terminator; (5) the amplitude of the D component in the morning is larger than that in the early evening. We also derived the global distributions of observed equivalent currents for two Pi2 events. The spatial patterns of dayside equivalent currents were similar to the spatial pattern of numerically derived equivalent currents. The results indicate that the oscillation of the magnetospheric-ionospheric current system is a plausible explanation of Pi2s on the dayside and near the terminator. These results are included in an accepted paper by Imajo et al. [2017JGR, DOI: 10.1002/2017JA024246].

Pointwise mutual information quantifies intratumor heterogeneity in tissue sections labeled with multiple fluorescent biomarkers.

PubMed

Spagnolo, Daniel M; Gyanchandani, Rekha; Al-Kofahi, Yousef; Stern, Andrew M; Lezon, Timothy R; Gough, Albert; Meyer, Dan E; Ginty, Fiona; Sarachan, Brion; Fine, Jeffrey; Lee, Adrian V; Taylor, D Lansing; Chennubhotla, S Chakra

2016-01-01

Measures of spatial intratumor heterogeneity are potentially important diagnostic biomarkers for cancer progression, proliferation, and response to therapy. Spatial relationships among cells including cancer and stromal cells in the tumor microenvironment (TME) are key contributors to heterogeneity. We demonstrate how to quantify spatial heterogeneity from immunofluorescence pathology samples, using a set of 3 basic breast cancer biomarkers as a test case. We learn a set of dominant biomarker intensity patterns and map the spatial distribution of the biomarker patterns with a network. We then describe the pairwise association statistics for each pattern within the network using pointwise mutual information (PMI) and visually represent heterogeneity with a two-dimensional map. We found a salient set of 8 biomarker patterns to describe cellular phenotypes from a tissue microarray cohort containing 4 different breast cancer subtypes. After computing PMI for each pair of biomarker patterns in each patient and tumor replicate, we visualize the interactions that contribute to the resulting association statistics. Then, we demonstrate the potential for using PMI as a diagnostic biomarker, by comparing PMI maps and heterogeneity scores from patients across the 4 different cancer subtypes. Estrogen receptor positive invasive lobular carcinoma patient, AL13-6, exhibited the highest heterogeneity score among those tested, while estrogen receptor negative invasive ductal carcinoma patient, AL13-14, exhibited the lowest heterogeneity score. This paper presents an approach for describing intratumor heterogeneity, in a quantitative fashion (via PMI), which departs from the purely qualitative approaches currently used in the clinic. PMI is generalizable to highly multiplexed/hyperplexed immunofluorescence images, as well as spatial data from complementary in situ methods including FISSEQ and CyTOF, sampling many different components within the TME. We hypothesize that PMI will uncover key spatial interactions in the TME that contribute to disease proliferation and progression.

Emotional modulation of cognitive control: approach-withdrawal states double-dissociate spatial from verbal two-back task performance.

PubMed

Gray, J R

2001-09-01

Emotional states might selectively modulate components of cognitive control. To test this hypothesis, the author randomly assigned 152 undergraduates (equal numbers of men and women) to watch short videos intended to induce emotional states (approach, neutral, or withdrawal). Each video was followed by a computerized 2-back working memory task (spatial or verbal, equated for difficulty and appearance). Spatial 2-back performance was enhanced by a withdrawal state and impaired by an approach state; the opposite pattern held for verbal performance. The double dissociation held more strongly for participants who made more errors than average across conditions. The results suggest that approach-withdrawal states can have selective influences on components of cognitive control, possibly on a hemispheric basis. They support and extend several frameworks for conceptualizing emotion-cognition interactions.

[Development of spatial orientation during pilot training].

PubMed

Ivanov, V V; Vorob'ev, O A; Snipkov, Iu Iu

1988-01-01

The problem of spatial orientation of pilots flying high-altitude aircraft is in the focus of present-day aviation medicine because of a growing number of accidents in the air. One of the productive lines of research is to study spatial orientation in terms of active formation and maintenance of its imagery in a complex environment. However investigators usually emphasize the role of visual (instrumental) information in the image construction, almost ignoring the sensorimotor component of spatial orientation. The theoretical analysis of the process of spatial orientation has facilitated the development of the concept assuming that the pattern of space perception changes with growing professional experience. The concept is based on an active approach to the essence, emergence, formation and variation in the pattern of sensory perception of space in man's consciousness. This concept asserts that as pilot's professional expertise increases, the pattern of spatial orientation becomes geocentric because a new system of spatial perception evolves which is a result of the development of a new (instrumental) type of motor activity in space. This finds expression in the fact that perception of spatial position inflight occurs when man has to resolve a new motor task--movement along a complex trajectory in the three-dimensional space onboard a flying vehicle. The meaningful structure of this problem which is to be implemented through controlling movements of the pilot acts as a factor that forms this new system of perception. All this underlies the arrangement of meaningful collection of instrumental data and detection of noninstrumental signals in the comprehensive perception of changes in the spatial position of a flying vehicle.

Spatiotemporal patterns of ERP based on combined ICA-LORETA analysis

NASA Astrophysics Data System (ADS)

Zhang, Jiacai; Guo, Taomei; Xu, Yaqin; Zhao, Xiaojie; Yao, Li

2007-03-01

In contrast to the FMRI methods widely used up to now, this method try to understand more profoundly how the brain systems work under sentence processing task map accurately the spatiotemporal patterns of activity of the large neuronal populations in the human brain from the analysis of ERP data recorded on the brain scalp. In this study, an event-related brain potential (ERP) paradigm to record the on-line responses to the processing of sentences is chosen as an example. In order to give attention to both utilizing the ERPs' temporal resolution of milliseconds and overcoming the insensibility of cerebral location ERP sources, we separate these sources in space and time based on a combined method of independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. ICA blindly separate the input ERP data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. And then the spatial maps associated with each ICA component are analyzed, with use of LORETA to uniquely locate its cerebral sources throughout the full brain according to the assumption that neighboring neurons are simultaneously and synchronously activated. Our results show that the cerebral computation mechanism underlies content words reading is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, and activate at distinct time intervals and are grouped into different statistically independent components. Thus ICA-LORETA analysis provides an encouraging and effective method to study brain dynamics from ERP.

Topoisomerase II Mediates Meiotic Crossover Interference

PubMed Central

Zhang, Liangran; Wang, Shunxin; Yin, Shen; Hong, Soogil; Kim, Keun P.; Kleckner, Nancy

2014-01-01

Summary Spatial patterning is a ubiquitous feature of biological systems. Meiotic crossovers provide an interesting example, defined by the classical phenomenon of crossover interference. Here, analysis of crossover patterns in budding yeast identifies a molecular pathway for interference. Topoisomerase II (Topo II) plays a central role, thus identifying a new function for this critical molecule. SUMOylation [of TopoII and axis component Red1] and ubiquitin-mediated removal of SUMOylated proteins are also required. These and other findings support the hypothesis that crossover interference involves accumulation, relief and redistribution of mechanical stress along the protein/DNA meshwork of meiotic chromosome axes, with TopoII required to adjust spatial relationships among DNA segments. PMID:25043020

Cluster pattern analysis of energy deposition sites for the brachytherapy sources 103Pd, 125I, 192Ir, 137Cs, and 60Co.

PubMed

Villegas, Fernanda; Tilly, Nina; Bäckström, Gloria; Ahnesjö, Anders

2014-09-21

Analysing the pattern of energy depositions may help elucidate differences in the severity of radiation-induced DNA strand breakage for different radiation qualities. It is often claimed that energy deposition (ED) sites from photon radiation form a uniform random pattern, but there is indication of differences in RBE values among different photon sources used in brachytherapy. The aim of this work is to analyse the spatial patterns of EDs from 103Pd, 125I, 192Ir, 137Cs sources commonly used in brachytherapy and a 60Co source as a reference radiation. The results suggest that there is both a non-uniform and a uniform random component to the frequency distribution of distances to the nearest neighbour ED. The closest neighbouring EDs show high spatial correlation for all investigated radiation qualities, whilst the uniform random component dominates for neighbours with longer distances for the three higher mean photon energy sources (192Ir, 137Cs, and 60Co). The two lower energy photon emitters (103Pd and 125I) present a very small uniform random component. The ratio of frequencies of clusters with respect to 60Co differs up to 15% for the lower energy sources and less than 2% for the higher energy sources when the maximum distance between each pair of EDs is 2 nm. At distances relevant to DNA damage, cluster patterns can be differentiated between the lower and higher energy sources. This may be part of the explanation to the reported difference in RBE values with initial DSB yields as an endpoint for these brachytherapy sources.

Cluster pattern analysis of energy deposition sites for the brachytherapy sources 103Pd, 125I, 192Ir, 137Cs, and 60Co

NASA Astrophysics Data System (ADS)

Villegas, Fernanda; Tilly, Nina; Bäckström, Gloria; Ahnesjö, Anders

2014-09-01

Analysing the pattern of energy depositions may help elucidate differences in the severity of radiation-induced DNA strand breakage for different radiation qualities. It is often claimed that energy deposition (ED) sites from photon radiation form a uniform random pattern, but there is indication of differences in RBE values among different photon sources used in brachytherapy. The aim of this work is to analyse the spatial patterns of EDs from 103Pd, 125I, 192Ir, 137Cs sources commonly used in brachytherapy and a 60Co source as a reference radiation. The results suggest that there is both a non-uniform and a uniform random component to the frequency distribution of distances to the nearest neighbour ED. The closest neighbouring EDs show high spatial correlation for all investigated radiation qualities, whilst the uniform random component dominates for neighbours with longer distances for the three higher mean photon energy sources (192Ir, 137Cs, and 60Co). The two lower energy photon emitters (103Pd and 125I) present a very small uniform random component. The ratio of frequencies of clusters with respect to 60Co differs up to 15% for the lower energy sources and less than 2% for the higher energy sources when the maximum distance between each pair of EDs is 2 nm. At distances relevant to DNA damage, cluster patterns can be differentiated between the lower and higher energy sources. This may be part of the explanation to the reported difference in RBE values with initial DSB yields as an endpoint for these brachytherapy sources.

Exploratory Temporal and Spatial Analysis of Myocardial Infarction Hospitalizations in Calgary, Canada

PubMed Central

Liu, Xiaoxiao; Bertazzon, Stefania

2017-01-01

Spatial and temporal analyses are critical to understand the pattern of myocardial infarction (MI) hospitalizations over space and time, and to identify their underlying determinants. In this paper, we analyze MI hospitalizations in Calgary from 2004 to 2013, stratified by age and gender. First, a seasonal trend decomposition analyzes the seasonality; then a linear regression models the trend component. Moran’s I and hot spot analyses explore the spatial pattern. Though exploratory, results show that most age and gender groups feature a statistically significant decline over the 10 years, consistent with previous studies in Canada. Decline rates vary across ages and genders, with the slowest decline observed for younger males. Each gender exhibits a seasonal pattern with peaks in both winter and summer. Spatially, MI hot spots are identified in older communities, and in socioeconomically and environmentally disadvantaged communities. In the older communities, higher MI rates appear to be more highly associated with demographics. Conversely, worse air quality appears to be locally associated with higher MI incidence in younger age groups. The study helps identify areas of concern, where MI hot spots are identified for younger age groups, suggesting the need for localized public health policies to target local risk factors. PMID:29232910

Floodplain complexity and surface metrics: influences of scale and geomorphology

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.

2015-01-01

Many studies of fluvial geomorphology and landscape ecology examine a single river or landscape, thus lack generality, making it difficult to develop a general understanding of the linkages between landscape patterns and larger-scale driving variables. We examined the spatial complexity of eight floodplain surfaces in widely different geographic settings and determined how patterns measured at different scales relate to different environmental drivers. Floodplain surface complexity is defined as having highly variable surface conditions that are also highly organised in space. These two components of floodplain surface complexity were measured across multiple sampling scales from LiDAR-derived DEMs. The surface character and variability of each floodplain were measured using four surface metrics; namely, standard deviation, skewness, coefficient of variation, and standard deviation of curvature from a series of moving window analyses ranging from 50 to 1000 m in radius. The spatial organisation of each floodplain surface was measured using spatial correlograms of the four surface metrics. Surface character, variability, and spatial organisation differed among the eight floodplains; and random, fragmented, highly patchy, and simple gradient spatial patterns were exhibited, depending upon the metric and window size. Differences in surface character and variability among the floodplains became statistically stronger with increasing sampling scale (window size), as did their associations with environmental variables. Sediment yield was consistently associated with differences in surface character and variability, as were flow discharge and variability at smaller sampling scales. Floodplain width was associated with differences in the spatial organization of surface conditions at smaller sampling scales, while valley slope was weakly associated with differences in spatial organisation at larger scales. A comparison of floodplain landscape patterns measured at different scales would improve our understanding of the role that different environmental variables play at different scales and in different geomorphic settings.

Perception of global image contrast involves transparent spatial filtering and the integration and suppression of local contrasts (not RMS contrast)

PubMed Central

2017-01-01

When adjusting the contrast setting on a television set, we experience a perceptual change in the global image contrast. But how is that statistic computed? We addressed this using a contrast-matching task for checkerboard configurations of micro-patterns in which the contrasts and spatial spreads of two interdigitated components were controlled independently. When the patterns differed greatly in contrast, the higher contrast determined the perceived global contrast. Crucially, however, low contrast additions of one pattern to intermediate contrasts of the other caused a paradoxical reduction in the perceived global contrast. None of the following metrics/models predicted this: max, linear sum, average, energy, root mean squared (RMS), Legge and Foley. However, a nonlinear gain control model, derived from contrast detection and discrimination experiments, incorporating wide-field summation and suppression, did predict the results with no free parameters, but only when spatial filtering was removed. We conclude that our model describes fundamental processes in human contrast vision (the pattern of results was the same for expert and naive observers), but that above threshold—when contrast pedestals are clearly visible—vision's spatial filtering characteristics become transparent, tending towards those of a delta function prior to spatial summation. The global contrast statistic from our model is as easily derived as the RMS contrast of an image, and since it more closely relates to human perception, we suggest it be used as an image contrast metric in practical applications. PMID:28989735

Modeling vertebrate diversity in Oregon using satellite imagery

NASA Astrophysics Data System (ADS)

Cablk, Mary Elizabeth

Vertebrate diversity was modeled for the state of Oregon using a parametric approach to regression tree analysis. This exploratory data analysis effectively modeled the non-linear relationships between vertebrate richness and phenology, terrain, and climate. Phenology was derived from time-series NOAA-AVHRR satellite imagery for the year 1992 using two methods: principal component analysis and derivation of EROS data center greenness metrics. These two measures of spatial and temporal vegetation condition incorporated the critical temporal element in this analysis. The first three principal components were shown to contain spatial and temporal information about the landscape and discriminated phenologically distinct regions in Oregon. Principal components 2 and 3, 6 greenness metrics, elevation, slope, aspect, annual precipitation, and annual seasonal temperature difference were investigated as correlates to amphibians, birds, all vertebrates, reptiles, and mammals. Variation explained for each regression tree by taxa were: amphibians (91%), birds (67%), all vertebrates (66%), reptiles (57%), and mammals (55%). Spatial statistics were used to quantify the pattern of each taxa and assess validity of resulting predictions from regression tree models. Regression tree analysis was relatively robust against spatial autocorrelation in the response data and graphical results indicated models were well fit to the data.

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil

PubMed Central

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J.

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns. PMID:27171522

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil.

PubMed

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns.

Speckle-based three-dimensional velocity measurement using spatial filtering velocimetry.

PubMed

Iversen, Theis F Q; Jakobsen, Michael L; Hanson, Steen G

2011-04-10

We present an optical method for measuring the real-time three-dimensional (3D) translational velocity of a diffusely scattering rigid object observed through an imaging system. The method is based on a combination of the motion of random speckle patterns and regular fringe patterns. The speckle pattern is formed in the observation plane of the imaging system due to reflection from an area of the object illuminated by a coherent light source. The speckle pattern translates in response to in-plane translation of the object, and the presence of an angular offset reference wave coinciding with the speckle pattern in the observation plane gives rise to interference, resulting in a fringe pattern that translates in response to the out-of-plane translation of the object. Numerical calculations are performed to evaluate the dynamic properties of the intensity distribution and the response of realistic spatial filters designed to measure the three components of the object's translational velocity. Furthermore, experimental data are presented that demonstrate full 3D velocity measurement. © 2011 Optical Society of America

Assessing patterns of spatial behavior in health studies: their socio-demographic determinants and associations with transportation modes (the RECORD Cohort Study).

PubMed

Perchoux, Camille; Kestens, Yan; Thomas, Frédérique; Van Hulst, Andraea; Thierry, Benoit; Chaix, Basile

2014-10-01

Prior epidemiological studies have mainly focused on local residential neighborhoods to assess environmental exposures. However, individual spatial behavior may modify residential neighborhood influences, with weaker health effects expected for mobile populations. By examining individual patterns of daily mobility and associated socio-demographic profiles and transportation modes, this article seeks to develop innovative methods to account for daily mobility in health studies. We used data from the RECORD Cohort Study collected in 2011-2012 in the Paris metropolitan area, France. A sample of 2062 individuals was investigated. Participants' perceived residential neighborhood boundaries and regular activity locations were geocoded using the VERITAS application. Twenty-four indicators were created to qualify individual space-time patterns, using spatial analysis methods and a geographic information system. Three domains of indicators were considered: lifestyle indicators, indicators related to the geometry of the activity space, and indicators related to the importance of the residential neighborhood in the overall activity space. Principal component analysis was used to identify main dimensions of spatial behavior. Multilevel linear regression was used to determine which individual characteristics were associated with each spatial behavior dimension. The factor analysis generated five dimensions of spatial behavior: importance of the residential neighborhood in the activity space, volume of activities, and size, eccentricity, and specialization of the activity space. Age, socioeconomic status, and location of the household in the region were the main predictors of daily mobility patterns. Activity spaces of small sizes centered on the residential neighborhood and implying a large volume of activities were associated with walking and/or biking as a transportation mode. Examination of patterns of spatial behavior by individual socio-demographic characteristics and in relation to transportation modes is useful to identify populations with specific mobility/accessibility needs and has implications for investigating transportation-related physical activity and assessing environmental exposures and their effects on health. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile.

PubMed

Inostroza, Luis; Palme, Massimo; de la Barrera, Francisco

2016-01-01

Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making.

A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile

PubMed Central

Palme, Massimo; de la Barrera, Francisco

2016-01-01

Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making. PMID:27606592

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.

Use of space-time models to investigate the stability of patterns of disease.

PubMed

Abellan, Juan Jose; Richardson, Sylvia; Best, Nicky

2008-08-01

The use of Bayesian hierarchical spatial models has become widespread in disease mapping and ecologic studies of health-environment associations. In this type of study, the data are typically aggregated over an extensive time period, thus neglecting the time dimension. The output of purely spatial disease mapping studies is therefore the average spatial pattern of risk over the period analyzed, but the results do not inform about, for example, whether a high average risk was sustained over time or changed over time. We investigated how including the time dimension in disease-mapping models strengthens the epidemiologic interpretation of the overall pattern of risk. We discuss a class of Bayesian hierarchical models that simultaneously characterize and estimate the stable spatial and temporal patterns as well as departures from these stable components. We show how useful rules for classifying areas as stable can be constructed based on the posterior distribution of the space-time interactions. We carry out a simulation study to investigate the sensitivity and specificity of the decision rules we propose, and we illustrate our approach in a case study of congenital anomalies in England. Our results confirm that extending hierarchical disease-mapping models to models that simultaneously consider space and time leads to a number of benefits in terms of interpretation and potential for detection of localized excesses.

Exploring the relation between spatial configuration of buildings and remotely sensed temperatures

NASA Astrophysics Data System (ADS)

Myint, S. W.; Zheng, B.; Kaplan, S.; Huang, H.

2013-12-01

While the relationship between fractional cover of buildings and the UHI has been well studied, relationships of how spatial arrangements (e.g., clustered, dispersed) of buildings influence urban warming are not well understood. Since a diversity of spatial patterns can be observed under the same percentage of buildings cover, it is of great interest and importance to investigate the amount of variation in certain urban thermal feature such as surface temperature that is accounted for by the inclusion of spatial arrangement component. The various spatial arrangements of buildings cover can give rise to different urban thermal behaviors that may not be uncovered with the information of buildings fraction only, but can be captured to some extent using spatial analysis. The goal of this study is to examine how spatial arrangements of buildings influence and shape surface temperature in different urban settings. The study area selected is the Las-Vegas metropolitan area in Nevada, located in the Mojave Desert. An object-oriented approach was used to identify buildings using a Geoeye-1 image acquired on October 12, 2011. A spatial autocorrelation technique (i.e., Moran's I) that can measure spatial pattern (clustered, dispersed) was used to determine spatial configuration of buildings. A daytime temperature layer in degree Celsius, generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image, was integrated with Moran's I values of building cover and building fractions to achieve the goals set in the study. To avoid uncertainty and properly evaluate if spatial pattern of buildings has an impact on urban warming, the relation between Moran's I values and surface temperatures was observed at different levels according to their fractions (e.g., 0-0.1, 0.5-0.6, 0.9-1). There is a negative correlation exists between spatial pattern of buildings and surface temperatures implying that dispersed building arrangements elevate surface temperatures more severely than clustered buildings. This suggests that more clustered buildings have less impact on the urban heat island (UHI) effect. We conclude that having buildings as clustered as possible can be expected to protect the settlements from increased heat island effects, reduce pollution, and preserve the hydrological systems.

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

What are hot and what are not in an urban landscape: quantifying and explaining the land surface temperature pattern in Beijing, China

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

Kuang, Wenhui; Liu, Yue; Dou, Yinyin

Understanding how landscape components affect the urban heat islands is crucial for urban ecological planning and sustainable development. The purpose of this research was to quantify the spatial pattern of land surface temperatures (LSTs) and associated heat fluxes in relation to land-cover types in Beijing, China, using portable infrared thermometers, thermal infrared imagers, and the moderate resolution imaging spectroradiometer. The spatial differences and the relationships between LSTs and the hierarchical landscape structure were analyzed with in situ observations of surface radiation and heat fluxes. Large LST differences were found among various land-use/land-cover types, urban structures, and building materials. Within themore » urban area, the mean LST of urban impervious surfaces was about 6–12°C higher than that of the urban green space. LSTs of built-up areas were on average 3–6°C higher than LSTs of rural areas. The observations for surface radiation and heat fluxes indicated that the differences were caused by different fractions of sensible heat or latent heat flux in net radiation. LSTs decreased with increasing elevation and normalized difference vegetation index. Variations in building materials and urban structure significantly influenced the spatial pattern of LSTs in urban areas. By contrast, elevation and vegetation cover are the major determinants of the LST pattern in rural areas. In summary, to alleviate urban heat island intensity, urban planners and policy makers should pay special attention to the selection of appropriate building materials, the reasonable arrangement of urban structures, and the rational design of landscape components.« less

Patterns of distribution, abundance, and change over time in a subarctic marine bird community

NASA Astrophysics Data System (ADS)

Cushing, Daniel A.; Roby, Daniel D.; Irons, David B.

2018-01-01

Over recent decades, marine ecosystems of Prince William Sound (PWS), Alaska, have experienced concurrent effects of natural and anthropogenic perturbations, including variability in the climate system of the northeastern Pacific Ocean. We documented spatial and temporal patterns of variability in the summer marine bird community in relation to habitat and climate variability using boat-based surveys of marine birds conducted during the period 1989-2012. We hypothesized that a major factor structuring marine bird communities in PWS would be proximity to the shoreline, which is theorized to relate to aspects of food web structure. We also hypothesized that shifts in physical ecosystem drivers differentially affected nearshore-benthic and pelagic components of PWS food webs. We evaluated support for our hypotheses using an approach centered on community-level patterns of spatial and temporal variability. We found that an environmental gradient related to water depth and distance from shore was the dominant factor spatially structuring the marine bird community. Responses of marine birds to this onshore-offshore environmental gradient were related to dietary specialization, and separated marine bird taxa by prey type. The primary form of temporal variability over the study period was monotonic increases or decreases in abundance for 11 of 18 evaluated genera of marine birds; 8 genera had declined, whereas 3 had increased. The greatest declines occurred in genera associated with habitats that were deeper and farther from shore. Furthermore, most of the genera that declined primarily fed on pelagic prey resources, such as forage fish and mesozooplankton, and few were directly affected by the 1989 Exxon Valdez oil spill. Our observations of synchronous declines are indicative of a shift in pelagic components of PWS food webs. This pattern was correlated with climate variability at time-scales of several years to a decade.

Spatial analysis of sunshine duration by combination of satellite and station data

NASA Astrophysics Data System (ADS)

Frei, C.; Stöckli, R.; Dürr, B.

2009-09-01

Sunshine duration can exhibit rich fine scale patterns associated with special meteorological phenomena, such as fog layers and topographically triggered clouds. Networks of climate stations are mostly too coarse and poorly representative to resolve these patterns explicitly. We present a method which combines station observations with satellite-derived cloud-cover data to produce km-scale fields of sunshine duration. The method is not relying on contemporous satellite information, hence it can be applied over climatological time scales. We apply and evaluate the combination method over the territory of Switzerland. The combination method is based on Universal Kriging. First, the satellite data (a Heliosat clear sky index from MSG, extending over a 5 year preiod) is subjected to a S-mode Principal Component (PC) Analysis. Second, a set of leading PC loadings (seasonally stratified) is introduced as external drift covariates and their optimal linear combination is estimated from the station data (70 stations). Finally, the stochastic component is an autocorrelated field with an exponential variogram, estimated climatologically for each calendar month. For Switzerland the leading PCs of the clear sky index depict familiar patterns of cloud variability which are inhereted in the combination process. The resulting sunshine duration fields exhibit fine-scale structures that are physically plausible, linked to the topography and characteristic of the regional climate. These patterns could not be inferred from station data and/or topographic predictors alone. A cross-validation reveals that the combination method explains between 80-90% of the spatial variance in winter and autumn months. In spring and summer the relative performance is lower (60-75% explained spatial variance) but absolute errors are smaller. Our presentation will also discuss some results from a climatology of the derived sunshine duration fields.

Patterns of distribution, abundance, and change over time in a subarctic marine bird community

USGS Publications Warehouse

Cushing, Daniel; Roby, Daniel D.; Irons, David B.

2017-01-01

Over recent decades, marine ecosystems of Prince William Sound (PWS), Alaska, have experienced concurrent effects of natural and anthropogenic perturbations, including variability in the climate system of the northeastern Pacific Ocean. We documented spatial and temporal patterns of variability in the summer marine bird community in relation to habitat and climate variability using boat-based surveys of marine birds conducted during the period 1989–2012. We hypothesized that a major factor structuring marine bird communities in PWS would be proximity to the shoreline, which is theorized to relate to aspects of food web structure. We also hypothesized that shifts in physical ecosystem drivers differentially affected nearshore-benthic and pelagic components of PWS food webs. We evaluated support for our hypotheses using an approach centered on community-level patterns of spatial and temporal variability. We found that an environmental gradient related to water depth and distance from shore was the dominant factor spatially structuring the marine bird community. Responses of marine birds to this onshore-offshore environmental gradient were related to dietary specialization, and separated marine bird taxa by prey type. The primary form of temporal variability over the study period was monotonic increases or decreases in abundance for 11 of 18 evaluated genera of marine birds; 8 genera had declined, whereas 3 had increased. The greatest declines occurred in genera associated with habitats that were deeper and farther from shore. Furthermore, most of the genera that declined primarily fed on pelagic prey resources, such as forage fish and mesozooplankton, and few were directly affected by the 1989 Exxon Valdez oil spill. Our observations of synchronous declines are indicative of a shift in pelagic components of PWS food webs. This pattern was correlated with climate variability at time-scales of several years to a decade.

What are hot and what are not in an urban landscape: quantifying and explaining the land surface temperature pattern in Beijing, China

DOE PAGES

Kuang, Wenhui; Liu, Yue; Dou, Yinyin; ...

2014-12-06

Understanding how landscape components affect the urban heat islands is crucial for urban ecological planning and sustainable development. The purpose of this research was to quantify the spatial pattern of land surface temperatures (LSTs) and associated heat fluxes in relation to land-cover types in Beijing, China, using portable infrared thermometers, thermal infrared imagers, and the moderate resolution imaging spectroradiometer. The spatial differences and the relationships between LSTs and the hierarchical landscape structure were analyzed with in situ observations of surface radiation and heat fluxes. Large LST differences were found among various land-use/land-cover types, urban structures, and building materials. Within themore » urban area, the mean LST of urban impervious surfaces was about 6–12°C higher than that of the urban green space. LSTs of built-up areas were on average 3–6°C higher than LSTs of rural areas. The observations for surface radiation and heat fluxes indicated that the differences were caused by different fractions of sensible heat or latent heat flux in net radiation. LSTs decreased with increasing elevation and normalized difference vegetation index. Variations in building materials and urban structure significantly influenced the spatial pattern of LSTs in urban areas. By contrast, elevation and vegetation cover are the major determinants of the LST pattern in rural areas. In summary, to alleviate urban heat island intensity, urban planners and policy makers should pay special attention to the selection of appropriate building materials, the reasonable arrangement of urban structures, and the rational design of landscape components.« less

Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity.

PubMed

de Pierrefeu, Amicie; Fovet, Thomas; Hadj-Selem, Fouad; Löfstedt, Tommy; Ciuciu, Philippe; Lefebvre, Stephanie; Thomas, Pierre; Lopes, Renaud; Jardri, Renaud; Duchesnay, Edouard

2018-04-01

Despite significant progress in the field, the detection of fMRI signal changes during hallucinatory events remains difficult and time-consuming. This article first proposes a machine-learning algorithm to automatically identify resting-state fMRI periods that precede hallucinations versus periods that do not. When applied to whole-brain fMRI data, state-of-the-art classification methods, such as support vector machines (SVM), yield dense solutions that are difficult to interpret. We proposed to extend the existing sparse classification methods by taking the spatial structure of brain images into account with structured sparsity using the total variation penalty. Based on this approach, we obtained reliable classifying performances associated with interpretable predictive patterns, composed of two clearly identifiable clusters in speech-related brain regions. The variation in transition-to-hallucination functional patterns not only from one patient to another but also from one occurrence to the next (e.g., also depending on the sensory modalities involved) appeared to be the major difficulty when developing effective classifiers. Consequently, second, this article aimed to characterize the variability within the prehallucination patterns using an extension of principal component analysis with spatial constraints. The principal components (PCs) and the associated basis patterns shed light on the intrinsic structures of the variability present in the dataset. Such results are promising in the scope of innovative fMRI-guided therapy for drug-resistant hallucinations, such as fMRI-based neurofeedback. © 2018 Wiley Periodicals, Inc.

Residential expansion as a continental threat to U.S. coastal ecosystems

Treesearch

J.G. Bartlett; D.M. Mageean; R.J. O' Connor

2000-01-01

Spatially extensive analysis of satellite, climate, and census data reveals human-environment interactions of regional or continental concern in the United States. A grid-based principal components analysis of Bureau of Census variables revealed two independent demographic phenomena, a-settlement reflecting traditional human settlement patterns and p-settlement...

Sensitivity to Landscape Features: A Spatial Analysis of Field Geoscientists on the Move

ERIC Educational Resources Information Center

Baker, Kathleen M.; Petcovic, L. Heather

2016-01-01

Intelligent behavior in everyday contexts may depend on both ability and an individual's disposition toward using that ability. Research into patterns of thinking has identified three logically distinct components necessary for dispositional behavior: ability, inclination, and sensitivity. Surprisingly, sensitivity appears to be the most common…

Morphological Spatial Pattern Analysis of the Conterminous US

EPA Science Inventory

Six data layers, all created using GUIDOS 1.3 MSPA software to identify green infrastructure components (e.g. core, edge, corridor, etc.). Water was treated three different ways: 1) as foreground, 2) as background, and 3) as missing using both NLCD 2001 and 2006 for six total lay...

Uses of GIS for Homeland Security and Emergency Management for Higher Education Institutions

ERIC Educational Resources Information Center

Murchison, Stuart B.

2010-01-01

Geographic information systems (GIS) are a major component of the geospatial sciences, which are also composed of geostatistical analysis, remote sensing, and global positional satellite systems. These systems can be integrated into GIS for georeferencing, pattern analysis, visualization, and understanding spatial concepts that transcend…

Physical vs. photolithographic patterning of plasma polymers: an investigation by ToF-SSIMS and multivariate analysis

PubMed Central

Mishra, Gautam; Easton, Christopher D.; McArthur, Sally L.

2009-01-01

Physical and photolithographic techniques are commonly used to create chemical patterns for a range of technologies including cell culture studies, bioarrays and other biomedical applications. In this paper, we describe the fabrication of chemical micropatterns from commonly used plasma polymers. Atomic force microcopy (AFM) imaging, Time-of-Flight Static Secondary Ion Mass Spectrometry (ToF-SSIMS) imaging and multivariate analysis have been employed to visualize the chemical boundaries created by these patterning techniques and assess the spatial and chemical resolution of the patterns. ToF-SSIMS analysis demonstrated that well defined chemical and spatial boundaries were obtained from photolithographic patterning, while the resolution of physical patterning via a transmission electron microscopy (TEM) grid varied depending on the properties of the plasma system including the substrate material. In general, physical masking allowed diffusion of the plasma species below the mask and bleeding of the surface chemistries. Multivariate analysis techniques including Principal Component Analysis (PCA) and Region of Interest (ROI) assessment were used to investigate the ToF-SSIMS images of a range of different plasma polymer patterns. In the most challenging case, where two strongly reacting polymers, allylamine and acrylic acid were deposited, PCA confirmed the fabrication of micropatterns with defined spatial resolution. ROI analysis allowed for the identification of an interface between the two plasma polymers for patterns fabricated using the photolithographic technique which has been previously overlooked. This study clearly demonstrated the versatility of photolithographic patterning for the production of multichemistry plasma polymer arrays and highlighted the need for complimentary characterization and analytical techniques during the fabrication plasma polymer micropatterns. PMID:19950941

Macroecology: A Primer for Biological Oceanography

NASA Astrophysics Data System (ADS)

Li, W. K. W.

2016-02-01

Macroecology is the study of ecological patterns discerned at a spatial, temporal, or organization scale higher than that at which the focal entities interact. Such patterns are statistical or emergent manifestations arising from the ensemble of component entities. Although macroecology is a neologism largely based in terrestrial and avian ecology, macroscopic patterns have long been recognised in biological oceanography. Familiar examples include Redfield elemental stoichiometry, Elton trophic pyramids, Sheldon biomass spectrum, and Margalef life-forms mandala. Macroecological regularities can often be found along various continua, such as along body size in power-law scaling or along habitat temperature in metabolic theory. Uniquely in oceanography, a partition of the world ocean continuum into Longhurst biogeochemical provinces provides a spatial organization well-suited for macroecological investigations. In this rational discrete approach, fundamental processes in physical and biological oceanography that differentiate a set of non-overlapping ocean regions also appear to shape the macroecological structure of phytoplankton communities.

Assessing long-term variations in sagebrush habitat: characterization of spatial extents and distribution patterns using multi-temporal satellite remote-sensing data

USGS Publications Warehouse

Xian, George; Homer, Collin G.; Aldridge, Cameron L.

2012-01-01

An approach that can generate sagebrush habitat change estimates for monitoring large-area sagebrush ecosystems has been developed and tested in southwestern Wyoming, USA. This prototype method uses a satellite-based image change detection algorithm and regression models to estimate sub-pixel percentage cover for five sagebrush habitat components: bare ground, herbaceous, litter, sagebrush and shrub. Landsat images from three different months in 1988, 1996 and 2006 were selected to identify potential landscape change during these time periods using change vector (CV) analysis incorporated with an image normalization algorithm. Regression tree (RT) models were used to estimate percentage cover for five components on all change areas identified in 1988 and 1996, using unchanged 2006 baseline data as training for both estimates. Over the entire study area (24 950 km2), a net increase of 98.83 km2, or 0.7%, for bare ground was measured between 1988 and 2006. Over the same period, the other four components had net losses of 20.17 km2, or 0.6%, for herbaceous vegetation; 30.16 km2, or 0.7%, for litter; 32.81 km2, or 1.5%, for sagebrush; and 33.34 km2, or 1.2%, for shrubs. The overall accuracy for shrub vegetation change between 1988 and 2006 was 89.56%. Change patterns within sagebrush habitat components differ spatially and quantitatively from each other, potentially indicating unique responses by these components to disturbances imposed upon them.

Principal components analysis of the photoresponse nonuniformity of a matrix detector.

PubMed

Ferrero, Alejandro; Alda, Javier; Campos, Joaquín; López-Alonso, Jose Manuel; Pons, Alicia

2007-01-01

The principal component analysis is used to identify and quantify spatial distributions of relative photoresponse as a function of the exposure time for a visible CCD array. The analysis shows a simple way to define an invariant photoresponse nonuniformity and compare it with the definition of this invariant pattern as the one obtained for long exposure times. Experimental data of radiant exposure from levels of irradiance obtained in a stable and well-controlled environment are used.

The stability and slow dynamics of spot patterns in the 2D Brusselator model: The effect of open systems and heterogeneities

NASA Astrophysics Data System (ADS)

Tzou, J. C.; Ward, M. J.

2018-06-01

Spot patterns, whereby the activator field becomes spatially localized near certain dynamically-evolving discrete spatial locations in a bounded multi-dimensional domain, is a common occurrence for two-component reaction-diffusion (RD) systems in the singular limit of a large diffusivity ratio. In previous studies of 2-D localized spot patterns for various specific well-known RD systems, the domain boundary was assumed to be impermeable to both the activator and inhibitor, and the reaction-kinetics were assumed to be spatially uniform. As an extension of this previous theory, we use formal asymptotic methods to study the existence, stability, and slow dynamics of localized spot patterns for the singularly perturbed 2-D Brusselator RD model when the domain boundary is only partially impermeable, as modeled by an inhomogeneous Robin boundary condition, or when there is an influx of inhibitor across the domain boundary. In our analysis, we will also allow for the effect of a spatially variable bulk feed term in the reaction kinetics. By applying our extended theory to the special case of one-spot patterns and ring patterns of spots inside the unit disk, we provide a detailed analysis of the effect on spot patterns of these three different sources of heterogeneity. In particular, when there is an influx of inhibitor across the boundary of the unit disk, a ring pattern of spots can become pinned to a ring-radius closer to the domain boundary. Under a Robin condition, a quasi-equilibrium ring pattern of spots is shown to exhibit a novel saddle-node bifurcation behavior in terms of either the inhibitor diffusivity, the Robin constant, or the ambient background concentration. A spatially variable bulk feed term, with a concentrated source of "fuel" inside the domain, is shown to yield a saddle-node bifurcation structure of spot equilibria, which leads to qualitatively new spot-pinning behavior. Results from our asymptotic theory are validated from full numerical simulations of the Brusselator model.

Patterns of Gray Matter Abnormalities in Schizophrenia Based on an International Mega-analysis.

PubMed

Gupta, Cota Navin; Calhoun, Vince D; Rachakonda, Srinivas; Chen, Jiayu; Patel, Veena; Liu, Jingyu; Segall, Judith; Franke, Barbara; Zwiers, Marcel P; Arias-Vasquez, Alejandro; Buitelaar, Jan; Fisher, Simon E; Fernandez, Guillen; van Erp, Theo G M; Potkin, Steven; Ford, Judith; Mathalon, Daniel; McEwen, Sarah; Lee, Hyo Jong; Mueller, Bryon A; Greve, Douglas N; Andreassen, Ole; Agartz, Ingrid; Gollub, Randy L; Sponheim, Scott R; Ehrlich, Stefan; Wang, Lei; Pearlson, Godfrey; Glahn, David C; Sprooten, Emma; Mayer, Andrew R; Stephen, Julia; Jung, Rex E; Canive, Jose; Bustillo, Juan; Turner, Jessica A

2015-09-01

Analyses of gray matter concentration (GMC) deficits in patients with schizophrenia (Sz) have identified robust changes throughout the cortex. We assessed the relationships between diagnosis, overall symptom severity, and patterns of gray matter in the largest aggregated structural imaging dataset to date. We performed both source-based morphometry (SBM) and voxel-based morphometry (VBM) analyses on GMC images from 784 Sz and 936 controls (Ct) across 23 scanning sites in Europe and the United States. After correcting for age, gender, site, and diagnosis by site interactions, SBM analyses showed 9 patterns of diagnostic differences. They comprised separate cortical, subcortical, and cerebellar regions. Seven patterns showed greater GMC in Ct than Sz, while 2 (brainstem and cerebellum) showed greater GMC for Sz. The greatest GMC deficit was in a single pattern comprising regions in the superior temporal gyrus, inferior frontal gyrus, and medial frontal cortex, which replicated over analyses of data subsets. VBM analyses identified overall cortical GMC loss and one small cluster of increased GMC in Sz, which overlapped with the SBM brainstem component. We found no significant association between the component loadings and symptom severity in either analysis. This mega-analysis confirms that the commonly found GMC loss in Sz in the anterior temporal lobe, insula, and medial frontal lobe form a single, consistent spatial pattern even in such a diverse dataset. The separation of GMC loss into robust, repeatable spatial patterns across multiple datasets paves the way for the application of these methods to identify subtle genetic and clinical cohort effects. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Pointwise mutual information quantifies intratumor heterogeneity in tissue sections labeled with multiple fluorescent biomarkers

PubMed Central

Spagnolo, Daniel M.; Gyanchandani, Rekha; Al-Kofahi, Yousef; Stern, Andrew M.; Lezon, Timothy R.; Gough, Albert; Meyer, Dan E.; Ginty, Fiona; Sarachan, Brion; Fine, Jeffrey; Lee, Adrian V.; Taylor, D. Lansing; Chennubhotla, S. Chakra

2016-01-01

Background: Measures of spatial intratumor heterogeneity are potentially important diagnostic biomarkers for cancer progression, proliferation, and response to therapy. Spatial relationships among cells including cancer and stromal cells in the tumor microenvironment (TME) are key contributors to heterogeneity. Methods: We demonstrate how to quantify spatial heterogeneity from immunofluorescence pathology samples, using a set of 3 basic breast cancer biomarkers as a test case. We learn a set of dominant biomarker intensity patterns and map the spatial distribution of the biomarker patterns with a network. We then describe the pairwise association statistics for each pattern within the network using pointwise mutual information (PMI) and visually represent heterogeneity with a two-dimensional map. Results: We found a salient set of 8 biomarker patterns to describe cellular phenotypes from a tissue microarray cohort containing 4 different breast cancer subtypes. After computing PMI for each pair of biomarker patterns in each patient and tumor replicate, we visualize the interactions that contribute to the resulting association statistics. Then, we demonstrate the potential for using PMI as a diagnostic biomarker, by comparing PMI maps and heterogeneity scores from patients across the 4 different cancer subtypes. Estrogen receptor positive invasive lobular carcinoma patient, AL13-6, exhibited the highest heterogeneity score among those tested, while estrogen receptor negative invasive ductal carcinoma patient, AL13-14, exhibited the lowest heterogeneity score. Conclusions: This paper presents an approach for describing intratumor heterogeneity, in a quantitative fashion (via PMI), which departs from the purely qualitative approaches currently used in the clinic. PMI is generalizable to highly multiplexed/hyperplexed immunofluorescence images, as well as spatial data from complementary in situ methods including FISSEQ and CyTOF, sampling many different components within the TME. We hypothesize that PMI will uncover key spatial interactions in the TME that contribute to disease proliferation and progression. PMID:27994939

Topography and Radiative Forcing Patterns on Glaciers in the Karakoram Himalaya

NASA Astrophysics Data System (ADS)

Dobreva, I. D.; Bishop, M. P.; Liu, J. C.; Liang, D.

2015-12-01

Glaciers in the western Himalaya exhibit significant spatial variations in morphology and dynamics. Climate, topography and debris cover variations are thought to significantly affect glacier fluctuations and glacier sensitivity to climate change, although the role of topography and radiative forcing have not been adequately characterized and related to glacier fluctuations and dynamics. Consequently, we examined the glaciers in the Karakoram Himalaya, as they exhibit high spatial variability in glacier fluctuation rates and ice dynamics including flow velocity and surging. Specifically, we wanted to examine the relationships between these glacier characteristics and temporal patterns of surface irradiance over the ablation season. To accomplish this, we developed and used a rigorous GIS-based solar radiative transfer model that accounts for the direct and diffuse-skylight irradiance components. The model accounts for multiple topographic effects on the magnitude of irradiance reaching glacier surfaces. We specifically used the ASTER GDEM digital elevation model for irradiance simulations. We then examined temporal patterns of irradiance at the grid-cell level to identify the dominant patterns that were used to train a 3-layer artificial neural network. Our results demonstrate that there are unique spatial and temporal patterns associated with downwasting and surging glaciers, and that these patterns partially account for the spatial distribution of advancing and retreating glaciers. Lower-altitude terminus regions of surging glaciers exhibited relatively low surface irradiance values that decreased in magnitude with time, demonstrating that high-velocity surging glaciers facilitate relief production and exhibit steeper surface irradiance gradients with altitude. Collectively, these results demonstrate the important role that local and regional topography play in governing climate-glacier dynamics in the Himalaya.

Characterization of Disease-Related Covariance Topographies with SSMPCA Toolbox: Effects of Spatial Normalization and PET Scanners

PubMed Central

Peng, Shichun; Ma, Yilong; Spetsieris, Phoebe G; Mattis, Paul; Feigin, Andrew; Dhawan, Vijay; Eidelberg, David

2013-01-01

In order to generate imaging biomarkers from disease-specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [18F]fluorodeoxyglucose PET scans from PD patients and normal controls. Motor-related (PDRP) and cognition-related (PDCP) metabolic patterns were derived from images spatially normalized using four versions of SPM software (spm99, spm2, spm5 and spm8). Differences between these patterns and subject scores were compared across multiple independent groups of patients and control subjects. These patterns and subject scores were highly reproducible with different normalization programs in terms of disease discrimination and cognitive correlation. Subject scores were also comparable in PD patients imaged across multiple PET scanners. Our findings confirm a very high degree of consistency among brain networks and their clinical correlates in PD using images normalized in four different SPM platforms. SSMPCA toolbox can be used reliably for generating disease-specific imaging biomarkers despite the continued evolution of image preprocessing software in the neuroimaging community. Network expressions can be quantified in individual patients independent of different physical characteristics of PET cameras. PMID:23671030

Characterization of disease-related covariance topographies with SSMPCA toolbox: effects of spatial normalization and PET scanners.

PubMed

Peng, Shichun; Ma, Yilong; Spetsieris, Phoebe G; Mattis, Paul; Feigin, Andrew; Dhawan, Vijay; Eidelberg, David

2014-05-01

To generate imaging biomarkers from disease-specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [(18) F]fluorodeoxyglucose PET scans from patients with PD and normal controls. Motor-related (PDRP) and cognition-related (PDCP) metabolic patterns were derived from images spatially normalized using four versions of SPM software (spm99, spm2, spm5, and spm8). Differences between these patterns and subject scores were compared across multiple independent groups of patients and control subjects. These patterns and subject scores were highly reproducible with different normalization programs in terms of disease discrimination and cognitive correlation. Subject scores were also comparable in patients with PD imaged across multiple PET scanners. Our findings confirm a very high degree of consistency among brain networks and their clinical correlates in PD using images normalized in four different SPM platforms. SSMPCA toolbox can be used reliably for generating disease-specific imaging biomarkers despite the continued evolution of image preprocessing software in the neuroimaging community. Network expressions can be quantified in individual patients independent of different physical characteristics of PET cameras. Copyright © 2013 Wiley Periodicals, Inc.

Species turnover drives β-diversity patterns across multiple spatial scales of plant-galling interactions in mountaintop grasslands.

PubMed

Coelho, Marcel Serra; Carneiro, Marco Antônio Alves; Branco, Cristina Alves; Borges, Rafael Augusto Xavier; Fernandes, Geraldo Wilson

2018-01-01

This study describes differences in species richness and composition of the assemblages of galling insects and their host plants at different spatial scales. Sampling was conducted along altitudinal gradients composed of campos rupestres and campos de altitude of two mountain complexes in southeastern Brazil: Espinhaço Range and Mantiqueira Range. The following hypotheses were tested: i) local and regional richness of host plants and galling insects are positively correlated; ii) beta diversity is the most important component of regional diversity of host plants and galling insects; and iii) Turnover is the main mechanism driving beta diversity of both host plants and galling insects. Local richness of galling insects and host plants increased with increasing regional richness of species, suggesting a pattern of unsaturated communities. The additive partition of regional richness (γ) into local and beta components shows that local richnesses (α) of species of galling insects and host plants are low relative to regional richness; the beta (β) component incorporates most of the regional richness. The multi-scale analysis of additive partitioning showed similar patterns for galling insects and host plants with the local component (α) incorporated a small part of regional richness. Beta diversity of galling insects and host plants were mainly the result of turnover, with little contribution from nesting. Although the species composition of galling insects and host plant species varied among sample sites, mountains and even mountain ranges, local richness remained relatively low. In this way, the addition of local habitats with different landscapes substantially affects regional richness. Each mountain contributes fundamentally to the composition of regional diversity of galling insects and host plants, and so the design of future conservation strategies should incorporate multiple scales.

Development of a Spatial Decision Support System for Analyzing Changes in Hydro-meteorological Risk

NASA Astrophysics Data System (ADS)

van Westen, Cees

2013-04-01

In the framework of the EU FP7 Marie Curie ITN Network "CHANGES: Changing Hydro-meteorological Risks, as Analyzed by a New Generation of European Scientists (http://www.changes-itn.eu)", a spatial decision support system is under development with the aim to analyze the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. The SDSS is one of the main outputs of the CHANGES network, which will develop an advanced understanding of how global changes, related to environmental and climate change as well as socio-economical change, may affect the temporal and spatial patterns of hydro-meteorological hazards and associated risks in Europe; how these changes can be assessed, modeled, and incorporated in sustainable risk management strategies, focusing on spatial planning, emergency preparedness and risk communication. The CHANGES network consists of 11 full partners and 6 associate partners of which 5 private companies, representing 10 European countries. The CHANGES network has hired 12 Early Stage Researchers (ESRs) and is currently hiring 3-6 researchers more for the implementation of the SDSS. The Spatial Decision Support System will be composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to quantitative analysis (using different hazard types, temporal scenarios and vulnerability curves) resulting into risk curves. The platform does not include a component to calculate hazard maps, and existing hazard maps are used as input data for the risk component. The second component of the SDSS is a risk reduction planning component, which forms the core of the platform. This component includes the definition of risk reduction alternatives (related to disaster response planning, risk reduction measures and spatial planning) and links back to the risk assessment module to calculate the new level of risk if the measure is implemented, and a cost-benefit (or cost-effectiveness/ Spatial Multi Criteria Evaluation) component to compare the alternatives and make decision on the optimal one. The third component of the SDSS is a temporal scenario component, which allows to define future scenarios in terms of climate change, land use change and population change, and the time periods for which these scenarios will be made. The component doesn't generate these scenarios but uses input maps for the effect of the scenarios on the hazard and assets maps. The last component is a communication and visualization component, which can compare scenarios and alternatives, not only in the form of maps, but also in other forms (risk curves, tables, graphs). The envisaged users of the platform are organizations involved in planning of risk reduction measures, and that have staff capable of visualizing and analyzing spatial data at a municipal scale. This paper presents the main components of the SDSS and the overall design and plans for the user interface.

Spatial variation in the ecological relationships among the components of Beijing's carbon metabolic system.

PubMed

Xia, Linlin; Fath, Brian D; Scharler, Ursula M; Zhang, Yan

2016-02-15

In this paper, we construct a spatially explicit model of carbon metabolism for the flows of carbon among the components of an urban area. We used the model to identify spatial heterogeneity in the ecological relationships within a carbon metabolic network. We combined land-use and cover type maps for Beijing from 1990 to 2010 with empirical coefficients and socioeconomic data to quantify the flows. We used utility analysis to determine the ecological relationships between the components of the system and analyzed their changes during urban development. We used ArcGIS to analyze their spatial variation. We found that the positive utilities in Beijing decreased over time and that negative relationships mostly outweighed positive relationships after 2000. The main ecological relationships were distributed throughout the entire urban area before 2000; subsequently, exploitation, control, and mutualism relationships became concentrated in the southeast, leaving competition relationships to dominate the northwest. Mutualism relationships were most common for natural components, but were not stable because they were easily disturbed by urban expansion. Transportation and industrial land and urban land were the most important contributors to exploitation and control relationships and may be important indicators of spatial adjustment. Increasing competition relationships unbalanced the carbon metabolism, and limitations on the area of land available for development and on the water resources led to increasingly serious competition. The results provide an objective basis for planning adjustments to Beijing's land-use patterns to improve its carbon metabolism and reduce carbon emission. Copyright © 2015 Elsevier B.V. All rights reserved.

Disrupted global metastability and static and dynamic brain connectivity across individuals in the Alzheimer’s disease continuum

NASA Astrophysics Data System (ADS)

Córdova-Palomera, Aldo; Kaufmann, Tobias; Persson, Karin; Alnæs, Dag; Doan, Nhat Trung; Moberget, Torgeir; Lund, Martina Jonette; Barca, Maria Lage; Engvig, Andreas; Brækhus, Anne; Engedal, Knut; Andreassen, Ole A.; Selbæk, Geir; Westlye, Lars T.

2017-01-01

As findings on the neuropathological and behavioral components of Alzheimer’s disease (AD) continue to accrue, converging evidence suggests that macroscale brain functional disruptions may mediate their association. Recent developments on theoretical neuroscience indicate that instantaneous patterns of brain connectivity and metastability may be a key mechanism in neural communication underlying cognitive performance. However, the potential significance of these patterns across the AD spectrum remains virtually unexplored. We assessed the clinical sensitivity of static and dynamic functional brain disruptions across the AD spectrum using resting-state fMRI in a sample consisting of AD patients (n = 80) and subjects with either mild (n = 44) or subjective (n = 26) cognitive impairment (MCI, SCI). Spatial maps constituting the nodes in the functional brain network and their associated time-series were estimated using spatial group independent component analysis and dual regression, and whole-brain oscillatory activity was analyzed both globally (metastability) and locally (static and dynamic connectivity). Instantaneous phase metrics showed functional coupling alterations in AD compared to MCI and SCI, both static (putamen, dorsal and default-mode) and dynamic (temporal, frontal-superior and default-mode), along with decreased global metastability. The results suggest that brains of AD patients display altered oscillatory patterns, in agreement with theoretical premises on cognitive dynamics.

Fractionating the neural correlates of individual working memory components underlying arithmetic problem solving skills in children

PubMed Central

Metcalfe, Arron W. S.; Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Menon, Vinod

2013-01-01

Baddeley and Hitch’s multi-component working memory (WM) model has played an enduring and influential role in our understanding of cognitive abilities. Very little is known, however, about the neural basis of this multi-component WM model and the differential role each component plays in mediating arithmetic problem solving abilities in children. Here, we investigate the neural basis of the central executive (CE), phonological (PL) and visuo-spatial (VS) components of WM during a demanding mental arithmetic task in 7–9 year old children (N=74). The VS component was the strongest predictor of math ability in children and was associated with increased arithmetic complexity-related responses in left dorsolateral and right ventrolateral prefrontal cortices as well as bilateral intra-parietal sulcus and supramarginal gyrus in posterior parietal cortex. Critically, VS, CE and PL abilities were associated with largely distinct patterns of brain response. Overlap between VS and CE components was observed in left supramarginal gyrus and no overlap was observed between VS and PL components. Our findings point to a central role of visuo-spatial WM during arithmetic problem-solving in young grade-school children and highlight the usefulness of the multi-component Baddeley and Hitch WM model in fractionating the neural correlates of arithmetic problem solving during development. PMID:24212504

Use of artificial landscapes to isolate controls on burn probability

Treesearch

Marc-Andre Parisien; Carol Miller; Alan A. Ager; Mark A. Finney

2010-01-01

Techniques for modeling burn probability (BP) combine the stochastic components of fire regimes (ignitions and weather) with sophisticated fire growth algorithms to produce high-resolution spatial estimates of the relative likelihood of burning. Despite the numerous investigations of fire patterns from either observed or simulated sources, the specific influence of...

Geographical and Temporal Body Size Variation in a Reptile: Roles of Sex, Ecology, Phylogeny and Ecology Structured in Phylogeny

PubMed Central

Aragón, Pedro; Fitze, Patrick S.

2014-01-01

Geographical body size variation has long interested evolutionary biologists, and a range of mechanisms have been proposed to explain the observed patterns. It is considered to be more puzzling in ectotherms than in endotherms, and integrative approaches are necessary for testing non-exclusive alternative mechanisms. Using lacertid lizards as a model, we adopted an integrative approach, testing different hypotheses for both sexes while incorporating temporal, spatial, and phylogenetic autocorrelation at the individual level. We used data on the Spanish Sand Racer species group from a field survey to disentangle different sources of body size variation through environmental and individual genetic data, while accounting for temporal and spatial autocorrelation. A variation partitioning method was applied to separate independent and shared components of ecology and phylogeny, and estimated their significance. Then, we fed-back our models by controlling for relevant independent components. The pattern was consistent with the geographical Bergmann's cline and the experimental temperature-size rule: adults were larger at lower temperatures (and/or higher elevations). This result was confirmed with additional multi-year independent data-set derived from the literature. Variation partitioning showed no sex differences in phylogenetic inertia but showed sex differences in the independent component of ecology; primarily due to growth differences. Interestingly, only after controlling for independent components did primary productivity also emerge as an important predictor explaining size variation in both sexes. This study highlights the importance of integrating individual-based genetic information, relevant ecological parameters, and temporal and spatial autocorrelation in sex-specific models to detect potentially important hidden effects. Our individual-based approach devoted to extract and control for independent components was useful to reveal hidden effects linked with alternative non-exclusive hypothesis, such as those of primary productivity. Also, including measurement date allowed disentangling and controlling for short-term temporal autocorrelation reflecting sex-specific growth plasticity. PMID:25090025

Spatial and temporal patterns of airflow across a foredune and beach surface under offshore winds: implications for aeolian sediment transport

NASA Astrophysics Data System (ADS)

Jackson, D.; Delgado-Fernandez, I.; Lynch, K.; Baas, A. C.; Cooper, J. A.; Beyers, M.

2010-12-01

The input of aeolian sediment into foredune systems from beaches represents a key component of sediment budget analysis along many soft sedimentary coastlines. Where there are significant offshore wind components in local wind regimes this is normally excluded from analysis. However, recent work has shown that if the topography of the foredune is favourable then this offshore component is steered or undergoes flow reversal through leeside eddying to give onshore transport events at the back beach under offshore flow conditions. At particular distances from the foredune crest flow reattaches to the surface to continue its incident offshore direction. The location of this reattachment point has important implications for aeolian transport of sand on the back beach and foredune toe locations. This study reports initial results where the positioning of the reattachment point is mobile and is driven by incident wind velocity (at the foredune crest) and the actual undulations of the foredune crest’s topography, dictating heterogeneous flow behaviour at the beach. Using detailed field measurements (25 Hz, three-dimensional sonic anemometry) and computational fluid dynamic modelling, a temporal and spatial pattern of reattachment positions are described. Implications for aeolian transport and dune evolution are also examined.

Ultrasound Technologies for the Spatial Patterning of Cells and Extracellular Matrix Proteins and the Vascularization of Engineered Tissue

NASA Astrophysics Data System (ADS)

Garvin, Kelley A.

Technological advancements in the field of tissue engineering could save the lives of thousands of organ transplant patients who die each year while waiting for donor organs. Currently, two of the primary challenges preventing tissue engineers from developing functional replacement tissues and organs are the need to recreate complex cell and extracellular microenvironments and to vascularize the tissue to maintain cell viability and function. Ultrasound is a form of mechanical energy that can noninvasively and nondestructively interact with tissues at the cell and protein level. In this thesis, novel ultrasound-based technologies were developed for the spatial patterning of cells and extracellular matrix proteins and the vascularization of three-dimensional engineered tissue constructs. Acoustic radiation forces associated with ultrasound standing wave fields were utilized to noninvasively control the spatial organization of cells and cell-bound extracellular matrix proteins within collagen-based engineered tissue. Additionally, ultrasound induced thermal mechanisms were exploited to site-specifically pattern various extracellular matrix collagen microstructures within a single engineered tissue construct. Finally, ultrasound standing wave field technology was used to promote the rapid and extensive vascularization of three-dimensional tissue constructs. As such, the ultrasound technologies developed in these studies have the potential to provide the field of tissue engineering with novel strategies to spatially pattern cells and extracellular matrix components and to vascularize engineered tissue, and thus, could advance the fabrication of functional replacement tissues and organs in the field of tissue engineering.

The upper spatial limit for perception of displacement is affected by preceding motion.

PubMed

Stefanova, Miroslava; Mateeff, Stefan; Hohnsbein, Joachim

2009-03-01

The upper spatial limit D(max) for perception of apparent motion of a random dot pattern may be strongly affected by another, collinear, motion that precedes it [Mateeff, S., Stefanova, M., &. Hohnsbein, J. (2007). Perceived global direction of a compound of real and apparent motion. Vision Research, 47, 1455-1463]. In the present study this phenomenon was studied with two-dimensional motion stimuli. A random dot pattern moved alternately in the vertical and oblique direction (zig-zag motion). The vertical motion was of 1.04 degrees length; it was produced by three discrete spatial steps of the dots. Thereafter the dots were displaced by a single spatial step in oblique direction. Each motion lasted for 57ms. The upper spatial limit for perception of the oblique motion was measured under two conditions: the vertical component of the oblique motion and the vertical motion were either in the same or in opposite directions. It was found that the perception of the oblique motion was strongly influenced by the relative direction of the vertical motion that preceded it; in the "same" condition the upper spatial limit was much shorter than in the "opposite" condition. Decreasing the speed of the vertical motion reversed this effect. Interpretations based on networks of motion detectors and on Gestalt theory are discussed.

Large-scale spatio-temporal monitoring highlights hotspots of demersal fish diversity in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Granger, Victoria; Fromentin, Jean-Marc; Bez, Nicolas; Relini, Giulio; Meynard, Christine N.; Gaertner, Jean-Claude; Maiorano, Porzia; Garcia Ruiz, Cristina; Follesa, Cristina; Gristina, Michele; Peristeraki, Panagiota; Brind'Amour, Anik; Carbonara, Pierluigi; Charilaou, Charis; Esteban, Antonio; Jadaud, Angélique; Joksimovic, Aleksandar; Kallianiotis, Argyris; Kolitari, Jerina; Manfredi, Chiara; Massuti, Enric; Mifsud, Roberta; Quetglas, Antoni; Refes, Wahid; Sbrana, Mario; Vrgoc, Nedo; Spedicato, Maria Teresa; Mérigot, Bastien

2015-01-01

Increasing human pressures and global environmental change may severely affect the diversity of species assemblages and associated ecosystem services. Despite the recent interest in phylogenetic and functional diversity, our knowledge on large spatio-temporal patterns of demersal fish diversity sampled by trawling remains still incomplete, notably in the Mediterranean Sea, one of the most threatened marine regions of the world. We investigated large spatio-temporal diversity patterns by analysing a dataset of 19,886 hauls from 10 to 800 m depth performed annually during the last two decades by standardised scientific bottom trawl field surveys across the Mediterranean Sea, within the MEDITS program. A multi-component (eight diversity indices) and multi-scale (local assemblages, biogeographic regions to basins) approach indicates that only the two most traditional components (species richness and evenness) were sufficient to reflect patterns in taxonomic, phylogenetic or functional richness and divergence. We also put into question the use of widely computed indices that allow comparing directly taxonomic, phylogenetic and functional diversity within a unique mathematical framework. In addition, demersal fish assemblages sampled by trawl do not follow a continuous decreasing longitudinal/latitudinal diversity gradients (spatial effects explained up to 70.6% of deviance in regression tree and generalised linear models), for any of the indices and spatial scales analysed. Indeed, at both local and regional scales species richness was relatively high in the Iberian region, Malta, the Eastern Ionian and Aegean seas, meanwhile the Adriatic Sea and Cyprus showed a relatively low level. In contrast, evenness as well as taxonomic, phylogenetic and functional divergences did not show regional hotspots. All studied diversity components remained stable over the last two decades. Overall, our results highlight the need to use complementary diversity indices through different spatial scales when developing conservation strategies and defining delimitations for protected areas.

