Utility of computer simulations in landscape genetics

Treesearch

Bryan K. Epperson; Brad H. McRae; Kim Scribner; Samuel A. Cushman; Michael S. Rosenberg; Marie-Josee Fortin; Patrick M. A. James; Melanie Murphy; Stephanie Manel; Pierre Legendre; Mark R. T. Dale

2010-01-01

Population genetics theory is primarily based on mathematical models in which spatial complexity and temporal variability are largely ignored. In contrast, the field of landscape genetics expressly focuses on how population genetic processes are affected by complex spatial and temporal environmental heterogeneity. It is spatially explicit and relates patterns to...

Quantifying Landscape Spatial Pattern: What Is the State of the Art?

Treesearch

Eric J. Gustafson

1998-01-01

Landscape ecology is based on the premise that there are strong links between ecological pattern and ecological function and process. Ecological systems are spatially heterogeneous, exhibiting consid-erable complexity and variability in time and space. This variability is typically represented by categorical maps or by a collection of samples taken at specific spatial...

Contrasting spatial patterns in active-fire and fire-suppressed Mediterranean climate old-growth mixed conifer forests

Treesearch

Danny L. Fry; Scott L. Stephens; Brandon M. Collins; Malcolm North; Ernesto Franco-Vizcaino; Samantha J. Gill

2014-01-01

In Mediterranean environments in western North America, historic fire regimes in frequent-fire conifer forests are highly variable both temporally and spatially. This complexity influenced forest structure and spatial patterns, but some of this diversity has been lost due to anthropogenic disruption of ecosystem processes, including fire. Information from reference...

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.

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.

Species-area relationships in coral communities: evaluating mechanisms for a commonly observed pattern

NASA Astrophysics Data System (ADS)

Huntington, B. E.; Lirman, D.

2012-12-01

Landscape-scale attributes of patch size, spatial isolation, and topographic complexity are known to influence diversity and abundance in terrestrial and marine systems, but remain collectively untested for reef-building corals. To investigate the relationship between the coral assemblage and seascape variation in reef habitats, we took advantage of the distinct boundaries, spatial configurations, and topographic complexities among artificial reef patches to overcome the difficulties of manipulating natural reefs. Reef size (m2) was found to be the foremost predictor of coral richness in accordance with species-area relationship predictions. Larger reefs were also found to support significantly higher colony densities, enabling us to reject the null hypothesis of random placement (a sampling artifact) in favor of target area predictions that suggest greater rates of immigration on larger reefs. Unlike the pattern previously documented for reef fishes, topographic complexity was not a significant predictor of any coral assemblage response variable, despite the range of complexity values sampled. Lastly, coral colony density was best explained by both increasing reef size and decreasing reef spatial isolation, a pattern found exclusively among brooding species with shorter larval dispersal distances. We conclude that seascape attributes of reef size and spatial configuration within the seascape can influence the species richness and abundance of the coral community at relatively small spatial scales (<1 km). Specifically, we demonstrate how patterns in the coral communities that have naturally established on these manipulated reefs agree with the target area and island biogeography mechanisms to drive species-area relationships in reef-building corals. Based on the patterns documented in artificial reefs, habitat degradation that results in smaller, more isolated natural reefs may compromise coral diversity.

Vegetation changes associated with a population irruption by Roosevelt elk

USGS Publications Warehouse

Starns, H D; Weckerly, Floyd W.; Ricca, Mark; Duarte, Adam

2015-01-01

Interactions between large herbivores and their food supply are central to the study of population dynamics. We assessed temporal and spatial patterns in meadow plant biomass over a 23-year period for meadow complexes that were spatially linked to three distinct populations of Roosevelt elk (Cervus elaphus roosevelti) in northwestern California. Our objectives were to determine whether the plant community exhibited a tolerant or resistant response when elk population growth became irruptive. Plant biomass for the three meadow complexes inhabited by the elk populations was measured using Normalized Difference Vegetation Index (NDVI), which was derived from Landsat 5 Thematic Mapper imagery. Elk populations exhibited different patterns of growth through the time series, whereby one population underwent a complete four-stage irruptive growth pattern while the other two did not. Temporal changes in NDVI for the meadow complex used by the irruptive population suggested a decline in forage biomass during the end of the dry season and a temporal decline in spatial variation of NDVI at the peak of plant biomass in May. Conversely, no such patterns were detected in the meadow complexes inhabited by the nonirruptive populations. Our findings suggest that the meadow complex used by the irruptive elk population may have undergone changes in plant community composition favoring plants that were resistant to elk grazing.

Twentieth-century fire patterns in the Selway-Bitterroot Wilderness Area, Idaho/Montana, and the Gila/Aldo Leopold Wilderness Complex, New Mexico

Treesearch

Matthew Rollins; Tom Swetnam; Penelope Morgan

2000-01-01

Twentieth century fire patterns were analyzed for two large, disparate wilderness areas in the Rocky Mountains. Spatial and temporal patterns of fires were represented as GIS-based digital fire atlases compiled from archival Forest Service data. We find that spatial and temporal fire patterns are related to landscape features and changes in land use. The rate and...

The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

NASA Astrophysics Data System (ADS)

Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon

2018-05-01

The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.

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

Generation of multifocal irradiance patterns by using complex Fresnel holograms.

PubMed

Mendoza-Yero, Omel; Carbonell-Leal, Miguel; Mínguez-Vega, Gladys; Lancis, Jesús

2018-03-01

We experimentally demonstrate Fresnel holograms able to produce multifocal irradiance patterns with micrometric spatial resolution. These holograms are assessed from the coherent sum of multiple Fresnel lenses. The utilized encoded technique guarantees full control over the reconstructed irradiance patterns due to an optimal codification of the amplitude and phase information of the resulting complex field. From a practical point of view, a phase-only spatial light modulator is used in a couple of experiments addressed to obtain two- and three-dimensional distributions of focal points to excite both linear and non-linear optical phenomena.

GeoPAT: A toolbox for pattern-based information retrieval from large geospatial databases

NASA Astrophysics Data System (ADS)

Jasiewicz, Jarosław; Netzel, Paweł; Stepinski, Tomasz

2015-07-01

Geospatial Pattern Analysis Toolbox (GeoPAT) is a collection of GRASS GIS modules for carrying out pattern-based geospatial analysis of images and other spatial datasets. The need for pattern-based analysis arises when images/rasters contain rich spatial information either because of their very high resolution or their very large spatial extent. Elementary units of pattern-based analysis are scenes - patches of surface consisting of a complex arrangement of individual pixels (patterns). GeoPAT modules implement popular GIS algorithms, such as query, overlay, and segmentation, to operate on the grid of scenes. To achieve these capabilities GeoPAT includes a library of scene signatures - compact numerical descriptors of patterns, and a library of distance functions - providing numerical means of assessing dissimilarity between scenes. Ancillary GeoPAT modules use these functions to construct a grid of scenes or to assign signatures to individual scenes having regular or irregular geometries. Thus GeoPAT combines knowledge retrieval from patterns with mapping tasks within a single integrated GIS environment. GeoPAT is designed to identify and analyze complex, highly generalized classes in spatial datasets. Examples include distinguishing between different styles of urban settlements using VHR images, delineating different landscape types in land cover maps, and mapping physiographic units from DEM. The concept of pattern-based spatial analysis is explained and the roles of all modules and functions are described. A case study example pertaining to delineation of landscape types in a subregion of NLCD is given. Performance evaluation is included to highlight GeoPAT's applicability to very large datasets. The GeoPAT toolbox is available for download from

EVALUATING EFFECTS OF LOW QUALITY HABITATS ON REGIONAL GROWTH IN PEOMYCUS LEUCOPUS: INSIGHTS FROM FIELD-PARAMETERIZED SPATIAL MATRIX MODELS.

EPA Science Inventory

Due to complex population dynamics and source-sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive fiel...

Different Perspectives: Spatial Ability Influences Where Individuals Look on a Timed Spatial Test

ERIC Educational Resources Information Center

Roach, Victoria A.; Fraser, Graham M.; Kryklywy, James H.; Mitchell, Derek G. V.; Wilson, Timothy D.

2017-01-01

Learning in anatomy can be both spatially and visually complex. Pedagogical investigations have begun exploration as to how spatial ability may mitigate learning. Emerging hypotheses suggests individuals with higher spatial reasoning may attend to images differently than those who are lacking. To elucidate attentional patterns associated with…

Pattern recognition neural-net by spatial mapping of biology visual field

NASA Astrophysics Data System (ADS)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

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.

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.

Pattern masking: the importance of remote spatial frequencies and their phase alignment.

PubMed

Huang, Pi-Chun; Maehara, Goro; May, Keith A; Hess, Robert F

2012-02-16

To assess the effects of spatial frequency and phase alignment of mask components in pattern masking, target threshold vs. mask contrast (TvC) functions for a sine-wave grating (S) target were measured for five types of mask: a sine-wave grating (S), a square-wave grating (Q), a missing fundamental square-wave grating (M), harmonic complexes consisting of phase-scrambled harmonics of a square wave (Qp), and harmonic complexes consisting of phase-scrambled harmonics of a missing fundamental square wave (Mp). Target and masks had the same fundamental frequency (0.46 cpd) and the target was added in phase with the fundamental frequency component of the mask. Under monocular viewing conditions, the strength of masking depends on phase relationships among mask spatial frequencies far removed from that of the target, at least 3 times the target frequency, only when there are common target and mask spatial frequencies. Under dichoptic viewing conditions, S and Q masks produced similar masking to each other and the phase-scrambled masks (Qp and Mp) produced less masking. The results suggest that pattern masking is spatial frequency broadband in nature and sensitive to the phase alignments of spatial components.

Modelling and formation of spatiotemporal patterns of fractional predation system in subdiffusion and superdiffusion scenarios

NASA Astrophysics Data System (ADS)

Owolabi, Kolade M.; Atangana, Abdon

2018-02-01

This paper primarily focused on the question of how population diffusion can affect the formation of the spatial patterns in the spatial fraction predator-prey system by Turing mechanisms. Our numerical findings assert that modeling by fractional reaction-diffusion equations should be considered as an appropriate tool for studying the fundamental mechanisms of complex spatiotemporal dynamics. We observe that pure Hopf instability gives rise to the formation of spiral patterns in 2D and pure Turing instability destroys the spiral pattern and results to the formation of chaotic or spatiotemporal spatial patterns. Existence and permanence of the species is also guaranteed with the 3D simulations at some instances of time for subdiffusive and superdiffusive scenarios.

Modeling the effects of fire severity and spatial complexity on Small Mammals in Yosemite National Park, California

USGS Publications Warehouse

Roberts, Susan L.; Van Wagtendonk, Jan W.; Miles, A. Keith; Kelt, Douglas A.; Lutz, James A.

2008-01-01

We evaluated the impact of fire severity and related spatial and vegetative parameters on small mammal populations in 2 yr- to 15 yr-old burns in Yosemite National Park, California, USA. We also developed habitat models that would predict small mammal responses to fires of differing severity. We hypothesized that fire severity would influence the abundances of small mammals through changes in vegetation composition, structure, and spatial habitat complexity. Deer mouse (Peromyscus maniculatus) abundance responded negatively to fire severity, and brush mouse (P. boylii) abundance increased with increasing oak tree (Quercus spp.) cover. Chipmunk (Neotamias spp.) abundance was best predicted through a combination of a negative response to oak tree cover and a positive response to spatial habitat complexity. California ground squirrel (Spermophilus beecheyi) abundance increased with increasing spatial habitat complexity. Our results suggest that fire severity, with subsequent changes in vegetation structure and habitat spatial complexity, can influence small mammal abundance patterns.

The landscape of fear as an emergent property of heterogeneity: Contrasting patterns of predation risk in grassland ecosystems.

PubMed

Atuo, Fidelis Akunke; O'Connell, Timothy John

2017-07-01

The likelihood of encountering a predator influences prey behavior and spatial distribution such that non-consumptive effects can outweigh the influence of direct predation. Prey species are thought to filter information on perceived predator encounter rates in physical landscapes into a landscape of fear defined by spatially explicit heterogeneity in predation risk. The presence of multiple predators using different hunting strategies further complicates navigation through a landscape of fear and potentially exposes prey to greater risk of predation. The juxtaposition of land cover types likely influences overlap in occurrence of different predators, suggesting that attributes of a landscape of fear result from complexity in the physical landscape. Woody encroachment in grasslands furnishes an example of increasing complexity with the potential to influence predator distributions. We examined the role of vegetation structure on the distribution of two avian predators, Red-tailed Hawk ( Buteo jamaicensis ) and Northern Harrier ( Circus cyaneus ), and the vulnerability of a frequent prey species of those predators, Northern Bobwhite ( Colinus virginianus ). We mapped occurrences of the raptors and kill locations of Northern Bobwhite to examine spatial vulnerability patterns in relation to landscape complexity. We use an offset model to examine spatially explicit habitat use patterns of these predators in the Southern Great Plains of the United States, and monitored vulnerability patterns of their prey species based on kill locations collected during radio telemetry monitoring. Both predator density and predation-specific mortality of Northern Bobwhite increased with vegetation complexity generated by fine-scale interspersion of grassland and woodland. Predation pressure was lower in more homogeneous landscapes where overlap of the two predators was less frequent. Predator overlap created areas of high risk for Northern Bobwhite amounting to 32% of the land area where landscape complexity was high and 7% where complexity was lower. Our study emphasizes the need to evaluate the role of landscape structure on predation dynamics and reveals another threat from woody encroachment in grasslands.

A Design Principle for an Autonomous Post-translational Pattern Formation.

PubMed

Sugai, Shuhei S; Ode, Koji L; Ueda, Hiroki R

2017-04-25

Previous autonomous pattern-formation models often assumed complex molecular and cellular networks. This theoretical study, however, shows that a system composed of one substrate with multisite phosphorylation and a pair of kinase and phosphatase can generate autonomous spatial information, including complex stripe patterns. All (de-)phosphorylation reactions are described with a generic Michaelis-Menten scheme, and all species freely diffuse without pre-existing gradients. Computational simulation upon >23,000,000 randomly generated parameter sets revealed the design motifs of cyclic reaction and enzyme sequestration by slow-diffusing substrates. These motifs constitute short-range positive and long-range negative feedback loops to induce Turing instability. The width and height of spatial patterns can be controlled independently by distinct reaction-diffusion processes. Therefore, multisite reversible post-translational modification can be a ubiquitous source for various patterns without requiring other complex regulations such as autocatalytic regulation of enzymes and is applicable to molecular mechanisms for inducing subcellular localization of proteins driven by post-translational modifications. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Spatial ecological processes and local factors predict the distribution and abundance of spawning by steelhead (Oncorhynchus mykiss) across a complex riverscape

Treesearch

Jeffrey A. Falke; Jason B. Dunham; Christopher E. Jordan; Kristina M. McNyset; Gordon H. Reeves

2013-01-01

Processes that influence habitat selection in landscapes involve the interaction of habitat composition and configuration and are particularly important for species with complex life cycles. We assessed the relative influence of landscape spatial processes and local habitat characteristics on patterns in the distribution and abundance of spawning steelhead (...

Comparison of in-situ and optical current-meter estimates of rip-current circulation

NASA Astrophysics Data System (ADS)

Moulton, M.; Chickadel, C. C.; Elgar, S.; Raubenheimer, B.

2016-12-01

Rip currents are fast, narrow, seaward flows that transport material from the shoreline to the shelf. Spatially and temporally complex rip current circulation patterns are difficult to resolve with in-situ instrument arrays. Here, high spatial-resolution estimates of rip current circulation from remotely sensed optical images of the sea surface are compared with in-situ estimates of currents in and near channels ( 1- to 2-m deep and 30-m wide) dredged across the surf zone. Alongshore flows are estimated using the optical current-meter method, and cross-shore flows are derived with the assumption of continuity. The observations span a range of wave conditions, tidal elevations, and flow patterns, including meandering alongshore currents near and in the channel, and 0.5 m/s alongshore flows converging at a 0.8 m/s rip jet in the channel. In addition, the remotely sensed velocities are used to investigate features of the spatially complex flow patterns not resolved by the spatially sparse in-situ sensors, including the spatial extent of feeder current zones and the width, alongshore position, and cross-shore extent of rip current jets. Funded by ASD(R&E) and NSF.

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.

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.

Instabilities and spatiotemporal patterns behind predator invasions with nonlocal prey competition.

PubMed

Merchant, Sandra M; Nagata, Wayne

2011-12-01

We study the influence of nonlocal intraspecies prey competition on the spatiotemporal patterns arising behind predator invasions in two oscillatory reaction-diffusion integro-differential models. We use three common types of integral kernels as well as develop a caricature system, to describe the influence of the standard deviation and kurtosis of the kernel function on the patterns observed. We find that nonlocal competition can destabilize the spatially homogeneous state behind the invasion and lead to the formation of complex spatiotemporal patterns, including stationary spatially periodic patterns, wave trains and irregular spatiotemporal oscillations. In addition, the caricature system illustrates how large standard deviation and low kurtosis facilitate the formation of these spatiotemporal patterns. This suggests that nonlocal competition may be an important mechanism underlying spatial pattern formation, particularly in systems where the competition between individuals varies over space in a platykurtic manner. Copyright © 2011 Elsevier Inc. All rights reserved.

A novel spatial performance metric for robust pattern optimization of distributed hydrological models

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, C.; Koch, J.

2017-12-01

Evaluation of performance is an integral part of model development and calibration as well as it is of paramount importance when communicating modelling results to stakeholders and the scientific community. There exists a comprehensive and well tested toolbox of metrics to assess temporal model performance in the hydrological modelling community. On the contrary, the experience to evaluate spatial performance is not corresponding to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study aims at making a contribution towards advancing spatial pattern oriented model evaluation for distributed hydrological models. This is achieved by introducing a novel spatial performance metric which provides robust pattern performance during model calibration. The promoted SPAtial EFficiency (spaef) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multi-component approach is necessary in order to adequately compare spatial patterns. spaef, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are tested in a spatial pattern oriented model calibration of a catchment model in Denmark. The calibration is constrained by a remote sensing based spatial pattern of evapotranspiration and discharge timeseries at two stations. Our results stress that stand-alone metrics tend to fail to provide holistic pattern information to the optimizer which underlines the importance of multi-component metrics. The three spaef components are independent which allows them to complement each other in a meaningful way. This study promotes the use of bias insensitive metrics which allow comparing variables which are related but may differ in unit in order to optimally exploit spatial observations made available by remote sensing platforms. We see great potential of spaef across environmental disciplines dealing with spatially distributed modelling.

Legacy of Pre-Disturbance Spatial Pattern Determines Early Structural Diversity following Severe Disturbance in Montane Spruce Forests

PubMed Central

Bače, Radek; Svoboda, Miroslav; Janda, Pavel; Morrissey, Robert C.; Wild, Jan; Clear, Jennifer L.; Čada, Vojtěch; Donato, Daniel C.

2015-01-01

Background Severe canopy-removing disturbances are native to many temperate forests and radically alter stand structure, but biotic legacies (surviving elements or patterns) can lend continuity to ecosystem function after such events. Poorly understood is the degree to which the structural complexity of an old-growth forest carries over to the next stand. We asked how pre-disturbance spatial pattern acts as a legacy to influence post-disturbance stand structure, and how this legacy influences the structural diversity within the early-seral stand. Methods Two stem-mapped one-hectare forest plots in the Czech Republic experienced a severe bark beetle outbreak, thus providing before-and-after data on spatial patterns in live and dead trees, crown projections, down logs, and herb cover. Results Post-disturbance stands were dominated by an advanced regeneration layer present before the disturbance. Both major species, Norway spruce (Picea abies) and rowan (Sorbus aucuparia), were strongly self-aggregated and also clustered to former canopy trees, pre-disturbance snags, stumps and logs, suggesting positive overstory to understory neighbourhood effects. Thus, although the disturbance dramatically reduced the stand’s height profile with ~100% mortality of the canopy layer, the spatial structure of post-disturbance stands still closely reflected the pre-disturbance structure. The former upper tree layer influenced advanced regeneration through microsite and light limitation. Under formerly dense canopies, regeneration density was high but relatively homogeneous in height; while in former small gaps with greater herb cover, regeneration density was lower but with greater heterogeneity in heights. Conclusion These findings suggest that pre-disturbance spatial patterns of forests can persist through severe canopy-removing disturbance, and determine the spatial structure of the succeeding stand. Such patterns constitute a subtle but key legacy effect, promoting structural complexity in early-seral forests as well as variable successional pathways and rates. This influence suggests a continuity in spatial ecosystem structure that may well persist through multiple forest generations. PMID:26421726

Spatial patterns of throughfall isotopic composition at the event and seasonal timescales

Treesearch

Scott T. Allen; Richard F. Keim; Jeffrey J. McDonnell

2015-01-01

Spatial variability of throughfall isotopic composition in forests is indicative of complex processes occurring in the canopy and remains insufficiently understood to properly characterize precipitation inputs to the catchment water balance. Here we investigate variability of throughfall isotopic composition with the objectives: (1) to quantify the spatial variability...

Scale effects on information theory-based measures applied to streamflow patterns in two rural watersheds

NASA Astrophysics Data System (ADS)

Pan, Feng; Pachepsky, Yakov A.; Guber, Andrey K.; McPherson, Brian J.; Hill, Robert L.

2012-01-01

SummaryUnderstanding streamflow patterns in space and time is important for improving flood and drought forecasting, water resources management, and predictions of ecological changes. Objectives of this work include (a) to characterize the spatial and temporal patterns of streamflow using information theory-based measures at two thoroughly-monitored agricultural watersheds located in different hydroclimatic zones with similar land use, and (b) to elucidate and quantify temporal and spatial scale effects on those measures. We selected two USDA experimental watersheds to serve as case study examples, including the Little River experimental watershed (LREW) in Tifton, Georgia and the Sleepers River experimental watershed (SREW) in North Danville, Vermont. Both watersheds possess several nested sub-watersheds and more than 30 years of continuous data records of precipitation and streamflow. Information content measures (metric entropy and mean information gain) and complexity measures (effective measure complexity and fluctuation complexity) were computed based on the binary encoding of 5-year streamflow and precipitation time series data. We quantified patterns of streamflow using probabilities of joint or sequential appearances of the binary symbol sequences. Results of our analysis illustrate that information content measures of streamflow time series are much smaller than those for precipitation data, and the streamflow data also exhibit higher complexity, suggesting that the watersheds effectively act as filters of the precipitation information that leads to the observed additional complexity in streamflow measures. Correlation coefficients between the information-theory-based measures and time intervals are close to 0.9, demonstrating the significance of temporal scale effects on streamflow patterns. Moderate spatial scale effects on streamflow patterns are observed with absolute values of correlation coefficients between the measures and sub-watershed area varying from 0.2 to 0.6 in the two watersheds. We conclude that temporal effects must be evaluated and accounted for when the information theory-based methods are used for performance evaluation and comparison of hydrological models.

The complex roles of space and environment in structuring functional, taxonomic and phylogenetic beta diversity of frogs in the Atlantic Forest

PubMed Central

Luiz, Amom Mendes; Sawaya, Ricardo J.

2018-01-01

Ecological communities are complex entities that can be maintained and structured by niche-based processes such as environmental conditions, and spatial processes such as dispersal. Thus, diversity patterns may be shaped simultaneously at different spatial scales by very distinct processes. Herein we assess whether and how functional, taxonomic, and phylogenetic beta diversities of frog tadpoles are explained by environmental and/or spatial predictors. We implemented a distance–based redundancy analysis to explore variation in components of beta diversity explained by pure environmental and pure spatial predictors, as well as their interactions, at both fine and broad spatial scales. Our results indicated important but complex roles of spatial and environmental predictors in structuring phylogenetic, taxonomic and functional beta diversities. The pure fine-scales spatial fraction was more important in structuring all beta diversity components, especially to functional and taxonomical spatial turnover. Environmental variables such as canopy cover and vegetation structure were important predictors of all components, but especially to functional and taxonomic beta diversity. We emphasize that distinct factors related to environment and space are affecting distinct components of beta diversity in different ways. Although weaker, phylogenetic beta diversity, which is structured more on biogeographical scales, and thus can be represented by spatially structured processes, was more related to broad spatial processes than other components. However, selected fine-scale spatial predictors denoted negative autocorrelation, which may be revealing the existence of differences in unmeasured habitat variables among samples. Although overall important, local environmental-based processes explained better functional and taxonomic beta diversity, as these diversity components carry an important ecological value. We highlight the importance of assessing different components of diversity patterns at different scales by spatially explicit models in order to improve our understanding of community structure and help to unravel the complex nature of biodiversity. PMID:29672575

Analysis of Alaskan burn severity patterns using remotely sensed data

USGS Publications Warehouse

Duffy, P.A.; Epting, J.; Graham, J.M.; Rupp, T.S.; McGuire, A.D.

2007-01-01

Wildland fire is the dominant large-scale disturbance mechanism in the Alaskan boreal forest, and it strongly influences forest structure and function. In this research, patterns of burn severity in the Alaskan boreal forest are characterised using 24 fires. First, the relationship between burn severity and area burned is quantified using a linear regression. Second, the spatial correlation of burn severity as a function of topography is modelled using a variogram analysis. Finally, the relationship between vegetation type and spatial patterns of burn severity is quantified using linear models where variograms account for spatial correlation. These results show that: 1) average burn severity increases with the natural logarithm of the area of the wildfire, 2) burn severity is more variable in topographically complex landscapes than in flat landscapes, and 3) there is a significant relationship between burn severity and vegetation type in flat landscapes but not in topographically complex landscapes. These results strengthen the argument that differential flammability of vegetation exists in some boreal landscapes of Alaska. Additionally, these results suggest that through feedbacks between vegetation and burn severity, the distribution of forest vegetation through time is likely more stable in flat terrain than it is in areas with more complex topography. ?? IAWF 2007.

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.

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.

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

NASA Astrophysics Data System (ADS)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and spatial statistics. The tool also includes some fundamental spatial and non-spatial database in regional population and environment, which can be updated by external database via CD or network. Utilizing this data mining and exploratory analytical tool, the users can easily and quickly analyse the huge mount of the interrelated regional data, and better understand the spatial patterns and trends of the regional development, so as to make a credible and scientific decision. Moreover, it can be used as an educational tool for spatial data analysis and environmental studies. In this paper, we also present a case study on Poyang Lake Basin as an application of the tool and spatial data mining in complex environmental studies. At last, several concluding remarks are discussed.

A necessarily complex model to explain the biogeography of the amphibians and reptiles of Madagascar.

PubMed

Brown, Jason L; Cameron, Alison; Yoder, Anne D; Vences, Miguel

2014-10-09

Pattern and process are inextricably linked in biogeographic analyses, though we can observe pattern, we must infer process. Inferences of process are often based on ad hoc comparisons using a single spatial predictor. Here, we present an alternative approach that uses mixed-spatial models to measure the predictive potential of combinations of hypotheses. Biodiversity patterns are estimated from 8,362 occurrence records from 745 species of Malagasy amphibians and reptiles. By incorporating 18 spatially explicit predictions of 12 major biogeographic hypotheses, we show that mixed models greatly improve our ability to explain the observed biodiversity patterns. We conclude that patterns are influenced by a combination of diversification processes rather than by a single predominant mechanism. A 'one-size-fits-all' model does not exist. By developing a novel method for examining and synthesizing spatial parameters such as species richness, endemism and community similarity, we demonstrate the potential of these analyses for understanding the diversification history of Madagascar's biota.

[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.

Influence of large-scale climate modes on dynamical complexity patterns of Indian Summer Monsoon rainfall

NASA Astrophysics Data System (ADS)

Papadimitriou, Constantinos; Donner, Reik V.; Stolbova, Veronika; Balasis, Georgios; Kurths, Jürgen

2015-04-01

Indian Summer monsoon is one of the most anticipated and important weather events with vast environmental, economical and social effects. Predictability of the Indian Summer Monsoon strength is crucial question for life and prosperity of the Indian population. In this study, we are attempting to uncover the relationship between the spatial complexity of Indian Summer Monsoon rainfall patterns, and the monsoon strength, in an effort to qualitatively determine how spatial organization of the rainfall patterns differs between strong and weak instances of the Indian Summer Monsoon. Here, we use observational satellite data from 1998 to 2012 from the Tropical Rainfall Measuring Mission (TRMM 3B42V7) and reanalysis gridded daily rainfall data for a time period of 57 years (1951-2007) (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE). In order to capture different aspects of the system's dynamics, first, we convert rainfall time series to binary symbolic sequences, exploring various thresholding criteria. Second, we apply the Shannon entropy formulation (in a block-entropy sense) using different measures of normalization of the resulting entropy values. Finally, we examine the effect of various large-scale climate modes such as El-Niño-Southern Oscillation, North Atlantic Oscillation, and Indian Ocean Dipole, on the emerging complexity patterns, and discuss the possibility for the utilization of such pattern maps in the forecasting of the spatial variability and strength of the Indian Summer Monsoon.

Spatial-pattern-induced evolution of a self-replicating loop network.

PubMed

Suzuki, Keisuke; Ikegami, Takashi

2006-01-01

We study a system of self-replicating loops in which interaction rules between individuals allow competition that leads to the formation of a hypercycle-like network. The main feature of the model is the multiple layers of interaction between loops, which lead to both global spatial patterns and local replication. The network of loops manifests itself as a spiral structure from which new kinds of self-replicating loops emerge at the boundaries between different species. In these regions, larger and more complex self-replicating loops live for longer periods of time, managing to self-replicate in spite of their slower replication. Of particular interest is how micro-scale interactions between replicators lead to macro-scale spatial pattern formation, and how these macro-scale patterns in turn perturb the micro-scale replication dynamics.

Artistic forms and complexity.

PubMed

Boon, J-P; Casti, J; Taylor, R P

2011-04-01

We discuss the inter-relationship between various concepts of complexity by introducing a complexity 'triangle' featuring objective complexity, subjective complexity and social complexity. Their connections are explored using visual and musical compositions of art. As examples, we quantify the complexity embedded within the paintings of the Jackson Pollock and the musical works of Johann Sebastian Bach. We discuss the challenges inherent in comparisons of the spatial patterns created by Pollock and the sonic patterns created by Bach, including the differing roles that time plays in these investigations. Our results draw attention to some common intriguing characteristics suggesting 'universality' and conjecturing that the fractal nature of art might have an intrinsic value of more general significance.

Single-trial detection of visual evoked potentials by common spatial patterns and wavelet filtering for brain-computer interface.

PubMed

Tu, Yiheng; Huang, Gan; Hung, Yeung Sam; Hu, Li; Hu, Yong; Zhang, Zhiguo

2013-01-01

Event-related potentials (ERPs) are widely used in brain-computer interface (BCI) systems as input signals conveying a subject's intention. A fast and reliable single-trial ERP detection method can be used to develop a BCI system with both high speed and high accuracy. However, most of single-trial ERP detection methods are developed for offline EEG analysis and thus have a high computational complexity and need manual operations. Therefore, they are not applicable to practical BCI systems, which require a low-complexity and automatic ERP detection method. This work presents a joint spatial-time-frequency filter that combines common spatial patterns (CSP) and wavelet filtering (WF) for improving the signal-to-noise (SNR) of visual evoked potentials (VEP), which can lead to a single-trial ERP-based BCI.

Medical image classification using spatial adjacent histogram based on adaptive local binary patterns.

PubMed

Liu, Dong; Wang, Shengsheng; Huang, Dezhi; Deng, Gang; Zeng, Fantao; Chen, Huiling

2016-05-01

Medical image recognition is an important task in both computer vision and computational biology. In the field of medical image classification, representing an image based on local binary patterns (LBP) descriptor has become popular. However, most existing LBP-based methods encode the binary patterns in a fixed neighborhood radius and ignore the spatial relationships among local patterns. The ignoring of the spatial relationships in the LBP will cause a poor performance in the process of capturing discriminative features for complex samples, such as medical images obtained by microscope. To address this problem, in this paper we propose a novel method to improve local binary patterns by assigning an adaptive neighborhood radius for each pixel. Based on these adaptive local binary patterns, we further propose a spatial adjacent histogram strategy to encode the micro-structures for image representation. An extensive set of evaluations are performed on four medical datasets which show that the proposed method significantly improves standard LBP and compares favorably with several other prevailing approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cell-type- and tissue-specific transcriptomes of the white spruce (Picea glauca) bark unmask fine-scale spatial patterns of constitutive and induced conifer defense.

PubMed

Celedon, Jose M; Yuen, Macaire M S; Chiang, Angela; Henderson, Hannah; Reid, Karen E; Bohlmann, Jörg

2017-11-01

Plant defenses often involve specialized cells and tissues. In conifers, specialized cells of the bark are important for defense against insects and pathogens. Using laser microdissection, we characterized the transcriptomes of cortical resin duct cells, phenolic cells and phloem of white spruce (Picea glauca) bark under constitutive and methyl jasmonate (MeJa)-induced conditions, and we compared these transcriptomes with the transcriptome of the bark tissue complex. Overall, ~3700 bark transcripts were differentially expressed in response to MeJa. Approximately 25% of transcripts were expressed in only one cell type, revealing cell specialization at the transcriptome level. MeJa caused cell-type-specific transcriptome responses and changed the overall patterns of cell-type-specific transcript accumulation. Comparison of transcriptomes of the conifer bark tissue complex and specialized cells resolved a masking effect inherent to transcriptome analysis of complex tissues, and showed the actual cell-type-specific transcriptome signatures. Characterization of cell-type-specific transcriptomes is critical to reveal the dynamic patterns of spatial and temporal display of constitutive and induced defense systems in a complex plant tissue or organ. This was demonstrated with the improved resolution of spatially restricted expression of sets of genes of secondary metabolism in the specialized cell types. © 2017 The Authors The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

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).

Effects of Topography-driven Micro-climatology on Evaporation

NASA Astrophysics Data System (ADS)

Adams, D. D.; Boll, J.; Wagenbrenner, N. S.

2017-12-01

The effects of spatial-temporal variation of climatic conditions on evaporation in micro-climates are not well defined. Current spatially-based remote sensing and modeling for evaporation is limited for high resolutions and complex topographies. We investigated the effect of topography-driven micro-climatology on evaporation supported by field measurements and modeling. Fourteen anemometers and thermometers were installed in intersecting transects over the complex topography of the Cook Agronomy Farm, Pullman, WA. WindNinja was used to create 2-D vector maps based on recorded observations for wind. Spatial analysis of vector maps using ArcGIS was performed for analysis of wind patterns and variation. Based on field measurements, wind speed and direction show consequential variability based on hill-slope location in this complex topography. Wind speed and wind direction varied up to threefold and more than 45 degrees, respectively for a given time interval. The use of existing wind models enables prediction of wind variability over the landscape and subsequently topography-driven evaporation patterns relative to wind. The magnitude of the spatial-temporal variability of wind therefore resulted in variable evaporation rates over the landscape. These variations may contribute to uneven crop development patterns observed during the late growth stages of the agricultural crops at the study location. Use of hill-slope location indexes and appropriate methods for estimating actual evaporation support development of methodologies to better define topography-driven heterogeneity in evaporation. The cumulative effects of spatially-variable climatic factors on evaporation are important to quantify the localized water balance and inform precision farming practices.

Understanding the Complexity of Temperature Dynamics in Xinjiang, China, from Multitemporal Scale and Spatial Perspectives

PubMed Central

Chen, Yaning; Li, Weihong; Liu, Zuhan; Wei, Chunmeng; Tang, Jie

2013-01-01

Based on the observed data from 51 meteorological stations during the period from 1958 to 2012 in Xinjiang, China, we investigated the complexity of temperature dynamics from the temporal and spatial perspectives by using a comprehensive approach including the correlation dimension (CD), classical statistics, and geostatistics. The main conclusions are as follows (1) The integer CD values indicate that the temperature dynamics are a complex and chaotic system, which is sensitive to the initial conditions. (2) The complexity of temperature dynamics decreases along with the increase of temporal scale. To describe the temperature dynamics, at least 3 independent variables are needed at daily scale, whereas at least 2 independent variables are needed at monthly, seasonal, and annual scales. (3) The spatial patterns of CD values at different temporal scales indicate that the complex temperature dynamics are derived from the complex landform. PMID:23843732

A novel instrumented multipeg running wheel system, Step-Wheel, for monitoring and controlling complex sequential stepping in mice

PubMed Central

Nagata, Masatoshi; Yanagihara, Dai; Tomioka, Ryohei; Utsumi, Hideko; Kubota, Yasuo; Yagi, Takeshi; Graybiel, Ann M.; Yamamori, Tetsuo

2011-01-01

Motor control is critical in daily life as well as in artistic and athletic performance and thus is the subject of intense interest in neuroscience. Mouse models of movement disorders have proven valuable for many aspects of investigation, but adequate methods for analyzing complex motor control in mouse models have not been fully established. Here, we report the development of a novel running-wheel system that can be used to evoke simple and complex stepping patterns in mice. The stepping patterns are controlled by spatially organized pegs, which serve as footholds that can be arranged in adjustable, ladder-like configurations. The mice run as they drink water from a spout, providing reward, while the wheel turns at a constant speed. The stepping patterns of the mice can thus be controlled not only spatially, but also temporally. A voltage sensor to detect paw touches is attached to each peg, allowing precise registration of footfalls. We show that this device can be used to analyze patterns of complex motor coordination in mice. We further demonstrate that it is possible to measure patterns of neural activity with chronically implanted tetrodes as the mice engage in vigorous running bouts. We suggest that this instrumented multipeg running wheel (which we name the Step-Wheel System) can serve as an important tool in analyzing motor control and motor learning in mice. PMID:21525375

A novel instrumented multipeg running wheel system, Step-Wheel, for monitoring and controlling complex sequential stepping in mice.

PubMed

Kitsukawa, Takashi; Nagata, Masatoshi; Yanagihara, Dai; Tomioka, Ryohei; Utsumi, Hideko; Kubota, Yasuo; Yagi, Takeshi; Graybiel, Ann M; Yamamori, Tetsuo

2011-07-01

Motor control is critical in daily life as well as in artistic and athletic performance and thus is the subject of intense interest in neuroscience. Mouse models of movement disorders have proven valuable for many aspects of investigation, but adequate methods for analyzing complex motor control in mouse models have not been fully established. Here, we report the development of a novel running-wheel system that can be used to evoke simple and complex stepping patterns in mice. The stepping patterns are controlled by spatially organized pegs, which serve as footholds that can be arranged in adjustable, ladder-like configurations. The mice run as they drink water from a spout, providing reward, while the wheel turns at a constant speed. The stepping patterns of the mice can thus be controlled not only spatially, but also temporally. A voltage sensor to detect paw touches is attached to each peg, allowing precise registration of footfalls. We show that this device can be used to analyze patterns of complex motor coordination in mice. We further demonstrate that it is possible to measure patterns of neural activity with chronically implanted tetrodes as the mice engage in vigorous running bouts. We suggest that this instrumented multipeg running wheel (which we name the Step-Wheel System) can serve as an important tool in analyzing motor control and motor learning in mice.

Quantify spatial relations to discover handwritten graphical symbols

NASA Astrophysics Data System (ADS)

Li, Jinpeng; Mouchère, Harold; Viard-Gaudin, Christian

2012-01-01

To model a handwritten graphical language, spatial relations describe how the strokes are positioned in the 2-dimensional space. Most of existing handwriting recognition systems make use of some predefined spatial relations. However, considering a complex graphical language, it is hard to express manually all the spatial relations. Another possibility would be to use a clustering technique to discover the spatial relations. In this paper, we discuss how to create a relational graph between strokes (nodes) labeled with graphemes in a graphical language. Then we vectorize spatial relations (edges) for clustering and quantization. As the targeted application, we extract the repetitive sub-graphs (graphical symbols) composed of graphemes and learned spatial relations. On two handwriting databases, a simple mathematical expression database and a complex flowchart database, the unsupervised spatial relations outperform the predefined spatial relations. In addition, we visualize the frequent patterns on two text-lines containing Chinese characters.