A Spatially-Explicit Modeling Approach to Examine the Interaction of Reproductive Traits and Landscape Characteristics on Arctic Shrub Expansion

NASA Astrophysics Data System (ADS)

Naito, A. T.; Cairns, D. M.; Feldman, R. M.; Grant, W. E.

2014-12-01

Shrub expansion is one of the most recognized components of terrestrial Arctic change. While experimental work has provided valuable insights into its fine-scale drivers and implications, the contribution of shrub reproductive characteristics to their spatial patterns is poorly understood at broader scales. Building upon our previous work in river valleys in northern Alaska, we developed a C#-based spatially-explicit model that simulates historic landscape-scale shrub establishment between the 1970s and the late 2000s on a yearly time-step while accounting for parameters relating to different reproduction modes (clonal development with and without the "mass effect" and short-distance dispersal), as well as the presence and absence of the interaction of hydrologic constraints using the topographic wetness index. We examined these treatments on floodplains, valley slopes, and interfluves in the Ayiyak, Colville, and Kurupa River valleys. After simulating 30 landscape realizations using each parameter combination, we quantified the spatial characteristics (patch density, edge density, patch size variability, area-weighted shape index, area-weighted fractal dimension index, and mean distance between patches) of the resulting shrub patches on the simulation end date using FRAGSTATS. We used Principal Components Analysis to determine which treatments produced spatial characteristics most similar to those observed in the late 2000s. Based upon our results, we hypothesize that historic shrub expansion in northern Alaska has been driven in part by clonal reproduction with the "mass effect" or short-distance dispersal (< 5 m). The interactive effect of hydrologic characteristics, however, is less clear. These hypotheses may then be tested in future work involving field observations. Given the potential that climate change may facilitate a shift from a clonal to a sexual reproductive strategy, this model may facilitate predictions regarding future Arctic vegetation patterns.

Two modes of the silk road pattern and their interannual variability simulated by LASG/IAP AGCM SAMIL2.0

NASA Astrophysics Data System (ADS)

Song, Fengfei; Zhou, Tianjun; Wang, Lu

2013-05-01

In this study, two modes of the Silk Road pattern were investigated using NCEP2 reanalysis data and the simulation produced by Spectral Atmospheric Circulation Model of IAP LASG, Version 2 (SAMIL2.0) that was forced by SST observation data. The horizontal distribution of both modes were reasonably reproduced by the simulation, with a pattern correlation coefficient of 0.63 for the first mode and 0.62 for the second mode. The wave train was maintained by barotropic energy conversion (denoted as CK) and baroclinic energy conversion (denoted as CP) from the mean flow. The distribution of CK was dominated by its meridional component (CK y ) in both modes. When integrated spatially, CK y was more efficient than its zonal component (CK x ) in the first mode but less in the second mode. The distribution and efficiency of CK were not captured well by SAMIL2.0. However, the model performed reasonably well at reproducing the distribution and efficiency of CP in both modes. Because CP is more efficient than CK, the spatial patterns of the Silk Road pattern were well reproduced. Interestingly, the temporal phase of the second mode was well captured by a single-member simulation. However, further analysis of other ensemble runs demonstrated that the successful reproduction of the temporal phase was a result of internal variability rather than a signal of SST forcing. The analysis shows that the observed temporal variations of both CP and CK were poorly reproduced, leading to the low accuracy of the temporal phase of the Silk Road pattern in the simulation.

Spatiotemporal Patterns of Precipitation-Modulated Landslide Deformation From Independent Component Analysis of InSAR Time Series

NASA Astrophysics Data System (ADS)

Cohen-Waeber, J.; Bürgmann, R.; Chaussard, E.; Giannico, C.; Ferretti, A.

2018-02-01

Long-term landslide deformation is disruptive and costly in urbanized environments. We rely on TerraSAR-X satellite images (2009-2014) and an improved data processing algorithm (SqueeSAR™) to produce an exceptionally dense Interferometric Synthetic Aperture Radar ground deformation time series for the San Francisco East Bay Hills. Independent and principal component analyses of the time series reveal four distinct spatial and temporal surface deformation patterns in the area around Blakemont landslide, which we relate to different geomechanical processes. Two components of time-dependent landslide deformation isolate continuous motion and motion driven by precipitation-modulated pore pressure changes controlled by annual seasonal cycles and multiyear drought conditions. Two components capturing more widespread seasonal deformation separate precipitation-modulated soil swelling from annual cycles that may be related to groundwater level changes and thermal expansion of buildings. High-resolution characterization of landslide response to precipitation is a first step toward improved hazard forecasting.

Complex Topographic Feature Ontology Patterns

USGS Publications Warehouse

Varanka, Dalia E.; Jerris, Thomas J.

2015-01-01

Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

PubMed

Orbán, Levente L; Chartier, Sylvain

2015-01-01

Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

The role of dispersal mode and habitat specialization for metacommunity structure of shallow beach invertebrates.

PubMed

Rodil, Iván F; Lucena-Moya, Paloma; Jokinen, Henri; Ollus, Victoria; Wennhage, Håkan; Villnäs, Anna; Norkko, Alf

2017-01-01

Metacommunity ecology recognizes the interplay between local and regional patterns in contributing to spatial variation in community structure. In aquatic systems, the relative importance of such patterns depends mainly on the potential connectivity of the specific system. Thus, connectivity is expected to increase in relation to the degree of water movement, and to depend on the specific traits of the study organism. We examined the role of environmental and spatial factors in structuring benthic communities from a highly connected shallow beach network using a metacommunity approach. Both factors contributed to a varying degree to the structure of the local communities suggesting that environmental filters and dispersal-related mechanisms played key roles in determining abundance patterns. We categorized benthic taxa according to their dispersal mode (passive vs. active) and habitat specialization (generalist vs. specialist) to understand the relative importance of environment and dispersal related processes for shallow beach metacommunities. Passive dispersers were predicted by a combination of environmental and spatial factors, whereas active dispersers were not spatially structured and responded only to local environmental factors. Generalists were predicted primarily by spatial factors, while specialists were only predicted by local environmental factors. The results suggest that the role of the spatial component in metacommunity organization is greater in open coastal waters, such as shallow beaches, compared to less-connected environmentally controlled aquatic systems. Our results also reveal a strong environmental role in structuring the benthic metacommunity of shallow beaches. Specifically, we highlight the sensitivity of shallow beach macrofauna to environmental factors related to eutrophication proxies.

The role of dispersal mode and habitat specialization for metacommunity structure of shallow beach invertebrates

PubMed Central

Lucena-Moya, Paloma; Jokinen, Henri; Ollus, Victoria; Wennhage, Håkan; Villnäs, Anna; Norkko, Alf

2017-01-01

Metacommunity ecology recognizes the interplay between local and regional patterns in contributing to spatial variation in community structure. In aquatic systems, the relative importance of such patterns depends mainly on the potential connectivity of the specific system. Thus, connectivity is expected to increase in relation to the degree of water movement, and to depend on the specific traits of the study organism. We examined the role of environmental and spatial factors in structuring benthic communities from a highly connected shallow beach network using a metacommunity approach. Both factors contributed to a varying degree to the structure of the local communities suggesting that environmental filters and dispersal-related mechanisms played key roles in determining abundance patterns. We categorized benthic taxa according to their dispersal mode (passive vs. active) and habitat specialization (generalist vs. specialist) to understand the relative importance of environment and dispersal related processes for shallow beach metacommunities. Passive dispersers were predicted by a combination of environmental and spatial factors, whereas active dispersers were not spatially structured and responded only to local environmental factors. Generalists were predicted primarily by spatial factors, while specialists were only predicted by local environmental factors. The results suggest that the role of the spatial component in metacommunity organization is greater in open coastal waters, such as shallow beaches, compared to less-connected environmentally controlled aquatic systems. Our results also reveal a strong environmental role in structuring the benthic metacommunity of shallow beaches. Specifically, we highlight the sensitivity of shallow beach macrofauna to environmental factors related to eutrophication proxies. PMID:28196112

A Review of Spatial Variation of Inorganic Nitrogen (N) Wet Deposition in China

PubMed Central

Liu, Lei; Zhang, Xiuying; Wang, Shanqian; Lu, Xuehe; Ouyang, Xiaoying

2016-01-01

Atmospheric nitrogen (N) deposition (Ndep), an important component of the global N cycle, has increased sharply in recent decades in China. Although there were already some studies on Ndep on a national scale, there were some gaps on the magnitude and the spatial patterns of Ndep. In this study, a national-scale Ndep pattern was constructed based on 139 published papers from 2003 to 2014 and the effects of precipitation (P), energy consumption (E) and N fertilizer use (FN) on spatial patterns of Ndep were analyzed. The wet deposition flux of NH4+-N, NO3--N and total Ndep was 6.83, 5.35 and 12.18 kg ha-1 a-1, respectively. Ndep exhibited a decreasing gradient from southeast to northwest of China. Through accuracy assessment of the spatial Ndep distribution and comparisons with other studies, the spatial Ndep distribution by Lu and Tian and this study both gained high accuracy. A strong exponential function was found between P and Ndep, FN and Ndep and E and Ndep, and P and FN had higher contribution than E on the spatial variation of Ndep. Fossil fuel combustion was the main contributor for NO3--N (86.0%) and biomass burning contributed 5.4% on the deposition of NO3--N. The ion of NH4+ was mainly from agricultural activities (85.9%) and fossil fuel combustion (6.0%). Overall, Ndep in China might be considerably affected by the high emissions of NOx and NH3 from fossil fuel combustion and agricultural activities. PMID:26731264

The effect of feature-based attention on flanker interference processing: An fMRI-constrained source analysis.

PubMed

Siemann, Julia; Herrmann, Manfred; Galashan, Daniela

2018-01-25

The present study examined whether feature-based cueing affects early or late stages of flanker conflict processing using EEG and fMRI. Feature cues either directed participants' attention to the upcoming colour of the target or were neutral. Validity-specific modulations during interference processing were investigated using the N200 event-related potential (ERP) component and BOLD signal differences. Additionally, both data sets were integrated using an fMRI-constrained source analysis. Finally, the results were compared with a previous study in which spatial instead of feature-based cueing was applied to an otherwise identical flanker task. Feature-based and spatial attention recruited a common fronto-parietal network during conflict processing. Irrespective of attention type (feature-based; spatial), this network responded to focussed attention (valid cueing) as well as context updating (invalid cueing), hinting at domain-general mechanisms. However, spatially and non-spatially directed attention also demonstrated domain-specific activation patterns for conflict processing that were observable in distinct EEG and fMRI data patterns as well as in the respective source analyses. Conflict-specific activity in visual brain regions was comparable between both attention types. We assume that the distinction between spatially and non-spatially directed attention types primarily applies to temporal differences (domain-specific dynamics) between signals originating in the same brain regions (domain-general localization).

Efficient use of bit planes in the generation of motion stimuli

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.; Stone, Leland S.

1988-01-01

The production of animated motion sequences on computer-controlled display systems presents a technical problem because large images cannot be transferred from disk storage to image memory at conventional frame rates. A technique is described in which a single base image can be used to generate a broad class of motion stimuli without the need for such memory transfers. This technique was applied to the generation of drifting sine-wave gratings (and by extension, sine wave plaids). For each drifting grating, sine and cosine spatial phase components are first reduced to 1 bit/pixel using a digital halftoning technique. The resulting pairs of 1-bit images are then loaded into pairs of bit planes of the display memory. To animate the patterns, the display hardware's color lookup table is modified on a frame-by-frame basis; for each frame the lookup table is set to display a weighted sum of the spatial sine and cosine phase components. Because the contrasts and temporal frequencies of the various components are mutually independent in each frame, the sine and cosine components can be counterphase modulated in temporal quadrature, yielding a single drifting grating. Using additional bit planes, multiple drifting gratings can be combined to form sine-wave plaid patterns. A large number of resultant plaid motions can be produced from a single image file because the temporal frequencies of all the components can be varied independently. For a graphics device having 8 bits/pixel, up to four drifting gratings may be combined, each having independently variable contrast and speed.

Excitation and Adaptation in Bacteria–a Model Signal Transduction System that Controls Taxis and Spatial Pattern Formation

PubMed Central

Othmer, Hans G.; Xin, Xiangrong; Xue, Chuan

2013-01-01

The machinery for transduction of chemotactic stimuli in the bacterium E. coli is one of the most completely characterized signal transduction systems, and because of its relative simplicity, quantitative analysis of this system is possible. Here we discuss models which reproduce many of the important behaviors of the system. The important characteristics of the signal transduction system are excitation and adaptation, and the latter implies that the transduction system can function as a “derivative sensor” with respect to the ligand concentration in that the DC component of a signal is ultimately ignored if it is not too large. This temporal sensing mechanism provides the bacterium with a memory of its passage through spatially- or temporally-varying signal fields, and adaptation is essential for successful chemotaxis. We also discuss some of the spatial patterns observed in populations and indicate how cell-level behavior can be embedded in population-level descriptions. PMID:23624608

Climatic suitability, isolation by distance and river resistance explain genetic variation in a Brazilian whiptail lizard.

PubMed

Oliveira, Eliana Faria; Martinez, Pablo Ariel; São-Pedro, Vinícius Avelar; Gehara, Marcelo; Burbrink, Frank Thomas; Mesquita, Daniel Oliveira; Garda, Adrian Antonio; Colli, Guarino Rinaldi; Costa, Gabriel Correa

2018-03-01

Spatial patterns of genetic variation can help understand how environmental factors either permit or restrict gene flow and create opportunities for regional adaptations. Organisms from harsh environments such as the Brazilian semiarid Caatinga biome may reveal how severe climate conditions may affect patterns of genetic variation. Herein we combine information from mitochondrial DNA with physical and environmental features to study the association between different aspects of the Caatinga landscape and spatial genetic variation in the whiptail lizard Ameivula ocellifera. We investigated which of the climatic, environmental, geographical and/or historical components best predict: (1) the spatial distribution of genetic diversity, and (2) the genetic differentiation among populations. We found that genetic variation in A. ocellifera has been influenced mainly by temperature variability, which modulates connectivity among populations. Past climate conditions were important for shaping current genetic diversity, suggesting a time lag in genetic responses. Population structure in A. ocellifera was best explained by both isolation by distance and isolation by resistance (main rivers). Our findings indicate that both physical and climatic features are important for explaining the observed patterns of genetic variation across the xeric Caatinga biome.

Identification of Resting State Networks Involved in Executive Function.

PubMed

Connolly, Joanna; McNulty, Jonathan P; Boran, Lorraine; Roche, Richard A P; Delany, David; Bokde, Arun L W

2016-06-01

The structural networks in the human brain are consistent across subjects, and this is reflected also in that functional networks across subjects are relatively consistent. These findings are not only present during performance of a goal oriented task but there are also consistent functional networks during resting state. It suggests that goal oriented activation patterns may be a function of component networks identified using resting state. The current study examines the relationship between resting state networks measured and patterns of neural activation elicited during a Stroop task. The association between the Stroop-activated networks and the resting state networks was quantified using spatial linear regression. In addition, we investigated if the degree of spatial association of resting state networks with the Stroop task may predict performance on the Stroop task. The results of this investigation demonstrated that the Stroop activated network can be decomposed into a number of resting state networks, which were primarily associated with attention, executive function, visual perception, and the default mode network. The close spatial correspondence between the functional organization of the resting brain and task-evoked patterns supports the relevance of resting state networks in cognitive function.

Assessing Potential Future Carbon Dynamics with Climate Change and Fire Management in a Mountainous Landscape on the Olympic Peninsula, Washington, USA

NASA Astrophysics Data System (ADS)

Kennedy, R. S.

2010-12-01

Forests of the mountainous landscapes of the maritime Pacific Northwestern USA may have high carbon sequestration potential via their high productivity and moderate to infrequent fire regimes. With climate change, there may be shifts in incidence and severity of fire, especially in the drier areas of the region, via changes to forest productivity and hydrology, and consequent effects to C sequestration and forest structure. To explore this issue, I assessed potential effects of fire management (little fire suppression/wildland fire management/highly effective fire suppression) under two climate change scenarios on future C sequestration dynamics (amounts and spatial pattern) in Olympic National Park, WA, over a 500-year simulation period. I used the simulation platform FireBGCv2, which contains a mechanistic, individual tree succession model, a spatially explicit climate-based biophysical model that uses daily weather data, and a spatially explicit fire model incorporating ignition, spread, and effects on ecosystem components. C sequestration patterns varied over time and spatial and temporal patterns differed somewhat depending on the climate change scenario applied and the fire management methods employed. Under the more extreme climate change scenario with little fire suppression, fires were most frequent and severe and C sequestration decreased. General trends were similar under the more moderate climate change scenario, as compared to current climate, but spatial patterns differed. Both climate change scenarios under highly effective fire suppression showed about 50% of starting total C after the initial transition phase, whereas with 10% fire suppression both scenarios exhibited about 10% of starting amounts. Areas of the landscape that served as refugia for older forest under increasing frequency of high severity fire were also hotspots for C sequestration in a landscape experiencing increasing frequency of disturbance with climate change.

Visuospatial deficits in schizophrenia: central executive and memory subsystems impairments.

PubMed

Leiderman, Eduardo A; Strejilevich, Sergio A

2004-06-01

Object and spatial visual working memory are impaired in schizophrenic patients. It is not clear if the impairments reside in each memory subsystem alone or also in the central executive component that coordinates these processes. In order to elucidate which memory component is impaired, we developed a paradigm with single spatial and object working memory tasks and dual ones with two different delays (5 and 30 s). Fifteen schizophrenic patients and 14 control subjects performed these tests. Schizophrenic patients had a poorer performance compared to normal controls in all tasks and in all time delays. Both schizophrenics and controls performed significantly worse in the object task than in the spatial task. The performance was even worse in the dual task compared to the singles ones in schizophrenic patients but not in controls. These data suggest that visuospatial performance deficits in schizophrenia are due to both visuospatial memory subsystems impairments and central executive ones. The pattern of deficits observed points to a codification or evocation deficit and not to a maintenance one.

Contact line motion over substrates with spatially non-uniform properties

NASA Astrophysics Data System (ADS)

Ajaev, Vladimir; Gatapova, Elizaveta; Kabov, Oleg

2017-11-01

We develop mathematical models of moving contact lines over flat solid surfaces with spatial variation of temperature and wetting properties under the conditions when evaporation is significant. The gas phase is assumed to be pure vapor and a lubrication-type framework is employed for describing viscous flow in the liquid. Marangoni stresses at the liquid surface arise as a result of temperature variation in the vapor phase, non-equilibrium effects during evaporation at the interface, and Kelvin effect. The relative importance of these three factors is determined. Variation of wetting properties is modeled through a two-component disjoining pressure, with the main focus on spatially periodic patterns leading to time-periodic variation of the contact line speed.

Dynamic in-plane potential gradients for actively controlling electrochemical reactions: Part I. Characterization of 1- and 2-component alkanethiol monolayer gradients on thin gold films. Part II. Applications of in-plane potential gradients

NASA Astrophysics Data System (ADS)

Balss, Karin Maria

The research contained in this thesis is focused on the formation and characterization of surface composition gradients on thin gold films that are formed by applications of in-plane potential gradients. Injecting milliamp currents into thin Au films yields significant in-plane voltage drops so that, rather than assuming a single value of potential, an in-plane potential gradient is imposed on the film which depends on the resistivity of the film, the cross sectional area and the magnitude of the potential drop. Furthermore, the in-plane electric potential gradient means that, relative to a solution reference couple, electrochemical reactions occurs at defined spatial positions corresponding to the local potential, V(x) ˜ E0. The spatial gradient in electrochemical potential can then produce spatially dependent electrochemistry. Surface-chemical potential gradients can be prepared by arranging the spread of potentials to span an electrochemical wave mediating redox-associated adsorption or desorption. Examples of reactions that can be spatially patterned include the electrosorption of alkanethiols and over-potential metal deposition. The unique advantage of this method for patterning spatial compositions is the control of surface coverage in both space and time. The thesis is organized into two parts. In Part I, formation and characterization of 1- and 2-component alkanethiol monolayer gradients is investigated. Numerous surface science tools are employed to examine the distribution in coverage obtained by application of in-plane potential gradients. Macroscopic characterization was obtained by sessile water drop contact angle measurements and surface plasmon resonance imaging. Gradients were also imaged on micron length scales with pulsed-force mode atomic force microscopy. Direct chemical evidence of surface compositions in aromatic thiol surface coverage was obtained by surface-enhanced Raman spectroscopy. In Part II, the applications of in-plane potential gradients is discussed. Electrochemical reactions other than electrosorption of alkanethiols were demonstrated with over-potential deposition of copper onto gold films. One application of these patterns is to control the movement of supermolecular objects. As a first step towards this goal, biological cells were seeded onto gradient patterns containing adhesion promoters and inhibitors. The morphology and adhesion was investigated as a function of concentration along the gradient.

Electromagnetic frozen waves with radial, azimuthal, linear, circular, and elliptical polarizations

NASA Astrophysics Data System (ADS)

Corato-Zanarella, Mateus; Zamboni-Rached, Michel

2016-11-01

Frozen waves (FWs) are a class of diffraction- and attenuation-resistant beams whose intensity pattern along the direction of propagation can be chosen arbitrarily, thus making them relevant for engineering the spatial configuration of optical fields. To date, analyses of such beams have been done essentially for the scalar case, with the vectorial nature of the electromagnetic fields often neglected. Although it is expected that the field components keep the fundamental properties of the scalar FWs, a deeper understanding of their electromagnetic counterparts is mandatory in order to exploit their different possible polarization states. The purpose of this paper is to study the properties of electromagnetic FWs with radial, azimuthal, linear, circular, and elliptical polarizations under paraxial and nonparaxial regimes in nonabsorbing media. An intensity pattern is chosen for a scalar FW, and the vectorial solutions are built after it via the use of Maxwell's equations. The results show that the field components and the longitudinal component of the time-averaged Poynting vector closely follow the pattern chosen even under highly nonparaxial conditions, showing the robustness of the FW structure to parameters variations.

A 3D stand generator for central Appalachian hardwood forests

Treesearch

Jingxin Wang; Yaoxiang Li; Gary W. Miller

2002-01-01

A 3-dimensional (3D) stand generator was developed for central Appalachian hardwood forests. It was designed for a harvesting simulator to examine the interactions of stand, harvest, and machine. The Component Object Model (COM) was used to design and implement the program. Input to the generator includes species composition, stand density, and spatial pattern. Output...

Fringe pattern demodulation with a two-frame digital phase-locked loop algorithm.

PubMed

Gdeisat, Munther A; Burton, David R; Lalor, Michael J

2002-09-10

A novel technique called a two-frame digital phase-locked loop for fringe pattern demodulation is presented. In this scheme, two fringe patterns with different spatial carrier frequencies are grabbed for an object. A digital phase-locked loop algorithm tracks and demodulates the phase difference between both fringe patterns by employing the wrapped phase components of one of the fringe patterns as a reference to demodulate the second fringe pattern. The desired phase information can be extracted from the demodulated phase difference. We tested the algorithm experimentally using real fringe patterns. The technique is shown to be suitable for noncontact measurement of objects with rapid surface variations, and it outperforms the Fourier fringe analysis technique in this aspect. Phase maps produced withthis algorithm are noisy in comparison with phase maps generated with the Fourier fringe analysis technique.

Cerebellar contribution to spatial event processing: involvement in procedural and working memory components.

PubMed

Mandolesi, L; Leggio, M G; Graziano, A; Neri, P; Petrosini, L

2001-12-01

Spatial function is one of the cognitive functions altered in the presence of cerebellar lesions. We investigated the cerebellar contribution to the acquisition of spatial procedural and working memory components by means of a radial maze. To establish whether a cerebellar lesion would cause a deficit in solving the radial maze, a first experiment was carried out by using a full-baited maze procedure in different experimental groups, with or without cerebellar lesion and with or without pretraining. Non-pretrained hemicerebellectomized (HCbed) animals exhibited impaired performances in all (motor, spatial and procedural) task aspects. Pre-trained HCbed animals performed similarly to control animals in the task aspects linked to the processing of spatial and procedural factors. To distinguish procedural from working memory components, a forced-choice paradigm of the radial maze was used in the second experiment. Non-pretrained HCbed rats continued to make a lot of errors and show severe perseverative tendencies, already observed in the first experiment, supporting a specific cerebellar role in acquiring new behaviours and in modifying them in relation to the context. Interestingly, hindered from putting the acquired explorative patterns into action and compelled to use only working memory abilities, the pretrained HCbed group exhibited a dramatic worsening of performance. In conclusion, the present findings demonstrate that cerebellar damage induces a specific behaviour in radial maze tasks, characterized by an inflexible use of the procedures (if indeed any procedure was acquired before the lesion) and by a severe impairment in working memory processes.

Protein subcellular location pattern classification in cellular images using latent discriminative models.

PubMed

Li, Jieyue; Xiong, Liang; Schneider, Jeff; Murphy, Robert F

2012-06-15

Knowledge of the subcellular location of a protein is crucial for understanding its functions. The subcellular pattern of a protein is typically represented as the set of cellular components in which it is located, and an important task is to determine this set from microscope images. In this article, we address this classification problem using confocal immunofluorescence images from the Human Protein Atlas (HPA) project. The HPA contains images of cells stained for many proteins; each is also stained for three reference components, but there are many other components that are invisible. Given one such cell, the task is to classify the pattern type of the stained protein. We first randomly select local image regions within the cells, and then extract various carefully designed features from these regions. This region-based approach enables us to explicitly study the relationship between proteins and different cell components, as well as the interactions between these components. To achieve these two goals, we propose two discriminative models that extend logistic regression with structured latent variables. The first model allows the same protein pattern class to be expressed differently according to the underlying components in different regions. The second model further captures the spatial dependencies between the components within the same cell so that we can better infer these components. To learn these models, we propose a fast approximate algorithm for inference, and then use gradient-based methods to maximize the data likelihood. In the experiments, we show that the proposed models help improve the classification accuracies on synthetic data and real cellular images. The best overall accuracy we report in this article for classifying 942 proteins into 13 classes of patterns is about 84.6%, which to our knowledge is the best so far. In addition, the dependencies learned are consistent with prior knowledge of cell organization. http://murphylab.web.cmu.edu/software/.

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.

Multi-functional optical signal processing using optical spectrum control circuit

NASA Astrophysics Data System (ADS)

Hayashi, Shuhei; Ikeda, Tatsuhiko; Mizuno, Takayuki; Takahashi, Hiroshi; Tsuda, Hiroyuki

2015-02-01

Processing ultra-fast optical signals without optical/electronic conversion is in demand and time-to-space conversion has been proposed as an effective solution. We have designed and fabricated an arrayed-waveguide grating (AWG) based optical spectrum control circuit (OSCC) using silica planar lightwave circuit (PLC) technology. This device is composed of an AWG, tunable phase shifters and a mirror. The principle of signal processing is to spatially decompose the signal's frequency components by using the AWG. Then, the phase of each frequency component is controlled by the tunable phase shifters. Finally, the light is reflected back to the AWG by the mirror and synthesized. Amplitude of each frequency component can be controlled by distributing the power to high diffraction order light. The spectral controlling range of the OSCC is 100 GHz and its resolution is 1.67 GHz. This paper describes equipping the OSCC with optical coded division multiplex (OCDM) encoder/decoder functionality. The encoding principle is to apply certain phase patterns to the signal's frequency components and intentionally disperse the signal. The decoding principle is also to apply certain phase patterns to the frequency components at the receiving side. If the applied phase pattern compensates the intentional dispersion, the waveform is regenerated, but if the pattern is not appropriate, the waveform remains dispersed. We also propose an arbitrary filter function by exploiting the OSCC's amplitude and phase control attributes. For example, a filtered optical signal transmitted through multiple optical nodes that use the wavelength multiplexer/demultiplexer can be equalized.

Metacommunity ecology meets biogeography: effects of geographical region, spatial dynamics and environmental filtering on community structure in aquatic organisms.

PubMed

Heino, Jani; Soininen, Janne; Alahuhta, Janne; Lappalainen, Jyrki; Virtanen, Risto

2017-01-01

Metacommunity patterns and underlying processes in aquatic organisms have typically been studied within a drainage basin. We examined variation in the composition of six freshwater organismal groups across various drainage basins in Finland. We first modelled spatial structures within each drainage basin using Moran eigenvector maps. Second, we partitioned variation in community structure among three groups of predictors using constrained ordination: (1) local environmental variables, (2) spatial variables, and (3) dummy variable drainage basin identity. Third, we examined turnover and nestedness components of multiple-site beta diversity, and tested the best fit patterns of our datasets using the "elements of metacommunity structure" analysis. Our results showed that basin identity and local environmental variables were significant predictors of community structure, whereas within-basin spatial effects were typically negligible. In half of the organismal groups (diatoms, bryophytes, zooplankton), basin identity was a slightly better predictor of community structure than local environmental variables, whereas the opposite was true for the remaining three organismal groups (insects, macrophytes, fish). Both pure basin and local environmental fractions were, however, significant after accounting for the effects of the other predictor variable sets. All organismal groups exhibited high levels of beta diversity, which was mostly attributable to the turnover component. Our results showed consistent Clementsian-type metacommunity structures, suggesting that subgroups of species responded similarly to environmental factors or drainage basin limits. We conclude that aquatic communities across large scales are mostly determined by environmental and basin effects, which leads to high beta diversity and prevalence of Clementsian community types.

Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG.

PubMed

Bai, Ou; Lin, Peter; Vorbach, Sherry; Li, Jiang; Furlani, Steve; Hallett, Mark

2007-12-01

To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG). Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis (ICA), common spatial patterns analysis (CSP), and surface Laplacian derivation (SLD); temporal filtering using power spectral density estimation (PSD) and discrete wavelet transform (DWT); pattern classification using linear Mahalanobis distance classifier (LMD), quadratic Mahalanobis distance classifier (QMD), Bayesian classifier (BSC), multi-layer perceptron neural network (MLP), probabilistic neural network (PNN), and support vector machine (SVM). A robust multivariate feature selection strategy using a genetic algorithm was employed. The combinations of spatial filtering using ICA and SLD, temporal filtering using PSD and DWT, and classification methods using LMD, QMD, BSC and SVM provided higher performance than those of other combinations. Utilizing one of the better combinations of ICA, PSD and SVM, the discrimination accuracy was as high as 75%. Further feature analysis showed that beta band EEG activity of the channels over right sensorimotor cortex was most appropriate for discrimination of right and left hand movement intention. Effective combinations of computational methods provide possible classification of human movement intention from single trial EEG. Such a method could be the basis for a potential brain-computer interface based on human natural movement, which might reduce the requirement of long-term training. Effective combinations of computational methods can classify human movement intention from single trial EEG with reasonable accuracy.

Visual motion integration by neurons in the middle temporal area of a New World monkey, the marmoset

PubMed Central

Solomon, Selina S; Tailby, Chris; Gharaei, Saba; Camp, Aaron J; Bourne, James A; Solomon, Samuel G

2011-01-01

Abstract The middle temporal area (MT/V5) is an anatomically distinct region of primate visual cortex that is specialized for the processing of image motion. It is generally thought that some neurons in area MT are capable of signalling the motion of complex patterns, but this has only been established in the macaque monkey. We made extracellular recordings from single units in area MT of anaesthetized marmosets, a New World monkey. We show through quantitative analyses that some neurons (35 of 185; 19%) are capable of signalling pattern motion (‘pattern cells’). Across several dimensions, the visual response of pattern cells in marmosets is indistinguishable from that of pattern cells in macaques. Other neurons respond to the motion of oriented contours in a pattern (‘component cells’) or show intermediate properties. In addition, we encountered a subset of neurons (22 of 185; 12%) insensitive to sinusoidal gratings but very responsive to plaids and other two-dimensional patterns and otherwise indistinguishable from pattern cells. We compared the response of each cell class to drifting gratings and dot fields. In pattern cells, directional selectivity was similar for gratings and dot fields; in component cells, directional selectivity was weaker for dot fields than gratings. Pattern cells were more likely to have stronger suppressive surrounds, prefer lower spatial frequencies and prefer higher speeds than component cells. We conclude that pattern motion sensitivity is a feature of some neurons in area MT of both New and Old World monkeys, suggesting that this functional property is an important stage in motion analysis and is likely to be conserved in humans. PMID:21946851

Fractionating the neural correlates of individual working memory components underlying arithmetic problem solving skills in children.

PubMed

Metcalfe, Arron W S; Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Menon, Vinod

2013-10-01

Baddeley and Hitch's multi-component working memory (WM) model has played an enduring and influential role in our understanding of cognitive abilities. Very little is known, however, about the neural basis of this multi-component WM model and the differential role each component plays in mediating arithmetic problem solving abilities in children. Here, we investigate the neural basis of the central executive (CE), phonological (PL) and visuo-spatial (VS) components of WM during a demanding mental arithmetic task in 7-9 year old children (N=74). The VS component was the strongest predictor of math ability in children and was associated with increased arithmetic complexity-related responses in left dorsolateral and right ventrolateral prefrontal cortices as well as bilateral intra-parietal sulcus and supramarginal gyrus in posterior parietal cortex. Critically, VS, CE and PL abilities were associated with largely distinct patterns of brain response. Overlap between VS and CE components was observed in left supramarginal gyrus and no overlap was observed between VS and PL components. Our findings point to a central role of visuo-spatial WM during arithmetic problem-solving in young grade-school children and highlight the usefulness of the multi-component Baddeley and Hitch WM model in fractionating the neural correlates of arithmetic problem solving during development. Copyright © 2013 Elsevier Ltd. All rights reserved.

Satellite retrieval of actual evapotranspiration in the Tibetan Plateau: Components partitioning, multidecadal trends and dominated factors identifying

NASA Astrophysics Data System (ADS)

Wang, Weiguang; Li, Jinxing; Yu, Zhongbo; Ding, Yimin; Xing, Wanqiu; Lu, Wenjun

2018-04-01

As the only connecting term between water balance and energy budget in the earth-atmospheric system, evapotranspiration (ET) is considered the most excellent indicator for the activity for the water and energy cycle. Under the background of global change, regional ET estimates, components partitioning as well as their spatial and temporal patterns recognition are of great importance in understanding the hydrological processes and improving water management practices. This is particularly true for the Tibetan Plateau (TP), one of most sensitive and vulnerable region in response to the environment change in the earth. In this study, with flux site observation data and monthly ET data from the monthly water balance method incorporating the terrestrial water storage changes from the Gravity Recovery and Climate Experiment satellite (GRACE) production as the multiple validations, the long-term daily ET in the TP was retrieved by a modified Penman-Monteith-Leuning (PML) model with considering evapotranspiration over snow covered area during 1982-2012. The spatial and temporal changes of partitioned three components of ET, i.e., soil evaporation (Es), transpiration through the stomata of plant (Ec) and canopy interception (Ei), were investigated in the TP. Meanwhile, how the ET components contribute to ET changes and respond to the change in environmental factors in the TP was revealed and discussed. The results indicate that Es dominates ET in most areas of the TP with the mean annual ratio of 65.7%, except southeastern regions where the vegetation coverage is high. Although regional average ET and three main components all present obvious increase trends during the past decades, high spatial heterogeneity for their trends are identified in the TP. Moreover, a mixed changing pattern can be apparently found for Es in southeastern area, Ec and Ei in northwestern and southeastern area. Spatially, the ET variation are mainly attributed to change in Es, followed by Ec and Ei. In addition, compared with evaporation-related meteorological variables, precipitation and leaf area index (LAI) provide the more dominated contributions to the changes of ET and Ei in the TP, while LAI is overwhelming contribution factor for Ec changes. As for Es changes, although precipitation play the important role, the effects of other factors are also non-negligible.

Synoptic sampling and principal components analysis to identify sources of water and metals to an acid mine drainage stream.

PubMed

Byrne, Patrick; Runkel, Robert L; Walton-Day, Katherine

2017-07-01

Combining the synoptic mass balance approach with principal components analysis (PCA) can be an effective method for discretising the chemistry of inflows and source areas in watersheds where contamination is diffuse in nature and/or complicated by groundwater interactions. This paper presents a field-scale study in which synoptic sampling and PCA are employed in a mineralized watershed (Lion Creek, Colorado, USA) under low flow conditions to (i) quantify the impacts of mining activity on stream water quality; (ii) quantify the spatial pattern of constituent loading; and (iii) identify inflow sources most responsible for observed changes in stream chemistry and constituent loading. Several of the constituents investigated (Al, Cd, Cu, Fe, Mn, Zn) fail to meet chronic aquatic life standards along most of the study reach. The spatial pattern of constituent loading suggests four primary sources of contamination under low flow conditions. Three of these sources are associated with acidic (pH <3.1) seeps that enter along the left bank of Lion Creek. Investigation of inflow water (trace metal and major ion) chemistry using PCA suggests a hydraulic connection between many of the left bank inflows and mine water in the Minnesota Mine shaft located to the north-east of the river channel. In addition, water chemistry data during a rainfall-runoff event suggests the spatial pattern of constituent loading may be modified during rainfall due to dissolution of efflorescent salts or erosion of streamside tailings. These data point to the complexity of contaminant mobilisation processes and constituent loading in mining-affected watersheds but the combined synoptic sampling and PCA approach enables a conceptual model of contaminant dynamics to be developed to inform remediation.

Synoptic sampling and principal components analysis to identify sources of water and metals to an acid mine drainage stream

USGS Publications Warehouse

Byrne, Patrick; Runkel, Robert L.; Walton-Day, Katie

2017-01-01

Combining the synoptic mass balance approach with principal components analysis (PCA) can be an effective method for discretising the chemistry of inflows and source areas in watersheds where contamination is diffuse in nature and/or complicated by groundwater interactions. This paper presents a field-scale study in which synoptic sampling and PCA are employed in a mineralized watershed (Lion Creek, Colorado, USA) under low flow conditions to (i) quantify the impacts of mining activity on stream water quality; (ii) quantify the spatial pattern of constituent loading; and (iii) identify inflow sources most responsible for observed changes in stream chemistry and constituent loading. Several of the constituents investigated (Al, Cd, Cu, Fe, Mn, Zn) fail to meet chronic aquatic life standards along most of the study reach. The spatial pattern of constituent loading suggests four primary sources of contamination under low flow conditions. Three of these sources are associated with acidic (pH <3.1) seeps that enter along the left bank of Lion Creek. Investigation of inflow water (trace metal and major ion) chemistry using PCA suggests a hydraulic connection between many of the left bank inflows and mine water in the Minnesota Mine shaft located to the north-east of the river channel. In addition, water chemistry data during a rainfall-runoff event suggests the spatial pattern of constituent loading may be modified during rainfall due to dissolution of efflorescent salts or erosion of streamside tailings. These data point to the complexity of contaminant mobilisation processes and constituent loading in mining-affected watersheds but the combined synoptic sampling and PCA approach enables a conceptual model of contaminant dynamics to be developed to inform remediation.

Point process models for localization and interdependence of punctate cellular structures.

PubMed

Li, Ying; Majarian, Timothy D; Naik, Armaghan W; Johnson, Gregory R; Murphy, Robert F

2016-07-01

Accurate representations of cellular organization for multiple eukaryotic cell types are required for creating predictive models of dynamic cellular function. To this end, we have previously developed the CellOrganizer platform, an open source system for generative modeling of cellular components from microscopy images. CellOrganizer models capture the inherent heterogeneity in the spatial distribution, size, and quantity of different components among a cell population. Furthermore, CellOrganizer can generate quantitatively realistic synthetic images that reflect the underlying cell population. A current focus of the project is to model the complex, interdependent nature of organelle localization. We built upon previous work on developing multiple non-parametric models of organelles or structures that show punctate patterns. The previous models described the relationships between the subcellular localization of puncta and the positions of cell and nuclear membranes and microtubules. We extend these models to consider the relationship to the endoplasmic reticulum (ER), and to consider the relationship between the positions of different puncta of the same type. Our results do not suggest that the punctate patterns we examined are dependent on ER position or inter- and intra-class proximity. With these results, we built classifiers to update previous assignments of proteins to one of 11 patterns in three distinct cell lines. Our generative models demonstrate the ability to construct statistically accurate representations of puncta localization from simple cellular markers in distinct cell types, capturing the complex phenomena of cellular structure interaction with little human input. This protocol represents a novel approach to vesicular protein annotation, a field that is often neglected in high-throughput microscopy. These results suggest that spatial point process models provide useful insight with respect to the spatial dependence between cellular structures. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Cluster detection methods applied to the Upper Cape Cod cancer data.

PubMed

Ozonoff, Al; Webster, Thomas; Vieira, Veronica; Weinberg, Janice; Ozonoff, David; Aschengrau, Ann

2005-09-15

A variety of statistical methods have been suggested to assess the degree and/or the location of spatial clustering of disease cases. However, there is relatively little in the literature devoted to comparison and critique of different methods. Most of the available comparative studies rely on simulated data rather than real data sets. We have chosen three methods currently used for examining spatial disease patterns: the M-statistic of Bonetti and Pagano; the Generalized Additive Model (GAM) method as applied by Webster; and Kulldorff's spatial scan statistic. We apply these statistics to analyze breast cancer data from the Upper Cape Cancer Incidence Study using three different latency assumptions. The three different latency assumptions produced three different spatial patterns of cases and controls. For 20 year latency, all three methods generally concur. However, for 15 year latency and no latency assumptions, the methods produce different results when testing for global clustering. The comparative analyses of real data sets by different statistical methods provides insight into directions for further research. We suggest a research program designed around examining real data sets to guide focused investigation of relevant features using simulated data, for the purpose of understanding how to interpret statistical methods applied to epidemiological data with a spatial component.

A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores

PubMed Central

Neelon, Brian; Gelfand, Alan E.; Miranda, Marie Lynn

2013-01-01

Summary Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from different cognitive domains. We propose a multivariate spatial mixture model for the joint analysis of continuous individual-level outcomes that are referenced to areal units. The responses are modeled as a finite mixture of multivariate normals, which accommodates a wide range of marginal response distributions and allows investigators to examine covariate effects within subpopulations of interest. The model has a hierarchical structure built at the individual level (i.e., individuals are nested within areal units), and thus incorporates both individual- and areal-level predictors as well as spatial random effects for each mixture component. Conditional autoregressive (CAR) priors on the random effects provide spatial smoothing and allow the shape of the multivariate distribution to vary flexibly across geographic regions. We adopt a Bayesian modeling approach and develop an efficient Markov chain Monte Carlo model fitting algorithm that relies primarily on closed-form full conditionals. We use the model to explore geographic patterns in end-of-grade math and reading test scores among school-age children in North Carolina. PMID:26401059

Additive Partitioning of Coral Reef Fish Diversity across Hierarchical Spatial Scales throughout the Caribbean

PubMed Central

Francisco-Ramos, Vanessa; Arias-González, Jesús Ernesto

2013-01-01

There is an increasing need to examine regional patterns of diversity in coral-reef systems since their biodiversity is declining globally. In this sense, additive partitioning might be useful since it quantifies the contribution of alpha and beta to total diversity across different scales. We applied this approach using an unbalanced design across four hierarchical scales (80 sites, 22 subregions, six ecoregions, and the Caribbean basin). Reef-fish species were compiled from the Reef Environmental Education Foundation (REEF) database and distributions were confirmed with published data. Permutation tests were used to compare observed values to those expected by chance. The primary objective was to identify patterns of reef-fish diversity across multiple spatial scales under different scenarios, examining factors such as fisheries and demographic connectivity. Total diversity at the Caribbean scale was attributed to β-diversity (nearly 62% of the species), with the highest β-diversity at the site scale. α¯-diversity was higher than expected by chance in all scenarios and at all studied scales. This suggests that fish assemblages are more homogenous than expected, particularly at the ecoregion scale. Within each ecoregion, diversity was mainly attributed to alpha, except for the Southern ecoregion where there was a greater difference in species among sites. β-components were lower than expected in all ecoregions, indicating that fishes within each ecoregion are a subsample of the same species pool. The scenario involving the effects of fisheries showed a shift in dominance for β-diversity from regions to subregions, with no major changes to the diversity patterns. In contrast, demographic connectivity partially explained the diversity pattern. β-components were low within connectivity regions and higher than expected by chance when comparing between them. Our results highlight the importance of ecoregions as a spatial scale to conserve local and regional coral reef-fish diversity. PMID:24205311

Consequences of Landscape Fragmentation on Lyme Disease Risk: A Cellular Automata Approach

PubMed Central

Li, Sen; Hartemink, Nienke; Speybroeck, Niko; Vanwambeke, Sophie O.

2012-01-01

The abundance of infected Ixodid ticks is an important component of human risk of Lyme disease, and various empirical studies have shown that this is associated, at least in part, to landscape fragmentation. In this study, we aimed at exploring how varying woodland fragmentation patterns affect the risk of Lyme disease, through infected tick abundance. A cellular automata model was developed, incorporating a heterogeneous landscape with three interactive components: an age-structured tick population, a classical disease transmission function, and hosts. A set of simplifying assumptions were adopted with respect to the study objective and field data limitations. In the model, the landscape influences both tick survival and host movement. The validation of the model was performed with an empirical study. Scenarios of various landscape configurations (focusing on woodland fragmentation) were simulated and compared. Lyme disease risk indices (density and infection prevalence of nymphs) differed considerably between scenarios: (i) the risk could be higher in highly fragmented woodlands, which is supported by a number of recently published empirical studies, and (ii) grassland could reduce the risk in adjacent woodland, which suggests landscape fragmentation studies of zoonotic diseases should not focus on the patch-level woodland patterns only, but also on landscape-level adjacent land cover patterns. Further analysis of the simulation results indicated strong correlations between Lyme disease risk indices and the density, shape and aggregation level of woodland patches. These findings highlight the strong effect of the spatial patterns of local host population and movement on the spatial dynamics of Lyme disease risks, which can be shaped by woodland fragmentation. In conclusion, using a cellular automata approach is beneficial for modelling complex zoonotic transmission systems as it can be combined with either real world landscapes for exploring direct spatial effects or artificial representations for outlining possible empirical investigations. PMID:22761842

Temporal changes of diffusion patterns in mild traumatic brain injury via group-based semi-blind source separation.

PubMed

Jing, Min; McGinnity, T Martin; Coleman, Sonya; Fuchs, Armin; Kelso, J A Scott

2015-07-01

Despite the emerging applications of diffusion tensor imaging (DTI) to mild traumatic brain injury (mTBI), very few investigations have been reported related to temporal changes in quantitative diffusion patterns, which may help to assess recovery from head injury and the long term impact associated with cognitive and behavioral impairments caused by mTBI. Most existing methods are focused on detection of mTBI affected regions rather than quantification of temporal changes following head injury. Furthermore, most methods rely on large data samples as required for statistical analysis and, thus, are less suitable for individual case studies. In this paper, we introduce an approach based on spatial group independent component analysis (GICA), in which the diffusion scalar maps from an individual mTBI subject and the average of a group of controls are arranged according to their data collection time points. In addition, we propose a constrained GICA (CGICA) model by introducing the prior information into the GICA decomposition process, thus taking available knowledge of mTBI into account. The proposed method is evaluated based on DTI data collected from American football players including eight controls and three mTBI subjects (at three time points post injury). The results show that common spatial patterns within the diffusion maps were extracted as spatially independent components (ICs) by GICA. The temporal change of diffusion patterns during recovery is revealed by the time course of the selected IC. The results also demonstrate that the temporal change can be further influenced by incorporating the prior knowledge of mTBI (if available) based on the proposed CGICA model. Although a small sample of mTBI subjects is studied, as a proof of concept, the preliminary results provide promising insight for applications of DTI to study recovery from mTBI and may have potential for individual case studies in practice.

Pattern transfer printing by kinetic control of adhesion to an elastomeric stamp

DOEpatents

Nuzzo, Ralph G [Champaign, IL; Rogers, John A [Champaign, IL; Menard, Etienne [Urbana, IL; Lee, Keon Jae [Tokyo, JP; Khang, Dahl-Young [Urbana, IL; Sun, Yugang [Champaign, IL; Meitl, Matthew [Champaign, IL; Zhu, Zhengtao [Urbana, IL

2011-05-17

The present invention provides methods, systems and system components for transferring, assembling and integrating features and arrays of features having selected nanosized and/or microsized physical dimensions, shapes and spatial orientations. Methods of the present invention utilize principles of `soft adhesion` to guide the transfer, assembly and/or integration of features, such as printable semiconductor elements or other components of electronic devices. Methods of the present invention are useful for transferring features from a donor substrate to the transfer surface of an elastomeric transfer device and, optionally, from the transfer surface of an elastomeric transfer device to the receiving surface of a receiving substrate. The present methods and systems provide highly efficient, registered transfer of features and arrays of features, such as printable semiconductor element, in a concerted manner that maintains the relative spatial orientations of transferred features.

Anthropogenic heat flux: advisable spatial resolutions when input data are scarce

NASA Astrophysics Data System (ADS)

Gabey, A. M.; Grimmond, C. S. B.; Capel-Timms, I.

2018-02-01

Anthropogenic heat flux (QF) may be significant in cities, especially under low solar irradiance and at night. It is of interest to many practitioners including meteorologists, city planners and climatologists. QF estimates at fine temporal and spatial resolution can be derived from models that use varying amounts of empirical data. This study compares simple and detailed models in a European megacity (London) at 500 m spatial resolution. The simple model (LQF) uses spatially resolved population data and national energy statistics. The detailed model (GQF) additionally uses local energy, road network and workday population data. The Fractions Skill Score (FSS) and bias are used to rate the skill with which the simple model reproduces the spatial patterns and magnitudes of QF, and its sub-components, from the detailed model. LQF skill was consistently good across 90% of the city, away from the centre and major roads. The remaining 10% contained elevated emissions and "hot spots" representing 30-40% of the total city-wide energy. This structure was lost because it requires workday population, spatially resolved building energy consumption and/or road network data. Daily total building and traffic energy consumption estimates from national data were within ± 40% of local values. Progressively coarser spatial resolutions to 5 km improved skill for total QF, but important features (hot spots, transport network) were lost at all resolutions when residential population controlled spatial variations. The results demonstrate that simple QF models should be applied with conservative spatial resolution in cities that, like London, exhibit time-varying energy use patterns.

Tree-based approach for exploring marine spatial patterns with raster datasets.

PubMed

Liao, Xiaohan; Xue, Cunjin; Su, Fenzhen

2017-01-01

From multiple raster datasets to spatial association patterns, the data-mining technique is divided into three subtasks, i.e., raster dataset pretreatment, mining algorithm design, and spatial pattern exploration from the mining results. Comparison with the former two subtasks reveals that the latter remains unresolved. Confronted with the interrelated marine environmental parameters, we propose a Tree-based Approach for eXploring Marine Spatial Patterns with multiple raster datasets called TAXMarSP, which includes two models. One is the Tree-based Cascading Organization Model (TCOM), and the other is the Spatial Neighborhood-based CAlculation Model (SNCAM). TCOM designs the "Spatial node→Pattern node" from top to bottom layers to store the table-formatted frequent patterns. Together with TCOM, SNCAM considers the spatial neighborhood contributions to calculate the pattern-matching degree between the specified marine parameters and the table-formatted frequent patterns and then explores the marine spatial patterns. Using the prevalent quantification Apriori algorithm and a real remote sensing dataset from January 1998 to December 2014, a successful application of TAXMarSP to marine spatial patterns in the Pacific Ocean is described, and the obtained marine spatial patterns present not only the well-known but also new patterns to Earth scientists.

Distinct spatiotemporal activity in principal neurons of the mouse olfactory bulb in anesthetized and awake states

PubMed Central

Blauvelt, David G.; Sato, Tomokazu F.; Wienisch, Martin; Murthy, Venkatesh N.

2013-01-01

The acquisition of olfactory information and its early processing in mammals are modulated by brain states through sniffing behavior and neural feedback. We imaged the spatiotemporal pattern of odor-evoked activity in a population of output neurons (mitral/tufted cells, MTCs) in the olfactory bulb (OB) of head-restrained mice expressing a genetically-encoded calcium indicator. The temporal dynamics of MTC population activity were relatively simple in anesthetized animals, but were highly variable in awake animals. However, the apparently irregular activity in awake animals could be predicted well using sniff timing measured externally, or inferred through fluctuations in the global responses of MTC population even without explicit knowledge of sniff times. The overall spatial pattern of activity was conserved across states, but odor responses had a diffuse spatial component in anesthetized mice that was less prominent during wakefulness. Multi-photon microscopy indicated that MTC lateral dendrites were the likely source of spatially disperse responses in the anesthetized animal. Our data demonstrate that the temporal and spatial dynamics of MTCs can be significantly modulated by behavioral state, and that the ensemble activity of MTCs can provide information about sniff timing to downstream circuits to help decode odor responses. PMID:23543674

Filter bank common spatial patterns in mental workload estimation.

PubMed

Arvaneh, Mahnaz; Umilta, Alberto; Robertson, Ian H

2015-01-01

EEG-based workload estimation technology provides a real time means of assessing mental workload. Such technology can effectively enhance the performance of the human-machine interaction and the learning process. When designing workload estimation algorithms, a crucial signal processing component is the feature extraction step. Despite several studies on this field, the spatial properties of the EEG signals were mostly neglected. Since EEG inherently has a poor spacial resolution, features extracted individually from each EEG channel may not be sufficiently efficient. This problem becomes more pronounced when we use low-cost but convenient EEG sensors with limited stability which is the case in practical scenarios. To address this issue, in this paper, we introduce a filter bank common spatial patterns algorithm combined with a feature selection method to extract spatio-spectral features discriminating different mental workload levels. To evaluate the proposed algorithm, we carry out a comparative analysis between two representative types of working memory tasks using data recorded from an Emotiv EPOC headset which is a mobile low-cost EEG recording device. The experimental results showed that the proposed spatial filtering algorithm outperformed the state-of-the algorithms in terms of the classification accuracy.

Metacommunity composition of web-spiders in a fragmented neotropical forest: relative importance of environmental and spatial effects.

PubMed

Baldissera, Ronei; Rodrigues, Everton N L; Hartz, Sandra M

2012-01-01

The distribution of beta diversity is shaped by factors linked to environmental and spatial control. The relative importance of both processes in structuring spider metacommunities has not yet been investigated in the Atlantic Forest. The variance explained by purely environmental, spatially structured environmental, and purely spatial components was compared for a metacommunity of web spiders. The study was carried out in 16 patches of Atlantic Forest in southern Brazil. Field work was done in one landscape mosaic representing a slight gradient of urbanization. Environmental variables encompassed plot- and patch-level measurements and a climatic matrix, while principal coordinates of neighbor matrices (PCNMs) acted as spatial variables. A forward selection procedure was carried out to select environmental and spatial variables influencing web-spider beta diversity. Variation partitioning was used to estimate the contribution of pure environmental and pure spatial effects and their shared influence on beta-diversity patterns, and to estimate the relative importance of selected environmental variables. Three environmental variables (bush density, land use in the surroundings of patches, and shape of patches) and two spatial variables were selected by forward selection procedures. Variation partitioning revealed that 15% of the variation of beta diversity was explained by a combination of environmental and PCNM variables. Most of this variation (12%) corresponded to pure environmental and spatially environmental structure. The data indicated that (1) spatial legacy was not important in explaining the web-spider beta diversity; (2) environmental predictors explained a significant portion of the variation in web-spider composition; (3) one-third of environmental variation was due to a spatial structure that jointly explains variation in species distributions. We were able to detect important factors related to matrix management influencing the web-spider beta-diversity patterns, which are probably linked to historical deforestation events.

A knowledge-based approach to estimating the magnitude and spatial patterns of potential threats to soil biodiversity.

PubMed

Orgiazzi, Alberto; Panagos, Panos; Yigini, Yusuf; Dunbar, Martha B; Gardi, Ciro; Montanarella, Luca; Ballabio, Cristiano

2016-03-01

Because of the increasing pressures exerted on soil, below-ground life is under threat. Knowledge-based rankings of potential threats to different components of soil biodiversity were developed in order to assess the spatial distribution of threats on a European scale. A list of 13 potential threats to soil biodiversity was proposed to experts with different backgrounds in order to assess the potential for three major components of soil biodiversity: soil microorganisms, fauna, and biological functions. This approach allowed us to obtain knowledge-based rankings of threats. These classifications formed the basis for the development of indices through an additive aggregation model that, along with ad-hoc proxies for each pressure, allowed us to preliminarily assess the spatial patterns of potential threats. Intensive exploitation was identified as the highest pressure. In contrast, the use of genetically modified organisms in agriculture was considered as the threat with least potential. The potential impact of climate change showed the highest uncertainty. Fourteen out of the 27 considered countries have more than 40% of their soils with moderate-high to high potential risk for all three components of soil biodiversity. Arable soils are the most exposed to pressures. Soils within the boreal biogeographic region showed the lowest risk potential. The majority of soils at risk are outside the boundaries of protected areas. First maps of risks to three components of soil biodiversity based on the current scientific knowledge were developed. Despite the intrinsic limits of knowledge-based assessments, a remarkable potential risk to soil biodiversity was observed. Guidelines to preliminarily identify and circumscribe soils potentially at risk are provided. This approach may be used in future research to assess threat at both local and global scale and identify areas of possible risk and, subsequently, design appropriate strategies for monitoring and protection of soil biota. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Abundance and fragmentation patterns of the ecosystem engineer Lithophyllum byssoides (Lamarck) Foslie along the Iberian Peninsula Atlantic coast. Conservation and management implications

NASA Astrophysics Data System (ADS)

Veiga, Puri; Rubal, Marcos; Cacabelos, Eva; Moreira, Juan; Sousa-Pinto, Isabel

2013-10-01

The crustose calcareous red macroalgae Lithophyllum byssoides (Lamarck) Foslie is a common ecosystem engineer along the Atlantic and Mediterranean coast of the Iberian Peninsula. This species is threatened by several anthropogenic impacts acting at different spatial scales, such as pollution or global warming. The aim of this study is to identify scales of spatial variation in the abundance and fragmentation patterns of L. byssoides along the Atlantic coast of the Iberian Peninsula. For this aim we used a hierarchical sampling design considering four spatial scales (from metres to 100s of kilometres). Results of the present study indicated no significant variability among regions investigated whereas significant variability was found at the scales of shore and site in spatial patterns of abundance and fragmentation of L. byssoides. Variance components were higher at the spatial scale of shore for abundance and fragmentation of L. byssoides with the only exception of percentage cover and thus, processes acting at the scale of 10s of kilometres seem to be more relevant in shaping the spatial variability both in abundance and fragmentation of L. byssoides. These results provided quantitative estimates of abundance and fragmentation of L. byssoides at the Atlantic coast of the Iberian Peninsula establishing the observational basis for future assessment, monitoring and experimental investigations to identify the processes and anthropogenic impacts affecting L. byssoides populations. Finally we have also identified percentage cover and patch density as the best variables for long-term monitoring programs aimed to detect future anthropogenic impacts on L. byssoides. Therefore, our results have important implications for conservation and management of this valuable ecosystem engineer along the Atlantic coast of the Iberian Peninsula.

Summer spatial patterning of chukars in relation to free water in Western Utah

USGS Publications Warehouse

Larsen, R.T.; Bissonette, J.A.; Flinders, J.T.; Hooten, M.B.; Wilson, T.L.

2010-01-01

Free water is considered important to wildlife in arid regions. In the western United States, thousands of water developments have been built to benefit wildlife in arid landscapes. Agencies and researchers have yet to clearly demonstrate their effectiveness. We combined a spatial analysis of summer chukar (Alectoris chukar) covey locations with dietary composition analysis in western Utah. Our specific objectives were to determine if chukars showed a spatial pattern that suggested association with free water in four study areas and to document summer dietary moisture content in relation to average distance from water. The observed data for the Cedar Mountains study area fell within the middle of the random mean distance to water distribution suggesting no association with free water. The observed mean distance to water for the other three areas was much closer than expected compared to a random spatial process, suggesting the importance of free water to these populations. Dietary moisture content of chukar food items from the Cedar Mountains (59%) was significantly greater (P < 0.05) than that of birds from Box Elder (44%) and Keg-Dugway (44%). Water developments on the Cedar Mountains are likely ineffective for chukars. Spatial patterns on the other areas, however, suggest association with free water and our results demonstrate the need for site-specific considerations. Researchers should be aware of the potential to satisfy water demand with pre-formed and metabolic water for a variety of species in studies that address the effects of wildlife water developments. We encourage incorporation of spatial structure in model error components in future ecological research. ?? Springer Science+Business Media B.V. 2009.

Non-destructive terahertz imaging of illicit drugs using spectral fingerprints

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuuki; Inoue, Hiroyuki

2003-10-01

The absence of non-destructive inspection techniques for illicit drugs hidden in mail envelopes has resulted in such drugs being smuggled across international borders freely. We have developed a novel basic technology for terahertz imaging, which allows detection and identification of drugs concealed in envelopes, by introducing the component spatial pattern analysis. The spatial distributions of the targets are obtained from terahertz multispectral transillumination images, using absorption spectra measured with a tunable terahertz-wave source. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network

Treesearch

Enric Batllori; Marc-Andre Parisien; Sean A. Parks; Max A. Moritz; Carol Miller

2017-01-01

Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform...

Combined ICA-LORETA analysis of mismatch negativity.

PubMed

Marco-Pallarés, J; Grau, C; Ruffini, G

2005-04-01

A major challenge for neuroscience is to map accurately the spatiotemporal patterns of activity of the large neuronal populations that are believed to underlie computing in the human brain. To study a specific example, we selected the mismatch negativity (MMN) brain wave (an event-related potential, ERP) because it gives an electrophysiological index of a "primitive intelligence" capable of detecting changes, even abstract ones, in a regular auditory pattern. ERPs have a temporal resolution of milliseconds but appear to result from mixed neuronal contributions whose spatial location is not fully understood. Thus, it is important to separate these sources in space and time. To tackle this problem, a two-step approach was designed combining the independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. Here we implement this approach to analyze the subsecond spatiotemporal dynamics of MMN cerebral sources using trial-by-trial experimental data. We show evidence that a cerebral computation mechanism underlies MMN. This mechanism is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, which activate at distinct time intervals and are grouped in six main statistically independent components.

Non-linear Min protein interactions generate harmonics that signal mid-cell division in Escherichia coli

PubMed Central

Walsh, James C.; Angstmann, Christopher N.; Duggin, Iain G.