Nonlinear ring resonator: spatial pattern generation

NASA Astrophysics Data System (ADS)

Ivanov, Vladimir Y.; Lachinova, Svetlana L.; Irochnikov, Nikita G.

2000-03-01

We consider theoretically spatial pattern formation processes in a unidirectional ring cavity with thin layer of Kerr-type nonlinear medium. Our method is based on studying of two coupled equations. The first is a partial differential equation for temporal dynamics of phase modulation of light wave in the medium. It describes nonlinear interaction in the Kerr-type lice. The second is a free propagation equation for the intracavity field complex amplitude. It involves diffraction effects of light wave in the cavity.

Geomorphic controls of soil spatial complexity in a primeval mountain forest in the Czech Republic

NASA Astrophysics Data System (ADS)

Daněk, Pavel; Šamonil, Pavel; Phillips, Jonathan D.

2016-11-01

Soil diversity and complexity is influenced by a variety of factors, and much recent research has been focused on interpreting or modeling complexity based on soil-topography relationships, and effects of biogeomorphic processes. We aimed to (i) describe local soil diversity in one of the oldest forest reserves in Europe, (ii) employ existing graph theory concepts in pedocomplexity calculation and extend them by a novel approach based on hypothesis testing and an index measuring graph sequentiality (the extent to which soils have gradual vs. abrupt variations in underlying soil factors), and (iii) reveal the main sources of pedocomplexity, with a particular focus on geomorphic controls. A total of 954 soil profiles were described and classified to soil taxonomic units (STU) within a 46 ha area. We analyzed soil diversity using the Shannon index, and soil complexity using a novel graph theory approach. Pairwise tests of observed adjacencies, spectral radius and a newly proposed sequentiality index were used to describe and quantify the complexity of the spatial pattern of STUs. This was then decomposed into the contributions of three soil factor sequences (SFS), (i) degree of weathering and leaching processes, (ii) hydromorphology, and (iii) proportion of rock fragments. Six Reference Soil Groups and 37 second-level soil units were found. A significant portion of pedocomplexity occurred at distances shorter than the 22 m spacing of neighbouring soil profiles. The spectral radius (an index of complexity) of the pattern of soil spatial adjacency was 14.73, to which the individual SFS accounted for values of 2.0, 8.0 and 3.5, respectively. Significant sequentiality was found for degree of weathering and hydromorphology. Exceptional overall pedocomplexity was particularly caused by enormous spatial variability of soil wetness, representing a crucial soil factor sequence in the primeval forest. Moreover, the soil wetness gradient was partly spatially correlated with the gradient of soil weathering and leaching, suggesting synergistic influences of topography, climate, (hydro)geology and biomechanical and biochemical effects of individual trees. The pattern of stony soils, random in most respects, resulted probably from local geology and quaternary biogeomorphological processes. Thus, while geomorphology is the primary control over a very locally complex soil pattern, microtopography and local disturbances, mostly related to the effects of individual trees, are also critical. Considerable local pedodiversity seems to be an important component of the dynamics of old-growth mixed temperate mountain forests, with implications for decreasing pedodiversity in managed forests and deforested areas.

Automated platform for determination of LEDs spatial radiation pattern

NASA Astrophysics Data System (ADS)

Vladescu, Marian; Vuza, Dan Tudor

2015-02-01

Nowadays technologies lead to remarkable properties of the light-emitting diodes (LEDs), making them attractive for more and more applications, such as: interior and exterior lighting, outdoor LED panels, traffic signals, automotive (tail and brake lights, backlighting in dashboard and switches), backlighting of display panels, LCD displays, symbols on switches, keyboards, graphic boards and measuring scales. Usually, LEDs are small light sources consisting of a chip placed into a package, which may bring additional optics to this encapsulated ensemble, resulting in a less or more complex spatial distribution of the light intensity, with particular radiation patterns. This paper presents an automated platform designed to allow a quick and accurate determination of the spatial radiation patterns of LEDs encapsulated in various packages. Keywords: LED, luminous

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.

Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

2017-12-01

During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.

Understanding spatial and temporal patterning of astrocyte calcium transients via interactions between network transport and extracellular diffusion

NASA Astrophysics Data System (ADS)

Shtrahman, E.; Maruyama, D.; Olariu, E.; Fink, C. G.; Zochowski, M.

2017-02-01

Astrocytes form interconnected networks in the brain and communicate via calcium signaling. We investigate how modes of coupling between astrocytes influence the spatio-temporal patterns of calcium signaling within astrocyte networks and specifically how these network interactions promote coordination within this group of cells. To investigate these complex phenomena, we study reduced cultured networks of astrocytes and neurons. We image the spatial temporal patterns of astrocyte calcium activity and quantify how perturbing the coupling between astrocytes influences astrocyte activity patterns. To gain insight into the pattern formation observed in these cultured networks, we compare the experimentally observed calcium activity patterns to the patterns produced by a reduced computational model, where we represent astrocytes as simple units that integrate input through two mechanisms: gap junction coupling (network transport) and chemical release (extracellular diffusion). We examine the activity patterns in the simulated astrocyte network and their dependence upon these two coupling mechanisms. We find that gap junctions and extracellular chemical release interact in astrocyte networks to modulate the spatiotemporal patterns of their calcium dynamics. We show agreement between the computational and experimental findings, which suggests that the complex global patterns can be understood as a result of simple local coupling mechanisms.

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.

Ecological Complexity in a Coffee Agroecosystem: Spatial Heterogeneity, Population Persistence and Biological Control

PubMed Central

Liere, Heidi; Jackson, Doug; Vandermeer, John

2012-01-01

Background Spatial heterogeneity is essential for the persistence of many inherently unstable systems such as predator-prey and parasitoid-host interactions. Since biological interactions themselves can create heterogeneity in space, the heterogeneity necessary for the persistence of an unstable system could be the result of local interactions involving elements of the unstable system itself. Methodology/Principal Findings Here we report on a predatory ladybird beetle whose natural history suggests that the beetle requires the patchy distribution of the mutualism between its prey, the green coffee scale, and the arboreal ant, Azteca instabilis. Based on known ecological interactions and the natural history of the system, we constructed a spatially-explicit model and showed that the clustered spatial pattern of ant nests facilitates the persistence of the beetle populations. Furthermore, we show that the dynamics of the beetle consuming the scale insects can cause the clustered distribution of the mutualistic ants in the first place. Conclusions/Significance From a theoretical point of view, our model represents a novel situation in which a predator indirectly causes a spatial pattern of an organism other than its prey, and in doing so facilitates its own persistence. From a practical point of view, it is noteworthy that one of the elements in the system is a persistent pest of coffee, an important world commodity. This pest, we argue, is kept within limits of control through a complex web of ecological interactions that involves the emergent spatial pattern. PMID:23029061

Contrasting spatial patterns in active-fire and fire-suppressed Mediterranean climate old-growth mixed conifer forests.

PubMed

Fry, Danny L; Stephens, Scott L; Collins, Brandon M; North, Malcolm P; Franco-Vizcaíno, Ernesto; Gill, Samantha J

2014-01-01

In Mediterranean environments in western North America, historic fire regimes in frequent-fire conifer forests are highly variable both temporally and spatially. This complexity influenced forest structure and spatial patterns, but some of this diversity has been lost due to anthropogenic disruption of ecosystem processes, including fire. Information from reference forest sites can help management efforts to restore forests conditions that may be more resilient to future changes in disturbance regimes and climate. In this study, we characterize tree spatial patterns using four-ha stem maps from four old-growth, Jeffrey pine-mixed conifer forests, two with active-fire regimes in northwestern Mexico and two that experienced fire exclusion in the southern Sierra Nevada. Most of the trees were in patches, averaging six to 11 trees per patch at 0.007 to 0.014 ha(-1), and occupied 27-46% of the study areas. Average canopy gap sizes (0.04 ha) covering 11-20% of the area were not significantly different among sites. The putative main effects of fire exclusion were higher densities of single trees in smaller size classes, larger proportion of trees (≥ 56%) in large patches (≥ 10 trees), and decreases in spatial complexity. While a homogenization of forest structure has been a typical result from fire exclusion, some similarities in patch, single tree, and gap attributes were maintained at these sites. These within-stand descriptions provide spatially relevant benchmarks from which to manage for structural heterogeneity in frequent-fire forest types.

Measuring floodplain spatial patterns using continuous surface metrics at multiple scales

USGS Publications Warehouse

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

2015-01-01

Interactions between fluvial processes and floodplain ecosystems occur upon a floodplain surface that is often physically complex. Spatial patterns in floodplain topography have only recently been quantified over multiple scales, and discrepancies exist in how floodplain surfaces are perceived to be spatially organised. We measured spatial patterns in floodplain topography for pool 9 of the Upper Mississippi River, USA, using moving window analyses of eight surface metrics applied to a 1 × 1 m2 DEM over multiple scales. The metrics used were Range, SD, Skewness, Kurtosis, CV, SDCURV,Rugosity, and Vol:Area, and window sizes ranged from 10 to 1000 m in radius. Surface metric values were highly variable across the floodplain and revealed a high degree of spatial organisation in floodplain topography. Moran's I correlograms fit to the landscape of each metric at each window size revealed that patchiness existed at nearly all window sizes, but the strength and scale of patchiness changed within window size, suggesting that multiple scales of patchiness and patch structure exist in the topography of this floodplain. Scale thresholds in the spatial patterns were observed, particularly between the 50 and 100 m window sizes for all surface metrics and between the 500 and 750 m window sizes for most metrics. These threshold scales are ~ 15–20% and 150% of the main channel width (1–2% and 10–15% of the floodplain width), respectively. These thresholds may be related to structuring processes operating across distinct scale ranges. By coupling surface metrics, multi-scale analyses, and correlograms, quantifying floodplain topographic complexity is possible in ways that should assist in clarifying how floodplain ecosystems are structured.

Geography. Focus on Economics.

ERIC Educational Resources Information Center

Watson, George C., Jr.; Domingo, Vernon; Landman, Margaret; Miller, Glenn; Watson, Carlyjane D.; Hopkins, Martha C.

This book allows students to use two specific geographic perspectives - spatial and ecological - to help them understand spatial patterns and processes and the interaction of living and nonliving elements in complex webs of relationships within nature and between nature and society. The set of 12 lessons include: (1) "Where in the World?…

USE OF REVA'S WEB-BASED ENVIRONMENTAL DECISION TOOLKIT (EDT) TO ASSESS VULNERABILITY TO MERCURY ACROSS THE UNITED STATES

EPA Science Inventory

The problem of assessing risk from mercury across the nation is extremely complex involving integration of 1) our understanding of the methylation process in ecosystems, 2) the identification and spatial distribution of sensitive populations, and 3) the spatial pattern of mercury...

ASSESSING THE RISK ASSOCIATED WITH MERCURY: USING REVA'S WEBTOOL TO COMPARE DATA, ASSUMPTIONS, AND MODELS

EPA Science Inventory

The problem of assessing risk from mercury across the nation is extremely complex involving integration of I) our understanding of the methylation process in ecosystems, 2) the identification and spatial distribution of sensitive populations, and 3) the spatial pattern of mercury...

Random technique to encode complex valued holograms with on axis reconstruction onto phase-only displays.

PubMed

Luis Martínez Fuentes, Jose; Moreno, Ignacio

2018-03-05

A new technique for encoding the amplitude and phase of diffracted fields in digital holography is proposed. It is based on a random spatial multiplexing of two phase-only diffractive patterns. The first one is the phase information of the intended pattern, while the second one is a diverging optical element whose purpose is the control of the amplitude. A random number determines the choice between these two diffractive patterns at each pixel, and the amplitude information of the desired field governs its discrimination threshold. This proposed technique is computationally fast and does not require iterative methods, and the complex field reconstruction appears on axis. We experimentally demonstrate this new encoding technique with holograms implemented onto a flicker-free phase-only spatial light modulator (SLM), which allows the axial generation of such holograms. The experimental verification includes the phase measurement of generated patterns with a phase-shifting polarization interferometer implemented in the same experimental setup.

Analysis of sea use landscape pattern based on GIS: a case study in Huludao, China.

PubMed

Suo, Anning; Wang, Chen; Zhang, Minghui

2016-01-01

This study aims to analyse sea use landscape patterns on a regional scale based on methods of landscape ecology integrated with sea use spatial characteristics. Several landscape-level analysis indices, such as the dominance index, complex index, intensivity index, diversity index and sea congruency index, were established using Geographic Information System (GIS) and applied in Huludao, China. The results indicated that sea use landscape analysis indices, which were created based on the characteristics of sea use spatial patterns using GIS, are suitable to quantitatively describe the landscape patterns of sea use. They are operable tools for the landscape analysis of sea use. The sea use landscape in Huludao was dominated by fishing use with a landscape dominance index of 0.724. The sea use landscape is a complex mosaic with high diversity and plenty of fishing areas, as shown by the landscape complex index of 27.21 and the landscape diversity index of 1.25. Most sea use patches correspond to the marine functional zonation plan and the sea use congruency index is 0.89 in the fishing zone and 0.92 in the transportation zone.

Quantifying spatial and temporal trends in beach-dune volumetric changes using spatial statistics

NASA Astrophysics Data System (ADS)

Eamer, Jordan B. R.; Walker, Ian J.

2013-06-01

Spatial statistics are generally underutilized in coastal geomorphology, despite offering great potential for identifying and quantifying spatial-temporal trends in landscape morphodynamics. In particular, local Moran's Ii provides a statistical framework for detecting clusters of significant change in an attribute (e.g., surface erosion or deposition) and quantifying how this changes over space and time. This study analyzes and interprets spatial-temporal patterns in sediment volume changes in a beach-foredune-transgressive dune complex following removal of invasive marram grass (Ammophila spp.). Results are derived by detecting significant changes in post-removal repeat DEMs derived from topographic surveys and airborne LiDAR. The study site was separated into discrete, linked geomorphic units (beach, foredune, transgressive dune complex) to facilitate sub-landscape scale analysis of volumetric change and sediment budget responses. Difference surfaces derived from a pixel-subtraction algorithm between interval DEMs and the LiDAR baseline DEM were filtered using the local Moran's Ii method and two different spatial weights (1.5 and 5 m) to detect statistically significant change. Moran's Ii results were compared with those derived from a more spatially uniform statistical method that uses a simpler student's t distribution threshold for change detection. Morphodynamic patterns and volumetric estimates were similar between the uniform geostatistical method and Moran's Ii at a spatial weight of 5 m while the smaller spatial weight (1.5 m) consistently indicated volumetric changes of less magnitude. The larger 5 m spatial weight was most representative of broader site morphodynamics and spatial patterns while the smaller spatial weight provided volumetric changes consistent with field observations. All methods showed foredune deflation immediately following removal with increased sediment volumes into the spring via deposition at the crest and on lobes in the lee, despite erosion on the stoss slope and dune toe. Generally, the foredune became wider by landward extension and the seaward slope recovered from erosion to a similar height and form to that of pre-restoration despite remaining essentially free of vegetation.

Complex Greenland outlet glacier flow captured

PubMed Central

Aschwanden, Andy; Fahnestock, Mark A.; Truffer, Martin

2016-01-01

The Greenland Ice Sheet is losing mass at an accelerating rate due to increased surface melt and flow acceleration in outlet glaciers. Quantifying future dynamic contributions to sea level requires accurate portrayal of outlet glaciers in ice sheet simulations, but to date poor knowledge of subglacial topography and limited model resolution have prevented reproduction of complex spatial patterns of outlet flow. Here we combine a high-resolution ice-sheet model coupled to uniformly applied models of subglacial hydrology and basal sliding, and a new subglacial topography data set to simulate the flow of the Greenland Ice Sheet. Flow patterns of many outlet glaciers are well captured, illustrating fundamental commonalities in outlet glacier flow and highlighting the importance of efforts to map subglacial topography. Success in reproducing present day flow patterns shows the potential for prognostic modelling of ice sheets without the need for spatially varying parameters with uncertain time evolution. PMID:26830316

Weak conservation of structural features in the interfaces of homologous transient protein–protein complexes

PubMed Central

Sudha, Govindarajan; Singh, Prashant; Swapna, Lakshmipuram S; Srinivasan, Narayanaswamy

2015-01-01

Residue types at the interface of protein–protein complexes (PPCs) are known to be reasonably well conserved. However, we show, using a dataset of known 3-D structures of homologous transient PPCs, that the 3-D location of interfacial residues and their interaction patterns are only moderately and poorly conserved, respectively. Another surprising observation is that a residue at the interface that is conserved is not necessarily in the interface in the homolog. Such differences in homologous complexes are manifested by substitution of the residues that are spatially proximal to the conserved residue and structural differences at the interfaces as well as differences in spatial orientations of the interacting proteins. Conservation of interface location and the interaction pattern at the core of the interfaces is higher than at the periphery of the interface patch. Extents of variability of various structural features reported here for homologous transient PPCs are higher than the variation in homologous permanent homomers. Our findings suggest that straightforward extrapolation of interfacial nature and inter-residue interaction patterns from template to target could lead to serious errors in the modeled complex structure. Understanding the evolution of interfaces provides insights to improve comparative modeling of PPC structures. PMID:26311309

Spatial complexity reduces interaction strengths in the meta-food web of a river floodplain mosaic

USGS Publications Warehouse

Bellmore, James Ryan; Baxter, Colden Vance; Connolly, Patrick J.

2015-01-01

Theory states that both the spatial complexity of landscapes and the strength of interactions between consumers and their resources are important for maintaining biodiversity and the 'balance of nature.' Spatial complexity is hypothesized to promote biodiversity by reducing potential for competitive exclusion; whereas, models show weak trophic interactions can enhance stability and maintain biodiversity by dampening destabilizing oscillations associated with strong interactions. Here we show that spatial complexity can reduce the strength of consumer-resource interactions in natural food webs. By sequentially aggregating food webs of individual aquatic habitat patches across a floodplain mosaic, we found that increasing spatial complexity resulted in decreases in the strength of interactions between predators and prey, owing to a greater proportion of weak interactions and a reduced proportion of strong interactions in the meta-food web. The main mechanism behind this pattern was that some patches provided predation refugia for species which were often strongly preyed upon in other patches. If weak trophic interactions do indeed promote stability, then our findings may signal an additional mechanism by which complexity and stability are linked in nature. In turn, this may have implications for how the values of landscape complexity, and the costs of biophysical homogenization, are assessed.

A STATISTICAL THERMODYNAMIC MODEL OF THE ORGANIZATIONAL ORDER OF VEGETATION. (R827676)

EPA Science Inventory

The complex pattern of vegetation is the macroscopic manifestation of biological diversity and the ecological order in space and time. How is this overwhelmingly diverse, yet wonderfully ordered spatial pattern formed, and how does it evolve? To answer these questions, most tr...

EUV lithography reticles fabricated without the use of a patterned absorber

DOEpatents

Stearns, Daniel G.; Sweeney, Donald W.; Mirkarimi, Paul B.

2006-05-23

Absorber material used in conventional EUVL reticles is eliminated by introducing a direct modulation in the complex-valued reflectance of the multilayer. A spatially localized energy source such as a focused electron or ion beam directly writes a reticle pattern onto the reflective multilayer coating. Interdiffusion is activated within the film by an energy source that causes the multilayer period to contract in the exposed regions. The contraction is accurately determined by the energy dose. A controllable variation in the phase and amplitude of the reflected field in the reticle plane is produced by the spatial modulation of the multilayer period. This method for patterning an EUVL reticle has the advantages (1) avoiding the process steps associated with depositing and patterning an absorber layer and (2) providing control of the phase and amplitude of the reflected field with high spatial resolution.

Method for fabricating reticles for EUV lithography without the use of a patterned absorber

DOEpatents

Stearns, Daniel G [Los Altos, CA; Sweeney, Donald W [San Ramon, CA; Mirkarimi, Paul B [Sunol, CA

2003-10-21

Absorber material used in conventional EUVL reticles is eliminated by introducing a direct modulation in the complex-valued reflectance of the multilayer. A spatially localized energy source such as a focused electron or ion beam directly writes a reticle pattern onto the reflective multilayer coating. Interdiffusion is activated within the film by an energy source that causes the multilayer period to contract in the exposed regions. The contraction is accurately determined by the energy dose. A controllable variation in the phase and amplitude of the reflected field in the reticle plane is produced by the spatial modulation of the multilayer period. This method for patterning an EUVL reticle has the advantages of (1) avoiding the process steps associated with depositing and patterning an absorber layer and (2) providing control of the phase and amplitude of the reflected field with high spatial resolution.

Plasticity of human spatial cognition: spatial language and cognition covary across cultures.

PubMed

Haun, Daniel B M; Rapold, Christian J; Janzen, Gabriele; Levinson, Stephen C

2011-04-01

The present paper explores cross-cultural variation in spatial cognition by comparing spatial reconstruction tasks by Dutch and Namibian elementary school children. These two communities differ in the way they predominantly express spatial relations in language. Four experiments investigate cognitive strategy preferences across different levels of task-complexity and instruction. Data show a correlation between dominant linguistic spatial frames of reference and performance patterns in non-linguistic spatial memory tasks. This correlation is shown to be stable across an increase of complexity in the spatial array. When instructed to use their respective non-habitual cognitive strategy, participants were not easily able to switch between strategies and their attempts to do so impaired their performance. These results indicate a difference not only in preference but also in competence and suggest that spatial language and non-linguistic preferences and competences in spatial cognition are systematically aligned across human populations. Copyright © 2011 Elsevier B.V. All rights reserved.

Approaches to understanding the impact of life-history features on plant-pathogen co-evolutionary dynamics

Treesearch

Jeremy J. Burdon; Peter H. Thrall; Adnane Nemri

2012-01-01

Natural plant-pathogen associations are complex interactions in which the interplay of environment, host, and pathogen factors results in spatially heterogeneous ecological and epidemiological dynamics. The evolutionary patterns that result from the interaction of these factors are still relatively poorly understood. Recently, integration of the appropriate spatial and...

Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index

Treesearch

Taehee Hwang; Conghe Song; James Vose; Lawrence Band

2011-01-01

Forest canopy phenology is an important constraint on annual water and carbon budgets, and responds to regional interannual climate variation. In steep terrain, there are complex spatial variations in phenology due to topographic influences on microclimate, community composition, and available soil moisture. In this study, we investigate spatial patterns of phenology...

Contrasting Spatial Patterns in Active-Fire and Fire-Suppressed Mediterranean Climate Old-Growth Mixed Conifer Forests

PubMed Central

Fry, Danny L.; Stephens, Scott L.; Collins, Brandon M.; North, Malcolm P.; Franco-Vizcaíno, Ernesto; Gill, Samantha J.

2014-01-01

In Mediterranean environments in western North America, historic fire regimes in frequent-fire conifer forests are highly variable both temporally and spatially. This complexity influenced forest structure and spatial patterns, but some of this diversity has been lost due to anthropogenic disruption of ecosystem processes, including fire. Information from reference forest sites can help management efforts to restore forests conditions that may be more resilient to future changes in disturbance regimes and climate. In this study, we characterize tree spatial patterns using four-ha stem maps from four old-growth, Jeffrey pine-mixed conifer forests, two with active-fire regimes in northwestern Mexico and two that experienced fire exclusion in the southern Sierra Nevada. Most of the trees were in patches, averaging six to 11 trees per patch at 0.007 to 0.014 ha−1, and occupied 27–46% of the study areas. Average canopy gap sizes (0.04 ha) covering 11–20% of the area were not significantly different among sites. The putative main effects of fire exclusion were higher densities of single trees in smaller size classes, larger proportion of trees (≥56%) in large patches (≥10 trees), and decreases in spatial complexity. While a homogenization of forest structure has been a typical result from fire exclusion, some similarities in patch, single tree, and gap attributes were maintained at these sites. These within-stand descriptions provide spatially relevant benchmarks from which to manage for structural heterogeneity in frequent-fire forest types. PMID:24586472

Solve the Dilemma of Over-Simplification

NASA Astrophysics Data System (ADS)

Schmitt, Gerhard

Complexity science can help to understand the functioning and the interaction of the components of a city. In 1965, Christopher Alexander gave in his book A city is not a tree a description of the complex nature of urban organization. At this time, neither high-speed computers nor urban big data existed. Today, Luis Bettencourt et al. use complexity science to analyze data for countries, regions, or cities. The results can be used globally in other cities. Objectives of complexity science with regard to future cities are the observation and identification of tendencies and regularities in behavioral patterns, and to find correlations between them and spatial configurations. Complex urban systems cannot be understood in total yet. But research focuses on describing the system by finding some simple, preferably general and emerging patterns and rules that can be used for urban planning. It is important that the influencing factors are not just geo-spatial patterns but also consider variables which are important for the design quality. Complexity science is a way to solve the dilemma of oversimplification of insights from existing cities and their applications to new cities. An example: The effects of streets, public places and city structures on citizens and their behavior depend on how they are perceived. To describe this perception, it is not sufficient to consider only particular characteristics of the urban environment. Different aspects play a role and influence each other. Complexity science could take this fact into consideration and handle the non-linearity of the system...

Small-scale spatial variability of soil microbial community composition and functional diversity in a mixed forest

NASA Astrophysics Data System (ADS)

Wang, Qiufeng; Tian, Jing; Yu, Guirui

2014-05-01

Patterns in the spatial distribution of organisms provide important information about mechanisms that regulate the diversity and complexity of soil ecosystems. Therefore, information on spatial distribution of microbial community composition and functional diversity is urgently necessary. The spatial variability on a 26×36 m plot and vertical distribution (0-10 cm and 10-20 cm) of soil microbial community composition and functional diversity were studied in a natural broad-leaved Korean pine (Pinus koraiensis) mixed forest soil in Changbai Mountain. The phospholipid fatty acid (PLFA) pattern was used to characterize the soil microbial community composition and was compared with the community substrate utilization pattern using Biolog. Bacterial biomass dominated and showed higher variability than fungal biomass at all scales examined. The microbial biomass decreased with soil depths increased and showed less variability in lower 10-20 cm soil layer. The Shannon-Weaver index value for microbial functional diversity showed higher variability in upper 0-10 cm than lower 10-20 cm soil layer. Carbohydrates, carboxylic acids, polymers and amino acids are the main carbon sources possessing higher utilization efficiency or utilization intensity. At the same time, the four carbon source types contributed to the differentiation of soil microbial communities. This study suggests the higher diversity and complexity for this mix forest ecosystem. To determine the driving factors that affect this spatial variability of microorganism is the next step for our study.

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks.

PubMed

Wu, Siqi; Joseph, Antony; Hammonds, Ann S; Celniker, Susan E; Yu, Bin; Frise, Erwin

2016-04-19

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set ofDrosophilaearly embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation ofDrosophilaexpression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. The performance of PP with theDrosophiladata suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.

Self-Induced Switchings between Multiple Space-Time Patterns on Complex Networks of Excitable Units

NASA Astrophysics Data System (ADS)

Ansmann, Gerrit; Lehnertz, Klaus; Feudel, Ulrike

2016-01-01

We report on self-induced switchings between multiple distinct space-time patterns in the dynamics of a spatially extended excitable system. These switchings between low-amplitude oscillations, nonlinear waves, and extreme events strongly resemble a random process, although the system is deterministic. We show that a chaotic saddle—which contains all the patterns as well as channel-like structures that mediate the transitions between them—is the backbone of such a pattern-switching dynamics. Our analyses indicate that essential ingredients for the observed phenomena are that the system behaves like an inhomogeneous oscillatory medium that is capable of self-generating spatially localized excitations and that is dominated by short-range connections but also features long-range connections. With our findings, we present an alternative to the well-known ways to obtain self-induced pattern switching, namely, noise-induced attractor hopping, heteroclinic orbits, and adaptation to an external signal. This alternative way can be expected to improve our understanding of pattern switchings in spatially extended natural dynamical systems like the brain and the heart.

Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline

PubMed Central

Fan, Yong; Batmanghelich, Nematollah; Clark, Chris M.; Davatzikos, Christos

2010-01-01

Spatial patterns of brain atrophy in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) were measured via methods of computational neuroanatomy. These patterns were spatially complex and involved many brain regions. In addition to the hippocampus and the medial temporal lobe gray matter, a number of other regions displayed significant atrophy, including orbitofrontal and medial-prefrontal grey matter, cingulate (mainly posterior), insula, uncus, and temporal lobe white matter. Approximately 2/3 of the MCI group presented patterns of atrophy that overlapped with AD, whereas the remaining 1/3 overlapped with cognitively normal individuals, thereby indicating that some, but not all, MCI patients have significant and extensive brain atrophy in this cohort of MCI patients. Importantly, the group with AD-like patterns presented much higher rate of MMSE decline in follow-up visits; conversely, pattern classification provided relatively high classification accuracy (87%) of the individuals that presented relatively higher MMSE decline within a year from baseline. High-dimensional pattern classification, a nonlinear multivariate analysis, provided measures of structural abnormality that can potentially be useful for individual patient classification, as well as for predicting progression and examining multivariate relationships in group analyses. PMID:18053747

Evaluation of the spatial variability of soil water content at the spatial resolution of SMAP data products : case studies in Italy and Morocco

NASA Astrophysics Data System (ADS)

Menenti, Massimo; Akdim, Nadia; Alfieri, Silvia Maria; Labbassi, Kamal; De Lorenzi, Francesca; Bonfante, Antonello; Basile, Angelo

2014-05-01

Frequent and contiguous observations of soil water content such as the ones to be provided by SMAP are potentially useful to improve distributed models of soil water balance. This requires matching of observations and model estimates provided both sample spatial patterns consistently. The spatial resolution of SMAP soil water content data products ranges from 3 km X 3 km to 40 km X 40 km. Even the highest spatial resolution may not be sufficient to capture the spatial variability due to terrain, soil properties and precipitation. We have evaluated the SMAP spatial resolution against spatial variability of soil water content in two Mediterranean landscapes: a hilly area dominated by vineyards and olive orchards in Central Italy and a large irrigation schemes (Doukkala) in Morocco. The "Valle Telesina" is a 20,000 ha complex landscape located in South Italy in the Campania region, which has a complex geology and geomorphology and it is characterised by an E-W elongated graben where the Calore river flows. The main crops are grapevine (6,448 ha) and olive (3,390 ha). Soil information was mainly derived from an existing soil map at 1:50 000 scale (Terribile et al., 1996). The area includes 47 SMUs (Soil Mapping Units) and about 60 soil typological units (STUs). (Bonfante et al., 2011). In Doukkala, the soil water retention and unsaturated capillary conductivity were estimated from grain size distribution of a number of samples (22 pilot points, each one sampled in 3 horizons of 20cm), and combined with a soil map. The land use classification was carried out using a NDVI time series at high spatial resolution (Landsat TM and SPOT HRV). We have calculated soil water content for each soil unit in each area in response to several climate cases generating daily maps of soil water content at different depths. To reproduce spatial sampling by SMAP we have filtered these spatial patterns by calculating box averages with grid sizes of 1 km X 1 km and 5 km X 5 km. We have repeated this procedure for soil water content in the 0 to 5 cm and 0 to 10 cm depths. For each case we have compared the variance of filtered soil water content with the expected accuracy of SMAP soil water content. The two areas are very different as regards morphology and soil formation. The Valle Telesina is characterized by a very significant variability of soil hydrological properties leading to complex patterns in soil water content. Contrariwise, the soil properties estimated for all soil mapping units in the Dhoukkala collapse into just two pairs of water retention and hydraulic conductivity characteristics, leading to smoother patterns of soil water content.

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.

Disturbance History,Spatial Variability, and Patterns of Biodiversity

NASA Astrophysics Data System (ADS)

Bendix, J.; Wiley, J. J.; Commons, M.

2012-12-01

The intermediate disturbance hypothesis predicts that species diversity will be maximized in environments experiencing intermediate intensity disturbance, after an intermediate timespan. Because many landscapes comprise mosaics with complex disturbance histories, the theory implies that each patch in those mosaics should have a distinct level of diversity reflecting combined impact of the magnitude of disturbance and the time since it occurred. We modeled the changing patterns of species richness across a landscape experiencing varied scenarios of simulated disturbance. Model outputs show that individual landscape patches have highly variable species richness through time, with the details reflecting the timing, intensity and sequence of their disturbance history. When the results are mapped across the landscape, the resulting temporal and spatial complexity illustrates both the contingent nature of diversity and the danger of generalizing about the impacts of disturbance.

Spatial Variation in Development of Epibenthic Assemblages in a Coastal Lagoon

NASA Astrophysics Data System (ADS)

Benedetti-Cecchi, L.; Rindi, F.; Bertocci, I.; Bulleri, F.; Cinelli, F.

2001-05-01

Spatial and temporal patterns in colonization of epibenthic assemblages were measured in a coastal lagoon on the west coast of Italy using recruitment panels. It was proposed that if the ecological processes influencing development of assemblages were homogeneous within the lagoon, then there should be no differences in mean cover of colonists nor in spatial patterns of variance in abundance in different areas of the lagoon. In contrast, heterogeneity in ecological processes affecting development would be revealed by spatial variability in colonization. To test these hypotheses, two sticks each with five replicate panels were placed 3-5 m apart in each of two sites 30-100 m apart in each of three locations 500-100 m apart; the experiment was repeated three times between April and December 1999, using new sites at each location each time. The results revealed considerable spatial variation in the structure of developing assemblages across locations. There were significant Location or Time×Location effects in the mean abundance of common taxa, such as Enteromorpha intestinalis , Ulva rigida, Cladophora spp., bryozoans and serpulids. Patterns in spatial variation differed among locations for these organisms. Collectively, the results supported a model of spatial heterogeneity in intensity of processes influencing patterns of recruitment and development of epibenthic assemblages in the Lagoon of Orbetello. The implications of these results for management of environmental problems in complex, variable habitats such as coastal lagoons, are discussed.

Exploring the effects of spatial autocorrelation when identifying key drivers of wildlife crop-raiding.

PubMed

Songhurst, Anna; Coulson, Tim

2014-03-01

Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions.

An Innovative Metric to Evaluate Satellite Precipitation's Spatial Distribution

NASA Astrophysics Data System (ADS)

Liu, H.; Chu, W.; Gao, X.; Sorooshian, S.

2011-12-01

Thanks to its capability to cover the mountains, where ground measurement instruments cannot reach, satellites provide a good means of estimating precipitation over mountainous regions. In regions with complex terrains, accurate information on high-resolution spatial distribution of precipitation is critical for many important issues, such as flood/landslide warning, reservoir operation, water system planning, etc. Therefore, in order to be useful in many practical applications, satellite precipitation products should possess high quality in characterizing spatial distribution. However, most existing validation metrics, which are based on point/grid comparison using simple statistics, cannot effectively measure satellite's skill of capturing the spatial patterns of precipitation fields. This deficiency results from the fact that point/grid-wised comparison does not take into account of the spatial coherence of precipitation fields. Furth more, another weakness of many metrics is that they can barely provide information on why satellite products perform well or poor. Motivated by our recent findings of the consistent spatial patterns of the precipitation field over the western U.S., we developed a new metric utilizing EOF analysis and Shannon entropy. The metric can be derived through two steps: 1) capture the dominant spatial patterns of precipitation fields from both satellite products and reference data through EOF analysis, and 2) compute the similarities between the corresponding dominant patterns using mutual information measurement defined with Shannon entropy. Instead of individual point/grid, the new metric treat the entire precipitation field simultaneously, naturally taking advantage of spatial dependence. Since the dominant spatial patterns are shaped by physical processes, the new metric can shed light on why satellite product can or cannot capture the spatial patterns. For demonstration, a experiment was carried out to evaluate a satellite precipitation product, CMORPH, against the U.S. daily precipitation analysis of Climate Prediction Center (CPC) at a daily and .25o scale over the Western U.S.

[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.

Patterns of precipitation and soil moisture extremes in Texas, US: A complex network analysis

NASA Astrophysics Data System (ADS)

Sun, Alexander Y.; Xia, Youlong; Caldwell, Todd G.; Hao, Zengchao

2018-02-01

Understanding of the spatial and temporal dynamics of extreme precipitation not only improves prediction skills, but also helps to prioritize hazard mitigation efforts. This study seeks to enhance the understanding of spatiotemporal covariation patterns embedded in precipitation (P) and soil moisture (SM) by using an event-based, complex-network-theoretic approach. Events concurrences are quantified using a nonparametric event synchronization measure, and spatial patterns of hydroclimate variables are analyzed by using several network measures and a community detection algorithm. SM-P coupling is examined using a directional event coincidence analysis measure that takes the order of event occurrences into account. The complex network approach is demonstrated for Texas, US, a region possessing a rich set of hydroclimate features and is frequented by catastrophic flooding. Gridded daily observed P data and simulated SM data are used to create complex networks of P and SM extremes. The uncovered high degree centrality regions and community structures are qualitatively in agreement with the overall existing knowledge of hydroclimate extremes in the study region. Our analyses provide new visual insights on the propagation, connectivity, and synchronicity of P extremes, as well as the SM-P coupling, in this flood-prone region, and can be readily used as a basis for event-driven predictive analytics for other regions.

Unravelling spatio-temporal evapotranspiration patterns in topographically complex landscapes

NASA Astrophysics Data System (ADS)

Metzen, Daniel; Sheridan, Gary; Nyman, Petter; Lane, Patrick

2016-04-01

Vegetation co-evolves with soils and topography under a given long-term climatic forcing. Previous studies demonstrated a strong eco-hydrologic feedback between topography, vegetation and energy and water fluxes. Slope orientation (aspect and gradient) alter the magnitude of incoming solar radiation resulting in larger evaporative losses and less water availability on equator-facing slopes. Furthermore, non-local water inputs from upslope areas potentially contribute to available water at downslope positions. The combined effect of slope orientation and drainage position creates complex spatial patterns in biological productivity and pedogenesis, which in turn alter the local hydrology. In complex upland landscapes, topographic alteration of incoming radiation can cause substantial aridity index (ratio of potential evapotranspiration to precipitation) variations over small spatial extents. Most of the upland forests in south-east Australia are located in an aridity index (AI) range of 1-2, around the energy limited to water limited boundary, where forested systems are expected to be most sensitive to AI changes. In this research we aim to improve the fundamental understanding of spatio-temporal evolution of evapotranspiration (ET) patterns in complex terrain, accounting for local topographic effects on system properties (e.g. soil depth, sapwood area, leaf area) and variation in energy and water exchange processes due to slope orientation and drainage position. Six measurement plots were set-up in a mixed species eucalypt forest on a polar and equatorial-facing hillslope (AI ˜1.3 vs. 1.8) at varying drainage position (ridge, mid-slope, gully), while minimizing variations in other factors, e.g. geology and weather patterns. Sap flow, soil water content, incoming solar radiation and throughfall were continuously monitored at field sites spanning a wide range of soil depth (0.5 - >3m), maximum tree heights (17 - 51m) and LAI (1.2 - 4.6). Site-specific response curves of vapour pressure deficit and sap velocity emerged in relation to landscape position from spring until autumn, while the relationship collapsed into a single curve in winter. These patterns were amplified by more sapwood area per ha in wetter locations compared to drier locations. Topographically downscaled (20x20m pixels) monthly AI values were significantly correlated with monthly observations of sap velocity (R2 of 0.54 - 0.91) for all landscape positions except the equator-facing ridge position. Moreover, spatial vegetation and sap velocity patterns could be predicted using AI, topographic wetness index and elevation above stream (R2 of 0.67 and 0.59, respectively). Our findings emphasise the co-dependence of climate, topography and vegetation, and the need of a more holistic approach that includes terrain and vegetation characteristics to explain ET patterns. Our strong correlations with vegetation patterns and sap velocities demonstrate the potential use of spatially mappable climatic and topographic information to scale ET fluxes in complex terrain, and we anticipate that this approach is applicable across a wide range of ecosystems.