2017-01-01

The Min protein system creates a dynamic spatial pattern in Escherichia coli cells where the proteins MinD and MinE oscillate from pole to pole. MinD positions MinC, an inhibitor of FtsZ ring formation, contributing to the mid-cell localization of cell division. In this paper, Fourier analysis is used to decompose experimental and model MinD spatial distributions into time-dependent harmonic components. In both experiment and model, the second harmonic component is responsible for producing a mid-cell minimum in MinD concentration. The features of this harmonic are robust in both experiment and model. Fourier analysis reveals a close correspondence between the time-dependent behaviour of the harmonic components in the experimental data and model. Given this, each molecular species in the model was analysed individually. This analysis revealed that membrane-bound MinD dimer shows the mid-cell minimum with the highest contrast when averaged over time, carrying the strongest signal for positioning the cell division ring. This concurs with previous data showing that the MinD dimer binds to MinC inhibiting FtsZ ring formation. These results show that non-linear interactions of Min proteins are essential for producing the mid-cell positioning signal via the generation of second-order harmonic components in the time-dependent spatial protein distribution. PMID:29040283

Making Temporal Search More Central in Spatial Data Infrastructures

NASA Astrophysics Data System (ADS)

Corti, P.; Lewis, B.

2017-10-01

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

Distribution patterns in the native vascular flora of Iceland.

PubMed

Wasowicz, Pawel; Pasierbiński, Andrzej; Przedpelska-Wasowicz, Ewa Maria; Kristinsson, Hörður

2014-01-01

The aim of our study was to reveal biogeographical patterns in the native vascular flora of Iceland and to define ecological factors responsible for these patterns. We analysed dataset of more than 500,000 records containing information on the occurrence of vascular plants. Analysis of ecological factors included climatic (derived from WORLDCLIM data), topographic (calculated from digital elevation model) and geological (bedrock characteristics) variables. Spherical k-means clustering and principal component analysis were used to detect biogeographical patterns and to study the factors responsible for them. We defined 10 biotic elements exhibiting different biogeographical patterns. We showed that climatic (temperature-related) and topographic variables were the most important factors contributing to the spatial patterns within the Icelandic vascular flora and that these patterns are almost completely independent of edaphic factors (bedrock type). Our study is the first one to analyse the biogeographical differentiation of the native vascular flora of Iceland.

Magneto-optical visualization of three spatial components of inhomogeneous stray fields

NASA Astrophysics Data System (ADS)

Ivanov, V. E.

2012-08-01

The article deals with the physical principles of magneto-optical visualization (MO) of three spatial components of inhomogeneous stray fields with the help of FeCo metal indicator films in the longitudinal Kerr effect geometry. The inhomogeneous field is created by permanent magnets. Both p- and s-polarization light is used for obtaining MO images with their subsequent summing, subtracting and digitizing. As a result, the MO images and corresponding intensity coordinate dependences reflecting the distributions of the horizontal and vertical magnetization components in pure form have been obtained. Modeling of both the magnetization distribution in the indicator film and the corresponding MO images shows that corresponding to polar sensitivity the intensity is proportional to the normal field component, which permits normal field component mapping. Corresponding to longitudinal sensitivity, the intensity of the MO images reflects the angular distribution of the planar field component. MO images have singular points in which the planar component is zero and their movement under an externally homogeneous planar field permits obtaining of additional information on the two planar components of the field under study. The intensity distribution character in the vicinity of sources and sinks (singular points) remains the same under different orientations of the light incidence plane. The change of incident plane orientation by π/2 alters the distribution pattern in the vicinity of the saddle points.

Accounting for biotic spatial variability in fields: Case of resistance screening against sunflower Verticillium wilt

PubMed Central

Missonnier, Hélène; Jacques, Alban; Bang, JiSu; Daydé, Jean; Mirleau-Thebaud, Virginie

2017-01-01

In breeding for disease resistance, the magnitude of the genetic response is difficult to appreciate because of environmental stresses that interact with the plant genotype. We discuss herein the fundamental problems in breeding for disease resistance with the aim being to better understand the interactions between plant, pathogen, and spatial patterns. The goal of this study is to fine tune breeding decisions by incorporating spatial patterns of such biotic factors into the definition of disease-occurrence probability. We use a preexisting statistics method based on geostatistics for a descriptive analysis of biotic factors for trial quality control. The plant-population structure used for spatial-pattern analysis consists of two F1-hybrid cultivars, defined as symptomatic and asymptomatic controls with respect to the studied pathogen. The controls are inserted at specific locations to establish a grid arrangement over the field that include the F1-hybrid cultivars under evaluation. We characterize the spatial structure of the pathogen population and of the general plant environment—with undetermined but present abiotic constraints—not by using direct notation such as flower time or rainfall but by using plant behavior (i.e., leaf symptom severity, indirect notation). The analysis indicates areas with higher or lower risk of disease and reveals a correlation between the symptomatic control and the effective level of disease for sunflowers. This result suggests that the pathogen and/or abiotic components are major factors in determining the probability that a plant develops the disease, which could lead to a misinterpretation of plant resistance. PMID:28817567

Accounting for biotic spatial variability in fields: Case of resistance screening against sunflower Verticillium wilt.

PubMed

Missonnier, Hélène; Jacques, Alban; Bang, JiSu; Daydé, Jean; Mirleau-Thebaud, Virginie

2017-01-01

In breeding for disease resistance, the magnitude of the genetic response is difficult to appreciate because of environmental stresses that interact with the plant genotype. We discuss herein the fundamental problems in breeding for disease resistance with the aim being to better understand the interactions between plant, pathogen, and spatial patterns. The goal of this study is to fine tune breeding decisions by incorporating spatial patterns of such biotic factors into the definition of disease-occurrence probability. We use a preexisting statistics method based on geostatistics for a descriptive analysis of biotic factors for trial quality control. The plant-population structure used for spatial-pattern analysis consists of two F1-hybrid cultivars, defined as symptomatic and asymptomatic controls with respect to the studied pathogen. The controls are inserted at specific locations to establish a grid arrangement over the field that include the F1-hybrid cultivars under evaluation. We characterize the spatial structure of the pathogen population and of the general plant environment-with undetermined but present abiotic constraints-not by using direct notation such as flower time or rainfall but by using plant behavior (i.e., leaf symptom severity, indirect notation). The analysis indicates areas with higher or lower risk of disease and reveals a correlation between the symptomatic control and the effective level of disease for sunflowers. This result suggests that the pathogen and/or abiotic components are major factors in determining the probability that a plant develops the disease, which could lead to a misinterpretation of plant resistance.

A multi-scale spatial analysis of native and exotic plant species richness within a mixed-disturbance oak savanna landscape.

PubMed

Schetter, Timothy A; Walters, Timothy L; Root, Karen V

2013-09-01

Impacts of human land use pose an increasing threat to global biodiversity. Resource managers must respond rapidly to this threat by assessing existing natural areas and prioritizing conservation actions across multiple spatial scales. Plant species richness is a useful measure of biodiversity but typically can only be evaluated on small portions of a given landscape. Modeling relationships between spatial heterogeneity and species richness may allow conservation planners to make predictions of species richness patterns within unsampled areas. We utilized a combination of field data, remotely sensed data, and landscape pattern metrics to develop models of native and exotic plant species richness at two spatial extents (60- and 120-m windows) and at four ecological levels for northwestern Ohio's Oak Openings region. Multiple regression models explained 37-77 % of the variation in plant species richness. These models consistently explained more variation in exotic richness than in native richness. Exotic richness was better explained at the 120-m extent while native richness was better explained at the 60-m extent. Land cover composition of the surrounding landscape was an important component of all models. We found that percentage of human-modified land cover (negatively correlated with native richness and positively correlated with exotic richness) was a particularly useful predictor of plant species richness and that human-caused disturbances exert a strong influence on species richness patterns within a mixed-disturbance oak savanna landscape. Our results emphasize the importance of using a multi-scale approach to examine the complex relationships between spatial heterogeneity and plant species richness.

Deep Independence Network Analysis of Structural Brain Imaging: Application to Schizophrenia

PubMed Central

Castro, Eduardo; Hjelm, R. Devon; Plis, Sergey M.; Dinh, Laurent; Turner, Jessica A.; Calhoun, Vince D.

2016-01-01

Linear independent component analysis (ICA) is a standard signal processing technique that has been extensively used on neuroimaging data to detect brain networks with coherent brain activity (functional MRI) or covarying structural patterns (structural MRI). However, its formulation assumes that the measured brain signals are generated by a linear mixture of the underlying brain networks and this assumption limits its ability to detect the inherent nonlinear nature of brain interactions. In this paper, we introduce nonlinear independent component estimation (NICE) to structural MRI data to detect abnormal patterns of gray matter concentration in schizophrenia patients. For this biomedical application, we further addressed the issue of model regularization of nonlinear ICA by performing dimensionality reduction prior to NICE, together with an appropriate control of the complexity of the model and the usage of a proper approximation of the probability distribution functions of the estimated components. We show that our results are consistent with previous findings in the literature, but we also demonstrate that the incorporation of nonlinear associations in the data enables the detection of spatial patterns that are not identified by linear ICA. Specifically, we show networks including basal ganglia, cerebellum and thalamus that show significant differences in patients versus controls, some of which show distinct nonlinear patterns. PMID:26891483

Spatiotemporal patterns of drought at various time scales in Shandong Province of Eastern China

NASA Astrophysics Data System (ADS)

Zuo, Depeng; Cai, Siyang; Xu, Zongxue; Li, Fulin; Sun, Wenchao; Yang, Xiaojing; Kan, Guangyuan; Liu, Pin

2018-01-01

The temporal variations and spatial patterns of drought in Shandong Province of Eastern China were investigated by calculating the standardized precipitation evapotranspiration index (SPEI) at 1-, 3-, 6-, 12-, and 24-month time scales. Monthly precipitation and air temperature time series during the period 1960-2012 were collected at 23 meteorological stations uniformly distributed over the region. The non-parametric Mann-Kendall test was used to explore the temporal trends of precipitation, air temperature, and the SPEI drought index. S-mode principal component analysis (PCA) was applied to identify the spatial patterns of drought. The results showed that an insignificant decreasing trend in annual total precipitation was detected at most stations, a significant increase of annual average air temperature occurred at all the 23 stations, and a significant decreasing trend in the SPEI was mainly detected at the coastal stations for all the time scales. The frequency of occurrence of extreme and severe drought at different time scales generally increased with decades; higher frequency and larger affected area of extreme and severe droughts occurred as the time scale increased, especially for the northwest of Shandong Province and Jiaodong peninsular. The spatial pattern of drought for SPEI-1 contains three regions: eastern Jiaodong Peninsular and northwestern and southern Shandong. As the time scale increased to 3, 6, and 12 months, the order of the three regions was transformed into another as northwestern Shandong, eastern Jiaodong Peninsular, and southern Shandong. For SPEI-24, the location identified by REOF1 was slightly shifted from northwestern Shandong to western Shandong, and REOF2 and REOF3 identified another two weak patterns in the south edge and north edge of Jiaodong Peninsular, respectively. The potential causes of drought and the impact of drought on agriculture in the study area have also been discussed. The temporal variations and spatial patterns of drought obtained in this study provide valuable information for water resources planning and drought disaster prevention and mitigation in Eastern China.

Stochastic Analysis and Probabilistic Downscaling of Soil Moisture

NASA Astrophysics Data System (ADS)

Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.

2017-12-01

Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.

Age, state, environment, and season dependence of senescence in body mass.

PubMed

Kroeger, Svenja B; Blumstein, Daniel T; Armitage, Kenneth B; Reid, Jane M; Martin, Julien G A

2018-02-01

Senescence is a highly variable process that comprises both age-dependent and state-dependent components and can be greatly affected by environmental conditions. However, few studies have quantified the magnitude of age-dependent and state-dependent senescence in key life-history traits across individuals inhabiting different spatially structured and seasonal environments. We used longitudinal data from wild female yellow-bellied marmots ( Marmota flaviventer ), living in two adjacent environments that differ in elevation and associated phenology, to quantify how age and individual state, measured as "time to death," affect body mass senescence in different environments. Further, we quantified how patterns of senescence differed between two biologically distinct seasons, spring, and late summer. Body mass senescence had an age-dependent component, expressed as a decrease in mass in old age. Overall, estimated age-dependent senescence was greater in females living in the more favorable lower elevation environment, than in the harsher higher elevation environment, and greater in late summer than in spring. Body mass senescence also had a state-dependent component, captured by effects of time to death, but only in the more favorable lower elevation environment. In spring, body mass gradually decreased from 2 years before death, whereas in late summer, state-dependent effects were expressed as a terminal decrease in body mass in the last year of life. Contrary to expectations, we found that senescence was more likely to be observed under more favorable environmental conditions, rather than under harsher conditions. By further demonstrating that senescence patterns differ among seasons, our results imply that within-year temporal environmental variation must be considered alongside spatial environmental variation in order to characterize and understand the pattern and magnitude of senescence in wild populations.

The Dynamics of Visual Experience, an EEG Study of Subjective Pattern Formation

PubMed Central

Elliott, Mark A.; Twomey, Deirdre; Glennon, Mark

2012-01-01

Background Since the origin of psychological science a number of studies have reported visual pattern formation in the absence of either physiological stimulation or direct visual-spatial references. Subjective patterns range from simple phosphenes to complex patterns but are highly specific and reported reliably across studies. Methodology/Principal Findings Using independent-component analysis (ICA) we report a reduction in amplitude variance consistent with subjective-pattern formation in ventral posterior areas of the electroencephalogram (EEG). The EEG exhibits significantly increased power at delta/theta and gamma-frequencies (point and circle patterns) or a series of high-frequency harmonics of a delta oscillation (spiral patterns). Conclusions/Significance Subjective-pattern formation may be described in a way entirely consistent with identical pattern formation in fluids or granular flows. In this manner, we propose subjective-pattern structure to be represented within a spatio-temporal lattice of harmonic oscillations which bind topographically organized visual-neuronal assemblies by virtue of low frequency modulation. PMID:22292053

Spatial assessment of air quality patterns in Malaysia using multivariate analysis

NASA Astrophysics Data System (ADS)

Dominick, Doreena; Juahir, Hafizan; Latif, Mohd Talib; Zain, Sharifuddin M.; Aris, Ahmad Zaharin

2012-12-01

This study aims to investigate possible sources of air pollutants and the spatial patterns within the eight selected Malaysian air monitoring stations based on a two-year database (2008-2009). The multivariate analysis was applied on the dataset. It incorporated Hierarchical Agglomerative Cluster Analysis (HACA) to access the spatial patterns, Principal Component Analysis (PCA) to determine the major sources of the air pollution and Multiple Linear Regression (MLR) to assess the percentage contribution of each air pollutant. The HACA results grouped the eight monitoring stations into three different clusters, based on the characteristics of the air pollutants and meteorological parameters. The PCA analysis showed that the major sources of air pollution were emissions from motor vehicles, aircraft, industries and areas of high population density. The MLR analysis demonstrated that the main pollutant contributing to variability in the Air Pollutant Index (API) at all stations was particulate matter with a diameter of less than 10 μm (PM10). Further MLR analysis showed that the main air pollutant influencing the high concentration of PM10 was carbon monoxide (CO). This was due to combustion processes, particularly originating from motor vehicles. Meteorological factors such as ambient temperature, wind speed and humidity were also noted to influence the concentration of PM10.

Temporal and spatial changes in social vulnerability to natural hazards

PubMed Central

Cutter, Susan L.; Finch, Christina

2008-01-01

During the past four decades (1960–2000), the United States experienced major transformations in population size, development patterns, economic conditions, and social characteristics. These social, economic, and built-environment changes altered the American hazardscape in profound ways, with more people living in high-hazard areas than ever before. To improve emergency management, it is important to recognize the variability in the vulnerable populations exposed to hazards and to develop place-based emergency plans accordingly. The concept of social vulnerability identifies sensitive populations that may be less likely to respond to, cope with, and recover from a natural disaster. Social vulnerability is complex and dynamic, changing over space and through time. This paper presents empirical evidence on the spatial and temporal patterns in social vulnerability in the United States from 1960 to the present. Using counties as our study unit, we found that those components that consistently increased social vulnerability for all time periods were density (urban), race/ethnicity, and socioeconomic status. The spatial patterning of social vulnerability, although initially concentrated in certain geographic regions, has become more dispersed over time. The national trend shows a steady reduction in social vulnerability, but there is considerable regional variability, with many counties increasing in social vulnerability during the past five decades. PMID:18268336

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

NASA Astrophysics Data System (ADS)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.

Spatial Patterns in the Efficiency of the Biological Pump: What Controls Export Ratios at the Global Scale?

NASA Astrophysics Data System (ADS)

Moore, J. K.

2016-02-01

The efficiency of the biological pump is influenced by complex interactions between chemical, biological, and physical processes. The efficiency of export out of surface waters and down through the water column to the deep ocean has been linked to a number of factors including biota community composition, production of mineral ballast components, physical aggregation and disaggregation processes, and ocean oxygen concentrations. I will examine spatial patterns in the export ratio and the efficiency of the biological pump at the global scale using the Community Earth System Model (CESM). There are strong spatial variations in the export efficiency as simulated by the CESM, which are strongly correlated with new nutrient inputs to the euphotic zone and their impacts on phytoplankton community structure. I will compare CESM simulations that include dynamic, variable export ratios driven by the phytoplankton community structure, with simulations that impose a near-constant export ratio to examine the effects of export efficiency on nutrient and surface chlorophyll distributions. The model predicted export ratios will also be compared with recent satellite-based estimates.

Exploring space-time structure of human mobility in urban space

NASA Astrophysics Data System (ADS)

Sun, J. B.; Yuan, J.; Wang, Y.; Si, H. B.; Shan, X. M.

2011-03-01

Understanding of human mobility in urban space benefits the planning and provision of municipal facilities and services. Due to the high penetration of cell phones, mobile cellular networks provide information for urban dynamics with a large spatial extent and continuous temporal coverage in comparison with traditional approaches. The original data investigated in this paper were collected by cellular networks in a southern city of China, recording the population distribution by dividing the city into thousands of pixels. The space-time structure of urban dynamics is explored by applying Principal Component Analysis (PCA) to the original data, from temporal and spatial perspectives between which there is a dual relation. Based on the results of the analysis, we have discovered four underlying rules of urban dynamics: low intrinsic dimensionality, three categories of common patterns, dominance of periodic trends, and temporal stability. It implies that the space-time structure can be captured well by remarkably few temporal or spatial predictable periodic patterns, and the structure unearthed by PCA evolves stably over time. All these features play a critical role in the applications of forecasting and anomaly detection.

Ontology patterns for complex topographic feature yypes

USGS Publications Warehouse

Varanka, Dalia E.

2011-01-01

Complex feature types are defined as integrated relations between basic features for a shared meaning or concept. The shared semantic concept is difficult to define in commonly used geographic information systems (GIS) and remote sensing technologies. The role of spatial relations between complex feature parts was recognized in early GIS literature, but had limited representation in the feature or coverage data models of GIS. Spatial relations are more explicitly specified in semantic technology. In this paper, semantics for topographic feature ontology design patterns (ODP) are developed as data models for the representation of complex features. In the context of topographic processes, component assemblages are supported by resource systems and are found on local landscapes. The topographic ontology is organized across six thematic modules that can account for basic feature types, resource systems, and landscape types. Types of complex feature attributes include location, generative processes and physical description. Node/edge networks model standard spatial relations and relations specific to topographic science to represent complex features. To demonstrate these concepts, data from The National Map of the U. S. Geological Survey was converted and assembled into ODP.

Living in the branches: population dynamics and ecological processes in dendritic networks

USGS Publications Warehouse

Grant, E.H.C.; Lowe, W.H.; Fagan, W.F.

2007-01-01

Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.

Nanoscale chemical imaging by photoinduced force microscopy

PubMed Central

Nowak, Derek; Morrison, William; Wickramasinghe, H. Kumar; Jahng, Junghoon; Potma, Eric; Wan, Lei; Ruiz, Ricardo; Albrecht, Thomas R.; Schmidt, Kristin; Frommer, Jane; Sanders, Daniel P.; Park, Sung

2016-01-01

Correlating spatial chemical information with the morphology of closely packed nanostructures remains a challenge for the scientific community. For example, supramolecular self-assembly, which provides a powerful and low-cost way to create nanoscale patterns and engineered nanostructures, is not easily interrogated in real space via existing nondestructive techniques based on optics or electrons. A novel scanning probe technique called infrared photoinduced force microscopy (IR PiFM) directly measures the photoinduced polarizability of the sample in the near field by detecting the time-integrated force between the tip and the sample. By imaging at multiple IR wavelengths corresponding to absorption peaks of different chemical species, PiFM has demonstrated the ability to spatially map nm-scale patterns of the individual chemical components of two different types of self-assembled block copolymer films. With chemical-specific nanometer-scale imaging, PiFM provides a powerful new analytical method for deepening our understanding of nanomaterials. PMID:27051870

Describing litho-constrained layout by a high-resolution model filter

NASA Astrophysics Data System (ADS)

Tsai, Min-Chun

2008-05-01

A novel high-resolution model (HRM) filtering technique was proposed to describe litho-constrained layouts. Litho-constrained layouts are layouts that have difficulties to pattern or are highly sensitive to process-fluctuations under current lithography technologies. HRM applies a short-wavelength (or high NA) model simulation directly on the pre-OPC, original design layout to filter out low spatial-frequency regions, and retain high spatial-frequency components which are litho-constrained. Since no OPC neither mask-synthesis steps are involved, this new technique is highly efficient in run time and can be used in design stage to detect and fix litho-constrained patterns. This method has successfully captured all the hot-spots with less than 15% overshoots on a realistic 80 mm2 full-chip M1 layout in 65nm technology node. A step by step derivation of this HRM technique is presented in this paper.

Deriving frequency-dependent spatial patterns in MEG-derived resting state sensorimotor network: A novel multiband ICA technique.

PubMed

Nugent, Allison C; Luber, Bruce; Carver, Frederick W; Robinson, Stephen E; Coppola, Richard; Zarate, Carlos A

2017-02-01

Recently, independent components analysis (ICA) of resting state magnetoencephalography (MEG) recordings has revealed resting state networks (RSNs) that exhibit fluctuations of band-limited power envelopes. Most of the work in this area has concentrated on networks derived from the power envelope of beta bandpass-filtered data. Although research has demonstrated that most networks show maximal correlation in the beta band, little is known about how spatial patterns of correlations may differ across frequencies. This study analyzed MEG data from 18 healthy subjects to determine if the spatial patterns of RSNs differed between delta, theta, alpha, beta, gamma, and high gamma frequency bands. To validate our method, we focused on the sensorimotor network, which is well-characterized and robust in both MEG and functional magnetic resonance imaging (fMRI) resting state data. Synthetic aperture magnetometry (SAM) was used to project signals into anatomical source space separately in each band before a group temporal ICA was performed over all subjects and bands. This method preserved the inherent correlation structure of the data and reflected connectivity derived from single-band ICA, but also allowed identification of spatial spectral modes that are consistent across subjects. The implications of these results on our understanding of sensorimotor function are discussed, as are the potential applications of this technique. Hum Brain Mapp 38:779-791, 2017. © 2016 Wiley Periodicals, Inc. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Cross-modal integration of polyphonic characters in Chinese audio-visual sentences: a MVPA study based on functional connectivity.

PubMed

Zhang, Zhengyi; Zhang, Gaoyan; Zhang, Yuanyuan; Liu, Hong; Xu, Junhai; Liu, Baolin

2017-12-01

This study aimed to investigate the functional connectivity in the brain during the cross-modal integration of polyphonic characters in Chinese audio-visual sentences. The visual sentences were all semantically reasonable and the audible pronunciations of the polyphonic characters in corresponding sentences contexts varied in four conditions. To measure the functional connectivity, correlation, coherence and phase synchronization index (PSI) were used, and then multivariate pattern analysis was performed to detect the consensus functional connectivity patterns. These analyses were confined in the time windows of three event-related potential components of P200, N400 and late positive shift (LPS) to investigate the dynamic changes of the connectivity patterns at different cognitive stages. We found that when differentiating the polyphonic characters with abnormal pronunciations from that with the appreciate ones in audio-visual sentences, significant classification results were obtained based on the coherence in the time window of the P200 component, the correlation in the time window of the N400 component and the coherence and PSI in the time window the LPS component. Moreover, the spatial distributions in these time windows were also different, with the recruitment of frontal sites in the time window of the P200 component, the frontal-central-parietal regions in the time window of the N400 component and the central-parietal sites in the time window of the LPS component. These findings demonstrate that the functional interaction mechanisms are different at different stages of audio-visual integration of polyphonic characters.

[Time-organization of EEG patterns' structure in anxiety and phobic disorders].

PubMed

Sviatogor, I A; Mokhovikova, I A

2005-01-01

Thirty-five patients, aged 19-48 years (mean age 38 years) with anxiety and phobic disorders were examined. According to ICD-10 criteria--social phobia (F40.1), panic disorder (F41.0), somatoform autonomic dysfunction (F45.3) were diagnosed. Using electroencephalography data, qualitative and quantitative characteristics of the time- and spatial-organization of brain EEG activity in anxiety and phobic disorders of different severity were established. It were determined 4 types of wave interactions between EEG components, which reflected a different extent of the regulatory mechanisms lesions: 2 structures with one core component (alpha or beta), a structure with two core components and a non-organized structure.

Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

USGS Publications Warehouse

Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.

2010-01-01

This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.

Derivation of two well-behaved theoretical contagion indices and their sampling properties and application for assessing forest landscape diversity

Treesearch

Bernard R. Parresol

2011-01-01

Studies of spatial patterns of landscapes are useful to quantify human impact, predict wildlife effects, or describe variability of landscape features. A common approach to identify and quantify landscape structure is with a landscape scale model known as a contagion index. A contagion index quantifies two distinct components of landscape diversity: composition and...

Predictive Spatial Analysis of Marine Mammal Habitats

DTIC Science & Technology

2010-01-01

Therefore, it would be desirable to focus on biological components of their habitat to describe their patterns of distribution and abundance . For...difficult (and often impossible) to determine prey abundance and distribution in the ocean, even with commercially important species. We currently do...not have the tools to determine the distribution and abundance of these prey species at scales that are relevant to either marine mammals or the

Visual Analysis of Social Networks in a Counter-Insurgency Context

DTIC Science & Technology

2011-06-01

Batagelj and Mrvar 2003] specifically focus on the analysis and visualisation of extremely large networks. Moreover, on top of these data about the...and behavioral components of a complex conflict ecosystem, SpringSim: 23. Batagelj , V. & Mrvar , A., (2003), Pajek - analysis and visualisation of...information regarding network patterns and structures, no spatial information is usually encoded. This is despite the fact that already Wellman [ 1996

Gelatin-based laser direct-write technique for the precise spatial patterning of cells.

PubMed

Schiele, Nathan R; Chrisey, Douglas B; Corr, David T

2011-03-01

Laser direct-writing provides a method to pattern living cells in vitro, to study various cell-cell interactions, and to build cellular constructs. However, the materials typically used may limit its long-term application. By utilizing gelatin coatings on the print ribbon and growth surface, we developed a new approach for laser cell printing that overcomes the limitations of Matrigel™. Gelatin is free of growth factors and extraneous matrix components that may interfere with cellular processes under investigation. Gelatin-based laser direct-write was able to successfully pattern human dermal fibroblasts with high post-transfer viability (91% ± 3%) and no observed double-strand DNA damage. As seen with atomic force microscopy, gelatin offers a unique benefit in that it is present temporarily to allow cell transfer, but melts and is removed with incubation to reveal the desired application-specific growth surface. This provides unobstructed cellular growth after printing. Monitoring cell location after transfer, we show that melting and removal of gelatin does not affect cellular placement; cells maintained registry within 5.6 ± 2.5 μm to the initial pattern. This study demonstrates the effectiveness of gelatin in laser direct-writing to create spatially precise cell patterns with the potential for applications in tissue engineering, stem cell, and cancer research.

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.

Effects of nitrogen nutrition on the synthesis and deposition of the ω-gliadins of wheat.

PubMed

Wan, Yongfang; Gritsch, Cristina Sanchis; Hawkesford, Malcolm J; Shewry, Peter R

2014-03-01

The ω-gliadin storage proteins of wheat are of interest in relation to their impact on grain processing properties and their role in food allergy, particularly the ω-5 sub-group and wheat-dependent exercise-induced anaphylaxis. The ω-gliadins are also known to be responsive to nitrogen application. This study therefore compares the effects of cultivar and nitrogen availability on the synthesis and deposition of ω-gliadins in wheat grown under field conditions in the UK, including temporal and spatial analyses at the protein and transcript levels. SDS-PAGE, western blotting and N-terminal amino acid sequencing were used to compare the patterns of ω-gliadin components in mature grain of six British wheat (Triticum aestivum) cultivars and their accumulation during the development of grain grown in field plots with varying nitrogen supply. Changes in gene expression during development were determined using real-time reverse transcription-PCR (RT-PCR). Spatial patterns of gene expression and protein accumulation were determined by in situ hybridization and immunofluorescence microscopy, respectively. Two patterns of ω-gliadins were identified in the six cultivars, including both monomeric 'gliadin' proteins and subunits present in polymeric 'glutenin' fractions. Increasing the level of nitrogen fertilizer in field plots resulted in increased expression of ω-gliadin transcripts and increased proportions of ω-5 gliadins. Nitrogen supply also affected the spatial patterns of ω-gliadin synthesis and deposition, which were differentially increased in the outer layers of the starchy endosperm with high levels of nitrogen. Wheat ω-gliadins vary in amount and composition between cultivars, and in their response to nitrogen supply. Their spatial distribution is also affected by nitrogen supply, being most highly concentrated in the sub-aleurone cells of the starchy endosperm under higher nitrogen availability.

a Multidisciplinary Analytical Framework for Studying Active Mobility Patterns

NASA Astrophysics Data System (ADS)

Orellana, D.; Hermida, C.; Osorio, P.

2016-06-01

Intermediate cities are urged to change and adapt their mobility systems from a high energy-demanding motorized model to a sustainable low-motorized model. In order to accomplish such a model, city administrations need to better understand active mobility patterns and their links to socio-demographic and cultural aspects of the population. During the last decade, researchers have demonstrated the potential of geo-location technologies and mobile devices to gather massive amounts of data for mobility studies. However, the analysis and interpretation of this data has been carried out by specialized research groups with relatively narrow approaches from different disciplines. Consequently, broader questions remain less explored, mainly those relating to spatial behaviour of individuals and populations with their geographic environment and the motivations and perceptions shaping such behaviour. Understanding sustainable mobility and exploring new research paths require an interdisciplinary approach given the complex nature of mobility systems and their social, economic and environmental impacts. Here, we introduce the elements for a multidisciplinary analytical framework for studying active mobility patterns comprised of three components: a) Methodological, b) Behavioural, and c) Perceptual. We demonstrate the applicability of the framework by analysing mobility patterns of cyclists and pedestrians in an intermediate city integrating a range of techniques, including: GPS tracking, spatial analysis, auto-ethnography, and perceptual mapping. The results demonstrated the existence of non-evident spatial behaviours and how perceptual features affect mobility. This knowledge is useful for developing policies and practices for sustainable mobility planning.

Protection Enhances Community and Habitat Stability: Evidence from a Mediterranean Marine Protected Area

PubMed Central

Fraschetti, Simonetta; Guarnieri, Giuseppe; Bevilacqua, Stanislao; Terlizzi, Antonio; Boero, Ferdinando

2013-01-01

Rare evidences support that Marine Protected Areas (MPAs) enhance the stability of marine habitats and assemblages. Based on nine years of observation (2001–2009) inside and outside a well managed MPA, we assessed the potential of conservation and management actions to modify patterns of spatial and/or temporal variability of Posidonia oceanica meadows, the lower midlittoral and the shallow infralittoral rock assemblages. Significant differences in both temporal variations and spatial patterns were observed between protected and unprotected locations. A lower temporal variability in the protected vs. unprotected assemblages was found in the shallow infralittoral, demonstrating that, at least at local scale, protection can enhance community stability. Macrobenthos with long-lived and relatively slow-growing invertebrates and structurally complex algal forms were homogeneously distributed in space and went through little fluctuations in time. In contrast, a mosaic of disturbed patches featured unprotected locations, with small-scale shifts from macroalgal stands to barrens, and harsh temporal variations between the two states. Opposite patterns of spatial and temporal variability were found for the midlittoral assemblages. Despite an overall clear pattern of seagrass regression through time, protected meadows showed a significantly higher shoot density than unprotected ones, suggesting a higher resistance to local human activities. Our results support the assumption that the exclusion/management of human activities within MPAs enhance the stability of the structural components of protected marine systems, reverting or arresting threat-induced trajectories of change. PMID:24349135

The Nature of Antarctic Temperature Change

NASA Astrophysics Data System (ADS)

Markle, B. R.; Steig, E. J.

2017-12-01

The Antarctic is an important component of global climate. While the Arctic has warmed significantly in the last century, the Antarctic as a whole has shown considerably less variability. There is, however, a pronounced spatial pattern to modern Antarctic temperature change. The high East Antarctic Ice Sheet shows little to no warming over recent decades while West Antarctica and the Peninsula shows some of the largest rates of warming on the globe. Examining past climate variability can help reveal the physical processes governing this spatial pattern of Antarctic temperature change. Modern Antarctic temperature variability is known from satellite and weather station observations. Understanding changes in the past, however, requires paleoclimate-proxies such as ice-core water-isotope records. Here we assess the spatial pattern of Antarctic temperature changes across a range of timescales, from modern decadal changes to millennial and orbital-scale variability. We reconstruct past changes in absolute temperatures from a suite of deep ice core records and an improved isotope-temperature reconstruction method. We use δ18O and deuterium excess records to reconstruct both evaporation source and condensation site temperatures. In contrast to previous studies we use a novel method that accounts for nonlinearities in the water-isotope distillation process. We quantify past temperature changes over the Southern Ocean and Antarctic Continent and the magnitude of polar amplification. We identify patterns of Antarctic temperature change that are common across a wide range of timescales and independent of the source of forcing. We examine the nature of these changes and their relationship to atmospheric thermodynamics.

Partitioning the impact of environment and spatial structure on alpha and beta components of taxonomic, functional, and phylogenetic diversity in European ants.

PubMed

Arnan, Xavier; Cerdá, Xim; Retana, Javier

2015-01-01

We analyze the relative contribution of environmental and spatial variables to the alpha and beta components of taxonomic (TD), phylogenetic (PD), and functional (FD) diversity in ant communities found along different climate and anthropogenic disturbance gradients across western and central Europe, in order to assess the mechanisms structuring ant biodiversity. To this aim we calculated alpha and beta TD, PD, and FD for 349 ant communities, which included a total of 155 ant species; we examined 10 functional traits and phylogenetic relatedness. Variation partitioning was used to examine how much variation in ant diversity was explained by environmental and spatial variables. Autocorrelation in diversity measures and each trait's phylogenetic signal were also analyzed. We found strong autocorrelation in diversity measures. Both environmental and spatial variables significantly contributed to variation in TD, PD, and FD at both alpha and beta scales; spatial structure had the larger influence. The different facets of diversity showed similar patterns along environmental gradients. Environment explained a much larger percentage of variation in FD than in TD or PD. All traits demonstrated strong phylogenetic signals. Our results indicate that environmental filtering and dispersal limitations structure all types of diversity in ant communities. Strong dispersal limitations appear to have led to clustering of TD, PD, and FD in western and central Europe, probably because different historical and evolutionary processes generated different pools of species. Remarkably, these three facets of diversity showed parallel patterns along environmental gradients. Trait-mediated species sorting and niche conservatism appear to structure ant diversity, as evidenced by the fact that more variation was explained for FD and that all traits had strong phylogenetic signals. Since environmental variables explained much more variation in FD than in PD, functional diversity should be a better indicator of community assembly processes than phylogenetic diversity.

An interpretation of flare-induced and decayless coronal-loop oscillations as interference patterns

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

Hindman, Bradley W.; Jain, Rekha, E-mail: hindman@solarz.colorado.edu

2014-04-01

We present an alternative model of coronal-loop oscillations, which considers that the waves are trapped in a two-dimensional waveguide formed by the entire arcade of field lines. This differs from the standard one-dimensional model which treats the waves as the resonant oscillations of just the visible bundle of field lines. Within the framework of our two-dimensional model, the two types of oscillations that have been observationally identified, flare-induced waves and 'decayless' oscillations, can both be attributed to MHD fast waves. The two components of the signal differ only because of the duration and spatial extent of the source that createsmore » them. The flare-induced waves are generated by strong localized sources of short duration, while the decayless background can be excited by a continuous, stochastic source. Further, the oscillatory signal arising from a localized, short-duration source can be interpreted as a pattern of interference fringes produced by waves that have traveled diverse routes of various pathlengths through the waveguide. The resulting amplitude of the fringes slowly decays in time with an inverse square root dependence. The details of the interference pattern depend on the shape of the arcade and the spatial variation of the Alfvén speed. The rapid decay of this wave component, which has previously been attributed to physical damping mechanisms that remove energy from resonant oscillations, occurs as a natural consequence of the interference process without the need for local dissipation.« less

Decoding and reconstructing color from responses in human visual cortex.

PubMed

Brouwer, Gijs Joost; Heeger, David J

2009-11-04

How is color represented by spatially distributed patterns of activity in visual cortex? Functional magnetic resonance imaging responses to several stimulus colors were analyzed with multivariate techniques: conventional pattern classification, a forward model of idealized color tuning, and principal component analysis (PCA). Stimulus color was accurately decoded from activity in V1, V2, V3, V4, and VO1 but not LO1, LO2, V3A/B, or MT+. The conventional classifier and forward model yielded similar accuracies, but the forward model (unlike the classifier) also reliably reconstructed novel stimulus colors not used to train (specify parameters of) the model. The mean responses, averaged across voxels in each visual area, were not reliably distinguishable for the different stimulus colors. Hence, each stimulus color was associated with a unique spatially distributed pattern of activity, presumably reflecting the color selectivity of cortical neurons. Using PCA, a color space was derived from the covariation, across voxels, in the responses to different colors. In V4 and VO1, the first two principal component scores (main source of variation) of the responses revealed a progression through perceptual color space, with perceptually similar colors evoking the most similar responses. This was not the case for any of the other visual cortical areas, including V1, although decoding was most accurate in V1. This dissociation implies a transformation from the color representation in V1 to reflect perceptual color space in V4 and VO1.

Physical-chemical mechanisms of pattern formation during gastrulation

NASA Astrophysics Data System (ADS)

Bozorgui, Behnaz; Kolomeisky, Anatoly B.; Teimouri, Hamid

2018-03-01

Gastrulation is a fundamental phase during the biological development of most animals when a single layer of identical embryo cells is transformed into a three-layer structure, from which the organs start to develop. Despite a remarkable progress in quantifying the gastrulation processes, molecular mechanisms of these processes remain not well understood. Here we theoretically investigate early spatial patterning in a geometrically confined colony of embryonic stem cells. Using a reaction-diffusion model, a role of Bone-Morphogenetic Protein 4 (BMP4) signaling pathway in gastrulation is specifically analyzed. Our results show that for slow diffusion rates of BMP4 molecules, a new length scale appears, which is independent of the size of the system. This length scale separates the central region of the colony with uniform low concentrations of BMP molecules from the region near the colony edge where the concentration of signaling molecules is elevated. The roles of different components of the signaling pathway are also explained. Theoretical results are consistent with recent in vitro experiments, providing microscopic explanations for some features of early embryonic spatial patterning. Physical-chemical mechanisms of these processes are discussed.

Visual analytics of geo-social interaction patterns for epidemic control.

PubMed

Luo, Wei

2016-08-10

Human interaction and population mobility determine the spatio-temporal course of the spread of an airborne disease. This research views such spreads as geo-social interaction problems, because population mobility connects different groups of people over geographical locations via which the viruses transmit. Previous research argued that geo-social interaction patterns identified from population movement data can provide great potential in designing effective pandemic mitigation. However, little work has been done to examine the effectiveness of designing control strategies taking into account geo-social interaction patterns. To address this gap, this research proposes a new framework for effective disease control; specifically this framework proposes that disease control strategies should start from identifying geo-social interaction patterns, designing effective control measures accordingly, and evaluating the efficacy of different control measures. This framework is used to structure design of a new visual analytic tool that consists of three components: a reorderable matrix for geo-social mixing patterns, agent-based epidemic models, and combined visualization methods. With real world human interaction data in a French primary school as a proof of concept, this research compares the efficacy of vaccination strategies between the spatial-social interaction patterns and the whole areas. The simulation results show that locally targeted vaccination has the potential to keep infection to a small number and prevent spread to other regions. At some small probability, the local control strategies will fail; in these cases other control strategies will be needed. This research further explores the impact of varying spatial-social scales on the success of local vaccination strategies. The results show that a proper spatial-social scale can help achieve the best control efficacy with a limited number of vaccines. The case study shows how GS-EpiViz does support the design and testing of advanced control scenarios in airborne disease (e.g., influenza). The geo-social patterns identified through exploring human interaction data can help target critical individuals, locations, and clusters of locations for disease control purposes. The varying spatial-social scales can help geographically and socially prioritize limited resources (e.g., vaccines).

Use of Raman microscopy and band-target entropy minimization analysis to identify dyes in a commercial stamp. Implications for authentication and counterfeit detection.

PubMed

Widjaja, Effendi; Garland, Marc

2008-02-01

Raman microscopy was used in mapping mode to collect more than 1000 spectra in a 100 microm x 100 microm area from a commercial stamp. Band-target entropy minimization (BTEM) was then employed to unmix the mixture spectra in order to extract the pure component spectra of the samples. Three pure component spectral patterns with good signal-to-noise ratios were recovered, and their spatial distributions were determined. The three pure component spectral patterns were then identified as copper phthalocyanine blue, calcite-like material, and yellow organic dye material by comparison to known spectral libraries. The present investigation, consisting of (1) advanced curve resolution (blind-source separation) followed by (2) spectral data base matching, readily suggests extensions to authenticity and counterfeit studies of other types of commercial objects. The presence or absence of specific observable components form the basis for assessment. The present spectral analysis (BTEM) is applicable to highly overlapping spectral information. Since a priori information such as the number of components present and spectral libraries are not needed in BTEM, and since minor signals arising from trace components can be reconstructed, this analysis offers a robust approach to a wide variety of material problems involving authenticity and counterfeit issues.

Comparison of multi-subject ICA methods for analysis of fMRI data

PubMed Central

Erhardt, Erik Barry; Rachakonda, Srinivas; Bedrick, Edward; Allen, Elena; Adali, Tülay; Calhoun, Vince D.

2010-01-01

Spatial independent component analysis (ICA) applied to functional magnetic resonance imaging (fMRI) data identifies functionally connected networks by estimating spatially independent patterns from their linearly mixed fMRI signals. Several multi-subject ICA approaches estimating subject-specific time courses (TCs) and spatial maps (SMs) have been developed, however there has not yet been a full comparison of the implications of their use. Here, we provide extensive comparisons of four multi-subject ICA approaches in combination with data reduction methods for simulated and fMRI task data. For multi-subject ICA, the data first undergo reduction at the subject and group levels using principal component analysis (PCA). Comparisons of subject-specific, spatial concatenation, and group data mean subject-level reduction strategies using PCA and probabilistic PCA (PPCA) show that computationally intensive PPCA is equivalent to PCA, and that subject-specific and group data mean subject-level PCA are preferred because of well-estimated TCs and SMs. Second, aggregate independent components are estimated using either noise free ICA or probabilistic ICA (PICA). Third, subject-specific SMs and TCs are estimated using back-reconstruction. We compare several direct group ICA (GICA) back-reconstruction approaches (GICA1-GICA3) and an indirect back-reconstruction approach, spatio-temporal regression (STR, or dual regression). Results show the earlier group ICA (GICA1) approximates STR, however STR has contradictory assumptions and may show mixed-component artifacts in estimated SMs. Our evidence-based recommendation is to use GICA3, introduced here, with subject-specific PCA and noise-free ICA, providing the most robust and accurate estimated SMs and TCs in addition to offering an intuitive interpretation. PMID:21162045

Thermal behaviour of nanofluids confined in nanochannels

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

Frank, Michael, E-mail: d.drikakis@cranfield.ac.uk; Drikakis, Dimitris, E-mail: d.drikakis@cranfield.ac.uk; Asproulis, Nikolaos, E-mail: d.drikakis@cranfield.ac.uk

2015-02-17

This work investigates the effect of spatial restriction on the thermal properties of nanofluids. Using Molecular Dynamics simulations, a Copper-Argon nanofluid is restricted within idealized walls. The thermal conductivity of the suspension is calculated using the Green-Kubo relations and is correlated with the volume fraction of the copper particles within the system as well as the channel width. The thermal conductivity is further broken down into its individual components in the three dimensions, revealing anisotropy between the directions parallel and normal to the channel walls. The observed thermodynamic patterns are justified by considering how the spatial restriction affects the liquidmore » structure around the nanoparticle.« less

Wavelength selection beyond turing

NASA Astrophysics Data System (ADS)

Zelnik, Yuval R.; Tzuk, Omer

2017-06-01

Spatial patterns arising spontaneously due to internal processes are ubiquitous in nature, varying from periodic patterns of dryland vegetation to complex structures of bacterial colonies. Many of these patterns can be explained in the context of a Turing instability, where patterns emerge due to two locally interacting components that diffuse with different speeds in the medium. Turing patterns are multistable, meaning that many different patterns with different wavelengths are possible for the same set of parameters. Nevertheless, in a given region typically only one such wavelength is dominant. In the Turing instability region, random initial conditions will mostly lead to a wavelength that is similar to that of the leading eigenvector that arises from the linear stability analysis, but when venturing beyond, little is known about the pattern that will emerge. Using dryland vegetation as a case study, we use different models of drylands ecosystems to study the wavelength pattern that is selected in various scenarios beyond the Turing instability region, focusing on the phenomena of localized states and repeated local disturbances.

COMPARISON OF SPATIAL PATTERNS OF POLLUTANT DISTRIBUTION WITH CMAQ PREDICTIONS

EPA Science Inventory

One indication of model performance is the comparison of spatial patterns of pollutants, either as concentration or deposition, predicted by the model with spatial patterns derived from measurements. If the spatial patterns produced by the model are similar to the observations i...

Mining Co-Location Patterns with Clustering Items from Spatial Data Sets

NASA Astrophysics Data System (ADS)

Zhou, G.; Li, Q.; Deng, G.; Yue, T.; Zhou, X.

2018-05-01

The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data mining. Spatial co-locations represent the subsets of features which are frequently located together in geographic space. However, the appearance of a spatial feature C is often not determined by a single spatial feature A or B but by the two spatial features A and B, that is to say where A and B appear together, C often appears. We note that this co-location pattern is different from the traditional co-location pattern. Thus, this paper presents a new concept called clustering terms, and this co-location pattern is called co-location patterns with clustering items. And the traditional algorithm cannot mine this co-location pattern, so we introduce the related concept in detail and propose a novel algorithm. This algorithm is extended by join-based approach proposed by Huang. Finally, we evaluate the performance of this algorithm.

Uniform functional structure across spatial scales in an intertidal benthic assemblage.

PubMed

Barnes, R S K; Hamylton, Sarah

2015-05-01

To investigate the causes of the remarkable similarity of emergent assemblage properties that has been demonstrated across disparate intertidal seagrass sites and assemblages, this study examined whether their emergent functional-group metrics are scale related by testing the null hypothesis that functional diversity and the suite of dominant functional groups in seagrass-associated macrofauna are robust structural features of such assemblages and do not vary spatially across nested scales within a 0.4 ha area. This was carried out via a lattice of 64 spatially referenced stations. Although densities of individual components were patchily dispersed across the locality, rank orders of importance of the 14 functional groups present, their overall functional diversity and evenness, and the proportions of the total individuals contained within each showed, in contrast, statistically significant spatial uniformity, even at areal scales <2 m(2). Analysis of the proportional importance of the functional groups in their geospatial context also revealed weaker than expected levels of spatial autocorrelation, and then only at the smaller scales and amongst the most dominant groups, and only a small number of negative correlations occurred between the proportional importances of the individual groups. In effect, such patterning was a surface veneer overlying remarkable stability of assemblage functional composition across all spatial scales. Although assemblage species composition is known to be homogeneous in some soft-sediment marine systems over equivalent scales, this combination of patchy individual components yet basically constant functional-group structure seems as yet unreported. Copyright © 2015 Elsevier Ltd. All rights reserved.

Macroscale patterns of synchrony identify complex relationships among spatial and temporal ecosystem drivers

USGS Publications Warehouse

Lottig, Noah R.; Tan, Pang-Ning; Wagner, Tyler; Cheruvelil, Kendra Spence; Soranno, Patricia A.; Stanley, Emily H.; Scott, Caren E.; Stow, Craig A.; Yuan, Shuai

2017-01-01

Ecology has a rich history of studying ecosystem dynamics across time and space that has been motivated by both practical management needs and the need to develop basic ideas about pattern and process in nature. In situations in which both spatial and temporal observations are available, similarities in temporal behavior among sites (i.e., synchrony) provide a means of understanding underlying processes that create patterns over space and time. We used pattern analysis algorithms and data spanning 22–25 yr from 601 lakes to ask three questions: What are the temporal patterns of lake water clarity at sub‐continental scales? What are the spatial patterns (i.e., geography) of synchrony for lake water clarity? And, what are the drivers of spatial and temporal patterns in lake water clarity? We found that the synchrony of water clarity among lakes is not spatially structured at sub‐continental scales. Our results also provide strong evidence that the drivers related to spatial patterns in water clarity are not related to the temporal patterns of water clarity. This analysis of long‐term patterns of water clarity and possible drivers contributes to understanding of broad‐scale spatial patterns in the geography of synchrony and complex relationships between spatial and temporal patterns across ecosystems.

Spatial and Temporal Patterns of Impervious Cover Relative to Watershed Stream Location

EPA Science Inventory

The influence of spatial pattern on ecological processes is a guiding principle of landscape ecology. The guiding principle of spatial pattern was used for a U.S. nationwide assessment of impervious cover (IC). Spatial pattern was measured by comparing IC concentration near strea...

Modeling and Compensating Temperature-Dependent Non-Uniformity Noise in IR Microbolometer Cameras

PubMed Central

Wolf, Alejandro; Pezoa, Jorge E.; Figueroa, Miguel

2016-01-01

Images rendered by uncooled microbolometer-based infrared (IR) cameras are severely degraded by the spatial non-uniformity (NU) noise. The NU noise imposes a fixed-pattern over the true images, and the intensity of the pattern changes with time due to the temperature instability of such cameras. In this paper, we present a novel model and a compensation algorithm for the spatial NU noise and its temperature-dependent variations. The model separates the NU noise into two components: a constant term, which corresponds to a set of NU parameters determining the spatial structure of the noise, and a dynamic term, which scales linearly with the fluctuations of the temperature surrounding the array of microbolometers. We use a black-body radiator and samples of the temperature surrounding the IR array to offline characterize both the constant and the temperature-dependent NU noise parameters. Next, the temperature-dependent variations are estimated online using both a spatially uniform Hammerstein-Wiener estimator and a pixelwise least mean squares (LMS) estimator. We compensate for the NU noise in IR images from two long-wave IR cameras. Results show an excellent NU correction performance and a root mean square error of less than 0.25 ∘C, when the array’s temperature varies by approximately 15 ∘C. PMID:27447637

Exploring the impact of climate variability during the Last Glacial Maximum on the pattern of human occupation of Iberia.

PubMed

Burke, Ariane; Levavasseur, Guillaume; James, Patrick M A; Guiducci, Dario; Izquierdo, Manuel Arturo; Bourgeon, Lauriane; Kageyama, Masa; Ramstein, Gilles; Vrac, Mathieu

2014-08-01

The Last Glacial Maximum (LGM) was a global climate event, which had significant repercussions for the spatial distribution and demographic history of prehistoric populations. In Eurasia, the LGM coincides with a potential bottleneck for modern humans and may mark the divergence date for Asian and European populations (Keinan et al., 2007). In this research, the impact of climate variability on human populations in the Iberian Peninsula during the Last Glacial Maximum (LGM) is examined with the aid of downscaled high-resolution (16 × 16 km) numerical climate experiments. Human sensitivity to short time-scale (inter-annual) climate variability during this key time period, which follows the initial modern human colonisation of Eurasia and the extinction of the Neanderthals, is tested using the spatial distribution of archaeological sites. Results indicate that anatomically modern human populations responded to small-scale spatial patterning in climate variability, specifically inter-annual variability in precipitation levels as measured by the standard precipitation index. Climate variability at less than millennial scale, therefore, is shown to be an important component of ecological risk, one that played a role in regulating the spatial behaviour of prehistoric human populations and consequently affected their social networks. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spatial distribution of antibodies to Salmonella enterica serovar Typhimurium O antigens in bulk milk from Texas dairy herds.

PubMed

Graham, S L; Barling, K S; Waghela, S; Scott, H M; Thompson, J A

2005-06-10

Environmental factors that enhance either the survivability or dispersion of Salmonella enterica serovar Typhimurium (S. Typhimurium) could result in a spatial pattern of disease risk. The objectives of this study were to: (1) describe herd status based on antibody response to Salmonella Typhimurium as estimated from bulk tank milk samples and (2) to describe the resulting geographical patterns found among Texas dairy herds. Eight hundred and fifty-two bulk milk samples were collected from georeferenced dairy farms and assayed by an indirect enzyme-linked immunosorbent assay (ELISA) using S. Typhimurium lipopolysaccharide (LPS). ELISA signal-to-noise ratios for each bulk tank milk sample were calculated and used for geostatistical analyses. Best-fit parameters for the exponential theoretical variogram included a range of 438.8 km, partial sill of 0.060 and nugget of 0.106. The partial sill is the classical geostatistical term for the variance that can be explained by the herd's location and the nugget is the spatially random component of the variance. We have identified a spatial process in bulk milk tank titers for S. Typhimurium in Texas dairy herds and present a map of the expected smoothed surface. Areas with higher expected titers should be targeted in further studies on controlling Salmonella infection with environmental modifications.

Temporal and spatial differences between taxonomic and trait biodiversity in a large marine ecosystem: Causes and consequences.

PubMed

Dencker, Tim Spaanheden; Pecuchet, Laurene; Beukhof, Esther; Richardson, Katherine; Payne, Mark R; Lindegren, Martin

2017-01-01

Biodiversity is a multifaceted concept, yet most biodiversity studies have taken a taxonomic approach, implying that all species are equally important. However, species do not contribute equally to ecosystem processes and differ markedly in their responses to changing environments. This recognition has led to the exploration of other components of biodiversity, notably the diversity of ecologically important traits. Recent studies taking into account both taxonomic and trait diversity have revealed that the two biodiversity components may exhibit pronounced temporal and spatial differences. These apparent incongruences indicate that the two components may respond differently to environmental drivers and that changes in one component might not affect the other. Such incongruences may provide insight into the structuring of communities through community assembly processes, and the resilience of ecosystems to change. Here we examine temporal and spatial patterns and drivers of multiple marine biodiversity indicators using the North Sea fish community as a case study. Based on long-term spatially resolved survey data on fish species occurrences and biomasses from 1983 to 2014 and an extensive trait dataset we: (i) investigate temporal and spatial incongruences between taxonomy and trait-based indicators of both richness and evenness; (ii) examine the underlying environmental drivers and, (iii) interpret the results in the context of assembly rules acting on community composition. Our study shows that taxonomy and trait-based biodiversity indicators differ in time and space and that these differences are correlated to natural and anthropogenic drivers, notably temperature, depth and substrate richness. Our findings show that trait-based biodiversity indicators add information regarding community composition and ecosystem structure compared to and in conjunction with taxonomy-based indicators. These results emphasize the importance of examining and monitoring multiple indicators of biodiversity in ecological studies as well as for conservation and ecosystem-based management purposes.

Temporal and spatial differences between taxonomic and trait biodiversity in a large marine ecosystem: Causes and consequences

PubMed Central

Pecuchet, Laurene; Beukhof, Esther; Richardson, Katherine; Payne, Mark R.; Lindegren, Martin

2017-01-01

Biodiversity is a multifaceted concept, yet most biodiversity studies have taken a taxonomic approach, implying that all species are equally important. However, species do not contribute equally to ecosystem processes and differ markedly in their responses to changing environments. This recognition has led to the exploration of other components of biodiversity, notably the diversity of ecologically important traits. Recent studies taking into account both taxonomic and trait diversity have revealed that the two biodiversity components may exhibit pronounced temporal and spatial differences. These apparent incongruences indicate that the two components may respond differently to environmental drivers and that changes in one component might not affect the other. Such incongruences may provide insight into the structuring of communities through community assembly processes, and the resilience of ecosystems to change. Here we examine temporal and spatial patterns and drivers of multiple marine biodiversity indicators using the North Sea fish community as a case study. Based on long-term spatially resolved survey data on fish species occurrences and biomasses from 1983 to 2014 and an extensive trait dataset we: (i) investigate temporal and spatial incongruences between taxonomy and trait-based indicators of both richness and evenness; (ii) examine the underlying environmental drivers and, (iii) interpret the results in the context of assembly rules acting on community composition. Our study shows that taxonomy and trait-based biodiversity indicators differ in time and space and that these differences are correlated to natural and anthropogenic drivers, notably temperature, depth and substrate richness. Our findings show that trait-based biodiversity indicators add information regarding community composition and ecosystem structure compared to and in conjunction with taxonomy-based indicators. These results emphasize the importance of examining and monitoring multiple indicators of biodiversity in ecological studies as well as for conservation and ecosystem-based management purposes. PMID:29253876

Development of spatially diverse and complex dune-field patterns: Gran Desierto Dune Field, Sonora, Mexico

USGS Publications Warehouse

Beveridge, C.; Kocurek, G.; Ewing, R.C.; Lancaster, N.; Morthekai, P.; Singhvi, A.K.; Mahan, S.A.

2006-01-01

The pattern of dunes within the Gran Desierto of Sonora, Mexico, is both spatially diverse and complex. Identification of the pattern components from remote-sensing images, combined with statistical analysis of their measured parameters demonstrate that the composite pattern consists of separate populations of simple dune patterns. Age-bracketing by optically stimulated luminescence (OSL) indicates that the simple patterns represent relatively short-lived aeolian constructional events since ???25 ka. The simple dune patterns consist of: (i) late Pleistocene relict linear dunes; (ii) degraded crescentic dunes formed at ???12 ka; (iii) early Holocene western crescentic dunes; (iv) eastern crescentic dunes emplaced at ???7 ka; and (v) star dunes formed during the last 3 ka. Recognition of the simple patterns and their ages allows for the geomorphic backstripping of the composite pattern. Palaeowind reconstructions, based upon the rule of gross bedform-normal transport, are largely in agreement with regional proxy data. The sediment state over time for the Gran Desierto is one in which the sediment supply for aeolian constructional events is derived from previously stored sediment (Ancestral Colorado River sediment), and contemporaneous influx from the lower Colorado River valley and coastal influx from the Bahia del Adair inlet. Aeolian constructional events are triggered by climatic shifts to greater aridity, changes in the wind regime, and the development of a sediment supply. The rate of geomorphic change within the Gran Desierto is significantly greater than the rate of subsidence and burial of the accumulation surface upon which it rests. ?? 2006 The Authors. Journal compilation 2006 International Association of Sedimentologists.

Spatial patterns of brain amyloid-beta burden and atrophy rate associations in mild cognitive impairment.

PubMed

Tosun, Duygu; Schuff, Norbert; Mathis, Chester A; Jagust, William; Weiner, Michael W

2011-04-01

Amyloid-β accumulation in the brain is thought to be one of the earliest events in Alzheimer's disease, possibly leading to synaptic dysfunction, neurodegeneration and cognitive/functional decline. The earliest detectable changes seen with neuroimaging appear to be amyloid-β accumulation detected by (11)C-labelled Pittsburgh compound B positron emission tomography imaging. However, some individuals tolerate high brain amyloid-β loads without developing symptoms, while others progressively decline, suggesting that events in the brain downstream from amyloid-β deposition, such as regional brain atrophy rates, play an important role. The main purpose of this study was to understand the relationship between the regional distributions of increased amyloid-β and the regional distribution of increased brain atrophy rates in patients with mild cognitive impairment. To simultaneously capture the spatial distributions of amyloid-β and brain atrophy rates, we employed the statistical concept of parallel independent component analysis, an effective method for joint analysis of multimodal imaging data. Parallel independent component analysis identified significant relationships between two patterns of amyloid-β deposition and atrophy rates: (i) increased amyloid-β burden in the left precuneus/cuneus and medial-temporal regions was associated with increased brain atrophy rates in the left medial-temporal and parietal regions; and (ii) in contrast, increased amyloid-β burden in bilateral precuneus/cuneus and parietal regions was associated with increased brain atrophy rates in the right medial temporal regions. The spatial distribution of increased amyloid-β and the associated spatial distribution of increased brain atrophy rates embrace a characteristic pattern of brain structures known for a high vulnerability to Alzheimer's disease pathology, encouraging for the use of (11)C-labelled Pittsburgh compound B positron emission tomography measures as early indicators of Alzheimer's disease. These results may begin to shed light on the mechanisms by which amyloid-β deposition leads to neurodegeneration and cognitive decline and the development of a more specific Alzheimer's disease-specific imaging signature for diagnosis and use of this knowledge in the development of new anti-therapies for Alzheimer's disease.

Control of Turing patterns and their usage as sensors, memory arrays, and logic gates

NASA Astrophysics Data System (ADS)

Muzika, František; Schreiber, Igor

2013-10-01

We study a model system of three diffusively coupled reaction cells arranged in a linear array that display Turing patterns with special focus on the case of equal coupling strength for all components. As a suitable model reaction we consider a two-variable core model of glycolysis. Using numerical continuation and bifurcation techniques we analyze the dependence of the system's steady states on varying rate coefficient of the recycling step while the coupling coefficients of the inhibitor and activator are fixed and set at the ratios 100:1, 1:1, and 4:5. We show that stable Turing patterns occur at all three ratios but, as expected, spontaneous transition from the spatially uniform steady state to the spatially nonuniform Turing patterns occurs only in the first case. The other two cases possess multiple Turing patterns, which are stabilized by secondary bifurcations and coexist with stable uniform periodic oscillations. For the 1:1 ratio we examine modular spatiotemporal perturbations, which allow for controllable switching between the uniform oscillations and various Turing patterns. Such modular perturbations are then used to construct chemical computing devices utilizing the multiple Turing patterns. By classifying various responses we propose: (a) a single-input resettable sensor capable of reading certain value of concentration, (b) two-input and three-input memory arrays capable of storing logic information, (c) three-input, three-output logic gates performing combinations of logical functions OR, XOR, AND, and NAND.

Simulation of vehicle acoustics in support of netted sensor research and development

NASA Astrophysics Data System (ADS)

Christou, Carol T.; Jacyna, Garry M.

2005-05-01

The MITRE Corporation has initiated a three-year internally-funded research program in netted sensors, the first-year effort focusing on vehicle detection for border monitoring. An important component is developing an understanding of the complex acoustic structure of vehicle noise to aid in netted sensor-based detection and classification. This presentation will discuss the design of a high-fidelity vehicle acoustic simulator to model the generation and transmission of acoustic energy from a moving vehicle to a collection of sensor nodes. Realistic spatially-dependent automobile sounds are generated from models of the engine cylinder firing rates, muffler and manifold resonances, and speed-dependent tire whine noise. Tire noise is the dominant noise source for vehicle speeds in excess of 30 miles per hour (MPH). As a result, we have developed detailed models that successfully predict the tire noise spectrum as a function of speed, road surface wave-number spectrum, tire geometry, and tire tread pattern. We have also included realistic descriptions of the spatial directivity patterns for the engine harmonics, muffler, and tire whine noise components. The acoustic waveforms are propagated to each sensor node using a simple phase-dispersive multi-path model. A brief description of the models and their corresponding outputs is provided.

Directed formation of micro- and nanoscale patterns of functional light-harvesting LH2 complexes.

PubMed

Reynolds, Nicholas P; Janusz, Stefan; Escalante-Marun, Maryana; Timney, John; Ducker, Robert E; Olsen, John D; Otto, Cees; Subramaniam, Vinod; Leggett, Graham J; Hunter, C Neil

2007-11-28

The precision placement of the desired protein components on a suitable substrate is an essential prelude to any hybrid "biochip" device, but a second and equally important condition must also be met: the retention of full biological activity. Here we demonstrate the selective binding of an optically active membrane protein, the light-harvesting LH2 complex from Rhodobacter sphaeroides, to patterned self-assembled monolayers at the micron scale and the fabrication of nanometer-scale patterns of these molecules using near-field photolithographic methods. In contrast to plasma proteins, which are reversibly adsorbed on many surfaces, the LH2 complex is readily patterned simply by spatial control of surface polarity. Near-field photolithography has yielded rows of light-harvesting complexes only 98 nm wide. Retention of the native optical properties of patterned LH2 molecules was demonstrated using in situ fluorescence emission spectroscopy.

Up, Down, and All Around: Scale-Dependent Spatial Variation in Rocky-Shore Communities of Fildes Peninsula, King George Island, Antarctica

PubMed Central

Valdivia, Nelson; Díaz, María J.; Holtheuer, Jorge; Garrido, Ignacio; Huovinen, Pirjo; Gómez, Iván

2014-01-01

Understanding the variation of biodiversity along environmental gradients and multiple spatial scales is relevant for theoretical and management purposes. Hereby, we analysed the spatial variability in diversity and structure of intertidal and subtidal macrobenthic Antarctic communities along vertical environmental stress gradients and across multiple horizontal spatial scales. Since biotic interactions and local topographic features are likely major factors for coastal assemblages, we tested the hypothesis that fine-scale processes influence the effects of the vertical environmental stress gradients on the macrobenthic diversity and structure. We used nested sampling designs in the intertidal and subtidal habitats, including horizontal spatial scales ranging from few centimetres to 1000s of metres along the rocky shore of Fildes Peninsula, King George Island. In both intertidal and subtidal habitats, univariate and multivariate analyses showed a marked vertical zonation in taxon richness and community structure. These patterns depended on the horizontal spatial scale of observation, as all analyses showed a significant interaction between height (or depth) and the finer spatial scale analysed. Variance and pseudo-variance components supported our prediction for taxon richness, community structure, and the abundance of dominant species such as the filamentous green alga Urospora penicilliformis (intertidal), the herbivore Nacella concinna (intertidal), the large kelp-like Himantothallus grandifolius (subtidal), and the red crustose red alga Lithothamnion spp. (subtidal). We suggest that in coastal ecosystems strongly governed by physical factors, fine-scale processes (e.g. biotic interactions and refugia availability) are still relevant for the structuring and maintenance of the local communities. The spatial patterns found in this study serve as a necessary benchmark to understand the dynamics and adaptation of natural assemblages in response to observed and predicted environmental changes in Antarctica. PMID:24956114

Multispectral and polarimetric photodetection using a plasmonic metasurface

NASA Astrophysics Data System (ADS)

Pelzman, Charles; Cho, Sang-Yeon

2018-01-01

We present a metasurface-integrated Si 2-D CMOS sensor array for multispectral and polarimetric photodetection applications. The demonstrated sensor is based on the polarization selective extraordinary optical transmission from periodic subwavelength nanostructures, acting as artificial atoms, known as meta-atoms. The meta-atoms were created by patterning periodic rectangular apertures that support optical resonance at the designed spectral bands. By spatially separating meta-atom clusters with different lattice constants and orientations, the demonstrated metasurface can convert the polarization and spectral information of an optical input into a 2-D intensity pattern. As a proof-of-concept experiment, we measured the linear components of the Stokes parameters directly from captured images using a CMOS camera at four spectral bands. Compared to existing multispectral polarimetric sensors, the demonstrated metasurface-integrated CMOS system is compact and does not require any moving components, offering great potential for advanced photodetection applications.

Laser Imaging of Airborne Acoustic Emission by Nonlinear Defects

NASA Astrophysics Data System (ADS)

Solodov, Igor; Döring, Daniel; Busse, Gerd

2008-06-01

Strongly nonlinear vibrations of near-surface fractured defects driven by an elastic wave radiate acoustic energy into adjacent air in a wide frequency range. The variations of pressure in the emitted airborne waves change the refractive index of air thus providing an acoustooptic interaction with a collimated laser beam. Such an air-coupled vibrometry (ACV) is proposed for detecting and imaging of acoustic radiation of nonlinear spectral components by cracked defects. The photoelastic relation in air is used to derive induced phase modulation of laser light in the heterodyne interferometer setup. The sensitivity of the scanning ACV to different spatial components of the acoustic radiation is analyzed. The animated airborne emission patterns are visualized for the higher harmonic and frequency mixing fields radiated by planar defects. The results confirm a high localization of the nonlinear acoustic emission around the defects and complicated directivity patterns appreciably different from those observed for fundamental frequencies.

Antarctic Sea Ice-Atmosphere Interactions: A Self-organizing Map-based Perspective

NASA Astrophysics Data System (ADS)

Reusch, D. B.

2005-12-01

Interactions between the ocean, sea ice and the atmosphere are a significant component of the dynamic nature of the Earth's climate system. Self-organizing maps (SOMs), an analysis tool from the field of artificial neural networks, have been used to study variability in Antarctic sea ice extent and the West Antarctic atmospheric circulation, plus the relationship and interactions between these two systems. Self-organizing maps enable unsupervised classification of large, multivariate/multidimensional data sets, e.g., time series of the atmospheric circulation or sea-ice extent, into a fixed number of distinct generalized states or modes, organized spatially as a two-dimensional grid, that are representative of the input data. When applied to atmospheric data, the analysis yields a nonlinear classification of the continuum of atmospheric conditions. In contrast to principal component analysis, SOMs do not force orthogonality or require subjective rotations to produce interpretable patterns. Twenty four years (1973-96) of monthly sea ice extent data (10 deg longitude bands; Simmonds and Jacka, 1995) were analyzed with a 30-node SOM. The resulting set of generalized patterns concisely captures the spatial and temporal variability in this data. An example of the former is variability in the longitudinal region of greatest extent. The SOM patterns readily show that there are multiple spatial patterns corresponding to "greatest extent conditions". Temporal variability is examined by creating frequency maps (i.e., which patterns occur most often) by month. With the annual cycle still in the data, the monthly frequency maps show a cycle moving from least extent, through expansion to greatest extent and back through retreat. When plotted in "SOM space", month-to-month transitions occur at different rates of change, suggesting that there is variability in the rate of change in extent at different times of the year, e.g., retreat in January is faster than November. Twenty five years (1977-2001) of monthly 500 mb temperature and pressure data (from the ECMWF 40-year reanalysis, ERA-40) from a region centered on the Antarctic Peninsula were analyzed independently for a separate SOMs-based study. Dominant SOM temperature patterns include the expected summer warmth and winter cold, plus "dipoles" of warm Atlantic (Pacific) and cold Pacific (Atlantic) sectors (with corresponding pressure patterns). Temporally, there is the expected annual progression from warmth, through cooling and back to warmth, with no particularly predominant patterns in many of the monthly frequency maps when the full record is used. Stratifying by high/low values of the Southern Oscillation Index (SOI) suggests that the spatial patterns of cooling and warming may be related to conditions in the tropical Pacific: in a low SOI year (1987), cooling and warming both begin in the Atlantic sector, with the opposite true in a high SOI year (1989). Further study of this aspect is planned. In addition to direct comparisons of the SOM analysis results from each study, a joint SOM analysis will be done on the combined data sets, exploiting the flexibility and power of this technique. We anticipate additional useful insights into the joint variability and relationships between Antarctic sea ice and the overlying atmosphere through this expanded analysis.

Independent effects of motivation and spatial attention in the human visual cortex.

PubMed

Bayer, Mareike; Rossi, Valentina; Vanlessen, Naomi; Grass, Annika; Schacht, Annekathrin; Pourtois, Gilles

2017-01-01

Motivation and attention constitute major determinants of human perception and action. Nonetheless, it remains a matter of debate whether motivation effects on the visual cortex depend on the spatial attention system, or rely on independent pathways. This study investigated the impact of motivation and spatial attention on the activity of the human primary and extrastriate visual cortex by employing a factorial manipulation of the two factors in a cued pattern discrimination task. During stimulus presentation, we recorded event-related potentials and pupillary responses. Motivational relevance increased the amplitudes of the C1 component at ∼70 ms after stimulus onset. This modulation occurred independently of spatial attention effects, which were evident at the P1 level. Furthermore, motivation and spatial attention had independent effects on preparatory activation as measured by the contingent negative variation; and pupil data showed increased activation in response to incentive targets. Taken together, these findings suggest independent pathways for the influence of motivation and spatial attention on the activity of the human visual cortex. © The Author (2016). Published by Oxford University Press.

Health Monitoring System for Composite Structures

NASA Technical Reports Server (NTRS)

Tang, S. S.; Riccardella, P. C.; Andrews, R. J.; Grady, J. E.; Mucciaradi, A. N.

1996-01-01

An automated system was developed to monitor the health status of composites. It uses the vibration characteristics of composites to identify a component's damage condition. The vibration responses are characterized by a set of signal features defined in the time, frequency and spatial domains. The identification of these changes in the vibration characteristics corresponding to different health conditions was performed using pattern recognition principles. This allows efficient data reduction and interpretation of vast amounts of information. Test components were manufactured from isogrid panels to evaluate performance of the monitoring system. The components were damaged by impact to simulate different health conditions. Free vibration response was induced by a tap test on the test components. The monitoring system was trained using these free vibration responses to identify three different health conditions. They are undamaged vs. damaged, damage location and damage zone size. High reliability in identifying the correct component health condition was achieved by the monitoring system.

Climate and landscape influence on indicators of lake carbon cycling through spatial patterns in dissolved organic carbon.

PubMed

Lapierre, Jean-Francois; Seekell, David A; Del Giorgio, Paul A

2015-12-01

Freshwater ecosystems are strongly influenced by both climate and the surrounding landscape, yet the specific pathways connecting climatic and landscape drivers to the functioning of lake ecosystems are poorly understood. Here, we hypothesize that the links that exist between spatial patterns in climate and landscape properties and the spatial variation in lake carbon (C) cycling at regional scales are at least partly mediated by the movement of terrestrial dissolved organic carbon (DOC) in the aquatic component of the landscape. We assembled a set of indicators of lake C cycling (bacterial respiration and production, chlorophyll a, production to respiration ratio, and partial pressure of CO2 ), DOC concentration and composition, and landscape and climate characteristics for 239 temperate and boreal lakes spanning large environmental and geographic gradients across seven regions. There were various degrees of spatial structure in climate and landscape features that were coherent with the regionally structured patterns observed in lake DOC and indicators of C cycling. These different regions aligned well, albeit nonlinearly along a mean annual temperature gradient; whereas there was a considerable statistical effect of climate and landscape properties on lake C cycling, the direct effect was small and the overall effect was almost entirely overlapping with that of DOC concentration and composition. Our results suggest that key climatic and landscape signals are conveyed to lakes in part via the movement of terrestrial DOC to lakes and that DOC acts both as a driver of lake C cycling and as a proxy for other external signals. © 2015 John Wiley & Sons Ltd.

Discrete Regularization for Calibration of Geologic Facies Against Dynamic Flow Data

NASA Astrophysics Data System (ADS)

Khaninezhad, Mohammad-Reza; Golmohammadi, Azarang; Jafarpour, Behnam

2018-04-01

Subsurface flow model calibration involves many more unknowns than measurements, leading to ill-posed problems with nonunique solutions. To alleviate nonuniqueness, the problem is regularized by constraining the solution space using prior knowledge. In certain sedimentary environments, such as fluvial systems, the contrast in hydraulic properties of different facies types tends to dominate the flow and transport behavior, making the effect of within facies heterogeneity less significant. Hence, flow model calibration in those formations reduces to delineating the spatial structure and connectivity of different lithofacies types and their boundaries. A major difficulty in calibrating such models is honoring the discrete, or piecewise constant, nature of facies distribution. The problem becomes more challenging when complex spatial connectivity patterns with higher-order statistics are involved. This paper introduces a novel formulation for calibration of complex geologic facies by imposing appropriate constraints to recover plausible solutions that honor the spatial connectivity and discreteness of facies models. To incorporate prior connectivity patterns, plausible geologic features are learned from available training models. This is achieved by learning spatial patterns from training data, e.g., k-SVD sparse learning or the traditional Principal Component Analysis. Discrete regularization is introduced as a penalty functions to impose solution discreteness while minimizing the mismatch between observed and predicted data. An efficient gradient-based alternating directions algorithm is combined with variable splitting to minimize the resulting regularized nonlinear least squares objective function. Numerical results show that imposing learned facies connectivity and discreteness as regularization functions leads to geologically consistent solutions that improve facies calibration quality.

Spatial and temporal drivers of wildfire occurrence in the context of rural development in northern Wisconsin, USA

Treesearch

Brian R Miranda; Brian R Sturtevant; Susan I Stewart; Roger B. Hammer

2012-01-01

Most drivers underlying wildfire are dynamic, but at different spatial and temporal scales. We quantified temporal and spatial trends in wildfire patterns over two spatial extents in northern Wisconsin to identify drivers and their change through time. We used spatial point pattern analysis to quantify the spatial pattern of wildfire occurrences, and linear regression...

Optical system

NASA Technical Reports Server (NTRS)

Breckinridge, J. B.; Page, N. A.; Shack, R. V.; Shannon, R. R. (Inventor)

1985-01-01

Disclosed is an otpical system used in a spacecraft to observe a remote surface and provide a spatial and spectral image of this surface. The optical system includes aspheric and spherical mirrors aligned to focus at a first focal plane an image of the surface, and a mirror at this first focal plane which reflects light back on to the spherical mirror. This spherical mirror collimates the light and directs it through a prism which disperses it. The dispersed light is then focused on an array of light responsive elements disposed at a second focal plane. The prism is designed such that it disperses light into components of different wavelengths, with the components of shorter wavelengths being dispersed more than the components of longer wavelengths to present at the second focal plane a distribution pattern in which preselected groupings of the components are dispersed over essentially equal spacing intervals.

A finite element model of the human head for auditory bone conduction simulation.

PubMed

Taschke, Henning; Hudde, Herbert

2006-01-01

In order to investigate the mechanisms of bone conduction, a finite element model of the human head was developed. The most important steps of the modelling process are described. The model was excited by means of percutaneously applied forces in order to get a deeper insight into the way the parts of the peripheral hearing organ and the surrounding tissue vibrate. The analysis is done based on the division of the bone conduction mechanisms into components. The frequency-dependent patterns of vibration of the components are analyzed. Furthermore, the model allows for the calculation of the contribution of each component to the overall bone-conducted sound. The components interact in a complicated way, which strongly depends on the nature of the excitation and the spatial region to which it is applied.

Gelatin-Based Laser Direct-Write Technique for the Precise Spatial Patterning of Cells

PubMed Central

Schiele, Nathan R.; Chrisey, Douglas B.

2011-01-01

Laser direct-writing provides a method to pattern living cells in vitro, to study various cell–cell interactions, and to build cellular constructs. However, the materials typically used may limit its long-term application. By utilizing gelatin coatings on the print ribbon and growth surface, we developed a new approach for laser cell printing that overcomes the limitations of Matrigel™. Gelatin is free of growth factors and extraneous matrix components that may interfere with cellular processes under investigation. Gelatin-based laser direct-write was able to successfully pattern human dermal fibroblasts with high post-transfer viability (91% ± 3%) and no observed double-strand DNA damage. As seen with atomic force microscopy, gelatin offers a unique benefit in that it is present temporarily to allow cell transfer, but melts and is removed with incubation to reveal the desired application-specific growth surface. This provides unobstructed cellular growth after printing. Monitoring cell location after transfer, we show that melting and removal of gelatin does not affect cellular placement; cells maintained registry within 5.6 ± 2.5 μm to the initial pattern. This study demonstrates the effectiveness of gelatin in laser direct-writing to create spatially precise cell patterns with the potential for applications in tissue engineering, stem cell, and cancer research. PMID:20849381

Low-dose cone-beam CT via raw counts domain low-signal correction schemes: Performance assessment and task-based parameter optimization (Part II. Task-based parameter optimization).

PubMed

Gomez-Cardona, Daniel; Hayes, John W; Zhang, Ran; Li, Ke; Cruz-Bastida, Juan Pablo; Chen, Guang-Hong

2018-05-01

Different low-signal correction (LSC) methods have been shown to efficiently reduce noise streaks and noise level in CT to provide acceptable images at low-radiation dose levels. These methods usually result in CT images with highly shift-variant and anisotropic spatial resolution and noise, which makes the parameter optimization process highly nontrivial. The purpose of this work was to develop a local task-based parameter optimization framework for LSC methods. Two well-known LSC methods, the adaptive trimmed mean (ATM) filter and the anisotropic diffusion (AD) filter, were used as examples to demonstrate how to use the task-based framework to optimize filter parameter selection. Two parameters, denoted by the set P, for each LSC method were included in the optimization problem. For the ATM filter, these parameters are the low- and high-signal threshold levels p l and p h ; for the AD filter, the parameters are the exponents δ and γ in the brightness gradient function. The detectability index d' under the non-prewhitening (NPW) mathematical observer model was selected as the metric for parameter optimization. The optimization problem was formulated as an unconstrained optimization problem that consisted of maximizing an objective function d'(P), where i and j correspond to the i-th imaging task and j-th spatial location, respectively. Since there is no explicit mathematical function to describe the dependence of d' on the set of parameters P for each LSC method, the optimization problem was solved via an experimentally measured d' map over a densely sampled parameter space. In this work, three high-contrast-high-frequency discrimination imaging tasks were defined to explore the parameter space of each of the LSC methods: a vertical bar pattern (task I), a horizontal bar pattern (task II), and a multidirectional feature (task III). Two spatial locations were considered for the analysis, a posterior region-of-interest (ROI) located within the noise streaks region and an anterior ROI, located further from the noise streaks region. Optimal results derived from the task-based detectability index metric were compared to other operating points in the parameter space with different noise and spatial resolution trade-offs. The optimal operating points determined through the d' metric depended on the interplay between the major spatial frequency components of each imaging task and the highly shift-variant and anisotropic noise and spatial resolution properties associated with each operating point in the LSC parameter space. This interplay influenced imaging performance the most when the major spatial frequency component of a given imaging task coincided with the direction of spatial resolution loss or with the dominant noise spatial frequency component; this was the case of imaging task II. The performance of imaging tasks I and III was influenced by this interplay in a smaller scale than imaging task II, since the major frequency component of task I was perpendicular to imaging task II, and because imaging task III did not have strong directional dependence. For both LSC methods, there was a strong dependence of the overall d' magnitude and shape of the contours on the spatial location within the phantom, particularly for imaging tasks II and III. The d' value obtained at the optimal operating point for each spatial location and imaging task was similar when comparing the LSC methods studied in this work. A local task-based detectability framework to optimize the selection of parameters for LSC methods was developed. The framework takes into account the potential shift-variant and anisotropic spatial resolution and noise properties to maximize the imaging performance of the CT system. Optimal parameters for a given LSC method depend strongly on the spatial location within the image object. © 2018 American Association of Physicists in Medicine.

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

2017-01-01

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

Flexural subsidence and basement tectonics of the Cretaceous Western Interior basin, United States

NASA Astrophysics Data System (ADS)

Pang, Ming; Nummedal, Dag

1995-02-01

The flexural subsidence history recorded in Cenomanian to early Campanian (97 to 80 Ma) strata in the Cretaceous U.S. Western Interior basin was studied with two-dimensional flexural backstripping techniques. Results indicate that the flexural subsidence resulting from thrust loading was superimposed on epeirogenic subsidence in the foreland basin. The flexural component exhibits significant spatial and temporal variations along both the strike and dip relative to the Sevier thrust belt. The greatest cumulative subsidence occurred in southwestern Wyoming and northern Utah. Concurrent subsidence in northwestern Montana and southern Utah was insignificant. Temporal trends in subsidence also show a distinct regional pattern. From the Cenomanian to late Turonian (97 to 90 Ma), subsidence rates were high in Utah and much lower in Wyoming and Montana. In contrast, during the Coniacian and Santonian (90 to 85 Ma) subsidence accelerated rapidly in Wyoming, increased slightly in Montana, and decreased in Utah. We suggest that these spatially and temporally varying subsidence patterns reflect the interplay of several geodynamic factors, including: (1) temporal and spatial variation in emplacement of the thrust loads, (2) segmentation of the basement into adjacent blocks with different rheological properties, (3) reactivation of basement fault trends, and (4) regional dynamic topographic effects.

Local and non-local deficits in amblyopia: acuity and spatial interactions.

PubMed

Bonneh, Yoram S; Sagi, Dov; Polat, Uri

2004-12-01

Amblyopic vision is thought to be limited by abnormal long-range spatial interactions, but their exact mode of action and relationship to the main amblyopic deficit in visual acuity is largely unknown. We studied this relationship in a group (N=59) of anisometropic (N=21) and strabismic (or combined, N=38) subjects, using (1) a single and multi-pattern (crowded) computerized static Tumbling-E test with scaled spacing of two pattern widths (TeVA), in addition to an optotype (ETDRS chart) acuity test (VA) and (2) contrast detection of Gabor patches with lateral flankers (lateral masking) along the horizontal and vertical axes as well as in collinear and parallel configurations. By correlating the different measures of visual acuity and contrast suppression, we found that (1) the VA of the strabismic subjects could be decomposed into two uncorrelated components measured in TeVA: acuity for isolated patterns and acuity reduction due to flanking patterns. The latter comprised over 60% of the VA magnitude, on the average and accounted for over 50% of its variance. In contrast, a slight reduction in acuity was found in the anisometropic subjects, and the acuity for a single pattern could account for 70% of the VA variance. (2) The lateral suppression (contrast threshold elevation) in a parallel configuration along the horizontal axis was correlated with the VA (R2=0.7), as well as with the crowding effect (TeVA elevation, R2=0.5) for the strabismic group. Some correlation with the VA was also found for the collinear configuration in the anisometropic group, but less suppression and no correlation were found for all the vertical configurations in all the groups. The results indicate the existence of a specific non-local component of the strabismic deficit, in addition to the local acuity deficit in all amblyopia types. This deficit might reflect long-range lateral inhibition, or alternatively, an inaccurate and scattered top-down attentional selection mechanism.

Decadal variability of precipitation over Western North America

USGS Publications Warehouse

Cayan, D.R.; Dettinger, M.D.; Diaz, Henry F.; Graham, N.E.

1998-01-01

Decadal (>7- yr period) variations of precipitation over western North America account for 20%-50% of the variance of annual precipitation. Spatially, the decadal variability is broken into several regional [O(1000 km)] components. These decadal variations are contributed by fluctuations in precipitation from seasons of the year that vary from region to region and that are not necessarily concentrated in the wettest season(s) alone. The precipitation variations are linked to various decadal atmospheric circulation and SST anomaly patterns where scales range from regional to global scales and that emphasize tropical or extratropical connections, depending upon which precipitation region is considered. Further, wet or dry decades are associated with changes in frequency of at least a few short-period circulation 'modes' such as the Pacific-North American pattern. Precipitation fluctuations over the southwestern United States and the Saskatchewan region of western Canada are associated with extensive shifts of sea level pressure and SST anomalies, suggesting that they are components of low-frequency precipitation variability from global-scale climate proceses. Consistent with the global scale of its pressure and SST connection, the Southwest decadal precipitation is aligned with opposing precipitation fluctuations in northern Africa.Decadal (>7-yr period) variations of precipitation over western North America account for 20%-50% of the variance of annual precipitation. Spatially, the decadal variability is broken into several regional [O(1000 km)] components. These decadal variations are contributed by fluctuations in precipitation from seasons of the year that vary from region to region and that are not necessarily concentrated in the wettest season(s) alone. The precipitation variations are linked to various decadal atmospheric circulation and SST anomaly patterns where scales range from regional to global scales and that emphasize tropical or extratropical connections, depending upon which precipitation region is considered. Further, wet or dry decades are associated with changes in frequency of at least a few short-period circulation `modes' such as the Pacific-North American pattern. Precipitation fluctuations over the southwestern United States and the Saskatchewan region of western Canada are associated with extensive shifts of sea level pressure and SST anomalies, suggesting that they are components of low-frequency precipitation variability from global-scale climate processes. Consistent with the global scale of its pressure and SST connection, the Southwest decadal precipitation is aligned with opposing precipitation fluctuations in northern Africa.

Time-alternating method based on single-sideband holography with half-zone-plate processing for the enlargement of viewing zones.

PubMed

Mishina, T; Okano, F; Yuyama, I

1999-06-10

The single-sideband method of holography, as is well known, cuts off beams that come from conjugate images for holograms produced in the Fraunhofer region and from objects with no phase components. The single-sideband method with half-zone-plate processing is also effective in the Fresnel region for beams from an object that has phase components. However, this method restricts the viewing zone to a narrow range. We propose a method to improve this restriction by time-alternating switching of hologram patterns and a spatial filter set on the focal plane of a reconstruction lens.

Spatial patterns of natural hazards mortality in the United States

PubMed Central

Borden, Kevin A; Cutter, Susan L

2008-01-01

Background Studies on natural hazard mortality are most often hazard-specific (e.g. floods, earthquakes, heat), event specific (e.g. Hurricane Katrina), or lack adequate temporal or geographic coverage. This makes it difficult to assess mortality from natural hazards in any systematic way. This paper examines the spatial patterns of natural hazard mortality at the county-level for the U.S. from 1970–2004 using a combination of geographical and epidemiological methods. Results Chronic everyday hazards such as severe weather (summer and winter) and heat account for the majority of natural hazard fatalities. The regions most prone to deaths from natural hazards are the South and intermountain west, but sub-regional county-level mortality patterns show more variability. There is a distinct urban/rural component to the county patterns as well as a coastal trend. Significant clusters of high mortality are in the lower Mississippi Valley, upper Great Plains, and Mountain West, with additional areas in west Texas, and the panhandle of Florida, Significant clusters of low mortality are in the Midwest and urbanized Northeast. Conclusion There is no consistent source of hazard mortality data, yet improvements in existing databases can produce quality data that can be incorporated into spatial epidemiological studies as demonstrated in this paper. It is important to view natural hazard mortality through a geographic lens so as to better inform the public living in such hazard prone areas, but more importantly to inform local emergency practitioners who must plan for and respond to disasters in their community. PMID:19091058

Spatial pattern of Baccharis platypoda shrub as determined by sex and life stages

NASA Astrophysics Data System (ADS)

Fonseca, Darliana da Costa; de Oliveira, Marcio Leles Romarco; Pereira, Israel Marinho; Gonzaga, Anne Priscila Dias; de Moura, Cristiane Coelho; Machado, Evandro Luiz Mendonça

2017-11-01

Spatial patterns of dioecious species can be determined by their nutritional requirements and intraspecific competition, apart from being a response to environmental heterogeneity. The aim of the study was to evaluate the spatial pattern of populations of a dioecious shrub reporting to sex and reproductive stage patterns of individuals. Sampling was carried out in three areas located in the meridional portion of Serra do Espinhaço, where in individuals of the studied species were mapped. The spatial pattern was determined through O-ring analysis and Ripley's K-function and the distribution of individuals' frequencies was verified through x2 test. Populations in two areas showed an aggregate spatial pattern tending towards random or uniform according to the observed scale. Male and female adults presented an aggregate pattern at smaller scales, while random and uniform patterns were verified above 20 m for individuals of both sexes of the areas A2 and A3. Young individuals presented an aggregate pattern in all areas and spatial independence in relation to adult individuals, especially female plants. The interactions between individuals of both genders presented spatial independence with respect to spatial distribution. Baccharis platypoda showed characteristics in accordance with the spatial distribution of savannic and dioecious species, whereas the population was aggregated tending towards random at greater spatial scales. Young individuals showed an aggregated pattern at different scales compared to adults, without positive association between them. Female and male adult individuals presented similar characteristics, confirming that adult individuals at greater scales are randomly distributed despite their distinct preferences for environments with moisture variation.

Analysis of Spatial Point Patterns in Nuclear Biology

PubMed Central

Weston, David J.; Adams, Niall M.; Russell, Richard A.; Stephens, David A.; Freemont, Paul S.

2012-01-01

There is considerable interest in cell biology in determining whether, and to what extent, the spatial arrangement of nuclear objects affects nuclear function. A common approach to address this issue involves analyzing a collection of images produced using some form of fluorescence microscopy. We assume that these images have been successfully pre-processed and a spatial point pattern representation of the objects of interest within the nuclear boundary is available. Typically in these scenarios, the number of objects per nucleus is low, which has consequences on the ability of standard analysis procedures to demonstrate the existence of spatial preference in the pattern. There are broadly two common approaches to look for structure in these spatial point patterns. First a spatial point pattern for each image is analyzed individually, or second a simple normalization is performed and the patterns are aggregated. In this paper we demonstrate using synthetic spatial point patterns drawn from predefined point processes how difficult it is to distinguish a pattern from complete spatial randomness using these techniques and hence how easy it is to miss interesting spatial preferences in the arrangement of nuclear objects. The impact of this problem is also illustrated on data related to the configuration of PML nuclear bodies in mammalian fibroblast cells. PMID:22615822

Tree invasion of a montane meadow complex: temporal trends, spatial patterns, and biotic interactions

Treesearch

Charles B. Halpern; Joseph A. Antos; Janine M. Rice; Ryan D. Haugo; Nicole L. Lang

2010-01-01

We combined spatial point pattern analysis, population age structures, and a time-series of stem maps to quantify spatial and temporal patterns of conifer invasion over a 200-yr period in three plots totaling 4 ha. In combination, spatial and temporal patterns of establishment suggest an invasion process shaped by biotic interactions, with facilitation promoting...

[Characteristics of temporal-spatial differentiation in landscape pattern vulnerability in Nansihu Lake wetland, China.

PubMed

Liang, Jia Xin; Li, Xin Ju

2018-02-01

With remote sensing images from 1985, 2000 Lantsat 5 TM and 2015 Lantsat 8 OLI as data sources, we tried to select the suitable research scale and examine the temporal-spatial diffe-rentiation with such scale in the Nansihu Lake wetland by using landscape pattern vulnerability index constructed by sensitivity index and adaptability index, and combined with space statistics such as semivariogram and spatial autocorrelation. The results showed that 1 km × 1 km equidistant grid was the suitable research scale, which could eliminate the influence of spatial heterogeneity induced by random factors. From 1985 to 2015, the landscape pattern vulnerability in the Nansihu Lake wetland deteriorated gradually. The high-risk area of landscape pattern vulnerability dramatically expanded with time. The spatial heterogeneity of landscape pattern vulnerability increased, and the influence of non-structural factors on landscape pattern vulnerability strengthened. Spatial variability affected by spatial autocorrelation slightly weakened. Landscape pattern vulnerability had strong general spatial positive correlation, with the significant form of spatial agglomeration. The positive spatial autocorrelation continued to increase and the phenomenon of spatial concentration was more and more obvious over time. The local autocorrelation mainly based on high-high accumulation zone and low-low accumulation zone had stronger spatial autocorrelation among neighboring space units. The high-high accumulation areas showed the strongest level of significance, and the significant level of low-low accumulation zone increased with time. Natural factors, such as temperature and precipitation, affected water-level and landscape distribution, and thus changed the landscape patterns vulnerability of Nansihu Lake wetland. The dominant driver for the deterioration of landscape patterns vulnerability was human activities, including social economy activity and policy system.

Neighborhood Landscape Spatial Patterns and Land Surface Temperature: An Empirical Study on Single-Family Residential Areas in Austin, Texas.

PubMed

Kim, Jun-Hyun; Gu, Donghwan; Sohn, Wonmin; Kil, Sung-Ho; Kim, Hwanyong; Lee, Dong-Kun

2016-09-02

Rapid urbanization has accelerated land use and land cover changes, and generated the urban heat island effect (UHI). Previous studies have reported positive effects of neighborhood landscapes on mitigating urban surface temperatures. However, the influence of neighborhood landscape spatial patterns on enhancing cooling effects has not yet been fully investigated. The main objective of this study was to assess the relationships between neighborhood landscape spatial patterns and land surface temperatures (LST) by using multi-regression models considering spatial autocorrelation issues. To measure the influence of neighborhood landscape spatial patterns on LST, this study analyzed neighborhood environments of 15,862 single-family houses in Austin, Texas, USA. Using aerial photos, geographic information systems (GIS), and remote sensing, FRAGSTATS was employed to calculate values of several landscape indices used to measure neighborhood landscape spatial patterns. After controlling for the spatial autocorrelation effect, results showed that larger and better-connected landscape spatial patterns were positively correlated with lower LST values in neighborhoods, while more fragmented and isolated neighborhood landscape patterns were negatively related to the reduction of LST.

Neighborhood Landscape Spatial Patterns and Land Surface Temperature: An Empirical Study on Single-Family Residential Areas in Austin, Texas

PubMed Central

Kim, Jun-Hyun; Gu, Donghwan; Sohn, Wonmin; Kil, Sung-Ho; Kim, Hwanyong; Lee, Dong-Kun

2016-01-01

Rapid urbanization has accelerated land use and land cover changes, and generated the urban heat island effect (UHI). Previous studies have reported positive effects of neighborhood landscapes on mitigating urban surface temperatures. However, the influence of neighborhood landscape spatial patterns on enhancing cooling effects has not yet been fully investigated. The main objective of this study was to assess the relationships between neighborhood landscape spatial patterns and land surface temperatures (LST) by using multi-regression models considering spatial autocorrelation issues. To measure the influence of neighborhood landscape spatial patterns on LST, this study analyzed neighborhood environments of 15,862 single-family houses in Austin, Texas, USA. Using aerial photos, geographic information systems (GIS), and remote sensing, FRAGSTATS was employed to calculate values of several landscape indices used to measure neighborhood landscape spatial patterns. After controlling for the spatial autocorrelation effect, results showed that larger and better-connected landscape spatial patterns were positively correlated with lower LST values in neighborhoods, while more fragmented and isolated neighborhood landscape patterns were negatively related to the reduction of LST. PMID:27598186

Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks

USGS Publications Warehouse

Sutherland, Christopher; Fuller, Angela K.; Royle, J. Andrew

2015-01-01

The ecological distance SCR model uses spatially indexed capture-recapture data to estimate how activity patterns are influenced by landscape structure. As well as reducing bias in estimates of abundance, this approach provides biologically realistic representations of home range geometry, and direct information about species-landscape interactions. The incorporation of both structural (landscape) and functional (movement) components of connectivity provides a direct measure of species-specific landscape connectivity.

EGFR Activation by Spatially Restricted Ligands

DTIC Science & Technology

2006-06-01

the level of ligand production, that result in human breast cancer. We have integrated genetic and biochemical methods to study (1) the effects of a...and spindle-B encode components of the RAD52 DNA repair pathway and affect meiosis and patterning in Drosophila oogenesis. Genes Dev 12, 2711-2723...findings contained in this report are those of the author(s) and should not be construed as an official Department of the Army position, policy or decision

Graphic design of pinhole cameras

NASA Technical Reports Server (NTRS)

Edwards, H. B.; Chu, W. P.

1979-01-01

The paper describes a graphic technique for the analysis and optimization of pinhole size and focal length. The technique is based on the use of the transfer function of optical elements described by Scott (1959) to construct the transfer function of a circular pinhole camera. This transfer function is the response of a component or system to a pattern of lines having a sinusoidally varying radiance at varying spatial frequencies. Some specific examples of graphic design are presented.

Pekong, the symbol identity of Chinese at Pekan Labuhan Medan Indonesia

NASA Astrophysics Data System (ADS)

Siagian, M.

2018-02-01

Urban architecture has always been combined by physical and non-physical components. The physical is formed by spatial pattern, space and history. The non physical is formed by social and cultural life of the community. The combination of that space would give the meaning as a place for the people that use it. Pekong has existed since 1890 in the area of Pekan Labuhan. The presence of two Pekongs in this area gives the symbol for distribution patterns of Chinese residential and community in Pekan Labuhan district. Symbolizing the Pekongs is sourced from being able to shape and influence the components such as the market, shophouses, and houses. Beside that the Pekongs also identify of districts and social influence of the community. The component activities enliven Pekongs make spaces for Pekongs grow to become a magnificent buildings in the comunity settlement. The aim of this research is to examine and describe the Pekong that has became the identity and attraction to the area. By using the qualitative method this research found that the Pekongs are the important buildings in identifying of the district.

Community-wide spatial and temporal discordances of seed-seedling shadows in a tropical rainforest.

PubMed

Rother, Débora Cristina; Pizo, Marco Aurélio; Siqueira, Tadeu; Rodrigues, Ricardo Ribeiro; Jordano, Pedro

2015-01-01

Several factors decrease plant survival throughout their lifecycles. Among them, seed dispersal limitation may play a major role by resulting in highly aggregated (contagious) seed and seedling distributions entailing increased mortality. The arrival of seeds, furthermore, may not match suitable environments for seed survival and, consequently, for seedling establishment. In this study, we investigated spatio-temporal patterns of seed and seedling distribution in contrasting microhabitats (bamboo and non-bamboo stands) from the Brazilian Atlantic Forest. Spatial distribution patterns, spatial concordance between seed rain and seedling recruitment between subsequent years in two fruiting seasons (2004-2005 and 2007-2009), and the relation between seeds and seedlings with environmental factors were examined within a spatially-explicit framework. Density and species richness of both seeds and seedlings were randomly distributed in non-bamboo stands, but showed significant clustering in bamboo stands. Seed and seedling distributions showed across-year inconsistency, suggesting a marked spatial decoupling of the seed and seedling stages. Generalized linear mixed effects models indicated that only seed density and seed species richness differed between stand types while accounting for variation in soil characteristics. Our analyses provide evidence of marked recruitment limitation as a result of the interplay between biotic and abiotic factors. Because bamboo stands promote heterogeneity in the forest, they are important components of the landscape. However, at high densities, bamboos may limit recruitment for the plant community by imposing marked discordances of seed arrival and early seedling recruitment.

Spatial synchrony of malaria outbreaks in a highland region of Ethiopia.

PubMed

Wimberly, Michael C; Midekisa, Alemayehu; Semuniguse, Paulos; Teka, Hiwot; Henebry, Geoffrey M; Chuang, Ting-Wu; Senay, Gabriel B

2012-10-01

To understand the drivers and consequences of malaria in epidemic-prone regions, it is important to know whether epidemics emerge independently in different areas as a consequence of local contingencies, or whether they are synchronised across larger regions as a result of climatic fluctuations and other broad-scale drivers. To address this question, we collected historical malaria surveillance data for the Amhara region of Ethiopia and analysed them to assess the consistency of various indicators of malaria risk and determine the dominant spatial and temporal patterns of malaria within the region. We collected data from a total of 49 districts from 1999-2010. Data availability was better for more recent years and more data were available for clinically diagnosed outpatient malaria cases than confirmed malaria cases. Temporal patterns of outpatient malaria case counts were correlated with the proportion of outpatients diagnosed with malaria and confirmed malaria case counts. The proportion of outpatients diagnosed with malaria was spatially clustered, and these cluster locations were generally consistent from year to year. Outpatient malaria cases exhibited spatial synchrony at distances up to 300 km, supporting the hypothesis that regional climatic variability is an important driver of epidemics. Our results suggest that decomposing malaria risk into separate spatial and temporal components may be an effective strategy for modelling and forecasting malaria risk across large areas. They also emphasise both the value and limitations of working with historical surveillance datasets and highlight the importance of enhancing existing surveillance efforts. © 2012 Blackwell Publishing Ltd.

Parameter Estimation for a Model of Space-Time Rainfall

NASA Astrophysics Data System (ADS)

Smith, James A.; Karr, Alan F.

1985-08-01

In this paper, parameter estimation procedures, based on data from a network of rainfall gages, are developed for a class of space-time rainfall models. The models, which are designed to represent the spatial distribution of daily rainfall, have three components, one that governs the temporal occurrence of storms, a second that distributes rain cells spatially for a given storm, and a third that determines the rainfall pattern within a rain cell. Maximum likelihood and method of moments procedures are developed. We illustrate that limitations on model structure are imposed by restricting data sources to rain gage networks. The estimation procedures are applied to a 240-mi2 (621 km2) catchment in the Potomac River basin.

A finite element method based microwave heat transfer modeling of frozen multi-component foods

NASA Astrophysics Data System (ADS)

Pitchai, Krishnamoorthy

Microwave heating is fast and convenient, but is highly non-uniform. Non-uniform heating in microwave cooking affects not only food quality but also food safety. Most food industries develop microwavable food products based on "cook-and-look" approach. This approach is time-consuming, labor intensive and expensive and may not result in optimal food product design that assures food safety and quality. Design of microwavable food can be realized through a simulation model which describes the physical mechanisms of microwave heating in mathematical expressions. The objective of this study was to develop a microwave heat transfer model to predict spatial and temporal profiles of various heterogeneous foods such as multi-component meal (chicken nuggets and mashed potato), multi-component and multi-layered meal (lasagna), and multi-layered food with active packages (pizza) during microwave heating. A microwave heat transfer model was developed by solving electromagnetic and heat transfer equations using finite element method in commercially available COMSOL Multiphysics v4.4 software. The microwave heat transfer model included detailed geometry of the cavity, phase change, and rotation of the food on the turntable. The predicted spatial surface temperature patterns and temporal profiles were validated against the experimental temperature profiles obtained using a thermal imaging camera and fiber-optic sensors. The predicted spatial surface temperature profile of different multi-component foods was in good agreement with the corresponding experimental profiles in terms of hot and cold spot patterns. The root mean square error values of temporal profiles ranged from 5.8 °C to 26.2 °C in chicken nuggets as compared 4.3 °C to 4.7 °C in mashed potatoes. In frozen lasagna, root mean square error values at six locations ranged from 6.6 °C to 20.0 °C for 6 min of heating. A microwave heat transfer model was developed to include susceptor assisted microwave heating of a frozen pizza. The root mean square error values of transient temperature profiles of five locations ranged from 5.0 °C to 12.6 °C. A methodology was developed to incorporate electromagnetic frequency spectrum in the coupled electromagnetic and heat transfer model. Implementing the electromagnetic frequency spectrum in the simulation improved the accuracy of temperature field pattern and transient temperature profile as compared to mono-chromatic frequency of 2.45 GHz. The bulk moisture diffusion coefficient of cooked pasta was calculated as a function of temperature at a constant water activity using desorption isotherms.

Multiple Spatial Coherence Resonances and Spatial Patterns in a Noise-Driven Heterogeneous Neuronal Network

NASA Astrophysics Data System (ADS)

Li, Yu-Ye; Ding, Xue-Li

2014-12-01

Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns.

RAPD variation and population genetic structure of Physalaemus cuvieri (Anura: Leptodactylidae) in Central Brazil.

PubMed

Telles, Mariana Pires de Campos; Bastos, Rogério Pereira; Soares, Thannya Nascimento; Resende, Lucileide Vilela; Diniz-Filho, José Alexandre Felizola

2006-01-01

Studies about the organization of the genetic variability and population structure in natural populations are used either to understand microevolutionary processes or the effects of isolation by human-inducted landscape modifications. In this paper, we analyzed patterns of genetic population structure using 126 RAPD loci scored for 214 individuals of Physalaemus cuvieri, sampled from 18 local populations. Around 97% of these loci were polymorphic. The among-population variation component (Phi(ST)) obtained by AMOVA was equal to 0.101 and theta B obtained using a Bayesian approach for dominant markers was 0.103. Genetic divergence, analyzed by Mantel spatial correlogram, revealed only a short-distance significant correlation between genetic and geographic distances. This is expected if low levels of population differentiation, due to high abundance buffering the effect of stochastic processes, are combined with low spatially restricted gene flow. Although this may be consistent with the current knowledge of species' biology, the spatial distribution of local populations observed in this study also suggest that, at least in part, recent human occupation and habitat fragmentation may also explain part of the interpopulational component of the genetic variation.

Spatial Patterns of NLCD Land Cover Change Thematic Accuracy (2001 - 2011)

EPA Science Inventory

Research on spatial non-stationarity of land cover classification accuracy has been ongoing for over two decades. We extend the understanding of thematic map accuracy spatial patterns by: 1) quantifying spatial patterns of map-reference agreement for class-specific land cover c...

Recurrence quantification analysis applied to spatiotemporal pattern analysis in high-density mapping of human atrial fibrillation.

PubMed

Zeemering, Stef; Bonizzi, Pietro; Maesen, Bart; Peeters, Ralf; Schotten, Ulrich

2015-01-01

Spatiotemporal complexity of atrial fibrillation (AF) patterns is often quantified by annotated intracardiac contact mapping. We introduce a new approach that applies recurrence plot (RP) construction followed by recurrence quantification analysis (RQA) to epicardial atrial electrograms, recorded with a high-density grid of electrodes. In 32 patients with no history of AF (aAF, n=11), paroxysmal AF (PAF, n=12) and persistent AF (persAF, n=9), RPs were constructed using a phase space electrogram embedding dimension equal to the estimated AF cycle length. Spatial information was incorporated by 1) averaging the recurrence over all electrodes, and 2) by applying principal component analysis (PCA) to the matrix of embedded electrograms and selecting the first principal component as a representation of spatial diversity. Standard RQA parameters were computed on the constructed RPs and correlated to the number of fibrillation waves per AF cycle (NW). Averaged RP RQA parameters showed no correlation with NW. Correlations improved when applying PCA, with maximum correlation achieved between RP threshold and NW (RR1%, r=0.68, p <; 0.001) and RP determinism (DET, r=-0.64, p <; 0.001). All studied RQA parameters based on the PCA RP were able to discriminate between persAF and aAF/PAF (DET persAF 0.40 ± 0.11 vs. 0.59 ± 0.14/0.62 ± 0.16, p <; 0.01). RP construction and RQA combined with PCA provide a quick and reliable tool to visualize dynamical behaviour and to assess the complexity of contact mapping patterns in AF.

Sensitivity of CONUS Summer Rainfall to the Selection of Cumulus Parameterization Schemes in NU-WRF Seasonal Simulations

NASA Technical Reports Server (NTRS)

Iguchi, Takamichi; Tao, Wei-Kuo; Wu, Di; Peters-Lidard, Christa; Santanello, Joseph A.; Kemp, Eric; Tian, Yudong; Case, Jonathan; Wang, Weile; Ferraro, Robert;

Spatial patterns of development drive water use

USGS Publications Warehouse

Sanchez, G.M.; Smith, J.W.; Terando, Adam J.; Sun, G.; Meentemeyer, R.K.

2018-01-01

Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non‐spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio‐economic and environmental variables and two water use variables: a) domestic water use, and b) total development‐related water use (a combination of public supply, domestic self‐supply and industrial self‐supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio‐economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water‐efficient land use planning.

Spatial Patterns of Development Drive Water Use

NASA Astrophysics Data System (ADS)

Sanchez, G. M.; Smith, J. W.; Terando, A.; Sun, G.; Meentemeyer, R. K.

2018-03-01

Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non-spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio-economic and environmental variables and two water use variables: a) domestic water use, and b) total development-related water use (a combination of public supply, domestic self-supply and industrial self-supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio-economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water-efficient land use planning.

DNA concentration modulation on supported lipid bilayers switched by surface acoustic waves.

PubMed

Hennig, Martin; Wolff, Manuel; Neumann, Jürgen; Wixforth, Achim; Schneider, Matthias F; Rädler, Joachim O

2011-12-20

Spatially addressable arrays of molecules embedded in or anchored to supported lipid bilayers are important for on-chip screening and binding assays; however, methods to sort or accumulate components in a fluid membrane on demand are still limited. Here we apply in-plane surface acoustic shear waves (SAWs) to laterally accumulate double-stranded DNA segments electrostatically bound to a cationic supported lipid bilayer. The fluorescently labeled DNA segments are found to segregate into stripe patterns with a spatial frequency corresponding to the periodicity of the standing SAW wave (~10 μm). The DNA molecules are accumulated 10-fold in the regions of SAW antinodes. The superposition of two orthogonal sets of SAW sources creates checkerboard like arrays of DNA demonstrating the potential to generate arrayed fields dynamically. The pattern relaxation time of 0.58 s, which is independent of the segment length, indicates a sorting and relaxation mechanism dominated by lipid diffusion rather than DNA self-diffusion. © 2011 American Chemical Society

Profiles of cognitive dysfunction in chronic amphetamine and heroin abusers.

PubMed

Ornstein, T J; Iddon, J L; Baldacchino, A M; Sahakian, B J; London, M; Everitt, B J; Robbins, T W

2000-08-01

Groups of subjects whose primary drug of abuse was amphetamine or heroin were compared, together with age- and IQ-matched control subjects. The study consisted of a neuropsychological test battery which included both conventional tests and also computerised tests of recognition memory, spatial working memory, planning, sequence generation, visual discrimination learning, and attentional set-shifting. Many of these tests have previously been shown to be sensitive to cortical damage (including selective lesions of the temporal or frontal lobes) and to cognitive deficits in dementia, basal ganglia disease, and neuropsychiatric disorder. Qualitative differences, as well as some commonalities, were found in the profile of cognitive impairment between the two groups. The chronic amphetamine abusers were significantly impaired in performance on the extra-dimensional shift task (a core component of the Wisconsin Card Sort Test) whereas in contrast, the heroin abusers were impaired in learning the normally easier intra-dimensional shift component. Both groups were impaired in some of tests of spatial working memory. However, the amphetamine group, unlike the heroin group, were not deficient in an index of strategic performance on this test. The heroin group failed to show significant improvement between two blocks of a sequence generation task after training and additionally exhibited more perseverative behavior on this task. The two groups were profoundly, but equivalently impaired on a test of pattern recognition memory sensitive to temporal lobe dysfunction. These results indicate that chronic drug use may lead to distinct patterns of cognitive impairment that may be associated with dysfunction of different components of cortico-striatal circuitry.

Gaussian process based independent analysis for temporal source separation in fMRI.

PubMed

Hald, Ditte Høvenhoff; Henao, Ricardo; Winther, Ole

2017-05-15

Functional Magnetic Resonance Imaging (fMRI) gives us a unique insight into the processes of the brain, and opens up for analyzing the functional activation patterns of the underlying sources. Task-inferred supervised learning with restrictive assumptions in the regression set-up, restricts the exploratory nature of the analysis. Fully unsupervised independent component analysis (ICA) algorithms, on the other hand, can struggle to detect clear classifiable components on single-subject data. We attribute this shortcoming to inadequate modeling of the fMRI source signals by failing to incorporate its temporal nature. fMRI source signals, biological stimuli and non-stimuli-related artifacts are all smooth over a time-scale compatible with the sampling time (TR). We therefore propose Gaussian process ICA (GPICA), which facilitates temporal dependency by the use of Gaussian process source priors. On two fMRI data sets with different sampling frequency, we show that the GPICA-inferred temporal components and associated spatial maps allow for a more definite interpretation than standard temporal ICA methods. The temporal structures of the sources are controlled by the covariance of the Gaussian process, specified by a kernel function with an interpretable and controllable temporal length scale parameter. We propose a hierarchical model specification, considering both instantaneous and convolutive mixing, and we infer source spatial maps, temporal patterns and temporal length scale parameters by Markov Chain Monte Carlo. A companion implementation made as a plug-in for SPM can be downloaded from https://github.com/dittehald/GPICA. Copyright © 2017 Elsevier Inc. All rights reserved.

Spatial/Temporal Variations of Crime: A Routine Activity Theory Perspective.

PubMed

de Melo, Silas Nogueira; Pereira, Débora V S; Andresen, Martin A; Matias, Lindon Fonseca

2018-05-01

Temporal and spatial patterns of crime in Campinas, Brazil, are analyzed considering the relevance of routine activity theory in a Latin American context. We use geo-referenced criminal event data, 2010-2013, analyzing spatial patterns using census tracts and temporal patterns considering seasons, months, days, and hours. Our analyses include difference in means tests, count-based regression models, and Kulldorff's scan test. We find that crime in Campinas, Brazil, exhibits both temporal and spatial-temporal patterns. However, the presence of these patterns at the different temporal scales varies by crime type. Specifically, not all crime types have statistically significant temporal patterns at all scales of analysis. As such, routine activity theory works well to explain temporal and spatial-temporal patterns of crime in Campinas, Brazil. However, local knowledge of Brazilian culture is necessary for understanding a portion of these crime patterns.

Sex and strategy use matters for pattern separation, adult neurogenesis, and immediate early gene expression in the hippocampus.

PubMed

Yagi, Shunya; Chow, Carmen; Lieblich, Stephanie E; Galea, Liisa A M

2016-01-01

Adult neurogenesis in the dentate gyrus (DG) plays a crucial role for pattern separation, and there are sex differences in the regulation of neurogenesis. Although sex differences, favoring males, in spatial navigation have been reported, it is not known whether there are sex differences in pattern separation. The current study was designed to determine whether there are sex differences in the ability for separating similar or distinct patterns, learning strategy choice, adult neurogenesis, and immediate early gene (IEG) expression in the DG in response to pattern separation training. Male and female Sprague-Dawley rats received a single injection of the DNA synthesis marker, bromodeoxyuridine (BrdU), and were tested for the ability of separating spatial patterns in a spatial pattern separation version of delayed nonmatching to place task using the eight-arm radial arm maze. Twenty-seven days following BrdU injection, rats received a probe trial to determine whether they were idiothetic or spatial strategy users. We found that male spatial strategy users outperformed female spatial strategy users only when separating similar, but not distinct, patterns. Furthermore, male spatial strategy users had greater neurogenesis in response to pattern separation training than all other groups. Interestingly, neurogenesis was positively correlated with performance on similar pattern trials during pattern separation in female spatial strategy users but negatively correlated with performance in male idiothetic strategy users. These results suggest that the survival of new neurons may play an important positive role for pattern separation of similar patterns in females. Furthermore, we found sex and strategy differences in IEG expression in the CA1 and CA3 regions in response to pattern separation. These findings emphasize the importance of studying biological sex on hippocampal function and neural plasticity. © 2015 Wiley Periodicals, Inc.

Ecoregions and ecodistricts: Ecological regionalizations for the Netherlands' environmental policy

NASA Astrophysics Data System (ADS)

Klijn, Frans; de Waal, Rein W.; Oude Voshaar, Jan H.

1995-11-01

For communicating data on the state of the environment to policy makers, various integrative frameworks are used, including regional integration. For this kind of integration we have developed two related ecological regionalizations, ecoregions and ecodistricts, which are two levels in a series of classifications for hierarchically nested ecosystems at different spatial scale levels. We explain the compilation of the maps from existing geographical data, demonstrating the relatively holistic, a priori integrated approach. The resulting maps are submitted to discriminant analysis to test the consistancy of the use of mapping characteristics, using data on individual abiotic ecosystem components from a national database on a 1-km2 grid. This reveals that the spatial patterns of soil, groundwater, and geomorphology correspond with the ecoregion and ecodistrict maps. Differences between the original maps and maps formed by automatically reclassifying 1-km2 cells with these discriminant components are found to be few. These differences are discussed against the background of the principal dilemma between deductive, a priori integrated, and inductive, a posteriori, classification.

Evaluation of LANDSAT-4 Thematic Mapper Data as Applied to Geologic Exploration: Summary of Results. [Death Valley, California, Cement-Velma, Oklahoma; Big Horn and Wind River Basins, Wyoming; Spanish Peaks, Colorado; and the Four Corners area (Paradox Basin of Utah and Colorado)

NASA Technical Reports Server (NTRS)

Dykstra, J. D.; Sheffield, C. A.; Everett, J. R.

1984-01-01

As with any tool applied to geologic exploration, maximum value results from the innovative integration of optimally processed LANDSAT-4 data with existing pertinent information and perceptive geologic thinking. The synoptic view of the satellite images and the relatively high resolution of the data permits recognization of regional tectonic patterns and their detailed mapping. The refined spatial and spectral characteristics and digital nature surface alterations associated with hydrothermal activity and microseepage of hydrocarbons. In general, as vegetation and soil cover increase, the value of spectral components of TM data decreases with respect to the value of the spatial component of the data. This observation reinforces the experience from working with MSS data that digital processing must be optimized both for the area and for the application.

Virtual Human Analogs to Rodent Spatial Pattern Separation and Completion Memory Tasks

ERIC Educational Resources Information Center

Paleja, Meera; Girard, Todd A.; Christensen, Bruce K.

2011-01-01

Spatial pattern separation (SPS) and spatial pattern completion (SPC) have played an increasingly important role in computational and rodent literatures as processes underlying associative memory. SPS and SPC are complementary processes, allowing the formation of unique representations and the reconstruction of complete spatial environments based…

Using Spatial Multiple Regression to Identify Intrinsic Connectivity Networks Involved in Working Memory Performance

PubMed Central

Gordon, Evan M.; Stollstorff, Melanie; Vaidya, Chandan J.

2012-01-01

Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship. PMID:21761505

Spatial Variability of Sources and Mixing State of Atmospheric Particles in a Metropolitan Area.

PubMed

Ye, Qing; Gu, Peishi; Li, Hugh Z; Robinson, Ellis S; Lipsky, Eric; Kaltsonoudis, Christos; Lee, Alex K Y; Apte, Joshua S; Robinson, Allen L; Sullivan, Ryan C; Presto, Albert A; Donahue, Neil M

2018-05-30

Characterizing intracity variations of atmospheric particulate matter has mostly relied on fixed-site monitoring and quantifying variability in terms of different bulk aerosol species. In this study, we performed ground-based mobile measurements using a single-particle mass spectrometer to study spatial patterns of source-specific particles and the evolution of particle mixing state in 21 areas in the metropolitan area of Pittsburgh, PA. We selected sampling areas based on traffic density and restaurant density with each area ranging from 0.2 to 2 km 2 . Organics dominate particle composition in all of the areas we sampled while the sources of organics differ. The contribution of particles from traffic and restaurant cooking varies greatly on the neighborhood scale. We also investigate how primary and aged components in particles mix across the urban scale. Lastly we quantify and map the particle mixing state for all areas we sampled and discuss the overall pattern of mixing state evolution and its implications. We find that in the upwind and downwind of the urban areas, particles are more internally mixed while in the city center, particle mixing state shows large spatial heterogeneity that is mostly driven by emissions. This study is to our knowledge, the first study to perform fine spatial scale mapping of particle mixing state using ground-based mobile measurement and single-particle mass spectrometry.

Spatial drought reconstructions for central High Asia based on tree rings

NASA Astrophysics Data System (ADS)

Fang, Keyan; Davi, Nicole; Gou, Xiaohua; Chen, Fahu; Cook, Edward; Li, Jinbao; D'Arrigo, Rosanne

2010-11-01

Spatial reconstructions of drought for central High Asia based on a tree-ring network are presented. Drought patterns for central High Asia are classified into western and eastern modes of variability. Tree-ring based reconstructions of the Palmer drought severity index (PDSI) are presented for both the western central High Asia drought mode (1587-2005), and for the eastern central High Asia mode (1660-2005). Both reconstructions, generated using a principal component regression method, show an increased variability in recent decades. The wettest epoch for both reconstructions occurred from the 1940s to the 1950s. The most extreme reconstructed drought for western central High Asia was from the 1640s to the 1650s, coinciding with the collapse of the Chinese Ming Dynasty. The eastern central High Asia reconstruction has shown a distinct tendency towards drier conditions since the 1980s. Our spatial reconstructions agree well with previous reconstructions that fall within each mode, while there is no significant correlation between the two spatial reconstructions.

The combined effects of exogenous and endogenous variability on the spatial distribution of ant communities in a forested ecosystem (Hymenoptera: Formicidae).

PubMed

Yitbarek, Senay; Vandermeer, John H; Allen, David

2011-10-01

Spatial patterns observed in ecosystems have traditionally been attributed to exogenous processes. Recently, ecologists have found that endogenous processes also have the potential to create spatial patterns. Yet, relatively few studies have attempted to examine the combined effects of exogenous and endogenous processes on the distribution of organisms across spatial and temporal scales. Here we aim to do this, by investigating whether spatial patterns of under-story tree species at a large spatial scale (18 ha) influences the spatial patterns of ground foraging ant species at a much smaller spatial scale (20 m by 20 m). At the regional scale, exogenous processes (under-story tree community) had a strong effect on the spatial patterns in the ground-foraging ant community. We found significantly more Camponotus noveboracensis, Formica subsericae, and Lasius alienus species in black cherry (Prunis serotine Ehrh.) habitats. In witch-hazel (Hamamelis virginiana L.) habitats, we similarly found significantly more Myrmica americana, Formica fusca, and Formica subsericae. At smaller spatial scales, we observed the emergence of mosaic ant patches changing rapidly in space and time. Our study reveals that spatial patterns are the result of both exogenous and endogenous forces, operating at distinct scales.

Parallel ICA of FDG-PET and PiB-PET in three conditions with underlying Alzheimer's pathology

PubMed Central

Laforce, Robert; Tosun, Duygu; Ghosh, Pia; Lehmann, Manja; Madison, Cindee M.; Weiner, Michael W.; Miller, Bruce L.; Jagust, William J.; Rabinovici, Gil D.

2014-01-01

The relationships between clinical phenotype, β-amyloid (Aβ) deposition and neurodegeneration in Alzheimer's disease (AD) are incompletely understood yet have important ramifications for future therapy. The goal of this study was to utilize multimodality positron emission tomography (PET) data from a clinically heterogeneous population of patients with probable AD in order to: (1) identify spatial patterns of Aβ deposition measured by (11C)-labeled Pittsburgh Compound B (PiB-PET) and glucose metabolism measured by FDG-PET that correlate with specific clinical presentation and (2) explore associations between spatial patterns of Aβ deposition and glucose metabolism across the AD population. We included all patients meeting the criteria for probable AD (NIA–AA) who had undergone MRI, PiB and FDG-PET at our center (N = 46, mean age 63.0 ± 7.7, Mini-Mental State Examination 22.0 ± 4.8). Patients were subclassified based on their cognitive profiles into an amnestic/dysexecutive group (AD-memory; n = 27), a language-predominant group (AD-language; n = 10) and a visuospatial-predominant group (AD-visuospatial; n = 9). All patients were required to have evidence of amyloid deposition on PiB-PET. To capture the spatial distribution of Aβ deposition and glucose metabolism, we employed parallel independent component analysis (pICA), a method that enables joint analyses of multimodal imaging data. The relationships between PET components and clinical group were examined using a Receiver Operator Characteristic approach, including age, gender, education and apolipoprotein E ε4 allele carrier status as covariates. Results of the first set of analyses independently examining the relationship between components from each modality and clinical group showed three significant components for FDG: a left inferior frontal and temporoparietal component associated with AD-language (area under the curve [AUC] 0.82, p = 0.011), and two components associated with AD-visuospatial (bilateral occipito-parieto-temporal [AUC 0.85, p = 0.009] and right posterior cingulate cortex [PCC]/precuneus and right lateral parietal [AUC 0.69, p = 0.045]). The AD-memory associated component included predominantly bilateral inferior frontal, cuneus and inferior temporal, and right inferior parietal hypometabolism but did not reach significance (AUC 0.65, p = 0.062). None of the PiB components correlated with clinical group. Joint analysis of PiB and FDG with pICA revealed a correlated component pair, in which increased frontal and decreased PCC/precuneus PiB correlated with decreased FDG in the frontal, occipital and temporal regions (partial r = 0.75, p < 0.0001). Using multivariate data analysis, this study reinforced the notion that clinical phenotype in AD is tightly linked to patterns of glucose hypometabolism but not amyloid deposition. These findings are strikingly similar to those of univariate paradigms and provide additional support in favor of specific involvement of the language network, higher-order visual network, and default mode network in clinical variants of AD. The inverse relationship between Aβ deposition and glucose metabolism in partially overlapping brain regions suggests that Aβ may exert both local and remote effects on brain metabolism. Applying multivariate approaches such as pICA to multimodal imaging data is a promising approach for unraveling the complex relationships between different elements of AD pathophysiology. PMID:24818077

Scaling biodiversity responses to hydrological regimes.