An experimental design method leading to chemical Turing patterns.

PubMed

Horváth, Judit; Szalai, István; De Kepper, Patrick

2009-05-08

Chemical reaction-diffusion patterns often serve as prototypes for pattern formation in living systems, but only two isothermal single-phase reaction systems have produced sustained stationary reaction-diffusion patterns so far. We designed an experimental method to search for additional systems on the basis of three steps: (i) generate spatial bistability by operating autoactivated reactions in open spatial reactors; (ii) use an independent negative-feedback species to produce spatiotemporal oscillations; and (iii) induce a space-scale separation of the activatory and inhibitory processes with a low-mobility complexing agent. We successfully applied this method to a hydrogen-ion autoactivated reaction, the thiourea-iodate-sulfite (TuIS) reaction, and noticeably produced stationary hexagonal arrays of spots and parallel stripes of pH patterns attributed to a Turing bifurcation. This method could be extended to biochemical reactions.

On the mechanical theory for biological pattern formation

NASA Astrophysics Data System (ADS)

Bentil, D. E.; Murray, J. D.

1993-02-01

We investigate the pattern-forming potential of mechanical models in embryology proposed by Oster, Murray and their coworkers. We show that the presence of source terms in the tissue extracellular matrix and cell density equations give rise to spatio-temporal oscillations. An extension of one such model to include ‘biologically realistic long range effects induces the formation of stationary spatial patterns. Previous attempts to solve the full system were in one dimension only. We obtain solutions in one dimension and extend our simulations to two dimensions. We show that a single mechanical model alone is capable of generating complex but regular spatial patterns rather than the requirement of model interaction as suggested by Nagorcka et al. and Shaw and Murray. We discuss some biological applications of the models among which are would healing and formation of dermatoglyphic (fingerprint) patterns.

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks

PubMed Central

2018-01-01

Much of the information the brain processes and stores is temporal in nature—a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds—we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. PMID:29537963

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks.

PubMed

Goudar, Vishwa; Buonomano, Dean V

2018-03-14

Much of the information the brain processes and stores is temporal in nature-a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds-we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. © 2018, Goudar et al.

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.

Spatial distribution of enzyme driven reactions at micro-scales

NASA Astrophysics Data System (ADS)

Kandeler, Ellen; Boeddinghaus, Runa; Nassal, Dinah; Preusser, Sebastian; Marhan, Sven; Poll, Christian

2017-04-01

Studies of microbial biogeography can often provide key insights into the physiologies, environmental tolerances, and ecological strategies of soil microorganisms that dominate in natural environments. In comparison with aquatic systems, soils are particularly heterogeneous. Soil heterogeneity results from the interaction of a hierarchical series of interrelated variables that fluctuate at many different spatial and temporal scales. Whereas spatial dependence of chemical and physical soil properties is well known at scales ranging from decimetres to several hundred metres, the spatial structure of soil enzymes is less clear. Previous work has primarily focused on spatial heterogeneity at a single analytical scale using the distribution of individual cells, specific types of organisms or collective parameters such as bacterial abundance or total microbial biomass. There are fewer studies that have considered variations in community function and soil enzyme activities. This presentation will give an overview about recent studies focusing on spatial pattern of different soil enzymes in the terrestrial environment. Whereas zymography allows the visualization of enzyme pattern in the close vicinity of roots, micro-sampling strategies followed by MUF analyses clarify micro-scale pattern of enzymes associated to specific microhabitats (micro-aggregates, organo-mineral complexes, subsoil compartments).

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

PubMed

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

Self-organization and complexity in historical landscape patterns

Treesearch

Janine Bolliger; Julien C. Sprott; David J. Mladenoff

2003-01-01

Self-organization describes the evolution process of complex structures where systems emerge spontaneously, driven internally by variations of the system itself. Self-organization to the critical state is manifested by scale-free behavior across many orders of magnitude (Bak et al. 1987, Bak 1996, Sole et a1. 1999). Spatial scale-free behavior implies fractal...

Spatial Patterns of Airborne Pesticides in the Alpine Habitat of a Declining Calfornia Amphibian, The Mountain Yellow-Legged Frog

EPA Science Inventory

The mountain yellow-legged frog complex (Rana muscosa complex) has disappeared from most of its historic localities in the Sierra Nevada of California, and airborne pesticides from the Central Valley have been implicated as a causal agent. To determine the distributions and conce...

Spatial Patterns of Airborne Pesticides in the Alpine Habitat of a Declining California Amphibian, The Mountain Yellow-Legged Frog

EPA Science Inventory

The mountain yellow-legged frog complex (Rana muscosa complex) has disappeared from most of its historic localities in the Sierra Nevada of California, and airborne pesticides from the Central Valley have been implicated as a causal agent. To determine the distributions and conce...

An Individual-Oriented Model on the Emergence of Support in Fights, Its Reciprocation and Exchange

PubMed Central

Hemelrijk, Charlotte K.; Puga-Gonzalez, Ivan

2012-01-01

Complex social behaviour of primates has usually been attributed to the operation of complex cognition. Recently, models have shown that constraints imposed by the socio-spatial structuring of individuals in a group may result in an unexpectedly high number of patterns of complex social behaviour, resembling the dominance styles of egalitarian and despotic species of macaques and the differences between them. This includes affiliative patterns, such as reciprocation of grooming, grooming up the hierarchy, and reconciliation. In the present study, we show that the distribution of support in fights, which is the social behaviour that is potentially most sophisticated in terms of cognitive processes, may emerge in the same way. The model represents the spatial grouping of individuals and their social behaviour, such as their avoidance of risks during attacks, the self-reinforcing effects of winning and losing their fights, their tendency to join in fights of others that are close by (social facilitation), their tendency to groom when they are anxious, the reduction of their anxiety by grooming, and the increase of anxiety when involved in aggression. Further, we represent the difference in intensity of aggression apparent in egalitarian and despotic macaques. The model reproduces many aspects of support in fights, such as its different types, namely, conservative, bridging and revolutionary, patterns of choice of coalition partners attributed to triadic awareness, those of reciprocation of support and ‘spiteful acts’ and of exchange between support and grooming. This work is important because it suggests that behaviour that seems to result from sophisticated cognition may be a side-effect of spatial structure and dominance interactions and it shows that partial correlations fail to completely omit these effects of spatial structure. Further, the model is falsifiable, since it results in many patterns that can easily be tested in real primates by means of existing data. PMID:22666348

Citizen science: A new perspective to advance spatial pattern evaluation in hydrology.

PubMed

Koch, Julian; Stisen, Simon

2017-01-01

Citizen science opens new pathways that can complement traditional scientific practice. Intuition and reasoning often make humans more effective than computer algorithms in various realms of problem solving. In particular, a simple visual comparison of spatial patterns is a task where humans are often considered to be more reliable than computer algorithms. However, in practice, science still largely depends on computer based solutions, which inevitably gives benefits such as speed and the possibility to automatize processes. However, the human vision can be harnessed to evaluate the reliability of algorithms which are tailored to quantify similarity in spatial patterns. We established a citizen science project to employ the human perception to rate similarity and dissimilarity between simulated spatial patterns of several scenarios of a hydrological catchment model. In total, the turnout counts more than 2500 volunteers that provided over 43000 classifications of 1095 individual subjects. We investigate the capability of a set of advanced statistical performance metrics to mimic the human perception to distinguish between similarity and dissimilarity. Results suggest that more complex metrics are not necessarily better at emulating the human perception, but clearly provide auxiliary information that is valuable for model diagnostics. The metrics clearly differ in their ability to unambiguously distinguish between similar and dissimilar patterns which is regarded a key feature of a reliable metric. The obtained dataset can provide an insightful benchmark to the community to test novel spatial metrics.

Remote Sensing-Based Detection and Spatial Pattern Analysis for Geo-Ecological Niche Modeling of Tillandsia SPP. In the Atacama, Chile

NASA Astrophysics Data System (ADS)

Wolf, N.; Siegmund, A.; del Río, C.; Osses, P.; García, J. L.

2016-06-01

In the coastal Atacama Desert in Northern Chile plant growth is constrained to so-called `fog oases' dominated by monospecific stands of the genus Tillandsia. Adapted to the hyperarid environmental conditions, these plants specialize on the foliar uptake of fog as main water and nutrient source. It is this characteristic that leads to distinctive macro- and micro-scale distribution patterns, reflecting complex geo-ecological gradients, mainly affected by the spatiotemporal occurrence of coastal fog respectively the South Pacific Stratocumulus clouds reaching inlands. The current work employs remote sensing, machine learning and spatial pattern/GIS analysis techniques to acquire detailed information on the presence and state of Tillandsia spp. in the Tarapacá region as a base to better understand the bioclimatic and topographic constraints determining the distribution patterns of Tillandsia spp. Spatial and spectral predictors extracted from WorldView-3 satellite data are used to map present Tillandsia vegetation in the Tarapaca region. Regression models on Vegetation Cover Fraction (VCF) are generated combining satellite-based as well as topographic variables and using aggregated high spatial resolution information on vegetation cover derived from UAV flight campaigns as a reference. The results are a first step towards mapping and modelling the topographic as well as bioclimatic factors explaining the spatial distribution patterns of Tillandsia fog oases in the Atacama, Chile.

The synergy between complex channel-specific FIR filter and spatial filter for single-trial EEG classification.

PubMed

Yu, Ke; Wang, Yue; Shen, Kaiquan; Li, Xiaoping

2013-01-01

The common spatial pattern analysis (CSP), a frequently utilized feature extraction method in brain-computer-interface applications, is believed to be time-invariant and sensitive to noises, mainly due to an inherent shortcoming of purely relying on spatial filtering. Therefore, temporal/spectral filtering which can be very effective to counteract the unfavorable influence of noises is usually used as a supplement. This work integrates the CSP spatial filters with complex channel-specific finite impulse response (FIR) filters in a natural and intuitive manner. Each hybrid spatial-FIR filter is of high-order, data-driven and is unique to its corresponding channel. They are derived by introducing multiple time delays and regularization into conventional CSP. The general framework of the method follows that of CSP but performs better, as proven in single-trial classification tasks like event-related potential detection and motor imagery.

Spatial pattern formation of microbes at the soil microscale affect soil C and N turnover in an individual-based microbial community model

NASA Astrophysics Data System (ADS)

Kaiser, Christina; Evans, Sarah; Dieckmann, Ulf; Widder, Stefanie

2016-04-01

At the μm-scale, soil is a highly structured and complex environment, both in physical as well as in biological terms, characterized by non-linear interactions between microbes, substrates and minerals. As known from mathematics and theoretical ecology, spatial structure significantly affects the system's behaviour by enabling synergistic dynamics, facilitating diversity, and leading to emergent phenomena such as self-organisation and self-regulation. Such phenomena, however, are rarely considered when investigating mechanisms of microbial soil organic matter turnover. Soil organic matter is the largest terrestrial reservoir for organic carbon (C) and nitrogen (N) and plays a pivotal role in global biogeochemical cycles. Still, the underlying mechanisms of microbial soil organic matter buildup and turnover remain elusive. We explored mechanisms of microbial soil organic matter turnover using an individual-based, stoichiometrically and spatially explicit computer model, which simulates the microbial de-composer system at the soil microscale (i.e. on a grid of 100 x 100 soil microsites). Soil organic matter dynamics in our model emerge as the result of interactions among individual microbes with certain functional traits (f.e. enzyme production rates, growth rates, cell stoichiometry) at the microscale. By degrading complex substrates, and releasing labile substances microbes in our model continusly shape their environment, which in turn feeds back to spatiotemporal dynamics of the microbial community. In order to test the effect of microbial functional traits and organic matter input rate on soil organic matter turnover and C and N storage, we ran the model into steady state using continuous inputs of fresh organic material. Surprisingly, certain parameter settings that induce resource limitation of microbes lead to regular spatial pattern formation (f.e. moving spiral waves) of microbes and substrate at the μm-scale at steady-state. The occurrence of these pattern can be explained by the Turing mechanism. These pattern formation had strong consequences for process rates, as well as for C and N storage in the soil at the steady state: Scenarios that exhibited pattern formation were generally associated with higher C storage at steady state compared to those without pattern formation (i.e. at non-limiting conditions for microbes). Moreover, pattern formation lead to a spatial decoupling of C and N turnover processes, and to a spatial decoupling of microbial N mineralization and N immobilization. Taken together, our theoretical analysis shows that self-organisation may be a feature of the soil decomposer system, with consequences for process rates of microbial C and N turnover. Pattern formation through spatial self-organization, which has been observed on larger spatial scales in other resource-limited communities (e.g., vegetation patterns in arid or wetland eco-systems), may also occur at the soil microscale, leaving its mark on the soil's storage capacity for C and N.

Trophic interactions induce spatial self-organization of microbial consortia on rough surfaces.

PubMed

Wang, Gang; Or, Dani

2014-10-24

The spatial context of microbial interactions common in natural systems is largely absent in traditional pure culture-based microbiology. The understanding of how interdependent microbial communities assemble and coexist in limited spatial domains remains sketchy. A mechanistic model of cell-level interactions among multispecies microbial populations grown on hydrated rough surfaces facilitated systematic evaluation of how trophic dependencies shape spatial self-organization of microbial consortia in complex diffusion fields. The emerging patterns were persistent irrespective of initial conditions and resilient to spatial and temporal perturbations. Surprisingly, the hydration conditions conducive for self-assembly are extremely narrow and last only while microbial cells remain motile within thin aqueous films. The resulting self-organized microbial consortia patterns could represent optimal ecological templates for the architecture that underlie sessile microbial colonies on natural surfaces. Understanding microbial spatial self-organization offers new insights into mechanisms that sustain small-scale soil microbial diversity; and may guide the engineering of functional artificial microbial consortia.

The characteristic patterns of neuronal avalanches in mice under anesthesia and at rest: An investigation using constrained artificial neural networks

PubMed Central

Knöpfel, Thomas; Leech, Robert

2018-01-01

Local perturbations within complex dynamical systems can trigger cascade-like events that spread across significant portions of the system. Cascades of this type have been observed across a broad range of scales in the brain. Studies of these cascades, known as neuronal avalanches, usually report the statistics of large numbers of avalanches, without probing the characteristic patterns produced by the avalanches themselves. This is partly due to limitations in the extent or spatiotemporal resolution of commonly used neuroimaging techniques. In this study, we overcome these limitations by using optical voltage (genetically encoded voltage indicators) imaging. This allows us to record cortical activity in vivo across an entire cortical hemisphere, at both high spatial (~30um) and temporal (~20ms) resolution in mice that are either in an anesthetized or awake state. We then use artificial neural networks to identify the characteristic patterns created by neuronal avalanches in our data. The avalanches in the anesthetized cortex are most accurately classified by an artificial neural network architecture that simultaneously connects spatial and temporal information. This is in contrast with the awake cortex, in which avalanches are most accurately classified by an architecture that treats spatial and temporal information separately, due to the increased levels of spatiotemporal complexity. This is in keeping with reports of higher levels of spatiotemporal complexity in the awake brain coinciding with features of a dynamical system operating close to criticality. PMID:29795654

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

Landscape evaluation for restoration planning on the Okanogan-Wenatchee National Forest, USA

Treesearch

Paul F. Hessburg; Keith M. Reynolds; R. Brion Salter; James D. Dickinson; William L. Gaines; Richy J. Harrod

2013-01-01

Land managers in the western US are beginning to understand that early 20th century forests displayed complex patterns of composition and structure at several different spatial scales, that there was interplay between patterns and processes within and across scales, and that these conditions have been radically altered by management. Further, they know that restoring...

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.

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

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

Wu, Siqi; Joseph, Antony; Hammonds, Ann S.

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identifiedmore » 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.« less

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

DOE PAGES

Wu, Siqi; Joseph, Antony; Hammonds, Ann S.; ...

2016-04-06

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identifiedmore » 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.« less

Spatial Light Modulators as Optical Crossbar Switches

NASA Technical Reports Server (NTRS)

Juday, Richard

2003-01-01

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

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.

Spatial Complexity Due to Bulk Electronic Liquid Crystals in Superconducting Dy-Bi2212

NASA Astrophysics Data System (ADS)

Carlson, Erica; Phillabaum, Benjamin; Dahmen, Karin

2012-02-01

Surface probes such as scanning tunneling microscopy (STM) have detected complex electronic patterns at the nanoscale in many high temperature superconductors. In cuprates, the pattern formation is associated with the pseudogap phase, a precursor to the high temperature superconducting state. Rotational symmetry breaking of the host crystal (i.e. from C4 to C2) in the form of electronic nematicity has recently been proposed as a unifying theme of the pseudogap phase [Lawler Nature 2010]. However, the fundamental physics governing the nanoscale pattern formation has not yet been identified. Here we use universal cluster properties extracted from STM studies of cuprate superconductors to identify the funda- mental physics controlling the complex pattern formation. We find that due to a delicate balance between disorder, interactions, and material anisotropy, the rotational symmetry breaking is fractal in nature, and that the electronic liquid crystal extends throughout the bulk of the material.

Ecological characterization and molecular differentiation of Culex pipiens complex taxa and Culex torrentium in eastern Austria.

PubMed

Zittra, Carina; Flechl, Eva; Kothmayer, Michael; Vitecek, Simon; Rossiter, Heidemarie; Zechmeister, Thomas; Fuehrer, Hans-Peter

2016-04-11

Culex pipiens complex taxa differ in behaviour, ecophysiology and epidemiologic importance. Despite their epidemiologic significance, information on genetic diversity, occurrence and seasonal and spatial distribution patterns of the Cx. pipiens complex is still insufficient. Assessment of seasonal and spatial distribution patterns of Culex pipiens forms and their congener Cx. torrentium is crucial for the understanding of their vector-pathogen dynamics. Female mosquitoes were trapped from April-October 2014 twice a month for a 24-h time period with BG-sentinel traps at 24 sampling sites in eastern Austria, using carbon dioxide as attractant. Ecological forms of Cx. pipiens s.l. and their hybrids were differentiated using the CQ11 locus, and Cx. pipiens forms and their congener Cx. torrentium using the ACE-2 gene. Differential exploitation of ecological niches by Cx. pipiens forms and Cx. torrentium was analysed using likelihood ratio tests. Possible effects of environmental parameters on these taxa were tested using PERMANOVA based on distance matrices and, if significant, were modelled in nMDS ordination space to estimate non-linear relationships. For this study, 1476 Culex spp. were sampled. Culex pipiens f. pipiens representing 87.33 % of the total catch was most abundant, followed by hybrids of both forms (5.62 %), Cx. torrentium (3.79 %) and Cx. pipiens f. molestus (3.25 %). Differences in proportional abundances were found between land cover classes. Ecological parameters affecting seasonal and spatial distribution of these taxa in eastern Austria are precipitation duration, air temperature, sunlight and the interaction term of precipitation amount and the Danube water level, which can be interpreted as a proxy for breeding habitat availability. The Cx. pipiens complex of eastern Austria comprises both ecologically different forms, the mainly ornithophilic form pipiens and the mainly mammalophilic and anthropophilic form molestus. Heterogeneous agricultural areas as areas of coexistence may serve as hybridization zones, resulting in potential bridge vectors between birds and humans. Occurrence, seasonal and spatial distribution patterns of the Cx. pipiens complex and Cx. torrentium and the presence of hybrids between both forms were quantified for the first time in Austria. These findings will improve the knowledge of their vector-pathogen dynamics in this country.

Texture-dependent motion signals in primate middle temporal area

PubMed Central

Gharaei, Saba; Tailby, Chris; Solomon, Selina S; Solomon, Samuel G

2013-01-01

Neurons in the middle temporal (MT) area of primate cortex provide an important stage in the analysis of visual motion. For simple stimuli such as bars and plaids some neurons in area MT – pattern cells – seem to signal motion independent of contour orientation, but many neurons – component cells – do not. Why area MT supports both types of receptive field is unclear. To address this we made extracellular recordings from single units in area MT of anaesthetised marmoset monkeys and examined responses to two-dimensional images with a large range of orientations and spatial frequencies. Component and pattern cell response remained distinct during presentation of these complex spatial textures. Direction tuning curves were sharpest in component cells when a texture contained a narrow range of orientations, but were similar across all neurons for textures containing all orientations. Response magnitude of pattern cells, but not component cells, increased with the spatial bandwidth of the texture. In addition, response variability in all neurons was reduced when the stimulus was rich in spatial texture. Fisher information analysis showed that component cells provide more informative responses than pattern cells when a texture contains a narrow range of orientations, but pattern cells had more informative responses for broadband textures. Component cells and pattern cells may therefore coexist because they provide complementary and parallel motion signals. PMID:24000175

Impacts of large dams on the complexity of suspended sediment dynamics in the Yangtze River

NASA Astrophysics Data System (ADS)

Wang, Yuankun; Rhoads, Bruce L.; Wang, Dong; Wu, Jichun; Zhang, Xiao

2018-03-01

The Yangtze River is one of the largest and most important rivers in the world. Over the past several decades, the natural sediment regime of the Yangtze River has been altered by the construction of dams. This paper uses multi-scale entropy analysis to ascertain the impacts of large dams on the complexity of high-frequency suspended sediment dynamics in the Yangtze River system, especially after impoundment of the Three Gorges Dam (TGD). In this study, the complexity of sediment dynamics is quantified by framing it within the context of entropy analysis of time series. Data on daily sediment loads for four stations located in the mainstem are analyzed for the past 60 years. The results indicate that dam construction has reduced the complexity of short-term (1-30 days) variation in sediment dynamics near the structures, but that complexity has actually increased farther downstream. This spatial pattern seems to reflect a filtering effect of the dams on the on the temporal pattern of sediment loads as well as decreased longitudinal connectivity of sediment transfer through the river system, resulting in downstream enhancement of the influence of local sediment inputs by tributaries on sediment dynamics. The TGD has had a substantial impact on the complexity of sediment series in the mainstem of the Yangtze River, especially after it became fully operational. This enhanced impact is attributed to the high trapping efficiency of this dam and its associated large reservoir. The sediment dynamics "signal" becomes more spatially variable after dam construction. This study demonstrates the spatial influence of dams on the high-frequency temporal complexity of sediment regimes and provides valuable information that can be used to guide environmental conservation of the Yangtze River.

Characteristics of pattern formation and evolution in approximations of Physarum transport networks.

PubMed

Jones, Jeff

2010-01-01

Most studies of pattern formation place particular emphasis on its role in the development of complex multicellular body plans. In simpler organisms, however, pattern formation is intrinsic to growth and behavior. Inspired by one such organism, the true slime mold Physarum polycephalum, we present examples of complex emergent pattern formation and evolution formed by a population of simple particle-like agents. Using simple local behaviors based on chemotaxis, the mobile agent population spontaneously forms complex and dynamic transport networks. By adjusting simple model parameters, maps of characteristic patterning are obtained. Certain areas of the parameter mapping yield particularly complex long term behaviors, including the circular contraction of network lacunae and bifurcation of network paths to maintain network connectivity. We demonstrate the formation of irregular spots and labyrinthine and reticulated patterns by chemoattraction. Other Turing-like patterning schemes were obtained by using chemorepulsion behaviors, including the self-organization of regular periodic arrays of spots, and striped patterns. We show that complex pattern types can be produced without resorting to the hierarchical coupling of reaction-diffusion mechanisms. We also present network behaviors arising from simple pre-patterning cues, giving simple examples of how the emergent pattern formation processes evolve into networks with functional and quasi-physical properties including tensionlike effects, network minimization behavior, and repair to network damage. The results are interpreted in relation to classical theories of biological pattern formation in natural systems, and we suggest mechanisms by which emergent pattern formation processes may be used as a method for spatially represented unconventional computation.

Optical Pattern Recognition

NASA Astrophysics Data System (ADS)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

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

Speckle-field digital holographic microscopy.

PubMed

Park, YongKeun; Choi, Wonshik; Yaqoob, Zahid; Dasari, Ramachandra; Badizadegan, Kamran; Feld, Michael S

2009-07-20

The use of coherent light in conventional holographic phase microscopy (HPM) poses three major drawbacks: poor spatial resolution, weak depth sectioning, and fixed pattern noise due to unwanted diffraction. Here, we report a technique which can overcome these drawbacks, but maintains the advantage of phase microscopy - high contrast live cell imaging and 3D imaging. A speckle beam of a complex spatial pattern is used for illumination to reduce fixed pattern noise and to improve optical sectioning capability. By recording of the electric field of speckle, we demonstrate high contrast 3D live cell imaging without the need for axial scanning - neither objective lens nor sample stage. This technique has great potential in studying biological samples with improved sensitivity, resolution and optical sectioning capability.

Spatial organization of xylem cell walls by ROP GTPases and microtubule-associated proteins.

PubMed

Oda, Yoshihisa; Fukuda, Hiroo

2013-12-01

Proper patterning of cellulosic cell walls is critical for cell shaping and differentiation of plant cells. Cortical microtubule arrays regulate the deposition patterns of cellulose microfibrils by controlling the targeting and trajectory of cellulose synthase complexes. Although some microtubule-associated proteins (MAPs) regulate the arrangement of cortical microtubules, knowledge about the overall mechanism governing the spacing of cortical microtubules is still limited. Recent studies reveal that ROP GTPases and MAPs spatially regulate the assembly and disassembly of cortical microtubules in developing xylem cells, in which localized secondary cell walls are deposited. Here, we review recent insights into the regulation of xylem cell wall patterning by cortical microtubules, ROP GTPases, and MAPs. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of harvest, fire, and pest/pathogen disturbances on the West Cascades ecoregion carbon balance

Treesearch

David P Turner; William D Ritts; Robert E Kennedy; Andrew N Gray; Zhiqiang Yang

2015-01-01

Background: Disturbance is a key influence on forest carbon dynamics, but the complexity of spatial and temporal patterns in forest disturbance makes it difficult to quantify their impacts on carbon flux over broad spatial domains. Here we used a time series of Landsat remote sensing images and a climate-driven carbon cycle process model to evaluate carbon fluxes at...

Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

USGS Publications Warehouse

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

2004-01-01

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

Historical and contemporary geographic data reveal complex spatial and temporal responses of vegetation to climate and land stewardship

USGS Publications Warehouse

Villarreal, Miguel L.; Norman, Laura M.; Webb, Robert H.; Turner, Raymond M.

2013-01-01

Vegetation and land-cover changes are not always directional but follow complex trajectories over space and time, driven by changing anthropogenic and abiotic conditions. We present a multi-observational approach to land-change analysis that addresses the complex geographic and temporal variability of vegetation changes related to climate and land use. Using land-ownership data as a proxy for land-use practices, multitemporal land-cover maps, and repeat photography dating to the late 19th century, we examine changing spatial and temporal distributions of two vegetation types with high conservation value in the southwestern United States: grasslands and riparian vegetation. In contrast to many reported vegetation changes, notably shrub encroachment in desert grasslands, we found an overall increase in grassland area and decline of xeroriparian and riparian vegetation. These observed change patterns were neither temporally directional nor spatially uniform over the landscape. Historical data suggest that long-term vegetation changes coincide with broad climate fluctuations while fine-scale patterns are determined by land-management practices. In some cases, restoration and active management appear to weaken the effects of climate on vegetation; therefore, if land managers in this region act in accord with on-going directional changes, the current drought and associated ecological reorganization may provide an opportunity to achieve desired restoration endpoints.

Methylmercury bioaccumulation in an urban estuary: Delaware River USA.

PubMed

Buckman, Kate; Taylor, Vivien; Broadley, Hannah; Hocking, Daniel; Balcom, Prentiss; Mason, Rob; Nislow, Keith; Chen, Celia

2017-09-01

Spatial variation in mercury (Hg) and methylmercury (MeHg) bioaccumulation in urban coastal watersheds reflects complex interactions between Hg sources, land use, and environmental gradients. We examined MeHg concentrations in fauna from the Delaware River estuary, and related these measurements to environmental parameters and human impacts on the waterway. The sampling sites followed a north to south gradient of increasing salinity, decreasing urban influence, and increasing marsh cover. Although mean total Hg in surface sediments (top 4cm) peaked in the urban estuarine turbidity maximum and generally decreased downstream, surface sediment MeHg concentrations showed no spatial patterns consistent with the examined environmental gradients, indicating urban influence on Hg loading to the sediment but not subsequent methylation. Surface water particulate MeHg concentration showed a positive correlation with marsh cover whereas dissolved MeHg concentrations were slightly elevated in the estuarine turbidity maximum region. Spatial patterns of MeHg bioaccumulation in resident fauna varied across taxa. Small fish showed increased MeHg concentrations in the more urban/industrial sites upstream, with concentrations generally decreasing farther downstream. Invertebrates either showed no clear spatial patterns in MeHg concentrations (blue crabs, fiddler crabs) or increasing concentrations further downstream (grass shrimp). Best-supported linear mixed models relating tissue concentration to environmental variables reflected these complex patterns, with species specific model results dominated by random site effects with a combination of particulate MeHg and landscape variables influencing bioaccumulation in some species. The data strengthen accumulating evidence that bioaccumulation in estuaries can be decoupled from sediment MeHg concentration, and that drivers of MeHg production and fate may vary within a small region.

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.

Chemistry with spatial control using particles and streams†

PubMed Central

Kalinin, Yevgeniy V.; Murali, Adithya

2012-01-01

Spatial control of chemical reactions, with micro- and nanometer scale resolution, has important consequences for one pot synthesis, engineering complex reactions, developmental biology, cellular biochemistry and emergent behavior. We review synthetic methods to engineer this spatial control using chemical diffusion from spherical particles, shells and polyhedra. We discuss systems that enable both isotropic and anisotropic chemical release from isolated and arrayed particles to create inhomogeneous and spatially patterned chemical fields. In addition to such finite chemical sources, we also discuss spatial control enabled with laminar flow in 2D and 3D microfluidic networks. Throughout the paper, we highlight applications of spatially controlled chemistry in chemical kinetics, reaction-diffusion systems, chemotaxis and morphogenesis. PMID:23145348

The Spatial Vision Tree: A Generic Pattern Recognition Engine- Scientific Foundations, Design Principles, and Preliminary Tree Design

NASA Technical Reports Server (NTRS)

Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

2010-01-01

New foundational ideas are used to define a novel approach to generic visual pattern recognition. These ideas proceed from the starting point of the intrinsic equivalence of noise reduction and pattern recognition when noise reduction is taken to its theoretical limit of explicit matched filtering. This led us to think of the logical extension of sparse coding using basis function transforms for both de-noising and pattern recognition to the full pattern specificity of a lexicon of matched filter pattern templates. A key hypothesis is that such a lexicon can be constructed and is, in fact, a generic visual alphabet of spatial vision. Hence it provides a tractable solution for the design of a generic pattern recognition engine. Here we present the key scientific ideas, the basic design principles which emerge from these ideas, and a preliminary design of the Spatial Vision Tree (SVT). The latter is based upon a cryptographic approach whereby we measure a large aggregate estimate of the frequency of occurrence (FOO) for each pattern. These distributions are employed together with Hamming distance criteria to design a two-tier tree. Then using information theory, these same FOO distributions are used to define a precise method for pattern representation. Finally the experimental performance of the preliminary SVT on computer generated test images and complex natural images is assessed.

Citizen science: A new perspective to advance spatial pattern evaluation in hydrology

PubMed Central

Stisen, Simon

2017-01-01

Citizen science opens new pathways that can complement traditional scientific practice. Intuition and reasoning often make humans more effective than computer algorithms in various realms of problem solving. In particular, a simple visual comparison of spatial patterns is a task where humans are often considered to be more reliable than computer algorithms. However, in practice, science still largely depends on computer based solutions, which inevitably gives benefits such as speed and the possibility to automatize processes. However, the human vision can be harnessed to evaluate the reliability of algorithms which are tailored to quantify similarity in spatial patterns. We established a citizen science project to employ the human perception to rate similarity and dissimilarity between simulated spatial patterns of several scenarios of a hydrological catchment model. In total, the turnout counts more than 2500 volunteers that provided over 43000 classifications of 1095 individual subjects. We investigate the capability of a set of advanced statistical performance metrics to mimic the human perception to distinguish between similarity and dissimilarity. Results suggest that more complex metrics are not necessarily better at emulating the human perception, but clearly provide auxiliary information that is valuable for model diagnostics. The metrics clearly differ in their ability to unambiguously distinguish between similar and dissimilar patterns which is regarded a key feature of a reliable metric. The obtained dataset can provide an insightful benchmark to the community to test novel spatial metrics. PMID:28558050

Formalized description and construction of semantic dictionary of graphic-text spatial relationship

NASA Astrophysics Data System (ADS)

Sun, Yizhong; Xue, Xiaolei; Zhao, Xiaoqin

2008-10-01

Graphic and text are two major elements in exhibiting of the results of urban planning and land administration. In combination, they convey the complex relationship resulting from spatial analysis and decision-making. Accurately interpreting and representing these relationships are important steps towards an intelligent GIS for urban planning. This paper employs concept-hierarchy-tree to formalize graphic-text relationships through a framework of spatial object lexicon, spatial relationship lexicon, restriction lexicon, applied pattern base, and word segmentation rule base. The methodology is further verified and shown effective on several urban planning archives.

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework.

PubMed

Namboodiri, Vijay Mohan K; Levy, Joshua M; Mihalas, Stefan; Sims, David W; Hussain Shuler, Marshall G

2016-08-02

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that "Lévy random walks"-which can produce power law path length distributions-are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent's goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers.

Entangled singularity patterns of photons in Ince-Gauss modes

NASA Astrophysics Data System (ADS)

Krenn, Mario; Fickler, Robert; Huber, Marcus; Lapkiewicz, Radek; Plick, William; Ramelow, Sven; Zeilinger, Anton

2013-01-01

Photons with complex spatial mode structures open up possibilities for new fundamental high-dimensional quantum experiments and for novel quantum information tasks. Here we show entanglement of photons with complex vortex and singularity patterns called Ince-Gauss modes. In these modes, the position and number of singularities vary depending on the mode parameters. We verify two-dimensional and three-dimensional entanglement of Ince-Gauss modes. By measuring one photon and thereby defining its singularity pattern, we nonlocally steer the singularity structure of its entangled partner, while the initial singularity structure of the photons is undefined. In addition we measure an Ince-Gauss specific quantum-correlation function with possible use in future quantum communication protocols.

Geographic patterns of networks derived from extreme precipitation over the Indian subcontinent

NASA Astrophysics Data System (ADS)

Stolbova, Veronika; Bookhagen, Bodo; Marwan, Norbert; Kurths, Juergen

2014-05-01

Complex networks (CN) and event synchronization (ES) methods have been applied to study a number of climate phenomena such as Indian Summer Monsoon (ISM), South-American Monsoon, and African Monsoon. These methods proved to be powerful tools to infer interdependencies in climate dynamics between geographical sites, spatial structures, and key regions of the considered climate phenomenon. Here, we use these methods to study the spatial temporal variability of the extreme rainfall over the Indian subcontinent, in order to filter the data by coarse-graining the network, and to identify geographic patterns that are signature features (spatial signatures) of the ISM. We find four main geographic patterns of networks derived from extreme precipitation over the Indian subcontinent using up-to-date satellite-derived, and high temporal and spatial resolution rain-gauge interpolated daily rainfall datasets. In order to prove that our results are also relevant for other climatic variables like pressure and temperature, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). We find that two of the patterns revealed from the CN extreme rainfall analysis coincide with those obtained for the pressure and temperature fields, and all four above mentioned patterns can be explained by topography, winds, and monsoon circulation. CN and ES enable to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to infer geographic pattern that are spatial signatures of the ISM. These patterns deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

Asynchronous ripple oscillations between left and right hippocampi during slow-wave sleep

PubMed Central

Villalobos, Claudio

2017-01-01

Spatial memory, among many other brain processes, shows hemispheric lateralization. Most of the published evidence suggests that the right hippocampus plays a leading role in the manipulation of spatial information. Concurrently in the hippocampus, memory consolidation during sleep periods is one of the key steps in the formation of newly acquired spatial memory traces. One of the most characteristic oscillatory patterns in the hippocampus are sharp-wave ripple (SWR) complexes. Within this complex, fast-field oscillations or ripples have been demonstrated to be instrumental in the memory consolidation process. Since these ripples are relevant for the consolidation of memory traces associated with spatial navigation, and this process appears to be lateralized, we hypothesize that ripple events between both hippocampi would exhibit different temporal dynamics. We tested this idea by using a modified "split-hyperdrive" that allows us to record simultaneous LFPs from both right and left hippocampi of Sprague-Dawley rats during sleep. We detected individual events and found that during sleep periods these ripples exhibited a different occurrence patterns between hemispheres. Most ripple events were synchronous between intra- rather than inter-hemispherical recordings, suggesting that ripples in the hippocampus are independently generated and locally propagated within a specific hemisphere. In this study, we propose the ripples’ lack of synchrony between left and right hippocampi as the putative physiological mechanism underlying lateralization of spatial memory. PMID:28158285

Asynchronous ripple oscillations between left and right hippocampi during slow-wave sleep.

PubMed

Villalobos, Claudio; Maldonado, Pedro E; Valdés, José L

2017-01-01

Spatial memory, among many other brain processes, shows hemispheric lateralization. Most of the published evidence suggests that the right hippocampus plays a leading role in the manipulation of spatial information. Concurrently in the hippocampus, memory consolidation during sleep periods is one of the key steps in the formation of newly acquired spatial memory traces. One of the most characteristic oscillatory patterns in the hippocampus are sharp-wave ripple (SWR) complexes. Within this complex, fast-field oscillations or ripples have been demonstrated to be instrumental in the memory consolidation process. Since these ripples are relevant for the consolidation of memory traces associated with spatial navigation, and this process appears to be lateralized, we hypothesize that ripple events between both hippocampi would exhibit different temporal dynamics. We tested this idea by using a modified "split-hyperdrive" that allows us to record simultaneous LFPs from both right and left hippocampi of Sprague-Dawley rats during sleep. We detected individual events and found that during sleep periods these ripples exhibited a different occurrence patterns between hemispheres. Most ripple events were synchronous between intra- rather than inter-hemispherical recordings, suggesting that ripples in the hippocampus are independently generated and locally propagated within a specific hemisphere. In this study, we propose the ripples' lack of synchrony between left and right hippocampi as the putative physiological mechanism underlying lateralization of spatial memory.

Advances in the use of observed spatial patterns of catchment hydrological response

NASA Astrophysics Data System (ADS)

Grayson, Rodger B.; Blöschl, Günter; Western, Andrew W.; McMahon, Thomas A.