PubMed

Rolls, Robert J; Heino, Jani; Ryder, Darren S; Chessman, Bruce C; Growns, Ivor O; Thompson, Ross M; Gido, Keith B

2018-05-01

Of all ecosystems, freshwaters support the most dynamic and highly concentrated biodiversity on Earth. These attributes of freshwater biodiversity along with increasing demand for water mean that these systems serve as significant models to understand drivers of global biodiversity change. Freshwater biodiversity changes are often attributed to hydrological alteration by water-resource development and climate change owing to the role of the hydrological regime of rivers, wetlands and floodplains affecting patterns of biodiversity. However, a major gap remains in conceptualising how the hydrological regime determines patterns in biodiversity's multiple spatial components and facets (taxonomic, functional and phylogenetic). We synthesised primary evidence of freshwater biodiversity responses to natural hydrological regimes to determine how distinct ecohydrological mechanisms affect freshwater biodiversity at local, landscape and regional spatial scales. Hydrological connectivity influences local and landscape biodiversity, yet responses vary depending on spatial scale. Biodiversity at local scales is generally positively associated with increasing connectivity whereas landscape-scale biodiversity is greater with increasing fragmentation among locations. The effects of hydrological disturbance on freshwater biodiversity are variable at separate spatial scales and depend on disturbance frequency and history and organism characteristics. The role of hydrology in determining habitat for freshwater biodiversity also depends on spatial scaling. At local scales, persistence, stability and size of habitat each contribute to patterns of freshwater biodiversity yet the responses are variable across the organism groups that constitute overall freshwater biodiversity. We present a conceptual model to unite the effects of different ecohydrological mechanisms on freshwater biodiversity across spatial scales, and develop four principles for applying a multi-scaled understanding of freshwater biodiversity responses to hydrological regimes. The protection and restoration of freshwater biodiversity is both a fundamental justification and a central goal of environmental water allocation worldwide. Clearer integration of concepts of spatial scaling in the context of understanding impacts of hydrological regimes on biodiversity will increase uptake of evidence into environmental flow implementation, identify suitable biodiversity targets responsive to hydrological change or restoration, and identify and manage risks of environmental flows contributing to biodiversity decline. © 2017 Cambridge Philosophical Society.

Fourier transform infrared spectroscopy microscopic imaging classification based on spatial-spectral features

NASA Astrophysics Data System (ADS)

Liu, Lian; Yang, Xiukun; Zhong, Mingliang; Liu, Yao; Jing, Xiaojun; Yang, Qin

2018-04-01

The discrete fractional Brownian incremental random (DFBIR) field is used to describe the irregular, random, and highly complex shapes of natural objects such as coastlines and biological tissues, for which traditional Euclidean geometry cannot be used. In this paper, an anisotropic variable window (AVW) directional operator based on the DFBIR field model is proposed for extracting spatial characteristics of Fourier transform infrared spectroscopy (FTIR) microscopic imaging. Probabilistic principal component analysis first extracts spectral features, and then the spatial features of the proposed AVW directional operator are combined with the former to construct a spatial-spectral structure, which increases feature-related information and helps a support vector machine classifier to obtain more efficient distribution-related information. Compared to Haralick’s grey-level co-occurrence matrix, Gabor filters, and local binary patterns (e.g. uniform LBPs, rotation-invariant LBPs, uniform rotation-invariant LBPs), experiments on three FTIR spectroscopy microscopic imaging datasets show that the proposed AVW directional operator is more advantageous in terms of classification accuracy, particularly for low-dimensional spaces of spatial characteristics.

Spatial Pattern of Standing Timber Value across the Brazilian Amazon

PubMed Central

Ahmed, Sadia E.; Ewers, Robert M.

2012-01-01

The Amazon is a globally important system, providing a host of ecosystem services from climate regulation to food sources. It is also home to a quarter of all global diversity. Large swathes of forest are removed each year, and many models have attempted to predict the spatial patterns of this forest loss. The spatial patterns of deforestation are determined largely by the patterns of roads that open access to frontier areas and expansion of the road network in the Amazon is largely determined by profit seeking logging activities. Here we present predictions for the spatial distribution of standing value of timber across the Amazon. We show that the patterns of timber value reflect large-scale ecological gradients, determining the spatial distribution of functional traits of trees which are, in turn, correlated with timber values. We expect that understanding the spatial patterns of timber value across the Amazon will aid predictions of logging movements and thus predictions of potential future road developments. These predictions in turn will be of great use in estimating the spatial patterns of deforestation in this globally important biome. PMID:22590520

Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior

DOE PAGES

Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois; ...

2017-06-18

Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less

Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior

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

Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois

Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less

“Left Neglected,” but Only in Far Space: Spatial Biases in Healthy Participants Revealed in a Visually Guided Grasping Task

PubMed Central

de Bruin, Natalie; Bryant, Devon C.; Gonzalez, Claudia L. R.

2014-01-01

Hemispatial neglect is a common outcome of stroke that is characterized by the inability to orient toward, and attend to stimuli in contralesional space. It is established that hemispatial neglect has a perceptual component, however, the presence and severity of motor impairments is controversial. Establishing the nature of space use and spatial biases during visually guided actions amongst healthy individuals is critical to understanding the presence of visuomotor deficits in patients with neglect. Accordingly, three experiments were conducted to investigate the effect of object spatial location on patterns of grasping. Experiment 1 required right-handed participants to reach and grasp for blocks in order to construct 3D models. The blocks were scattered on a tabletop divided into equal size quadrants: left near, left far, right near, and right far. Identical sets of building blocks were available in each quadrant. Space use was dynamic, with participants initially grasping blocks from right near space and tending to “neglect” left far space until the final stages of the task. Experiment 2 repeated the protocol with left-handed participants. Remarkably, left-handed participants displayed a similar pattern of space use to right-handed participants. In Experiment 3 eye movements were examined to investigate whether “neglect” for grasping in left far reachable space had its origins in attentional biases. It was found that patterns of eye movements mirrored patterns of reach-to-grasp movements. We conclude that there are spatial biases during visually guided grasping, specifically, a tendency to neglect left far reachable space, and that this “neglect” is attentional in origin. The results raise the possibility that visuomotor impairments reported among patients with right hemisphere lesions when working in contralesional space may result in part from this inherent tendency to “neglect” left far space irrespective of the presence of unilateral visuospatial neglect. PMID:24478751

Spatial patterns of recreational impact on experimental campsites

Treesearch

David N. Cole; Christopher A. Monz

2004-01-01

Management of camping impacts in protected areas worldwide is limited by inadequate understanding of spatial patterns of impact and attention to spatial management strategies. Spatial patterns of campsite impact were studied in two subalpine plant communities in the Wind River Mountains, Wyoming, USA (a forest and a meadow). Response to chronic disturbance and recovery...

Spatial patterns of heavy metals in soil under different geological structures and land uses for assessing metal enrichments.

PubMed

Krami, Loghman Khoda; Amiri, Fazel; Sefiyanian, Alireza; Shariff, Abdul Rashid B Mohamed; Tabatabaie, Tayebeh; Pradhan, Biswajeet

2013-12-01

One hundred and thirty composite soil samples were collected from Hamedan county, Iran to characterize the spatial distribution and trace the sources of heavy metals including As, Cd, Co, Cr, Cu, Ni, Pb, V, Zn, and Fe. The multivariate gap statistical analysis was used; for interrelation of spatial patterns of pollution, the disjunctive kriging and geoenrichment factor (EF(G)) techniques were applied. Heavy metals and soil properties were grouped using agglomerative hierarchical clustering and gap statistic. Principal component analysis was used for identification of the source of metals in a set of data. Geostatistics was used for the geospatial data processing. Based on the comparison between the original data and background values of the ten metals, the disjunctive kriging and EF(G) techniques were used to quantify their geospatial patterns and assess the contamination levels of the heavy metals. The spatial distribution map combined with the statistical analysis showed that the main source of Cr, Co, Ni, Zn, Pb, and V in group A land use (agriculture, rocky, and urban) was geogenic; the origin of As, Cd, and Cu was industrial and agricultural activities (anthropogenic sources). In group B land use (rangeland and orchards), the origin of metals (Cr, Co, Ni, Zn, and V) was mainly controlled by natural factors and As, Cd, Cu, and Pb had been added by organic factors. In group C land use (water), the origin of most heavy metals is natural without anthropogenic sources. The Cd and As pollution was relatively more serious in different land use. The EF(G) technique used confirmed the anthropogenic influence of heavy metal pollution. All metals showed concentrations substantially higher than their background values, suggesting anthropogenic pollution.

Throughfall and its spatial variability beneath xerophytic shrub canopies within water-limited arid desert ecosystems

NASA Astrophysics Data System (ADS)

Zhang, Ya-feng; Wang, Xin-ping; Hu, Rui; Pan, Yan-xia

2016-08-01

Throughfall is known to be a critical component of the hydrological and biogeochemical cycles of forested ecosystems with inherently temporal and spatial variability. Yet little is understood concerning the throughfall variability of shrubs and the associated controlling factors in arid desert ecosystems. Here we systematically investigated the variability of throughfall of two morphological distinct xerophytic shrubs (Caragana korshinskii and Artemisia ordosica) within a re-vegetated arid desert ecosystem, and evaluated the effects of shrub structure and rainfall characteristics on throughfall based on heavily gauged throughfall measurements at the event scale. We found that morphological differences were not sufficient to generate significant difference (P < 0.05) in throughfall between two studied shrub species under the same rainfall and meteorological conditions in our study area, with a throughfall percentage of 69.7% for C. korshinskii and 64.3% for A. ordosica. We also observed a highly variable patchy pattern of throughfall beneath individual shrub canopies, but the spatial patterns appeared to be stable among rainfall events based on time stability analysis. Throughfall linearly increased with the increasing distance from the shrub base for both shrubs, and radial direction beneath shrub canopies had a pronounced impact on throughfall. Throughfall variability, expressed as the coefficient of variation (CV) of throughfall, tended to decline with the increase in rainfall amount, intensity and duration, and stabilized passing a certain threshold. Our findings highlight the great variability of throughfall beneath the canopies of xerophytic shrubs and the time stability of throughfall pattern among rainfall events. The spatially heterogeneous and temporally stable throughfall is expected to generate a dynamic patchy distribution of soil moisture beneath shrub canopies within arid desert ecosystems.

Modality-Spanning Deficits in Attention-Deficit/Hyperactivity Disorder in Functional Networks, Gray Matter, and White Matter

PubMed Central

Kessler, Daniel; Angstadt, Michael; Welsh, Robert C.

2014-01-01

Previous neuroimaging investigations in attention-deficit/hyperactivity disorder (ADHD) have separately identified distributed structural and functional deficits, but interconnections between these deficits have not been explored. To unite these modalities in a common model, we used joint independent component analysis, a multivariate, multimodal method that identifies cohesive components that span modalities. Based on recent network models of ADHD, we hypothesized that altered relationships between large-scale networks, in particular, default mode network (DMN) and task-positive networks (TPNs), would co-occur with structural abnormalities in cognitive regulation regions. For 756 human participants in the ADHD-200 sample, we produced gray and white matter volume maps with voxel-based morphometry, as well as whole-brain functional connectomes. Joint independent component analysis was performed, and the resulting transmodal components were tested for differential expression in ADHD versus healthy controls. Four components showed greater expression in ADHD. Consistent with our a priori hypothesis, we observed reduced DMN-TPN segregation co-occurring with structural abnormalities in dorsolateral prefrontal cortex and anterior cingulate cortex, two important cognitive control regions. We also observed altered intranetwork connectivity in DMN, dorsal attention network, and visual network, with co-occurring distributed structural deficits. There was strong evidence of spatial correspondence across modalities: For all four components, the impact of the respective component on gray matter at a region strongly predicted the impact on functional connectivity at that region. Overall, our results demonstrate that ADHD involves multiple, cohesive modality spanning deficits, each one of which exhibits strong spatial overlap in the pattern of structural and functional alterations. PMID:25505309

Spatial-structural analysis of leafless woody riparian vegetation for hydraulic considerations

NASA Astrophysics Data System (ADS)

Weissteiner, Clemens; Jalonen, Johanna; Järvelä, Juha; Rauch, Hans Peter

2013-04-01

Woody riparian vegetation is a vital element of riverine environments. On one hand woody riparian vegetation has to be taken into account from a civil engineering point of view due to boundary shear stress and vegetation drag. On the other hand it has to be considered from a river ecological point of view due to shadowing effects and as a source of organic material for aquatic habitats. In hydrodynamic and hydro-ecological studies the effects of woody riparian vegetation on flow patterns are usually investigated on a very detailed level. On the contrary vegetation elements and their spatial patterns are generally analysed and discussed on the basis of an integral approach measuring for example basal diameters, heights and projected plant areas. For a better understanding of the influence of woody riparian vegetation on turbulent flow and on river ecology, it is essential to record and analyse plant data sets on the same level of quality as for hydrodynamic or hydro-ecologic purposes. As a result of the same scale of the analysis it is possible to incorporate riparian vegetation as a sub-model in the hydraulic analysis. For plant structural components, such as branches on different topological levels it is crucial to record plant geometrical parameters describing the habitus of the plant on branch level. An exact 3D geometrical model of real plants allows for an extraction of various spatial-structural plant parameters. In addition, allometric relationships help to summarize and describe plant traits of riparian vegetation. This paper focuses on the spatial-structural composition of leafless riparia woddy vegetation. Structural and spatial analyses determine detailed geometric properties of the structural components of the plants. Geometrical and topological parameters were recorded with an electro-magnetic scanning device. In total, 23 plants (willows, alders and birches) were analysed in the study. Data were recorded on branch level, which allowed for the development of a 3D geometric plant model. The results are expected to improve knowledge on how the architectural system and allometric relationships of the plants relate to ecological and hydrodynamic properties.

Spatial and temporal patterns in trace element deposition to lakes in the Athabasca oil sands region (Alberta, Canada)

NASA Astrophysics Data System (ADS)

Cooke, Colin A.; Kirk, Jane L.; Muir, Derek C. G.; Wiklund, Johan A.; Wang, Xiaowa; Gleason, Amber; Evans, Marlene S.

2017-12-01

The mining and processing of the Athabasca oil sands (Alberta, Canada) has been occurring for decades; however, a lack of consistent regional monitoring has obscured the long-term environmental impact. Here, we present sediment core results to reconstruct spatial and temporal patterns in trace element deposition to lakes in the Athabasca oil sands region. Early mining operations (during the 1970s and 1980s) led to elevated V and Pb inputs to lakes located <50 km from mining operations. Subsequent improvements to mining and upgrading technologies since the 1980s have reduced V and Pb loading to near background levels at many sites. In contrast, Hg deposition increased by a factor of ~3 to all 20 lakes over the 20th century, reflecting global-scale patterns in atmospheric Hg emissions. Base cation deposition (from fugitive dust emissions) has not measurably impacted regional lake sediments. Instead, results from a principal components analysis suggest that the presence of carbonate bedrock underlying lakes located close to development appears to exert a first-order control over lake sediment base cation concentrations and overall lake sediment geochemical composition. Trace element concentrations generally did not exceed Canadian sediment quality guidelines, and no spatial or temporal trends were observed in the frequency of guideline exceedence. Our results demonstrate that early mining efforts had an even greater impact on trace element cycling than has been appreciated previously, placing recent monitoring efforts in a critical long-term context.

[Spatial patterns in communities of aquatic macroinvertebrates of Argentinean Puna].

PubMed

Nieto, Carolina; Malizia, Agustina; Carilla, Julieta; Izquierdo, Andrea; Rodríguez, José; Cuello, Soledad; Zannier, Martín; Grau, H Ricardo

2016-06-01

Spatial patterns in communities of aquatic macroinvertebrates of Argentinean Puna. The macroinvertebrates are a vital component of freshwater ecosystems as they contribute to the process of organic matter while serving as food for other organisms such as fish and amphibians. Unfortunately, the knowledge of the aquatic diversity is poor in the high Andean systems (between 3 200 and 5 200 m.a.s.l. and rainfall below 300 mm per year), especially in the Argentinean peatbogs, a fact which has made difficult the interpretation of spatial patterns on a regional scale. The present study aimed to describe the composition of aquatic macroinvertebrates in seven peatbogs in the Argentinean Puna, and to analyze for the first time their spatial patterns. For this, we studied the relationship of these organisms with the environment, and obtained information about the surrounding vegetation and water physico-chemical characteristics. A total of 3 131 specimens of aquatic macroinvertebrates were collected, representing 25 taxa belonging to 22 families and 24 genera. In addition, 62 species of vascular plants were recorded, belonging to 20 families. The most abundant life form were the tufted grasses, followed by cushions. By using an NMDS (Non-Metrical Multidimensional Scaling) statistical analysis, the sampling sites were ordered in each peatbog as follows. The peatbogs located furthest West and South with higher water temperature were grouped on axis 1, whereas those with higher conductivity, whole water dissolved solids and salt concentration were grouped on axis 2. The water temperature was higher than air temperature at all times, and we found no association between temperature and altitude. The altitude had no correlation with the abundance of macroinvertebrates or with plant richness. Life forms such as scattered graminoids, trailing and prostrate herbs (in many cases they get into the channel) and aquatic plants were more abundant in peatbogs 4, 5 and 7 and they had a correlation with some macroinvertebrates belonging to functional trophic groups such as filter-collectors, collectors and scrapers. Finally, conductivity, whole dissolved solids and salt concentration had their highest value in peatbog 6, where Bivalvia (filter-collector) and Hyalella (collector) were also found. The results obtained attest that these macroinvertebrates displayed diversity and composition spatial patterns, the most important feature being their relationship with the surrounding vegetation, and to a lesser extent, with the physical and chemical traits of water in seven fertile lowlands in the Argentinean Puna.

Precoded spatial multiplexing MIMO system with spatial component interleaver.

PubMed

Gao, Xiang; Wu, Zhanji

In this paper, the performance of precoded bit-interleaved coded modulation (BICM) spatial multiplexing multiple-input multiple-output (MIMO) system with spatial component interleaver is investigated. For the ideal precoded spatial multiplexing MIMO system with spatial component interleaver based on singular value decomposition (SVD) of the MIMO channel, the average pairwise error probability (PEP) of coded bits is derived. Based on the PEP analysis, the optimum spatial Q-component interleaver design criterion is provided to achieve the minimum error probability. For the limited feedback precoded proposed scheme with linear zero forcing (ZF) receiver, in order to minimize a bound on the average probability of a symbol vector error, a novel effective signal-to-noise ratio (SNR)-based precoding matrix selection criterion and a simplified criterion are proposed. Based on the average mutual information (AMI)-maximization criterion, the optimal constellation rotation angles are investigated. Simulation results indicate that the optimized spatial multiplexing MIMO system with spatial component interleaver can achieve significant performance advantages compared to the conventional spatial multiplexing MIMO system.

Spatio-temporal Analysis for New York State SPARCS Data

PubMed Central

Chen, Xin; Wang, Yu; Schoenfeld, Elinor; Saltz, Mary; Saltz, Joel; Wang, Fusheng

2017-01-01

Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data. We analyzed spatial distribution patterns of typical diseases at ZIP code level. We performed temporal analysis of common diseases based on 12 years’ historical data. We then compared the spatial variations for diseases with different levels of clustering tendency, and studied the evolution history of such spatial patterns. Case studies based on asthma demonstrated that the discovered spatial clusters are consistent with prior studies. We visualized our spatial-temporal patterns as animations through videos. PMID:28815148

A Method to Categorize 2-Dimensional Patterns Using Statistics of Spatial Organization.

PubMed

López-Sauceda, Juan; Rueda-Contreras, Mara D

2017-01-01

We developed a measurement framework of spatial organization to categorize 2-dimensional patterns from 2 multiscalar biological architectures. We propose that underlying shapes of biological entities can be approached using the statistical concept of degrees of freedom, defining it through expansion of area variability in a pattern. To help scope this suggestion, we developed a mathematical argument recognizing the deep foundations of area variability in a polygonal pattern (spatial heterogeneity). This measure uses a parameter called eutacticity . Our measuring platform of spatial heterogeneity can assign particular ranges of distribution of spatial areas for 2 biological architectures: ecological patterns of Namibia fairy circles and epithelial sheets. The spatial organizations of our 2 analyzed biological architectures are demarcated by being in a particular position among spatial order and disorder. We suggest that this theoretical platform can give us some insights about the nature of shapes in biological systems to understand organizational constraints.

Spatial Patterns in Water Temperature in Pacific Northwest Rivers: Diversity at Multiple Scales and Potential Influence of Climate Change

NASA Astrophysics Data System (ADS)

Torgersen, C. E.; Fullerton, A.; Lawler, J. J.; Ebersole, J. L.; Leibowitz, S. G.; Steel, E. A.; Beechie, T. J.; Faux, R.

2016-12-01

Understanding spatial patterns in water temperature will be essential for evaluating vulnerability of aquatic biota to future climate and for identifying and protecting diverse thermal habitats. We used high-resolution remotely sensed water temperature data for over 16,000 km of 2nd to 7th-order rivers throughout the Pacific Northwest and California to evaluate spatial patterns of summertime water temperature at multiple spatial scales. We found a diverse and geographically distributed suite of whole-river patterns. About half of rivers warmed asymptotically in a downstream direction, whereas the rest exhibited complex and unique spatial patterns. Patterns were associated with both broad-scale hydroclimatic variables as well as characteristics unique to each basin. Within-river thermal heterogeneity patterns were highly river-specific; across rivers, median size and spacing of cool patches <15 °C were around 250 m. Patches of this size are large enough for juvenile salmon rearing and for resting during migration, and the distance between patches is well within the movement capabilities of both juvenile and adult salmon. We found considerable thermal heterogeneity at fine spatial scales that may be important to fish that would be missed if data were analyzed at coarser scales. We estimated future thermal heterogeneity and concluded that climate change will cause warmer temperatures overall, but that thermal heterogeneity patterns may remain similar in the future for many rivers. We demonstrated considerable spatial complexity in both current and future water temperature, and resolved spatial patterns that could not have been perceived without spatially continuous data.

Quantifying seascape structure: Extending terrestrial spatial pattern metrics to the marine realm

USGS Publications Warehouse

Wedding, L.M.; Christopher, L.A.; Pittman, S.J.; Friedlander, A.M.; Jorgensen, S.

2011-01-01

Spatial pattern metrics have routinely been applied to characterize and quantify structural features of terrestrial landscapes and have demonstrated great utility in landscape ecology and conservation planning. The important role of spatial structure in ecology and management is now commonly recognized, and recent advances in marine remote sensing technology have facilitated the application of spatial pattern metrics to the marine environment. However, it is not yet clear whether concepts, metrics, and statistical techniques developed for terrestrial ecosystems are relevant for marine species and seascapes. To address this gap in our knowledge, we reviewed, synthesized, and evaluated the utility and application of spatial pattern metrics in the marine science literature over the past 30 yr (1980 to 2010). In total, 23 studies characterized seascape structure, of which 17 quantified spatial patterns using a 2-dimensional patch-mosaic model and 5 used a continuously varying 3-dimensional surface model. Most seascape studies followed terrestrial-based studies in their search for ecological patterns and applied or modified existing metrics. Only 1 truly unique metric was found (hydrodynamic aperture applied to Pacific atolls). While there are still relatively few studies using spatial pattern metrics in the marine environment, they have suffered from similar misuse as reported for terrestrial studies, such as the lack of a priori considerations or the problem of collinearity between metrics. Spatial pattern metrics offer great potential for ecological research and environmental management in marine systems, and future studies should focus on (1) the dynamic boundary between the land and sea; (2) quantifying 3-dimensional spatial patterns; and (3) assessing and monitoring seascape change. ?? Inter-Research 2011.

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

Flower colours through the lens: quantitative measurement with visible and ultraviolet digital photography.

PubMed

Garcia, Jair E; Greentree, Andrew D; Shrestha, Mani; Dorin, Alan; Dyer, Adrian G

2014-01-01

The study of the signal-receiver relationship between flowering plants and pollinators requires a capacity to accurately map both the spectral and spatial components of a signal in relation to the perceptual abilities of potential pollinators. Spectrophotometers can typically recover high resolution spectral data, but the spatial component is difficult to record simultaneously. A technique allowing for an accurate measurement of the spatial component in addition to the spectral factor of the signal is highly desirable. Consumer-level digital cameras potentially provide access to both colour and spatial information, but they are constrained by their non-linear response. We present a robust methodology for recovering linear values from two different camera models: one sensitive to ultraviolet (UV) radiation and another to visible wavelengths. We test responses by imaging eight different plant species varying in shape, size and in the amount of energy reflected across the UV and visible regions of the spectrum, and compare the recovery of spectral data to spectrophotometer measurements. There is often a good agreement of spectral data, although when the pattern on a flower surface is complex a spectrophotometer may underestimate the variability of the signal as would be viewed by an animal visual system. Digital imaging presents a significant new opportunity to reliably map flower colours to understand the complexity of these signals as perceived by potential pollinators. Compared to spectrophotometer measurements, digital images can better represent the spatio-chromatic signal variability that would likely be perceived by the visual system of an animal, and should expand the possibilities for data collection in complex, natural conditions. However, and in spite of its advantages, the accuracy of the spectral information recovered from camera responses is subject to variations in the uncertainty levels, with larger uncertainties associated with low radiance levels.

Spatial Analysis of Large Woody Debris Arrangement in a Midwestern U.S. River System: Geomorphic Implications and Influences

NASA Astrophysics Data System (ADS)

Martin, D. J.

2013-12-01

Large woody debris (LWD) is universally recognized as a key component of the geomorphological and ecological function of fluvial systems and has been increasingly incorporated into stream restoration and watershed management projects. However, 'natural' processes of recruitment and the subsequent arrangement of LWD within the river network are poorly understood and are thus, rarely a management consideration. Additionally, LWD research tends to be regionally biased toward mountainous regions, and scale biased toward the micro-scale. In many locations, the lack of understanding has led to the failure of restoration/rehabilitation projects that involved the use of LWD. This research uses geographic information systems and spatial analysis techniques to investigate longitudinal arrangement patterns of LWD in a low-gradient, Midwestern river. A large-scale GPS inventory of LWD was performed on the Big River, located in the eastern Missouri Ozarks resulting in over 5,000 logged positions of LWD along seven river segments covering nearly 100 km of the 237 km river system. A time series analysis framework was used to statistically identify longitudinal spatial patterns of LWD arrangement along the main stem of the river, and correlation analyses were performed to help identify physical controls of those patterns. Results indicate that upstream segments have slightly lower densities than downstream segments, with the exception of the farthest upstream segment. Results also show lack of an overall longitudinal trend in LWD density; however, periodogram analysis revealed an inherent periodicity in LWD arrangement. Periodicities were most evident in the downstream segments with frequencies ranging from 3 km to 7 km. Additionally, Pearson correlation analysis, performed within the segment displaying the strongest periodic behavior, show that LWD densities are correlated with channel sinuosity (r=0.25). Ongoing research is investigating further relationships between arrangement patterns and geomorphic and riparian variables. Understanding these spatial patterns and relationships will provide valuable insight into the application of LWD-related stream and watershed management practices, and fill a necessary regional knowledge gap in our understanding of LWD's role in fluvial processes.

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

NASA Technical Reports Server (NTRS)

Goetz, Scott J.; Bockstael, Nancy E.; Jantz, Claire A.

2005-01-01

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

Iterative approach of dual regression with a sparse prior enhances the performance of independent component analysis for group functional magnetic resonance imaging (fMRI) data.

PubMed

Kim, Yong-Hwan; Kim, Junghoe; Lee, Jong-Hwan

2012-12-01

This study proposes an iterative dual-regression (DR) approach with sparse prior regularization to better estimate an individual's neuronal activation using the results of an independent component analysis (ICA) method applied to a temporally concatenated group of functional magnetic resonance imaging (fMRI) data (i.e., Tc-GICA method). An ordinary DR approach estimates the spatial patterns (SPs) of neuronal activation and corresponding time courses (TCs) specific to each individual's fMRI data with two steps involving least-squares (LS) solutions. Our proposed approach employs iterative LS solutions to refine both the individual SPs and TCs with an additional a priori assumption of sparseness in the SPs (i.e., minimally overlapping SPs) based on L(1)-norm minimization. To quantitatively evaluate the performance of this approach, semi-artificial fMRI data were created from resting-state fMRI data with the following considerations: (1) an artificially designed spatial layout of neuronal activation patterns with varying overlap sizes across subjects and (2) a BOLD time series (TS) with variable parameters such as onset time, duration, and maximum BOLD levels. To systematically control the spatial layout variability of neuronal activation patterns across the "subjects" (n=12), the degree of spatial overlap across all subjects was varied from a minimum of 1 voxel (i.e., 0.5-voxel cubic radius) to a maximum of 81 voxels (i.e., 2.5-voxel radius) across the task-related SPs with a size of 100 voxels for both the block-based and event-related task paradigms. In addition, several levels of maximum percentage BOLD intensity (i.e., 0.5, 1.0, 2.0, and 3.0%) were used for each degree of spatial overlap size. From the results, the estimated individual SPs of neuronal activation obtained from the proposed iterative DR approach with a sparse prior showed an enhanced true positive rate and reduced false positive rate compared to the ordinary DR approach. The estimated TCs of the task-related SPs from our proposed approach showed greater temporal correlation coefficients with a reference hemodynamic response function than those of the ordinary DR approach. Moreover, the efficacy of the proposed DR approach was also successfully demonstrated by the results of real fMRI data acquired from left-/right-hand clenching tasks in both block-based and event-related task paradigms. Copyright © 2012 Elsevier Inc. All rights reserved.

Bayesian spatiotemporal crash frequency models with mixture components for space-time interactions.

PubMed

Cheng, Wen; Gill, Gurdiljot Singh; Zhang, Yongping; Cao, Zhong

2018-03-01

The traffic safety research has developed spatiotemporal models to explore the variations in the spatial pattern of crash risk over time. Many studies observed notable benefits associated with the inclusion of spatial and temporal correlation and their interactions. However, the safety literature lacks sufficient research for the comparison of different temporal treatments and their interaction with spatial component. This study developed four spatiotemporal models with varying complexity due to the different temporal treatments such as (I) linear time trend; (II) quadratic time trend; (III) Autoregressive-1 (AR-1); and (IV) time adjacency. Moreover, the study introduced a flexible two-component mixture for the space-time interaction which allows greater flexibility compared to the traditional linear space-time interaction. The mixture component allows the accommodation of global space-time interaction as well as the departures from the overall spatial and temporal risk patterns. This study performed a comprehensive assessment of mixture models based on the diverse criteria pertaining to goodness-of-fit, cross-validation and evaluation based on in-sample data for predictive accuracy of crash estimates. The assessment of model performance in terms of goodness-of-fit clearly established the superiority of the time-adjacency specification which was evidently more complex due to the addition of information borrowed from neighboring years, but this addition of parameters allowed significant advantage at posterior deviance which subsequently benefited overall fit to crash data. The Base models were also developed to study the comparison between the proposed mixture and traditional space-time components for each temporal model. The mixture models consistently outperformed the corresponding Base models due to the advantages of much lower deviance. For cross-validation comparison of predictive accuracy, linear time trend model was adjudged the best as it recorded the highest value of log pseudo marginal likelihood (LPML). Four other evaluation criteria were considered for typical validation using the same data for model development. Under each criterion, observed crash counts were compared with three types of data containing Bayesian estimated, normal predicted, and model replicated ones. The linear model again performed the best in most scenarios except one case of using model replicated data and two cases involving prediction without including random effects. These phenomena indicated the mediocre performance of linear trend when random effects were excluded for evaluation. This might be due to the flexible mixture space-time interaction which can efficiently absorb the residual variability escaping from the predictable part of the model. The comparison of Base and mixture models in terms of prediction accuracy further bolstered the superiority of the mixture models as the mixture ones generated more precise estimated crash counts across all four models, suggesting that the advantages associated with mixture component at model fit were transferable to prediction accuracy. Finally, the residual analysis demonstrated the consistently superior performance of random effect models which validates the importance of incorporating the correlation structures to account for unobserved heterogeneity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Circulation controls of the spatial structure of maximum daily precipitation over Poland

NASA Astrophysics Data System (ADS)

Stach, Alfred

2015-04-01

Among forecasts made on the basis of global and regional climatic models is one of a high probability of an increase in the frequency and intensity of extreme precipitation events. Learning the regularities underlying the recurrence and spatial extent of extreme precipitation is obviously of great importance, both economic and social. The main goal of the study was to analyse regularities underlying spatial and temporal variations in monthly Maximum Daily Precipitation Totals (MDPTs) observed in Poland over the years 1956-1980. These data are specific because apart from being spatially discontinuous, which is typical of precipitation, they are also non-synchronic. The main aim of the study was accomplished via several detailed goals: • identification and typology of the spatial structure of monthly MDPTs, • determination of the character and probable origin of events generating MDPTs, and • quantitative assessment of the contribution of the particular events to the overall MDPT figures. The analysis of the spatial structure of MDPTs was based on 300 models of spatial structure, one for each of the analysed sets of monthly MDPTs. The models were built on the basis of empirical anisotropic semivariograms of normalised data. In spite of their spatial discontinuity and asynchronicity, the MDPT data from Poland display marked regularities in their spatial pattern that yield readily to mathematical modelling. The MDPT field in Poland is usually the sum of the outcomes of three types of processes operating at various spatial scales: local (<10-20 km), regional (50-150 km), and supra-regional (>200 km). The spatial scales are probably connected with a convective/ orographic, a frontal and a 'planetary waves' genesis of high precipitation. Their contributions are highly variable. Generally predominant, however, are high daily precipitation totals with a spatial extent of 50 to 150 km connected with mesoscale phenomena and the migration of atmospheric fronts (35-38%). The spatial extent of areas of high local-scale precipitation usually varies at random, especially in the warm season. At supra-local scales, structures of repetitive size predominate. Eight types of anisotropic structures of monthly MDPTs were distinguished. To identify them, an analysis was made of semivariance surface similarities. The types differ not only in the level and direction of anisotropy, but also in the number and type of elementary components, which is evidence of genetic differences in precipitation. Their appearance shows a significant seasonal variability, so the most probable supposition was that temporal variations in the MDPT pattern were connected with circulation conditions: the type and direction of inflow of air masses. This hypothesis was validated by testing differences in the frequency of occurrence of Grosswetterlagen circulation situations in the months belonging to the distinguished types of the spatial MDPT pattern.

Landscape patterns and soil organic carbon stocks in agricultural bocage landscapes

NASA Astrophysics Data System (ADS)

Viaud, Valérie; Lacoste, Marine; Michot, Didier; Walter, Christian

2014-05-01

Soil organic carbon (SOC) has a crucial impact on global carbon storage at world scale. SOC spatial variability is controlled by the landscape patterns resulting from the continuous interactions between the physical environment and the society. Natural and anthropogenic processes occurring and interplaying at the landscape scale, such as soil redistribution in the lateral and vertical dimensions by tillage and water erosion processes or spatial differentiation of land-use and land-management practices, strongly affect SOC dynamics. Inventories of SOC stocks, reflecting their spatial distribution, are thus key elements to develop relevant management strategies to improving carbon sequestration and mitigating climate change and soil degradation. This study aims to quantify SOC stocks and their spatial distribution in a 1,000-ha agricultural bocage landscape with dairy production as dominant farming system (Zone Atelier Armorique, LTER Europe, NW France). The site is characterized by high heterogeneity on short distance due to a high diversity of soils with varying waterlogging, soil parent material, topography, land-use and hedgerow density. SOC content and stocks were measured up to 105-cm depth in 200 sampling locations selected using conditioned Latin hypercube sampling. Additive sampling was designed to specifically explore SOC distribution near to hedges: 112 points were sampled at fixed distance on 14 transects perpendicular from hedges. We illustrate the heterogeneity of spatial and vertical distribution of SOC stocks at landscape scale, and quantify SOC stocks in the various landscape components. Using multivariate statistics, we discuss the variability and co-variability of existing spatial organization of cropping systems, environmental factors, and SOM stocks, over landscape. Ultimately, our results may contribute to improving regional or national digital soil mapping approaches, by considering the distribution of SOC stocks within each modeling unit and by accounting for the impact of sensitive ecosystems.

Very high resolution Earth Observation features for testing the direct and indirect effects of landscape structure on local habitat quality

NASA Astrophysics Data System (ADS)

Mairota, Paola; Cafarelli, Barbara; Labadessa, Rocco; Lovergine, Francesco P.; Tarantino, Cristina; Nagendra, Harini; Didham, Raphael K.

2015-02-01

Modelling the empirical relationships between habitat quality and species distribution patterns is the first step to understanding human impacts on biodiversity. It is important to build on this understanding to develop a broader conceptual appreciation of the influence of surrounding landscape structure on local habitat quality, across multiple spatial scales. Traditional models which report that 'habitat amount' in the landscape is sufficient to explain patterns of biodiversity, irrespective of habitat configuration or spatial variation in habitat quality at edges, implicitly treat each unit of habitat as interchangeable and ignore the high degree of interdependence between spatial components of land-use change. Here, we test the contrasting hypothesis, that local habitat units are not interchangeable in their habitat attributes, but are instead dependent on variation in surrounding habitat structure at both patch- and landscape levels. As the statistical approaches needed to implement such hierarchical causal models are observation-intensive, we utilise very high resolution (VHR) Earth Observation (EO) images to rapidly generate fine-grained measures of habitat patch internal heterogeneities over large spatial extents. We use linear mixed-effects models to test whether these remotely-sensed proxies for habitat quality were influenced by surrounding patch or landscape structure. The results demonstrate the significant influence of surrounding patch and landscape context on local habitat quality. They further indicate that such an influence can be direct, when a landscape variable alone influences the habitat structure variable, and/or indirect when the landscape and patch attributes have a conjoined effect on the response variable. We conclude that a substantial degree of interaction among spatial configuration effects is likely to be the norm in determining the ecological consequences of habitat fragmentation, thus corroborating the notion of the spatial context dependence of habitat quality.

Construction of an integrated social vulnerability index in urban areas prone to flash flooding

NASA Astrophysics Data System (ADS)

Aroca-Jimenez, Estefania; Bodoque, Jose Maria; Garcia, Juan Antonio; Diez-Herrero, Andres

2017-09-01

Among the natural hazards, flash flooding is the leading cause of weather-related deaths. Flood risk management (FRM) in this context requires a comprehensive assessment of the social risk component. In this regard, integrated social vulnerability (ISV) can incorporate spatial distribution and contribution and the combined effect of exposure, sensitivity and resilience to total vulnerability, although these components are often disregarded. ISV is defined by the demographic and socio-economic characteristics that condition a population's capacity to cope with, resist and recover from risk and can be expressed as the integrated social vulnerability index (ISVI). This study describes a methodological approach towards constructing the ISVI in urban areas prone to flash flooding in Castilla y León (Castile and León, northern central Spain, 94 223 km2, 2 478 376 inhabitants). A hierarchical segmentation analysis (HSA) was performed prior to the principal components analysis (PCA), which helped to overcome the sample size limitation inherent in PCA. ISVI was obtained from weighting vulnerability factors based on the tolerance statistic. In addition, latent class cluster analysis (LCCA) was carried out to identify spatial patterns of vulnerability within the study area. Our results show that the ISVI has high spatial variability. Moreover, the source of vulnerability in each urban area cluster can be identified from LCCA. These findings make it possible to design tailor-made strategies for FRM, thereby increasing the efficiency of plans and policies and helping to reduce the cost of mitigation measures.

Water balance dynamics in the Nile Basin

USGS Publications Warehouse

Senay, Gabriel B.; Asante, Kwabena; Artan, Guleid A.

2009-01-01

Understanding the temporal and spatial dynamics of key water balance components of the Nile River will provide important information for the management of its water resources. This study used satellite-derived rainfall and other key weather variables derived from the Global Data Assimilation System to estimate and map the distribution of rainfall, actual evapotranspiration (ETa), and runoff. Daily water balance components were modelled in a grid-cell environment at 0·1 degree (∼10 km) spatial resolution for 7 years from 2001 through 2007. Annual maps of the key water balance components and derived variables such as runoff and ETa as a percent of rainfall were produced. Generally, the spatial patterns of rainfall and ETa indicate high values in the upstream watersheds (Uganda, southern Sudan, and southwestern Ethiopia) and low values in the downstream watersheds. However, runoff as a percent of rainfall is much higher in the Ethiopian highlands around the Blue Nile subwatershed. The analysis also showed the possible impact of land degradation in the Ethiopian highlands in reducing ETa magnitudes despite the availability of sufficient rainfall. Although the model estimates require field validation for the different subwatersheds, the runoff volume estimate for the Blue Nile subwatershed is within 7·0% of a figure reported from an earlier study. Further research is required for a thorough validation of the results and their integration with ecohydrologic models for better management of water and land resources in the various Nile Basin ecosystems.

Coherent manipulation of spin correlations in the Hubbard model

NASA Astrophysics Data System (ADS)

Wurz, N.; Chan, C. F.; Gall, M.; Drewes, J. H.; Cocchi, E.; Miller, L. A.; Pertot, D.; Brennecke, F.; Köhl, M.

2018-05-01

We coherently manipulate spin correlations in a two-component atomic Fermi gas loaded into an optical lattice using spatially and time-resolved Ramsey spectroscopy combined with high-resolution in situ imaging. This technique allows us not only to imprint spin patterns but also to probe the static magnetic structure factor at an arbitrary wave vector, in particular, the staggered structure factor. From a measurement along the diagonal of the first Brillouin zone of the optical lattice, we determine the magnetic correlation length and the individual spatial spin correlators. At half filling, the staggered magnetic structure factor serves as a sensitive thermometer, which we employ to study the equilibration in the spin and density sector during a slow quench of the lattice depth.

Space-time airborne disease mapping applied to detect specific behaviour of varicella in Valencia, Spain.

PubMed

Iftimi, Adina; Montes, Francisco; Santiyán, Ana Míguez; Martínez-Ruiz, Francisco

2015-01-01

Airborne diseases are one of humanity's most feared sicknesses and have regularly caused concern among specialists. Varicella is an airborne disease which usually affects children before the age of 10. Because of its nature, varicella gives rise to interesting spatial, temporal and spatio-temporal patterns. This paper studies spatio-temporal exploratory analysis tools to detect specific behaviour of varicella in the city of Valencia, Spain, from 2008 to 2013. These methods have shown a significant association between the spatial and the temporal component, confirmed by the space-time models applied to the data. High relative risk of varicella is observed in economically disadvantaged regions, areas less involved in vaccination programmes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Detection and Analysis of Complex Patterns of Ice Dynamics in Antarctica from ICESat Laser Altimetry

NASA Astrophysics Data System (ADS)

Babonis, Gregory Scott

There remains much uncertainty in estimating the amount of Antarctic ice mass change, its dynamic component, and its spatial and temporal patterns. This work remedies the limitations of previous studies by generating the first detailed reconstruction of total and dynamic ice thickness and mass changes across Antarctica, from ICESat satellite altimetry observations in 2003-2009 using the Surface Elevation Reconstruction and Change Detection (SERAC) method. Ice sheet thickness changes are calculated with quantified error estimates for each time when ICESat flew over a ground-track crossover region, at approximately 110,000 locations across the Antarctic Ice Sheet. The time series are partitioned into changes due to surficial processes and ice dynamics. The new results markedly improve the spatial and temporal resolution of surface elevation, volume, and mass change rates for the AIS, and can be sampled at annual temporal resolutions. The results indicate a complex spatiotemporal pattern of dynamic mass loss in Antarctica, especially along individual outlet glaciers, and allow for the quantification of the annual contribution of Antarctic ice loss to sea level rise. Over 5000 individual locations exhibit either strong dynamic ice thickness change patterns, accounting for approximately 500 unique spatial clusters that identify regions likely influenced by subglacial hydrology. The spatial distribution and temporal behavior of these regions reveal the complexity and short-time scale variability in the subglacial hydrological system. From the 500 unique spatial clusters, over 370 represent newly identified, and not previously published, potential subglacial water bodies indicating an active subglacial hydrological system over a much larger region than previously observed. These numerous new observations of dynamic changes provide more than simply a larger set of data. Examination of both regional and local scale dynamic change patterns across Antarctica shows newly discovered connections between the geology and ice sheet dynamics of Antarctica, particularly along the boundary between East and West Antarctica in the Pagano Shear Zone. Additionally, increased dynamic activity is shown to concentrate in regions of Antarctica most likely to experience catastrophic failure and collapse in the future. Further quantification of mass and volume changes demonstrates that the methods described within allow for a true reconciliation between different satellite methods of measuring ice sheet mass and volume balance, and show that Antarctica is losing enough mass between 2003 and 2009 to raise global sea levels 0.1 mm/yr during that time. Additionally, analysis of local patterns of dynamic ice thickness changes shows that there is continued or increased ice loss, since before the ICESat mission period, in many of the coastal sectors of Antarctica.

Visually induced adaptation in three-dimensional organization of primate vestibuloocular reflex

NASA Technical Reports Server (NTRS)

Angelaki, D. E.; Hess, B. J.

1998-01-01

The adaptive plasticity of the spatial organization of the vestibuloocular reflex (VOR) has been investigated in intact and canal-plugged primates using 2-h exposure to conflicting visual (optokinetic, OKN) and vestibular rotational stimuli about mutually orthogonal axes (generating torsional VOR + vertical OKN, torsional VOR + horizontal OKN, vertical VOR + horizontal OKN, and horizontal VOR + vertical OKN). Adaptation protocols with 0.5-Hz (+/-18 degrees ) head movements about either an earth-vertical or an earth-horizontal axis induced orthogonal response components as high as 40-70% of those required for ideal adaptation. Orthogonal response gains were highest at the adapting frequency with phase leads present at lower and phase lags present at higher frequencies. Furthermore, the time course of adaptation, as well as orthogonal response dynamics were similar and relatively independent of the particular visual/vestibular stimulus combination. Low-frequency (0. 05 Hz, vestibular stimulus: +/-60 degrees ; optokinetic stimulus: +/-180 degrees ) adaptation protocols with head movements about an earth-vertical axis induced smaller orthogonal response components that did not exceed 20-40% of the head velocity stimulus (i.e., approximately 10% of that required for ideal adaptation). At the same frequency, adaptation with head movements about an earth-horizontal axis generated large orthogonal responses that reached values as high as 100-120% of head velocity after 2 h of adaptation (i.e., approximately 40% of ideal adaptation gains). The particular spatial and temporal response characteristics after low-frequency, earth-horizontal axis adaptation in both intact and canal-plugged animals strongly suggests that the orienting (and perhaps translational) but not inertial (velocity storage) components of the primate otolith-ocular system exhibit spatial adaptability. Due to the particular nested arrangement of the visual and vestibular stimuli, the optic flow pattern exhibited a significant component about the third spatial axis (i.e., orthogonal to the axes of rotation of the head and visual surround) at twice the oscillation frequency. Accordingly, the adapted VOR was characterized consistently by a third response component (orthogonal to both the axes of head and optokinetic drum rotation) at twice the oscillation frequency after earth-horizontal but not after earth-vertical axis 0.05-Hz adaptation. This suggests that the otolith-ocular (but not the semicircular canal-ocular) system can adaptively change its spatial organization at frequencies different from those of the head movement.

Impact of scale on morphological spatial pattern of forest

Treesearch

Katarzyna Ostapowicz; Peter Vogt; Kurt H. Riitters; Jacek Kozak; Christine Estreguil

2008-01-01

Assessing and monitoring landscape pattern structure from multi-scale land-cover maps can utilize morphological spatial pattern analysis (MSPA), only if various influences of scale are known and taken into account. This paper lays part of the foundation for applying MSPA analysis in landscape monitoring by quantifying scale effects on six classes of spatial patterns...

The walk is never random: subtle landscape effects shape gene flow in a continuous white-tailed deer population in the Midwestern United States

USGS Publications Warehouse

Robinson, Stacie J.; Samuel, Michael D.; Lopez, Davin L.; Shelton, Paul

2012-01-01

One of the pervasive challenges in landscape genetics is detecting gene flow patterns within continuous populations of highly mobile wildlife. Understanding population genetic structure within a continuous population can give insights into social structure, movement across the landscape and contact between populations, which influence ecological interactions, reproductive dynamics or pathogen transmission. We investigated the genetic structure of a large population of deer spanning the area of Wisconsin and Illinois, USA, affected by chronic wasting disease. We combined multiscale investigation, landscape genetic techniques and spatial statistical modelling to address the complex questions of landscape factors influencing population structure. We sampled over 2000 deer and used spatial autocorrelation and a spatial principal components analysis to describe the population genetic structure. We evaluated landscape effects on this pattern using a spatial autoregressive model within a model selection framework to test alternative hypotheses about gene flow. We found high levels of genetic connectivity, with gradients of variation across the large continuous population of white-tailed deer. At the fine scale, spatial clustering of related animals was correlated with the amount and arrangement of forested habitat. At the broader scale, impediments to dispersal were important to shaping genetic connectivity within the population. We found significant barrier effects of individual state and interstate highways and rivers. Our results offer an important understanding of deer biology and movement that will help inform the management of this species in an area where overabundance and disease spread are primary concerns.

Dual Tasking and Working Memory in Alcoholism: Relation to Frontocerebellar Circuitry

PubMed Central

Chanraud, Sandra; Pitel, Anne-Lise; Rohlfing, Torsten; Pfefferbaum, Adolf; Sullivan, Edith V

2010-01-01

Controversy exists regarding the role of cerebellar systems in cognition and whether working memory compromise commonly marking alcoholism can be explained by compromise of nodes of corticocerebellar circuitry. We tested 17 alcoholics and 31 age-matched controls with dual-task, working memory paradigms. Interference tasks competed with verbal and spatial working memory tasks using low (three item) or high (six item) memory loads. Participants also underwent structural MRI to obtain volumes of nodes of the frontocerebellar system. On the verbal working memory task, both groups performed equally. On the spatial working memory with the high-load task, the alcoholic group was disproportionately more affected by the arithmetic distractor than were controls. In alcoholics, volumes of the left thalamus and left cerebellar Crus I volumes were more robust predictors of performance in the spatial working memory task with the arithmetic distractor than the left frontal superior cortex. In controls, volumes of the right middle frontal gyrus and right cerebellar Crus I were independent predictors over the left cerebellar Crus I, left thalamus, right superior parietal cortex, or left middle frontal gyrus of spatial working memory performance with tracking interference. The brain–behavior correlations suggest that alcoholics and controls relied on the integrity of certain nodes of corticocerebellar systems to perform these verbal and spatial working memory tasks, but that the specific pattern of relationships differed by group. The resulting brain structure–function patterns provide correlational support that components of this corticocerebellar system not typically related to normal performance in dual-task conditions may be available to augment otherwise dampened performance by alcoholics. PMID:20410871

Perceived image quality with simulated segmented bifocal corrections

PubMed Central

Dorronsoro, Carlos; Radhakrishnan, Aiswaryah; de Gracia, Pablo; Sawides, Lucie; Marcos, Susana

2016-01-01

Bifocal contact or intraocular lenses use the principle of simultaneous vision to correct for presbyopia. A modified two-channel simultaneous vision simulator provided with an amplitude transmission spatial light modulator was used to optically simulate 14 segmented bifocal patterns (+ 3 diopters addition) with different far/near pupillary distributions of equal energy. Five subjects with paralyzed accommodation evaluated image quality and subjective preference through the segmented bifocal corrections. There are strong and systematic perceptual differences across the patterns, subjects and observation distances: 48% of the conditions evaluated were significantly preferred or rejected. Optical simulations (in terms of through-focus Strehl ratio from Hartmann-Shack aberrometry) accurately predicted the pattern producing the highest perceived quality in 4 out of 5 patients, both for far and near vision. These perceptual differences found arise primarily from optical grounds, but have an important neural component. PMID:27895981

Inferring Population Genetic Structure in Widely and Continuously Distributed Carnivores: The Stone Marten (Martes foina) as a Case Study

PubMed Central

Vergara, María; Basto, Mafalda P.; Madeira, María José; Gómez-Moliner, Benjamín J.; Santos-Reis, Margarida; Fernandes, Carlos; Ruiz-González, Aritz

2015-01-01

The stone marten is a widely distributed mustelid in the Palaearctic region that exhibits variable habitat preferences in different parts of its range. The species is a Holocene immigrant from southwest Asia which, according to fossil remains, followed the expansion of the Neolithic farming cultures into Europe and possibly colonized the Iberian Peninsula during the Early Neolithic (ca. 7,000 years BP). However, the population genetic structure and historical biogeography of this generalist carnivore remains essentially unknown. In this study we have combined mitochondrial DNA (mtDNA) sequencing (621 bp) and microsatellite genotyping (23 polymorphic markers) to infer the population genetic structure of the stone marten within the Iberian Peninsula. The mtDNA data revealed low haplotype and nucleotide diversities and a lack of phylogeographic structure, most likely due to a recent colonization of the Iberian Peninsula by a few mtDNA lineages during the Early Neolithic. The microsatellite data set was analysed with a) spatial and non-spatial Bayesian individual-based clustering (IBC) approaches (STRUCTURE, TESS, BAPS and GENELAND), and b) multivariate methods [discriminant analysis of principal components (DAPC) and spatial principal component analysis (sPCA)]. Additionally, because isolation by distance (IBD) is a common spatial genetic pattern in mobile and continuously distributed species and it may represent a challenge to the performance of the above methods, the microsatellite data set was tested for its presence. Overall, the genetic structure of the stone marten in the Iberian Peninsula was characterized by a NE-SW spatial pattern of IBD, and this may explain the observed disagreement between clustering solutions obtained by the different IBC methods. However, there was significant indication for contemporary genetic structuring, albeit weak, into at least three different subpopulations. The detected subdivision could be attributed to the influence of the rivers Ebro, Tagus and Guadiana, suggesting that main watercourses in the Iberian Peninsula may act as semi-permeable barriers to gene flow in stone martens. To our knowledge, this is the first phylogeographic and population genetic study of the species at a broad regional scale. We also wanted to make the case for the importance and benefits of using and comparing multiple different clustering and multivariate methods in spatial genetic analyses of mobile and continuously distributed species. PMID:26222680

Inferring Population Genetic Structure in Widely and Continuously Distributed Carnivores: The Stone Marten (Martes foina) as a Case Study.

PubMed

Vergara, María; Basto, Mafalda P; Madeira, María José; Gómez-Moliner, Benjamín J; Santos-Reis, Margarida; Fernandes, Carlos; Ruiz-González, Aritz

2015-01-01

The stone marten is a widely distributed mustelid in the Palaearctic region that exhibits variable habitat preferences in different parts of its range. The species is a Holocene immigrant from southwest Asia which, according to fossil remains, followed the expansion of the Neolithic farming cultures into Europe and possibly colonized the Iberian Peninsula during the Early Neolithic (ca. 7,000 years BP). However, the population genetic structure and historical biogeography of this generalist carnivore remains essentially unknown. In this study we have combined mitochondrial DNA (mtDNA) sequencing (621 bp) and microsatellite genotyping (23 polymorphic markers) to infer the population genetic structure of the stone marten within the Iberian Peninsula. The mtDNA data revealed low haplotype and nucleotide diversities and a lack of phylogeographic structure, most likely due to a recent colonization of the Iberian Peninsula by a few mtDNA lineages during the Early Neolithic. The microsatellite data set was analysed with a) spatial and non-spatial Bayesian individual-based clustering (IBC) approaches (STRUCTURE, TESS, BAPS and GENELAND), and b) multivariate methods [discriminant analysis of principal components (DAPC) and spatial principal component analysis (sPCA)]. Additionally, because isolation by distance (IBD) is a common spatial genetic pattern in mobile and continuously distributed species and it may represent a challenge to the performance of the above methods, the microsatellite data set was tested for its presence. Overall, the genetic structure of the stone marten in the Iberian Peninsula was characterized by a NE-SW spatial pattern of IBD, and this may explain the observed disagreement between clustering solutions obtained by the different IBC methods. However, there was significant indication for contemporary genetic structuring, albeit weak, into at least three different subpopulations. The detected subdivision could be attributed to the influence of the rivers Ebro, Tagus and Guadiana, suggesting that main watercourses in the Iberian Peninsula may act as semi-permeable barriers to gene flow in stone martens. To our knowledge, this is the first phylogeographic and population genetic study of the species at a broad regional scale. We also wanted to make the case for the importance and benefits of using and comparing multiple different clustering and multivariate methods in spatial genetic analyses of mobile and continuously distributed species.

Interactions between Hillslope Hydraulic Response Function, Vegetation Organisation and Catchment Behaviour

NASA Astrophysics Data System (ADS)

Schymanski, Stanislaus J.; McDonnell, Jeffrey; Or, Dani

2013-04-01

The behaviour of a catchment is sensitive to the pattern and organisation of its components (hillslopes, land cover etc.). Explaining observed organisation and emergence of pattern requires understanding of key organising principles, recognising that albeit similarities, the larger scale behaviour is likely to differ from that of individual components. In other words, the whole does not necessarily behave like the sum of its parts, because the arrangement of the parts matters. For example, hillslopes involve complex and hydrologically interacting elements (rapid flow pathways, depression storage, slope, and variable soil thickness) that shape hillslope hydrologic response in ways that cannot be represented by a collection of pores as implied by standard hydraulic functions. Additionally, inherent spatial and temporal variability of vegetation prohibits detailed and mechanistic parameterisation of root water uptake and evapotranspiration. The interplay of hydrologic hillslope function, climatic forcing and vegetation dynamics translates into complex catchment behaviour at the outlet. Vegetation, one of the most dynamic determinants of catchment behaviour, may interact with its environment by varying different elements such as root system properties, foliage properties and spatial arrangement. These interactions span different temporal scales from minutes (stomatal conductance) to decades (spatial arrangement) all of which may shape evapotranspiration and hence catchment behaviour. Evidence suggests that vegetation adapts to its environment in a self-organised, predictable way, guided by some overarching goal function, such as maximum net carbon profit or maximum entropy production. Appropriate optimality considerations under prevailing constraints enabled predictions of spatial heterogeneity of vegetation cover, or temporal dynamics of root distribution, canopy properties and water use. The hydrologic hillslope behaviour (e.g., surface and subsurface water fluxes and storage) is a powerful ingredient that defines boundary conditions for vegetation self-organisation. To systematically evaluate the role of this element, we propose a Hillslope Hydraulic Response Function (HHRF) a standardised parameterisation framework based on simplified and analytical representation of a prototypic hillslope. The HHRF uses a few geometrical parameters and intrinsic parameters to represent hillslope response in terms of fluxes and storage dynamics. Such an approach has been instrumental in deducing hydrologic response of watersheds (Kirchner, 2009, WRR) but has not been used for systematic parameterisation of HHRF. Here we separate out the biotic and abiotic components of catchment behaviour and test the sensitivity of vegetation and the catchment water balance to different hypothetical parameterisations of the HHRF.

[Soil and forest structure in the Colombian Amazon].

PubMed

Calle-Rendón, Bayron R; Moreno, Flavio; Cárdenas López, Dairon

2011-09-01

Forests structural differences could result of environmental variations at different scales. Because soils are an important component of plant's environment, it is possible that edaphic and structural variables are associated and that, in consequence, spatial autocorrelation occurs. This paper aims to answer two questions: (1) are structural and edaphic variables associated at local scale in a terra firme forest of Colombian Amazonia? and (2) are these variables regionalized at the scale of work? To answer these questions we analyzed the data of a 6ha plot established in a terra firme forest of the Amacayacu National Park. Structural variables included basal area and density of large trees (diameter > or = 10cm) (Gdos and Ndos), basal area and density of understory individuals (diameter < 10cm) (Gsot and Nsot) and number of species of large trees (sp). Edaphic variables included were pH, organic matter, P, Mg, Ca, K, Al, sand, silt and clay. Structural and edaphic variables were reduced through a principal component analysis (PCA); then, the association between edaphic and structural components from PCA was evaluated by multiple regressions. The existence of regionalization of these variables was studied through isotropic variograms, and autocorrelated variables were spatially mapped. PCA found two significant components for structure, corresponding to the structure of large trees (G, Gdos, Ndos and sp) and of small trees (N, Nsot and Gsot), which explained 43.9% and 36.2% of total variance, respectively. Four components were identified for edaphic variables, which globally explained 81.9% of total variance and basically represent drainage and soil fertility. Regression analyses were significant (p < 0.05) and showed that the structure of both large and small trees is associated with greater sand contents and low soil fertility, though they explained a low proportion of total variability (R2 was 4.9% and 16.5% for the structure of large trees and small tress, respectively). Variables with spatial autocorrelation were the structure of small trees, Al, silt, and sand. Among them, Nsot and sand content showed similar patterns of spatial distribution inside the plot.

Shades of grey; Assessing the contribution of the magno- and parvocellular systems to neural processing of the retinal input in the human visual system from the influence of neural population size and its discharge activity on the VEP.

PubMed

Marcar, Valentine L; Baselgia, Silvana; Lüthi-Eisenegger, Barbara; Jäncke, Lutz

2018-03-01

Retinal input processing in the human visual system involves a phasic and tonic neural response. We investigated the role of the magno- and parvocellular systems by comparing the influence of the active neural population size and its discharge activity on the amplitude and latency of four VEP components. We recorded the scalp electric potential of 20 human volunteers viewing a series of dartboard images presented as a pattern reversing and pattern on-/offset stimulus. These patterns were designed to vary both neural population size coding the temporal- and spatial luminance contrast property and the discharge activity of the population involved in a systematic manner. When the VEP amplitude reflected the size of the neural population coding the temporal luminance contrast property of the image, the influence of luminance contrast followed the contrast response function of the parvocellular system. When the VEP amplitude reflected the size of the neural population responding to the spatial luminance contrast property the image, the influence of luminance contrast followed the contrast response function of the magnocellular system. The latencies of the VEP components examined exhibited the same behavior across our stimulus series. This investigation demonstrates the complex interplay of the magno- and parvocellular systems on the neural response as captured by the VEP. It also demonstrates a linear relationship between stimulus property, neural response, and the VEP and reveals the importance of feedback projections in modulating the ongoing neural response. In doing so, it corroborates the conclusions of our previous study.