Over the past two decades there have been repeated calls for the collection of new data for use in developing hydrological science. The last few years have begun to bear fruit from the seeds sown by these calls, through increases in the availability and utility of remote sensing data, as well as the execution of campaigns in research catchments aimed at providing new data for advancing hydrological understanding and predictive capability. In this paper we discuss some philosophical considerations related to model complexity, data availability and predictive performance, highlighting the potential of observed patterns in moving the science and practice of catchment hydrology forward. We then review advances that have arisen from recent work on spatial patterns, including in the characterisation of spatial structure and heterogeneity, and the use of patterns for developing, calibrating and testing distributed hydrological models. We illustrate progress via examples using observed patterns of snow cover, runoff occurrence and soil moisture. Methods for the comparison of patterns are presented, illustrating how they can be used to assess hydrologically important characteristics of model performance. These methods include point-to-point comparisons, spatial relationships between errors and landscape parameters, transects, and optimal local alignment. It is argued that the progress made to date augers well for future developments, but there is scope for improvements in several areas. These include better quantitative methods for pattern comparisons, better use of pattern information in data assimilation and modelling, and a call for improved archiving of data from field studies to assist in comparative studies for generalising results and developing fundamental understanding.

Regional Patterns of Stress Transfer in the Ablation Zone of the Western Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Andrews, L. C.; Hoffman, M. J.; Neumann, T.; Catania, G. A.; Luethi, M. P.; Hawley, R. L.

2016-12-01

Current understanding of the subglacial system indicates that the seasonal evolution of ice flow is strongly controlled by the gradual upstream progression of an inefficient - efficient transition within the subglacial hydrologic system followed by the reduction of melt and a downstream collapse of the efficient system. Using a spatiotemporally dense network of GPS-derived surface velocities from the Pâkitsoq Region of the western Greenland Ice Sheet, we find that this pattern of subglacial development is complicated by heterogeneous bed topography, resulting in complex patterns of ice flow. Following low elevation melt onset, early melt season strain rate anomalies are dominated by regional extension, which then gives way to spatially expansive compression. However, once daily minimum ice velocities fall below the observed winter background velocities, an alternating spatial pattern of extension and compression prevails. This pattern of strain rate anomalies is correlated with changing basal topography and differences in the magnitude of diurnal surface ice speeds. Along subglacial ridges, diurnal variability in ice speed is large, suggestive of a mature, efficient subglacial system. In regions of subglacial lows, diurnal variability in ice velocity is relatively low, likely associated with a less developed efficient subglacial system. The observed pattern suggests that borehole observations and modeling results demonstrating the importance of longitudinal stress transfer at a single field location are likely widely applicable in our study area and other regions of the Greenland Ice Sheet with highly variable bed topography. Further, the complex pattern of ice flow and evidence of spatially extensive longitudinal stress transfer add to the body of work indicating that the bed character plays an important role in the development of the subglacial system; closely matching diurnal ice velocity patterns with subglacial models may be difficult without coupling these models to high order ice flow models.

Decade-long bird community response to the spatial pattern of variable retention harvesting in red pine (Pinus resinosa) forests

Treesearch

Eddie L. Shea; Lisa A. Schulte; Brian J. Palik

2017-01-01

Structural complexity is widely recognized as an inherent characteristic of unmanaged forests critical to their function and resilience, but often reduced in their managed counterparts. Variable retention harvesting (VRH) has been proposed as a way to restore or enhance structural complexity in managed forests, and thereby sustain attendant biodiversity and ecosystem...

The human footprint in Mexico: physical geography and historical legacies.

PubMed

González-Abraham, Charlotte; Ezcurra, Exequiel; Garcillán, Pedro P; Ortega-Rubio, Alfredo; Kolb, Melanie; Bezaury Creel, Juan E

2015-01-01

Using publicly available data on land use and transportation corridors we calculated the human footprint index for the whole of Mexico to identify large-scale spatial patterns in the anthropogenic transformation of the land surface. We developed a map of the human footprint for the whole country and identified the ecological regions that have most transformed by human action. Additionally, we analyzed the extent to which (a) physical geography, expressed spatially in the form of biomes and ecoregions, compared to (b) historical geography, expressed as the spatial distribution of past human settlements, have driven the patterns of human modification of the land. Overall Mexico still has 56% of its land surface with low impact from human activities, but these areas are not evenly distributed. The lowest values are on the arid north and northwest, and the tropical southeast, while the highest values run along the coast of the Gulf of Mexico and from there inland along an east-to-west corridor that follows the Mexican transversal volcanic ranges and the associated upland plateau. The distribution of low- and high footprint areas within ecoregions forms a complex mosaic: the generally well-conserved Mexican deserts have some highly transformed agro-industrial areas, while many well-conserved, low footprint areas still persist in the highly-transformed ecoregions of central Mexico. We conclude that the spatial spread of the human footprint in Mexico is both the result of the limitations imposed by physical geography to human development at the biome level, and, within different biomes, of a complex history of past civilizations and technologies, including the 20th Century demographic explosion but also the spatial pattern of ancient settlements that were occupied by the Spanish Colony.

Simulation of spatial and temporal properties of aftershocks by means of the fiber bundle model

NASA Astrophysics Data System (ADS)

Monterrubio-Velasco, Marisol; Zúñiga, F. R.; Márquez-Ramírez, Victor Hugo; Figueroa-Soto, Angel

2017-11-01

The rupture processes of any heterogeneous material constitute a complex physical problem. Earthquake aftershocks show temporal and spatial behaviors which are consequence of the heterogeneous stress distribution and multiple rupturing following the main shock. This process is difficult to model deterministically due to the number of parameters and physical conditions, which are largely unknown. In order to shed light on the minimum requirements for the generation of aftershock clusters, in this study, we perform a simulation of the main features of such a complex process by means of a fiber bundle (FB) type model. The FB model has been widely used to analyze the fracture process in heterogeneous materials. It is a simple but powerful tool that allows modeling the main characteristics of a medium such as the brittle shallow crust of the earth. In this work, we incorporate spatial properties, such as the Coulomb stress change pattern, which help simulate observed characteristics of aftershock sequences. In particular, we introduce a parameter ( P) that controls the probability of spatial distribution of initial loads. Also, we use a "conservation" parameter ( π), which accounts for the load dissipation of the system, and demonstrate its influence on the simulated spatio-temporal patterns. Based on numerical results, we find that P has to be in the range 0.06 < P < 0.30, whilst π needs to be limited by a very narrow range ( 0.60 < π < 0.66) in order to reproduce aftershocks pattern characteristics which resemble those of observed sequences. This means that the system requires a small difference in the spatial distribution of initial stress, and a very particular fraction of load transfer in order to generate realistic aftershocks.

The Human Footprint in Mexico: Physical Geography and Historical Legacies

PubMed Central

Ortega-Rubio, Alfredo; Kolb, Melanie; Bezaury Creel, Juan E.

2015-01-01

Using publicly available data on land use and transportation corridors we calculated the human footprint index for the whole of Mexico to identify large-scale spatial patterns in the anthropogenic transformation of the land surface. We developed a map of the human footprint for the whole country and identified the ecological regions that have most transformed by human action. Additionally, we analyzed the extent to which (a) physical geography, expressed spatially in the form of biomes and ecoregions, compared to (b) historical geography, expressed as the spatial distribution of past human settlements, have driven the patterns of human modification of the land. Overall Mexico still has 56% of its land surface with low impact from human activities, but these areas are not evenly distributed. The lowest values are on the arid north and northwest, and the tropical southeast, while the highest values run along the coast of the Gulf of Mexico and from there inland along an east-to-west corridor that follows the Mexican transversal volcanic ranges and the associated upland plateau. The distribution of low- and high footprint areas within ecoregions forms a complex mosaic: the generally well-conserved Mexican deserts have some highly transformed agro-industrial areas, while many well-conserved, low footprint areas still persist in the highly-transformed ecoregions of central Mexico. We conclude that the spatial spread of the human footprint in Mexico is both the result of the limitations imposed by physical geography to human development at the biome level, and, within different biomes, of a complex history of past civilizations and technologies, including the 20th Century demographic explosion but also the spatial pattern of ancient settlements that were occupied by the Spanish Colony. PMID:25803839

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

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

Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less

Post-Fire Spatial Patterns of Soil Nitrogen Mineralization and Microbial Abundance

PubMed Central

Smithwick, Erica A. H.; Naithani, Kusum J.; Balser, Teri C.; Romme, William H.; Turner, Monica G.

2012-01-01

Stand-replacing fires influence soil nitrogen availability and microbial community composition, which may in turn mediate post-fire successional dynamics and nutrient cycling. However, fires create patchiness at both local and landscape scales and do not result in consistent patterns of ecological dynamics. The objectives of this study were to (1) quantify the spatial structure of microbial communities in forest stands recently affected by stand-replacing fire and (2) determine whether microbial variables aid predictions of in situ net nitrogen mineralization rates in recently burned stands. The study was conducted in lodgepole pine (Pinus contorta var. latifolia) and Engelmann spruce/subalpine fir (Picea engelmannii/Abies lasiocarpa) forest stands that burned during summer 2000 in Greater Yellowstone (Wyoming, USA). Using a fully probabilistic spatial process model and Bayesian kriging, the spatial structure of microbial lipid abundance and fungi-to-bacteria ratios were found to be spatially structured within plots two years following fire (for most plots, autocorrelation range varied from 1.5 to 10.5 m). Congruence of spatial patterns among microbial variables, in situ net N mineralization, and cover variables was evident. Stepwise regression resulted in significant models of in situ net N mineralization and included variables describing fungal and bacterial abundance, although explained variance was low (R2<0.29). Unraveling complex spatial patterns of nutrient cycling and the biotic factors that regulate it remains challenging but is critical for explaining post-fire ecosystem function, especially in Greater Yellowstone, which is projected to experience increased fire frequencies by mid 21st Century. PMID:23226324

Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.

2017-12-01

The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.

Landscape analysis of pesticide use patterns and ecological exposure

EPA Science Inventory

Background/Question/Methods The pesticide exposure landscape in the US is spatially and temporally complex. Researchers studying ecological exposure and effects of pesticides must consider a number of dimensions when framing experiments and conducting assessments. These dimension...

Topological patterns in street networks of self-organized urban settlements

NASA Astrophysics Data System (ADS)

Buhl, J.; Gautrais, J.; Reeves, N.; Solé, R. V.; Valverde, S.; Kuntz, P.; Theraulaz, G.

2006-02-01

Many urban settlements result from a spatially distributed, decentralized building process. Here we analyze the topological patterns of organization of a large collection of such settlements using the approach of complex networks. The global efficiency (based on the inverse of shortest-path lengths), robustness to disconnections and cost (in terms of length) of these graphs is studied and their possible origins analyzed. A wide range of patterns is found, from tree-like settlements (highly vulnerable to random failures) to meshed urban patterns. The latter are shown to be more robust and efficient.

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.

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.

Improvement of Speckle Contrast Image Processing by an Efficient Algorithm.

PubMed

Steimers, A; Farnung, W; Kohl-Bareis, M

2016-01-01

We demonstrate an efficient algorithm for the temporal and spatial based calculation of speckle contrast for the imaging of blood flow by laser speckle contrast analysis (LASCA). It reduces the numerical complexity of necessary calculations, facilitates a multi-core and many-core implementation of the speckle analysis and enables an independence of temporal or spatial resolution and SNR. The new algorithm was evaluated for both spatial and temporal based analysis of speckle patterns with different image sizes and amounts of recruited pixels as sequential, multi-core and many-core code.

Modelling the development and arrangement of the primary vascular structure in plants.

PubMed

Cartenì, Fabrizio; Giannino, Francesco; Schweingruber, Fritz Hans; Mazzoleni, Stefano

2014-09-01

The process of vascular development in plants results in the formation of a specific array of bundles that run throughout the plant in a characteristic spatial arrangement. Although much is known about the genes involved in the specification of procambium, phloem and xylem, the dynamic processes and interactions that define the development of the radial arrangement of such tissues remain elusive. This study presents a spatially explicit reaction-diffusion model defining a set of logical and functional rules to simulate the differentiation of procambium, phloem and xylem and their spatial patterns, starting from a homogeneous group of undifferentiated cells. Simulation results showed that the model is capable of reproducing most vascular patterns observed in plants, from primitive and simple structures made up of a single strand of vascular bundles (protostele), to more complex and evolved structures, with separated vascular bundles arranged in an ordered pattern within the plant section (e.g. eustele). The results presented demonstrate, as a proof of concept, that a common genetic-molecular machinery can be the basis of different spatial patterns of plant vascular development. Moreover, the model has the potential to become a useful tool to test different hypotheses of genetic and molecular interactions involved in the specification of vascular tissues.

Changing the spatial pattern of TFL1 expression reveals its key role in the shoot meristem in controlling Arabidopsis flowering architecture

PubMed Central

Baumann, Kim; Venail, Julien; Berbel, Ana; Domenech, Maria Jose; Money, Tracy; Conti, Lucio; Hanzawa, Yoshie; Madueno, Francisco; Bradley, Desmond

2015-01-01

Models for the control of above-ground plant architectures show how meristems can be programmed to be either shoots or flowers. Molecular, genetic, transgenic, and mathematical studies have greatly refined these models, suggesting that the phase of the shoot reflects different genes contributing to its repression of flowering, its vegetativeness (‘veg’), before activators promote flower development. Key elements of how the repressor of flowering and shoot meristem gene TFL1 acts have now been tested, by changing its spatiotemporal pattern. It is shown that TFL1 can act outside of its normal expression domain in leaf primordia or floral meristems to repress flower identity. These data show how the timing and spatial pattern of TFL1 expression affect overall plant architecture. This reveals that the underlying pattern of TFL1 interactors is complex and that they may be spatially more widespread than TFL1 itself, which is confined to shoots. However, the data show that while TFL1 and floral genes can both act and compete in the same meristem, it appears that the main shoot meristem is more sensitive to TFL1 rather than floral genes. This spatial analysis therefore reveals how a difference in response helps maintain the ‘veg’ state of the shoot meristem. PMID:26019254

Application of geostatistics with Indicator Kriging for analyzing spatial variability of groundwater arsenic concentrations in Southwest Bangladesh.

PubMed

Hassan, M Manzurul; Atkins, Peter J

2011-01-01

This article seeks to explore the spatial variability of groundwater arsenic (As) concentrations in Southwestern Bangladesh. Facts about spatial pattern of As are important to understand the complex processes of As concentrations and its spatial predictions in the unsampled areas of the study site. The relevant As data for this study were collected from Southwest Bangladesh and were analyzed with Flow Injection Hydride Generation Atomic Absorption Spectrometry (FI-HG-AAS). A geostatistical analysis with Indicator Kriging (IK) was employed to investigate the regionalized variation of As concentration. The IK prediction map shows a highly uneven spatial pattern of arsenic concentrations. The safe zones are mainly concentrated in the north, central and south part of the study area in a scattered manner, while the contamination zones are found to be concentrated in the west and northeast parts of the study area. The southwest part of the study area is contaminated with a highly irregular pattern. A Generalized Linear Model (GLM) was also used to investigate the relationship between As concentrations and aquifer depths. A negligible negative correlation between aquifer depth and arsenic concentrations was found in the study area. The fitted value with 95 % confidence interval shows a decreasing tendency of arsenic concentrations with the increase of aquifer depth. The adjusted mean smoothed lowess curve with a bandwidth of 0.8 shows an increasing trend of arsenic concentration up to a depth of 75 m, with some erratic fluctuations and regional variations at the depth between 30 m and 60 m. The borehole lithology was considered to analyze and map the pattern of As variability with aquifer depths. The study has performed an investigation of spatial pattern and variation of As concentrations.

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.

Citizen science: A new perspective to evaluate spatial patterns in hydrology.

NASA Astrophysics Data System (ADS)

Koch, J.; Stisen, S.

2016-12-01

Citizen science opens new pathways that can complement traditional scientific practice. Intuition and reasoning make humans often more effective than computer algorithms in various realms of problem solving. In particular, a simple visual comparison of spatial patterns is a task where humans are often considered to be more reliable than computer algorithms. However, in practice, science still largely depends on computer based solutions, which is inevitable giving benefits such as speed and the possibility to automatize processes. This study highlights the integration of the generally underused human resource into hydrology. We established a citizen science project on the zooniverse platform entitled Pattern Perception. The aim is to employ the human perception to rate similarity and dissimilarity between simulated spatial patterns of a hydrological catchment model. In total, the turnout counts more than 2,800 users that provided over 46,000 classifications of 1,095 individual subjects within 64 days after the launch. Each subject displays simulated spatial patterns of land-surface variables of a baseline model and six modelling scenarios. The citizen science data discloses a numeric pattern similarity score for each of the scenarios with respect to the reference. We investigate the capability of a set of innovative statistical performance metrics to mimic the human perception to distinguish between similarity and dissimilarity. Results suggest that more complex metrics are not necessarily better at emulating the human perception, but clearly provide flexibility and auxiliary information that is valuable for model diagnostics. The metrics clearly differ in their ability to unambiguously distinguish between similar and dissimilar patterns which is regarded a key feature of a reliable metric.

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.

Landscape analysis of methane flux across complex terrain

NASA Astrophysics Data System (ADS)

Kaiser, K. E.; McGlynn, B. L.; Dore, J. E.

2014-12-01

Greenhouse gas (GHG) fluxes into and out of the soil are influenced by environmental conditions resulting in landscape-mediated patterns of spatial heterogeneity. The temporal variability of inputs (e.g. precipitation) and internal redistribution (e.g. groundwater flow) and dynamics (e.g. microbial communities) make predicating these fluxes challenging. Complex terrain can provide a laboratory for improving understanding of the spatial patterns, temporal dynamics, and drivers of trace gas flux rates, requisite to constraining current GHG budgets and future scenarios. Our research builds on previous carbon cycle research at the USFS Tenderfoot Creek Experimental Forest, Little Belt Mountains, Montana that highlighted the relationships between landscape position and seasonal CO2 efflux, induced by the topographic redistribution of water. Spatial patterns and landscape scale mediation of CH4 fluxes in seasonally aerobic soils have not yet been elucidated. We measured soil methane concentrations and fluxes across a full range of landscape positions, leveraging topographic and seasonal gradients, to examine the relationships between environmental variables, hydrologic dynamics, and CH4 production and consumption. We determined that a threshold of ~30% VWC distinguished the direction of flux at individual time points, with the riparian area and uplands having distinct source/sink characteristics respectively. Riparian locations were either strong sources or fluctuated between sink and source behavior, resulting in near neutral seasonal flux. Upland sites however, exhibited significant relationships between sink strength and topographic/energy balance indices. Our results highlight spatial and temporal coherence to landscape scale heterogeneity of CH4 dynamics that can improve estimates of landscape scale CH4 balances and sensitivity to change.

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.

Field patterns: a new mathematical object

PubMed Central

Mattei, Ornella

2017-01-01

Field patterns occur in space–time microstructures such that a disturbance propagating along a characteristic line does not evolve into a cascade of disturbances, but rather concentrates on a pattern of characteristic lines. This pattern is the field pattern. In one spatial direction plus time, the field patterns occur when the slope of the characteristics is, in a sense, commensurate with the space–time microstructure. Field patterns with different spatial shifts do not generally interact, but rather evolve as if they live in separate dimensions, as many dimensions as the number of field patterns. Alternatively one can view a collection as a multi-component potential, with as many components as the number of field patterns. Presumably, if one added a tiny nonlinear term to the wave equation one would then see interactions between these field patterns in the multi-dimensional space that one can consider them to live, or between the different field components of the multi-component potential if one views them that way. As a result of PT-symmetry many of the complex eigenvalues of an appropriately defined transfer matrix have unit norm and hence the corresponding eigenvectors correspond to propagating modes. There are also modes that blow up exponentially with time. PMID:28293143

Microfluidic-based patterning of embryonic stem cells for in vitro development studies.

PubMed

Suri, Shalu; Singh, Ankur; Nguyen, Anh H; Bratt-Leal, Andres M; McDevitt, Todd C; Lu, Hang

2013-12-07

In vitro recapitulation of mammalian embryogenesis and examination of the emerging behaviours of embryonic structures require both the means to engineer complexity and accurately assess phenotypes of multicellular aggregates. Current approaches to study multicellular populations in 3D configurations are limited by the inability to create complex (i.e. spatially heterogeneous) environments in a reproducible manner with high fidelity thus impeding the ability to engineer microenvironments and combinations of cells with similar complexity to that found during morphogenic processes such as development, remodelling and wound healing. Here, we develop a multicellular embryoid body (EB) fusion technique as a higher-throughput in vitro tool, compared to a manual assembly, to generate developmentally relevant embryonic patterns. We describe the physical principles of the EB fusion microfluidic device design; we demonstrate that >60 conjoined EBs can be generated overnight and emulate a development process analogous to mouse gastrulation during early embryogenesis. Using temporal delivery of bone morphogenic protein 4 (BMP4) to embryoid bodies, we recapitulate embryonic day 6.5 (E6.5) during mouse embryo development with induced mesoderm differentiation in murine embryonic stem cells leading to expression of Brachyury-T-green fluorescent protein (T-GFP), an indicator of primitive streak development and mesoderm differentiation during gastrulation. The proposed microfluidic approach could be used to manipulate hundreds or more of individual embryonic cell aggregates in a rapid fashion, thereby allowing controlled differentiation patterns in fused multicellular assemblies to generate complex yet spatially controlled microenvironments.

Microfluidic-based patterning of embryonic stem cells for in vitro development studies

PubMed Central

Suri, Shalu; Singh, Ankur; Nguyen, Anh H.; Bratt-Leal, Andres M.; McDevitt, Todd C.

2013-01-01

In vitro recapitulation of mammalian embryogenesis and examination of the emerging behaviours of embryonic structures require both the means to engineer complexity and accurately assess phenotypes of multicellular aggregates. Current approaches to study multicellular populations in 3D configurations are limited by the inability to create complex (i.e. spatially heterogeneous) environments in a reproducible manner with high fidelity thus impeding the ability to engineer microenvironments and combinations of cells with similar complexity to that found during morphogenic processes such as development, remodelling and wound healing. Here, we develop a multicellular embryoid body (EB) fusion technique as a higher-throughput in vitro tool, compared to a manual assembly, to generate developmentally relevant embryonic patterns. We describe the physical principles of the EB fusion microfluidic device design; we demonstrate that >60 conjoined EBs can be generated overnight and emulate a development process analogous to mouse gastrulation during early embryogenesis. Using temporal delivery of bone morphogenic protein 4 (BMP4) to embryoid bodies, we recapitulate embryonic day 6.5 (E6.5) during mouse embryo development with induced mesoderm differentiation in murine embryonic stem cells leading to expression of Brachyury-T-green fluorescent protein (T-GFP), an indicator of primitive streak development and mesoderm differentiation during gastrulation. The proposed microfluidic approach could be used to manipulate hundreds or more of individual embryonic cell aggregates in a rapid fashion, thereby allowing controlled differentiation patterns in fused multicellular assemblies to generate complex yet spatially controlled microenvironments. PMID:24113509

Sediment heavy metals and benthic diversities in Hun-Tai River, northeast of China.

PubMed

Qu, Xiaodong; Ren, Ze; Zhang, Min; Liu, Xiaobo; Peng, Wenqi

2017-04-01

In aquatic ecosystems, metal contamination in sediments has become a ubiquitous environmental problem, causing serious issues. Hun-Tai River, located in northeast of China, flows through an important heavy industry region and metropolitan area. This study examined the heavy metals (Cd, Cr, Cu, Fe, Mn, Pb, Ni, and Zn) of sediments and diversities (taxa richness, Shannon diversity, and evenness) of benthic assemblages (benthic algae and macroinvertebrate) in Hun-Tai River. The results clearly described the spatial patterns of metal contamination in terms of geo-accumulation index and contamination factor, as well as the spatial patterns of benthic diversities in terms of taxa richness, Shannon index, and evenness by kriging interpolation. The sediments were largely contaminated by Cd, followed by Cu, Fe, Zn, Mn, and Ni. Cd and Zn had similar spatial patterns and similar sources. Cu, Fe, Mn, and Ni showed similar spatial patterns and similar sources. The surface sediments were unpolluted by Cr and Pb. The metal mines and the heavy industry in the major cities were the potential pollution sources. Benthic algae and macroinvertebrate responded similarly to the heterogeneous environment and metal contamination, with high taxa richness and Shannon index in middle-upper reaches of Hun-Tai River. Evenness showed complex spatial patterns. Under low contamination, both taxa richness, Shannon diversity, and evenness had a large variation range. However, under the moderate and high contamination, the taxa richness and Shannon diversity kept to a low level but the evenness had a high level. This study provided insights into the sediment heavy metal contamination in Hun-Tai River.

Large-scale patterns formed by solar active regions during the ascending phase of cycle 21

NASA Astrophysics Data System (ADS)

Gaizauskas, V.; Harvey, K. L.; Harvey, J. W.; Zwaan, C.

1983-02-01

Synoptic maps of photospheric magnetic fields prepared at the Kitt Peak National Observatory are used in investigating large-scale patterns in the spatial and temporal distribution of solar active regions for 27 solar rotations between 1977 and 1979. The active regions are found to be distributed in 'complexes of activity' (Bumba and Howard, 1965). With the working definition of a complex of activity based on continuity and proximity of the constituent active regions, the phenomenology of complexes is explored. It is found that complexes of activity form within one month and that they are typically maintained for 3 to 6 solar rotations by fresh injections of magnetic flux. During the active lifetime of a complex of activity, the total magnetic flux in the complex remains steady to within a factor of 2. The magnetic polarities are closely balanced, and each complex rotates about the sun at its own special, constant rate. In certain cases, the complexes form two diverging branches.

Regimes of Flow over Complex Structures of Endothelial Glycocalyx: A Molecular Dynamics Simulation Study.

PubMed

Jiang, Xi Zhuo; Feng, Muye; Ventikos, Yiannis; Luo, Kai H

2018-04-10

Flow patterns on surfaces grafted with complex structures play a pivotal role in many engineering and biomedical applications. In this research, large-scale molecular dynamics (MD) simulations are conducted to study the flow over complex surface structures of an endothelial glycocalyx layer. A detailed structure of glycocalyx has been adopted and the flow/glycocalyx system comprises about 5,800,000 atoms. Four cases involving varying external forces and modified glycocalyx configurations are constructed to reveal intricate fluid behaviour. Flow profiles including temporal evolutions and spatial distributions of velocity are illustrated. Moreover, streamline length and vorticity distributions under the four scenarios are compared and discussed to elucidate the effects of external forces and glycocalyx configurations on flow patterns. Results show that sugar chain configurations affect streamline length distributions but their impact on vorticity distributions is statistically insignificant, whilst the influence of the external forces on both streamline length and vorticity distributions are trivial. Finally, a regime diagram for flow over complex surface structures is proposed to categorise flow patterns.

A two-step patterning process increases the robustness of periodic patterning in the fly eye.

PubMed

Gavish, Avishai; Barkai, Naama

2016-06-01

Complex periodic patterns can self-organize through dynamic interactions between diffusible activators and inhibitors. In the biological context, self-organized patterning is challenged by spatial heterogeneities ('noise') inherent to biological systems. How spatial variability impacts the periodic patterning mechanism and how it can be buffered to ensure precise patterning is not well understood. We examine the effect of spatial heterogeneity on the periodic patterning of the fruit fly eye, an organ composed of ∼800 miniature eye units (ommatidia) whose periodic arrangement along a hexagonal lattice self-organizes during early stages of fly development. The patterning follows a two-step process, with an initial formation of evenly spaced clusters of ∼10 cells followed by a subsequent refinement of each cluster into a single selected cell. Using a probabilistic approach, we calculate the rate of patterning errors resulting from spatial heterogeneities in cell size, position and biosynthetic capacity. Notably, error rates were largely independent of the desired cluster size but followed the distributions of signaling speeds. Pre-formation of large clusters therefore greatly increases the reproducibility of the overall periodic arrangement, suggesting that the two-stage patterning process functions to guard the pattern against errors caused by spatial heterogeneities. Our results emphasize the constraints imposed on self-organized patterning mechanisms by the need to buffer stochastic effects. Author summary Complex periodic patterns are common in nature and are observed in physical, chemical and biological systems. Understanding how these patterns are generated in a precise manner is a key challenge. Biological patterns are especially intriguing, as they are generated in a noisy environment; cell position and cell size, for example, are subject to stochastic variations, as are the strengths of the chemical signals mediating cell-to-cell communication. The need to generate a precise and robust pattern in this 'noisy' environment restricts the space of patterning mechanisms that can function in the biological setting. Mathematical modeling is useful in comparing the sensitivity of different mechanisms to such variations, thereby highlighting key aspects of their design.We use mathematical modeling to study the periodic patterning of the fruit fly eye. In this system, a highly ordered lattice of differentiated cells is generated in a two-dimensional cell epithelium. The pattern is first observed by the appearance of evenly spaced clusters of ∼10 cells that express specific genes. Each cluster is subsequently refined into a single cell, which initiates the formation and differentiation of a miniature eye unit, the ommatidium. We formulate a mathematical model based on the known molecular properties of the patterning mechanism, and use a probabilistic approach to calculate the errors in cluster formation and refinement resulting from stochastic cell-to-cell variations ('noise') in different quantitative parameters. This enables us to define the parameters most influencing noise sensitivity. Notably, we find that this error is roughly independent of the desired cluster size, suggesting that large clusters are beneficial for ensuring the overall reproducibility of the periodic cluster arrangement. For the stage of cluster refinement, we find that rapid communication between cells is critical for reducing error. Our work provides new insights into the constraints imposed on mechanisms generating periodic patterning in a realistic, noisy environment, and in particular, discusses the different considerations in achieving optimal design of the patterning network.

Cross-diffusion-induced subharmonic spatial resonances in a predator-prey system

NASA Astrophysics Data System (ADS)

Gambino, G.; Lombardo, M. C.; Sammartino, M.

2018-01-01

In this paper we investigate the complex dynamics originated by a cross-diffusion-induced subharmonic destabilization of the fundamental subcritical Turing mode in a predator-prey reaction-diffusion system. The model we consider consists of a two-species Lotka-Volterra system with linear diffusion and a nonlinear cross-diffusion term in the predator equation. The taxis term in the search strategy of the predator is responsible for the onset of complex dynamics. In fact, our model does not exhibit any Hopf or wave instability, and on the basis of the linear analysis one should only expect stationary patterns; nevertheless, the presence of the nonlinear cross-diffusion term is able to induce a secondary instability: due to a subharmonic spatial resonance, the stationary primary branch bifurcates to an out-of-phase oscillating solution. Noticeably, the strong resonance between the harmonic and the subharmonic is able to generate the oscillating pattern albeit the subharmonic is below criticality. We show that, as the control parameter is varied, the oscillating solution (sub T mode) can undergo a sequence of secondary instabilities, generating a transition toward chaotic dynamics. Finally, we investigate the emergence of sub T -mode solutions on two-dimensional domains: when the fundamental mode describes a square pattern, subharmonic resonance originates oscillating square patterns. In the case of subcritical Turing hexagon solutions, the internal interactions with a subharmonic mode are able to generate the so-called "twinkling-eyes" pattern.

The geography of conflict between elk and agricultural values in the Cypress Hills, Canada.

PubMed

Hegel, Troy M; Gates, C Cormack; Eslinger, Dale

2009-01-01

Complex ecological issues like depredation and its management are determined by multiple factors acting at more than one scale and are interlinked with complex human social and economic behaviour. Depredation by wild herbivores can be a major obstacle to agricultural community support for wildlife conservation. For three decades, crop and fence damage, competition with livestock for native rangeland and tame pasture, and depredation of stored feed by elk (Cervus elaphus canadensis) have been the cause of conflict with agricultural producers in the Cypress Hills, Alberta and Saskatchewan. Tolerance of elk presence on private lands is low because few benefits accrue to private landowners; rather they largely perceive elk as a public resource produced at their expense. Government management actions have focused on abatement inputs (e.g., population reduction; fencing) and compensation, but incentives to alter land use patterns (crop choice and location) in response to damages have not been considered. Nor has there been information on spatial structure of the elk population that would allow targeted management actions instead of attempting to manage the entire population. In this study we analysed the spatial structure of the Cypress Hills elk population, the distribution of the elk harvest in relation to agricultural conflicts, developed models of the spatial patterns of conflict fields, and evaluated compensation patterns for damage by wild herbivores. We propose modifications to current abatement and compensation programs and discuss alternative approaches involving changes to agricultural land use patterns that may reduce the intensity of conflicts with elk, and increase the acceptance capacity of landowners.

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework

PubMed Central

Namboodiri, Vijay Mohan K.; Levy, Joshua M.; Mihalas, Stefan; Sims, David W.; Hussain Shuler, Marshall G.

2016-01-01

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that “Lévy random walks”—which can produce power law path length distributions—are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent’s goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers. PMID:27385831

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A < 103 km2) are usually mild enough to guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes involved in the river food web (e.g. biofilm and riparian vegetation dynamics), the study of rivers as dynamic networks provides important clues to water management strategies and freshwater ecosystem studies.

Structural complexity, movement bias, and metapopulation extinction risk in dendritic ecological networks

USGS Publications Warehouse

Campbell Grant, Evan H.

2011-01-01

Spatial complexity in metacommunities can be separated into 3 main components: size (i.e., number of habitat patches), spatial arrangement of habitat patches (network topology), and diversity of habitat patch types. Much attention has been paid to lattice-type networks, such as patch-based metapopulations, but interest in understanding ecological networks of alternative geometries is building. Dendritic ecological networks (DENs) include some increasingly threatened ecological systems, such as caves and streams. The restrictive architecture of dendritic ecological networks might have overriding implications for species persistence. I used a modeling approach to investigate how number and spatial arrangement of habitat patches influence metapopulation extinction risk in 2 DENs of different size and topology. Metapopulation persistence was higher in larger networks, but this relationship was mediated by network topology and the dispersal pathways used to navigate the network. Larger networks, especially those with greater topological complexity, generally had lower extinction risk than smaller and less-complex networks, but dispersal bias and magnitude affected the shape of this relationship. Applying these general results to real systems will require empirical data on the movement behavior of organisms and will improve our understanding of the implications of network complexity on population and community patterns and processes.

A category adjustment approach to memory for spatial location in natural scenes.

PubMed

Holden, Mark P; Curby, Kim M; Newcombe, Nora S; Shipley, Thomas F

2010-05-01

Memories for spatial locations often show systematic errors toward the central value of the surrounding region. This bias has been explained using a Bayesian model in which fine-grained and categorical information are combined (Huttenlocher, Hedges, & Duncan, 1991). However, experiments testing this model have largely used locations contained in simple geometric shapes. Use of this paradigm raises 2 issues. First, do results generalize to the complex natural world? Second, what types of information might be used to segment complex spaces into constituent categories? Experiment 1 addressed the 1st question by showing a bias toward prototypical values in memory for spatial locations in complex natural scenes. Experiment 2 addressed the 2nd question by manipulating the availability of basic visual cues (using color negatives) or of semantic information about the scene (using inverted images). Error patterns suggest that both perceptual and conceptual information are involved in segmentation. The possible neurological foundations of location memory of this kind are discussed. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Modeling the Impact of Spatial Structure on Growth Dynamics of Invasive Plant Species

NASA Astrophysics Data System (ADS)

Murphy, James T.; Johnson, Mark P.; Walshe, Ray

2013-07-01

Invasive nonindigenous plant species can have potentially serious detrimental effects on local ecosystems and, as a result, costly control efforts often have to be put in place to protect habitats. An example of an invasive problem on a global scale involves the salt marsh grass species from the genus Spartina. The spread of Spartina anglica in Europe and Asia has drawn much concern due to its ability to convert coastal habitats into cord-grass monocultures and to alter the native food webs. However, the patterns of invasion of Spartina species are amenable to spatially-explicit modeling strategies that take into account both temporal and spatio-temporal processes. In this study, an agent-based model of Spartina growth on a simulated mud flat environment was developed in order to study the effects of spatial pattern and initial seedling placement on the invasion dynamics of the population. The spatial pattern of an invasion plays a key role in the rate of spread of the species and understanding this can lead to significant cost savings when designing efficient control strategies. We present here a model framework that can be used to explicitly represent complex spatial and temporal patterns of invasion in order to be able to predict quantitatively the impact of these factors on invasion dynamics. This would be a useful tool for assessing eradication strategies and choosing optimal control solutions in order to be able to minimize future control costs.

Improving Spectral Results Using Row-by-Row Fourier Transform of Spatial Heterodyne Raman Spectrometer Interferogram.

PubMed

Barnett, Patrick D; Strange, K Alicia; Angel, S Michael

2017-06-01

This work describes a method of applying the Fourier transform to the two-dimensional Fizeau fringe patterns generated by the spatial heterodyne Raman spectrometer (SHRS), a dispersive interferometer, to correct the effects of certain types of optical alignment errors. In the SHRS, certain types of optical misalignments result in wavelength-dependent and wavelength-independent rotations of the fringe pattern on the detector. We describe here a simple correction technique that can be used in post-processing, by applying the Fourier transform in a row-by-row manner. This allows the user to be more forgiving of fringe alignment and allows for a reduction in the mechanical complexity of the SHRS.

Global terrestrial water storage connectivity revealed using complex climate network analyses

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Chen, J.; Donges, J.

2015-07-01

Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.

Patterns of cold-air drainage and microclimate in mid-latitude versus high-latitude mountains: contrasts and implications for climate change (Invited)

NASA Astrophysics Data System (ADS)

Pepin, N. C.

2009-12-01

Predictions of current spatial patterns of climate are difficult in areas of complex relief in all parts of the world, because of the interweaving influences of topography, elevation and aspect. These influences vary temporally as a result of the seasonal and diurnal cycles in radiation balance. In periods of negative energy balance, surface decoupling can occur as cold air drainage develops low-level temperature inversions, and the surface temperature regime beneath the inversion becomes divorced from free atmospheric forcing. Both the spatial scale and temporal persistence of this decoupling vary according to latitude, and although the physical processes that influence inversion formation are similar in polar areas and mid-latitude mountains, the contrasting seasonal and diurnal forcings make the end results very different. Examples are contrasted from detailed field temperature measurements (~50 sites per field area) taken over several years in areas of complex relief in the eastern Pyrenees (~42.5 deg N), the Oregon Cascades (also ~42.5 deg N) and Finnish Lapland (70 deg N and above the Arctic circle). In the former two locations decoupling is mostly diurnally driven, and small-scale topography is important in mediating the effects. Summer decoupling is brief and spatially limited, whereas winter decoupling can be more spatially extensive. There are strong relationships between synoptic conditions, as measured by objective flow indices at the 700 mb level (derived from NCEP/NCAR reanalysis fields) and the patterns of decoupling, which allow us to assess the effects of past and potential future circulation change on spatial patterns of future climate warming. In Finnish Lapland the decoupling regime most clearly approaches the mid-latitude pattern around the equinoxes when there are clear day and night periods. In winter and summer however (the polar night and polar day) with the muting of the diurnal cycle, processes are more poorly understood. Winter cold pools can develop and strengthen over days until eventually they extend over and above the topography. Strangely, there are also indistinct relationships with circulation indices at this time. While build-up can take days, destruction is often immediate and is dynamically forced. In summer, localized decoupling occurs on clear nights even though the sun is above the horizon, but micro-scale patterns are different than in mid-latitudes. The above comparison shows that polar areas are very different in their micro-temperature regimes than mid-latitude mountains and in their relationships of these regimes with circulation. Thus we expect detailed spatial patterns of climate change may be very different in the two regions.

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.

Thin-film Faraday patterns in three dimensions

NASA Astrophysics Data System (ADS)

Richter, Sebastian; Bestehorn, Michael

2017-04-01

We investigate the long time evolution of a thin fluid layer in three spatial dimensions located on a horizontal planar substrate. The substrate is subjected to time-periodic external vibrations in normal and in tangential direction with respect to the plane surface. The governing partial differential equation system of our model is obtained from the incompressible Navier-Stokes equations considering the limit of a thin fluid geometry and using the long wave lubrication approximation. It includes inertia and viscous friction. Numerical simulations evince the existence of persistent spatially complex surface patterns (periodic and quasiperiodic) for certain superpositions of two vertical excitations and initial conditions. Additional harmonic lateral excitations cause deformations but retain the basic structure of the patterns. Horizontal ratchet-shaped forces lead to a controllable lateral movement of the fluid. A Floquet analysis is used to determine the stability of the linearized system.

Coupled economic-coastline modeling with suckers and free riders

NASA Astrophysics Data System (ADS)

Williams, Zachary C.; McNamara, Dylan E.; Smith, Martin D.; Murray, A. Brad.; Gopalakrishnan, Sathya

2013-06-01

erosion is a natural trend along most sandy coastlines. Humans often respond to shoreline erosion with beach nourishment to maintain coastal property values. Locally extending the shoreline through nourishment alters alongshore sediment transport and changes shoreline dynamics in adjacent coastal regions. If left unmanaged, sandy coastlines can have spatially complex or simple patterns of erosion due to the relationship of large-scale morphology and the local wave climate. Using a numerical model that simulates spatially decentralized and locally optimal nourishment decisions characteristic of much of U.S. East Coast beach management, we find that human erosion intervention does not simply reflect the alongshore erosion pattern. Spatial interactions generate feedbacks in economic and physical variables that lead to widespread emergence of "free riders" and "suckers" with subsequent inequality in the alongshore distribution of property value. Along cuspate coastlines, such as those found along the U.S. Southeast Coast, these long-term property value differences span an order of magnitude. Results imply that spatially decentralized management of nourishment can lead to property values that are divorced from spatial erosion signals; this management approach is unlikely to be optimal.

A new framework for an electrophotographic printer model

NASA Astrophysics Data System (ADS)

Colon-Lopez, Fermin A.

Digital halftoning is a printing technology that creates the illusion of continuous tone images for printing devices such as electrophotographic printers that can only produce a limited number of tone levels. Digital halftoning works because the human visual system has limited spatial resolution which blurs the printed dots of the halftone image, creating the gray sensation of a continuous tone image. Because the printing process is imperfect it introduces distortions to the halftone image. The quality of the printed image depends, among other factors, on the complex interactions between the halftone image, the printer characteristics, the colorant, and the printing substrate. Printer models are used to assist in the development of new types of halftone algorithms that are designed to withstand the effects of printer distortions. For example, model-based halftone algorithms optimize the halftone image through an iterative process that integrates a printer model within the algorithm. The two main goals of a printer model are to provide accurate estimates of the tone and of the spatial characteristics of the printed halftone pattern. Various classes of printer models, from simple tone calibrations to complex mechanistic models, have been reported in the literature. Existing models have one or more of the following limiting factors: they only predict tone reproduction, they depend on the halftone pattern, they require complex calibrations or complex calculations, they are printer specific, they reproduce unrealistic dot structures, and they are unable to adapt responses to new data. The two research objectives of this dissertation are (1) to introduce a new framework for printer modeling and (2) to demonstrate the feasibility of such a framework in building an electrophotographic printer model. The proposed framework introduces the concept of modeling a printer as a texture transformation machine. The basic premise is that modeling the texture differences between the output printed images and the input images encompasses all printing distortions. The feasibility of the framework was tested with a case study modeling a monotone electrophotographic printer. The printer model was implemented as a bank of feed-forward neural networks, each one specialized in modeling a group of textural features of the printed halftone pattern. The textural features were obtained using a parametric representation of texture developed from a multiresolution decomposition proposed by other researchers. The textural properties of halftone patterns were analyzed and the key texture parameters to be modeled by the bank were identified. Guidelines for the multiresolution texture decomposition and the model operational parameters and operational limits were established. A method for the selection of training sets based on the morphological properties of the halftone patterns was also developed. The model is fast and has the capability to continue to learn with additional training. The model can be easily implemented because it only requires a calibrated scanner. The model was tested with halftone patterns representing a range of spatial characteristics found in halftoning. Results show that the model provides accurate predictions for the tone and the spatial characteristics when modeling halftone patterns individually and it provides close approximations when modeling multiple halftone patterns simultaneously. The success of the model justifies continued research of this new printer model framework.

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

Describing the brain in autism in five dimensions--magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach.

PubMed

Ecker, Christine; Marquand, Andre; Mourão-Miranda, Janaina; Johnston, Patrick; Daly, Eileen M; Brammer, Michael J; Maltezos, Stefanos; Murphy, Clodagh M; Robertson, Dene; Williams, Steven C; Murphy, Declan G M

2010-08-11

Autism spectrum disorder (ASD) is a neurodevelopmental condition with multiple causes, comorbid conditions, and a wide range in the type and severity of symptoms expressed by different individuals. This makes the neuroanatomy of autism inherently difficult to describe. Here, we demonstrate how a multiparameter classification approach can be used to characterize the complex and subtle structural pattern of gray matter anatomy implicated in adults with ASD, and to reveal spatially distributed patterns of discriminating regions for a variety of parameters describing brain anatomy. A set of five morphological parameters including volumetric and geometric features at each spatial location on the cortical surface was used to discriminate between people with ASD and controls using a support vector machine (SVM) analytic approach, and to find a spatially distributed pattern of regions with maximal classification weights. On the basis of these patterns, SVM was able to identify individuals with ASD at a sensitivity and specificity of up to 90% and 80%, respectively. However, the ability of individual cortical features to discriminate between groups was highly variable, and the discriminating patterns of regions varied across parameters. The classification was specific to ASD rather than neurodevelopmental conditions in general (e.g., attention deficit hyperactivity disorder). Our results confirm the hypothesis that the neuroanatomy of autism is truly multidimensional, and affects multiple and most likely independent cortical features. The spatial patterns detected using SVM may help further exploration of the specific genetic and neuropathological underpinnings of ASD, and provide new insights into the most likely multifactorial etiology of the condition.

Bet-hedging as a complex interaction among developmental instability, environmental heterogeneity, dispersal, and life-history strategy.

PubMed

Scheiner, Samuel M

2014-02-01

One potential evolutionary response to environmental heterogeneity is the production of randomly variable offspring through developmental instability, a type of bet-hedging. I used an individual-based, genetically explicit model to examine the evolution of developmental instability. The model considered both temporal and spatial heterogeneity alone and in combination, the effect of migration pattern (stepping stone vs. island), and life-history strategy. I confirmed that temporal heterogeneity alone requires a threshold amount of variation to select for a substantial amount of developmental instability. For spatial heterogeneity only, the response to selection on developmental instability depended on the life-history strategy and the form and pattern of dispersal with the greatest response for island migration when selection occurred before dispersal. Both spatial and temporal variation alone select for similar amounts of instability, but in combination resulted in substantially more instability than either alone. Local adaptation traded off against bet-hedging, but not in a simple linear fashion. I found higher-order interactions between life-history patterns, dispersal rates, dispersal patterns, and environmental heterogeneity that are not explainable by simple intuition. We need additional modeling efforts to understand these interactions and empirical tests that explicitly account for all of these factors.

Spatial analysis of agro-ecological data: Detection of spatial patterns combining three different methodical approaches

NASA Astrophysics Data System (ADS)

Heuer, A.; Casper, M. C.; Vohland, M.

2009-04-01

Processes in natural systems and the resulting patterns occur in ecological space and time. To study natural structures and to understand the functional processes it is necessary to identify the relevant spatial and temporal space at which these all occur; or with other words to isolate spatial and temporal patterns. In this contribution we will concentrate on the spatial aspects of agro-ecological data analysis. Data were derived from two agricultural plots, each of about 5 hectares, in the area of Newel, located in Western Palatinate, Germany. The plots had been conventionally cultivated with a crop rotation of winter rape, winter wheat and spring barley. Data about physical and chemical soil properties, vegetation and topography were i) collected by measurements in the field during three vegetation periods (2005-2008) and/or ii) derived from hyperspectral image data, acquired by a HyMap airborne imaging sensor (2005). To detect spatial variability within the plots, we applied three different approaches that examine and describe relationships among data. First, we used variography to get an overview of the data. A comparison of the experimental variograms facilitated to distinguish variables, which seemed to occur in related or dissimilar spatial space. Second, based on data available in raster-format basic cell statistics were conducted, using a geographic information system. Here we could make advantage of the powerful classification and visualization tool, which supported the spatial distribution of patterns. Third, we used an approach that is being used for visualization of complex highly dimensional environmental data, the Kohonen self-organizing map. The self-organizing map (SOM) uses multidimensional data that gets further reduced in dimensionality (2-D) to detect similarities in data sets and correlation between single variables. One of SOM's advantages is its powerful visualization capability. The combination of the three approaches leads to comprehensive and reasonable results, which will be presented in detail. It can be concluded, that the chosen strategy made it possible to complement preliminary findings, to validate the results of a single approach and to clearly delineate spatial patterns.

Combined point and distributed techniques for multidimensional estimation of spatial groundwater-stream water exchange in a heterogeneous sand bed-stream.

NASA Astrophysics Data System (ADS)

Gaona Garcia, J.; Lewandowski, J.; Bellin, A.

2017-12-01

Groundwater-stream water interactions in rivers determine water balances, but also chemical and biological processes in the streambed at different spatial and temporal scales. Due to the difficult identification and quantification of gaining, neutral and losing conditions, it is necessary to combine techniques with complementary capabilities and scale ranges. We applied this concept to a study site at the River Schlaube, East Brandenburg-Germany, a sand bed stream with intense sediment heterogeneity and complex environmental conditions. In our approach, point techniques such as temperature profiles of the streambed together with vertical hydraulic gradients provide data for the estimation of fluxes between groundwater and surface water with the numerical model 1DTempPro. On behalf of distributed techniques, fiber optic distributed temperature sensing identifies the spatial patterns of neutral, down- and up-welling areas by analysis of the changes in the thermal patterns at the streambed interface under certain flow. The study finally links point and surface temperatures to provide a method for upscaling of fluxes. Point techniques provide point flux estimates with essential depth detail to infer streambed structures while the results hardly represent the spatial distribution of fluxes caused by the heterogeneity of streambed properties. Fiber optics proved capable of providing spatial thermal patterns with enough resolution to observe distinct hyporheic thermal footprints at multiple scales. The relation of thermal footprint patterns and temporal behavior with flux results from point techniques enabled the use of methods for spatial flux estimates. The lack of detailed information of the physical driver's spatial distribution restricts the spatial flux estimation to the application of the T-proxy method, whose highly uncertain results mainly provide coarse spatial flux estimates. The study concludes that the upscaling of groundwater-stream water interactions using thermal measurements with combined point and distributed techniques requires the integration of physical drivers because of the heterogeneity of the flux patterns. Combined experimental and modeling approaches may help to obtain more reliable understanding of groundwater-surface water interactions at multiple scales.

Neuromagnetic Evidence of Spatially Distributed Sources Underlying Epileptiform Spikes in the Human Brain

NASA Astrophysics Data System (ADS)

Barth, Daniel S.; Sutherling, William; Engle, Jerome; Beatty, Jackson

1984-01-01

Neuromagnetic measurements were performed on 17 subjects with focal seizure disorders. In all of the subjects, the interictal spike in the scalp electroencephalogram was associated with an orderly extracranial magnetic field pattern. In eight of these subjects, multiple current sources underlay the magnetic spike complex. The multiple sources within a given subject displayed a fixed chronological sequence of discharge, demonstrating a high degree of spatial and temporal organization within the interictal focus.

Urban Public Space Context and Cognitive Psychology Evolution in Information Environment

NASA Astrophysics Data System (ADS)

Feng, Chen; Xu, Hua-wei

2017-11-01

The rapid development of information technology has had a great impact on the understanding of urban environment, which brings different spatially psychological experience. Information and image transmission has been full with the streets, both the physical space and virtual space have been unprecedentedly blended together through pictures, images, electronic media and other tools, which also stimulates people’s vision and psychology and gives birth to a more complex form of urban space. Under the dual role of spatial mediumlization and media spatialization, the psychological cognitive pattern of urban public space context is changing.

Modelling dendritic ecological networks in space: anintegrated network perspective

USGS Publications Warehouse

Peterson, Erin E.; Ver Hoef, Jay M.; Isaak, Dan J.; Falke, Jeffrey A.; Fortin, Marie-Josée; Jordon, Chris E.; McNyset, Kristina; Monestiez, Pascal; Ruesch, Aaron S.; Sengupta, Aritra; Som, Nicholas; Steel, E. Ashley; Theobald, David M.; Torgersen, Christian E.; Wenger, Seth J.

2013-01-01

the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2-D space can be used to explore the influence of multi-scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).

Point pattern analysis applied to flood and landslide damage events in Switzerland (1972-2009)

NASA Astrophysics Data System (ADS)

Barbería, Laura; Schulte, Lothar; Carvalho, Filipe; Peña, Juan Carlos

2017-04-01

Damage caused by meteorological and hydrological extreme events depends on many factors, not only on hazard, but also on exposure and vulnerability. In order to reach a better understanding of the relation of these complex factors, their spatial pattern and underlying processes, the spatial dependency between values of damage recorded at sites of different distances can be investigated by point pattern analysis. For the Swiss flood and landslide damage database (1972-2009) first steps of point pattern analysis have been carried out. The most severe events have been selected (severe, very severe and catastrophic, according to GEES classification, a total number of 784 damage points) and Ripley's K-test and L-test have been performed, amongst others. For this purpose, R's library spatstat has been used. The results confirm that the damage points present a statistically significant clustered pattern, which could be connected to prevalence of damages near watercourses and also to rainfall distribution of each event, together with other factors. On the other hand, bivariate analysis shows there is no segregated pattern depending on process type: flood/debris flow vs landslide. This close relation points to a coupling between slope and fluvial processes, connectivity between small-size and middle-size catchments and the influence of spatial distribution of precipitation, temperature (snow melt and snow line) and other predisposing factors such as soil moisture, land-cover and environmental conditions. Therefore, further studies will investigate the relationship between the spatial pattern and one or more covariates, such as elevation, distance from watercourse or land use. The final goal will be to perform a regression model to the data, so that the adjusted model predicts the intensity of the point process as a function of the above mentioned covariates.

Deconstructing Visual Scenes in Cortex: Gradients of Object and Spatial Layout Information

PubMed Central

Kravitz, Dwight J.; Baker, Chris I.

2013-01-01

Real-world visual scenes are complex cluttered, and heterogeneous stimuli engaging scene- and object-selective cortical regions including parahippocampal place area (PPA), retrosplenial complex (RSC), and lateral occipital complex (LOC). To understand the unique contribution of each region to distributed scene representations, we generated predictions based on a neuroanatomical framework adapted from monkey and tested them using minimal scenes in which we independently manipulated both spatial layout (open, closed, and gradient) and object content (furniture, e.g., bed, dresser). Commensurate with its strong connectivity with posterior parietal cortex, RSC evidenced strong spatial layout information but no object information, and its response was not even modulated by object presence. In contrast, LOC, which lies within the ventral visual pathway, contained strong object information but no background information. Finally, PPA, which is connected with both the dorsal and the ventral visual pathway, showed information about both objects and spatial backgrounds and was sensitive to the presence or absence of either. These results suggest that 1) LOC, PPA, and RSC have distinct representations, emphasizing different aspects of scenes, 2) the specific representations in each region are predictable from their patterns of connectivity, and 3) PPA combines both spatial layout and object information as predicted by connectivity. PMID:22473894

Pattern formation--A missing link in the study of ecosystem response to environmental changes.

PubMed

Meron, Ehud

2016-01-01

Environmental changes can affect the functioning of an ecosystem directly, through the response of individual life forms, or indirectly, through interspecific interactions and community dynamics. The feasibility of a community-level response has motivated numerous studies aimed at understanding the mutual relationships between three elements of ecosystem dynamics: the abiotic environment, biodiversity and ecosystem function. Since ecosystems are inherently nonlinear and spatially extended, environmental changes can also induce pattern-forming instabilities that result in spatial self-organization of life forms and resources. This, in turn, can affect the relationships between these three elements, and make the response of ecosystems to environmental changes far more complex. Responses of this kind can be expected in dryland ecosystems, which show a variety of self-organizing vegetation patterns along the rainfall gradient. This paper describes the progress that has been made in understanding vegetation patterning in dryland ecosystems, and the roles it plays in ecosystem response to environmental variability. The progress has been achieved by modeling pattern-forming feedbacks at small spatial scales and up-scaling their effects to large scales through model studies. This approach sets the basis for integrating pattern formation theory into the study of ecosystem dynamics and addressing ecologically significant questions such as the dynamics of desertification, restoration of degraded landscapes, biodiversity changes along environmental gradients, and shrubland-grassland transitions. Copyright © 2015 Elsevier Inc. All rights reserved.

Range expansion through fragmented landscapes under a variable climate

PubMed Central

Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J

2013-01-01

Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124

Development of the Neurochemical Architecture of the Central Complex

PubMed Central

Boyan, George S.; Liu, Yu

2016-01-01

The central complex represents one of the most conspicuous neuroarchitectures to be found in the insect brain and regulates a wide repertoire of behaviors including locomotion, stridulation, spatial orientation and spatial memory. In this review article, we show that in the grasshopper, a model insect system, the intricate wiring of the fan-shaped body (FB) begins early in embryogenesis when axons from the first progeny of four protocerebral stem cells (called W, X, Y, Z, respectively) in each brain hemisphere establish a set of tracts to the primary commissural system. Decussation of subsets of commissural neurons at stereotypic locations across the brain midline then establishes a columnar neuroarchitecture in the FB which is completed during embryogenesis. Examination of the expression patterns of various neurochemicals in the central complex including neuropeptides, a neurotransmitter and the gas nitric oxide (NO), show that these appear progressively and in a substance-specific manner during embryogenesis. Each neuroactive substance is expressed by neurons located at stereotypic locations in a given central complex lineage, confirming that the stem cells are biochemically multipotent. The organization of axons expressing the various neurochemicals within the central complex is topologically related to the location, and hence birthdate, of the neurons within the lineages. The neurochemical expression patterns within the FB are layered, and so reflect the temporal topology present in the lineages. This principle relates the neuroanatomical to the neurochemical architecture of the central complex and so may provide insights into the development of adaptive behaviors. PMID:27630548

EMAP and EMAGE: a framework for understanding spatially organized data.

PubMed

Baldock, Richard A; Bard, Jonathan B L; Burger, Albert; Burton, Nicolas; Christiansen, Jeff; Feng, Guanjie; Hill, Bill; Houghton, Derek; Kaufman, Matthew; Rao, Jianguo; Sharpe, James; Ross, Allyson; Stevenson, Peter; Venkataraman, Shanmugasundaram; Waterhouse, Andrew; Yang, Yiya; Davidson, Duncan R

2003-01-01

The Edinburgh MouseAtlas Project (EMAP) is a time-series of mouse-embryo volumetric models. The models provide a context-free spatial framework onto which structural interpretations and experimental data can be mapped. This enables collation, comparison, and query of complex spatial patterns with respect to each other and with respect to known or hypothesized structure. The atlas also includes a time-dependent anatomical ontology and mapping between the ontology and the spatial models in the form of delineated anatomical regions or tissues. The models provide a natural, graphical context for browsing and visualizing complex data. The Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) is one of the first applications of the EMAP framework and provides a spatially mapped gene-expression database with associated tools for data mapping, submission, and query. In this article, we describe the underlying principles of the Atlas and the gene-expression database, and provide a practical introduction to the use of the EMAP and EMAGE tools, including use of new techniques for whole body gene-expression data capture and mapping.

Spatial Patterns of Forest Cover Loss in the Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

Molinario, G.; Hansen, M.; Potapov, P.; Justice, C. O.

2013-12-01

Three groups of metrics of spatial patterns of forest cover loss were calculated for the Democratic Republic of Congo (DRC). While other studies had previously assessed landscape patterns in the Congo Basin, they had done so for small areas due to data limitations. The input data for this study, the Forets d;Afrique Central Evaluee par Teledetection(FACET), allowed the analysis to be performed at the national level. FACET is a landsat-scale dataset giving an unprecedented synoptic view of forest cover and forest cover loss for the DRC for three time periods: 2000, 2005 and 2010. The three groups of metrics evaluated the following spatial characteristics of forest cover loss for the same standard 1.5km unit of area: proportions of typologies of forest lost, forest fragmentation and proximity of forest loss patches from other land cover types. Results indicate that there are several different typologies of forest cover loss in the DRC, and offer quantitative explanations of these differences, providing a valuable locally-relevant tool for land use planning, available at the national level. Spatial patterns of forest cover loss highlight differences between areas of high primary forest loss due to agriculture conversion in frontier deforestation, such as in the east of the country, areas of equivalent primary and secondary forest loss emanating from the rural complex and areas of variable proportions of primary and secondary forest loss but important ecological repercussions of forest fragmentation due to isolated, but systematic forest perforations. Typologies of spatial patterns of forest cover loss are presented as well as their correlated drivers, and ecological, conservation and land use planning considerations are discussed.

An evaluation of space time cube representation of spatiotemporal patterns.

PubMed

Kristensson, Per Ola; Dahlbäck, Nils; Anundi, Daniel; Björnstad, Marius; Gillberg, Hanna; Haraldsson, Jonas; Mårtensson, Ingrid; Nordvall, Mathias; Ståhl, Josefine

2009-01-01

Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns.

American chestnut persistence in southwestern Virginia 80 years after chestnut blight introduction

Treesearch

Katie L. Burke

2010-01-01

Forest disease noticeably alters spatial patterns of a species' distribution and this alteration is complex when host mortality is affected by site qualities. In the 1930s, chestnut blight (Cryphonectria parasitica) spread through southwestern Virginia, after its introduction to New York in 1904.

A platform for the advanced spatial and temporal control of biomolecules

NASA Astrophysics Data System (ADS)

Hook, Andrew L.; Thissen, Helmut; Hayes, Jason P.; Voelcker, Nicolas H.

2007-01-01

Manipulating biomolecules at solid/liquid interfaces is important for the development of various biodevices including microarrays. Smart materials that enable both spatial and temporal control of biomolecules by combining switchability with patterned surface chemistry offer unprecedented levels of control of biomolecule manipulation. Such a system has been developed for the microscale spatial control over both DNA and cell growth on highly doped p-type silicon. Surface modification, involving plasma polymerisation of allylamine and poly(ethlylene glycol) grafting with subsequent laser ablation, led to the production of a patterned surface with dual biomolecule adsorption and desorption properties. On patterned surfaces, preferential electro-stimulated adsorption of DNA to the allylamine plasma polymer surface and subsequent desorption by the application of a negative bias was observed. The ability of this surface to control both DNA and cell attachment in four dimensions has been demonstrated, exemplifying its capacity to be used for complex biological studies such as gene function analysis. This system has been successfully applied to living microarray applications and is an exciting platform for any system incorporating biomolecules.

Dentate network activity is necessary for spatial working memory by supporting CA3 sharp-wave ripple generation and prospective firing of CA3 neurons.

PubMed

Sasaki, Takuya; Piatti, Verónica C; Hwaun, Ernie; Ahmadi, Siavash; Lisman, John E; Leutgeb, Stefan; Leutgeb, Jill K

2018-02-01

Complex spatial working memory tasks have been shown to require both hippocampal sharp-wave ripple (SWR) activity and dentate gyrus (DG) neuronal activity. We therefore asked whether DG inputs to CA3 contribute to spatial working memory by promoting SWR generation. Recordings from DG and CA3 while rats performed a dentate-dependent working memory task on an eight-arm radial maze revealed that the activity of dentate neurons and the incidence rate of SWRs both increased during reward consumption. We then found reduced reward-related CA3 SWR generation without direct input from dentate granule neurons. Furthermore, CA3 cells with place fields in not-yet-visited arms preferentially fired during SWRs at reward locations, and these prospective CA3 firing patterns were more pronounced for correct trials and were dentate-dependent. These results indicate that coordination of CA3 neuronal activity patterns by DG is necessary for the generation of neuronal firing patterns that support goal-directed behavior and memory.

Investigating Geosparql Requirements for Participatory Urban Planning

NASA Astrophysics Data System (ADS)

Mohammadi, E.; Hunter, A. J. S.

2015-06-01

We propose that participatory GIS (PGIS) activities including participatory urban planning can be made more efficient and effective if spatial reasoning rules are integrated with PGIS tools to simplify engagement for public contributors. Spatial reasoning is used to describe relationships between spatial entities. These relationships can be evaluated quantitatively or qualitatively using geometrical algorithms, ontological relations, and topological methods. Semantic web services utilize tools and methods that can facilitate spatial reasoning. GeoSPARQL, introduced by OGC, is a spatial reasoning standard used to make declarations about entities (graphical contributions) that take the form of a subject-predicate-object triple or statement. GeoSPARQL uses three basic methods to infer topological relationships between spatial entities, including: OGC's simple feature topology, RCC8, and the DE-9IM model. While these methods are comprehensive in their ability to define topological relationships between spatial entities, they are often inadequate for defining complex relationships that exist in the spatial realm. Particularly relationships between urban entities, such as those between a bus route, the collection of associated bus stops and their overall surroundings as an urban planning pattern. In this paper we investigate common qualitative spatial reasoning methods as a preliminary step to enhancing the capabilities of GeoSPARQL in an online participatory GIS framework in which reasoning is used to validate plans based on standard patterns that can be found in an efficient/effective urban environment.

Electrical Programming of Soft Matter: Using Temporally Varying Electrical Inputs To Spatially Control Self Assembly.

PubMed

Yan, Kun; Liu, Yi; Zhang, Jitao; Correa, Santiago O; Shang, Wu; Tsai, Cheng-Chieh; Bentley, William E; Shen, Jana; Scarcelli, Giuliano; Raub, Christopher B; Shi, Xiao-Wen; Payne, Gregory F

2018-02-12

The growing importance of hydrogels in translational medicine has stimulated the development of top-down fabrication methods, yet often these methods lack the capabilities to generate the complex matrix architectures observed in biology. Here we show that temporally varying electrical signals can cue a self-assembling polysaccharide to controllably form a hydrogel with complex internal patterns. Evidence from theory and experiment indicate that internal structure emerges through a subtle interplay between the electrical current that triggers self-assembly and the electrical potential (or electric field) that recruits and appears to orient the polysaccharide chains at the growing gel front. These studies demonstrate that short sequences (minutes) of low-power (∼1 V) electrical inputs can provide the program to guide self-assembly that yields hydrogels with stable, complex, and spatially varying structure and properties.

Outputs of paired Gabor filters summed across the background frame of reference predict the direction of movement

NASA Technical Reports Server (NTRS)

Lawton, Teri B.

1989-01-01

A cortical neural network that computes the visibility of shifts in the direction of movement is proposed. The network computes: (1) the magnitude of the position difference between the test and background patterns, (2) localized contrast differences at different spatial scales analyzed by computing temporal gradients of the difference and sum of the outputs of paired even- and odd-symmetric bandpass filters convolved with the input pattern, and (3) using global processes that pool the output from paired even- and odd-symmetric simple and complex cells across the spatial extent of the background frame of reference the direction a test pattern moved relative to a textured background. Evidence that magnocellular pathways are used to discriminate the direction of movement is presented. Since magnocellular pathways are used to discriminate the direction of movement, this task is not affected by small pattern changes such as jitter, short presentations, blurring, and different background contrasts that result when the veiling illumination in a scene changes.

Ecosystem properties self-organize in response to a directional fog-vegetation interaction.

PubMed

Stanton, Daniel E; Armesto, Juan J; Hedin, Lars O

2014-05-01

Feedbacks between vegetation and resource inputs can lead to the local, self-organization of ecosystem properties. In particular, feedbacks in response to directional resources (e.g., coastal fog, slope runoff) can create complex spatial patterns, such as vegetation banding. Although similar feedbacks are thought to be involved in the development of ecosystems, clear empirical examples are rare. We created a simple model of a fog-influenced, temperate rainforest in central Chile, which allows the comparison of natural banding patterns to simulations of various putative mechanisms. We show that only feedbacks between plants and fog were able to replicate the characteristic distributions of vegetation, soil water, and soil nutrients observed in field transects. Other processes, such as rainfall, were unable to match these diagnostic distributions. Furthermore, fog interception by windward trees leads to increased downwind mortality, leading to progressive extinction of the leeward edge. This pattern of ecosystem development and decay through self-organized processes illustrates, on a relatively small spatial and temporal scale, the patterns predicted for ecosystem evolution.

Spatial patterning in PM2.5 constituents under an inversion-focused sampling design across an urban area of complex terrain

PubMed Central

Tunno, Brett J; Dalton, Rebecca; Michanowicz, Drew R; Shmool, Jessie L C; Kinnee, Ellen; Tripathy, Sheila; Cambal, Leah; Clougherty, Jane E

2016-01-01

Health effects of fine particulate matter (PM2.5) vary by chemical composition, and composition can help to identify key PM2.5 sources across urban areas. Further, this intra-urban spatial variation in concentrations and composition may vary with meteorological conditions (e.g., mixing height). Accordingly, we hypothesized that spatial sampling during atmospheric inversions would help to better identify localized source effects, and reveal more distinct spatial patterns in key constituents. We designed a 2-year monitoring campaign to capture fine-scale intra-urban variability in PM2.5 composition across Pittsburgh, PA, and compared both spatial patterns and source effects during “frequent inversion” hours vs 24-h weeklong averages. Using spatially distributed programmable monitors, and a geographic information systems (GIS)-based design, we collected PM2.5 samples across 37 sampling locations per year to capture variation in local pollution sources (e.g., proximity to industry, traffic density) and terrain (e.g., elevation). We used inductively coupled plasma mass spectrometry (ICP-MS) to determine elemental composition, and unconstrained factor analysis to identify source suites by sampling scheme and season. We examined spatial patterning in source factors using land use regression (LUR), wherein GIS-based source indicators served to corroborate factor interpretations. Under both summer sampling regimes, and for winter inversion-focused sampling, we identified six source factors, characterized by tracers associated with brake and tire wear, steel-making, soil and road dust, coal, diesel exhaust, and vehicular emissions. For winter 24-h samples, four factors suggested traffic/fuel oil, traffic emissions, coal/industry, and steel-making sources. In LURs, as hypothesized, GIS-based source terms better explained spatial variability in inversion-focused samples, including a greater contribution from roadway, steel, and coal-related sources. Factor analysis produced source-related constituent suites under both sampling designs, though factors were more distinct under inversion-focused sampling. PMID:26507005

Non-Covalent Photo-Patterning of Gelatin Matrices Using Caged Collagen Mimetic Peptides

PubMed Central

Li, Yang; Hoa San, Boi; L. Kessler, Julian; Hwan Kim, Jin; Xu, Qingguo; Hanes, Justin; Yu, Seungju Michael

2015-01-01

Advancements in photolithography have enabled us to spatially encode biochemical cues in biocompatible platforms such as synthetic hydrogels. Conventional patterning works through photo-activated chemical reactions on inert polymer networks. However, these techniques cannot be directly applied to protein hydrogels without chemically altering the protein scaffolds. To this end, we developed a non-covalent photo-patterning strategy for gelatin (denatured collagen) hydrogels utilizing a caged collagen mimetic peptide (caged CMP) which binds to gelatin strands through UV activated, triple helix hybridization. Here we present 2D and 3D photo-patterning of gelatin hydrogels enabled by the caged CMPs as well as creation of concentration gradients of CMPs. We show that photo-patterning of PEG-conjugated caged CMPs can be used to spatially control cell adhesion on gelatin films. CMP’s specificity for binding to gelatin allows patterning of almost any synthetic or natural gelatin-containing matrix, such as zymograms, gelatin-methacrylate hydrogels, and even a corneal tissue. Since the CMP is a chemically and biologically inert peptide which is proven to be an ideal carrier for bioactive molecules, our patterning method provides a radically new tool for immobilizing drugs to natural tissues and for functionalizing scaffolds for complex tissue formation. PMID:25476588

Predictive computation of genomic logic processing functions in embryonic development

PubMed Central

Peter, Isabelle S.; Faure, Emmanuel; Davidson, Eric H.

2012-01-01

Gene regulatory networks (GRNs) control the dynamic spatial patterns of regulatory gene expression in development. Thus, in principle, GRN models may provide system-level, causal explanations of developmental process. To test this assertion, we have transformed a relatively well-established GRN model into a predictive, dynamic Boolean computational model. This Boolean model computes spatial and temporal gene expression according to the regulatory logic and gene interactions specified in a GRN model for embryonic development in the sea urchin. Additional information input into the model included the progressive embryonic geometry and gene expression kinetics. The resulting model predicted gene expression patterns for a large number of individual regulatory genes each hour up to gastrulation (30 h) in four different spatial domains of the embryo. Direct comparison with experimental observations showed that the model predictively computed these patterns with remarkable spatial and temporal accuracy. In addition, we used this model to carry out in silico perturbations of regulatory functions and of embryonic spatial organization. The model computationally reproduced the altered developmental functions observed experimentally. Two major conclusions are that the starting GRN model contains sufficiently complete regulatory information to permit explanation of a complex developmental process of gene expression solely in terms of genomic regulatory code, and that the Boolean model provides a tool with which to test in silico regulatory circuitry and developmental perturbations. PMID:22927416

Digital Speckle Photography of Subpixel Displacements of Speckle Structures Based on Analysis of Their Spatial Spectra

NASA Astrophysics Data System (ADS)

Maksimova, L. A.; Ryabukho, P. V.; Mysina, N. Yu.; Lyakin, D. V.; Ryabukho, V. P.

2018-04-01

We have investigated the capabilities of the method of digital speckle interferometry for determining subpixel displacements of a speckle structure formed by a displaceable or deformable object with a scattering surface. An analysis of spatial spectra of speckle structures makes it possible to perform measurements with a subpixel accuracy and to extend the lower boundary of the range of measurements of displacements of speckle structures to the range of subpixel values. The method is realized on the basis of digital recording of the images of undisplaced and displaced speckle structures, their spatial frequency analysis using numerically specified constant phase shifts, and correlation analysis of spatial spectra of speckle structures. Transformation into the frequency range makes it possible to obtain quantities to be measured with a subpixel accuracy from the shift of the interference-pattern minimum in the diffraction halo by introducing an additional phase shift into the complex spatial spectrum of the speckle structure or from the slope of the linear plot of the function of accumulated phase difference in the field of the complex spatial spectrum of the displaced speckle structure. The capabilities of the method have been investigated in natural experiment.

Visual Information Processing Based on Spatial Filters Constrained by Biological Data.

DTIC Science & Technology

1978-12-01

was provided by Pantie and Sekuler ( 19681. They found that the detection (if gratings was affected most by adapting isee Section 6.1. 11 to square...evidence for certain eye scans being directed by spatial information in filtered images is given. Eye scan paths of a portrait of a young girl I Figure 08...multistable objects to more complex objects such as the man- girl figure of Fisher 119681, decision boundaries that are a natural concomitant to any pattern

Simple models for studying complex spatiotemporal patterns of animal behavior

NASA Astrophysics Data System (ADS)

Tyutyunov, Yuri V.; Titova, Lyudmila I.

2017-06-01

Minimal mathematical models able to explain complex patterns of animal behavior are essential parts of simulation systems describing large-scale spatiotemporal dynamics of trophic communities, particularly those with wide-ranging species, such as occur in pelagic environments. We present results obtained with three different modelling approaches: (i) an individual-based model of animal spatial behavior; (ii) a continuous taxis-diffusion-reaction system of partial-difference equations; (iii) a 'hybrid' approach combining the individual-based algorithm of organism movements with explicit description of decay and diffusion of the movement stimuli. Though the models are based on extremely simple rules, they all allow description of spatial movements of animals in a predator-prey system within a closed habitat, reproducing some typical patterns of the pursuit-evasion behavior observed in natural populations. In all three models, at each spatial position the animal movements are determined by local conditions only, so the pattern of collective behavior emerges due to self-organization. The movement velocities of animals are proportional to the density gradients of specific cues emitted by individuals of the antagonistic species (pheromones, exometabolites or mechanical waves of the media, e.g., sound). These cues play a role of taxis stimuli: prey attract predators, while predators repel prey. Depending on the nature and the properties of the movement stimulus we propose using either a simplified individual-based model, a continuous taxis pursuit-evasion system, or a little more detailed 'hybrid' approach that combines simulation of the individual movements with the continuous model describing diffusion and decay of the stimuli in an explicit way. These can be used to improve movement models for many species, including large marine predators.

Module Based Complexity Formation: Periodic Patterning in Feathers and Hairs

PubMed Central

Chuong, Cheng-Ming; Yeh, Chao-Yuan; Jiang, Ting-Xin; Widelitz, Randall

2012-01-01

Patterns describe order which emerges from homogeneity. Complex patterns on the integument are striking because of their visibility throughout an organism's lifespan. Periodic patterning is an effective design because the ensemble of hair or feather follicles (modules) allows the generation of complexity, including regional variations and cyclic regeneration, giving the skin appendages a new lease on life. Spatial patterns include the arrangements of feathers and hairs in specified number, size, and spacing. We explore how a field of equivalent progenitor cells can generate periodically arranged modules based on genetic information, physical-chemical rules and developmental timing. Reconstitution experiments suggest a competitive equilibrium regulated by activators / inhibitors involving Turing reaction-diffusion. Temporal patterns result from oscillating stem cell activities within each module (micro-environment regulation), reflected as growth (anagen) and resting (telogen) phases during the cycling of feather and hair follicles. Stimulating modules with activators initiates the spread of regenerative hair waves, while global inhibitors outside each module (macro-environment) prevent this. Different wave patterns can be simulated by Cellular Automata principles. Hormonal status and seasonal changes can modulate appendage phenotypes, leading to “organ metamorphosis”, with multiple ectodermal organ phenotypes generated from the same precursors. We discuss potential evolutionary novel steps using this module based complexity in several amniote integument organs, exemplified by the spectacular peacock feather pattern. We thus explore the application of the acquired knowledge of patterning in tissue engineering. New hair follicles can be generated after wounding. Hairs and feathers can be reconstituted through self-organization of dissociated progenitor cells. PMID:23539312

Module-based complexity formation: periodic patterning in feathers and hairs.

PubMed

Chuong, Cheng-Ming; Yeh, Chao-Yuan; Jiang, Ting-Xin; Widelitz, Randall

2013-01-01

Patterns describe order which emerges from homogeneity. Complex patterns on the integument are striking because of their visibility throughout an organism’s lifespan. Periodic patterning is an effective design because the ensemble of hair or feather follicles (modules) allows the generation of complexity, including regional variations and cyclic regeneration, giving the skin appendages a new lease on life. Spatial patterns include the arrangements of feathers and hairs in specific number, size, and spacing.We explorehowa field of equivalent progenitor cells can generate periodically arranged modules based on genetic information, physical–chemical rules and developmental timing. Reconstitution experiments suggest a competitive equilibrium regulated by activators/inhibitors involving Turing reaction-diffusion. Temporal patterns result from oscillating stem cell activities within each module (microenvironment regulation), reflected as growth (anagen) and resting (telogen) phases during the cycling of feather and hair follicles. Stimulating modules with activators initiates the spread of regenerative hair waves, while global inhibitors outside each module (macroenvironment) prevent this. Different wave patterns can be simulated by cellular automata principles. Hormonal status and seasonal changes can modulate appendage phenotypes, leading to ‘organ metamorphosis’, with multiple ectodermal organ phenotypes generated from the same precursors. We discuss potential novel evolutionary steps using this module-based complexity in several amniote integument organs, exemplified by the spectacular peacock feather pattern. We thus explore the application of the acquired knowledge of patterning in tissue engineering. New hair follicles can be generated after wounding. Hairs and feathers can be reconstituted through self-organization of dissociated progenitor cells. © 2012 Wiley Periodicals, Inc.