Scale linkage and contingency effects of field-scale and hillslope-scale controls of long-term soil erosion: Anthropogeomorphic sediment flux in agricultural loess watersheds of Southern Germany

NASA Astrophysics Data System (ADS)

Houben, Peter

2008-10-01

Agricultural landscapes with a millennial-scale history of cultivation are common in many loess areas of central Europe. Over time, patterns of erosion and sedimentation have been continually modified via the variable imposition of anthropogenic discontinuities and linkages on fragmented hillslope sediment cascades, which eventually caused the complicated soilscape pattern. These field records challenge topographically oriented models of hillslope erosion and simple predictions of longer-term change of spatial soilscape by cultivation activities. A thorough understanding how soilscape patterns form in the long-term, however, is essential to develop spatial concepts of the sediment budget, particularly for the spatial modeling of anthropogenic hillslope sediment flux using GIS. In this study I used extensive datasets of anthropogenic soil truncation and burial in a typical undulating loess watershed in southern Germany (10 km 2, Wetterau Basin, N of Frankfurt a.M.). Spatial soilscape properties and historic sediment flux, as caused by cultivation over seven millennia, were evaluated by these data. The soilscape pattern on the low-gradient hillslopes of the study area was found to be marked by a statistical near-random pattern of varying depth (thickness) of truncation and overthickened burial. Moreover, it was shown that truncation and burial had developed independently from each other and did not correlate with either hillslope gradient or downslope curvature. Hence, in the field any combination of (few) nearly preserved, severely truncated or completely removed soil profiles with either no, some or a thick sediment cover is present, thereby lacking an obvious spatial pattern. Here, I suggest putting long-term change of the soilscape into a contextual anthropogeomorphic systems perspective, that accommodates components of human-induced soil erosion operating at different spatial scales to interpret the longer-term spatial consequences at the hillslope-system level. In the study area, system scale linkages are marked by the spatial intersection of a finer-scaled managed field system with a broader hillslope-scale framework of 'natural' erosion controls. In the low-gradient study area, field borders exert control over the spatial reference of soil erosion and sedimentation sites. Over time, this brought about a growing historical and spatial contingency change to the soilscape, because of arbitrary spatial changes of the field system which are inherent in its socio-agricultural maintenance. Thus, the very low-gradient and low-erosivity setting of the study area have singled out the agency of human-induced spatial and connectivity controls and contingency for long-term spatial hillslope sediment flux. Although these findings may be less true for different settings, they allow for deriving a generic conceptual model of the linkages between 'natural' and anthropogenic subsystems to interpret the effects of long-term human-induced sediment flux. Accordingly, the resulting balance between on-hillslope net storage and net delivery to streams is scaling with basic physiographic properties of erosivity and sedimentation as well as the degree of anthropogenic hillslope fragmentation. For loess areas in Europe variable fields are fundamental anthropogeomorphic units that determine appropriate system scaling for historic sediment flux analysis and constrain retrodiction and prediction of changing fluxes at a point and a time at watershed scales. Methodical implications address adequate sampling strategies to record soilscape change, as a result of which a critical review of the applicability of the catena concept to long-cultivated hillslopes in central Europe was included. Finally, the suggested refined generic model of long-term, human-controlled sediment flux involves a number of research opportunities, particularly for linking modeling approaches to long-term field records of cultivation-related change in the soilscape.

Long Term Precipitation Pattern Identification and Derivation of Non Linear Precipitation Trend in a Catchment using Singular Spectrum Analysis

NASA Astrophysics Data System (ADS)

Unnikrishnan, Poornima; Jothiprakash, Vinayakam

2017-04-01

Precipitation is the major component in the hydrologic cycle. Awareness of not only the total amount of rainfall pertaining to a catchment, but also the pattern of its spatial and temporal distribution are equally important in the management of water resources systems in an efficient way. Trend is the long term direction of a time series; it determines the overall pattern of a time series. Singular Spectrum Analysis (SSA) is a time series analysis technique that decomposes the time series into small components (eigen triples). This property of the method of SSA has been utilized to extract the trend component of the rainfall time series. In order to derive trend from the rainfall time series, we need to select components corresponding to trend from the eigen triples. For this purpose, periodogram analysis of the eigen triples have been proposed to be coupled with SSA, in the present study. In the study, seasonal data of England and Wales Precipitation (EWP) for a time period of 1766-2013 have been analyzed and non linear trend have been derived out of the precipitation data. In order to compare the performance of SSA in deriving trend component, Mann Kendall (MK) test is also used to detect trends in EWP seasonal series and the results have been compared. The result showed that the MK test could detect the presence of positive or negative trend for a significance level, whereas the proposed methodology of SSA could extract the non-linear trend present in the rainfall series along with its shape. We will discuss further the comparison of both the methodologies along with the results in the presentation.

Species sorting and patch dynamics in harlequin metacommunities affect the relative importance of environment and space.

PubMed

Leibold, Mathew A; Loeuille, Nicolas

2015-12-01

Metacommunity theory indicates that variation in local community structure can be partitioned into components including those related to local environmental conditions vs. spatial effects and that these can be quantified using statistical methods based on variation partitioning. It has been hypothesized that joint associations of community composition with environment and space could be due to patch dynamics involving colonization-extinction processes in environmentally heterogeneous landscapes but this has yet to be theoretically shown. We develop a two-patch, type-two, species competition model in such a "harlequin" landscape (where different patches have different environments) to evaluate how composition is related to environmental and spatial effects as a function of background extinction rate. Using spatially implicit analytical models, we find that the environmental association of community composition declines with extinction rate as expected. Using spatially explicit simulation models, we further find that there is an increase in the spatial structure with extinction due to spatial patterning into clusters that are not related to environmental conditions but that this increase is limited. Natural metacommunities often show both environment and spatial determination even under conditions of relatively high isolation and these could be more easily explained by our model than alternative metacommunity models.

Preliminary studies of radiation coupling between remote soft X-ray laser amplifiers

NASA Astrophysics Data System (ADS)

Cairns, G.; Lewis, C. L. S.; Macphee, A. G.; Neely, D.; Holden, M.; Krishnan, J.; Tallents, G. J.; Key, M. H.; Norreys, P. N.; Smith, C. G.; Zhang, J.; Holden, P. B.; Pert, G. J.; Plowes, J.; Ramsden, S. A.

1994-01-01

Coupling of a soft X-ray laser beam with a relaying concave mirror in a sequentially pumped amplifier geometry using the Ne-like Ge system has been studied experimentally. Preliminary observations indicate an increase in the spatial coherence of the amplified relayed beam. In addition, near-field imaging of one of the amplifier plasmas shows a double-lobed intensity pattern of the emergent beam indicating refractive guiding of the amplified beam with components both normal and tangential to the target surface.

COMPARISON OF SPATIAL PATTERNS OF POLLUTANT DISTRIBUTION WITH CMAQ PREDICTIONS

EPA Science Inventory

To evaluate the Models-3/Community Multiscale Air Quality (CMAQ) modeling system in reproducing the spatial patterns of aerosol concentrations over the country on timescales of months and years, the spatial patterns of model output are compared with those derived from observation...

Wave spectral energy variability in the northeast Pacific

USGS Publications Warehouse

Bromirski, P.D.; Cayan, D.R.; Flick, R.E.

2005-01-01

The dominant characteristics of wave energy variability in the eastern North Pacific are described from NOAA National Data Buoy Center (NDBC) buoy data collected from 1981 to 2003. Ten buoys at distributed locations were selected for comparison based on record duration and data continuity. Long-period (LP) [T > 12] s, intermediate-period [6 ??? T ??? 12] s, and short-period [T < 6] s wave spectral energy components are considered separately. Empirical orthogonal function (EOF) analyses of monthly wave energy anomalies reveal that all three wave energy components exhibit similar patterns of spatial variability. The dominant mode represents coherent heightened (or diminished) wave energy along the West Coast from Alaska to southern California, as indicated by composites of the 700 hPa height field. The second EOF mode reveals a distinct El Nin??o-Southern Oscillation (ENSO)-associated spatial distribution of wave energy, which occurs when the North Pacific storm track is extended unusually far south or has receded to the north. Monthly means and principal components (PCs) of wave energy levels indicate that the 1997-1998 El Nin??o winter had the highest basin-wide wave energy within this record, substantially higher than the 1982-1983 El Nin??o. An increasing trend in the dominant PC of LP wave energy suggests that storminess has increased in the northeast Pacific since 1980. This trend is emphasized at central eastern North Pacific locations. Patterns of storminess variability are consistent with increasing activity in the central North Pacific as well as the tendency for more extreme waves in the south during El Nin??o episodes and in the north during La Nin??a. Copyright 2005 by the American Geophysical Union.

Spatial and temporal influences on the physiological condition of invasive silver carp.

PubMed

Liss, Stephanie A; Sass, Greg G; Suski, Cory D

2013-01-01

We quantified nutritional and stress parameters (alkaline phosphatase, cholesterol, protein, triglycerides, cortisol, and glucose) in invasive silver carp (Hypophthalmichthys molitrix) inhabiting four large rivers throughout three distinct time periods in the Midwestern USA. Examining the basic biology and ecology of an invasive species is crucial to gain an understanding of the interaction between an organism and its environment. Analysis of the physiological condition of wild-caught silver carp across broad spatial and temporal scales is essential because stress and nutritional parameters can link individuals to their habitats and vary among populations across environments. During each time period, we collected blood samples from individual silver carp in the Illinois River and portions of the Mississippi, Ohio, and Wabash rivers in Illinois. We tested for relationships between silver carp nutrition and stress across rivers, reaches within rivers, and time periods. Principal component analyses separated physiological parameters into a stress component (cortisol and glucose) and two nutritional components representative of short-term feeding (alkaline phosphatase, protein, and triglycerides) and body energy reserves (cholesterol and protein). Akaike's information criterion suggested that time period had the greatest influence on stress. Stress levels were consistent in all four rivers, and declined across time periods. Akaike's information criterion also suggested that interactions of time period and river had the greatest influence on short-term feeding and body energy reserves. There was no specific pattern across time periods within each river, nor was there a pattern across rivers. Our results provide a better understanding of nutritional and stress conditions in invasive silver carp across a broad landscape and temporal scale, with implications for managing and predicting the spread of this species.

Spatial Patterns and Risk Assessment of Heavy Metals in Soils in a Resource-Exhausted City, Northeast China

PubMed Central

Chen, Hongwei; An, Jing; Wei, Shuhe; Gu, Jian

2015-01-01

Northeast China is an intensive area of resource-exhausted city, which is facing the challenges of industry conversion and sustainable development. In order to evaluate the soil environmental quality influenced by mining activities over decades, the concentration and spatial distribution of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and Zinc (Zn) in surface soils (0-20cm) of a typical resource-exhausted city were investigated by analyzing 306 soil samples. The results showed that the average concentrations in the samples were 6.17 mg/kg for As, 0.19 mg/kg for Cd, 51.08 mg/kg for Cr, 23.27 mg/kg for Cu, 31.15 mg/kg for Ni, 22.17 mg/kg for Pb, and 54.21 mg/kg for Zn. Metals distribution maps produced by using the inverse distance weighted interpolation method and results revealed that all investigated metals showed distinct geographical patterns, and the concentrations were higher in urban and industrial areas than in farmland. Pearson correlation and principal component analysis showed that there were significant positive correlations (p<0.05) between all of the metals, and As, Cd, Cr, Mn, Ni, Pb, and Zn were closely associated with the first principal component (PC1), which explained 39.81% of the total variance. Cu and As were mainly associated with the second component (PC2). Based on the calculated Nemerow pollution index, percentage for slightly polluted (1

Generation of High Resolution Water Vapour Fields from GPS Observations and Integration With ECMWF and MODIS

NASA Astrophysics Data System (ADS)

Yu, C.; Li, Z.; Penna, N. T.

2016-12-01

Precipitable water vapour (PWV) can be routinely retrieved from ground-based GPS arrays in all-weather conditions and also in real-time. But to provide dense spatial coverage maps, for example for calibrating SAR images, for correcting atmospheric effects in Network RTK GPS positioning and which may be used for numerical weather prediction, the pointwise GPS PWV measurements must be interpolated. Several previous interpolation studies have addressed the importance of the elevation dependency of water vapour, but it is often a challenge to separate elevation-dependent tropospheric delays from turbulent components. We present a tropospheric turbulence iterative decomposition model that decouples the total PWV into (i) a stratified component highly correlated with topography which therefore delineates the vertical troposphere profile, and (ii) a turbulent component resulting from disturbance processes (e.g., severe weather) in the troposphere which trigger uncertain patterns in space and time. We will demonstrate that the iterative decoupled interpolation model generates improved dense tropospheric water vapour fields compared with elevation dependent models, with similar accuracies obtained over both flat and mountainous terrain, as well as for both inland and coastal areas. We will also show that our GPS-based model may be enhanced with ECMWF zenith tropospheric delay and MODIS PWV, producing multi-data sources high temporal-spatial resolution PWV fields. These fields were applied to Sentinel-1 SAR interferograms over the Los Angeles region, for which a maximum noise reduction due to atmosphere artifacts reached 85%. The results reveal that the turbulent troposphere noise, especially those in a SAR image, often occupy more than 50% of the total zenith tropospheric delay and exert systematic, rather than random patterns.

Spatial Patterns in Alternative States and Thresholds: A Missing Link for Management of Landscapes?

USDA-ARS?s Scientific Manuscript database

The detection of threshold dynamics (and other dynamics of interest) would benefit from explicit representations of spatial patterns of disturbance, spatial dependence in responses to disturbance, and the spatial structure of feedbacks in the design of monitoring and management strategies. Spatially...

Spatial reconstruction of single-cell gene expression data.

PubMed

Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv

2015-05-01

Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

Spatial reconstruction of single-cell gene expression

PubMed Central

Satija, Rahul; Farrell, Jeffrey A.; Gennert, David; Schier, Alexander F.; Regev, Aviv

2015-01-01

Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. PMID:25867923

Varying congruence among spatial patterns of vascular plants and vertebrates based on habitat groups.

PubMed

Xu, Haigen; Cao, Yun; Cao, Mingchang; Wu, Jun; Wu, Yi; Le, Zhifang; Cui, Peng; Li, Jiaqi; Ma, Fangzhou; Liu, Li; Hu, Feilong; Chen, Mengmeng; Tong, Wenjun

2017-11-01

Proxies are adopted to represent biodiversity patterns due to inadequate information for all taxa. Despite the wide use of proxies, their efficacy remains unclear. Previous analyses focused on overall species richness for fewer groups, affecting the generality and depth of inference. Biological taxa often exhibit very different habitat preferences. Habitat groupings may be an appropriate approach to advancing the study of richness patterns. Diverse geographical patterns of species richness and their potential mechanisms were then examined for habitat groups. We used a database of the spatial distribution of 32,824 species of mammals, birds, reptiles, amphibians and plants from 2,376 counties across China, divided the five taxa into 30 habitat groups, calculated Spearman correlations of species richness among taxa and habitat groups, and tested five hypotheses about richness patterns using multivariate models. We identified one major group [i.e., forest- and shrub-dependent (FS) groups], and some minor groups such as grassland-dependent vertebrates and desert-dependent vertebrates. There were mostly high or moderate correlations among FS groups, but mostly low or moderate correlations among other habitat groups. The prominent variables differed among habitat groups of the same taxon, such as birds and reptiles. The sets of predictors were also different within the same habitat, such as forests, grasslands, and deserts. Average correlations among the same habitat groups of vertebrates and among habitat groups of a single taxon were low or moderate, except correlations among FS groups. The sets of prominent variables of species richness differed strongly among habitat groups, although elevation range was the most important variable for most FS groups. The ecological and evolutionary processes that underpin richness patterns might be disparate among different habitat groups. Appropriate groupings based on habitats could reveal important patterns of richness gradients and valuable biodiversity components.

Spatially-resolved mean flow and turbulence help explain observed erosion and deposition patterns of snow over Antarctic sea ice

NASA Astrophysics Data System (ADS)

Trujillo, E.; Giometto, M. G.; Leonard, K. C.; Maksym, T. L.; Meneveau, C. V.; Parlange, M. B.; Lehning, M.

2014-12-01

Sea ice-atmosphere interactions are major drivers of patterns of sea ice drift and deformations in the Polar regions, and affect snow erosion and deposition at the surface. Here, we combine analyses of sea ice surface topography at very high-resolutions (1-10 cm), and Large Eddy Simulations (LES) to study surface drag and snow erosion and deposition patterns from process scales to floe scales (1 cm - 100 m). The snow/ice elevations were obtained using a Terrestrial Laser Scanner during the SIPEX II (Sea Ice Physics and Ecosystem eXperiment II) research voyage to East Antarctica (September-November 2012). LES are performed on a regular domain adopting a mixed pseudo-spectral/finite difference spatial discretization. A scale-dependent dynamic subgrid-scale model based on Lagrangian time averaging is adopted to determine the eddy-viscosity in the bulk of the flow. Effects of larger-scale features of the surface on wind flows (those features that can be resolved in the LES) are accounted for through an immersed boundary method. Conversely, drag forces caused by subgrid-scale features of the surface should be accounted for through a parameterization. However, the effective aerodynamic roughness parameter z0 for snow/ice is not known. Hence, a novel dynamic approach is utilized, in which z0 is determined using the constraint that the total momentum flux (drag) must be independent on grid-filter scale. We focus on three ice floe surfaces. The first of these surfaces (October 6, 2012) is used to test the performance of the model, validate the algorithm, and study the spatial distributed fields of resolved and modeled stress components. The following two surfaces, scanned at the same location before and after a snow storm event (October 20/23, 2012), are used to propose an application to study how spatially resolved mean flow and turbulence relates to observed patterns of snow erosion and deposition. We show how erosion and deposition patterns are correlated with the computed stresses, with modeled stresses having higher explanatory power. Deposition is mainly occurring in wake regions of specific ridges that strongly affect wind flow patterns. These larger ridges also lock in place elongated streaks of relatively high speeds with axes along the stream-wise direction, and which are largely responsible for the observed erosion.

A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface.

PubMed

Zhou, Bangyan; Wu, Xiaopei; Lv, Zhao; Zhang, Lei; Guo, Xiaojin

2016-01-01

Independent component analysis (ICA) as a promising spatial filtering method can separate motor-related independent components (MRICs) from the multichannel electroencephalogram (EEG) signals. However, the unpredictable burst interferences may significantly degrade the performance of ICA-based brain-computer interface (BCI) system. In this study, we proposed a new algorithm frame to address this issue by combining the single-trial-based ICA filter with zero-training classifier. We developed a two-round data selection method to identify automatically the badly corrupted EEG trials in the training set. The "high quality" training trials were utilized to optimize the ICA filter. In addition, we proposed an accuracy-matrix method to locate the artifact data segments within a single trial and investigated which types of artifacts can influence the performance of the ICA-based MIBCIs. Twenty-six EEG datasets of three-class motor imagery were used to validate the proposed methods, and the classification accuracies were compared with that obtained by frequently used common spatial pattern (CSP) spatial filtering algorithm. The experimental results demonstrated that the proposed optimizing strategy could effectively improve the stability, practicality and classification performance of ICA-based MIBCI. The study revealed that rational use of ICA method may be crucial in building a practical ICA-based MIBCI system.

Spatial diversity of bacterioplankton communities in surface water of northern South China Sea.

PubMed

Li, Jialin; Li, Nan; Li, Fuchao; Zou, Tao; Yu, Shuxian; Wang, Yinchu; Qin, Song; Wang, Guangyi

2014-01-01

The South China Sea is one of the largest marginal seas, with relatively frequent passage of eddies and featuring distinct spatial variation in the western tropical Pacific Ocean. Here, we report a phylogenetic study of bacterial community structures in surface seawater of the northern South China Sea (nSCS). Samples collected from 31 sites across large environmental gradients were used to construct clone libraries and yielded 2,443 sequences grouped into 170 OTUs. Phylogenetic analysis revealed 23 bacterial classes with major components α-, β- and γ-Proteobacteria, as well as Cyanobacteria. At class and genus taxon levels, community structure of coastal waters was distinctively different from that of deep-sea waters and displayed a higher diversity index. Redundancy analyses revealed that bacterial community structures displayed a significant correlation with the water depth of individual sampling sites. Members of α-Proteobacteria were the principal component contributing to the differences of the clone libraries. Furthermore, the bacterial communities exhibited heterogeneity within zones of upwelling and anticyclonic eddies. Our results suggested that surface bacterial communities in nSCS had two-level patterns of spatial distribution structured by ecological types (coastal VS. oceanic zones) and mesoscale physical processes, and also provided evidence for bacterial phylogenetic phyla shaped by ecological preferences.

Spatial arrangement of faults and opening-mode fractures

NASA Astrophysics Data System (ADS)

Laubach, S. E.; Lamarche, J.; Gauthier, B. D. M.; Dunne, W. M.; Sanderson, David J.

2018-03-01

Spatial arrangement is a fundamental characteristic of fracture arrays. The pattern of fault and opening-mode fracture positions in space defines structural heterogeneity and anisotropy in a rock volume, governs how faults and fractures affect fluid flow, and impacts our understanding of the initiation, propagation and interactions during the formation of fracture patterns. This special issue highlights recent progress with respect to characterizing and understanding the spatial arrangements of fault and fracture patterns, providing examples over a wide range of scales and structural settings. Five papers describe new methods and improvements of existing techniques to quantify spatial arrangement. One study unravels the time evolution of opening-mode fracture spatial arrangement, which are data needed to compare natural patterns with progressive fracture growth in kinematic and mechanical models. Three papers investigate the role of evolving diagenesis in localizing fractures by mechanical stratigraphy and nine discuss opening-mode fracture spatial arrangement. Two papers show the relevance of complex cluster patterns to unconventional reservoirs through examples of fractures in tight gas sandstone horizontal wells, and a study of fracture arrangement in shale. Four papers demonstrate the roles of folds in fracture localization and the development spatial patterns. One paper models along-fault friction and fluid pressure and their effects on fault-related fracture arrangement. Contributions address deformation band patterns in carbonate rocks and fault size and arrangement above a detachment fault. Three papers describe fault and fracture arrangements in basement terrains, and three document fracture patterns in shale. This collection of papers points toward improvement in field methods, continuing improvements in computer-based data analysis and creation of synthetic fracture patterns, and opportunities for further understanding fault and fracture attributes in the subsurface through coupled spatial, size, and pattern analysis.

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template

PubMed Central

Dong, Xiaoli; Grimm, Nancy B.

2017-01-01

Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, “wetland”) system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995–2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns. PMID:28559326

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template.

PubMed

Dong, Xiaoli; Ruhí, Albert; Grimm, Nancy B

2017-06-13

Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, "wetland") system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995-2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns.

Ecological Importance of Large-Diameter Trees in a Temperate Mixed-Conifer Forest

PubMed Central

Lutz, James A.; Larson, Andrew J.; Swanson, Mark E.; Freund, James A.

2012-01-01

Large-diameter trees dominate the structure, dynamics and function of many temperate and tropical forests. Although both scaling theory and competition theory make predictions about the relative composition and spatial patterns of large-diameter trees compared to smaller diameter trees, these predictions are rarely tested. We established a 25.6 ha permanent plot within which we tagged and mapped all trees ≥1 cm dbh, all snags ≥10 cm dbh, and all shrub patches ≥2 m2. We sampled downed woody debris, litter, and duff with line intercept transects. Aboveground live biomass of the 23 woody species was 507.9 Mg/ha, of which 503.8 Mg/ha was trees (SD = 114.3 Mg/ha) and 4.1 Mg/ha was shrubs. Aboveground live and dead biomass was 652.0 Mg/ha. Large-diameter trees comprised 1.4% of individuals but 49.4% of biomass, with biomass dominated by Abies concolor and Pinus lambertiana (93.0% of tree biomass). The large-diameter component dominated the biomass of snags (59.5%) and contributed significantly to that of woody debris (36.6%). Traditional scaling theory was not a good model for either the relationship between tree radii and tree abundance or tree biomass. Spatial patterning of large-diameter trees of the three most abundant species differed from that of small-diameter conspecifics. For A. concolor and P. lambertiana, as well as all trees pooled, large-diameter and small-diameter trees were spatially segregated through inter-tree distances <10 m. Competition alone was insufficient to explain the spatial patterns of large-diameter trees and spatial relationships between large-diameter and small-diameter trees. Long-term observations may reveal regulation of forest biomass and spatial structure by fire, wind, pathogens, and insects in Sierra Nevada mixed-conifer forests. Sustaining ecosystem functions such as carbon storage or provision of specialist species habitat will likely require different management strategies when the functions are performed primarily by a few large trees as opposed to many smaller trees. PMID:22567132

The mosaic structure of plasma bulk flows in the Earth's magnetotail

NASA Technical Reports Server (NTRS)

Ashour-Abdalla, M.; Richard, R. L.; Zelenyi, L. M.; Peroomian, V.; Bosqued, J. M.

1995-01-01

Moments of plasma distributions observed in the magnetotail vary with different time scales. In this paper we attempt to explain the observed variability on intermediate timescales of approximately 10-20 min that result from the simultaneous energization and spatial structuring of solar wind plasma in the distant magnetotail. These processes stimulate the formation of a system of spatially disjointed. highly accelerated filaments (beamlets) in the tail. We use the results from large-scale kinetic modeling of magnetotail formation from a plasma mantle source to calculate moments of ion distribution functions throughout the tail. Statistical restrictions related to the limited number of particles in our system naturally reduce the spatial resolution of our results, but we show that our model is valid on intermediate spatial scales Delta(x) x Delta(z) equal to approximately 1 R(sub E) x 1000 km. For these spatial scales the resulting pattern, which resembles a mosaic, appears to be quite variable. The complexity of the pattern is related to the spatial interference between beamlets accelerated at various locations within the distant tail which mirror in the strong near-Earth magnetic field. Global motion of the magnetotail results in the displacement of spacecraft with respect to this mosaic pattern and can produce variations in all of the moments (especially the x-component of the bulk velocity) on intermediate timescales. The results obtained enable us to view the magnetotail plasma as consisting of two different populations: a tailward-Earthward system of highly accelerated beamlets interfering with each other, and an energized quasithermal population which gradually builds as the Earth is approached. In the near-Earth tail, these populations merge into a hot quasi-isotropic ion population typical of the near-Earth plasma sheet. The transformation of plasma sheet boundary layer (PSBL) beam energy into central plasma sheet (CPS) quasi-thermal energy occurs in the absence of collisions or noise. This paper also clarifies the relationship between the global scale where an MHD description might be appropriate and the lower intermediate scales where MHD fails and large-scale kinetic theory should be used.

Mapping spatial patterns with morphological image processing

Treesearch

Peter Vogt; Kurt H. Riitters; Christine Estreguil; Jacek Kozak; Timothy G. Wade; James D. Wickham

2006-01-01

We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as 'perforated,' 'edge,' 'patch,' and 'core' with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the...

High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals.

PubMed

Marcon, Luciano; Diego, Xavier; Sharpe, James; Müller, Patrick

2016-04-08

The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems.

High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals

PubMed Central

Marcon, Luciano; Diego, Xavier; Sharpe, James; Müller, Patrick

2016-01-01

The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems. DOI: http://dx.doi.org/10.7554/eLife.14022.001 PMID:27058171

The neural basis of form and form-motion integration from static and dynamic translational Glass patterns: A rTMS investigation.

PubMed

Pavan, Andrea; Ghin, Filippo; Donato, Rita; Campana, Gianluca; Mather, George

2017-08-15

A long-held view of the visual system is that form and motion are independently analysed. However, there is physiological and psychophysical evidence of early interaction in the processing of form and motion. In this study, we used a combination of Glass patterns (GPs) and repetitive Transcranial Magnetic Stimulation (rTMS) to investigate in human observers the neural mechanisms underlying form-motion integration. GPs consist of randomly distributed dot pairs (dipoles) that induce the percept of an oriented stimulus. GPs can be either static or dynamic. Dynamic GPs have both a form component (i.e., orientation) and a non-directional motion component along the orientation axis. GPs were presented in two temporal intervals and observers were asked to discriminate the temporal interval containing the most coherent GP. rTMS was delivered over early visual area (V1/V2) and over area V5/MT shortly after the presentation of the GP in each interval. The results showed that rTMS applied over early visual areas affected the perception of static GPs, but the stimulation of area V5/MT did not affect observers' performance. On the other hand, rTMS was delivered over either V1/V2 or V5/MT strongly impaired the perception of dynamic GPs. These results suggest that early visual areas seem to be involved in the processing of the spatial structure of GPs, and interfering with the extraction of the global spatial structure also affects the extraction of the motion component, possibly interfering with early form-motion integration. However, visual area V5/MT is likely to be involved only in the processing of the motion component of dynamic GPs. These results suggest that motion and form cues may interact as early as V1/V2. Copyright © 2017 Elsevier Inc. All rights reserved.

Hierarchical analysis of spatial pattern and processes of Douglas-fir forests. Ph.D. Thesis, 10 Sep. 1991 Abstract Only

NASA Technical Reports Server (NTRS)

Bradshaw, G. A.

1995-01-01

There has been an increased interest in the quantification of pattern in ecological systems over the past years. This interest is motivated by the desire to construct valid models which extend across many scales. Spatial methods must quantify pattern, discriminate types of pattern, and relate hierarchical phenomena across scales. Wavelet analysis is introduced as a method to identify spatial structure in ecological transect data. The main advantage of the wavelet transform over other methods is its ability to preserve and display hierarchical information while allowing for pattern decomposition. Two applications of wavelet analysis are illustrated, as a means to: (1) quantify known spatial patterns in Douglas-fir forests at several scales, and (2) construct spatially-explicit hypotheses regarding pattern generating mechanisms. Application of the wavelet variance, derived from the wavelet transform, is developed for forest ecosystem analysis to obtain additional insight into spatially-explicit data. Specifically, the resolution capabilities of the wavelet variance are compared to the semi-variogram and Fourier power spectra for the description of spatial data using a set of one-dimensional stationary and non-stationary processes. The wavelet cross-covariance function is derived from the wavelet transform and introduced as a alternative method for the analysis of multivariate spatial data of understory vegetation and canopy in Douglas-fir forests of the western Cascades of Oregon.

Long-term consistency in spatial patterns of primate seed dispersal.

PubMed

Heymann, Eckhard W; Culot, Laurence; Knogge, Christoph; Noriega Piña, Tony Enrique; Tirado Herrera, Emérita R; Klapproth, Matthias; Zinner, Dietmar

2017-03-01

Seed dispersal is a key ecological process in tropical forests, with effects on various levels ranging from plant reproductive success to the carbon storage potential of tropical rainforests. On a local and landscape scale, spatial patterns of seed dispersal create the template for the recruitment process and thus influence the population dynamics of plant species. The strength of this influence will depend on the long-term consistency of spatial patterns of seed dispersal. We examined the long-term consistency of spatial patterns of seed dispersal with spatially explicit data on seed dispersal by two neotropical primate species, Leontocebus nigrifrons and Saguinus mystax (Callitrichidae), collected during four independent studies between 1994 and 2013. Using distributions of dispersal probability over distances independent of plant species, cumulative dispersal distances, and kernel density estimates, we show that spatial patterns of seed dispersal are highly consistent over time. For a specific plant species, the legume Parkia panurensis , the convergence of cumulative distributions at a distance of 300 m, and the high probability of dispersal within 100 m from source trees coincide with the dimension of the spatial-genetic structure on the embryo/juvenile (300 m) and adult stage (100 m), respectively, of this plant species. Our results are the first demonstration of long-term consistency of spatial patterns of seed dispersal created by tropical frugivores. Such consistency may translate into idiosyncratic patterns of regeneration.

Spatially uniform but temporally variable bacterioplankton in a semi-enclosed coastal area.

PubMed

Meziti, Alexandra; Kormas, Konstantinos A; Moustaka-Gouni, Maria; Karayanni, Hera

2015-07-01

Studies focusing on the temporal and spatial dynamics of bacterioplankton communities within littoral areas undergoing direct influences from the coast are quite limited. In addition, they are more complicated to resolve compared to communities in the open ocean. In order to elucidate the effects of spatial vs. temporal variability on bacterial communities in a highly land-influenced semi-enclosed gulf, surface bacterioplankton communities from five coastal sites in Igoumenitsa Gulf (Ionian Sea, Greece) were analyzed over a nine-month period using 16S rDNA 454-pyrosequencing. Temporal differences were more pronounced than spatial ones, with lower diversity indices observed during the summer months. During winter and early spring, bacterial communities were dominated by SAR11 representatives, while this pattern changed in May when they were abruptly replaced by members of Flavobacteriales, Pseudomonadales, and Alteromonadales. Additionally, correlation analysis showed high negative correlations between the presence of SAR11 OTUs in relation to temperature and sunlight that might have driven, directly or indirectly, the disappearance of these OTUs in the summer months. The dominance of SAR11 during the winter months further supported the global distribution of the clade, not only in the open-sea, but also in coastal systems. This study revealed that specific bacteria exhibited distinct succession patterns in an anthropogenic-impacted coastal system. The major bacterioplankton component was represented by commonly found marine bacteria exhibiting seasonal dynamics, while freshwater and terrestrial-related phylotypes were absent. Copyright © 2015 Elsevier GmbH. All rights reserved.

Effects of Freshwater Discharge in Sandy Beach Populations: The Mole Crab Emerita brasiliensis in Uruguay

NASA Astrophysics Data System (ADS)

Lercari, D.; Defeo, O.

1999-10-01

Sandy beaches are ecosystems which are heavily affected by human activities. An example of this is freshwater discharges, which are known to change salinity, temperature and nutrient regimes and degrade nearshore environments. However, the effects of this kind of disturbance on sandy beach fauna have been little studied. This paper reports the spatial effects of a man-made freshwater canal discharge on the population structure, abundance and reproductive characteristics of the sandy beach mole crab Emerita brasiliensis. Along the 22 km of sandy beach sampled, the mole crab showed a marked longshore variability in population structure and abundance. Abundance of different population components (juveniles, males, females and ovigerous females) significantly decreased towards the canal. Population structure by sex and size, individual weight, fecundity and female maturity patterns at size also displayed a non-linear response to the distance from the freshwater discharge. Only the size structure of males did not follow this pattern. For males, spatial heterogeneity enhanced the detection of density-dependence at less disturbed sites. The authors conclude that artificial freshwater discharges could significantly influence the distribution, abundance and life-history traits of the biota of sandy beaches, and that further study of these ecosystems should include human activities as important factors affecting spatial and temporal trends. The need to consider different spatial and temporal scales in order to detect the effect of anthropogenically-driven impacts in sandy beach populations is stressed.

Spatial variation of PM2.5, PM10, PM2.5 absorbance and PMcoarse concentrations between and within 20 European study areas and the relationship with NO2 - Results of the ESCAPE project

NASA Astrophysics Data System (ADS)

Eeftens, Marloes; Tsai, Ming-Yi; Ampe, Christophe; Anwander, Bernhard; Beelen, Rob; Bellander, Tom; Cesaroni, Giulia; Cirach, Marta; Cyrys, Josef; de Hoogh, Kees; De Nazelle, Audrey; de Vocht, Frank; Declercq, Christophe; Dėdelė, Audrius; Eriksen, Kirsten; Galassi, Claudia; Gražulevičienė, Regina; Grivas, Georgios; Heinrich, Joachim; Hoffmann, Barbara; Iakovides, Minas; Ineichen, Alex; Katsouyanni, Klea; Korek, Michal; Krämer, Ursula; Kuhlbusch, Thomas; Lanki, Timo; Madsen, Christian; Meliefste, Kees; Mölter, Anna; Mosler, Gioia; Nieuwenhuijsen, Mark; Oldenwening, Marieke; Pennanen, Arto; Probst-Hensch, Nicole; Quass, Ulrich; Raaschou-Nielsen, Ole; Ranzi, Andrea; Stephanou, Euripides; Sugiri, Dorothee; Udvardy, Orsolya; Vaskövi, Éva; Weinmayr, Gudrun; Brunekreef, Bert; Hoek, Gerard

2012-12-01

The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates relationships between long-term exposure to outdoor air pollution and health using cohort studies across Europe. This paper analyses the spatial variation of PM2.5, PM2.5 absorbance, PM10 and PMcoarse concentrations between and within 20 study areas across Europe.We measured NO2, NOx, PM2.5, PM2.5 absorbance and PM10 between October 2008 and April 2011 using standardized methods. PMcoarse was determined as the difference between PM10 and PM2.5. In each of the twenty study areas, we selected twenty PM monitoring sites to represent the variability in important air quality predictors, including population density, traffic intensity and altitude. Each site was monitored over three 14-day periods spread over a year, using Harvard impactors. Results for each site were averaged after correcting for temporal variation using data obtained from a reference site, which was operated year-round.Substantial concentration differences were observed between and within study areas. Concentrations for all components were higher in Southern Europe than in Western and Northern Europe, but the pattern differed per component with the highest average PM2.5 concentrations found in Turin and the highest PMcoarse in Heraklion. Street/urban background concentration ratios for PMcoarse (mean ratio 1.42) were as large as for PM2.5 absorbance (mean ratio 1.38) and higher than those for PM2.5 (1.14) and PM10 (1.23), documenting the importance of non-tailpipe emissions. Correlations between components varied between areas, but were generally high between NO2 and PM2.5 absorbance (average R2 = 0.80). Correlations between PM2.5 and PMcoarse were lower (average R2 = 0.39). Despite high correlations, concentration ratios between components varied, e.g. the NO2/PM2.5 ratio varied between 0.67 and 3.06.In conclusion, substantial variability was found in spatial patterns of PM2.5, PM2.5 absorbance, PM10 and PMcoarse. The highly standardized measurement of particle concentrations across Europe will contribute to a consistent assessment of health effects across Europe.

Tree species exhibit complex patterns of distribution in bottomland hardwood forests

Treesearch

Luben D Dimov; Jim L Chambers; Brian R. Lockhart

2013-01-01

& Context Understanding tree interactions requires an insight into their spatial distribution. & Aims We looked for presence and extent of tree intraspecific spatial point pattern (random, aggregated, or overdispersed) and interspecific spatial point pattern (independent, aggregated, or segregated). & Methods We established twelve 0.64-ha plots in natural...

Spatial image modulation to improve performance of computed tomography imaging spectrometer

NASA Technical Reports Server (NTRS)

Bearman, Gregory H. (Inventor); Wilson, Daniel W. (Inventor); Johnson, William R. (Inventor)

2010-01-01

Computed tomography imaging spectrometers ("CTIS"s) having patterns for imposing spatial structure are provided. The pattern may be imposed either directly on the object scene being imaged or at the field stop aperture. The use of the pattern improves the accuracy of the captured spatial and spectral information.

Mapping the bycatch seascape: multispecies and multi-scale spatial patterns of fisheries bycatch.

PubMed

Lewison, Rebecca L; Soykan, Candan U; Franklin, Janet

2009-06-01

Fisheries bycatch is a worldwide conservation issue. Despite a growing awareness of bycatch problems in particular ocean regions, there have been few efforts to identify spatial patterns in bycatch events. Furthermore, many studies of fisheries bycatch have been myopic, focusing on a single species or a single region. Using a range of analytical approaches to identify spatial patterns in bycatch data, we demonstrate the utility and applications of area and point pattern analyses to single and multispecies bycatch seascapes of pelagic longline fisheries in the Atlantic and Pacific Oceans. We find clear evidence of spatial clustering within bycatch species in both ocean basins, both in terms of the underlying pattern of the locations of bycatch events relative to fishing locations and for areas of high bycatch rates. Furthermore, we find significant spatial overlap in the pattern of bycatch across species relative to the spatial distribution in fishing effort and target catch. These results point to the importance of considering spatial patterns of both single and multispecies bycatch to meet the ultimate goal of reducing bycatch encounters. These analyses also highlight the importance of considering bycatch relative to target catch as a way of identifying areas where fishing effort reduction may help to reduce multispecies bycatch with minimal impact on target catch.

Investigation of spatial and historical variations of air pollution around an industrial region using trace and macro elements in tree components.

PubMed

Odabasi, Mustafa; Tolunay, Doganay; Kara, Melik; Ozgunerge Falay, Ezgi; Tuna, Gizem; Altiok, Hasan; Dumanoglu, Yetkin; Bayram, Abdurrahman; Elbir, Tolga

2016-04-15

Several trace and macro elements (n=48) were measured in pine needle, branch, bark, tree ring, litter, and soil samples collected at 27 sites (21 industrial, 6 background) to investigate their spatial and historical variation in Aliaga industrial region in Turkey. Concentrations generally decreased with distance from the sources and the lowest ones were measured at background sites far from major sources. Spatial distribution of anthropogenic trace elements indicated that their major sources in the region are the iron-steel plants, ship-breaking activities and the petroleum refinery. Patterns of 40 elements that were detected in most of the samples were also evaluated to assess their suitability for investigation of historical variations. Observed increasing trends of several trace and macro elements (As, Cr, Fe, Mo, Ni, V, Cu, Pb, Sb, Sn, and Hg) in the tree-ring samples were representative for the variations in anthropogenic emissions and resulting atmospheric concentrations in Aliaga region. It was shown that lanthanides (La, Ce, Pr, Nd, Sm, Gd, Dy, Er, Yb) could also be used for the investigation of historical variations due to specific industrial emissions (i.e., petroleum refining). Results of the present study showed that tree components, litter, and soil could be used to determine the spatial variations of atmospheric pollution in a region while tree rings could be used to assess the historical variations. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatial accumulation pattern of citrulline and other nutrients in immature and mature watermelon fruits.

PubMed

Akashi, Kinya; Mifune, Yuki; Morita, Kaori; Ishitsuka, Souichi; Tsujimoto, Hisashi; Ishihara, Toshiyuki

2017-01-01

Watermelon (Citrullus lanatus L.) originates from arid regions of southern Africa, and its fruit contains a large amount of the amino acid citrulline, an efficient hydroxyl radical scavenger. Citrulline is implicated in the production of nitric oxide in human endothelium, and potential health benefits including vasodilatation and antioxidant functions have been suggested. However, citrulline metabolism in watermelon fruits is poorly understood. This study examined the accumulation pattern of citrulline and other nutrients in immature and mature watermelon fruits. In mature fruits, highest citrulline concentration was observed in the outer peel, followed by the central portion of the flesh and inner rinds, whereas the level was lower in the peripheral portion of the flesh. Citrulline content was generally low in immature fruits. Spatial and developmental patterns of citrulline accumulation were largely different from those of the antioxidant lycopene, total proteins, and soluble sugars such as glucose, fructose, and sucrose. Principal component analysis suggested a clear distinction of the central flesh and outer peels in mature fruits from other tissues in terms of the levels of major nutrients. These observations suggested that citrulline accumulation may be regulated in a distinct manner from other nutrients during watermelon fruit maturation. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Hebbian Plasticity Realigns Grid Cell Activity with External Sensory Cues in Continuous Attractor Models

PubMed Central

Mulas, Marcello; Waniek, Nicolai; Conradt, Jörg

2016-01-01

After the discovery of grid cells, which are an essential component to understand how the mammalian brain encodes spatial information, three main classes of computational models were proposed in order to explain their working principles. Amongst them, the one based on continuous attractor networks (CAN), is promising in terms of biological plausibility and suitable for robotic applications. However, in its current formulation, it is unable to reproduce important electrophysiological findings and cannot be used to perform path integration for long periods of time. In fact, in absence of an appropriate resetting mechanism, the accumulation of errors over time due to the noise intrinsic in velocity estimation and neural computation prevents CAN models to reproduce stable spatial grid patterns. In this paper, we propose an extension of the CAN model using Hebbian plasticity to anchor grid cell activity to environmental landmarks. To validate our approach we used as input to the neural simulations both artificial data and real data recorded from a robotic setup. The additional neural mechanism can not only anchor grid patterns to external sensory cues but also recall grid patterns generated in previously explored environments. These results might be instrumental for next generation bio-inspired robotic navigation algorithms that take advantage of neural computation in order to cope with complex and dynamic environments. PMID:26924979

A tale of two seas: contrasting patterns of population structure in the small-spotted catshark across Europe

PubMed Central

Gubili, Chrysoula; Sims, David W.; Veríssimo, Ana; Domenici, Paolo; Ellis, Jim; Grigoriou, Panagiotis; Johnson, Andrew F.; McHugh, Matthew; Neat, Francis; Satta, Andrea; Scarcella, Giuseppe; Serra-Pereira, Bárbara; Soldo, Alen; Genner, Martin J.; Griffiths, Andrew M.

2014-01-01

Elasmobranchs represent important components of marine ecosystems, but they can be vulnerable to overexploitation. This has driven investigations into the population genetic structure of large-bodied pelagic sharks, but relatively little is known of population structure in smaller demersal taxa, which are perhaps more representative of the biodiversity of the group. This study explores spatial population genetic structure of the small-spotted catshark (Scyliorhinus canicula), across European seas. The results show significant genetic differences among most of the Mediterranean sample collections, but no significant structure among Atlantic shelf areas. The data suggest the Mediterranean populations are likely to have persisted in a stable and structured environment during Pleistocene sea-level changes. Conversely, the Northeast Atlantic populations would have experienced major changes in habitat availability during glacial cycles, driving patterns of population reduction and expansion. The data also provide evidence of male-biased dispersal and female philopatry over large spatial scales, implying complex sex-determined differences in the behaviour of elasmobranchs. On the basis of this evidence, we suggest that patterns of connectivity are determined by trends of past habitat stability that provides opportunity for local adaptation in species exhibiting philopatric behaviour, implying that resilience of populations to fisheries and other stressors may differ across the range of species. PMID:26064555

Temporally variable environments maintain more beta-diversity in Mediterranean landscapes

NASA Astrophysics Data System (ADS)

Martin, Beatriz; Ferrer, Miguel

2015-10-01

We examined the relationships between different environmental factors and the alpha and beta-diversity of terrestrial vertebrates (birds, mammals, amphibians and reptiles) in a Mediterranean region at the landscape level. We investigated whether the mechanisms underlying alpha and beta-diversity patterns are influenced by energy availability, habitat heterogeneity and temporal variability and if the drivers of the diversity patterns differed between both components of diversity. We defined alpha-diversity as synonym of species richness whereas beta-diversity was measured as distinctiveness. We evaluated a total of 13 different predictors using generalized linear mixed model (GLMM) analysis. Habitat spatial heterogeneity increased alpha-diversity, but contrastingly, it did not significantly affect beta-diversity among sites. Disturbed landscapes may show higher habitat spatial variation and higher alpha-diversity due to the contribution of highly generalist species that are wide-distributed and do not differ in composition (beta-diversity) among different sites within the region. Contrastingly, higher beta-diversity levels were negatively related to more stable sites in terms of temporal environmental variation. This negative relationship between environmental stability and beta-diversity levels is explained in terms of species adaptation to the local environmental conditions. Our study highlights the importance of temporal environmental variability in maintaining beta-diversity patterns under highly variable environmental conditions.

Consciousness of the first order in blindsight

PubMed Central

Sahraie, Arash; Hibbard, Paul B.; Trevethan, Ceri T.; Ritchie, Kay L.; Weiskrantz, Lawrence

2010-01-01

At suprathreshold levels, detection and awareness of visual stimuli are typically synonymous in nonclinical populations. But following postgeniculate lesions, some patients may perform above chance in forced-choice detection paradigms, while reporting not to see the visual events presented within their blind field. This phenomenon, termed “blindsight,” is intriguing because it demonstrates a dissociation between detection and perception. It is possible, however, for a blindsight patient to have some “feeling” of the occurrence of an event without seeing per se. This is termed blindsight type II to distinguish it from the type I, defined as discrimination capability in the total absence of any acknowledged awareness. Here we report on a well-studied patient, D.B., whose blindsight capabilities have been previously documented. We have found that D.B. is capable of detecting visual patterns defined by changes in luminance (first-order gratings) and those defined by contrast modulation of textured patterns (textured gratings; second-order stimuli) while being aware of the former but reporting no awareness of the latter. We have systematically investigated the parameters that could lead to visual awareness of the patterns and show that mechanisms underlying the subjective reports of visual awareness rely primarily on low spatial frequency, first-order spatial components of the image. PMID:21078979

A diffusion-matched principal component analysis (DM-PCA) based two-channel denoising procedure for high-resolution diffusion-weighted MRI

PubMed Central

Chang, Hing-Chiu; Bilgin, Ali; Bernstein, Adam; Trouard, Theodore P.

2018-01-01

Over the past several years, significant efforts have been made to improve the spatial resolution of diffusion-weighted imaging (DWI), aiming at better detecting subtle lesions and more reliably resolving white-matter fiber tracts. A major concern with high-resolution DWI is the limited signal-to-noise ratio (SNR), which may significantly offset the advantages of high spatial resolution. Although the SNR of DWI data can be improved by denoising in post-processing, existing denoising procedures may potentially reduce the anatomic resolvability of high-resolution imaging data. Additionally, non-Gaussian noise induced signal bias in low-SNR DWI data may not always be corrected with existing denoising approaches. Here we report an improved denoising procedure, termed diffusion-matched principal component analysis (DM-PCA), which comprises 1) identifying a group of (not necessarily neighboring) voxels that demonstrate very similar magnitude signal variation patterns along the diffusion dimension, 2) correcting low-frequency phase variations in complex-valued DWI data, 3) performing PCA along the diffusion dimension for real- and imaginary-components (in two separate channels) of phase-corrected DWI voxels with matched diffusion properties, 4) suppressing the noisy PCA components in real- and imaginary-components, separately, of phase-corrected DWI data, and 5) combining real- and imaginary-components of denoised DWI data. Our data show that the new two-channel (i.e., for real- and imaginary-components) DM-PCA denoising procedure performs reliably without noticeably compromising anatomic resolvability. Non-Gaussian noise induced signal bias could also be reduced with the new denoising method. The DM-PCA based denoising procedure should prove highly valuable for high-resolution DWI studies in research and clinical uses. PMID:29694400

Temporal-spatial variation and source apportionment of soil heavy metals in the representative river-alluviation depositional system.

PubMed

Wang, Cheng; Yang, Zhongfang; Zhong, Cong; Ji, Junfeng

2016-09-01

The contributions of major driving forces on temporal changes of heavy metals in the soil in a representative river-alluviation area at the lower of Yangtze River were successfully quantified by combining geostatistics analysis with the modified principal component scores & multiple linear regressions approach (PCS-MLR). The results showed that the temporal (2003-2014) changes of Cu, Zn, Ni and Cr presented a similar spatial distribution pattern, whereas the Cd and Hg showed the distinctive patterns. The temporal changes of soil Cu, Zn, Ni and Cr may be predominated by the emission of the shipbuilding industry, whereas the significant changes of Cd and Hg were possibly predominated by the geochemical and geographical processes, such as the erosion of the Yangtze River water and leaching because of soil acidification. The emission of metal-bearing shipbuilding industry contributed an estimated 74%-83% of the changes in concentrations of Cu, Zn, Ni and Cr, whereas the geochemical and geographical processes may contribute 58% of change of Cd in the soil and 59% of decrease of Hg. Copyright © 2016 Elsevier Ltd. All rights reserved.

Collective ordering of microscale matters in natural analogy

PubMed Central

Ahn, Sungsook; Joon Lee, Sang

2015-01-01

Collective interaction occurs in many natural and artificial matters in broad scales. In a biological system, collective spatial organization of live individuals in a colony is important for their viability determination. Interactive motions between a single individual and an agglomerate are critical for whole procedure of the collective behaviors, but few has been clarified for these intermediate range behaviors. Here, collective interactions of microscale matters are investigated with human cells, plant seeds and artificial microspheres in terms of commonly occurring spatial arrangements. Human cancer cells are inherently attractive to form an agglomerate by cohesive motion, while plant chia seeds are repulsive by excreting mucilage. Microsphere model is employed to investigate the dynamic assembly equilibrated by an attraction and repulsion. There is a fundamental analogy in terms of an onset of regular pattern formation even without physical contact of individuals. The collective interactions are suggested to start before the individual components become physically agglomerated. This study contributes to fundamental understanding on the microscale particulate matters and natural pattern formation which are further useful for various applications both in academic and industrial areas. PMID:26027819

[Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula].

PubMed

Yang, Xiao Ming; Li, Yi Xin; Zhu, Guo Ping

2016-12-01

As a key species in the Antarctic ecosystem, the spatial distribution of Antarctic krill (thereafter krill) often tends to present aggregation characteristics, which therefore reflects the spatial patterns of krill fishing operation. Based on the fishing data collected from Chinese krill fishing vessels, of which vessel A was professional krill fishing vessel and Vessel B was a fishing vessel which shifted between Chilean jack mackerel (Trachurus murphyi) fishing ground and krill fishing ground. In order to explore the characteristics of spatial distribution pattern and their ecological effects of two obvious different fishing fleets under a high and low nominal catch per unit effort (CPUE), from the viewpoint of spatial point pattern, the present study analyzed the spatial distribution characteristics of krill fishery in the northern Antarctic Peninsula from three aspects: (1) the two vessels' point pattern characteristics of higher CPUEs and lower CPUEs at different scales; (2) correlation of the bivariate point patterns between these points of higher CPUE and lower CPUE; and (3) correlation patterns of CPUE. Under the analysis derived from the Ripley's L function and mark correlation function, the results showed that the point patterns of the higher/lo-wer catch available were similar, both showing an aggregation distribution in this study windows at all scale levels. The aggregation intensity of krill fishing was nearly maximum at 15 km spatial scale, and kept stably higher values at the scale of 15-50 km. The aggregation intensity of krill fishery point patterns could be described in order as higher CPUE of vessel A > lower CPUE of vessel B >higher CPUE of vessel B > higher CPUE of vessel B. The relationship of the higher and lo-wer CPUEs of vessel A showed positive correlation at the spatial scale of 0-75 km, and presented stochastic relationship after 75 km scale, whereas vessel B showed positive correlation at all spatial scales. The point events of higher and lower CPUEs were synchronized, showing significant correlations at most of spatial scales because of the dynamics nature and complex of krill aggregation patterns. The distribution of vessel A's CPUEs was positively correlated at scales of 0-44 km, but negatively correlated at the scales of 44-80 km. The distribution of vessel B's CPUEs was negatively correlated at the scales of 50-70 km, but no significant correlations were found at other scales. The CPUE mark point patterns showed a negative correlation, which indicated that intraspecific competition for space and prey was significant. There were significant differences in spatial point pattern distribution between vessel A with higher fishing capacity and vessel B with lower fishing capacity. The results showed that the professional krill fishing vessel is suitable to conduct the analysis of spatial point pattern and scientific fishery survey.

Multiscale analysis of surface soil moisture dynamics in a mesoscale catchment utilizing an integrated ecohydrological model

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2012-12-01

Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil moisture remained in contrast to the measurements very responsive to precipitation with high soil moisture after precipitation events. This behavior indicates that the soil properties might have changed due to the formation of a surface crust or seal towards the end of the growing season. Spatial soil moisture patterns were investigated using a grid resolution of 150 meter. Spatial autocorrelation was computed on a daily basis using patterns of soil texture as well as transpiration and precipitation indices as co-variables. Spatial patterns of surface soil moisture are mostly determined by the structure of the soil properties (soil type) during winter, early growing season and after harvest of all crops. Later in the growing season, after establishment of a closed canopy the dependence of the soil moisture patterns on soil texture patterns becomes smaller and diminishes quickly after precipitation events, due to differences of the transpiration rate of the different crops. When changing the spatial scale of the analysis, the highest autocorrelation values can be found on a grid cell size between 450 and 1200 meters. Thus, small scale variability of transpiration induced by the land use pattern almost averages out, leaving the larger scale structure of soil properties to explain the soil moisture patterns.

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

DOE PAGES

Leng, Guoyong; Huang, Maoyi

2017-05-03

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

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

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

Leng, Guoyong; Huang, Maoyi

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

PHYLOGEOrec: A QGIS plugin for spatial phylogeographic reconstruction from phylogenetic tree and geographical information data

NASA Astrophysics Data System (ADS)

Nashrulloh, Maulana Malik; Kurniawan, Nia; Rahardi, Brian

2017-11-01

The increasing availability of genetic sequence data associated with explicit geographic and environment (including biotic and abiotic components) information offers new opportunities to study the processes that shape biodiversity and its patterns. Developing phylogeography reconstruction, by integrating phylogenetic and biogeographic knowledge, provides richer and deeper visualization and information on diversification events than ever before. Geographical information systems such as QGIS provide an environment for spatial modeling, analysis, and dissemination by which phylogenetic models can be explicitly linked with their associated spatial data, and subsequently, they will be integrated with other related georeferenced datasets describing the biotic and abiotic environment. We are introducing PHYLOGEOrec, a QGIS plugin for building spatial phylogeographic reconstructions constructed from phylogenetic tree and geographical information data based on QGIS2threejs. By using PHYLOGEOrec, researchers can integrate existing phylogeny and geographical information data, resulting in three-dimensional geographic visualizations of phylogenetic trees in the Keyhole Markup Language (KML) format. Such formats can be overlaid on a map using QGIS and finally, spatially viewed in QGIS by means of a QGIS2threejs engine for further analysis. KML can also be viewed in reputable geobrowsers with KML-support (i.e., Google Earth).

Co-Seismic Gravity Gradient Changes of the 2006-2007 Great Earthquakes in the Central Kuril Islands from GRACE Observations

NASA Astrophysics Data System (ADS)

Rahimi, A.; Shahrisvand, M.

2017-09-01

GRACE satellites (the Gravity Recovery And climate Experiment) are very useful sensors to extract gravity anomalies after earthquakes. In this study, we reveal co-seismic signals of the two combined earthquakes, the 2006 Mw8.3 thrust and 2007 Mw8.1 normal fault earthquakes of the central Kuril Islands from GRACE observations. We compute monthly full gravitational gradient tensor in the local north-east-down frame for Kuril Islands earthquakes without spatial averaging and de-striping filters. Some of gravitational gradient components (e.g. ΔVxx, ΔVxz) enhance high frequency components of the earth gravity field and reveal more details in spatial and temporal domain. Therefore, co-seismic activity can be better illustrated. For the first time, we show that the positive-negative-positive co-seismic ΔVxx due to the Kuril Islands earthquakes ranges from - 0.13 to + 0.11 milli Eötvös, and ΔVxz shows a positive-negative-positive pattern ranges from - 0.16 to + 0.13 milli Eötvös, agree well with seismic model predictions.

Landscape-scale spatial abundance distributions discriminate core from random components of boreal lake bacterioplankton.

PubMed

Niño-García, Juan Pablo; Ruiz-González, Clara; Del Giorgio, Paul A

2016-12-01

Aquatic bacterial communities harbour thousands of coexisting taxa. To meet the challenge of discriminating between a 'core' and a sporadically occurring 'random' component of these communities, we explored the spatial abundance distribution of individual bacterioplankton taxa across 198 boreal lakes and their associated fluvial networks (188 rivers). We found that all taxa could be grouped into four distinct categories based on model statistical distributions (normal like, bimodal, logistic and lognormal). The distribution patterns across lakes and their associated river networks showed that lake communities are composed of a core of taxa whose distribution appears to be linked to in-lake environmental sorting (normal-like and bimodal categories), and a large fraction of mostly rare bacteria (94% of all taxa) whose presence appears to be largely random and linked to downstream transport in aquatic networks (logistic and lognormal categories). These rare taxa are thus likely to reflect species sorting at upstream locations, providing a perspective of the conditions prevailing in entire aquatic networks rather than only in lakes. © 2016 John Wiley & Sons Ltd/CNRS.

Spatial and temporal variability of picocyanobacteria Synechococcus sp. in San Francisco Bay

USGS Publications Warehouse

Ning, X.; Cloern, J.E.; Cole, B.E.

2000-01-01

We collected samples monthly, from April to August 1998, to measure the abundance of autotrophic picoplankton in San Francisco Bay. Samples taken along a 160-km transect showed that picocyanobacteria (Synechococcus sp.) was a persistent component of the San Francisco Bay phytoplankton in all the estuarine habitats, from freshwater to seawater and during all months of the spring-summer transition. Abundance ranged from 4.6 X 106 to 5.2 X 108 cells L-1, with peak abundance during the spring bloom (April and May) and during July with a persistent spatial pattern of smallest abundance near the coastal ocean and highest abundance in the landward domains of the estuary. The picocyanobacterial component (as estimated percentage of chlorophyll a concentration) was, on average, 15% of total phytoplankton biomass during the summer-autumn nonbloom periods and only 2% of chlorophyll biomass during the spring bloom. This result is consistent with the emerging concept of a gradient of increasing importance of picocyanobacteria along the gradient of decreasing nutrient concentrations from estuaries to the open ocean.

Computation by symmetry operations in a structured model of the brain: Recognition of rotational invariance and time reversal

NASA Astrophysics Data System (ADS)

McGrann, John V.; Shaw, Gordon L.; Shenoy, Krishna V.; Leng, Xiaodan; Mathews, Robert B.

1994-06-01

Symmetries have long been recognized as a vital component of physical and biological systems. What we propose here is that symmetry operations are an important feature of higher brain function and result from the spatial and temporal modularity of the cortex. These symmetry operations arise naturally in the trion model of the cortex. The trion model is a highly structured mathematical realization of the Mountcastle organizational principle [Mountcastle, in The Mindful Brain (MIT, Cambridge, 1978)] in which the cortical column is the basic neural network of the cortex and is comprised of subunit minicolumns, which are idealized as trions with three levels of firing. A columnar network of a small number of trions has a large repertoire of quasistable, periodic spatial-temporal firing magic patterns (MP's), which can be excited. The MP's are related by specific symmetries: Spatial rotation, parity, ``spin'' reversal, and time reversal as well as other ``global'' symmetry operations in this abstract internal language of the brain. These MP's can be readily enhanced (as well as inherent categories of MP's) by only a small change in connection strengths via a Hebb learning rule. Learning introduces small breaking of the symmetries in the connectivities which enables a symmetry in the patterns to be recognized in the Monte Carlo evolution of the MP's. Examples of the recognition of rotational invariance and of a time-reversed pattern are presented. We propose the possibility of building a logic device from the hardware implementation of a higher level architecture of trion cortical columns.

EEG resolutions in detecting and decoding finger movements from spectral analysis

PubMed Central

Xiao, Ran; Ding, Lei

2015-01-01

Mu/beta rhythms are well-studied brain activities that originate from sensorimotor cortices. These rhythms reveal spectral changes in alpha and beta bands induced by movements of different body parts, e.g., hands and limbs, in electroencephalography (EEG) signals. However, less can be revealed in them about movements of different fine body parts that activate adjacent brain regions, such as individual fingers from one hand. Several studies have reported spatial and temporal couplings of rhythmic activities at different frequency bands, suggesting the existence of well-defined spectral structures across multiple frequency bands. In the present study, spectral principal component analysis (PCA) was applied on EEG data, obtained from a finger movement task, to identify cross-frequency spectral structures. Features from identified spectral structures were examined in their spatial patterns, cross-condition pattern changes, detection capability of finger movements from resting, and decoding performance of individual finger movements in comparison to classic mu/beta rhythms. These new features reveal some similar, but more different spatial and spectral patterns as compared with classic mu/beta rhythms. Decoding results further indicate that these new features (91%) can detect finger movements much better than classic mu/beta rhythms (75.6%). More importantly, these new features reveal discriminative information about movements of different fingers (fine body-part movements), which is not available in classic mu/beta rhythms. The capability in decoding fingers (and hand gestures in the future) from EEG will contribute significantly to the development of non-invasive BCI and neuroprosthesis with intuitive and flexible controls. PMID:26388720

Frugivorous birds influence the spatial organization of tropical forests through the generation of seedling recruitment foci under zoochoric trees

NASA Astrophysics Data System (ADS)

Trolliet, Franck; Forget, Pierre-Michel; Doucet, Jean-Louis; Gillet, Jean-François; Hambuckers, Alain

2017-11-01

Animal-mediated seed dispersal is recognized to influence the spatial organization of plant communities but little is known about how frugivores cause such patterns. Here, we explored the role of hornbills and primates in generating recruitment foci under two zoochoric trees, namely Staudtia kamerunensis (Myristicaceae) and Dialium spp. (Fabaceae - Caesalpiniodea) in a forest-savanna mosaic landscape in D.R. Congo. We also examined the influence of the availability of fruits in the neighborhood and the amount of forest cover in the landscape on such clumping patterns. The density and species richness of hornbill-dispersed and the density of primate-dispersed seedlings were significantly higher under Staudtia kamerunensis trees than at control locations. However, we did not find such patterns under Dialium spp. trees compared to control locations except for the density of hornbill-dispersed seedlings which was lower at control locations. Also, we found that an increasing amount of forest cover in the landscape was associated with an increase in the density of hornbill-dispersed seedlings, although the tendency was weak (R2 = 0.065). We concluded that S. kamerunensis acts as a recruitment foci and plays a structuring role in Afrotropical forests. Hornbills were probably the main frugivore taxon responsible for the clumping under that tree and appear as a key ecological component in fragmented and disturbed landscapes where the diversity of large frugivores such as primates is reduced. Our findings improve our understanding of the causal mechanisms responsible for the spatial organization of tropical forests.

Imaging auditory representations of song and syllables in populations of sensorimotor neurons essential to vocal communication.

PubMed

Peh, Wendy Y X; Roberts, Todd F; Mooney, Richard

2015-04-08

Vocal communication depends on the coordinated activity of sensorimotor neurons important to vocal perception and production. How vocalizations are represented by spatiotemporal activity patterns in these neuronal populations remains poorly understood. Here we combined intracellular recordings and two-photon calcium imaging in anesthetized adult zebra finches (Taeniopygia guttata) to examine how learned birdsong and its component syllables are represented in identified projection neurons (PNs) within HVC, a sensorimotor region important for song perception and production. These experiments show that neighboring HVC PNs can respond at markedly different times to song playback and that different syllables activate spatially intermingled PNs within a local (~100 μm) region of HVC. Moreover, noise correlations were stronger between PNs that responded most strongly to the same syllable and were spatially graded within and between classes of PNs. These findings support a model in which syllabic and temporal features of song are represented by spatially intermingled PNs functionally organized into cell- and syllable-type networks within local spatial scales in HVC. Copyright © 2015 the authors 0270-6474/15/355589-17$15.00/0.

Large-area imaging reveals biologically driven non-random spatial patterns of corals at a remote reef

NASA Astrophysics Data System (ADS)

Edwards, Clinton B.; Eynaud, Yoan; Williams, Gareth J.; Pedersen, Nicole E.; Zgliczynski, Brian J.; Gleason, Arthur C. R.; Smith, Jennifer E.; Sandin, Stuart A.

2017-12-01

For sessile organisms such as reef-building corals, differences in the degree of dispersion of individuals across a landscape may result from important differences in life-history strategies or may reflect patterns of habitat availability. Descriptions of spatial patterns can thus be useful not only for the identification of key biological and physical mechanisms structuring an ecosystem, but also by providing the data necessary to generate and test ecological theory. Here, we used an in situ imaging technique to create large-area photomosaics of 16 plots at Palmyra Atoll, central Pacific, each covering 100 m2 of benthic habitat. We mapped the location of 44,008 coral colonies and identified each to the lowest taxonomic level possible. Using metrics of spatial dispersion, we tested for departures from spatial randomness. We also used targeted model fitting to explore candidate processes leading to differences in spatial patterns among taxa. Most taxa were clustered and the degree of clustering varied by taxon. A small number of taxa did not significantly depart from randomness and none revealed evidence of spatial uniformity. Importantly, taxa that readily fragment or tolerate stress through partial mortality were more clustered. With little exception, clustering patterns were consistent with models of fragmentation and dispersal limitation. In some taxa, dispersion was linearly related to abundance, suggesting density dependence of spatial patterning. The spatial patterns of stony corals are non-random and reflect fundamental life-history characteristics of the taxa, suggesting that the reef landscape may, in many cases, have important elements of spatial predictability.

SMART: A Spatially Explicit Bio-Economic Model for Assessing and Managing Demersal Fisheries, with an Application to Italian Trawlers in the Strait of Sicily

PubMed Central

Russo, Tommaso; Parisi, Antonio; Garofalo, Germana; Gristina, Michele; Cataudella, Stefano; Fiorentino, Fabio

2014-01-01

Management of catches, effort and exploitation pattern are considered the most effective measures to control fishing mortality and ultimately ensure productivity and sustainability of fisheries. Despite the growing concerns about the spatial dimension of fisheries, the distribution of resources and fishing effort in space is seldom considered in assessment and management processes. Here we propose SMART (Spatial MAnagement of demersal Resources for Trawl fisheries), a tool for assessing bio-economic feedback in different management scenarios. SMART combines information from different tasks gathered within the European Data Collection Framework on fisheries and is composed of: 1) spatial models of fishing effort, environmental characteristics and distribution of demersal resources; 2) an Artificial Neural Network which captures the relationships among these aspects in a spatially explicit way and uses them to predict resources abundances; 3) a deterministic module which analyzes the size structure of catches and the associated revenues, according to different spatially-based management scenarios. SMART is applied to demersal fishery in the Strait of Sicily, one of the most productive fisheries of the Mediterranean Sea. Three of the main target species are used as proxies for the whole range exploited by trawlers. After training, SMART is used to evaluate different management scenarios, including spatial closures, using a simulation approach that mimics the recent exploitation patterns. Results evidence good model performance, with a noteworthy coherence and reliability of outputs for the different components. Among others, the main finding is that a partial improvement in resource conditions can be achieved by means of nursery closures, even if the overall fishing effort in the area remains stable. Accordingly, a series of strategically designed areas of trawling closures could significantly improve the resource conditions of demersal fisheries in the Strait of Sicily, also supporting sustainable economic returns for fishermen if not applied simultaneously for different species. PMID:24465971

Evaluation of spatial models to predict vulnerability of forest birds to brood parasitism by cowbirds

USGS Publications Warehouse

Gustafson, E.J.; Knutson, M.G.; Niemi, G.J.; Friberg, M.

2002-01-01

We constructed alternative spatial models at two scales to predict Brown-headed Cowbird (Molothrus ater) parasitism rates from land cover maps. The local-scale models tested competing hypotheses about the relationship between cowbird parasitism and distance of host nests from a forest edge (forest-nonforest boundary). The landscape models tested competing hypotheses about how landscape features (e.g., forests, agricultural fields) interact to determine rates of cowbird parasitism. The models incorporate spatial neighborhoods with a radius of 2.5 km in their formulation, reflecting the scale of the majority of cowbird commuting activity. Field data on parasitism by cowbirds (parasitism rate and number of cowbird eggs per nest) were collected at 28 sites in the Driftless Area Ecoregion of Wisconsin, Minnesota, and Iowa and were compared to the predictions of the alternative models. At the local scale, there was a significant positive relationship between cowbird parasitism and mean distance of nest sites from the forest edge. At the landscape scale, the best fitting models were the forest-dependent and forest-fragmentation-dependent models, in which more heavily forested and less fragmented landscapes had higher parasitism rates. However, much of the explanatory power of these models results from the inclusion of the local-scale relationship in these models. We found lower rates of cowbird parasitism than did most Midwestern studies, and we identified landscape patterns of cowbird parasitism that are opposite to those reported in several other studies of Midwestern songbirds. We caution that cowbird parasitism patterns can be unpredictable, depending upon ecoregional location and the spatial extent, and that our models should be tested in other ecoregions before they are applied there. Our study confirms that cowbird biology has a strong spatial component, and that improved spatial models applied at multiple spatial scales will be required to predict the effects of landscape and forest management on cowbird parasitism of forest birds.

Spatial patterns of development drive water use

Treesearch

G. M. Sanchez; J. W. Smith; A. Terando; G. Sun; R. K. Meentemeyer

2018-01-01

Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land...

Improving Photometry and Stellar Signal Preservation with Pixel-Level Systematic Error Correction

NASA Technical Reports Server (NTRS)

Kolodzijczak, Jeffrey J.; Smith, Jeffrey C.; Jenkins, Jon M.

2013-01-01

The Kepler Mission has demonstrated that excellent stellar photometric performance can be achieved using apertures constructed from optimally selected CCD pixels. The clever methods used to correct for systematic errors, while very successful, still have some limitations in their ability to extract long-term trends in stellar flux. They also leave poorly correlated bias sources, such as drifting moiré pattern, uncorrected. We will illustrate several approaches where applying systematic error correction algorithms to the pixel time series, rather than the co-added raw flux time series, provide significant advantages. Examples include, spatially localized determination of time varying moiré pattern biases, greater sensitivity to radiation-induced pixel sensitivity drops (SPSDs), improved precision of co-trending basis vectors (CBV), and a means of distinguishing the stellar variability from co-trending terms even when they are correlated. For the last item, the approach enables physical interpretation of appropriately scaled coefficients derived in the fit of pixel time series to the CBV as linear combinations of various spatial derivatives of the pixel response function (PRF). We demonstrate that the residuals of a fit of soderived pixel coefficients to various PRF-related components can be deterministically interpreted in terms of physically meaningful quantities, such as the component of the stellar flux time series which is correlated with the CBV, as well as, relative pixel gain, proper motion and parallax. The approach also enables us to parameterize and assess the limiting factors in the uncertainties in these quantities.

Linking storm surge activity and circulation variability along the Spanish coast through a synoptic pattern classification

NASA Astrophysics Data System (ADS)

Rasilla Álvarez, Domingo; Garcia Codrón, Juan Carlos

2010-05-01

The potentially negative consequences resulting from the estimations of global sea level rising along the current century are a matter of serious concern in many coastal areas worldwide. Most of the negative consequences of the sea level variability, such as flooding or erosion, are linked to episodic events of strong atmospheric forcing represented by deep atmospheric disturbances, especially if they combine with extreme astronomical high tides. Moreover, the interaction between the prevailing flows during such events and the actual orientation of the coast line might accelerate or mitigate such impacts. This contribution analyses sea surge variations measured at five tide-gauge stations located around the Iberian Peninsula and their relationships with regional scale circulation patterns with local-scale winds. Its aim is to improve the knowledge of surge related-coastal-risks by analysing the relationship between surges and their atmospheric forcing factors at different spatial scales. The oceanographic data set consists of hourly data from 5 tide gauge stations (Santander, Vigo, Bonanza, Málaga, Valencia and Barcelona) disseminated along the Spanish coastline, provided by Puertos del Estado. To explore the atmospheric mechanisms responsible for the sign and magnitude of sea surges, a regional Eulerian approach (a synoptic typing) were combined with a larger-scale Lagrangian method, based on the analysis of storm-tracks over the Atlantic and local information (synop reports) obtained from the closest meteorological stations to the tide gauges. The synoptic catalogue was obtained following a procedure that combines Principal Component Analysis (PCA) for reduction purposes and clustering (Ward plus K-means) to define the circulation types. Sea level pressure, surface 10m U and V wind components gridded data were obtained from NCEP Reanalysis, while storm tracks and cyclone statistics were extracted from the CDC Map Room Climate Products Storm Track Data (http://www.cdc.noaa.gov/map/clim/st_data.html). The second task was to evaluate the performance of each circulation type on the spatial patterns of a daily fire danger risk index (Canadian Fire Weather Index, FWI). Finally, anomaly maps of several surface and low level climate variables, corresponding to the dates of ignition of the very large forest fires within each synoptic pattern, were calculated to provide insight of the specific conditions associated to those extreme events. A principal component analysis upon 6 hourly residuals highlighted the homogeneous behaviour of the tide gauges and provided a regional quantitative index to identify the largest storm surges. The leading PCA displayed a homogeneous spatial pattern, describing the low frequency variability along the entire coast, in spite of different orientations of the coast, accounting for more than 80% of the total variability. The second PCA displayed opposite phases between the Atlantic and the Mediterranean. Furthermore, the results suggest that surges are a regional rather than local phenomenon, probably related to the same single physical forcing. The comparison between extreme surge events and circulation patterns highlighted that single physical mechanism is represented by extratropical cyclonic disturbances located at the north-western corner of the Iberian Peninsula, responsible for an environment characterized by low pressure readings and westerly-southwesterly winds. That wind pattern acquires an onshore component in the Atlantic coast, but becomes offshore in the Mediterranean. So, the main mechanism responsible for those storm surges is the inverse barometer effect, being the wind dragging secondary. The main physical forcing of the storm surges, the extratropical cyclones, have experience a reduction of this frequency and a marked reduction in their strength since 1950, replaced by stable circulations. Both conditions suggest a long term reduction of the frequency and the magnitude of storm surges.

Identification of Surface Water Quality along the Coast of Sanya, South China Sea

PubMed Central

Wu, Zhen-Zhen; Che, Zhi-Wei; Wang, You-Shao; Dong, Jun-De; Wu, Mei-Lin

2015-01-01

Principal component analysis (PCA) and cluster analysis (CA) are utilized to identify the effects caused by human activities on water quality along the coast of Sanya, South China Sea. PCA and CA identify the seasonality of water quality (dry and wet seasons) and polluted status (polluted area). The seasonality of water quality is related to climate change and Southeast monsoons. Spatial pattern is mainly related to anthropogenic activities (especially land input of pollutions). PCA reveals the characteristics underlying the generation of coastal water quality. The temporal and spatial variation of the trophic status along the coast of Sanya is governed by hydrodynamics and human activities. The results provide a novel typological understanding of seasonal trophic status in a shallow, tropical, open marine bay. PMID:25894980

Behavioral states may be associated with distinct spatial patterns in electrocorticogram.

PubMed

Panagiotides, Heracles; Freeman, Walter J; Holmes, Mark D; Pantazis, Dimitrios

2011-03-01

To determine if behavioral states are associated with unique spatial electrocorticographic (ECoG) patterns, we obtained recordings with a microgrid electrode array applied to the cortical surface of a human subject. The array was constructed with the intent of extracting maximal spatial information by optimizing interelectrode distances. A 34-year-old patient with intractable epilepsy underwent intracranial ECoG monitoring after standard methods failed to reveal localization of seizures. During the 8-day period of invasive recording, in addition to standard clinical electrodes a square 1 × 1 cm microgrid array with 64 electrodes (1.25 mm separation) was placed on the right inferior temporal gyrus. Careful review of video recordings identified four extended naturalistic behaviors: reading, conversing on the telephone, looking at photographs, and face-to-face interactions. ECoG activity recorded with the microgrid that corresponded to these behaviors was collected and ECoG spatial patterns were analyzed. During periods of ECoG selected for analysis, no electrographic seizures or epileptiform patterns were present. Moments of maximal spatial variance are shown to cluster by behavior. Comparisons between conditions using a permutation test reveal significantly different spatial patterns for each behavior. We conclude that ECoG recordings obtained on the cortical surface with optimal high spatial frequency resolution reveal distinct local spatial patterns that reflect different behavioral states, and we predict that similar patterns will be found in many if not most cortical areas on which a microgrid is placed.

A Gibbs point field model for the spatial pattern of coronary capillaries

NASA Astrophysics Data System (ADS)

Karch, R.; Neumann, M.; Neumann, F.; Ullrich, R.; Neumüller, J.; Schreiner, W.

2006-09-01

We propose a Gibbs point field model for the pattern of coronary capillaries in transverse histologic sections from human hearts, based on the physiology of oxygen supply from capillaries to tissue. To specify the potential energy function of the Gibbs point field, we draw on an analogy between the equation of steady-state oxygen diffusion from an array of parallel capillaries to the surrounding tissue and Poisson's equation for the electrostatic potential of a two-dimensional distribution of identical point charges. The influence of factors other than diffusion is treated as a thermal disturbance. On this basis, we arrive at the well-known two-dimensional one-component plasma, a system of identical point charges exhibiting a weak (logarithmic) repulsive interaction that is completely characterized by a single dimensionless parameter. By variation of this parameter, the model is able to reproduce many characteristics of real capillary patterns.

Experimental Observation of Near-Field Deterioration Induced by Stimulated Rotational Raman Scattering in Long Air Paths

NASA Astrophysics Data System (ADS)

Wang, Jing; Zhang, Xiao-Min; Han, Wei; Li, Fu-Quan; Zhou, Li-Dan; Feng, Bin; Xiang, Yong

2011-08-01

We report the experimental investigation of a stimulated rotational Raman scattering effect in long air paths on SG-III TIL, with a 1053 nm, 20-cm-diameter, linearly polarized, 3 ns flat-topped laser pulse. An intense speckle pattern of near field with thickly dotted hot spots is observed at the end of propagation with an intensity-length product above 17TW/cm. The Stokes developing from the scattering of the laser beam by quantum fluctuations is characterized by a combination of high spatial frequency components. The observed speckle pattern with small-diameter hot spots results from the combination of the nonlinear Raman amplification and the linear diffraction propagation effect of the Stokes with a noise pattern arising from the spontaneous Raman scattering. A new promising suppression concept based on the special characteristic of the Stokes, called active and selective filtering of Stokes, is proposed.

Selective directed self-assembly of coexisting morphologies using block copolymer blends

NASA Astrophysics Data System (ADS)

Stein, A.; Wright, G.; Yager, K. G.; Doerk, G. S.; Black, C. T.

2016-08-01

Directed self-assembly (DSA) of block copolymers is an emergent technique for nano-lithography, but is limited in the range of structures possible in a single fabrication step. Here we expand on traditional DSA chemical patterning. A blend of lamellar- and cylinder-forming block copolymers assembles on specially designed surface chemical line gratings, leading to the simultaneous formation of coexisting ordered morphologies in separate areas of the substrate. The competing energetics of polymer chain distortions and chemical mismatch with the substrate grating bias the system towards either line/space or dot array patterns, depending on the pitch and linewidth of the prepattern. This is in contrast to the typical DSA, wherein assembly of a single-component block copolymer on chemical templates generates patterns of either lines/spaces (lamellar) or hexagonal dot arrays (cylinders). In our approach, the chemical template encodes desired local spatial arrangements of coexisting design motifs, self-assembled from a single, sophisticated resist.

Global Patterns in the Implementation of Payments for Environmental Services

PubMed Central

Ezzine-de-Blas, Driss; Wunder, Sven; Ruiz-Pérez, Manuel; Moreno-Sanchez, Rocio del Pilar

2016-01-01

Assessing global tendencies and impacts of conditional payments for environmental services (PES) programs is challenging because of their heterogeneity, and scarcity of comparative studies. This meta-study systematizes 55 PES schemes worldwide in a quantitative database. Using categorical principal component analysis to highlight clustering patterns, we reconfirm frequently hypothesized differences between public and private PES schemes, but also identify diverging patterns between commercial and non-commercial private PES vis-à-vis their service focus, area size, and market orientation. When do these PES schemes likely achieve significant environmental additionality? Using binary logistical regression, we find additionality to be positively influenced by three theoretically recommended PES ‘best design’ features: spatial targeting, payment differentiation, and strong conditionality, alongside some contextual controls (activity paid for and implementation time elapsed). Our results thus stress the preeminence of customized design over operational characteristics when assessing what determines the outcomes of PES implementation. PMID:26938065

High-quality regional gravity field determination from GOCE gravity gradient and heterogeneous gravimetry and altimetry data

NASA Astrophysics Data System (ADS)

Wu, Y.; Luo, Z.; Zhou, H.; Xu, C.

2017-12-01

Regional gravity field recovery is of great importance for understanding ocean circulation and currents in oceanography and investigating the structure of the lithosphere in geophysics. Under the framework of remove-compute-restore methodology (RCR), a regional approach using spherical radial basis functions (SRBFs) is set up for gravity field determination using the GOCE (Gravity Field and Steady-State Ocean Circulation Explorer) gravity gradient tensor, heterogeneous gravimetry and altimetry measurements. The additional value on regional model introduced by GOCE data is validated and quantified. Numerical experiments in a western European region show that the effects introduced by GOCE data display as long-wavelength patterns on the centimeter scale in terms of quasi-geoid heights, which may allow to highlight and reduce the remaining long-wavelength errors and biases in ground-based data and improve the regional model. The accuracy of the gravimetric quasi-geoid computed with a combination of three diagonal components is improved by 0.6 cm (0.5 cm) in the Netherlands (Belgium), compared to that derived from gravimetry and altimetry data alone, when GOCO05s is used as the reference model. Performances of different diagonal components and their combinations are not identical; the solution with vertical gradients shows highest quality when a single component is used. Incorporation of multiple components further improves the model, and the combination of three components shows the best fit to GPS/leveling data. Moreover, the contributions introduced by different components are heterogeneous in terms of spatial coverage and magnitude, although similar structures occur in the spatial domain. Contributions introduced by the vertical components have the most significant effects when a single component is applied. Combination of multiple components further magnifies these effects and improves the solutions, and the incorporation of three components has the most prominent effects. This work is supported by the State Scholarship Fund from Chinese Scholarship Council (201306270014), China Postdoctoral Science Foundation (No.2016M602301), and the National Natural Science Foundation of China (No. 41374023).

Temporal consistency of spatial pattern in growth of the mussel, Mytilus edulis: Implications for predictive modelling

NASA Astrophysics Data System (ADS)

Bergström, Per; Lindegarth, Susanne; Lindegarth, Mats

2013-10-01

Human pressures on coastal seas are increasing and methods for sustainable management, including spatial planning and mitigative actions, are therefore needed. In coastal areas worldwide, the development of mussel farming as an economically and ecologically sustainable industry requires geographic information on the growth and potential production capacity. In practice this means that coherent maps of temporally stable spatial patterns of growth need to be available in the planning process and that maps need to be based on mechanistic or empirical models. Therefore, as a first step towards development of models of growth, we assessed empirically the fundamental requirement that there are temporally consistent spatial patterns of growth in the blue mussel, Mytilus edulis. Using a pilot study we designed and dimensioned a transplant experiment, where the spatial consistency in the growth of mussels was evaluated at two resolutions. We found strong temporal and scale-dependent spatial variability in growth but patterns suggested that spatial patterns were uncoupled between growth of shell and that of soft tissue. Spatial patterns of shell growth were complex and largely inconsistent among years. Importantly, however, the growth of soft tissue was qualitatively consistent among years at the scale of km. The results suggest that processes affecting the whole coastal area cause substantial differences in growth of soft tissue among years but that factors varying at the scale of km create strong and persistent spatial patterns of growth, with a potential doubling of productivity by identifying the most suitable locations. We conclude that the observed spatial consistency provides a basis for further development of predictive modelling and mapping of soft tissue growth in these coastal areas. Potential causes of observed patterns, consequences for mussel-farming as a tool for mitigating eutrophication, aspects of precision of modelling and sampling of mussel growth as well as ecological functions in general are discussed.

Towards a 3d Spatial Urban Energy Modelling Approach

NASA Astrophysics Data System (ADS)

Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.

2013-09-01

Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies conceptually and practically integrate urban spatial and energy planning approaches. The combined modelling approach that will be developed based on the described sectorial models holds the potential to represent hybrid energy systems coupling distributed generation of electricity with thermal conversion systems.

Spatial Patterns of Inshore Marine Soundscapes.

PubMed

McWilliam, Jamie

2016-01-01

Passive acoustic monitoring was employed to investigate spatial patterns of soundscapes within a marine reserve. High energy level broadband snaps dominated nearly all habitat soundscapes. Snaps, the principal acoustic feature of soundscapes, were primarily responsible for the observed spatial patterns, and soundscapes appeared to retain a level of compositional and configurational stability. In the presence of high-level broadband snaps, soundscape composition was more influenced by geographic location than habitat type. Future research should focus on investigating the spatial patterns of soundscapes across a wider range of coastal and offshore seascapes containing a variety of distinct ecosystems and habitats.

Boundary-induced pattern formation from uniform temporal oscillation

NASA Astrophysics Data System (ADS)

Kohsokabe, Takahiro; Kaneko, Kunihiko

2018-04-01

Pattern dynamics triggered by fixing a boundary is investigated. By considering a reaction-diffusion equation that has a unique spatially uniform and limit cycle attractor under a periodic or Neumann boundary condition, and then by choosing a fixed boundary condition, we found three novel phases depending on the ratio of diffusion constants of activator to inhibitor: transformation of temporally periodic oscillation into a spatially periodic fixed pattern, travelling wave emitted from the boundary, and aperiodic spatiotemporal dynamics. The transformation into a fixed, periodic pattern is analyzed by crossing of local nullclines at each spatial point, shifted by diffusion terms, as is analyzed by using recursive equations, to obtain the spatial pattern as an attractor. The generality of the boundary-induced pattern formation as well as its relevance to biological morphogenesis is discussed.

Spatial coherence resonance and spatial pattern transition induced by the decrease of inhibitory effect in a neuronal network

NASA Astrophysics Data System (ADS)

Tao, Ye; Gu, Huaguang; Ding, Xueli

2017-10-01

Spiral waves were observed in the biological experiment on rat brain cortex with the application of carbachol and bicuculline which can block inhibitory coupling from interneurons to pyramidal neurons. To simulate the experimental spiral waves, a two-dimensional neuronal network composed of pyramidal neurons and inhibitory interneurons was built. By decreasing the percentage of active inhibitory interneurons, the random-like spatial patterns change to spiral waves and to random-like spatial patterns or nearly synchronous behaviors. The spiral waves appear at a low percentage of inhibitory interneurons, which matches the experimental condition that inhibitory couplings of the interneurons were blocked. The spiral waves exhibit a higher order or signal-to-noise ratio (SNR) characterized by spatial structure function than both random-like spatial patterns and nearly synchronous behaviors, which shows that changes of the percentage of active inhibitory interneurons can induce spatial coherence resonance-like behaviors. In addition, the relationship between the coherence degree and the spatial structures of the spiral waves is identified. The results not only present a possible and reasonable interpretation to the spiral waves observed in the biological experiment on the brain cortex with disinhibition, but also reveal that the spiral waves exhibit more ordered degree in spatial patterns.

Integrating spatial and numerical structure in mathematical patterning

NASA Astrophysics Data System (ADS)

Ni’mah, K.; Purwanto; Irawan, E. B.; Hidayanto, E.

2018-03-01

This paper reports a study monitoring the integrating spatial and numerical structure in mathematical patterning skills of 30 students grade 7th of junior high school. The purpose of this research is to clarify the processes by which learners construct new knowledge in mathematical patterning. Findings indicate that: (1) students are unable to organize the structure of spatial and numerical, (2) students were only able to organize the spatial structure, but the numerical structure is still incorrect, (3) students were only able to organize numerical structure, but its spatial structure is still incorrect, (4) students were able to organize both of the spatial and numerical structure.

Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells.

PubMed

Recouvreux, Pierre; Sokolowski, Thomas R; Grammoustianou, Aristea; ten Wolde, Pieter Rein; Dogterom, Marileen

2016-02-16

Cell polarity refers to a functional spatial organization of proteins that is crucial for the control of essential cellular processes such as growth and division. To establish polarity, cells rely on elaborate regulation networks that control the distribution of proteins at the cell membrane. In fission yeast cells, a microtubule-dependent network has been identified that polarizes the distribution of signaling proteins that restricts growth to cell ends and targets the cytokinetic machinery to the middle of the cell. Although many molecular components have been shown to play a role in this network, it remains unknown which molecular functionalities are minimally required to establish a polarized protein distribution in this system. Here we show that a membrane-binding protein fragment, which distributes homogeneously in wild-type fission yeast cells, can be made to concentrate at cell ends by attaching it to a cytoplasmic microtubule end-binding protein. This concentration results in a polarized pattern of chimera proteins with a spatial extension that is very reminiscent of natural polarity patterns in fission yeast. However, chimera levels fluctuate in response to microtubule dynamics, and disruption of microtubules leads to disappearance of the pattern. Numerical simulations confirm that the combined functionality of membrane anchoring and microtubule tip affinity is in principle sufficient to create polarized patterns. Our chimera protein may thus represent a simple molecular functionality that is able to polarize the membrane, onto which additional layers of molecular complexity may be built to provide the temporal robustness that is typical of natural polarity patterns.

Secondary ion mass spectrometry imaging and multivariate data analysis reveal co-aggregation patterns of Populus trichocarpa leaf surface compounds on a micrometer scale.

PubMed

Kulkarni, Purva; Dost, Mina; Bulut, Özgül Demir; Welle, Alexander; Böcker, Sebastian; Boland, Wilhelm; Svatoš, Aleš

2018-01-01

Spatially resolved analysis of a multitude of compound classes has become feasible with the rapid advancement in mass spectrometry imaging strategies. In this study, we present a protocol that combines high lateral resolution time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging with a multivariate data analysis (MVA) approach to probe the complex leaf surface chemistry of Populus trichocarpa. Here, epicuticular waxes (EWs) found on the adaxial leaf surface of P. trichocarpa were blotted on silicon wafers and imaged using TOF-SIMS at 10 μm and 1 μm lateral resolution. Intense M +● and M -● molecular ions were clearly visible, which made it possible to resolve the individual compound classes present in EWs. Series of long-chain aliphatic saturated alcohols (C 21 -C 30 ), hydrocarbons (C 25 -C 33 ) and wax esters (WEs; C 44 -C 48 ) were clearly observed. These data correlated with the 7 Li-chelation matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis, which yielded mostly molecular adduct ions of the analyzed compounds. Subsequently, MVA was used to interrogate the TOF-SIMS dataset for identifying hidden patterns on the leaf's surface based on its chemical profile. After the application of principal component analysis (PCA), a small number of principal components (PCs) were found to be sufficient to explain maximum variance in the data. To further confirm the contributions from pure components, a five-factor multivariate curve resolution (MCR) model was applied. Two distinct patterns of small islets, here termed 'crystals', were apparent from the resulting score plots. Based on PCA and MCR results, the crystals were found to be formed by C 23 or C 29 alcohols. Other less obvious patterns observed in the PCs revealed that the adaxial leaf surface is coated with a relatively homogenous layer of alcohols, hydrocarbons and WEs. The ultra-high-resolution TOF-SIMS imaging combined with the MVA approach helped to highlight the diverse patterns underlying the leaf's surface. Currently, the methods available to analyze the surface chemistry of waxes in conjunction with the spatial information related to the distribution of compounds are limited. This study uses tools that may provide important biological insights into the composition of the wax layer, how this layer is repaired after mechanical damage or insect feeding, and which transport mechanisms are involved in deploying wax constituents to specific regions on the leaf surface. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Using spatial patterns in illegal wildlife uses to reveal connections between subsistence hunting and trade.

PubMed

Sánchez-Mercado, Ada; Asmüssen, Marianne; Rodríguez-Clark, Kathryn M; Rodríguez, Jon Paul; Jedrzejewski, Wlodzimierz

2016-12-01

Although most often considered independently, subsistence hunting, domestic trade, and international trade as components of illegal wildlife use (IWU) may be spatially correlated. Understanding how and where subsistence and commercial uses may co-occur has important implications for the design and implementation of effective conservation actions. We analyzed patterns in the joint geographical distribution of illegal commercial and subsistence use of multiple wildlife species in Venezuela and evaluated whether available data were sufficient to provide accurate estimates of the magnitude, scope, and detectability of IWU. We compiled records of illegal subsistence hunting and trade from several sources and fitted a random-forest classification model to predict the spatial distribution of IWUs. From 1969 to 2014, 404 species and 8,340,921 specimens were involved in IWU, for a mean extraction rate of 185,354 individuals/year. Birds were the most speciose group involved (248 spp.), but reptiles had the highest extraction rates (126,414 individuals/year vs. 3,133 individuals/year for birds). Eighty-eight percent of international trade records spatially overlapped with domestic trade, especially in the north and along the coast but also in western inland areas. The distribution of domestic trade was broadly distributed along roads, suggesting that domestic trade does not depend on large markets in cities. Seventeen percent of domestic trade records overlapped with subsistence hunting, but the spatial distribution of this overlap covered a much larger area than between commercial uses. Domestic trade seems to respond to demand from rural more than urban communities. Our approach will be useful for understanding how IWU works at national scales in other parts of the world. © 2016 Society for Conservation Biology.

The Farther the Better: Effects of Multiple Environmental Variables on Reef Fish Assemblages along a Distance Gradient from River Influences.

PubMed

Neves, Leonardo M; Teixeira-Neves, Tatiana P; Pereira-Filho, Guilherme H; Araújo, Francisco G

2016-01-01

The conservation and management of site-attached assemblages of coastal reefs are particularly challenging because of the tremendous environmental variation that exists at small spatial scales. In this sense, understanding the primary sources of variation in spatial patterns of the biota is fundamental for designing effective conservation policies. We investigated spatial variation in fish assemblages around the windward and leeward sides of coastal islands situated across a gradient of riverine influence (13 km in length). Specifically, relationships between rocky reef fish assemblages and benthic, topographic and physical predictors were assessed. We hypothesized that river induced disturbances may overcome local habitat features in modeling spatial patterns of fish distribution. Fish assemblages varied primarily due to the strong directional gradient of riverine influence (22.6% of the estimated components of variation), followed by topographic complexity (15%), wave exposure (9.9%), and benthic cover (8%). The trophic structure of fish assemblages changed from having a high abundance of invertebrate feeders in macroalgae-dominated reefs close to river mouths to a high proportion of herbivores, planktivores and invertebrate feeder species in reefs with large boulders covered by epilithic algal matrices, as the distance from rivers increased. This gradient led to an increase of 4.5-fold in fish richness and fish trophic group diversity, 11-fold in fish biomass and 10-fold in fish abundance. Our results have implications for the conservation and monitoring of assemblages patchily distributed at small spatial scales. The major role of distance from river influences on fish assemblages rather than benthic cover and topographic complexity suggest that managing land-based activities should be a conservation priority toward reef restoration.

Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes

NASA Astrophysics Data System (ADS)

Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.

2017-12-01

Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), soil properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn affect the available soil moisture content. Interestingly, changes in soil properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation differences amplify the soil moisture variability of semi-arid landscapes.

The Farther the Better: Effects of Multiple Environmental Variables on Reef Fish Assemblages along a Distance Gradient from River Influences

PubMed Central

Neves, Leonardo M.; Teixeira-Neves, Tatiana P.; Pereira-Filho, Guilherme H.; Araújo, Francisco G.

2016-01-01

The conservation and management of site-attached assemblages of coastal reefs are particularly challenging because of the tremendous environmental variation that exists at small spatial scales. In this sense, understanding the primary sources of variation in spatial patterns of the biota is fundamental for designing effective conservation policies. We investigated spatial variation in fish assemblages around the windward and leeward sides of coastal islands situated across a gradient of riverine influence (13 km in length). Specifically, relationships between rocky reef fish assemblages and benthic, topographic and physical predictors were assessed. We hypothesized that river induced disturbances may overcome local habitat features in modeling spatial patterns of fish distribution. Fish assemblages varied primarily due to the strong directional gradient of riverine influence (22.6% of the estimated components of variation), followed by topographic complexity (15%), wave exposure (9.9%), and benthic cover (8%). The trophic structure of fish assemblages changed from having a high abundance of invertebrate feeders in macroalgae-dominated reefs close to river mouths to a high proportion of herbivores, planktivores and invertebrate feeder species in reefs with large boulders covered by epilithic algal matrices, as the distance from rivers increased. This gradient led to an increase of 4.5-fold in fish richness and fish trophic group diversity, 11-fold in fish biomass and 10-fold in fish abundance. Our results have implications for the conservation and monitoring of assemblages patchily distributed at small spatial scales. The major role of distance from river influences on fish assemblages rather than benthic cover and topographic complexity suggest that managing land-based activities should be a conservation priority toward reef restoration. PMID:27907017

Estimating spatially distributed turbulent heat fluxes from high-resolution thermal imagery acquired with a UAV system

PubMed Central

Brenner, Claire; Thiem, Christina Elisabeth; Wizemann, Hans-Dieter; Bernhardt, Matthias; Schulz, Karsten

2017-01-01

ABSTRACT In this study, high-resolution thermal imagery acquired with a small unmanned aerial vehicle (UAV) is used to map evapotranspiration (ET) at a grassland site in Luxembourg. The land surface temperature (LST) information from the thermal imagery is the key input to a one-source and two-source energy balance model. While the one-source model treats the surface as a single uniform layer, the two-source model partitions the surface temperature and fluxes into soil and vegetation components. It thus explicitly accounts for the different contributions of both components to surface temperature as well as turbulent flux exchange with the atmosphere. Contrary to the two-source model, the one-source model requires an empirical adjustment parameter in order to account for the effect of the two components. Turbulent heat flux estimates of both modelling approaches are compared to eddy covariance (EC) measurements using the high-resolution input imagery UAVs provide. In this comparison, the effect of different methods for energy balance closure of the EC data on the agreement between modelled and measured fluxes is also analysed. Additionally, the sensitivity of the one-source model to the derivation of the empirical adjustment parameter is tested. Due to the very dry and hot conditions during the experiment, pronounced thermal patterns developed over the grassland site. These patterns result in spatially variable turbulent heat fluxes. The model comparison indicates that both models are able to derive ET estimates that compare well with EC measurements under these conditions. However, the two-source model, with a more complex treatment of the energy and surface temperature partitioning between the soil and vegetation, outperformed the simpler one-source model in estimating sensible and latent heat fluxes. This is consistent with findings from prior studies. For the one-source model, a time-variant expression of the adjustment parameter (to account for the difference between aerodynamic and radiometric temperature) that depends on the surface-to-air temperature gradient yielded the best agreement with EC measurements. This study showed that the applied UAV system equipped with a dual-camera set-up allows for the acquisition of thermal imagery with high spatial and temporal resolution that illustrates the small-scale heterogeneity of thermal surface properties. The UAV-based thermal imagery therefore provides the means for analysing patterns of LST and other surface properties with a high level of detail that cannot be obtained by traditional remote sensing methods. PMID:28515537

Estimating spatially distributed turbulent heat fluxes from high-resolution thermal imagery acquired with a UAV system.

PubMed

Brenner, Claire; Thiem, Christina Elisabeth; Wizemann, Hans-Dieter; Bernhardt, Matthias; Schulz, Karsten

2017-05-19

In this study, high-resolution thermal imagery acquired with a small unmanned aerial vehicle (UAV) is used to map evapotranspiration (ET) at a grassland site in Luxembourg. The land surface temperature (LST) information from the thermal imagery is the key input to a one-source and two-source energy balance model. While the one-source model treats the surface as a single uniform layer, the two-source model partitions the surface temperature and fluxes into soil and vegetation components. It thus explicitly accounts for the different contributions of both components to surface temperature as well as turbulent flux exchange with the atmosphere. Contrary to the two-source model, the one-source model requires an empirical adjustment parameter in order to account for the effect of the two components. Turbulent heat flux estimates of both modelling approaches are compared to eddy covariance (EC) measurements using the high-resolution input imagery UAVs provide. In this comparison, the effect of different methods for energy balance closure of the EC data on the agreement between modelled and measured fluxes is also analysed. Additionally, the sensitivity of the one-source model to the derivation of the empirical adjustment parameter is tested. Due to the very dry and hot conditions during the experiment, pronounced thermal patterns developed over the grassland site. These patterns result in spatially variable turbulent heat fluxes. The model comparison indicates that both models are able to derive ET estimates that compare well with EC measurements under these conditions. However, the two-source model, with a more complex treatment of the energy and surface temperature partitioning between the soil and vegetation, outperformed the simpler one-source model in estimating sensible and latent heat fluxes. This is consistent with findings from prior studies. For the one-source model, a time-variant expression of the adjustment parameter (to account for the difference between aerodynamic and radiometric temperature) that depends on the surface-to-air temperature gradient yielded the best agreement with EC measurements. This study showed that the applied UAV system equipped with a dual-camera set-up allows for the acquisition of thermal imagery with high spatial and temporal resolution that illustrates the small-scale heterogeneity of thermal surface properties. The UAV-based thermal imagery therefore provides the means for analysing patterns of LST and other surface properties with a high level of detail that cannot be obtained by traditional remote sensing methods.

Interaction of Soil Heavy Metal Pollution with Industrialisation and the Landscape Pattern in Taiyuan City, China

PubMed Central

Liu, Yong; Su, Chao; Zhang, Hong; Li, Xiaoting; Pei, Jingfei

2014-01-01

Many studies indicated that industrialization and urbanization caused serious soil heavy metal pollution from industrialized age. However, fewer previous studies have conducted a combined analysis of the landscape pattern, urbanization, industrialization, and heavy metal pollution. This paper was aimed at exploring the relationships of heavy metals in the soil (Pb, Cu, Ni, As, Cd, Cr, Hg, and Zn) with landscape pattern, industrialisation, urbanisation in Taiyuan city using multivariate analysis. The multivariate analysis included correlation analysis, analysis of variance (ANOVA), independent-sample T test, and principal component analysis (PCA). Geographic information system (GIS) was also applied to determine the spatial distribution of the heavy metals. The spatial distribution maps showed that the heavy metal pollution of the soil was more serious in the centre of the study area. The results of the multivariate analysis indicated that the correlations among heavy metals were significant, and industrialisation could significantly affect the concentrations of some heavy metals. Landscape diversity showed a significant negative correlation with the heavy metal concentrations. The PCA showed that a two-factor model for heavy metal pollution, industrialisation, and the landscape pattern could effectively demonstrate the relationships between these variables. The model explained 86.71% of the total variance of the data. Moreover, the first factor was mainly loaded with the comprehensive pollution index (P), and the second factor was primarily loaded with landscape diversity and dominance (H and D). An ordination of 80 samples could show the pollution pattern of all the samples. The results revealed that local industrialisation caused heavy metal pollution of the soil, but such pollution could respond negatively to the landscape pattern. The results of the study could provide a basis for agricultural, suburban, and urban planning. PMID:25251460

Interaction of soil heavy metal pollution with industrialisation and the landscape pattern in Taiyuan city, China.

PubMed

Liu, Yong; Su, Chao; Zhang, Hong; Li, Xiaoting; Pei, Jingfei

2014-01-01

Many studies indicated that industrialization and urbanization caused serious soil heavy metal pollution from industrialized age. However, fewer previous studies have conducted a combined analysis of the landscape pattern, urbanization, industrialization, and heavy metal pollution. This paper was aimed at exploring the relationships of heavy metals in the soil (Pb, Cu, Ni, As, Cd, Cr, Hg, and Zn) with landscape pattern, industrialisation, urbanisation in Taiyuan city using multivariate analysis. The multivariate analysis included correlation analysis, analysis of variance (ANOVA), independent-sample T test, and principal component analysis (PCA). Geographic information system (GIS) was also applied to determine the spatial distribution of the heavy metals. The spatial distribution maps showed that the heavy metal pollution of the soil was more serious in the centre of the study area. The results of the multivariate analysis indicated that the correlations among heavy metals were significant, and industrialisation could significantly affect the concentrations of some heavy metals. Landscape diversity showed a significant negative correlation with the heavy metal concentrations. The PCA showed that a two-factor model for heavy metal pollution, industrialisation, and the landscape pattern could effectively demonstrate the relationships between these variables. The model explained 86.71% of the total variance of the data. Moreover, the first factor was mainly loaded with the comprehensive pollution index (P), and the second factor was primarily loaded with landscape diversity and dominance (H and D). An ordination of 80 samples could show the pollution pattern of all the samples. The results revealed that local industrialisation caused heavy metal pollution of the soil, but such pollution could respond negatively to the landscape pattern. The results of the study could provide a basis for agricultural, suburban, and urban planning.

Spatial scaling patterns and functional redundancies in a changing boreal lake landscape

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Uden, Daniel R.; Johnson, Richard K.

2015-01-01

Global transformations extend beyond local habitats; therefore, larger-scale approaches are needed to assess community-level responses and resilience to unfolding environmental changes. Using longterm data (1996–2011), we evaluated spatial patterns and functional redundancies in the littoral invertebrate communities of 85 Swedish lakes, with the objective of assessing their potential resilience to environmental change at regional scales (that is, spatial resilience). Multivariate spatial modeling was used to differentiate groups of invertebrate species exhibiting spatial patterns in composition and abundance (that is, deterministic species) from those lacking spatial patterns (that is, stochastic species). We then determined the functional feeding attributes of the deterministic and stochastic invertebrate species, to infer resilience. Between one and three distinct spatial patterns in invertebrate composition and abundance were identified in approximately one-third of the species; the remainder were stochastic. We observed substantial differences in metrics between deterministic and stochastic species. Functional richness and diversity decreased over time in the deterministic group, suggesting a loss of resilience in regional invertebrate communities. However, taxon richness and redundancy increased monotonically in the stochastic group, indicating the capacity of regional invertebrate communities to adapt to change. Our results suggest that a refined picture of spatial resilience emerges if patterns of both the deterministic and stochastic species are accounted for. Spatially extensive monitoring may help increase our mechanistic understanding of community-level responses and resilience to regional environmental change, insights that are critical for developing management and conservation agendas in this current period of rapid environmental transformation.

Using spatial analysis to demonstrate the heterogeneity of the cardiovascular drug-prescribing pattern in Taiwan

PubMed Central

2011-01-01

Background Geographic Information Systems (GIS) combined with spatial analytical methods could be helpful in examining patterns of drug use. Little attention has been paid to geographic variation of cardiovascular prescription use in Taiwan. The main objective was to use local spatial association statistics to test whether or not the cardiovascular medication-prescribing pattern is homogenous across 352 townships in Taiwan. Methods The statistical methods used were the global measures of Moran's I and Local Indicators of Spatial Association (LISA). While Moran's I provides information on the overall spatial distribution of the data, LISA provides information on types of spatial association at the local level. LISA statistics can also be used to identify influential locations in spatial association analysis. The major classes of prescription cardiovascular drugs were taken from Taiwan's National Health Insurance Research Database (NHIRD), which has a coverage rate of over 97%. The dosage of each prescription was converted into defined daily doses to measure the consumption of each class of drugs. Data were analyzed with ArcGIS and GeoDa at the township level. Results The LISA statistics showed an unusual use of cardiovascular medications in the southern townships with high local variation. Patterns of drug use also showed more low-low spatial clusters (cold spots) than high-high spatial clusters (hot spots), and those low-low associations were clustered in the rural areas. Conclusions The cardiovascular drug prescribing patterns were heterogeneous across Taiwan. In particular, a clear pattern of north-south disparity exists. Such spatial clustering helps prioritize the target areas that require better education concerning drug use. PMID:21609462

The GeoViz Toolkit: Using component-oriented coordination methods for geographic visualization and analysis

PubMed Central

Hardisty, Frank; Robinson, Anthony C.

2010-01-01

In this paper we present the GeoViz Toolkit, an open-source, internet-delivered program for geographic visualization and analysis that features a diverse set of software components which can be flexibly combined by users who do not have programming expertise. The design and architecture of the GeoViz Toolkit allows us to address three key research challenges in geovisualization: allowing end users to create their own geovisualization and analysis component set on-the-fly, integrating geovisualization methods with spatial analysis methods, and making geovisualization applications sharable between users. Each of these tasks necessitates a robust yet flexible approach to inter-tool coordination. The coordination strategy we developed for the GeoViz Toolkit, called Introspective Observer Coordination, leverages and combines key advances in software engineering from the last decade: automatic introspection of objects, software design patterns, and reflective invocation of methods. PMID:21731423

Balancing geo-privacy and spatial patterns in epidemiological studies.

PubMed

Chen, Chien-Chou; Chuang, Jen-Hsiang; Wang, Da-Wei; Wang, Chien-Min; Lin, Bo-Cheng; Chan, Ta-Chien

2017-11-08

To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-spatial tool (GeoMasker) intended to mask the residential locations of patients or cases in a geographic information system (GIS). To elucidate the effects of geo-masking parameters, we applied 2010 dengue epidemic data from Taiwan testing the tool's performance in an empirical situation. The similarity of pre- and post-spatial patterns was measured by D statistics under a 95% confidence interval. In the empirical study, different magnitudes of anonymisation (estimated Kanonymity ≥10 and 100) were achieved and different degrees of agreement on the pre- and post-patterns were evaluated. The application is beneficial for public health workers and researchers when processing data with individuals' spatial information.

Pattern transitions in spatial epidemics: Mechanisms and emergent properties.

PubMed

Sun, Gui-Quan; Jusup, Marko; Jin, Zhen; Wang, Yi; Wang, Zhen

2016-12-01

Infectious diseases are a threat to human health and a hindrance to societal development. Consequently, the spread of diseases in both time and space has been widely studied, revealing the different types of spatial patterns. Transitions between patterns are an emergent property in spatial epidemics that can serve as a potential trend indicator of disease spread. Despite the usefulness of such an indicator, attempts to systematize the topic of pattern transitions have been few and far between. We present a mini-review on pattern transitions in spatial epidemics, describing the types of transitions and their underlying mechanisms. We show that pattern transitions relate to the complexity of spatial epidemics by, for example, being accompanied with phenomena such as coherence resonance and cyclic evolution. The results presented herein provide valuable insights into disease prevention and control, and may even be applicable outside epidemiology, including other branches of medical science, ecology, quantitative finance, and elsewhere. Copyright © 2016 Elsevier B.V. All rights reserved.

An exploration of spatial patterns of seasonal diarrhoeal morbidity in Thailand.

PubMed

McCormick, B J J; Alonso, W J; Miller, M A

2012-07-01

Studies of temporal and spatial patterns of diarrhoeal disease can suggest putative aetiological agents and environmental or socioeconomic drivers. Here, the seasonal patterns of monthly acute diarrhoeal morbidity in Thailand, where diarrhoeal morbidity is increasing, are explored. Climatic data (2003-2006) and Thai Ministry of Health annual reports (2003-2009) were used to construct a spatially weighted panel regression model. Seasonal patterns of diarrhoeal disease were generally bimodal with aetiological agents peaking at different times of the year. There is a strong association between daily mean temperature and precipitation and the incidence of hospitalization due to acute diarrhoea in Thailand leading to a distinct spatial pattern in the seasonal pattern of diarrhoea. Model performance varied across the country in relation to per capita GDP and population density. While climatic factors are likely to drive the general pattern of diarrhoeal disease in Thailand, the seasonality of diarrhoeal disease is dampened in affluent urban populations.

Geospatial Data Stream Processing in Python Using FOSS4G Components

NASA Astrophysics Data System (ADS)

McFerren, G.; van Zyl, T.

2016-06-01

One viewpoint of current and future IT systems holds that there is an increase in the scale and velocity at which data are acquired and analysed from heterogeneous, dynamic sources. In the earth observation and geoinformatics domains, this process is driven by the increase in number and types of devices that report location and the proliferation of assorted sensors, from satellite constellations to oceanic buoy arrays. Much of these data will be encountered as self-contained messages on data streams - continuous, infinite flows of data. Spatial analytics over data streams concerns the search for spatial and spatio-temporal relationships within and amongst data "on the move". In spatial databases, queries can assess a store of data to unpack spatial relationships; this is not the case on streams, where spatial relationships need to be established with the incomplete data available. Methods for spatially-based indexing, filtering, joining and transforming of streaming data need to be established and implemented in software components. This article describes the usage patterns and performance metrics of a number of well known FOSS4G Python software libraries within the data stream processing paradigm. In particular, we consider the RTree library for spatial indexing, the Shapely library for geometric processing and transformation and the PyProj library for projection and geodesic calculations over streams of geospatial data. We introduce a message oriented Python-based geospatial data streaming framework called Swordfish, which provides data stream processing primitives, functions, transports and a common data model for describing messages, based on the Open Geospatial Consortium Observations and Measurements (O&M) and Unidata Common Data Model (CDM) standards. We illustrate how the geospatial software components are integrated with the Swordfish framework. Furthermore, we describe the tight temporal constraints under which geospatial functionality can be invoked when processing high velocity, potentially infinite geospatial data streams. The article discusses the performance of these libraries under simulated streaming loads (size, complexity and volume of messages) and how they can be deployed and utilised with Swordfish under real load scenarios, illustrated by a set of Vessel Automatic Identification System (AIS) use cases. We conclude that the described software libraries are able to perform adequately under geospatial data stream processing scenarios - many real application use cases will be handled sufficiently by the software.

Simple Process-Based Simulators for Generating Spatial Patterns of Habitat Loss and Fragmentation: A Review and Introduction to the G-RaFFe Model

PubMed Central

Pe'er, Guy; Zurita, Gustavo A.; Schober, Lucia; Bellocq, Maria I.; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model “G-RaFFe” generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non-fractal in nature. PMID:23724108

Simple process-based simulators for generating spatial patterns of habitat loss and fragmentation: a review and introduction to the G-RaFFe model.

PubMed

Pe'er, Guy; Zurita, Gustavo A; Schober, Lucia; Bellocq, Maria I; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model "G-RaFFe" generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non-fractal in nature.

Spatial Analysis of Hospital Incidence and in Hospital Mortality of Abdominal Aortic Aneurysms in Germany: Secondary Data Analysis of Nationwide Hospital Episode (DRG) Data.

PubMed

Kuehnl, Andreas; Salvermoser, Michael; Erk, Alexander; Trenner, Matthias; Schmid, Volker; Eckstein, Hans-Henning

2018-06-01

This study aimed to analyze the spatial distribution and regional variation of the hospital incidence and in hospital mortality of abdominal aortic aneurysms (AAA) in Germany. German DRG statistics (2011-2014) were analysed. Patients with ruptured AAA (rAAA, I71.3, treated or not) and patients with non-ruptured AAA (nrAAA, I71.4, treated by open or endovascular aneurysm repair) were included. Age, sex, and risk standardisation was done using standard statistical procedures. Regional variation was quantified using systematic component of variation. To analyse spatial auto-correlation and spatial pattern, global Moran's I and Getis-Ord Gi* were calculated. A total of 50,702 cases were included. Raw hospital incidence of AAA was 15.7 per 100,000 inhabitants (nrAAA 13.1; all rAAA 2.7; treated rAAA 1.6). The standardised hospital incidence of AAA ranged from 6.3 to 30.3 per 100,000. Systematic component of variation proportion was 96% in nrAAA and 55% in treated rAAA. Incidence rates of all AAA were significantly clustered with above average values in the northwestern parts of Germany and below average values in the south and eastern regions. Standardised mortality of nrAAA ranged from 1.7% to 4.3%, with that of treated rAAA ranging from 28% to 52%. Regional variation and spatial distribution of standardised mortality was not different from random. There was significant regional variation and clustering of the hospital incidence of AAA in Germany, with higher rates in the northwest and lower rates in the southeast. There was no significant variation in standardised (age/sex/risk) mortality between counties. Copyright © 2018. Published by Elsevier B.V.

Quantifying Sources and Fluxes of Aquatic Carbon in U.S. Streams and Reservoirs Using Spatially Referenced Regression Models

NASA Astrophysics Data System (ADS)

Boyer, E. W.; Smith, R. A.; Alexander, R. B.; Schwarz, G. E.

2004-12-01

Organic carbon (OC) is a critical water quality characteristic in riverine systems that is an important component of the aquatic carbon cycle and energy balance. Examples of processes controlled by OC interactions are complexation of trace metals; enhancement of the solubility of hydrophobic organic contaminants; formation of trihalomethanes in drinking water; and absorption of visible and UV radiation. Organic carbon also can have indirect effects on water quality by influencing internal processes of aquatic ecosystems (e.g. photosynthesis and autotrophic and heterotrophic activity). The importance of organic matter dynamics on water quality has been recognized, but challenges remain in quantitatively addressing OC processes over broad spatial scales in a hydrological context. In this study, we apply spatially referenced watershed models (SPARROW) to statistically estimate long-term mean-annual rates of dissolved- and total- organic carbon export in streams and reservoirs across the conterminous United States. We make use of a GIS framework for the analysis, describing sources, transport, and transformations of organic matter from spatial databases providing characterizations of climate, land use, primary productivity, topography, soils, and geology. This approach is useful because it illustrates spatial patterns of organic carbon fluxes in streamflow, highlighting hot spots (e.g., organic-rich environments in the southeastern coastal plain). Further, our simulations provide estimates of the relative contributions to streams from allochthonous and autochthonous sources. We quantify surface water fluxes of OC with estimates of uncertainty in relation to the overall US carbon budget; our simulations highlight that aquatic sources and sinks of OC may be a more significant component of regional carbon cycling than was previously thought. Further, we are using our simulations to explore the potential role of climate and other changes in the terrestrial environment on OC fluxes in aquatic systems.

Mapping multi-scale vascular plant richness in a forest landscape with integrated LiDAR and hyperspectral remote-sensing.

PubMed

Hakkenberg, C R; Zhu, K; Peet, R K; Song, C

2018-02-01

The central role of floristic diversity in maintaining habitat integrity and ecosystem function has propelled efforts to map and monitor its distribution across forest landscapes. While biodiversity studies have traditionally relied largely on ground-based observations, the immensity of the task of generating accurate, repeatable, and spatially-continuous data on biodiversity patterns at large scales has stimulated the development of remote-sensing methods for scaling up from field plot measurements. One such approach is through integrated LiDAR and hyperspectral remote-sensing. However, despite their efficiencies in cost and effort, LiDAR-hyperspectral sensors are still highly constrained in structurally- and taxonomically-heterogeneous forests - especially when species' cover is smaller than the image resolution, intertwined with neighboring taxa, or otherwise obscured by overlapping canopy strata. In light of these challenges, this study goes beyond the remote characterization of upper canopy diversity to instead model total vascular plant species richness in a continuous-cover North Carolina Piedmont forest landscape. We focus on two related, but parallel, tasks. First, we demonstrate an application of predictive biodiversity mapping, using nonparametric models trained with spatially-nested field plots and aerial LiDAR-hyperspectral data, to predict spatially-explicit landscape patterns in floristic diversity across seven spatial scales between 0.01-900 m 2 . Second, we employ bivariate parametric models to test the significance of individual, remotely-sensed predictors of plant richness to determine how parameter estimates vary with scale. Cross-validated results indicate that predictive models were able to account for 15-70% of variance in plant richness, with LiDAR-derived estimates of topography and forest structural complexity, as well as spectral variance in hyperspectral imagery explaining the largest portion of variance in diversity levels. Importantly, bivariate tests provide evidence of scale-dependence among predictors, such that remotely-sensed variables significantly predict plant richness only at spatial scales that sufficiently subsume geolocational imprecision between remotely-sensed and field data, and best align with stand components including plant size and density, as well as canopy gaps and understory growth patterns. Beyond their insights into the scale-dependent patterns and drivers of plant diversity in Piedmont forests, these results highlight the potential of remotely-sensible essential biodiversity variables for mapping and monitoring landscape floristic diversity from air- and space-borne platforms. © 2017 by the Ecological Society of America.

Printing of Patterned, Engineered E. coli Biofilms with a Low-Cost 3D Printer.

PubMed

Schmieden, Dominik T; Basalo Vázquez, Samantha J; Sangüesa, Héctor; van der Does, Marit; Idema, Timon; Meyer, Anne S

2018-05-18

Biofilms can grow on virtually any surface available, with impacts ranging from endangering the lives of patients to degrading unwanted water contaminants. Biofilm research is challenging due to the high degree of biofilm heterogeneity. A method for the production of standardized, reproducible, and patterned biofilm-inspired materials could be a boon for biofilm research and allow for completely new engineering applications. Here, we present such a method, combining 3D printing with genetic engineering. We prototyped a low-cost 3D printer that prints bioink, a suspension of bacteria in a solution of alginate that solidifies on a calcium-containing substrate. We 3D-printed Escherichia coli in different shapes and in discrete layers, after which the cells survived in the printing matrix for at least 1 week. When printed bacteria were induced to form curli fibers, the major proteinaceous extracellular component of E. coli biofilms, they remained adherent to the printing substrate and stably spatially patterned even after treatment with a matrix-dissolving agent, indicating that a biofilm-mimicking structure had formed. This work is the first demonstration of patterned, biofilm-inspired living materials that are produced by genetic control over curli formation in combination with spatial control by 3D printing. These materials could be used as living, functional materials in applications such as water filtration, metal ion sequestration, or civil engineering, and potentially as standardizable models for certain curli-containing biofilms.

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.

Spatial Pattern of Attacks of the Invasive Woodwasp Sirex noctilio, at Landscape and Stand Scales.

PubMed

Lantschner, M Victoria; Corley, Juan C

2015-01-01

Invasive insect pests are responsible for important damage to native and plantation forests, when population outbreaks occur. Understanding the spatial pattern of attacks by forest pest populations is essential to improve our understanding of insect population dynamics and for predicting attack risk by invasives or planning pest management strategies. The woodwasp Sirex noctilio is an invasive woodwasp that has become probably the most important pest of pine plantations in the Southern Hemisphere. Our aim was to study the spatial dynamics of S. noctilio populations in Southern Argentina. Specifically we describe: (1) the spatial patterns of S. noctilio outbreaks and their relation with environmental factors at a landscape scale; and (2) characterize the spatial pattern of attacked trees at the stand scale. We surveyed the spatial distribution of S. noctilio outbreaks in three pine plantation landscapes, and we assessed potential associations with topographic variables, habitat characteristics, and distance to other outbreaks. We also looked at the spatial distribution of attacked trees in 20 stands with different levels of infestation, and assessed the relationship of attacks with stand composition and management. We found that the spatial pattern of pine stands with S. noctilio outbreaks at the landscape scale is influenced mainly by the host species present, slope aspect, and distance to other outbreaks. At a stand scale, there is strong aggregation of attacked trees in stands with intermediate infestation levels, and the degree of attacks is influenced by host species and plantation management. We conclude that the pattern of S. noctilio damage at different spatial scales is influenced by a combination of both inherent population dynamics and the underlying patterns of environmental factors. Our results have important implications for the understanding and management of invasive insect outbreaks in forest systems.

Describing spatial pattern in stream networks: A practical approach

USGS Publications Warehouse

Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.

2005-01-01

The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.

A geostatistical approach for describing spatial pattern in stream networks

USGS Publications Warehouse

Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.

2005-01-01

The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.

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

NASA Astrophysics Data System (ADS)

Wang, J.; Cai, X.

2007-12-01

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

Point pattern analysis of FIA data

Treesearch

Chris Woodall

2002-01-01

Point pattern analysis is a branch of spatial statistics that quantifies the spatial distribution of points in two-dimensional space. Point pattern analysis was conducted on stand stem-maps from FIA fixed-radius plots to explore point pattern analysis techniques and to determine the ability of pattern descriptions to describe stand attributes. Results indicate that the...

Phase separation driven by density-dependent movement: A novel mechanism for ecological patterns.