Complex Dynamics of Wetland Ecosystem with Nonlinear Harvesting: Application to Chilika Lake in Odisha, India

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Tiwari, S. K.; Roy, Parimita

2015-06-01

In this paper, an attempt has been made to study the spatial and temporal dynamical interactions among the species of wetland ecosystem through a mathematical model. The model represents the population dynamics of phytoplankton, zooplankton and fish species found in Chilika lake, Odisha, India. Nonlinear stability analysis of both the temporal and spatial models has been carried out. Maximum sustainable yield and optimal harvesting policy have been studied for a nonspatial model system. Numerical simulation has been performed to figure out the parameters responsible for the complex dynamics of the wetland system. Significant outcomes of our numerical findings and their interpretations from an ecological point of view are provided in this paper. Numerical simulation of spatial model exhibits some interesting and beautiful patterns. We have also pointed out the parameters that are responsible for the good health of wetland ecosystem.

Neural Representation of Spatial Topology in the Rodent Hippocampus

PubMed Central

Chen, Zhe; Gomperts, Stephen N.; Yamamoto, Jun; Wilson, Matthew A.

2014-01-01

Pyramidal cells in the rodent hippocampus often exhibit clear spatial tuning in navigation. Although it has been long suggested that pyramidal cell activity may underlie a topological code rather than a topographic code, it remains unclear whether an abstract spatial topology can be encoded in the ensemble spiking activity of hippocampal place cells. Using a statistical approach developed previously, we investigate this question and related issues in greater details. We recorded ensembles of hippocampal neurons as rodents freely foraged in one and two-dimensional spatial environments, and we used a “decode-to-uncover” strategy to examine the temporally structured patterns embedded in the ensemble spiking activity in the absence of observed spatial correlates during periods of rodent navigation or awake immobility. Specifically, the spatial environment was represented by a finite discrete state space. Trajectories across spatial locations (“states”) were associated with consistent hippocampal ensemble spiking patterns, which were characterized by a state transition matrix. From this state transition matrix, we inferred a topology graph that defined the connectivity in the state space. In both one and two-dimensional environments, the extracted behavior patterns from the rodent hippocampal population codes were compared against randomly shuffled spike data. In contrast to a topographic code, our results support the efficiency of topological coding in the presence of sparse sample size and fuzzy space mapping. This computational approach allows us to quantify the variability of ensemble spiking activity, to examine hippocampal population codes during off-line states, and to quantify the topological complexity of the environment. PMID:24102128

Task-level feedback can explain temporal recruitment of spatially fixed muscle synergies throughout postural perturbations

PubMed Central

Safavynia, Seyed A.

2012-01-01

Recent evidence suggests that complex spatiotemporal patterns of muscle activity can be explained with a low-dimensional set of muscle synergies or M-modes. While it is clear that both spatial and temporal aspects of muscle coordination may be low dimensional, constraints on spatial versus temporal features of muscle coordination likely involve different neural control mechanisms. We hypothesized that the low-dimensional spatial and temporal features of muscle coordination are independent of each other. We further hypothesized that in reactive feedback tasks, spatially fixed muscle coordination patterns—or muscle synergies—are hierarchically recruited via time-varying neural commands based on delayed task-level feedback. We explicitly compared the ability of spatially fixed (SF) versus temporally fixed (TF) muscle synergies to reconstruct the entire time course of muscle activity during postural responses to anterior-posterior support-surface translations. While both SF and TF muscle synergies could account for EMG variability in a postural task, SF muscle synergies produced more consistent and physiologically interpretable results than TF muscle synergies during postural responses to perturbations. Moreover, a majority of SF muscle synergies were consistent in structure when extracted from epochs throughout postural responses. Temporal patterns of SF muscle synergy recruitment were well-reconstructed by delayed feedback of center of mass (CoM) kinematics and reproduced EMG activity of multiple muscles. Consistent with the idea that independent and hierarchical low-dimensional neural control structures define spatial and temporal patterns of muscle activity, our results suggest that CoM kinematics are a task variable used to recruit SF muscle synergies for feedback control of balance. PMID:21957219

Distribution, abundance, and diversity of stream fishes under variable environmental conditions

Treesearch

Christopher M. Taylor; Thomas L. Holder; Richard A. Fiorillo; Lance R. Williams; R. Brent Thomas; Melvin L. Warren

2006-01-01

The effects of stream size and flow regime on spatial and temporal variability of stream fish distribution, abundance, and diversity patterns were investigated. Assemblage variability and species richness were each significantly associated with a complex environmental gradient contrasting smaller, hydrologically variable stream localities with larger localities...

Research and Studies Directory for Manpower, Personnel, and Training

DTIC Science & Technology

1989-05-01

LOUIS MO 314-889-6805 CONTROL OF BIOSONAR BEHAVIOR BY THE AUDITORY CORTEX TANGNEY J AIR FORCE OFFICE OF SCIENTIFIC RESEARCH 202-767-5021 A MODEL FOR...VISUAL ATTENTION AUDITORY PERCEPTION OF COMPLEX SOUNDS CONTROL OF BIOSONAR BEHAVIOR BY THE AUDITORY CORTEX EYE MOVEMENTS AND SPATIAL PATTERN VISION EYE

Evolution of Patterns in Rotating Bénard Convection

NASA Astrophysics Data System (ADS)

Fantz, M.; Friedrich, R.; Bestehorn, M.; Haken, H.

We present an extension of the Swift-Hohenberg equation to the case of a high Prandtl number Bénard experiment in rotating fluid containers. For the case of circular containers we find complex spatio-temporal behaviour at Taylor numbers smaller than the critical one for the onset of the Küppers-Lortz instability. Furthermore, above the critical Taylor number the experimentally well-known time dependent and spatially disordered patterns in form of local patches of rolls are reproduced.

Surface Acoustic Waves Grant Superior Spatial Control of Cells Embedded in Hydrogel Fibers.

PubMed

Lata, James P; Guo, Feng; Guo, Jinshan; Huang, Po-Hsun; Yang, Jian; Huang, Tony Jun

2016-10-01

By exploiting surface acoustic waves and a coupling layer technique, cells are patterned within a photosensitive hydrogel fiber to mimic physiological cell arrangement in tissues. The aligned cell-polymer matrix is polymerized with short exposure to UV light and the fiber is extracted. These patterned cell fibers are manipulated into simple and complex architectures, demonstrating feasibility for tissue-engineering applications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Divergent and nonuniform gene expression patterns in mouse brain

PubMed Central

Morris, John A.; Royall, Joshua J.; Bertagnolli, Darren; Boe, Andrew F.; Burnell, Josh J.; Byrnes, Emi J.; Copeland, Cathy; Desta, Tsega; Fischer, Shanna R.; Goldy, Jeff; Glattfelder, Katie J.; Kidney, Jolene M.; Lemon, Tracy; Orta, Geralyn J.; Parry, Sheana E.; Pathak, Sayan D.; Pearson, Owen C.; Reding, Melissa; Shapouri, Sheila; Smith, Kimberly A.; Soden, Chad; Solan, Beth M.; Weller, John; Takahashi, Joseph S.; Overly, Caroline C.; Lein, Ed S.; Hawrylycz, Michael J.; Hohmann, John G.; Jones, Allan R.

2010-01-01

Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs. PMID:20956311

Time takes space: selective effects of multitasking on concurrent spatial processing.

PubMed

Mäntylä, Timo; Coni, Valentina; Kubik, Veit; Todorov, Ivo; Del Missier, Fabio

2017-08-01

Many everyday activities require coordination and monitoring of complex relations of future goals and deadlines. Cognitive offloading may provide an efficient strategy for reducing control demands by representing future goals and deadlines as a pattern of spatial relations. We tested the hypothesis that multiple-task monitoring involves time-to-space transformational processes, and that these spatial effects are selective with greater demands on coordinate (metric) than categorical (nonmetric) spatial relation processing. Participants completed a multitasking session in which they monitored four series of deadlines, running on different time scales, while making concurrent coordinate or categorical spatial judgments. We expected and found that multitasking taxes concurrent coordinate, but not categorical, spatial processing. Furthermore, males showed a better multitasking performance than females. These findings provide novel experimental evidence for the hypothesis that efficient multitasking involves metric relational processing.

Network based approaches reveal clustering in protein point patterns

NASA Astrophysics Data System (ADS)

Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang

2014-03-01

Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.

Spatio-spectral color filter array design for optimal image recovery.

PubMed

Hirakawa, Keigo; Wolfe, Patrick J

2008-10-01

In digital imaging applications, data are typically obtained via a spatial subsampling procedure implemented as a color filter array-a physical construction whereby only a single color value is measured at each pixel location. Owing to the growing ubiquity of color imaging and display devices, much recent work has focused on the implications of such arrays for subsequent digital processing, including in particular the canonical demosaicking task of reconstructing a full color image from spatially subsampled and incomplete color data acquired under a particular choice of array pattern. In contrast to the majority of the demosaicking literature, we consider here the problem of color filter array design and its implications for spatial reconstruction quality. We pose this problem formally as one of simultaneously maximizing the spectral radii of luminance and chrominance channels subject to perfect reconstruction, and-after proving sub-optimality of a wide class of existing array patterns-provide a constructive method for its solution that yields robust, new panchromatic designs implementable as subtractive colors. Empirical evaluations on multiple color image test sets support our theoretical results, and indicate the potential of these patterns to increase spatial resolution for fixed sensor size, and to contribute to improved reconstruction fidelity as well as significantly reduced hardware complexity.

[Spatial scale effect of urban land use landscape pattern in Shanghai City].

PubMed

Xu, Li-Hua; Yue, Wen Ze; Cao, Yu

2007-12-01

Based on geographic information system (GIS) and remote sensing (RS) techniques, the landscape classes of urban land use in Shanghai City were extracted from SPOT images with 5 m spatial resolution in 2002, and then, the classified data were applied to quantitatively explore the change patterns of several basic landscape metrics at different scales. The results indicated that landscape metrics were sensitive to grain- and extent variance. Urban landscape pattern was spatially dependent. In other words, different landscape metrics showed different responses to scale. The resolution of 40 m was an intrinsic observing scale for urban landscape in Shanghai City since landscape metrics showed random characteristics while the grain was less than 40 m. The extent of 24 km was a symbol scale in a series of extents, which was consistent with the boundary between urban built-up area and suburban area in Shanghai City. As a result, the extent of 12 km away from urban center would be an intrinsic handle scale for urban landscape in Shanghai City. However, due to the complexity of urban structure and asymmetry of urban spatial expansion, the intrinsic handle scale was not regular extent, and the square with size of 24 km was just an approximate intrinsic extent for Shanghai City.

Geostatistics for spatial genetic structures: study of wild populations of perennial ryegrass.

PubMed

Monestiez, P; Goulard, M; Charmet, G

1994-04-01

Methods based on geostatistics were applied to quantitative traits of agricultural interest measured on a collection of 547 wild populations of perennial ryegrass in France. The mathematical background of these methods, which resembles spatial autocorrelation analysis, is briefly described. When a single variable is studied, the spatial structure analysis is similar to spatial autocorrelation analysis, and a spatial prediction method, called "kriging", gives a filtered map of the spatial pattern over all the sampled area. When complex interactions of agronomic traits with different evaluation sites define a multivariate structure for the spatial analysis, geostatistical methods allow the spatial variations to be broken down into two main spatial structures with ranges of 120 km and 300 km, respectively. The predicted maps that corresponded to each range were interpreted as a result of the isolation-by-distance model and as a consequence of selection by environmental factors. Practical collecting methodology for breeders may be derived from such spatial structures.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

Biological pattern formation: from basic mechanisms to complex structures

NASA Astrophysics Data System (ADS)

Koch, A. J.; Meinhardt, H.

1994-10-01

The reliable development of highly complex organisms is an intriguing and fascinating problem. The genetic material is, as a rule, the same in each cell of an organism. How then do cells, under the influence of their common genes, produce spatial patterns? Simple models are discussed that describe the generation of patterns out of an initially nearly homogeneous state. They are based on nonlinear interactions of at least two chemicals and on their diffusion. The concepts of local autocatalysis and of long-range inhibition play a fundamental role. Numerical simulations show that the models account for many basic biological observations such as the regeneration of a pattern after excision of tissue or the production of regular (or nearly regular) arrays of organs during (or after) completion of growth. Very complex patterns can be generated in a reproducible way by hierarchical coupling of several such elementary reactions. Applications to animal coats and to the generation of polygonally shaped patterns are provided. It is further shown how to generate a strictly periodic pattern of units that themselves exhibit a complex and polar fine structure. This is illustrated by two examples: the assembly of photoreceptor cells in the eye of Drosophila and the positioning of leaves and axillary buds in a growing shoot. In both cases, the substructures have to achieve an internal polarity under the influence of some primary pattern-forming system existing in the fly's eye or in the plant. The fact that similar models can describe essential steps in organisms as distantly related as animals and plants suggests that they reveal some universal mechanisms.

Environmental Complexity and Biodiversity: The Multi-Layered Evolutionary History of a Log-Dwelling Velvet Worm in Montane Temperate Australia

PubMed Central

Garrick, Ryan C.; Gardner, Michael G.; Tait, Noel N.; Briscoe, David A.; Rowell, David M.; Sunnucks, Paul

2013-01-01

Phylogeographic studies provide a framework for understanding the importance of intrinsic versus extrinsic factors in shaping patterns of biodiversity through identifying past and present microevolutionary processes that contributed to lineage divergence. Here we investigate population structure and diversity of the Onychophoran (velvet worm) Euperipatoides rowelli in southeastern Australian montane forests that were not subject to Pleistocene glaciations, and thus likely retained more forest cover than systems under glaciation. Over a ~100 km transect of structurally-connected forest, we found marked nuclear and mitochondrial (mt) DNA genetic structuring, with spatially-localised groups. Patterns from mtDNA and nuclear data broadly corresponded with previously defined geographic regions, consistent with repeated isolation in refuges during Pleistocene climatic cycling. Nevertheless, some E. rowelli genetic contact zones were displaced relative to hypothesized influential landscape structures, implying more recent processes overlying impacts of past environmental history. Major impacts at different timescales were seen in the phylogenetic relationships among mtDNA sequences, which matched geographic relationships and nuclear data only at recent timescales, indicating historical gene flow and/or incomplete lineage sorting. Five major E. rowelli phylogeographic groups were identified, showing substantial but incomplete reproductive isolation despite continuous habitat. Regional distinctiveness, in the face of lineages abutting within forest habitat, could indicate pre- and/or postzygotic gene flow limitation. A potentially functional phenotypic character, colour pattern variation, reflected the geographic patterns in the molecular data. Spatial-genetic patterns broadly match those in previously-studied, co-occurring low-mobility organisms, despite a variety of life histories. We suggest that for E. rowelli, the complex topography and history of the region has led to interplay among limited dispersal ability, historical responses to environmental change, local adaptation, and some resistance to free admixture at geographic secondary contact, leading to strong genetic structuring at fine spatial scale. PMID:24358365

Spatial and temporal variation at major histocompatibility complex class IIB genes in the endangered Blakiston's fish owl.

PubMed

Kohyama, Tetsuo I; Omote, Keita; Nishida, Chizuko; Takenaka, Takeshi; Saito, Keisuke; Fujimoto, Satoshi; Masuda, Ryuichi

2015-01-01

Quantifying intraspecific genetic variation in functionally important genes, such as those of the major histocompatibility complex (MHC), is important in the establishment of conservation plans for endangered species. The MHC genes play a crucial role in the vertebrate immune system and generally show high levels of diversity, which is likely due to pathogen-driven balancing selection. The endangered Blakiston's fish owl (Bubo blakistoni) has suffered marked population declines on Hokkaido Island, Japan, during the past several decades due to human-induced habitat loss and fragmentation. We investigated the spatial and temporal patterns of genetic diversity in MHC class IIβ genes in Blakiston's fish owl, using massively parallel pyrosequencing. We found that the Blakiston's fish owl genome contains at least eight MHC class IIβ loci, indicating recent gene duplications. An analysis of sequence polymorphism provided evidence that balancing selection acted in the past. The level of MHC variation, however, was low in the current fish owl populations in Hokkaido: only 19 alleles were identified from 174 individuals. We detected considerable spatial differences in MHC diversity among the geographically isolated populations. We also detected a decline of MHC diversity in some local populations during the past decades. Our study demonstrated that the current spatial patterns of MHC variation in Blakiston's fish owl populations have been shaped by loss of variation due to the decline and fragmentation of populations, and that the short-term effects of genetic drift have counteracted the long-term effects of balancing selection.

Mechanochemical pattern formation in simple models of active viscoelastic fluids and solids

NASA Astrophysics Data System (ADS)

Alonso, Sergio; Radszuweit, Markus; Engel, Harald; Bär, Markus

2017-11-01

The cytoskeleton of the organism Physarum polycephalum is a prominent example of a complex active viscoelastic material wherein stresses induce flows along the organism as a result of the action of molecular motors and their regulation by calcium ions. Experiments in Physarum polycephalum have revealed a rich variety of mechanochemical patterns including standing, traveling and rotating waves that arise from instabilities of spatially homogeneous states without gradients in stresses and resulting flows. Herein, we investigate simple models where an active stress induced by molecular motors is coupled to a model describing the passive viscoelastic properties of the cellular material. Specifically, two models for viscoelastic fluids (Maxwell and Jeffrey model) and two models for viscoelastic solids (Kelvin-Voigt and Standard model) are investigated. Our focus is on the analysis of the conditions that cause destabilization of spatially homogeneous states and the related onset of mechano-chemical waves and patterns. We carry out linear stability analyses and numerical simulations in one spatial dimension for different models. In general, sufficiently strong activity leads to waves and patterns. The primary instability is stationary for all active fluids considered, whereas all active solids have an oscillatory primary instability. All instabilities found are of long-wavelength nature reflecting the conservation of the total calcium concentration in the models studied.

Beaver assisted river valley formation

USGS Publications Warehouse

Westbrook, Cherie J.; Cooper, D.J.; Baker, B.W.

2011-01-01

We examined how beaver dams affect key ecosystem processes, including pattern and process of sediment deposition, the composition and spatial pattern of vegetation, and nutrient loading and processing. We provide new evidence for the formation of heterogeneous beaver meadows on riverine system floodplains and terraces where dynamic flows are capable of breaching in-channel beaver dams. Our data show a 1.7-m high beaver dam triggered overbank flooding that drowned vegetation in areas deeply flooded, deposited nutrient-rich sediment in a spatially heterogeneous pattern on the floodplain and terrace, and scoured soils in other areas. The site quickly de-watered following the dam breach by high stream flows, protecting the deposited sediment from future re-mobilization by overbank floods. Bare sediment either exposed by scouring or deposited by the beaver flood was quickly colonized by a spatially heterogeneous plant community, forming a beaver meadow. Many willow and some aspen seedlings established in the more heavily disturbed areas, suggesting the site may succeed to a willow carr plant community suitable for future beaver re-occupation. We expand existing theory beyond the beaver pond to include terraces within valleys. This more fully explains how beavers can help drive the formation of alluvial valleys and their complex vegetation patterns as was first postulated by Ruedemann and Schoonmaker in 1938. ?? 2010 John Wiley & Sons, Ltd.

Computational pathology: Exploring the spatial dimension of tumor ecology.

PubMed

Nawaz, Sidra; Yuan, Yinyin

2016-09-28

Tumors are evolving ecosystems where cancer subclones and the microenvironment interact. This is analogous to interaction dynamics between species in their natural habitats, which is a prime area of study in ecology. Spatial statistics are frequently used in ecological studies to infer complex relations including predator-prey, resource dependency and co-evolution. Recently, the emerging field of computational pathology has enabled high-throughput spatial analysis by using image processing to identify different cell types and their locations within histological tumor samples. We discuss how these data may be analyzed with spatial statistics used in ecology to reveal patterns and advance our understanding of ecological interactions occurring among cancer cells and their microenvironment. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Individual Patient Diagnosis of AD and FTD via High-Dimensional Pattern Classification of MRI

PubMed Central

Davatzikos, C.; Resnick, S. M.; Wu, X.; Parmpi, P.; Clark, C. M.

2008-01-01

The purpose of this study is to determine the diagnostic accuracy of MRI-based high-dimensional pattern classification in differentiating between patients with Alzheimer’s Disease (AD), Frontotemporal Dementia (FTD), and healthy controls, on an individual patient basis. MRI scans of 37 patients with AD and 37 age-matched cognitively normal elderly individuals, as well as 12 patients with FTD and 12 age-matched cognitively normal elderly individuals, were analyzed using voxel-based analysis and high-dimensional pattern classification. Diagnostic sensitivity and specificity of spatial patterns of regional brain atrophy found to be characteristic of AD and FTD were determined via cross-validation and via split-sample methods. Complex spatial patterns of relatively reduced brain volumes were identified, including temporal, orbitofrontal, parietal and cingulate regions, which were predominantly characteristic of either AD or FTD. These patterns provided 100% diagnostic accuracy, when used to separate AD or FTD from healthy controls. The ability to correctly distinguish AD from FTD averaged 84.3%. All estimates of diagnostic accuracy were determined via cross-validation. In conclusion, AD- and FTD-specific patterns of brain atrophy can be detected with high accuracy using high-dimensional pattern classification of MRI scans obtained in a typical clinical setting. PMID:18474436

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.

Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics.

PubMed

Atasoy, Selen; Deco, Gustavo; Kringelbach, Morten L; Pearson, Joel

2018-06-01

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at "rest." Here, we introduce the concept of harmonic brain modes-fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

Genetic analysis across different spatial scales reveals multiple dispersal mechanisms for the invasive hydrozoan Cordylophora in the Great Lakes.

PubMed

Darling, John A; Folino-Rorem, Nadine C

2009-12-01

Discerning patterns of post-establishment spread by invasive species is critically important for the design of effective management strategies and the development of appropriate theoretical models predicting spatial expansion of introduced populations. The globally invasive colonial hydrozoan Cordylophora produces propagules both sexually and vegetatively and is associated with multiple potential dispersal mechanisms, making it a promising system to investigate complex patterns of population structure generated throughout the course of rapid range expansion. Here, we explore genetic patterns associated with the spread of this taxon within the North American Great Lakes basin. We collected intensively from eight harbours in the Chicago area in order to conduct detailed investigation of local population expansion. In addition, we collected from Lakes Michigan, Erie, and Ontario, as well as Lake Cayuga in the Finger Lakes of upstate New York in order to assess genetic structure on a regional scale. Based on data from eight highly polymorphic microsatellite loci we examined the spatial extent of clonal genotypes, assessed levels of neutral genetic diversity, and explored patterns of migration and dispersal at multiple spatial scales through assessment of population level genetic differentiation (pairwise F(ST) and factorial correspondence analysis), Bayesian inference of population structure, and assignment tests on individual genotypes. Results of these analyses indicate that Cordylophora populations in this region spread predominantly through sexually produced propagules, and that while limited natural larval dispersal can drive expansion locally, regional expansion likely relies on anthropogenic dispersal vectors.

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

NASA Astrophysics Data System (ADS)

Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.

2018-07-01

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

NASA Astrophysics Data System (ADS)

Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.

2017-11-01

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

Beach-dune dynamics: Spatio-temporal patterns of aeolian sediment transport under complex offshore airflow

NASA Astrophysics Data System (ADS)

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

2010-12-01

This study examines sand transport and wind speed across a beach at Magilligan Strand, Northern Ireland, under offshore wind conditions. Traditionally the offshore component of local wind regimes has been ignored when quantifying beach-dune sediment budgets, with the sheltering effect of the foredune assumed to prohibit grain entrainment on the adjoining beach. Recent investigations of secondary airflow patterns over coastal dunes have suggested this may not be the case, that the turbulent nature of the airflow in these zones enhances sediment transport potential. Beach sediment may be delivered to the dune toe by re-circulating eddies under offshore winds in coastal areas, which may explain much of the dynamics of aeolian dunes on coasts where the dominant wind direction is offshore. The present study investigated aeolian sediment transport patterns under an offshore wind event. Empirical data were collected using load cell traps, for aeolian sediment transport, co-located with 3-D ultrasonic anemometers. The instrument positioning on the sub-aerial beach was informed by prior analysis of the airflow patterns using computational fluid dynamics. The array covered a total beach area of 90 m alongshore by 65 m cross-shore from the dune crest. Results confirm that sediment transport occurred in the ‘sheltered’ area under offshore winds. Over short time and space scales the nature of the transport is highly complex; however, preferential zones for sand entrainment may be identified. Alongshore spatial heterogeneity of sediment transport seems to show a relationship to undulations in the dune crest, while temporal and spatial variations may also be related to the position of the airflow reattachment zone. These results highlight the important feedbacks between flow characteristics and transport in a complex three dimensional surface.

Self-organization of multifunctional surfaces--the fingerprints of light on a complex system.

PubMed

Reinhardt, Hendrik; Kim, Hee-Cheol; Pietzonka, Clemens; Kruempelmann, Julia; Harbrecht, Bernd; Roling, Bernhard; Hampp, Norbert

2013-06-25

Nanocomposite patterns and nanotemplates are generated by a single-step bottom-up concept that introduces laser-induced periodic surface structures (LIPSS) as a tool for site-specific reaction control in multicomponent systems. Periodic intensity fluctuations of this photothermal stimulus inflict spatial-selective reorganizations, dewetting scenarios and phase segregations, thus creating regular patterns of anisotropic physicochemical properties that feature attractive optical, electrical, magnetic, and catalytic properties. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Surface Structuring with Polarization-Singular Femtosecond Laser Beams Generated by a q-plate

PubMed Central

Nivas, Jijil JJ; Cardano, Filippo; Song, Zhenming; Rubano, Andrea; Fittipaldi, Rosalba; Vecchione, Antonio; Paparo, Domenico; Marrucci, Lorenzo; Bruzzese, Riccardo; Amoruso, Salvatore

2017-01-01

In the last few years femtosecond optical vortex beams with different spatial distributions of the state of polarization (e.g. azimuthal, radial, spiral, etc.) have been used to generate complex, regular surface patterns on different materials. Here we present an experimental investigation on direct femtosecond laser surface structuring based on a larger class of vector beams generated by means of a q-plate with topological charge q = +1/2. In fact, voltage tuning of q-plate optical retardation allows generating a family of ultrashort laser beams with a continuous spatial evolution of polarization and fluence distribution in the focal plane. These beams can be thought of as a controlled coherent superposition of a Gaussian beam with uniform polarization and a vortex beam with a radial or azimuthal state of polarization. The use of this family of ultrashort laser beams in surface structuring leads to a further extension of the achievable surface patterns. The comparison of theoretical predictions of the vector beam characteristics at the focal plane and the generated surface patterns is used to rationalize the dependence of the surface structures on the local state of the laser beam, thus offering an effective way to either design unconventional surface structures or diagnose complex ultrashort laser beams. PMID:28169342

Surface Structuring with Polarization-Singular Femtosecond Laser Beams Generated by a q-plate.

PubMed

Nivas, Jijil Jj; Cardano, Filippo; Song, Zhenming; Rubano, Andrea; Fittipaldi, Rosalba; Vecchione, Antonio; Paparo, Domenico; Marrucci, Lorenzo; Bruzzese, Riccardo; Amoruso, Salvatore

2017-02-07

In the last few years femtosecond optical vortex beams with different spatial distributions of the state of polarization (e.g. azimuthal, radial, spiral, etc.) have been used to generate complex, regular surface patterns on different materials. Here we present an experimental investigation on direct femtosecond laser surface structuring based on a larger class of vector beams generated by means of a q-plate with topological charge q = +1/2. In fact, voltage tuning of q-plate optical retardation allows generating a family of ultrashort laser beams with a continuous spatial evolution of polarization and fluence distribution in the focal plane. These beams can be thought of as a controlled coherent superposition of a Gaussian beam with uniform polarization and a vortex beam with a radial or azimuthal state of polarization. The use of this family of ultrashort laser beams in surface structuring leads to a further extension of the achievable surface patterns. The comparison of theoretical predictions of the vector beam characteristics at the focal plane and the generated surface patterns is used to rationalize the dependence of the surface structures on the local state of the laser beam, thus offering an effective way to either design unconventional surface structures or diagnose complex ultrashort laser beams.

Surface Structuring with Polarization-Singular Femtosecond Laser Beams Generated by a q-plate

NASA Astrophysics Data System (ADS)

Nivas, Jijil Jj; Cardano, Filippo; Song, Zhenming; Rubano, Andrea; Fittipaldi, Rosalba; Vecchione, Antonio; Paparo, Domenico; Marrucci, Lorenzo; Bruzzese, Riccardo; Amoruso, Salvatore

2017-02-01

In the last few years femtosecond optical vortex beams with different spatial distributions of the state of polarization (e.g. azimuthal, radial, spiral, etc.) have been used to generate complex, regular surface patterns on different materials. Here we present an experimental investigation on direct femtosecond laser surface structuring based on a larger class of vector beams generated by means of a q-plate with topological charge q = +1/2. In fact, voltage tuning of q-plate optical retardation allows generating a family of ultrashort laser beams with a continuous spatial evolution of polarization and fluence distribution in the focal plane. These beams can be thought of as a controlled coherent superposition of a Gaussian beam with uniform polarization and a vortex beam with a radial or azimuthal state of polarization. The use of this family of ultrashort laser beams in surface structuring leads to a further extension of the achievable surface patterns. The comparison of theoretical predictions of the vector beam characteristics at the focal plane and the generated surface patterns is used to rationalize the dependence of the surface structures on the local state of the laser beam, thus offering an effective way to either design unconventional surface structures or diagnose complex ultrashort laser beams.

Pedological memory in forest soil development

Treesearch

Jonathan D. Phillips; Daniel A. Marion

2004-01-01

Individual trees may have significant impacts on soil morphology. If these impacts are non-random such that some microsites are repeatedly preferentially affected by trees, complex local spatial variability of soils would result. A model of self-reinforcing pedologic influences of trees (SRPIT) is proposed to explain patterns of soil variability in the Ouachita...

A simulation study to determine the attenuation and bias in health risk estimates due to exposure measurement error in bi-pollutant models

EPA Science Inventory

To understand the combined health effects of exposure to ambient air pollutant mixtures, it is becoming more common to include multiple pollutants in epidemiologic models. However, the complex spatial and temporal pattern of ambient pollutant concentrations and related exposures ...

Visualization of heterogeneous forest structures following treatment in the southern Rocky Mountains

Treesearch

Wade T. Tinkham; Yvette Dickinson; Chad M. Hoffman; Mike A. Battaglia; Seth Ex; Jeffrey Underhill

2017-01-01

Manipulation of forest spatial patterns has become a common objective in restoration prescriptions throughout the central and southern Rocky Mountain dry-mixed conifer forest systems. Pre-Euro-American settlement forest reconstructions indicate that frequent-fire regimes developed forests with complex mosaics of individual trees, tree clumps of varying size, and...

Spatial scaling and multi-model inference in landscape genetics: Martes americana in northern Idaho

Treesearch

Tzeidle N. Wasserman; Samuel A. Cushman; Michael K. Schwartz; David O. Wallin

2010-01-01

Individual-based analyses relating landscape structure to genetic distances across complex landscapes enable rigorous evaluation of multiple alternative hypotheses linking landscape structure to gene flow. We utilize two extensions to increase the rigor of the individual-based causal modeling approach to inferring relationships between landscape patterns and gene flow...

Yosemite Hydroclimate Network: Distributed stream and atmospheric data for the Tuolumne River watershed and surroundings

NASA Astrophysics Data System (ADS)

Lundquist, Jessica D.; Roche, James W.; Forrester, Harrison; Moore, Courtney; Keenan, Eric; Perry, Gwyneth; Cristea, Nicoleta; Henn, Brian; Lapo, Karl; McGurk, Bruce; Cayan, Daniel R.; Dettinger, Michael D.

2016-09-01

Regions of complex topography and remote wilderness terrain have spatially varying patterns of temperature and streamflow, but due to inherent difficulties of access, are often very poorly sampled. Here we present a data set of distributed stream stage, streamflow, stream temperature, barometric pressure, and air temperature from the Tuolumne River Watershed in Yosemite National Park, Sierra Nevada, California, USA, for water years 2002-2015, as well as a quality-controlled hourly meteorological forcing time series for use in hydrologic modeling. We also provide snow data and daily inflow to the Hetch Hetchy Reservoir for 1970-2015. This paper describes data collected using low-visibility and low-impact installations for wilderness locations and can be used alone or as a critical supplement to ancillary data sets collected by cooperating agencies, referenced herein. This data set provides a unique opportunity to understand spatial patterns and scaling of hydroclimatic processes in complex terrain and can be used to evaluate downscaling techniques or distributed modeling. The paper also provides an example methodology and lessons learned in conducting hydroclimatic monitoring in remote wilderness.

The roosting spatial network of a bird-predator bat.

PubMed

Fortuna, Miguel A; Popa-Lisseanu, Ana G; Ibáñez, Carlos; Bascompte, Jordi

2009-04-01

The use of roosting sites by animal societies is important in conservation biology, animal behavior, and epidemiology. The giant noctule bat (Nyctalus lasiopterus) constitutes fission-fusion societies whose members spread every day in multiple trees for shelter. To assess how the pattern of roosting use determines the potential for information exchange or disease spreading, we applied the framework of complex networks. We found a social and spatial segregation of the population in well-defined modules or compartments, formed by groups of bats sharing the same trees. Inside each module, we revealed an asymmetric use of trees by bats representative of a nested pattern. By applying a simple epidemiological model, we show that there is a strong correlation between network structure and the rate and shape of infection dynamics. This modular structure slows down the spread of diseases and the exchange of information through the entire network. The implication for management is complex, affecting differently the cohesion inside and among colonies and the transmission of parasites and diseases. Network analysis can hence be applied to quantifying the conservation status of individual trees used by species depending on hollows for shelter.

Identifying Typhoon Tracks based on Event Synchronization derived Spatially Embedded Climate Networks

NASA Astrophysics Data System (ADS)

Ozturk, Ugur; Marwan, Norbert; Kurths, Jürgen

2017-04-01

Complex networks are commonly used for investigating spatiotemporal dynamics of complex systems, e.g. extreme rainfall. Especially directed networks are very effective tools in identifying climatic patterns on spatially embedded networks. They can capture the network flux, so as the principal dynamics of spreading significant phenomena. Network measures, such as network divergence, bare the source-receptor relation of the directed networks. However, it is still a challenge how to catch fast evolving atmospheric events, i.e. typhoons. In this study, we propose a new technique, namely Radial Ranks, to detect the general pattern of typhoons forward direction based on the strength parameter of the event synchronization over Japan. We suggest to subset a circular zone of high correlation around the selected grid based on the strength parameter. Radial sums of the strength parameter along vectors within this zone, radial ranks are measured for potential directions, which allows us to trace the network flux over long distances. We employed also the delay parameter of event synchronization to identify and separate the frontal storms' and typhoons' individual behaviors.

Yosemite Hydroclimate Network: Distributed stream and atmospheric data for the Tuolumne River watershed and surroundings

USGS Publications Warehouse

Lundquist, Jessica D.; Roche, James W.; Forrester, Harrison; Moore, Courtney; Keenan, Eric; Perry, Gwyneth; Cristea, Nicoleta; Henn, Brian; Lapo, Karl; McGurk, Bruce; Cayan, Daniel R.; Dettinger, Michael D.

2016-01-01

Regions of complex topography and remote wilderness terrain have spatially varying patterns of temperature and streamflow, but due to inherent difficulties of access, are often very poorly sampled. Here we present a data set of distributed stream stage, streamflow, stream temperature, barometric pressure, and air temperature from the Tuolumne River Watershed in Yosemite National Park, Sierra Nevada, California, USA, for water years 2002–2015, as well as a quality-controlled hourly meteorological forcing time series for use in hydrologic modeling. We also provide snow data and daily inflow to the Hetch Hetchy Reservoir for 1970–2015. This paper describes data collected using low-visibility and low-impact installations for wilderness locations and can be used alone or as a critical supplement to ancillary data sets collected by cooperating agencies, referenced herein. This data set provides a unique opportunity to understand spatial patterns and scaling of hydroclimatic processes in complex terrain and can be used to evaluate downscaling techniques or distributed modeling. The paper also provides an example methodology and lessons learned in conducting hydroclimatic monitoring in remote wilderness.

The interplay between human population dynamics and flooding in Bangladesh: a spatial analysis

NASA Astrophysics Data System (ADS)

di Baldassarre, G.; Yan, K.; Ferdous, MD. R.; Brandimarte, L.

2014-09-01

In Bangladesh, socio-economic and hydrological processes are both extremely dynamic and inter-related. Human population patterns are often explained as a response, or adaptation strategy, to physical events, e.g. flooding, salt-water intrusion, and erosion. Meanwhile, these physical processes are exacerbated, or mitigated, by diverse human interventions, e.g. river diversion, levees and polders. In this context, this paper describes an attempt to explore the complex interplay between floods and societies in Bangladeshi floodplains. In particular, we performed a spatially-distributed analysis of the interactions between the dynamics of human settlements and flood inundation patterns. To this end, we used flooding simulation results from inundation modelling, LISFLOOD-FP, as well as global datasets of population distribution data, such as the Gridded Population of the World (20 years, from 1990 to 2010) and HYDE datasets (310 years, from 1700 to 2010). The outcomes of this work highlight the behaviour of Bangladeshi floodplains as complex human-water systems and indicate the need to go beyond the traditional narratives based on one-way cause-effects, e.g. climate change leading to migrations.

Nonlinear periodic wavetrains in thin liquid films falling on a uniformly heated horizontal plate

NASA Astrophysics Data System (ADS)

Issokolo, Remi J. Noumana; Dikandé, Alain M.

2018-05-01

A thin liquid film falling on a uniformly heated horizontal plate spreads into fingering ripples that can display a complex dynamics ranging from continuous waves, nonlinear spatially localized periodic wave patterns (i.e., rivulet structures) to modulated nonlinear wavetrain structures. Some of these structures have been observed experimentally; however, conditions under which they form are still not well understood. In this work, we examine profiles of nonlinear wave patterns formed by a thin liquid film falling on a uniformly heated horizontal plate. For this purpose, the Benney model is considered assuming a uniform temperature distribution along the film propagation on the horizontal surface. It is shown that for strong surface tension but a relatively small Biot number, spatially localized periodic-wave structures can be analytically obtained by solving the governing equation under appropriate conditions. In the regime of weak nonlinearity, a multiple-scale expansion combined with the reductive perturbation method leads to a complex Ginzburg-Landau equation: the solutions of which are modulated periodic pulse trains which amplitude and width and period are expressed in terms of characteristic parameters of the model.

Stochastic population dynamics in spatially extended predator-prey systems

NASA Astrophysics Data System (ADS)

Dobramysl, Ulrich; Mobilia, Mauro; Pleimling, Michel; Täuber, Uwe C.