PubMed

Liu, Quan-Xing; Rietkerk, Max; Herman, Peter M J; Piersma, Theunis; Fryxell, John M; van de Koppel, Johan

2016-12-01

Many ecosystems develop strikingly regular spatial patterns because of small-scale interactions between organisms, a process generally referred to as spatial self-organization. Self-organized spatial patterns are important determinants of the functioning of ecosystems, promoting the growth and survival of the involved organisms, and affecting the capacity of the organisms to cope with changing environmental conditions. The predominant explanation for self-organized pattern formation is spatial heterogeneity in establishment, growth and mortality, resulting from the self-organization processes. A number of recent studies, however, have revealed that movement of organisms can be an important driving process creating extensive spatial patterning in many ecosystems. Here, we review studies that detail movement-based pattern formation in contrasting ecological settings. Our review highlights that a common principle, where movement of organisms is density-dependent, explains observed spatial regular patterns in all of these studies. This principle, well known to physics as the Cahn-Hilliard principle of phase separation, has so-far remained unrecognized as a general mechanism for self-organized complexity in ecology. Using the examples presented in this paper, we explain how this movement principle can be discerned in ecological settings, and clarify how to test this mechanism experimentally. Our study highlights that animal movement, both in isolation and in unison with other processes, is an important mechanism for regular pattern formation in ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.

Relationships between landscape pattern and land surface temperature and their applications to the study of West Nile Virus: As case studies in cities of Indianapolis and Chicago, United States

NASA Astrophysics Data System (ADS)

Liu, Hua

A new synthesis of remote sensing and landscape ecology approaches was developed to establish relationships between the landscape patterns and land surface temperatures (LST) in the city of Indianapolis, Indiana, United States. Land use and land cover (LULC) and LST images were derived from Terra Satellite's Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. An analytical procedure using landscape metrics was developed, applying configuration analysis of landscape patterns and land surface temperature zones. Detailed landscape pattern analyses at the landscape and class scales were conducted using landscape metrics in the City of Indianapolis. The effects of spatial resolution on the identification of the relationship were examined in the same city. The best level of equalization between the LULC and LST maps was determined based on minimum distance analysis in landscape metrics space. The analyses of relationships between the landscape patterns and land surface temperatures, and scaling effects were applied to the spread of West Nile Virus (WNV) in the City of Chicago, Illinois. Results show that urban, forest, and grassland were the main landscape components in Indianapolis. They possessed relatively higher fractal dimensions but lower spatial aggregation levels in April 5, 2004, June 16, 2001, and October 3, 2000, but not in February 6, 2006. Obvious seasonal differences existed with the most distinct landscape pattern detected on February 6, 2006. Urban was the dominant LULC type in high-temperature zones, while water and vegetation mainly fell in low-temperature zones. For each individual date, the metrics of LST zones apparently corresponded to the metrics of LULC types. In the study of scaling-up effect analysis, Patch Percentage, Patch Density, and Landscape Shape index were found to be able to effectively quantify the spatial changes of LULC types and temperature zones at different scales without contradiction. Urban, forest, and grassland in each season were more easily affected by the process in Patch Density and Landscape Shape index. Ninety meters was believed to be the optimal spatial resolution to examine relationships between landscape patterns and LSTs in the City of Indianapolis. In the study of the spread of West Nile Virus in the City of Chicago, WNV was found to have been spread throughout all of Cook County since 2001. Landscape factors, like landscape aggregation index and areas of urban, grass, and water showed a strong correlation with the number of WNV infections. Socioeconomic conditions, like population above 65 years old also showed a strong relationship with the spread of WNV in Cook County. Thermal conditions of water had a lower but still significant correlation to the spread of WNV. This research offers an opportunity to explore the mechanism of interaction between urban landscape patterns and land surface temperatures at different spatial scales, and show the effects of landscape pattern and land surface temperature on the spread of West Nile Virus. This study can be useful for urban planning and environmental management practices in the studied areas. It also contributes to public health management and protection.

Movement is the glue connecting home ranges and habitat selection.

PubMed

Van Moorter, Bram; Rolandsen, Christer M; Basille, Mathieu; Gaillard, Jean-Michel

2016-01-01

Animal space use has been studied by focusing either on geographic (e.g. home ranges, species' distribution) or on environmental (e.g. habitat use and selection) space. However, all patterns of space use emerge from individual movements, which are the primary means by which animals change their environment. Individuals increase their use of a given area by adjusting two key movement components: the duration of their visit and/or the frequency of revisits. Thus, in spatially heterogeneous environments, animals exploit known, high-quality resource areas by increasing their residence time (RT) in and/or decreasing their time to return (TtoR) to these areas. We expected that spatial variation in these two movement properties should lead to observed patterns of space use in both geographic and environmental spaces. We derived a set of nine predictions linking spatial distribution of movement properties to emerging space-use patterns. We predicted that, at a given scale, high variation in RT and TtoR among habitats leads to strong habitat selection and that long RT and short TtoR result in a small home range size. We tested these predictions using moose (Alces alces) GPS tracking data. We first modelled the relationship between landscape characteristics and movement properties. Then, we investigated how the spatial distribution of predicted movement properties (i.e. spatial autocorrelation, mean, and variance of RT and TtoR) influences home range size and hierarchical habitat selection. In landscapes with high spatial autocorrelation of RT and TtoR, a high variation in both RT and TtoR occurred in home ranges. As expected, home range location was highly selective in such landscapes (i.e. second-order habitat selection); RT was higher and TtoR lower within the selected home range than outside, and moose home ranges were small. Within home ranges, a higher variation in both RT and TtoR was associated with higher selectivity among habitat types (i.e. third-order habitat selection). Our findings show how patterns of geographic and environmental space use correspond to the two sides of a coin, linked by movement responses of individuals to environmental heterogeneity. By demonstrating the potential to assess the consequences of altering RT or TtoR (e.g. through human disturbance or climatic changes) on home range size and habitat selection, our work sets the basis for new theoretical and methodological advances in movement ecology. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

Spatiotemporal variability of rainfall extremes in monsoonal climates - examples from the South American Monsoon and the Indian Monsoon Systems (Invited)

NASA Astrophysics Data System (ADS)

Bookhagen, B.; Boers, N.; Marwan, N.; Malik, N.; Kurths, J.

2013-12-01

Monsoonal rainfall is the crucial component for more than half of the world's population. Runoff associated with monsoon systems provide water resources for agriculture, hydropower, drinking-water generation, recreation, and social well-being and are thus a fundamental part of human society. However, monsoon systems are highly stochastic and show large variability on various timescales. Here, we use various rainfall datasets to characterize spatiotemporal rainfall patterns using traditional as well as new approaches emphasizing nonlinear spatial correlations from a complex networks perspective. Our analyses focus on the South American (SAMS) and Indian (ISM) Monsoon Systems on the basis of Tropical Rainfall Measurement Mission (TRMM) using precipitation radar and passive-microwave products with horizontal spatial resolutions of ~5x5 km^2 (products 2A25, 2B31) and 25x25 km^2 (3B42) and interpolated rainfall-gauge data for the ISM (APHRODITE, 25x25 km^2). The eastern slopes of the Andes of South America and the southern front of the Himalaya are characterized by significant orographic barriers that intersect with the moisture-bearing, monsoonal wind systems. We demonstrate that topography exerts a first-order control on peak rainfall amounts on annual timescales in both mountain belts. Flooding in the downstream regions is dominantly caused by heavy rainfall storms that propagate deep into the mountain range and reach regions that are arid and without vegetation cover promoting rapid runoff. These storms exert a significantly different spatial distribution than average-rainfall conditions and assessing their recurrence intervals and prediction is key in understanding flooding for these regions. An analysis of extreme-value distributions of our high-spatial resolution data reveal that semi-arid areas are characterized by low-frequency/high-magnitude events (i.e., are characterized by a ';heavy tail' distribution), whereas regions with high mean annual rainfall have a less skewed distribution. In a second step, an analysis of the spatial characteristics of extreme rainfall synchronicity by means of complex networks reveals patterns of the propagation of extreme rainfall events. These patterns differ substantially from those obtained from the mean annual rainfall distribution. In addition, we have developed a scheme to predict rainfall extreme events in the eastern Central Andes based on event synchronization and spatial patterns of complex networks. The presented methods and result will allow to critically evaluate data and models in space and time.

Geospatial Characterization of Fluvial Wood Arrangement in a Semi-confined Alluvial River

NASA Astrophysics Data System (ADS)

Martin, D. J.; Harden, C. P.; Pavlowsky, R. T.

2014-12-01

Large woody debris (LWD) has become universally recognized as an integral component of fluvial systems, and as a result, has become increasingly common as a river restoration tool. However, "natural" processes of wood recruitment and the subsequent arrangement of LWD within the river network are poorly understood. This research used a suite of spatial statistics to investigate longitudinal arrangement patterns of LWD in a low-gradient, Midwestern river. First, a large-scale GPS inventory of LWD, performed on the Big River in the eastern Missouri Ozarks, resulted in over 4,000 logged positions of LWD along seven river segments that covered nearly 100 km of the 237 km river system. A global Moran's I analysis indicates that LWD density is spatially autocorrelated and displays a clustering tendency within all seven river segments (P-value range = 0.000 to 0.054). A local Moran's I analysis identified specific locations along the segments where clustering occurs and revealed that, on average, clusters of LWD density (high or low) spanned 400 m. Spectral analyses revealed that, in some segments, LWD density is spatially periodic. Two segments displayed strong periodicity, while the remaining segments displayed varying degrees of noisiness. Periodicity showed a positive association with gravel bar spacing and meander wavelength, although there were insufficient data to statistically confirm the relationship. A wavelet analysis was then performed to investigate periodicity relative to location along the segment. The wavelet analysis identified significant (α = 0.05) periodicity at discrete locations along each of the segments. Those reaches yielding strong periodicity showed stronger relationships between LWD density and the geomorphic/riparian independent variables tested. Analyses consistently identified valley width and sinuosity as being associated with LWD density. The results of these analyses contribute a new perspective on the longitudinal distribution of LWD in a river system, which should help identify physical and/or riparian control mechanisms of LWD arrangement and support the development of models of LWD arrangement. Additionally, the spatial statistical tools presented here have shown to be valuable for identifying longitudinal patterns in river system components.

Individual subject classification for Alzheimer's disease based on incremental learning using a spatial frequency representation of cortical thickness data.

PubMed

Cho, Youngsang; Seong, Joon-Kyung; Jeong, Yong; Shin, Sung Yong

2012-02-01

Patterns of brain atrophy measured by magnetic resonance structural imaging have been utilized as significant biomarkers for diagnosis of Alzheimer's disease (AD). However, brain atrophy is variable across patients and is non-specific for AD in general. Thus, automatic methods for AD classification require a large number of structural data due to complex and variable patterns of brain atrophy. In this paper, we propose an incremental method for AD classification using cortical thickness data. We represent the cortical thickness data of a subject in terms of their spatial frequency components, employing the manifold harmonic transform. The basis functions for this transform are obtained from the eigenfunctions of the Laplace-Beltrami operator, which are dependent only on the geometry of a cortical surface but not on the cortical thickness defined on it. This facilitates individual subject classification based on incremental learning. In general, methods based on region-wise features poorly reflect the detailed spatial variation of cortical thickness, and those based on vertex-wise features are sensitive to noise. Adopting a vertex-wise cortical thickness representation, our method can still achieve robustness to noise by filtering out high frequency components of the cortical thickness data while reflecting their spatial variation. This compromise leads to high accuracy in AD classification. We utilized MR volumes provided by Alzheimer's Disease Neuroimaging Initiative (ADNI) to validate the performance of the method. Our method discriminated AD patients from Healthy Control (HC) subjects with 82% sensitivity and 93% specificity. It also discriminated Mild Cognitive Impairment (MCI) patients, who converted to AD within 18 months, from non-converted MCI subjects with 63% sensitivity and 76% specificity. Moreover, it showed that the entorhinal cortex was the most discriminative region for classification, which is consistent with previous pathological findings. In comparison with other classification methods, our method demonstrated high classification performance in both categories, which supports the discriminative power of our method in both AD diagnosis and AD prediction. Copyright © 2011 Elsevier Inc. All rights reserved.

Use of multivariate analysis for determining sources of solutes found in wet atmospheric deposition in the United States

USGS Publications Warehouse

Hooper, R.P.; Peters, N.E.

1989-01-01

A principal-components analysis was performed on the major solutes in wet deposition collected from 194 stations in the United States and its territories. Approximately 90% of the components derived could be interpreted as falling into one of three categories - acid, salt, or an agricultural/soil association. The total mass, or the mass of any one solute, was apportioned among these components by multiple linear regression techniques. The use of multisolute components for determining trends or spatial distribution represents a substantial improvement over single-solute analysis in that these components are more directly related to the sources of the deposition. The geographic patterns displayed by the components in this analysis indicate a far more important role for acid deposition in the Southeast and intermountain regions of the United States than would be indicated by maps of sulfate or nitrate deposition alone. In the Northeast and Midwest, the acid component is not declining at most stations, as would be expected from trends in sulfate deposition, but is holding constant or increasing. This is due, in part, to a decline in the agriculture/soil factor throughout this region, which would help to neutralize the acidity.

Spatial variation in diesel-related elemental and organic PM2.5 components during workweek hours across a downtown core.

PubMed

Tunno, Brett J; Shmool, Jessie L C; Michanowicz, Drew R; Tripathy, Sheila; Chubb, Lauren G; Kinnee, Ellen; Cambal, Leah; Roper, Courtney; Clougherty, Jane E

2016-12-15

Capturing intra-urban variation in diesel-related pollution exposures remains a challenge, given its complex chemical mix, and relatively few well-characterized ambient-air tracers for the multiple diesel sources in densely-populated urban areas. To capture fine-scale spatial resolution (50×50m grid cells) in diesel-related pollution, we used geographic information systems (GIS) to systematically allocate 36 sampling sites across downtown Pittsburgh, PA, USA (2.8km 2 ), cross-stratifying to disentangle source impacts (i.e., truck density, bus route frequency, total traffic density). For buses, outbound and inbound trips per week were summed by route and a kernel density was calculated across sites. Programmable monitors collected fine particulate matter (PM 2.5 ) samples specific to workweek hours (Monday-Friday, 7 am-7 pm), summer and winter 2013. Integrated filters were analyzed for black carbon (BC), elemental carbon (EC), organic carbon (OC), elemental constituents, and diesel-related organic compounds [i.e., polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes]. To our knowledge, no studies have collected this suite of pollutants with such high sampling density, with the ability to capture spatial patterns during specific hours of interest. We hypothesized that we would find substantial spatial variation for each pollutant and significant associations with key sources (e.g. diesel and gasoline vehicles), with higher concentrations near the center of this small downtown core. Using a forward stepwise approach, we developed seasonal land use regression (LUR) models for PM 2.5 , BC, total EC, OC, PAHs, hopanes, steranes, aluminum (Al), calcium (Ca), and iron (Fe). Within this small domain, greater concentration differences were observed in most pollutants across sites, on average, than between seasons. Higher PM 2.5 and BC concentrations were found in the downtown core compared to the boundaries. PAHs, hopanes, and steranes displayed different spatial patterning across the study area by constituent. Most LUR models suggested a strong influence of bus-related emissions on pollution gradients. Buses were more dominant predictors compared to truck and vehicular traffic for several pollutants. Overall, we found substantial variation in diesel-related concentrations in a very small downtown area, which varied across elemental and organic components. Copyright © 2016. Published by Elsevier B.V.

Inferring controls on the epidemiology of beech bark disease from spatial patterning of disease organisms

Treesearch

Jeffrey R. Garnas; David R. Houston; Mark J. Twery; Matthew P. Ayres; Celia Evans

2013-01-01

Spatial pattern in the distribution and abundance of organisms is an emergent property of collective rates of reproduction, survival and movement of individuals in a heterogeneous environment. The form, intensity and scale of spatial patterning can be used to test hypotheses regarding the relative importance of candidate processes to population dynamics. Using 84 plots...

Life-History and Spatial Determinants of Somatic Growth Dynamics in Komodo Dragon Populations

PubMed Central

Laver, Rebecca J.; Purwandana, Deni; Ariefiandy, Achmad; Imansyah, Jeri; Forsyth, David; Ciofi, Claudio; Jessop, Tim S.

2012-01-01

Somatic growth patterns represent a major component of organismal fitness and may vary among sexes and populations due to genetic and environmental processes leading to profound differences in life-history and demography. This study considered the ontogenic, sex-specific and spatial dynamics of somatic growth patterns in ten populations of the world’s largest lizard the Komodo dragon (Varanus komodoensis). The growth of 400 individual Komodo dragons was measured in a capture-mark-recapture study at ten sites on four islands in eastern Indonesia, from 2002 to 2010. Generalized Additive Mixed Models (GAMMs) and information-theoretic methods were used to examine how growth rates varied with size, age and sex, and across and within islands in relation to site-specific prey availability, lizard population density and inbreeding coefficients. Growth trajectories differed significantly with size and between sexes, indicating different energy allocation tactics and overall costs associated with reproduction. This leads to disparities in maximum body sizes and longevity. Spatial variation in growth was strongly supported by a curvilinear density-dependent growth model with highest growth rates occurring at intermediate population densities. Sex-specific trade-offs in growth underpin key differences in Komodo dragon life-history including evidence for high costs of reproduction in females. Further, inverse density-dependent growth may have profound effects on individual and population level processes that influence the demography of this species. PMID:23028983

Identifying Genetic Hotspots by Mapping Molecular Diversity of Widespread Trees: When Commonness Matters.

PubMed

Souto, Cintia P; Mathiasen, Paula; Acosta, María Cristina; Quiroga, María Paula; Vidal-Russell, Romina; Echeverría, Cristian; Premoli, Andrea C

2015-01-01

Conservation planning requires setting priorities at the same spatial scale at which decision-making processes are undertaken considering all levels of biodiversity, but current methods for identifying biodiversity hotspots ignore its genetic component. We developed a fine-scale approach based on the definition of genetic hotspots, which have high genetic diversity and unique variants that represent their evolutionary potential and evolutionary novelties. Our hypothesis is that wide-ranging taxa with similar ecological tolerances, yet of phylogenetically independent lineages, have been and currently are shaped by ecological and evolutionary forces that result in geographically concordant genetic patterns. We mapped previously published genetic diversity and unique variants of biparentally inherited markers and chloroplast sequences for 9 species from 188 and 275 populations, respectively, of the 4 woody dominant families of the austral temperate forest, an area considered a biodiversity hotspot. Spatial distribution patterns of genetic polymorphisms differed among taxa according to their ecological tolerances. Eight genetic hotspots were detected and we recommend conservation actions for some in the southern Coastal Range in Chile. Existing spatially explicit genetic data from multiple populations and species can help to identify biodiversity hotspots and guide conservation actions to establish science-based protected areas that will preserve the evolutionary potential of key habitats and species. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data

PubMed Central

Liu, Yu; Sui, Zhengwei; Kang, Chaogui; Gao, Yong

2014-01-01

The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips. PMID:24465849

Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data.

PubMed

Liu, Yu; Sui, Zhengwei; Kang, Chaogui; Gao, Yong

2014-01-01

The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips.

Performance measurement of commercial electronic still picture cameras

NASA Astrophysics Data System (ADS)

Hsu, Wei-Feng; Tseng, Shinn-Yih; Chiang, Hwang-Cheng; Cheng, Jui-His; Liu, Yuan-Te

1998-06-01

Commercial electronic still picture cameras need a low-cost, systematic method for evaluating the performance. In this paper, we present a measurement method to evaluating the dynamic range and sensitivity by constructing the opto- electronic conversion function (OECF), the fixed pattern noise by the peak S/N ratio (PSNR) and the image shading function (ISF), and the spatial resolution by the modulation transfer function (MTF). The evaluation results of individual color components and the luminance signal from a PC camera using SONY interlaced CCD array as the image sensor are then presented.

Spatial super-resolution of colored images by micro mirrors

NASA Astrophysics Data System (ADS)

Dahan, Daniel; Yaacobi, Ami; Pinsky, Ephraim; Zalevsky, Zeev

2018-06-01

In this paper, we present two methods of dealing with the geometric resolution limit of color imaging sensors. It is possible to overcome the pixel size limit by adding a digital micro-mirror device component on the intermediate image plane of an optical system, and adapting its pattern in a computerized manner before sampling each frame. The full RGB image can be reconstructed from the Bayer camera by building a dedicated optical design, or by adjusting the demosaicing process to the special format of the enhanced image.

Estimating particle speciation concentrations using MISR retrieved aerosol properties in southern California

NASA Astrophysics Data System (ADS)

Meng, X.; Liu, Y.; Diner, D. J.; Garay, M. J.

2016-12-01

Ambient fine particle (PM2.5) has been positively associated with increased mortality and morbidity worldwide. Recent studies highlight the characteristics and differential toxicity of PM2.5 chemical components, which are important for identifying sources, developing targeted particulate matter (PM) control strategies, and protecting public health. Modelling with satellite retrieved data has been proved as the most cost-effective way to estimate ground PM2.5 levels; however, limited studies have predict PM2.5 chemical components with this method. In this study, the experimental MISR 4.4 km aerosol retrievals were used to predict ground-level particle sulfate, nitrite, organic carbon and element carbon concentrations in 16 counties of southern California. The PM2.5 chemical components concentrations were obtained from the National Chemical Speciation Network (CSN) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) network. A generalized additive model (GAM) was developed based on 16-years data (2000-2015) by combining the MISR aerosol retrievals, meteorological variables and geographical indicators together. Model performance was assessed by model fitted R2 and root-mean-square error (RMSE) and 10-fold cross validation. Spatial patterns of sulfate, nitrate, OC and EC concentrations were also examined with 2-D prediction surfaces. This is the first attempt to develop high-resolution spatial models to predict PM2.5 chemical component concentrations with MISR retrieved aerosol properties, which will provide valuable population exposure estimates for future studies on the characteristics and differential toxicity of PM2.5 speciation.

Functional subdivision of group-ICA results of fMRI data collected during cinema viewing.

PubMed

Pamilo, Siina; Malinen, Sanna; Hlushchuk, Yevhen; Seppä, Mika; Tikka, Pia; Hari, Riitta

2012-01-01

Independent component analysis (ICA) can unravel functional brain networks from functional magnetic resonance imaging (fMRI) data. The number of the estimated components affects both the spatial pattern of the identified networks and their time-course estimates. Here group-ICA was applied at four dimensionalities (10, 20, 40, and 58 components) to fMRI data collected from 15 subjects who viewed a 15-min silent film ("At land" by Maya Deren). We focused on the dorsal attention network, the default-mode network, and the sensorimotor network. The lowest dimensionalities demonstrated most prominent activity within the dorsal attention network, combined with the visual areas, and in the default-mode network; the sensorimotor network only appeared with ICA comprising at least 20 components. The results suggest that even very low-dimensional ICA can unravel the most prominent functionally-connected brain networks. However, increasing the number of components gives a more detailed picture and functionally feasible subdivision of the major networks. These results improve our understanding of the hierarchical subdivision of brain networks during viewing of a movie that provides continuous stimulation embedded in an attention-directing narrative.

Integrating satellite actual evapotranspiration patterns into distributed model parametrization and evaluation for a mesoscale catchment

NASA Astrophysics Data System (ADS)

Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.

2016-12-01

Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.

A Theoretical Approach to Analyze the Parametric Influence on Spatial Patterns of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) Populations.

PubMed

Garcia, A G; Godoy, W A C

2017-06-01

Studies of the influence of biological parameters on the spatial distribution of lepidopteran insects can provide useful information for managing agricultural pests, since the larvae of many species cause serious impacts on crops. Computational models to simulate the spatial dynamics of insect populations are increasingly used, because of their efficiency in representing insect movement. In this study, we used a cellular automata model to explore different patterns of population distribution of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), when the values of two biological parameters that are able to influence the spatial pattern (larval viability and adult longevity) are varied. We mapped the spatial patterns observed as the parameters varied. Additionally, by using population data for S. frugiperda obtained in different hosts under laboratory conditions, we were able to describe the expected spatial patterns occurring in corn, cotton, millet, and soybean crops based on the parameters varied. The results are discussed from the perspective of insect ecology and pest management. We concluded that computational approaches can be important tools to study the relationship between the biological parameters and spatial distributions of lepidopteran insect pests.

Spatial controls of occurrence and spread of wildfires in the Missouri Ozark Highlands.

PubMed

Yang, Jian; He, Hong S; Shifley, Stephen R

2008-07-01

Understanding spatial controls on wildfires is important when designing adaptive fire management plans and optimizing fuel treatment locations on a forest landscape. Previous research about this topic focused primarily on spatial controls for fire origin locations alone. Fire spread and behavior were largely overlooked. This paper contrasts the relative importance of biotic, abiotic, and anthropogenic constraints on the spatial pattern of fire occurrence with that on burn probability (i.e., the probability that fire will spread to a particular location). Spatial point pattern analysis and landscape succession fire model (LANDIS) were used to create maps to show the contrast. We quantified spatial controls on both fire occurrence and fire spread in the Midwest Ozark Highlands region, USA. This area exhibits a typical anthropogenic surface fire regime. We found that (1) human accessibility and land ownership were primary limiting factors in shaping clustered fire origin locations; (2) vegetation and topography had a negligible influence on fire occurrence in this anthropogenic regime; (3) burn probability was higher in grassland and open woodland than in closed-canopy forest, even though fire occurrence density was less in these vegetation types; and (4) biotic and abiotic factors were secondary descriptive ingredients for determining the spatial patterns of burn probability. This study demonstrates how fire occurrence and spread interact with landscape patterns to affect the spatial distribution of wildfire risk. The application of spatial point pattern data analysis would also be valuable to researchers working on landscape forest fire models to integrate historical ignition location patterns in fire simulation.

Changes in Spatial Patterns of Caragana stenophylla along a Climatic Drought Gradient on the Inner Mongolian Plateau

PubMed Central

Xie, Li-Na; Guo, Hong-Yu; Gabler, Christopher A.; Li, Qing-Fang; Ma, Cheng-Cang

2015-01-01

Few studies have investigated the influence of water availability on plant population spatial patterns. We studied changes in the spatial patterns of Caragana stenophylla along a climatic drought gradient within the Inner Mongolian Plateau, China. We examined spatial patterns, seed density, “nurse effects” of shrubs on seedlings, transpiration rates and water use efficiency (WUE) of C. stenophylla across semi-arid, arid, and intensively arid zones. Our results showed that patches of C. stenophylla populations shifted from a random to a clumped spatial pattern towards drier environments. Seed density and seedling survival rate of C. stenophylla decreased from the semi-arid zone to the intensively arid zone. Across the three zones, there were more C. stenophylla seeds and seedlings underneath shrub canopies than outside shrub canopies; and in the intensively arid zone, there were almost no seeds or seedlings outside shrub canopies. Transpiration rates of outer-canopy leaves and WUE of both outer-canopy and inner-canopy leaves increased from the semi-arid zone to the intensively arid zone. In the intensively arid zone, transpiration rates and WUE of inner-canopy leaves were significantly lower and higher, respectively, than those of outer-canopy leaves. We conclude that, as drought stress increased, seed density decreased, seed proportions inside shrubs increased, and “nurse effects” of shrubs on seedlings became more important. These factors, combined with water-saving characteristics associated with clumped spatial patterns, are likely driving the changes in C. stenophylla spatial patterns. PMID:25785848

Spatio-temporal diffusion pattern and hotspot detection of dengue in Chachoengsao province, Thailand.

PubMed

Jeefoo, Phaisarn; Tripathi, Nitin Kumar; Souris, Marc

2011-01-01

In recent years, dengue has become a major international public health concern. In Thailand it is also an important concern as several dengue outbreaks were reported in last decade. This paper presents a GIS approach to analyze the spatial and temporal dynamics of dengue epidemics. The major objective of this study was to examine spatial diffusion patterns and hotspot identification for reported dengue cases. Geospatial diffusion pattern of the 2007 dengue outbreak was investigated. Map of daily cases was generated for the 153 days of the outbreak. Epidemiological data from Chachoengsao province, Thailand (reported dengue cases for the years 1999-2007) was used for this study. To analyze the dynamic space-time pattern of dengue outbreaks, all cases were positioned in space at a village level. After a general statistical analysis (by gender and age group), data was subsequently analyzed for temporal patterns and correlation with climatic data (especially rainfall), spatial patterns and cluster analysis, and spatio-temporal patterns of hotspots during epidemics. The results revealed spatial diffusion patterns during the years 1999-2007 representing spatially clustered patterns with significant differences by village. Villages on the urban fringe reported higher incidences. The space and time of the cases showed outbreak movement and spread patterns that could be related to entomologic and epidemiologic factors. The hotspots showed the spatial trend of dengue diffusion. This study presents useful information related to the dengue outbreak patterns in space and time and may help public health departments to plan strategies to control the spread of disease. The methodology is general for space-time analysis and can be applied for other infectious diseases as well.

Quantitative study on spatio-temporal change of urban landscape pattern based on RS/GIS: a case of Xi'an metropolitan area in China

NASA Astrophysics Data System (ADS)

Chen, Meiwu; Zong, Yueguang; Ma, Qiang; Li, Jian

2007-06-01

The study on landscape pattern is an important field of urban land use and ecological change. Since 1990s, the widely accepted Patch-Corridor-Matrix model is generally used in qualitative description of landscape pattern. In recent years, quantitative evaluation on urban landscape dynamics is becoming hot in research. By making a critical review on existing research methods of landscape pattern, a new approach based on RS/GIS is put forward in this paper, comprising three steps, "General pattern characteristics - Gradient differentiation feature- Directional signature of the landscape", and we call it GGD. This method is applied to the case study of Xi'an metropolitan area in China. The result shows that the method is effective on quantitative study of urban landscape. The preparation of the method GGD is setting up research platform based on RS and GIS. By using the software of Geographical Information System (Arcgis9.0 & Erdas), the authors got the interpretation of remote sensing images of different years, and carried on the division of the landscape type of the research region. By calculating various index of landscape level with software Fragstats3.3 as an assistant tool and adopting three steps of GGD combined with landscape index, this paper can assesses the landscape spatial pattern of urban area: 1) General pattern characteristics analysis is to get transition probability of various landscape through Markov chain and to predict the landscape transformation by introducing CA model. The analysis emphasizes on total landscape structure and its change over time; 2) Gradient characteristic analysis, which makes gradient zone by taking city as a center outwardly with certain distance and contrastively analyzes the landscape index of each subarea, stresses the spatial character of landscape pattern, verifies urban morphology theories and provides the quantitative warranty for establishment of urban modality. Therefore, the analysis is useful for supervising urban expanding speed; 3)Direction characteristic analysis, which is setting up radiate strip on west-east, south-north, southwest-northeast and northwest-southeast and form certain width on each direction, can precisely and quantitatively indicate different characteristic of urban landscape at each development direction, and by combined with gradient analysis it is highly advantageous to the examination and planning of urban expanding direction. In the case study on Xi'an metropolitan area, remote sensing images of 1988 and 2005 Landsat-TM were handled, and the division of the landscape type of the region was also carried on. According to the above approach, the result was got and some valuable information was showed as follows: 1) The diversity of overall landscape of Xi'an metropolitan area tends to increase and the degree of fragmentation tends to deepen. With the increase of urbanization level, the visual component of landscape is more and more diversified, the shapes of landscape is more and more complicated and ecologically more and more fragmented. In the region where urbanization level is low, natural landscape is the main component of the landscape, the diversity of the landscape is low. And because landscape is seriously disturbed by human activities with urbanization, fragmentation of the landscape emerges periodically. 2) In the process of transect gradient analysis, the landscape pattern index can explore the urbanization gradient, and its trend to reduce gradually towards the suburban. The landscape of area with a high urbanization level is mainly man-created, and its patches show large number, small area, simple shape and higher landscape heterogeneity. The transect gradient analysis on different time series indicates the relationship between urbanization level and landscape pattern. The landscape of urban area suffers intensely from human being, and its pattern component and spatial collocation depends on the interference intensity to a large degree. In the area with a high urbanization level, its pattern component is more man-created and less natural landscape. The landscape collocation characteristic of its patches takes on a large number, little average area, simple shape and low polymerization degree. 3) Analysis of direction and gradient of Xi'an metropolitan area can quantitatively reflect influence of urbanization and characteristics of urban landscape in the main development axes of north-south and east. Result shows that the degree of internal integration between Xi'an city and Xianyang city is gradually enhanced with the quickly urbanization course in China.

What We Observe Is Biased by What Other People Tell Us: Beliefs about the Reliability of Gaze Behavior Modulate Attentional Orienting to Gaze Cues

PubMed Central

Wiese, Eva; Wykowska, Agnieszka; Müller, Hermann J.

2014-01-01

For effective social interactions with other people, information about the physical environment must be integrated with information about the interaction partner. In order to achieve this, processing of social information is guided by two components: a bottom-up mechanism reflexively triggered by stimulus-related information in the social scene and a top-down mechanism activated by task-related context information. In the present study, we investigated whether these components interact during attentional orienting to gaze direction. In particular, we examined whether the spatial specificity of gaze cueing is modulated by expectations about the reliability of gaze behavior. Expectations were either induced by instruction or could be derived from experience with displayed gaze behavior. Spatially specific cueing effects were observed with highly predictive gaze cues, but also when participants merely believed that actually non-predictive cues were highly predictive. Conversely, cueing effects for the whole gazed-at hemifield were observed with non-predictive gaze cues, and spatially specific cueing effects were attenuated when actually predictive gaze cues were believed to be non-predictive. This pattern indicates that (i) information about cue predictivity gained from sampling gaze behavior across social episodes can be incorporated in the attentional orienting to social cues, and that (ii) beliefs about gaze behavior modulate attentional orienting to gaze direction even when they contradict information available from social episodes. PMID:24722348

Heart-Brain Interactions in the MR Environment: Characterization of the Ballistocardiogram in EEG Signals Collected During Simultaneous fMRI.

PubMed

Marino, Marco; Liu, Quanying; Del Castello, Mariangela; Corsi, Cristiana; Wenderoth, Nicole; Mantini, Dante

2018-05-01

The ballistocardiographic (BCG) artifact is linked to cardiac activity and occurs in electroencephalographic (EEG) recordings acquired inside the magnetic resonance (MR) environment. Its variability in terms of amplitude, waveform shape and spatial distribution over subject's scalp makes its attenuation a challenging task. In this study, we aimed to provide a detailed characterization of the BCG properties, including its temporal dependency on cardiac events and its spatio-temporal dynamics. To this end, we used high-density EEG data acquired during simultaneous functional MR imaging in six healthy volunteers. First, we investigated the relationship between cardiac activity and BCG occurrences in the EEG recordings. We observed large variability in the delay between ECG and subsequent BCG events (ECG-BCG delay) across subjects and non-negligible epoch-by-epoch variations at the single subject level. The inspection of spatial-temporal variations revealed a prominent non-stationarity of the BCG signal. We identified five main BCG waves, which were common across subjects. Principal component analysis revealed two spatially distinct patterns to explain most of the variance (85% in total). These components are possibly related to head rotation and pulse-driven scalp expansion, respectively. Our results may inspire the development of novel, more effective methods for the removal of the BCG, capable of isolating and attenuating artifact occurrences while preserving true neuronal activity.

Macroecological factors shape local-scale spatial patterns in agriculturalist settlements.

PubMed

Tao, Tingting; Abades, Sebastián; Teng, Shuqing; Huang, Zheng Y X; Reino, Luís; Chen, Bin J W; Zhang, Yong; Xu, Chi; Svenning, Jens-Christian

2017-11-15

Macro-scale patterns of human systems ranging from population distribution to linguistic diversity have attracted recent attention, giving rise to the suggestion that macroecological rules shape the assembly of human societies. However, in which aspects the geography of our own species is shaped by macroecological factors remains poorly understood. Here, we provide a first demonstration that macroecological factors shape strong local-scale spatial patterns in human settlement systems, through an analysis of spatial patterns in agriculturalist settlements in eastern mainland China based on high-resolution Google Earth images. We used spatial point pattern analysis to show that settlement spatial patterns are characterized by over-dispersion at fine spatial scales (0.05-1.4 km), consistent with territory segregation, and clumping at coarser spatial scales beyond the over-dispersion signals, indicating territorial clustering. Statistical modelling shows that, at macroscales, potential evapotranspiration and topographic heterogeneity have negative effects on territory size, but positive effects on territorial clustering. These relationships are in line with predictions from territory theory for hunter-gatherers as well as for many animal species. Our results help to disentangle the complex interactions between intrinsic spatial processes in agriculturalist societies and external forcing by macroecological factors. While one may speculate that humans can escape ecological constraints because of unique abilities for environmental modification and globalized resource transportation, our work highlights that universal macroecological principles still shape the geography of current human agricultural societies. © 2017 The Author(s).

Exploring the Linkage between Urban Flood Risk and Spatial Patterns in Small Urbanized Catchments of Beijing, China

PubMed Central

Yao, Lei; Chen, Liding; Wei, Wei

2017-01-01

In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area (TIA), Directly Connected Impervious Area (DCIA), and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth (Qt and Qp) were simulated by using Strom Water Management Model (SWMM). The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1) imperviousness acts as an effective indicator in affecting both Qt and Qp; (2) reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3) different spatial concentrations of impervious surfaces have inherent influences on Qp. These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management. PMID:28264521

Exploring the Linkage between Urban Flood Risk and Spatial Patterns in Small Urbanized Catchments of Beijing, China.

PubMed

Yao, Lei; Chen, Liding; Wei, Wei

2017-02-28

In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area ( TIA ), Directly Connected Impervious Area ( DCIA ), and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth ( Q t and Q p ) were simulated by using Strom Water Management Model (SWMM). The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1) imperviousness acts as an effective indicator in affecting both Q t and Q p ; (2) reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3) different spatial concentrations of impervious surfaces have inherent influences on Q p . These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management.

3D Pathology Volumetric Technique: A Method for Calculating Breast Tumour Volume from Whole-Mount Serial Section Images

PubMed Central

Clarke, G. M.; Murray, M.; Holloway, C. M. B.; Liu, K.; Zubovits, J. T.; Yaffe, M. J.

2012-01-01

Tumour size, most commonly measured by maximum linear extent, remains a strong predictor of survival in breast cancer. Tumour volume, proportional to the number of tumour cells, may be a more accurate surrogate for size. We describe a novel “3D pathology volumetric technique” for lumpectomies and compare it with 2D measurements. Volume renderings and total tumour volume are computed from digitized whole-mount serial sections using custom software tools. Results are presented for two lumpectomy specimens selected for tumour features which may challenge accurate measurement of tumour burden with conventional, sampling-based pathology: (1) an infiltrative pattern admixed with normal breast elements; (2) a localized invasive mass separated from the in situ component by benign tissue. Spatial relationships between key features (tumour foci, close or involved margins) are clearly visualized in volume renderings. Invasive tumour burden can be underestimated using conventional pathology, compared to the volumetric technique (infiltrative pattern: 30% underestimation; localized mass: 3% underestimation for invasive tumour, 44% for in situ component). Tumour volume approximated from 2D measurements (i.e., maximum linear extent), assuming elliptical geometry, was seen to overestimate volume compared to the 3D volumetric calculation (by a factor of 7x for the infiltrative pattern; 1.5x for the localized invasive mass). PMID:23320179

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Developing an ecosystem perspective from experimental monitoring programs: I. Demographic responses of a rare geothermal grass to soil temperature.

PubMed

Pavlik, B M; Enberg, A

2001-08-01

The geysers panic grass [Dichanthelium lanuginosum Spellenberg var. thermale (Bol.) Spellenberg or DILA] is exclusively associated with surface geothermal manifestations in Sonoma County, California, USA (38 degrees 46'N, 122 degrees 38'W). Steam extraction by power plants could alter the subsurface distribution of heat and water to the site, potentially impacting subpopulations of this rare plant. The purpose of this study was to use demographic monitoring to determine: (1) temporal and spatial patterns of soil temperature in relation to the distribution of established DILA individuals at Little Geysers, (2) in situ response of experimental populations of DILA to spatial variations in soil temperature, and (3) habitat requirements of DILA as an indicator of its tolerance to variations in surficial geothermal features. Thermocouple transects and a datalogger provided data for characterizing the spatial and temporal patterns of soil temperature in four microhabitats (fumarole, DILA stand, Andropogon stand, and cleared). Experimental populations were established by precisely sowing and monitoring DILA seeds in these microhabitats. The results indicated that spatial and temporal variations in soil temperature had significant effects on the processes of germination, growth, survivorship, and reproduction, thus producing a readily observed metapopulation patch dynamic in relation to geothermal activity. Seasonal depressions of soil temperature near the fumaroles by cold air and prolonged rainfall events also promoted the emergence and survival of DILA seedlings in a microhabitat that was previously too hot to occupy. Over longer periods of time, DILA metapopulation dynamism reflected climatic and geothermal variation. Drought years inhibited germination for lack of water, but more importantly for the lack of requisite soil temperature depressions in the fumarole microhabitat. Wet years promoted subpopulation expansion into transition areas that were once too hot and dry. There have also been shifts in the underground distribution of steam into areas distant from known geothermal features. The demographic responses of DILA to spatial and temporal variations in soil temperature indicate that heat is an absolutely essential component of the steam resource. In its absence, germination, seeding survivorship, growth, and maturation are significantly inhibited even if soil conditions are favorable and potential competitors are controlled. Ultimately, persistence of the species depends on maintaining the ecosystem dynamic of colonization and extirpation in response to variations in surficial geothermal features over long spatial and temporal scales. This should shift management perspective from its narrow focus on individual plants to a wider focus on monitoring the essential habitat component of steam.

Optimization of landscape pattern [Chapter 8

Treesearch

John Hof; Curtis Flather

2007-01-01

A fundamental assumption in landscape ecology is that spatial patterns have significant influences on the flows of materials, energy, and information while processes create, modify, and maintain spatial patterns. Thus, it is of paramount importance in both theory and practice to address the questions of landscape pattern optimization ... For example, can landscape...

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.

Intelligent estimation of spatially distributed soil physical properties

USGS Publications Warehouse

Iwashita, F.; Friedel, M.J.; Ribeiro, G.F.; Fraser, Stephen J.

2012-01-01

Spatial analysis of soil samples is often times not possible when measurements are limited in number or clustered. To obviate potential problems, we propose a new approach based on the self-organizing map (SOM) technique. This approach exploits underlying nonlinear relation of the steady-state geomorphic concave-convex nature of hillslopes (from hilltop to bottom of the valley) to spatially limited soil textural data. The topographic features are extracted from Shuttle Radar Topographic Mission elevation data; whereas soil textural (clay, silt, and sand) and hydraulic data were collected in 29 spatially random locations (50 to 75. cm depth). In contrast to traditional principal component analysis, the SOM identifies relations among relief features, such as, slope, horizontal curvature and vertical curvature. Stochastic cross-validation indicates that the SOM is unbiased and provides a way to measure the magnitude of prediction uncertainty for all variables. The SOM cross-component plots of the soil texture reveals higher clay proportions at concave areas with convergent hydrological flux and lower proportions for convex areas with divergent flux. The sand ratio has an opposite pattern with higher values near the ridge and lower values near the valley. Silt has a trend similar to sand, although less pronounced. The relation between soil texture and concave-convex hillslope features reveals that subsurface weathering and transport is an important process that changed from loss-to-gain at the rectilinear hillslope point. These results illustrate that the SOM can be used to capture and predict nonlinear hillslope relations among relief, soil texture, and hydraulic conductivity data. ?? 2011 Elsevier B.V.

Environmental drivers and spatial dependency in wildfire ignition patterns of northwestern Patagonia.

PubMed

Mundo, Ignacio A; Wiegand, Thorsten; Kanagaraj, Rajapandian; Kitzberger, Thomas

2013-07-15

Fire management requires an understanding of the spatial characteristics of fire ignition patterns and how anthropogenic and natural factors influence ignition patterns across space. In this study we take advantage of a recent fire ignition database (855 points) to conduct a comprehensive analysis of the spatial pattern of fire ignitions in the western area of Neuquén province (57,649 km(2)), Argentina, for the 1992-2008 period. The objectives of our study were to better understand the spatial pattern and the environmental drivers of the fire ignitions, with the ultimate aim of supporting fire management. We conducted our analyses on three different levels: statistical "habitat" modelling of fire ignition (natural, anthropogenic, and all causes) based on an information theoretic approach to test several competing hypotheses on environmental drivers (i.e. topographic, climatic, anthropogenic, land cover, and their combinations); spatial point pattern analysis to quantify additional spatial autocorrelation in the ignition patterns; and quantification of potential spatial associations between fires of different causes relative to towns using a novel implementation of the independence null model. Anthropogenic fire ignitions were best predicted by the most complex habitat model including all groups of variables, whereas natural ignitions were best predicted by topographic, climatic and land-cover variables. The spatial pattern of all ignitions showed considerable clustering at intermediate distances (<40 km) not captured by the probability of fire ignitions predicted by the habitat model. There was a strong (linear) and highly significant increase in the density of fire ignitions with decreasing distance to towns (<5 km), but fire ignitions of natural and anthropogenic causes were statistically independent. A two-dimensional habitat model that quantifies differences between ignition probabilities of natural and anthropogenic causes allows fire managers to delineate target areas for consideration of major preventive treatments, strategic placement of fuel treatments, and forecasting of fire ignition. The techniques presented here can be widely applied to situations where a spatial point pattern is jointly influenced by extrinsic environmental factors and intrinsic point interactions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Spatial pattern and ecological process in the coffee agroforestry system.

PubMed

Perfecto, Ivette; Vandermeer, John

2008-04-01

The coffee agroforestry system provides an ideal platform for the study of spatial ecology. The uniform pattern of the coffee plants and shade trees allows for the study of pattern generation through intrinsic biological forces rather than extrinsic habitat patchiness. Detailed studies, focusing on a key mutualism between an ant (Azteca instabilis) and a scale insect (Coccus viridis), conducted in a 45-ha plot in a coffee agroforestry system have provided insights into (1) the quantitative evaluation of spatial pattern of the scale insect Coccus viridis on coffee bushes, (2) the mechanisms for the generation of patterns through the combination of local satellite ant nest formation and regional control from natural enemies, and (3) the consequences of the spatial pattern for the stability of predator-prey (host-parasitoid) systems, for a key coccinelid beetle preying on the scale insects and a phorid fly parasitoid parasitizing the ant.

Contributions of GRACE to Understanding of Spatial Distribution of Spring Flooding in Snow-dominated Afghan Watersheds

NASA Astrophysics Data System (ADS)

Roningen, J. M.; Daly, S. F.; Vuyovich, C.

2012-12-01

In Afghanistan, where both historical and current in situ hydrologic records are extremely limited, the development and stability operations communities require guidance as to how to best utilize capabilities in remote sensing of the water cycle to understand and predict seasonal flooding. In this study, three versions of Level 3 GRACE datasets (CSR, CSR 4.1 and GRGS) are compared to TRMM 3B42 products, SSM/I-derived snow water equivalent products (SWE), and MODIS-derived flooding extents to assess their potential for contributing to an understanding of the spatial and temporal patterns of spring flooding in Afghanistan from the period 2002-2012. GRACE, which allows for assessment of correlations between small-scale temporal changes in the gravitational field of the earth with changes in the total water storage in the hydrosphere, opens the possibility for incorporation of subsurface components of the hydrologic cycle into remote monitoring and modeling of water resources. GRACE data exhibit clear seasonal fluctuations in many areas of Afghanistan, but an assessment is required of the extent to which this data can be disaggregated spatially and related to geographic patterns of precipitation, snowmelt and flooding. In this study, TRMM 3B42 and SSM/I-derived SWE datasets were used as proxies for measured precipitation. These datasets were convolved with a Gaussian filter with a 300 km half-radius at each reported GRACE data point in order to compensate for spatial correlation ('leakage' effects) in the GRACE data. In mountainous and snowmelt-dominated basins such as the majority of those in this study, GRACE analyses that make use of land surface model (LSM) derived estimates may not provide adequate characterization of snow water equivalent and soil moisture in this region. Therefore, soil and subsurface moisture were evaluated as a single storage component using the GRACE data, and flooding occurrence was evaluated as a qualitative surface expression of this storage component. Initial results show that cumulative Gaussian-smoothed TRMM data correlate positively with GRACE CSR during the periods between yearly GRACE minima and maxima at points throughout most watersheds. The timing of peaks in GRACE data in central Afghanistan following the onset of the seasonal SWE decline also corresponds to seasonal rises in the nearby Kajakai Reservoir as measured by Jason-2 satellite altimetry and validated by manual records. Differences between datasets also appear to confirm the irregularities introduced in this region by the CSR 4.1 product that used a land surface model in the signal restoration process.

Sex-specific effects of prenatal chronic mild stress on adult spatial learning capacity and regional glutamate receptor expression profiles.

PubMed

Wang, Yan; Ma, Yuchao; Hu, Jingmin; Zhang, Xinxin; Cheng, Wenwen; Jiang, Han; Li, Min; Ren, Jintao; Zhang, Xiaosong; Liu, Mengxi; Sun, Anji; Wang, Qi; Li, Xiaobai

2016-07-01

Both animal experiments and clinical studies have demonstrated that prenatal stress can cause cognitive disorders in offspring. To explore the scope of these deficits and identify potential underlying mechanisms, we examined the spatial learning and memory performance and glutamate receptor (GluR) expression patterns of adult rats exposed to prenatal chronic mild stress (PCMS). Principal component analysis (PCA) was employed to reveal the interrelationships among spatial learning indices and GluR expression changes. Female PCMS-exposed offspring exhibited markedly impaired spatial learning and memory in the Morris water maze (MWM) task compared to control females, while PCMS-exposed males showed better initial spatial learning in the MWM compared to control males. PCMS also altered basal and post-MWM glutamate receptor expression patterns, but these effects differed markedly between sexes. Male PCMS-exposed offspring exhibited elevated basal expression of NR1, mGluR5, and mGluR2/3 in the prefrontal cortex (PFC), whereas females showed no basal expression changes. Following MWM training, PCMS-exposed males expressed higher NR1 in the PFC and mammillary body (MB), higher mGluR2/3 in PFC, and lower NR2B in the hippocampus (HIP), PFC, and MB compared to unstressed MWM-trained males. Female PCMS-exposed offspring showed strongly reduced NR1 in MB and NR2B in the HIP, PFC, and MB, and increased mGluR2/3 in PFC compared to unstressed MWM-trained females. This is the first report suggesting that NMDA subunits in the MB are involved in spatial learning. Additionally, PCA further suggests that the NR1-NR2B form is the most important for spatial memory formation. These results reveal long-term sex-specific effects of PCMS on spatial learning and memory performance in adulthood and implicate GluR expression changes within HIP, PFC, and MB as possible molecular mechanisms underlying cognitive dysfunction in offspring exposed to prenatal stress. Copyright © 2016 Elsevier Inc. All rights reserved.

A downscaled 1 km dataset of daily Greenland ice sheet surface mass balance components (1958-2014)

NASA Astrophysics Data System (ADS)

Noel, B.; Van De Berg, W. J.; Fettweis, X.; Machguth, H.; Howat, I. M.; van den Broeke, M. R.

2015-12-01

The current spatial resolution in regional climate models (RCMs), typically around 5 to 20 km, remains too coarse to accurately reproduce the spatial variability in surface mass balance (SMB) components over the narrow ablation zones, marginal outlet glaciers and neighbouring ice caps of the Greenland ice sheet (GrIS). In these topographically rough terrains, the SMB components are highly dependent on local variations in topography. However, the relatively low-resolution elevation and ice mask prescribed in RCMs contribute to significantly underestimate melt and runoff in these regions due to unresolved valley glaciers and fjords. Therefore, near-km resolution topography is essential to better capture SMB variability in these spatially restricted regions. We present a 1 km resolution dataset of daily GrIS SMB covering the period 1958-2014, which is statistically downscaled from data of the polar regional climate model RACMO2.3 at 11 km, using an elevation dependence. The dataset includes all individual SMB components projected on the elevation and ice mask from the GIMP DEM, down-sampled to 1 km. Daily runoff and sublimation are interpolated to the 1 km topography using a local regression to elevation valid for each day specifically; daily precipitation is bi-linearly downscaled without elevation corrections. The daily SMB dataset is then reconstructed by summing downscaled precipitation, sublimation and runoff. High-resolution elevation and ice mask allow for properly resolving the narrow ablation zones and valley glaciers at the GrIS margins, leading to significant increase in runoff estimate. In these regions, and especially over narrow glaciers tongues, the downscaled products improve on the original RACMO2.3 outputs by better representing local SMB patterns through a gradual ablation increase towards the GrIS margins. We discuss the impact of downscaling on the SMB components in a case study for a spatially restricted region, where large elevation discrepancies are observed between both resolutions. Owing to generally enhanced runoff in the GrIS ablation zone, the evaluation of daily downscaled SMB against ablation measurements, collected at in-situ measuring sites derived from a newly compiled ablation dataset, shows a better agreement with observations relative to native RACMO2.3 SMB at 11 km.

Report on Component 2 - Designing New Methods for Visualizing Text in Spatial Contexts

DTIC Science & Technology

2012-10-31

W9132V-11-P-0010 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Alexander Savelyev , Scott Pezanowski, Anthony C. Robinson, and Alan M...e Component 2 – Designing New Methods for Visualizing Text in Spatial Contexts Alexander Savelyev , Scott Pezanowski, Anthony Robinson and Alan...Center, Penn State University Report on Component 2: Component 2 – Designing New Methods for Visualizing Text in Spatial Contexts Alexander

Elucidating the Functional Roles of Spatial Organization in Cross-Membrane Signal Transduction by a Hybrid Simulation Method.

PubMed

Chen, Jiawen; Xie, Zhong-Ru; Wu, Yinghao

2016-07-01

The ligand-binding of membrane receptors on cell surfaces initiates the dynamic process of cross-membrane signal transduction. It is an indispensable part of the signaling network for cells to communicate with external environments. Recent experiments revealed that molecular components in signal transduction are not randomly mixed, but spatially organized into distinctive patterns. These patterns, such as receptor clustering and ligand oligomerization, lead to very different gene expression profiles. However, little is understood about the molecular mechanisms and functional impacts of this spatial-temporal regulation in cross-membrane signal transduction. In order to tackle this problem, we developed a hybrid computational method that decomposes a model of signaling network into two simulation modules. The physical process of binding between receptors and ligands on cell surfaces are simulated by a diffusion-reaction algorithm, while the downstream biochemical reactions are modeled by stochastic simulation of Gillespie algorithm. These two processes are coupled together by a synchronization framework. Using this method, we tested the dynamics of a simple signaling network in which the ligand binding of cell surface receptors triggers the phosphorylation of protein kinases, and in turn regulates the expression of target genes. We found that spatial aggregation of membrane receptors at cellular interfaces is able to either amplify or inhibit downstream signaling outputs, depending on the details of clustering mechanism. Moreover, by providing higher binding avidity, the co-localization of ligands into multi-valence complex modulates signaling in very different ways that are closely related to the binding affinity between ligand and receptor. We also found that the temporal oscillation of the signaling pathway that is derived from genetic feedback loops can be modified by the spatial clustering of membrane receptors. In summary, our method demonstrates the functional importance of spatial organization in cross-membrane signal transduction. The method can be applied to any specific signaling pathway in cells.

Assessing Genetic Structure in Common but Ecologically Distinct Carnivores: The Stone Marten and Red Fox.

PubMed

Basto, Mafalda P; Santos-Reis, Margarida; Simões, Luciana; Grilo, Clara; Cardoso, Luís; Cortes, Helder; Bruford, Michael W; Fernandes, Carlos

2016-01-01

The identification of populations and spatial genetic patterns is important for ecological and conservation research, and spatially explicit individual-based methods have been recognised as powerful tools in this context. Mammalian carnivores are intrinsically vulnerable to habitat fragmentation but not much is known about the genetic consequences of fragmentation in common species. Stone martens (Martes foina) and red foxes (Vulpes vulpes) share a widespread Palearctic distribution and are considered habitat generalists, but in the Iberian Peninsula stone martens tend to occur in higher quality habitats. We compared their genetic structure in Portugal to see if they are consistent with their differences in ecological plasticity, and also to illustrate an approach to explicitly delineate the spatial boundaries of consistently identified genetic units. We analysed microsatellite data using spatial Bayesian clustering methods (implemented in the software BAPS, GENELAND and TESS), a progressive partitioning approach and a multivariate technique (Spatial Principal Components Analysis-sPCA). Three consensus Bayesian clusters were identified for the stone marten. No consensus was achieved for the red fox, but one cluster was the most probable clustering solution. Progressive partitioning and sPCA suggested additional clusters in the stone marten but they were not consistent among methods and were geographically incoherent. The contrasting results between the two species are consistent with the literature reporting stricter ecological requirements of the stone marten in the Iberian Peninsula. The observed genetic structure in the stone marten may have been influenced by landscape features, particularly rivers, and fragmentation. We suggest that an approach based on a consensus clustering solution of multiple different algorithms may provide an objective and effective means to delineate potential boundaries of inferred subpopulations. sPCA and progressive partitioning offer further verification of possible population structure and may be useful for revealing cryptic spatial genetic patterns worth further investigation.

Creating a spatially-explicit index: a method for assessing the global wildfire-water risk

NASA Astrophysics Data System (ADS)

Robinne, François-Nicolas; Parisien, Marc-André; Flannigan, Mike; Miller, Carol; Bladon, Kevin D.

2017-04-01

The wildfire-water risk (WWR) has been defined as the potential for wildfires to adversely affect water resources that are important for downstream ecosystems and human water needs for adequate water quantity and quality, therefore compromising the security of their water supply. While tools and methods are numerous for watershed-scale risk analysis, the development of a toolbox for the large-scale evaluation of the wildfire risk to water security has only started recently. In order to provide managers and policy-makers with an adequate tool, we implemented a method for the spatial analysis of the global WWR based on the Driving forces-Pressures-States-Impacts-Responses (DPSIR) framework. This framework relies on the cause-and-effect relationships existing between the five categories of the DPSIR chain. As this approach heavily relies on data, we gathered an extensive set of spatial indicators relevant to fire-induced hydrological hazards and water consumption patterns by human and natural communities. When appropriate, we applied a hydrological routing function to our indicators in order to simulate downstream accumulation of potentially harmful material. Each indicator was then assigned a DPSIR category. We collapsed the information in each category using a principal component analysis in order to extract the most relevant pixel-based information provided by each spatial indicator. Finally, we compiled our five categories using an additive indexation process to produce a spatially-explicit index of the WWR. A thorough sensitivity analysis has been performed in order to understand the relationship between the final risk values and the spatial pattern of each category used during the indexation. For comparison purposes, we aggregated index scores by global hydrological regions, or hydrobelts, to get a sense of regional DPSIR specificities. This rather simple method does not necessitate the use of complex physical models and provides a scalable and efficient tool for the analysis of global water security issues.

Assessing Genetic Structure in Common but Ecologically Distinct Carnivores: The Stone Marten and Red Fox

PubMed Central

Basto, Mafalda P.; Santos-Reis, Margarida; Simões, Luciana; Grilo, Clara; Cardoso, Luís; Cortes, Helder; Bruford, Michael W.; Fernandes, Carlos

2016-01-01

The identification of populations and spatial genetic patterns is important for ecological and conservation research, and spatially explicit individual-based methods have been recognised as powerful tools in this context. Mammalian carnivores are intrinsically vulnerable to habitat fragmentation but not much is known about the genetic consequences of fragmentation in common species. Stone martens (Martes foina) and red foxes (Vulpes vulpes) share a widespread Palearctic distribution and are considered habitat generalists, but in the Iberian Peninsula stone martens tend to occur in higher quality habitats. We compared their genetic structure in Portugal to see if they are consistent with their differences in ecological plasticity, and also to illustrate an approach to explicitly delineate the spatial boundaries of consistently identified genetic units. We analysed microsatellite data using spatial Bayesian clustering methods (implemented in the software BAPS, GENELAND and TESS), a progressive partitioning approach and a multivariate technique (Spatial Principal Components Analysis-sPCA). Three consensus Bayesian clusters were identified for the stone marten. No consensus was achieved for the red fox, but one cluster was the most probable clustering solution. Progressive partitioning and sPCA suggested additional clusters in the stone marten but they were not consistent among methods and were geographically incoherent. The contrasting results between the two species are consistent with the literature reporting stricter ecological requirements of the stone marten in the Iberian Peninsula. The observed genetic structure in the stone marten may have been influenced by landscape features, particularly rivers, and fragmentation. We suggest that an approach based on a consensus clustering solution of multiple different algorithms may provide an objective and effective means to delineate potential boundaries of inferred subpopulations. sPCA and progressive partitioning offer further verification of possible population structure and may be useful for revealing cryptic spatial genetic patterns worth further investigation. PMID:26727497

Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework

PubMed Central

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-01-01

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859

Flower Colours through the Lens: Quantitative Measurement with Visible and Ultraviolet Digital Photography

PubMed Central

Garcia, Jair E.; Greentree, Andrew D.; Shrestha, Mani; Dorin, Alan; Dyer, Adrian G.

2014-01-01

Background The study of the signal-receiver relationship between flowering plants and pollinators requires a capacity to accurately map both the spectral and spatial components of a signal in relation to the perceptual abilities of potential pollinators. Spectrophotometers can typically recover high resolution spectral data, but the spatial component is difficult to record simultaneously. A technique allowing for an accurate measurement of the spatial component in addition to the spectral factor of the signal is highly desirable. Methodology/Principal findings Consumer-level digital cameras potentially provide access to both colour and spatial information, but they are constrained by their non-linear response. We present a robust methodology for recovering linear values from two different camera models: one sensitive to ultraviolet (UV) radiation and another to visible wavelengths. We test responses by imaging eight different plant species varying in shape, size and in the amount of energy reflected across the UV and visible regions of the spectrum, and compare the recovery of spectral data to spectrophotometer measurements. There is often a good agreement of spectral data, although when the pattern on a flower surface is complex a spectrophotometer may underestimate the variability of the signal as would be viewed by an animal visual system. Conclusion Digital imaging presents a significant new opportunity to reliably map flower colours to understand the complexity of these signals as perceived by potential pollinators. Compared to spectrophotometer measurements, digital images can better represent the spatio-chromatic signal variability that would likely be perceived by the visual system of an animal, and should expand the possibilities for data collection in complex, natural conditions. However, and in spite of its advantages, the accuracy of the spectral information recovered from camera responses is subject to variations in the uncertainty levels, with larger uncertainties associated with low radiance levels. PMID:24827828

Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework.

PubMed

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-11-27

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex.

PubMed

Mhatre, Himanshu; Gorchetchnikov, Anatoli; Grossberg, Stephen

2012-02-01

Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. It has previously been shown how a self-organizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? This article describes a simple and general mathematical property of the trigonometry of spatial navigation which favors hexagonal patterns. The article also develops a neural model that can learn to exploit this trigonometric relationship. This GRIDSmap self-organizing map model converts path integration signals into hexagonal grid cell patterns of multiple scales. GRIDSmap creates only grid cell firing patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support an emerging unified computational framework based on a hierarchy of self-organizing maps for explaining how entorhinal-hippocampal interactions support spatial navigation. Copyright © 2010 Wiley Periodicals, Inc.

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review.

PubMed

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-12-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0-0.10 m, or 0-0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis (PCA) and cluster analysis (CA). Copyright © 2017 Elsevier Ltd. All rights reserved.

THz-wave parametric source and its imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo

2004-08-01

Widely tunable coherent terahertz (THz) wave generation has been demonstrated based on the parametric oscillation using MgO doped LiNbO3 crystal pumped by a Q-switched Nd:YAG laser. This method exhibits multiple advantages like wide tunability, coherency and compactness of its system. We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.