2018-02-01

Spatially extended population dynamics models that incorporate demographic noise serve as case studies for the crucial role of fluctuations and correlations in biological systems. Numerical and analytic tools from non-equilibrium statistical physics capture the stochastic kinetics of these complex interacting many-particle systems beyond rate equation approximations. Including spatial structure and stochastic noise in models for predator-prey competition invalidates the neutral Lotka-Volterra population cycles. Stochastic models yield long-lived erratic oscillations stemming from a resonant amplification mechanism. Spatially extended predator-prey systems display noise-stabilized activity fronts that generate persistent correlations. Fluctuation-induced renormalizations of the oscillation parameters can be analyzed perturbatively via a Doi-Peliti field theory mapping of the master equation; related tools allow detailed characterization of extinction pathways. The critical steady-state and non-equilibrium relaxation dynamics at the predator extinction threshold are governed by the directed percolation universality class. Spatial predation rate variability results in more localized clusters, enhancing both competing species’ population densities. Affixing variable interaction rates to individual particles and allowing for trait inheritance subject to mutations induces fast evolutionary dynamics for the rate distributions. Stochastic spatial variants of three-species competition with ‘rock-paper-scissors’ interactions metaphorically describe cyclic dominance. These models illustrate intimate connections between population dynamics and evolutionary game theory, underscore the role of fluctuations to drive populations toward extinction, and demonstrate how space can support species diversity. Two-dimensional cyclic three-species May-Leonard models are characterized by the emergence of spiraling patterns whose properties are elucidated by a mapping onto a complex Ginzburg-Landau equation. Multiple-species extensions to general ‘food networks’ can be classified on the mean-field level, providing both fundamental understanding of ensuing cooperativity and profound insight into the rich spatio-temporal features and coarsening kinetics in the corresponding spatially extended systems. Novel space-time patterns emerge as a result of the formation of competing alliances; e.g. coarsening domains that each incorporate rock-paper-scissors competition games.

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

Efficient visual object and word recognition relies on high spatial frequency coding in the left posterior fusiform gyrus: evidence from a case-series of patients with ventral occipito-temporal cortex damage.

PubMed

Roberts, Daniel J; Woollams, Anna M; Kim, Esther; Beeson, Pelagie M; Rapcsak, Steven Z; Lambon Ralph, Matthew A

2013-11-01

Recent visual neuroscience investigations suggest that ventral occipito-temporal cortex is retinotopically organized, with high acuity foveal input projecting primarily to the posterior fusiform gyrus (pFG), making this region crucial for coding high spatial frequency information. Because high spatial frequencies are critical for fine-grained visual discrimination, we hypothesized that damage to the left pFG should have an adverse effect not only on efficient reading, as observed in pure alexia, but also on the processing of complex non-orthographic visual stimuli. Consistent with this hypothesis, we obtained evidence that a large case series (n = 20) of patients with lesions centered on left pFG: 1) Exhibited reduced sensitivity to high spatial frequencies; 2) demonstrated prolonged response latencies both in reading (pure alexia) and object naming; and 3) were especially sensitive to visual complexity and similarity when discriminating between novel visual patterns. These results suggest that the patients' dual reading and non-orthographic recognition impairments have a common underlying mechanism and reflect the loss of high spatial frequency visual information normally coded in the left pFG.

[Explore the spatial and temporal patterns of water pollution in the Yincungang canal of the Lake Taihu basin, China].

PubMed

Yang, Xiao-Ying; Luo, Xing-Zhang; Zheng, Zheng; Fang, Shu-Bo

2012-09-01

Two high-density snap-shot samplings were conducted along the Yincungang canal, one important tributary of the Lake Tai, in April (low flow period) and June (high flow period) of 2010. Geostatistical analysis based on the river network distance was used to analyze the spatial and temporal patterns of the pollutant concentrations along the canal with an emphasis on chemical oxygen demand (COD) and total nitrogen (TN). Study results have indicated: (1) COD and TN concentrations display distinctly different spatial and temporal patterns between the low and high flow periods. COD concentration in June is lower than that in April, while TN concentration has the contrary trend. (2) COD load is relatively constant during the period between the two monitoring periods. The spatial correlation structure of COD is exponential for both April and June, and the change of COD concentration is mainly influenced by hydrological conditions. (3) Nitrogen load from agriculture increased significantly during the period between the two monitoring periods. Large amount of chaotic fertilizing by individual farmers has led to the loss of the spatial correlation among the observed TN concentrations. Hence, changes of TN concentration in June are under the dual influence of agricultural fertilizing and hydrological conditions. In the view of the complex hydrological conditions and serious water pollution in the Lake Taihu region, geostatistical analysis is potentially a useful tool for studying the characteristics of pollutant distribution and making predictions in the region.

Związek rozmieszczenia powierzchniowych form krasowych międzyrzecza środkowego Wieprza i Bugu z tektoniką dysjunktywną w świetle analizy statystycznej

NASA Astrophysics Data System (ADS)

Kamińska, Anna

2010-01-01

The relationship between karst of chalk and tectonics in the interfluve of the middle Wieprz and Bug Rivers has been already examined by Maruszczak (1966), Harasimiuk (1980) and Dobrowolski (1998). Investigating the connection of the karst formation course and the substratum structure, the direction of the landforms and their spatial pattern were analysed and compared later to the structural pattern. The obvious completion of the collected data is a quantity analysis using statistical methods. This paper deals with the characteristics of such quantity analysis. By using the tools of the directional statistics, the following indexes have been calculated: the mean vector orientation, the length of the vector mean, strength of the vector mean, the Batschelet variance, as well as determined confidence intervals for the mean vector. In order to examine the distribution structure of these forms, the selected methods of the spatial statistics have been used-angular wavelet analysis (Rosenberg 2004) and the semivariogram analysis (Namysłowska-Wilczyńska 2006). On the basis of conducted analyses, it is possible to describe in detail the regularities in spatial distribution of the surface karst forms in the interfluve of the middle Wieprz and Bug Rivers. The orientation analysis reveals an important feature of their direction-along with a rise in the size of surface karst forms, the level of concentration around the mean vector orientation increases. Primary karst forms point out poor concentration along the longitudinal direction whereas complex forms are clearly concentrated along the WNW-ESE direction. Hence, only after clumping of the primary forms into the complex ones, the convergence of the surface karst forms direction with the direction of the main faults in the Meso-Cenozoic complex is visible (after A. Henkiel 1984). The results of the wavelet analysis modified by Rosenberg (2004) have indicated significant directions of the clumping of the surface karst forms. A clear difference in the distribution of these forms in west and east areas is noticed. Whereas the west area is dominated by the W-E, NW-SE, N-S directions, the karst forms in the east are concentrated along the NE-SW direction. The semivariogram analysis has confirmed the importance of the W-E and NE-SW directions. Moreover, this analysis has indicated which areas are characterized by the poor karst forms direction. It is a region where the Kock-Wasylów dislocation zone crosses the Święcica dislocation zone in the north-east part of the analysed area. The south-east region is the second such area. The picture of the spatial pattern one confirms the previous results (Dobrowolski 1998) and refers clearly to the structural pattern of this area. Nevertheless, the analyses mentioned above have shown the dominance of the W-E direction over the NW-SE one. The obtained results of the spatial and direction analyses expand and confirm hitherto information about the relation between the spatial pattern of the karst landforms and the tectonics in the interfluve of the middle Wieprz and Bug Rivers.

Population genomic analysis suggests strong influence of river network on spatial distribution of genetic variation in invasive saltcedar across the southwestern United States

USGS Publications Warehouse

Lee, Soo-Rang; Jo, Yeong-Seok; Park, Chan-Ho; Friedman, Jonathan M.; Olson, Matthew S.

2018-01-01

Understanding the complex influences of landscape and anthropogenic elements that shape the population genetic structure of invasive species provides insight into patterns of colonization and spread. The application of landscape genomics techniques to these questions may offer detailed, previously undocumented insights into factors influencing species invasions. We investigated the spatial pattern of genetic variation and the influences of landscape factors on population similarity in an invasive riparian shrub, saltcedar (Tamarix L.) by analysing 1,997 genomewide SNP markers for 259 individuals from 25 populations collected throughout the southwestern United States. Our results revealed a broad-scale spatial genetic differentiation of saltcedar populations between the Colorado and Rio Grande river basins and identified potential barriers to population similarity along both river systems. River pathways most strongly contributed to population similarity. In contrast, low temperature and dams likely served as barriers to population similarity. We hypothesize that large-scale geographic patterns in genetic diversity resulted from a combination of early introductions from distinct populations, the subsequent influence of natural selection, dispersal barriers and founder effects during range expansion.

Spatial and temporal drivers of phenotypic diversity in polymorphic snakes.

PubMed

Cox, Christian L; Davis Rabosky, Alison R

2013-08-01

Color polymorphism in natural populations presents an ideal opportunity to study the evolutionary drivers of phenotypic diversity. Systems with striking spatial, temporal, and qualitative variation in color can be leveraged to study the mechanisms promoting the distribution of different types of variation in nature. We used the highly polymorphic ground snake (Sonora semiannulata), a putative coral snake mimic with both cryptic and conspicuous morphs, to compare patterns of neutral genetic variation and variation over space and time in color polymorphism to investigate the mechanistic drivers of phenotypic variation across scales. We found that strong selection promotes color polymorphism across spatial and temporal scales, with morph frequencies differing markedly between juvenile and adult age classes within a single population, oscillating over time within multiple populations, and varying drastically over the landscape despite minimal population genetic structure. However, we found no evidence that conspicuousness of morphs was related to which color pattern was favored by selection or to any geographic factors, including sympatry with coral snakes. We suggest that complex patterns of phenotypic variation in polymorphic systems may be a fundamental outcome of the conspicuousness of morphs and that explicit tests of temporal and geographic variation are critical to the interpretation of conspicuousness and mimicry.

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.

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

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model.

PubMed

Shafer, Sarah L; Bartlein, Patrick J; Gray, Elizabeth M; Pelltier, Richard T

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0°N latitude by 136.6-103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Comparative Phylogeographic Analyses Illustrate the Complex Evolutionary History of Threatened Cloud Forests of Northern Mesoamerica

PubMed Central

Ornelas, Juan Francisco; Sosa, Victoria; Soltis, Douglas E.; Daza, Juan M.; González, Clementina; Soltis, Pamela S.; Gutiérrez-Rodríguez, Carla; de los Monteros, Alejandro Espinosa; Castoe, Todd A.; Bell, Charles; Ruiz-Sanchez, Eduardo

2013-01-01

Comparative phylogeography can elucidate the influence of historical events on current patterns of biodiversity and can identify patterns of co-vicariance among unrelated taxa that span the same geographic areas. Here we analyze temporal and spatial divergence patterns of cloud forest plant and animal species and relate them to the evolutionary history of naturally fragmented cloud forests–among the most threatened vegetation types in northern Mesoamerica. We used comparative phylogeographic analyses to identify patterns of co-vicariance in taxa that share geographic ranges across cloud forest habitats and to elucidate the influence of historical events on current patterns of biodiversity. We document temporal and spatial genetic divergence of 15 species (including seed plants, birds and rodents), and relate them to the evolutionary history of the naturally fragmented cloud forests. We used fossil-calibrated genealogies, coalescent-based divergence time inference, and estimates of gene flow to assess the permeability of putative barriers to gene flow. We also used the hierarchical Approximate Bayesian Computation (HABC) method implemented in the program msBayes to test simultaneous versus non-simultaneous divergence of the cloud forest lineages. Our results show shared phylogeographic breaks that correspond to the Isthmus of Tehuantepec, Los Tuxtlas, and the Chiapas Central Depression, with the Isthmus representing the most frequently shared break among taxa. However, dating analyses suggest that the phylogeographic breaks corresponding to the Isthmus occurred at different times in different taxa. Current divergence patterns are therefore consistent with the hypothesis of broad vicariance across the Isthmus of Tehuantepec derived from different mechanisms operating at different times. This study, coupled with existing data on divergence cloud forest species, indicates that the evolutionary history of contemporary cloud forest lineages is complex and often lineage-specific, and thus difficult to capture in a simple conservation strategy. PMID:23409165

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.

A MS-lesion pattern discrimination plot based on geostatistics.

PubMed

Marschallinger, Robert; Schmidt, Paul; Hofmann, Peter; Zimmer, Claus; Atkinson, Peter M; Sellner, Johann; Trinka, Eugen; Mühlau, Mark

2016-03-01

A geostatistical approach to characterize MS-lesion patterns based on their geometrical properties is presented. A dataset of 259 binary MS-lesion masks in MNI space was subjected to directional variography. A model function was fit to express the observed spatial variability in x, y, z directions by the geostatistical parameters Range and Sill. Parameters Range and Sill correlate with MS-lesion pattern surface complexity and total lesion volume. A scatter plot of ln(Range) versus ln(Sill), classified by pattern anisotropy, enables a consistent and clearly arranged presentation of MS-lesion patterns based on geometry: the so-called MS-Lesion Pattern Discrimination Plot. The geostatistical approach and the graphical representation of results are considered efficient exploratory data analysis tools for cross-sectional, follow-up, and medication impact analysis.

Master stability functions reveal diffusion-driven pattern formation in networks

NASA Astrophysics Data System (ADS)

Brechtel, Andreas; Gramlich, Philipp; Ritterskamp, Daniel; Drossel, Barbara; Gross, Thilo

2018-03-01

We study diffusion-driven pattern formation in networks of networks, a class of multilayer systems, where different layers have the same topology, but different internal dynamics. Agents are assumed to disperse within a layer by undergoing random walks, while they can be created or destroyed by reactions between or within a layer. We show that the stability of homogeneous steady states can be analyzed with a master stability function approach that reveals a deep analogy between pattern formation in networks and pattern formation in continuous space. For illustration, we consider a generalized model of ecological meta-food webs. This fairly complex model describes the dispersal of many different species across a region consisting of a network of individual habitats while subject to realistic, nonlinear predator-prey interactions. In this example, the method reveals the intricate dependence of the dynamics on the spatial structure. The ability of the proposed approach to deal with this fairly complex system highlights it as a promising tool for ecology and other applications.

Validating a spatially distributed hydrological model with soil morphology data

NASA Astrophysics Data System (ADS)

Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

2013-10-01

Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas. The groundwater level dynamics were not adequately reproduced and the predicted spatial patterns of soil saturation did not correspond to the patterns estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a more complex model. Especially high spatial resolution and very detailed process representations at the boundary between the unsaturated and the saturated zone are expected to be crucial. The data needed for such a detailed model are not generally available. The high computational demand and the complex model setup would require more resources than the direct identification of saturated areas in the field. This severely hampers the practical use of such models despite their usefulness for scientific purposes.

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.

A novel single neuron perceptron with universal approximation and XOR computation properties.

PubMed

Lotfi, Ehsan; Akbarzadeh-T, M-R

2014-01-01

We propose a biologically motivated brain-inspired single neuron perceptron (SNP) with universal approximation and XOR computation properties. This computational model extends the input pattern and is based on the excitatory and inhibitory learning rules inspired from neural connections in the human brain's nervous system. The resulting architecture of SNP can be trained by supervised excitatory and inhibitory online learning rules. The main features of proposed single layer perceptron are universal approximation property and low computational complexity. The method is tested on 6 UCI (University of California, Irvine) pattern recognition and classification datasets. Various comparisons with multilayer perceptron (MLP) with gradient decent backpropagation (GDBP) learning algorithm indicate the superiority of the approach in terms of higher accuracy, lower time, and spatial complexity, as well as faster training. Hence, we believe the proposed approach can be generally applicable to various problems such as in pattern recognition and classification.

Determination of the stacking fault density in highly defective single GaAs nanowires by means of coherent diffraction imaging

NASA Astrophysics Data System (ADS)

Davtyan, Arman; Biermanns, Andreas; Loffeld, Otmar; Pietsch, Ullrich

2016-06-01

Coherent x-ray diffraction imaging is used to measure diffraction patterns from individual highly defective nanowires, showing a complex speckle pattern instead of well-defined Bragg peaks. The approach is tested for nanowires of 500 nm diameter and 500 nm height predominately composed by zinc-blende (ZB) and twinned zinc-blende (TZB) phase domains. Phase retrieval is used to reconstruct the measured 2-dimensional intensity patterns recorded from single nanowires with 3.48 nm and 0.98 nm spatial resolution. Whereas the speckle amplitudes and distribution are perfectly reconstructed, no unique solution could be obtained for the phase structure. The number of phase switches is found to be proportional to the number of measured speckles and follows a narrow number distribution. Using data with 0.98 nm spatial resolution the mean number of phase switches is in reasonable agreement with estimates taken from TEM. However, since the resolved phase domain still is 3-4 times larger than a single GaAs bilayer we explain the non-ambiguous phase reconstruction by the fact that depending on starting phase and sequence of subroutines used during the phase retrieval the retrieved phase domain host a different sequence of randomly stacked bilayers. Modelling possible arrangements of bilayer sequences within a phase domain demonstrate that the complex speckle patterns measured can indeed be explained by the random arrangement of the ZB and TZB phase domains.

The spatial organisation of joint surface chondrocytes: review of its potential roles in tissue functioning, disease and early, preclinical diagnosis of osteoarthritis.

PubMed

Aicher, Wilhelm K; Rolauffs, Bernd

2014-04-01

Chondrocytes display within the articular cartilage depth-dependent variations of their many properties that are comparable to the depth-dependent changes of the properties of the surrounding extracellular matrix. However, not much is known about the spatial organisation of the chondrocytes throughout the tissue. Recent studies revealed that human chondrocytes display distinct spatial patterns of organisation within the articular surface, and each joint surface is dominated in a typical way by one of four basic spatial patterns. The resulting complex spatial organisations correlate with the specific diarthrodial joint type, suggesting an association of the chondrocyte organisation within the joint surface with the occurring biomechanical forces. In response to focal osteoarthritis (OA), the superficial chondrocytes experience a destruction of their spatial organisation within the OA lesion, but they also undergo a defined remodelling process distant from the OA lesion in the remaining, intact cartilage surface. One of the biological insights that can be derived from this spatial remodelling process is that the chondrocytes are able to respond in a generalised and coordinated fashion to distant focal OA. The spatial characteristics of this process are tremendously different from the cellular aggregations typical for OA lesions, suggesting differences in the underlying mechanisms. Here we summarise the available information on the spatial organisation of chondrocytes and its potential roles in cartilage functioning. The spatial organisation could be used to diagnose early OA onset before manifest OA results in tissue destruction and clinical symptoms. With further development, this concept may become clinically suitable for the diagnosis of preclinical OA.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Dissipative structure in the photo-induced phase under steady light irradiation in the spin crossover complex.

PubMed

Nishihara, Taishi; Bousseksou, Azzdine; Tanaka, Koichiro

2013-12-16

We report the spatial and temporal dynamics of the photo-induced phase in the iron (II) spin crossover complex Fe(ptz)(6)(BF(4))(2) studied by image measurement under steady light irradiation and transient absorption measurement. The dynamic factors are derived from the spatial and temporal fluctuation of the image in the steady state under light irradiation between 65 and 100 K. The dynamic factors clearly indicate that the fluctuation has a resonant frequency that strongly depends on the temperature, and is proportional to the relaxation rate of the photo-induced phase. This oscillation of the speckle pattern under steady light irradiation is ascribed to the nonlinear interaction between the spin state and the lattice volume at the surface.

A multiscale analysis of coral reef topographic complexity using lidar-derived bathymetry

USGS Publications Warehouse

Zawada, D.G.; Brock, J.C.

2009-01-01

Coral reefs represent one of the most irregular substrates in the marine environment. This roughness or topographic complexity is an important structural characteristic of reef habitats that affects a number of ecological and environmental attributes, including species diversity and water circulation. Little is known about the range of topographic complexity exhibited within a reef or between different reef systems. The objective of this study was to quantify topographic complexity for a 5-km x 5-km reefscape along the northern Florida Keys reef tract, over spatial scales ranging from meters to hundreds of meters. The underlying dataset was a 1-m spatial resolution, digital elevation model constructed from lidar measurements. Topographic complexity was quantified using a fractal algorithm, which provided a multi-scale characterization of reef roughness. The computed fractal dimensions (D) are a measure of substrate irregularity and are bounded between values of 2 and 3. Spatial patterns in D were positively correlated with known reef zonation in the area. Landward regions of the study site contain relatively smooth (D ??? 2.35) flat-topped patch reefs, which give way to rougher (D ??? 2.5), deep, knoll-shaped patch reefs. The seaward boundary contains a mixture of substrate features, including discontinuous shelf-edge reefs, and exhibits a corresponding range of roughness values (2.28 ??? D ??? 2.61). ?? 2009 Coastal Education and Research Foundation.

Positioning cell wall synthetic complexes by the bacterial morphogenetic proteins MreB and MreD.

PubMed

White, Courtney L; Kitich, Aleksandar; Gober, James W

2010-05-01

In Caulobacter crescentus, intact cables of the actin homologue, MreB, are required for the proper spatial positioning of MurG which catalyses the final step in peptidoglycan precursor synthesis. Similarly, in the periplasm, MreC controls the spatial orientation of the penicillin binding proteins and a lytic transglycosylase. We have now found that MreB cables are required for the organization of several other cytosolic murein biosynthetic enzymes such as MraY, MurB, MurC, MurE and MurF. We also show these proteins adopt a subcellular pattern of localization comparable to MurG, suggesting the existence of cytoskeletal-dependent interactions. Through extensive two-hybrid analyses, we have now generated a comprehensive interaction map of components of the bacterial morphogenetic complex. In the cytosol, this complex contains both murein biosynthetic enzymes and morphogenetic proteins, including RodA, RodZ and MreD. We show that the integral membrane protein, MreD, is essential for lateral peptidoglycan synthesis, interacts with the precursor synthesizing enzymes MurG and MraY, and additionally, determines MreB localization. Our results suggest that the interdependent localization of MreB and MreD functions to spatially organize a complex of peptidoglycan precursor synthesis proteins, which is required for propagation of a uniform cell shape and catalytically efficient peptidoglycan synthesis.

Complex terrain in the Critical Zone: How topography drives ecohydrological patterns of soil and plant carbon exchange in a semiarid mountainous system

NASA Astrophysics Data System (ADS)

Barron-Gafford, G.; Minor, R. L.; Heard, M. M.; Sutter, L. F.; Yang, J.; Potts, D. L.

2015-12-01

The southwestern U.S. is predicted to experience increasing temperatures and longer periods of inter-storm drought. High temperature and water deficit restrict plant productivity and ecosystem functioning, but the influence of future climate is predicted to be highly heterogeneous because of the complex terrain characteristic of much of the Critical Zone (CZ). Within our Critical Zone Observatory (CZO) in the Southwestern US, we monitor ecosystem-scale carbon and water fluxes using eddy covariance. This whole-ecosystem metric is a powerful integrating measure of ecosystem function over time, but details on spatial heterogeneity resulting from topographic features of the landscape are not captured, nor are interactions among below- and aboveground processes. We supplement eddy covariance monitoring with distributed measures of carbon flux from soil and vegetation across different aspects to quantify the causes and consequences of spatial heterogeneity through time. Given that (i) aspect influences how incoming energy drives evaporative water loss and (ii) seasonality drives temporal patterns of soil moisture recharge, we were able to examine the influence of these processes on CO2 efflux by investigating variation across aspect. We found that aspect was a significant source of spatial heterogeneity in soil CO2 efflux, but the influence varied across seasonal periods. Snow on South-facing aspects melted earlier and yielded higher efflux rates in the spring. However, during summer, North- and South-facing aspects had similar amounts of soil moisture, but soil temperatures were warmer on the North-facing aspect, yielding greater rates of CO2 efflux. Interestingly, aspect did not influence photosynthetic rates. Taken together, we found that physical features of the landscape yielded predictable patterns of levels and phenologies of soil moisture and temperature, but these drivers differentially influenced below- and aboveground sources of carbon exchange. Conducting these spatially distributed measurements are time consuming. Looking forward, we have begun using unmanned aerial vehicles outfitted with thermal and multi-spectral cameras to quantify patterns of water flux, NDVI, needle browning due to moisture stress, and overall phenology in the CZ.

Hydroclimatology of Dual-Peak Annual Cholera Incidence: Insights from a Spatially Explicit Model

NASA Astrophysics Data System (ADS)

Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.

2012-12-01

Cholera incidence in some regions of the Indian subcontinent may exhibit two annual peaks although the main environmental drivers that have been linked to the disease (e.g. sea surface temperature, zooplankton abundance, river discharge) peak once per year during the summer. An empirical hydroclimatological explanation relating cholera transmission to river flows and to the disease spatial spreading has been recently proposed. We specifically support and substantiate mechanistically such hypothesis by means of a spatially explicit model of cholera transmission. Our framework directly accounts for the role of the river network in transporting and redistributing cholera bacteria among human communities as well as for spatial and temporal annual fluctuations of precipitation and river flows. To single out the single out the hydroclimatologic controls on the prevalence patterns in a non-specific geographical context, we first apply the model to Optimal Channel Networks as a general model of hydrological networks. Moreover, we impose a uniform distribution of population. The model is forced by seasonal environmental drivers, namely precipitation, temperature and chlorophyll concentration in the coastal environment, a proxy for Vibrio cholerae concentration. Our results show that these drivers may suffice to generate dual-peak cholera prevalence patterns for proper combinations of timescales involved in pathogen transport, hydrologic variability and disease unfolding. The model explains the possible occurrence of spatial patterns of cholera incidence characterized by a spring peak confined to coastal areas and a fall peak involving inland regions. We then proceed applying the model to the specific settings of Bay of Bengal accounting for the actual river networks (derived from digital terrain map manipulations), the proper distribution of population (estimated from downscaling of census data based on remotely sensed features) and precipitation patterns. Overall our modeling framework suggests insights on how environmental drivers concert the generation of complex spatiotemporal infections and proposes an explanation for the different cholera patterns (dual or single annual peaks) exhibited by regions that share similar hydroclimatological forcings.

Application of hierarchical clustering method to classify of space-time rainfall patterns

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Chang, Tu-Je

2010-05-01

Understanding the local precipitation patterns is essential to the water resources management and flooding mitigation. The precipitation patterns can vary in space and time depending upon the factors from different spatial scales such as local topological changes and macroscopic atmospheric circulation. The spatiotemporal variation of precipitation in Taiwan is significant due to its complex terrain and its location at west pacific and subtropical area, where is the boundary between the pacific ocean and Asia continent with the complex interactions among the climatic processes. This study characterizes local-scale precipitation patterns by classifying the historical space-time precipitation records. We applied the hierarchical ascending clustering method to analyze the precipitation records from 1960 to 2008 at the six rainfall stations located in Lan-yang catchment at the northeast of the island. Our results identify the four primary space-time precipitation types which may result from distinct driving forces from the changes of atmospheric variables and topology at different space-time scales. This study also presents an important application of the statistical downscaling to combine large-scale upper-air circulation with local space-time precipitation patterns.

Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape

NASA Astrophysics Data System (ADS)

Ramírez-Forero, Sandra Carolina; López-Caloca, Alejandra; Silván-Cárdenas, José Luis

2011-11-01

The tropical coastal landscape of Tulum in Quintana Roo, Mexico has a high ecological, economical, social and cultural value, it provides environmental and tourism services at global, national, regional and local levels. The landscape of the area is heterogeneous and presents random fragmentation patterns. In recent years, tourist services of the region has been increased promoting an accelerate expansion of hotels, transportation and recreation infrastructure altering the complex landscape. It is important to understand the environmental dynamics through temporal changes on the spatial patterns and to propose a better management of this ecological area to the authorities. This paper addresses a multi-temporal analysis of land cover changes from 1993 to 2000 in Tulum using Thematic Mapper data acquired by Landsat-5. Two independent methodologies were applied for the analysis of changes in the landscape and for the definition of fragmentation patterns. First, an Iteratively Multivariate Alteration Detection (IR-MAD) algorithm was used to detect and localize land cover change/no-change areas. Second, the post-classification change detection evaluated using the Support Vector Machine (SVM) algorithm. Landscape metrics were calculated from the results of IR-MAD and SVM. The analysis of the metrics indicated, among other things, a higher fragmentation pattern along roadways.

Separation of parallel encoded complex-valued slices (SPECS) from a single complex-valued aliased coil image.

PubMed

Rowe, Daniel B; Bruce, Iain P; Nencka, Andrew S; Hyde, James S; Kociuba, Mary C

2016-04-01

Achieving a reduction in scan time with minimal inter-slice signal leakage is one of the significant obstacles in parallel MR imaging. In fMRI, multiband-imaging techniques accelerate data acquisition by simultaneously magnetizing the spatial frequency spectrum of multiple slices. The SPECS model eliminates the consequential inter-slice signal leakage from the slice unaliasing, while maintaining an optimal reduction in scan time and activation statistics in fMRI studies. When the combined k-space array is inverse Fourier reconstructed, the resulting aliased image is separated into the un-aliased slices through a least squares estimator. Without the additional spatial information from a phased array of receiver coils, slice separation in SPECS is accomplished with acquired aliased images in shifted FOV aliasing pattern, and a bootstrapping approach of incorporating reference calibration images in an orthogonal Hadamard pattern. The aliased slices are effectively separated with minimal expense to the spatial and temporal resolution. Functional activation is observed in the motor cortex, as the number of aliased slices is increased, in a bilateral finger tapping fMRI experiment. The SPECS model incorporates calibration reference images together with coefficients of orthogonal polynomials into an un-aliasing estimator to achieve separated images, with virtually no residual artifacts and functional activation detection in separated images. Copyright © 2015 Elsevier Inc. All rights reserved.

Collagen Organization in Facet Capsular Ligaments Varies With Spinal Region and With Ligament Deformation.

PubMed

Ban, Ehsan; Zhang, Sijia; Zarei, Vahhab; Barocas, Victor H; Winkelstein, Beth A; Picu, Catalin R

2017-07-01

The spinal facet capsular ligament (FCL) is primarily comprised of heterogeneous arrangements of collagen fibers. This complex fibrous structure and its evolution under loading play a critical role in determining the mechanical behavior of the FCL. A lack of analytical tools to characterize the spatial anisotropy and heterogeneity of the FCL's microstructure has limited the current understanding of its structure-function relationships. Here, the collagen organization was characterized using spatial correlation analysis of the FCL's optically obtained fiber orientation field. FCLs from the cervical and lumbar spinal regions were characterized in terms of their structure, as was the reorganization of collagen in stretched cervical FCLs. Higher degrees of intra- and intersample heterogeneity were found in cervical FCLs than in lumbar specimens. In the cervical FCLs, heterogeneity was manifested in the form of curvy patterns formed by collections of collagen fibers or fiber bundles. Tensile stretch, a common injury mechanism for the cervical FCL, significantly increased the spatial correlation length in the stretch direction, indicating an elongation of the observed structural features. Finally, an affine estimation for the change of correlation length under loading was performed which gave predictions very similar to the actual values. These findings provide structural insights for multiscale mechanical analyses of the FCLs from various spinal regions and also suggest methods for quantitative characterization of complex tissue patterns.

Nonlinear Focal Modulation Microscopy.

PubMed

Zhao, Guangyuan; Zheng, Cheng; Kuang, Cuifang; Zhou, Renjie; Kabir, Mohammad M; Toussaint, Kimani C; Wang, Wensheng; Xu, Liang; Li, Haifeng; Xiu, Peng; Liu, Xu

2018-05-11

We demonstrate nonlinear focal modulation microscopy (NFOMM) to achieve superresolution imaging. Traditional approaches to superresolution that utilize point scanning often rely on spatially reducing the size of the emission pattern by directly narrowing (e.g., through minimizing the detection pinhole in Airyscan, Zeiss) or indirectly peeling its outer profiles [e.g., through depleting the outer emission region in stimulated emission depletion (STED) microscopy]. We show that an alternative conceptualization that focuses on maximizing the optical system's frequency shifting ability offers advantages in further improving resolution while reducing system complexity. In NFOMM, a spatial light modulator and a suitably intense laser illumination are used to implement nonlinear focal-field modulation to achieve a transverse spatial resolution of ∼60  nm (∼λ/10). We show that NFOMM is comparable with STED microscopy and suitable for fundamental biology studies, as evidenced in imaging nuclear pore complexes, tubulin and vimentin in Vero cells. Since NFOMM is readily implemented as an add-on module to a laser-scanning microscope, we anticipate wide utility of this new imaging technique.

Nonlinear Focal Modulation Microscopy

NASA Astrophysics Data System (ADS)

Zhao, Guangyuan; Zheng, Cheng; Kuang, Cuifang; Zhou, Renjie; Kabir, Mohammad M.; Toussaint, Kimani C.; Wang, Wensheng; Xu, Liang; Li, Haifeng; Xiu, Peng; Liu, Xu

2018-05-01

We demonstrate nonlinear focal modulation microscopy (NFOMM) to achieve superresolution imaging. Traditional approaches to superresolution that utilize point scanning often rely on spatially reducing the size of the emission pattern by directly narrowing (e.g., through minimizing the detection pinhole in Airyscan, Zeiss) or indirectly peeling its outer profiles [e.g., through depleting the outer emission region in stimulated emission depletion (STED) microscopy]. We show that an alternative conceptualization that focuses on maximizing the optical system's frequency shifting ability offers advantages in further improving resolution while reducing system complexity. In NFOMM, a spatial light modulator and a suitably intense laser illumination are used to implement nonlinear focal-field modulation to achieve a transverse spatial resolution of ˜60 nm (˜λ /10 ). We show that NFOMM is comparable with STED microscopy and suitable for fundamental biology studies, as evidenced in imaging nuclear pore complexes, tubulin and vimentin in Vero cells. Since NFOMM is readily implemented as an add-on module to a laser-scanning microscope, we anticipate wide utility of this new imaging technique.

Spatial Distribution Patterns in the Very Rare and Species-Rich Picea chihuahuana Tree Community (Mexico).

PubMed

Wehenkel, Christian; Brazão-Protázio, João Marcelo; Carrillo-Parra, Artemio; Martínez-Guerrero, José Hugo; Crecente-Campo, Felipe

2015-01-01

The very rare Mexican Picea chihuahuana tree community covers an area of no more than 300 ha in the Sierra Madre Occidental. This special tree community has been the subject of several studies aimed at learning more about the genetic structure and ecology of the species and the potential effects of climate change. The spatial distribution of trees is a result of many ecological processes and can affect the degree of competition between neighbouring trees, tree density, variability in size and distribution, regeneration, survival, growth, mortality, crown formation and the biological diversity within forest communities. Numerous scale-dependent measures have been established in order to describe spatial forest structure. The overall aim of most of these studies has been to obtain data to help design preservation and conservation strategies. In this study, we examined the spatial distribution pattern of trees in the P. chihuahuana tree community in 12 localities, in relation to i) tree stand density, ii) diameter distribution (vertical structure), iii) tree species diversity, iv) geographical latitude and v) tree dominance at a fine scale (in 0.25 ha plots), with the aim of obtaining a better understanding of the complex ecosystem processes and biological diversity. Because of the strongly mixed nature of this tree community, which often produces low population densities of each tree species and random tree fall gaps caused by tree death, we expect aggregated patterns in individual Picea chihuahuana trees and in the P. chihuahuana tree community, repulsive Picea patterns to other tree species and repulsive patterns of young to adult trees. Each location was represented by one plot of 50 x 50 m (0.25 ha) established in the centre of the tree community. The findings demonstrate that the hypothesis of aggregated tree pattern is not applicable to the mean pattern measured by Clark-Evans index, Uniform Angle index and Mean Directional index of the uneven-aged P. chihuahuana trees and P. chihuahuana tree community and but to specific spatial scales measured by the univariate L-function. The spatial distribution pattern of P. chihuahuana trees was found to be independent of patches of other tree species measured by the bivariate L-function. The spatial distribution was not significantly related to tree density, diameter distribution or tree species diversity. The index of Clark and Evans decreased significantly from the southern to northern plots containing all tree species. Self-thinning due to intra and inter-specific competition-induced mortality is probably the main cause of the decrease in aggregation intensity during the course of population development in this tree community. We recommend the use of larger sampling plots (> 0.25 ha) in uneven-aged and species-rich forest ecosystems to detect less obvious, but important, relationships between spatial tree pattern and functioning and diversity in these forests.

Spatial Distribution Patterns in the Very Rare and Species-Rich Picea chihuahuana Tree Community (Mexico)

PubMed Central

Wehenkel, Christian; Brazão-Protázio, João Marcelo; Carrillo-Parra, Artemio; Martínez-Guerrero, José Hugo; Crecente-Campo, Felipe

2015-01-01

The very rare Mexican Picea chihuahuana tree community covers an area of no more than 300 ha in the Sierra Madre Occidental. This special tree community has been the subject of several studies aimed at learning more about the genetic structure and ecology of the species and the potential effects of climate change. The spatial distribution of trees is a result of many ecological processes and can affect the degree of competition between neighbouring trees, tree density, variability in size and distribution, regeneration, survival, growth, mortality, crown formation and the biological diversity within forest communities. Numerous scale-dependent measures have been established in order to describe spatial forest structure. The overall aim of most of these studies has been to obtain data to help design preservation and conservation strategies. In this study, we examined the spatial distribution pattern of trees in the P. chihuahuana tree community in 12 localities, in relation to i) tree stand density, ii) diameter distribution (vertical structure), iii) tree species diversity, iv) geographical latitude and v) tree dominance at a fine scale (in 0.25 ha plots), with the aim of obtaining a better understanding of the complex ecosystem processes and biological diversity. Because of the strongly mixed nature of this tree community, which often produces low population densities of each tree species and random tree fall gaps caused by tree death, we expect aggregated patterns in individual Picea chihuahuana trees and in the P. chihuahuana tree community, repulsive Picea patterns to other tree species and repulsive patterns of young to adult trees. Each location was represented by one plot of 50 x 50 m (0.25 ha) established in the centre of the tree community. The findings demonstrate that the hypothesis of aggregated tree pattern is not applicable to the mean pattern measured by Clark-Evans index, Uniform Angle index and Mean Directional index of the uneven-aged P. chihuahuana trees and P. chihuahuana tree community and but to specific spatial scales measured by the univariate L-function. The spatial distribution pattern of P. chihuahuana trees was found to be independent of patches of other tree species measured by the bivariate L-function. The spatial distribution was not significantly related to tree density, diameter distribution or tree species diversity. The index of Clark and Evans decreased significantly from the southern to northern plots containing all tree species. Self-thinning due to intra and inter-specific competition-induced mortality is probably the main cause of the decrease in aggregation intensity during the course of population development in this tree community. We recommend the use of larger sampling plots (> 0.25 ha) in uneven-aged and species-rich forest ecosystems to detect less obvious, but important, relationships between spatial tree pattern and functioning and diversity in these forests. PMID:26496189

Characterization of spiraling patterns in spatial rock-paper-scissors games.

PubMed

Szczesny, Bartosz; Mobilia, Mauro; Rucklidge, Alastair M

2014-09-01

The spatiotemporal arrangement of interacting populations often influences the maintenance of species diversity and is a subject of intense research. Here, we study the spatiotemporal patterns arising from the cyclic competition between three species in two dimensions. Inspired by recent experiments, we consider a generic metapopulation model comprising "rock-paper-scissors" interactions via dominance removal and replacement, reproduction, mutations, pair exchange, and hopping of individuals. By combining analytical and numerical methods, we obtain the model's phase diagram near its Hopf bifurcation and quantitatively characterize the properties of the spiraling patterns arising in each phase. The phases characterizing the cyclic competition away from the Hopf bifurcation (at low mutation rate) are also investigated. Our analytical approach relies on the careful analysis of the properties of the complex Ginzburg-Landau equation derived through a controlled (perturbative) multiscale expansion around the model's Hopf bifurcation. Our results allow us to clarify when spatial "rock-paper-scissors" competition leads to stable spiral waves and under which circumstances they are influenced by nonlinear mobility.

Networks, narratives and territory in anthropological race classification: towards a more comprehensive historical geography of Europe's culture.

PubMed

McMahon, Richard

2011-01-01

This article aims to integrate discourse analysis of politically instrumental imagined identity geographies with the relational and territorial geography of the communities of praxis and interpretation that produce them. My case study is the international community of nationalist scientists who classified Europe's biological races in the 1820s-1940s. I draw on network analysis, relational geography, historical sociology and the historical turn to problematize empirically how spatial patterns of this community's shifting disciplinary and political coalitions, communication networks and power relations emerged, were structured, persisted, changed, interacted and disappeared. I focus especially on core-periphery relations. I argue that if local historical spatial patterns affect those of later phenomena, geographies like that of European integration should be understood in the context of Europe's complex historical cultural geography. Unlike discourse deconstruction alone, this complementary relational de-essentialization of geography can identify large-scale, enduring associations of cultural patterns as well as cultural flux and ambiguity.

An overview of the floristic richness and conservation of the arid regions of northern Mexico

Treesearch

Laura Arriaga; Elizabeth Moreno; Claudia Aguilar

2005-01-01

The arid and semiarid regions of Northern Mexico harbor diverse, highly endemic, and geographically complex ecosystems. These share topographic and biogeographic similarities that can be used as an analytical framework to assess biodiversity patterns. This study presents the current status of vascular plant inventories for Mexican Aridamerica. The spatial distribution...

An Integrated Theory of Attention and Decision Making in Visual Signal Detection

ERIC Educational Resources Information Center

Smith, Philip L.; Ratcliff, Roger

2009-01-01

The simplest attentional task, detecting a cued stimulus in an otherwise empty visual field, produces complex patterns of performance. Attentional cues interact with backward masks and with spatial uncertainty, and there is a dissociation in the effects of these variables on accuracy and on response time. A computational theory of performance in…

Validation of solar radiation surfaces from MODIS and reanalysis data over topographically complex terrain

Treesearch

Todd A. Schroeder; Robbie Hember; Nicholas C. Coops; Shunlin Liang

2009-01-01

The magnitude and distribution of incoming shortwave solar radiation (SW) has significant influence on the productive capacity of forest vegetation. Models that estimate forest productivity require accurate and spatially explicit radiation surfaces that resolve both long- and short-term temporal climatic patterns and that account for topographic variability of the land...

Lamina-specific contribution of glutamatergic and GABAergic potentials to hippocampal sharp wave-ripple complexes.

PubMed

Schönberger, Jan; Draguhn, Andreas; Both, Martin

2014-01-01

The mammalian hippocampus expresses highly organized patterns of neuronal activity which form a neuronal correlate of spatial memories. These memory-encoding neuronal ensembles form on top of different network oscillations which entrain neurons in a state- and experience-dependent manner. The mechanisms underlying activation, timing and selection of participating neurons are incompletely understood. Here we studied the synaptic mechanisms underlying one prominent network pattern called sharp wave-ripple complexes (SPW-R) which are involved in memory consolidation during sleep. We recorded SPW-R with extracellular electrodes along the different layers of area CA1 in mouse hippocampal slices. Contribution of glutamatergic excitation and GABAergic inhibition, respectively, was probed by local application of receptor antagonists into s. radiatum, pyramidale and oriens. Laminar profiles of field potentials show that GABAergic potentials contribute substantially to sharp waves and superimposed ripple oscillations in s. pyramidale. Inhibitory inputs to s. pyramidale and s. oriens are crucial for action potential timing by ripple oscillations, as revealed by multiunit-recordings in the pyramidal cell layer. Glutamatergic afferents, on the other hand, contribute to sharp waves in s. radiatum where they also evoke a fast oscillation at ~200 Hz. Surprisingly, field ripples in s. radiatum are slightly slower than ripples in s. pyramidale, resulting in a systematic shift between dendritic and somatic oscillations. This complex interplay between dendritic excitation and perisomatic inhibition may be responsible for the precise timing of discharge probability during the time course of SPW-R. Together, our data illustrate a complementary role of spatially confined excitatory and inhibitory transmission during highly ordered network patterns in the hippocampus.

Patterns of Precipitation and Streamflow Responses to Moisture Fluxes during Atmospheric Rivers

NASA Astrophysics Data System (ADS)

Henn, B. M.; Wilson, A. M.; Asgari Lamjiri, M.; Ralph, M.

2017-12-01

Precipitation from landfalling atmospheric rivers (ARs) have been shown to dominate the hydroclimate of many parts of the world. ARs are associated with saturated, neutrally-stable profiles in the lower atmosphere, in which forced ascent by topography induces precipitation. Understanding the spatial and temporal variability of precipitation over complex terrain during AR-driven precipitation is critical for accurate forcing of distributed hydrologic models and streamflow forecasts. Past studies using radar wind profilers and radiosondes have demonstrated predictability of precipitation rates based on upslope water vapor flux over coastal terrain, with certain levels of moisture flux exhibiting the greatest influence on precipitation. Additionally, these relationships have been extended to show that streamflow in turn responds predictably to upslope vapor flux. However, past studies have focused on individual pairs of profilers and precipitation gauges; the question of how orographic precipitation in ARs is distributed spatially over complex terrain, at different topographic scales, is less well known. Here, we examine profiles of atmospheric moisture transport from radiosondes and wind profilers, against a relatively dense network of precipitation gauges, as well as stream gauges, to assess relationships between upslope moisture flux and the spatial response of precipitation and streamflow. We focus on California's Russian River watershed in the 2016-2017 cool season, when regular radiosonde launches were made at two locations during an active sequence of landfalling ARs. We examine how atmospheric water vapor flux results in precipitation patterns across gauges with different topographic relationships to the prevailing moisture-bearing winds, and conduct a similar comparison of runoff volume response from several unimpaired watersheds in the upper Russian watershed, taking into account antecedent soil moisture conditions that influence runoff generation. Finally, we compare observed spatial patterns of precipitation accumulations to those in a topographically-aided gridded precipitation dataset to understand how atmospheric moisture transport may inform methods to downscale precipitation to high resolution for use in hydrologic modeling.

Spatiotemporal patterns of precipitation inferred from streamflow observations across the Sierra Nevada mountain range

NASA Astrophysics Data System (ADS)

Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Newman, Andrew J.; Hughes, Mimi; McGurk, Bruce; Lundquist, Jessica D.

2018-01-01

Given uncertainty in precipitation gauge-based gridded datasets over complex terrain, we use multiple streamflow observations as an additional source of information about precipitation, in order to identify spatial and temporal differences between a gridded precipitation dataset and precipitation inferred from streamflow. We test whether gridded datasets capture across-crest and regional spatial patterns of variability, as well as year-to-year variability and trends in precipitation, in comparison to precipitation inferred from streamflow. We use a Bayesian model calibration routine with multiple lumped hydrologic model structures to infer the most likely basin-mean, water-year total precipitation for 56 basins with long-term (>30 year) streamflow records in the Sierra Nevada mountain range of California. We compare basin-mean precipitation derived from this approach with basin-mean precipitation from a precipitation gauge-based, 1/16° gridded dataset that has been used to simulate and evaluate trends in Western United States streamflow and snowpack over the 20th century. We find that the long-term average spatial patterns differ: in particular, there is less precipitation in the gridded dataset in higher-elevation basins whose aspect faces prevailing cool-season winds, as compared to precipitation inferred from streamflow. In a few years and basins, there is less gridded precipitation than there is observed streamflow. Lower-elevation, southern, and east-of-crest basins show better agreement between gridded and inferred precipitation. Implied actual evapotranspiration (calculated as precipitation minus streamflow) then also varies between the streamflow-based estimates and the gridded dataset. Absolute uncertainty in precipitation inferred from streamflow is substantial, but the signal of basin-to-basin and year-to-year differences are likely more robust. The findings suggest that considering streamflow when spatially distributing precipitation in complex terrain may improve its representation, particularly for basins whose orientations (e.g., windward-facing) are favored for orographic precipitation enhancement.

Advanced analysis of forest fire clustering

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Pereira, Mario; Golay, Jean

2017-04-01

Analysis of point pattern clustering is an important topic in spatial statistics and for many applications: biodiversity, epidemiology, natural hazards, geomarketing, etc. There are several fundamental approaches used to quantify spatial data clustering using topological, statistical and fractal measures. In the present research, the recently introduced multi-point Morisita index (mMI) is applied to study the spatial clustering of forest fires in Portugal. The data set consists of more than 30000 fire events covering the time period from 1975 to 2013. The distribution of forest fires is very complex and highly variable in space. mMI is a multi-point extension of the classical two-point Morisita index. In essence, mMI is estimated by covering the region under study by a grid and by computing how many times more likely it is that m points selected at random will be from the same grid cell than it would be in the case of a complete random Poisson process. By changing the number of grid cells (size of the grid cells), mMI characterizes the scaling properties of spatial clustering. From mMI, the data intrinsic dimension (fractal dimension) of the point distribution can be estimated as well. In this study, the mMI of forest fires is compared with the mMI of random patterns (RPs) generated within the validity domain defined as the forest area of Portugal. It turns out that the forest fires are highly clustered inside the validity domain in comparison with the RPs. Moreover, they demonstrate different scaling properties at different spatial scales. The results obtained from the mMI analysis are also compared with those of fractal measures of clustering - box counting and sand box counting approaches. REFERENCES Golay J., Kanevski M., Vega Orozco C., Leuenberger M., 2014: The multipoint Morisita index for the analysis of spatial patterns. Physica A, 406, 191-202. Golay J., Kanevski M. 2015: A new estimator of intrinsic dimension based on the multipoint Morisita index. Pattern Recognition, 48, 4070-4081.

Chemical morphogenesis: recent experimental advances in reaction–diffusion system design and control

PubMed Central

Szalai, István; Cuiñas, Daniel; Takács, Nándor; Horváth, Judit; De Kepper, Patrick

2012-01-01

In his seminal 1952 paper, Alan Turing predicted that diffusion could spontaneously drive an initially uniform solution of reacting chemicals to develop stable spatially periodic concentration patterns. It took nearly 40 years before the first two unquestionable experimental demonstrations of such reaction–diffusion patterns could be made in isothermal single phase reaction systems. The number of these examples stagnated for nearly 20 years. We recently proposed a design method that made their number increase to six in less than 3 years. In this report, we formally justify our original semi-empirical method and support the approach with numerical simulations based on a simple but realistic kinetic model. To retain a number of basic properties of real spatial reactors but keep calculations to a minimal complexity, we introduce a new way to collapse the confined spatial direction of these reactors. Contrary to similar reduced descriptions, we take into account the effect of the geometric size in the confinement direction and the influence of the differences in the diffusion coefficient on exchange rates of species with their feed environment. We experimentally support the method by the observation of stationary patterns in red-ox reactions not based on oxihalogen chemistry. Emphasis is also brought on how one of these new systems can process different initial conditions and memorize them in the form of localized patterns of different geometries. PMID:23919126

Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

PubMed Central

Goovaerts, Pierre; Jacquez, Geoffrey M

2004-01-01

Background Complete Spatial Randomness (CSR) is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new methodology allows one to identify geographic pattern above and beyond background variation. The implementation of this approach in spatial statistical software will facilitate the detection of spatial disparities in mortality rates, establishing the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. It will allow researchers to systematically evaluate how sensitive their results are to assumptions implicit under alternative null hypotheses. PMID:15272930

Microparticles controllable accumulation, arrangement, and spatial shaping performed by tapered-fiber-based laser-induced convection flow.

PubMed

Zhang, Yu; Lei, Jiaojie; Zhang, Yaxun; Liu, Zhihai; Zhang, Jianzhong; Yang, Xinghua; Yang, Jun; Yuan, Libo

2017-10-30

The ability to arrange cells and/or microparticles into the desired pattern is critical in biological, chemical, and metamaterial studies and other applications. Researchers have developed a variety of patterning techniques, which either have a limited capacity to simultaneously trap massive particles or lack the spatial resolution necessary to manipulate individual particle. Several approaches have been proposed that combine both high spatial selectivity and high throughput simultaneously. However, those methods are complex and difficult to fabricate. In this article, we propose and demonstrate a simple method that combines the laser-induced convection flow and fiber-based optical trapping methods to perform both regular and special spatial shaping arrangement. Essentially, we combine a light field with a large optical intensity gradient distribution and a thermal field with a large temperature gradient distribution to perform the microparticles shaping arrangement. The tapered-fiber-based laser-induced convection flow provides not only the batch manipulation of massive particles, but also the finer manipulation of special one or several particles, which break out the limit of single-fiber-based massive/individual particles photothermal manipulation. The combination technique allows for microparticles quick accumulation, single-layer and multilayer arrangement; special spatial shaping arrangement/adjustment, and microparticles sorting.

Landsat classification of surface-water presence during multiple years to assess response of playa wetlands to climatic variability across the Great Plains Landscape Conservation Cooperative region

USGS Publications Warehouse

Manier, Daniel J.; Rover, Jennifer R.

2018-02-15

To improve understanding of the distribution of ecologically important, ephemeral wetland habitats across the Great Plains, the occurrence and distribution of surface water in playa wetland complexes were documented for four different years across the Great Plains Landscape Conservation Cooperative (GPLCC) region. This information is important because it informs land and wildlife managers about the timing and location of habitat availability. Data with an accurate timestamp that indicate the presence of water, the percent of the area inundated with water, and the spatial distribution of playa wetlands with water are needed for a host of resource inventory, monitoring, and research applications. For example, the distribution of inundated wetlands forms the spatial pattern of available habitat for resident shorebirds and water birds, stop-over habitats for migratory birds, connectivity and clustering of wetland habitats, and surface waters that recharge the Ogallala aquifer; there is considerable variability in the distribution of playa wetlands holding water through time. Documentation of these spatially and temporally intricate processes, here, provides data required to assess connections between inundation and multiple environmental drivers, such as climate, land use, soil, and topography. Climate drivers are understood to interact with land cover, land use and soil attributes in determining the amount of water that flows overland into playa wetlands. Results indicated significant spatial variability represented by differences in the percent of playas inundated among States within the GPLCC. Further, analysis-of-variance comparison of differences in inundation between years showed significant differences in all cases. Although some connections with seasonal moisture patterns may be observed, the complex spatial-temporal gradients of precipitation, temperature, soils, and land use need to be combined as covariates in multivariate models to effectively account for these patterns. We demonstrate the feasibility of using classification of Landsat satellite imagery to describe playa-wetland inundation across years and seasons. Evaluating classifications representing only 4 years of imagery, we found significant year-to-year and state-to-state differences in inundation rates.

The isolation of spatial patterning modes in a mathematical model of juxtacrine cell signalling.

PubMed

O'Dea, R D; King, J R

2013-06-01

Juxtacrine signalling mechanisms are known to be crucial in tissue and organ development, leading to spatial patterns in gene expression. We investigate the patterning behaviour of a discrete model of juxtacrine cell signalling due to Owen & Sherratt (1998, Mathematical modelling of juxtacrine cell signalling. Math. Biosci., 153, 125-150) in which ligand molecules, unoccupied receptors and bound ligand-receptor complexes are modelled. Feedback between the ligand and receptor production and the level of bound receptors is incorporated. By isolating two parameters associated with the feedback strength and employing numerical simulation, linear stability and bifurcation analysis, the pattern-forming behaviour of the model is analysed under regimes corresponding to lateral inhibition and induction. Linear analysis of this model fails to capture the patterning behaviour exhibited in numerical simulations. Via bifurcation analysis, we show that since the majority of periodic patterns fold subcritically from the homogeneous steady state, a wide variety of stable patterns exists at a given parameter set, providing an explanation for this failure. The dominant pattern is isolated via numerical simulation. Additionally, by sampling patterns of non-integer wavelength on a discrete mesh, we highlight a disparity between the continuous and discrete representations of signalling mechanisms: in the continuous case, patterns of arbitrary wavelength are possible, while sampling such patterns on a discrete mesh leads to longer wavelength harmonics being selected where the wavelength is rational; in the irrational case, the resulting aperiodic patterns exhibit 'local periodicity', being constructed from distorted stable shorter wavelength patterns. This feature is consistent with experimentally observed patterns, which typically display approximate short-range periodicity with defects.

Disturbance Impacts on Thermal Hot Spots and Hot Moments at the Peatland-Atmosphere Interface

NASA Astrophysics Data System (ADS)

Leonard, R. M.; Kettridge, N.; Devito, K. J.; Petrone, R. M.; Mendoza, C. A.; Waddington, J. M.; Krause, S.

2018-01-01

Soil-surface temperature acts as a master variable driving nonlinear terrestrial ecohydrological, biogeochemical, and micrometeorological processes, inducing short-lived or spatially isolated extremes across heterogeneous landscape surfaces. However, subcanopy soil-surface temperatures have been, to date, characterized through isolated, spatially discrete measurements. Using spatially complex forested northern peatlands as an exemplar ecosystem, we explore the high-resolution spatiotemporal thermal behavior of this critical interface and its response to disturbances by using Fiber-Optic Distributed Temperature Sensing. Soil-surface thermal patterning was identified from 1.9 million temperature measurements under undisturbed, trees removed and vascular subcanopy removed conditions. Removing layers of the structurally diverse vegetation canopy not only increased mean temperatures but it shifted the spatial and temporal distribution, range, and longevity of thermal hot spots and hot moments. We argue that linking hot spots and/or hot moments with spatially variable ecosystem processes and feedbacks is key for predicting ecosystem function and resilience.

Receptive fields of locust brain neurons are matched to polarization patterns of the sky.

PubMed

Bech, Miklós; Homberg, Uwe; Pfeiffer, Keram

2014-09-22

Many animals, including insects, are able to use celestial cues as a reference for spatial orientation and long-distance navigation [1]. In addition to direct sunlight, the chromatic gradient of the sky and its polarization pattern are suited to serve as orientation cues [2-5]. Atmospheric scattering of sunlight causes a regular pattern of E vectors in the sky, which are arranged along concentric circles around the sun [5, 6]. Although certain insects rely predominantly on sky polarization for spatial orientation [7], it has been argued that detection of celestial E vector orientation may not suffice to differentiate between solar and antisolar directions [8, 9]. We show here that polarization-sensitive (POL) neurons in the brain of the desert locust Schistocerca gregaria can overcome this ambiguity. Extracellular recordings from POL units in the central complex and lateral accessory lobes revealed E vector tunings arranged in concentric circles within large receptive fields, matching the sky polarization pattern at certain solar positions. Modeling of neuronal responses under an idealized sky polarization pattern (Rayleigh sky) suggests that these "matched filter" properties allow locusts to unambiguously determine the solar azimuth by relying solely on the sky polarization pattern for compass navigation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Grid cells form a global representation of connected environments.

PubMed

Carpenter, Francis; Manson, Daniel; Jeffery, Kate; Burgess, Neil; Barry, Caswell

2015-05-04

The firing patterns of grid cells in medial entorhinal cortex (mEC) and associated brain areas form triangular arrays that tessellate the environment [1, 2] and maintain constant spatial offsets to each other between environments [3, 4]. These cells are thought to provide an efficient metric for navigation in large-scale space [5-8]. However, an accurate and universal metric requires grid cell firing patterns to uniformly cover the space to be navigated, in contrast to recent demonstrations that environmental features such as boundaries can distort [9-11] and fragment [12] grid patterns. To establish whether grid firing is determined by local environmental cues, or provides a coherent global representation, we recorded mEC grid cells in rats foraging in an environment containing two perceptually identical compartments connected via a corridor. During initial exposures to the multicompartment environment, grid firing patterns were dominated by local environmental cues, replicating between the two compartments. However, with prolonged experience, grid cell firing patterns formed a single, continuous representation that spanned both compartments. Thus, we provide the first evidence that in a complex environment, grid cell firing can form the coherent global pattern necessary for them to act as a metric capable of supporting large-scale spatial navigation. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Grid Cells Form a Global Representation of Connected Environments

PubMed Central

Carpenter, Francis; Manson, Daniel; Jeffery, Kate; Burgess, Neil; Barry, Caswell

2015-01-01

Summary The firing patterns of grid cells in medial entorhinal cortex (mEC) and associated brain areas form triangular arrays that tessellate the environment [1, 2] and maintain constant spatial offsets to each other between environments [3, 4]. These cells are thought to provide an efficient metric for navigation in large-scale space [5–8]. However, an accurate and universal metric requires grid cell firing patterns to uniformly cover the space to be navigated, in contrast to recent demonstrations that environmental features such as boundaries can distort [9–11] and fragment [12] grid patterns. To establish whether grid firing is determined by local environmental cues, or provides a coherent global representation, we recorded mEC grid cells in rats foraging in an environment containing two perceptually identical compartments connected via a corridor. During initial exposures to the multicompartment environment, grid firing patterns were dominated by local environmental cues, replicating between the two compartments. However, with prolonged experience, grid cell firing patterns formed a single, continuous representation that spanned both compartments. Thus, we provide the first evidence that in a complex environment, grid cell firing can form the coherent global pattern necessary for them to act as a metric capable of supporting large-scale spatial navigation. PMID:25913404

Boundary-driven anomalous spirals in oscillatory media

NASA Astrophysics Data System (ADS)

Kessler, David A.; Levine, Herbert

2017-06-01

We study a heretofore ignored class of spiral patterns in oscillatory media as characterized by the complex Landau-Ginzburg model. These spirals emerge from modulating the growth rate as a function of r, thereby turning off the instability at large r. They are uniquely determined by matching to this outer condition, lifting a degeneracy in the set of steady-state solutions of the original equations. Unlike the well-studied spiral which acts as a wave source, has a simple core structure and is insensitive to the details of the boundary on which no-flux conditions are imposed, these new spirals are wave sinks, have non-monotonic wavefront curvature near the core, and can be patterned by the form of the spatial boundary. We predict that these anomalous spirals could be produced in nonlinear optics experiments via spatially modulating the gain of the medium.

Trading strategy based on dynamic mode decomposition: Tested in Chinese stock market

NASA Astrophysics Data System (ADS)

Cui, Ling-xiao; Long, Wen

2016-11-01

Dynamic mode decomposition (DMD) is an effective method to capture the intrinsic dynamical modes of complex system. In this work, we adopt DMD method to discover the evolutionary patterns in stock market and apply it to Chinese A-share stock market. We design two strategies based on DMD algorithm. The strategy which considers only timing problem can make reliable profits in a choppy market with no prominent trend while fails to beat the benchmark moving-average strategy in bull market. After considering the spatial information from spatial-temporal coherent structure of DMD modes, we improved the trading strategy remarkably. Then the DMD strategies profitability is quantitatively evaluated by performing SPA test to correct the data-snooping effect. The results further prove that DMD algorithm can model the market patterns well in sideways market.

A Spatial Probit Econometric Model of Land Change: The Case of Infrastructure Development in Western Amazonia, Peru

PubMed Central

Arima, E. Y.

2016-01-01

Tropical forests are now at the center stage of climate mitigation policies worldwide given their roles as sources of carbon emissions resulting from deforestation and forest degradation. Although the international community has created mechanisms such as REDD+ to reduce those emissions, developing tropical countries continue to invest in infrastructure development in an effort to spur economic growth. Construction of roads in particular is known to be an important driver of deforestation. This article simulates the impact of road construction on deforestation in Western Amazonia, Peru, and quantifies the amount of carbon emissions associated with projected deforestation. To accomplish this objective, the article adopts a Bayesian probit land change model in which spatial dependencies are defined between regions or groups of pixels instead of between individual pixels, thereby reducing computational requirements. It also compares and contrasts the patterns of deforestation predicted by both spatial and non-spatial probit models. The spatial model replicates complex patterns of deforestation whereas the non-spatial model fails to do so. In terms of policy, both models suggest that road construction will increase deforestation by a modest amount, between 200–300 km2. This translates into aboveground carbon emissions of 1.36 and 1.85 x 106 tons. However, recent introduction of palm oil in the region serves as a cautionary example that the models may be underestimating the impact of roads. PMID:27010739

A Spatial Probit Econometric Model of Land Change: The Case of Infrastructure Development in Western Amazonia, Peru.

PubMed

Arima, E Y

2016-01-01

Tropical forests are now at the center stage of climate mitigation policies worldwide given their roles as sources of carbon emissions resulting from deforestation and forest degradation. Although the international community has created mechanisms such as REDD+ to reduce those emissions, developing tropical countries continue to invest in infrastructure development in an effort to spur economic growth. Construction of roads in particular is known to be an important driver of deforestation. This article simulates the impact of road construction on deforestation in Western Amazonia, Peru, and quantifies the amount of carbon emissions associated with projected deforestation. To accomplish this objective, the article adopts a Bayesian probit land change model in which spatial dependencies are defined between regions or groups of pixels instead of between individual pixels, thereby reducing computational requirements. It also compares and contrasts the patterns of deforestation predicted by both spatial and non-spatial probit models. The spatial model replicates complex patterns of deforestation whereas the non-spatial model fails to do so. In terms of policy, both models suggest that road construction will increase deforestation by a modest amount, between 200-300 km2. This translates into aboveground carbon emissions of 1.36 and 1.85 x 106 tons. However, recent introduction of palm oil in the region serves as a cautionary example that the models may be underestimating the impact of roads.

The Transcriptional Regulator CBP Has Defined Spatial Associations within Interphase Nuclei

PubMed Central

McManus, Kirk J; Stephens, David A; Adams, Niall M; Islam, Suhail A; Freemont, Paul S; Hendzel, Michael J

2006-01-01

It is becoming increasingly clear that nuclear macromolecules and macromolecular complexes are compartmentalized through binding interactions into an apparent three-dimensionally ordered structure. This ordering, however, does not appear to be deterministic to the extent that chromatin and nonchromatin structures maintain a strict 3-D arrangement. Rather, spatial ordering within the cell nucleus appears to conform to stochastic rather than deterministic spatial relationships. The stochastic nature of organization becomes particularly problematic when any attempt is made to describe the spatial relationship between proteins involved in the regulation of the genome. The CREB–binding protein (CBP) is one such transcriptional regulator that, when visualised by confocal microscopy, reveals a highly punctate staining pattern comprising several hundred individual foci distributed within the nuclear volume. Markers for euchromatic sequences have similar patterns. Surprisingly, in most cases, the predicted one-to-one relationship between transcription factor and chromatin sequence is not observed. Consequently, to understand whether spatial relationships that are not coincident are nonrandom and potentially biologically important, it is necessary to develop statistical approaches. In this study, we report on the development of such an approach and apply it to understanding the role of CBP in mediating chromatin modification and transcriptional regulation. We have used nearest-neighbor distance measurements and probability analyses to study the spatial relationship between CBP and other nuclear subcompartments enriched in transcription factors, chromatin, and splicing factors. Our results demonstrate that CBP has an order of spatial association with other nuclear subcompartments. We observe closer associations between CBP and RNA polymerase II–enriched foci and SC35 speckles than nascent RNA or specific acetylated histones. Furthermore, we find that CBP has a significantly higher probability of being close to its known in vivo substrate histone H4 lysine 5 compared with the closely related H4 lysine 12. This study demonstrates that complex relationships not described by colocalization exist in the interphase nucleus and can be characterized and quantified. The subnuclear distribution of CBP is difficult to reconcile with a model where chromatin organization is the sole determinant of the nuclear organization of proteins that regulate transcription but is consistent with a close link between spatial associations and nuclear functions. PMID:17054391

Nanoscale Spatial Organization of Prokaryotic Cells Studied by Super-Resolution Optical Microscopy

NASA Astrophysics Data System (ADS)

McEvoy, Andrea Lynn

All cells spatially organize their interiors, and this arrangement is necessary for cell viability. Until recently, it was believed that only eukaryotic cells spatially segregate their components. However, it is becoming increasingly clear that bacteria also assemble their proteins into complex patterns. In eukaryotic cells, spatial organization arises from membrane bound organelles as well as motor transport proteins which can move cargos within the cell. To date, there are no known motor transport proteins in bacteria and most microbes lack membrane bound organelles, so it remains a mystery how bacterial spatial organization emerges. In hind-sight it is not surprising that bacteria also exhibit complex spatial organization considering much of what we have learned about the basic processes that take place in all cells, such as transcription and translation was first discovered in prokaryotic cells. Perhaps the fundamental principles that govern spatial organization in prokaryotic cells may be applicable in eukaryotic cells as well. In addition, bacteria are attractive model organism for spatial organization studies because they are genetically tractable, grow quickly and much biochemical and structural data is known about them. A powerful tool for observing spatial organization in cells is the fluorescence microscope. By specifically tagging a protein of interest with a fluorescent probe, it is possible to examine how proteins organize and dynamically assemble inside cells. A significant disadvantage of this technology is its spatial resolution (approximately 250 nm laterally and 500 nm axially). This limitation on resolution causes closely spaced proteins to look blurred making it difficult to observe the fine structure within the complexes. This resolution limit is especially problematic within small cells such as bacteria. With the recent invention of new optical microscopies, we now can surpass the existing limits of fluorescence imaging. In some cases, we can now see individual proteins inside of large complexes or observe structures with ten times the resolution of conventional imaging. These techniques are known as super-resolution microscopes. In this dissertation, I use super-resolution microscopes to understand how a model microbe, Escherichia coli, assembles complex protein structures. I focus on two spatially organized systems, the chemotaxis network and the cell division machinery. These assembly mechanisms could be general mechanisms for protein assembly in all organisms. I also characterize new fluorescent probes for use in multiple super-resolution imaging modalities and discuss the practicalities of using different super-resolution microscopes. The chemotaxis network in E. coli is the best understood signal transduction network in biology. Chemotaxis receptors cluster into complexes of thousands of proteins located at the cell poles and are used to move bacteria towards favorable stimuli in the environment. In these dense clusters, the receptors can bind each other and communicate to filter out noise and amplify weak signals. It is surprising that chemotaxis receptors are spatially segregated and the mechanism for polar localization of these complexes remains unclear. Using data from PALM images, we develop a model to understand how bacteria organize their receptors into large clusters. The model, stochastic cluster nucleation, is surprising in that is generates micron-scale periodic patterns without the need for accessory proteins to provide scaffolding or active transport. This model may be a general mechanism that cells utilize to organize small and large complexes of proteins. During cell division, E. coli must elongate, replicate its DNA and position its components properly prior to binary fission. Prior to septum formation, a ubiquitous protein called FtsZ, assembles into a ring at mid-cell (Z-ring) which constricts during cell division and recruits the remaining proteins necessary for cytokinesis. Though many details have been revealed about FtsZ, the detailed in vivo structure of the Z-ring is not well understood, and many questions remain about how ring constriction occurs. Using multiple super-resolution imaging modalities, in combination with conventional time-lapse fluorescence imaging, we show that the Z-ring does not form a long uniform filament around the circumference of the bacterium. We detail how this structure changes during division and how removal of proteins that help to position FtsZ affects the Z-ring as it proceeds through cytokinesis. Ultimately we present a simple model for Z-ring constriction during division.

Environmental drivers of spatial patterns of topsoil nitrogen and phosphorus under monsoon conditions in a complex terrain of South Korea

PubMed Central

Choi, Kwanghun; Spohn, Marie; Park, Soo Jin; Huwe, Bernd; Ließ, Mareike

2017-01-01

Nitrogen (N) and phosphorus (P) in topsoils are critical for plant nutrition. Relatively little is known about the spatial patterns of N and P in the organic layer of mountainous landscapes. Therefore, the spatial distributions of N and P in both the organic layer and the A horizon were analyzed using a light detection and ranging (LiDAR) digital elevation model and vegetation metrics. The objective of the study was to analyze the effect of vegetation and topography on the spatial patterns of N and P in a small watershed covered by forest in South Korea. Soil samples were collected using the conditioned latin hypercube method. LiDAR vegetation metrics, the normalized difference vegetation index (NDVI), and terrain parameters were derived as predictors. Spatial explicit predictions of N/P ratios were obtained using a random forest with uncertainty analysis. We tested different strategies of model validation (repeated 2-fold to 20-fold and leave-one-out cross validation). Repeated 10-fold cross validation was selected for model validation due to the comparatively high accuracy and low variance of prediction. Surface curvature was the best predictor of P contents in the organic layer and in the A horizon, while LiDAR vegetation metrics and NDVI were important predictors of N in the organic layer. N/P ratios increased with surface curvature and were higher on the convex upper slope than on the concave lower slope. This was due to P enrichment of the soil on the lower slope and a more even spatial distribution of N. Our digital soil maps showed that the topsoils on the upper slopes contained relatively little P. These findings are critical for understanding N and P dynamics in mountainous ecosystems. PMID:28837590

Modeling the Land Use/Cover Change in an Arid Region Oasis City Constrained by Water Resource and Environmental Policy Change using Cellular Automata Model

NASA Astrophysics Data System (ADS)

Hu, X.; Li, X.; Lu, L.

2017-12-01

Land use/cover change (LUCC) is an important subject in the research of global environmental change and sustainable development, while spatial simulation on land use/cover change is one of the key content of LUCC and is also difficult due to the complexity of the system. The cellular automata (CA) model had an irreplaceable role in simulating of land use/cover change process due to the powerful spatial computing power. However, the majority of current CA land use/cover models were binary-state model that could not provide more general information about the overall spatial pattern of land use/cover change. Here, a multi-state logistic-regression-based Markov cellular automata (MLRMCA) model and a multi-state artificial-neural-network-based Markov cellular automata (MANNMCA) model were developed and were used to simulate complex land use/cover evolutionary process in an arid region oasis city constrained by water resource and environmental policy change, the Zhangye city during the period of 1990-2010. The results indicated that the MANNMCA model was superior to MLRMCA model in simulated accuracy. These indicated that by combining the artificial neural network with CA could more effectively capture the complex relationships between the land use/cover change and a set of spatial variables. Although the MLRMCA model were also some advantages, the MANNMCA model was more appropriate for simulating complex land use/cover dynamics. The two proposed models were effective and reliable, and could reflect the spatial evolution of regional land use/cover changes. These have also potential implications for the impact assessment of water resources, ecological restoration, and the sustainable urban development in arid areas.

Rule-based spatial modeling with diffusing, geometrically constrained molecules.

PubMed

Gruenert, Gerd; Ibrahim, Bashar; Lenser, Thorsten; Lohel, Maiko; Hinze, Thomas; Dittrich, Peter

2010-06-07

We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly.

Rule-based spatial modeling with diffusing, geometrically constrained molecules

PubMed Central

2010-01-01

Background We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Results Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. Conclusions We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly. PMID:20529264

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.

Spatial and Temporal Microbial Patterns in a Tropical Macrotidal Estuary Subject to Urbanization

PubMed Central

Kaestli, Mirjam; Skillington, Anna; Kennedy, Karen; Majid, Matthew; Williams, David; McGuinness, Keith; Munksgaard, Niels; Gibb, Karen

2017-01-01

Darwin Harbour in northern Australia is an estuary in the wet-dry tropics subject to increasing urbanization with localized water quality degradation due to increased nutrient loads from urban runoff and treated sewage effluent. Tropical estuaries are poorly studied compared to temperate systems and little is known about the microbial community-level response to nutrients. We aimed to examine the spatial and temporal patterns of the bacterial community and its association with abiotic factors. Since Darwin Harbour is macrotidal with strong seasonal patterns and mixing, we sought to determine if a human impact signal was discernible in the microbiota despite the strong hydrodynamic forces. Adopting a single impact–double reference design, we investigated the bacterial community using next-generation sequencing of the 16S rRNA gene from water and sediment from reference creeks and creeks affected by effluent and urban runoff. Samples were collected over two years during neap and spring tides, in the dry and wet seasons. Temporal drivers, namely seasons and tides had the strongest relationship to the water microbiota, reflecting the macrotidal nature of the estuary and its location in the wet-dry tropics. The neap-tide water microbiota provided the clearest spatial resolution while the sediment microbiota reflected current and past water conditions. Differences in patterns of the microbiota between different parts of the harbor reflected the harbor's complex hydrodynamics and bathymetry. Despite these variations, a microbial signature was discernible relating to specific effluent sources and urban runoff, and the composite of nutrient levels accounted for the major part of the explained variation in the microbiota followed by salinity. Our results confirm an overall good water quality but they also reflect the extent of some hypereutrophic areas. Our results show that the microbiota is a sensitive indicator to assess ecosystem health even in this dynamic and complex ecosystem. PMID:28751882

Using high resolution aridity and drainage position data to better predict rainfall-runoff relationships in complex upland topography

NASA Astrophysics Data System (ADS)

Metzen, D.; Sheridan, G. J.; Benyon, R. G.; Lane, P. N. J.

2015-12-01

In topographically complex terrain, the interaction of aspect-dependent solar exposure and drainage-position-dependent flow accumulation results in energy and water partitioning that is highly spatially variable. Catchment scale rainfall-runoff relationships are dependent on these smaller scale spatial patterns. However, there remains considerable uncertainty as to how to represent this smaller scale variability within lumped parameter, catchment scale rainfall-runoff models. In this study we aim to measure and represent the key interactions between aridity and drainage position in complex terrain to inform the development of simple catchment-scale hydrologic model parameters. Six measurement plots were setup on opposing slopes in an east-west facing eucalypt forest headwater catchment. The field sites are spanning three drainage positions with two contrasting aridity indices each, while minimizing variations in other factors, e.g. geology and weather patterns. Sapflow, soil water content (SWC) and throughfall were continuously monitored on two convergent hillslopes with similar size (1.3 and 1.6ha) but contrasting aspects (north and south). Soil depth varied from 0.6m at the topslope to >2m at the bottomslope positions. Maximum tree heights ranged from 16.2m to 36.9m on the equator-facing slope and from 30.1m to 45.5m on the pole-facing slope, with height decreasing upslope on both aspects. Two evapotranspiration (ET) patterns emerged in relation to aridity and drainage position. On the equator-facing slope (AI~ 2.1), seasonal understorey and overstorey ET patterns were in sync, whereas on the pole-facing slope (AI~1.5) understorey ET showed larger seasonal fluctuations than overstorey ET. Seasonal ET patterns and competition between soil evaporation and root water uptake lead to distinct differences in profile SWC across the sites, likely caused by depletion from different depths. Topsoil water content on equator-facing slopes was generally lower and responded more rapidly to rainfall pulses than on pole-facing slopes. Future work will focus on how observed ET and SWC patterns in relation to aridity and drainage position can be implemented into a simplistic modelling framework.

Unique Temporal Expression of Triplicated Long-Wavelength Opsins in Developing Butterfly Eyes

PubMed Central

Arikawa, Kentaro; Iwanaga, Tomoyuki; Wakakuwa, Motohiro; Kinoshita, Michiyo

2017-01-01

Following gene duplication events, the expression patterns of the resulting gene copies can often diverge both spatially and temporally. Here we report on gene duplicates that are expressed in distinct but overlapping patterns, and which exhibit temporally divergent expression. Butterflies have sophisticated color vision and spectrally complex eyes, typically with three types of heterogeneous ommatidia. The eyes of the butterfly Papilio xuthus express two green- and one red-absorbing visual pigment, which came about via gene duplication events, in addition to one ultraviolet (UV)- and one blue-absorbing visual pigment. We localized mRNAs encoding opsins of these visual pigments in developing eye disks throughout the pupal stage. The mRNAs of the UV and blue opsin are expressed early in pupal development (pd), specifying the type of the ommatidium in which they appear. Red sensitive photoreceptors first express a green opsin mRNA, which is replaced later by the red opsin mRNA. Broadband photoreceptors (that coexpress the green and red opsins) first express the green opsin mRNA, later change to red opsin mRNA and finally re-express the green opsin mRNA in addition to the red mRNA. Such a unique temporal and spatial expression pattern of opsin mRNAs may reflect the evolution of visual pigments and provide clues toward understanding how the spectrally complex eyes of butterflies evolved. PMID:29238294

Chimera patterns in the Kuramoto-Battogtokh model

NASA Astrophysics Data System (ADS)

Smirnov, Lev; Osipov, Grigory; Pikovsky, Arkady

2017-02-01

Kuramoto and Battogtokh (2002 Nonlinear Phenom. Complex Syst. 5 380) discovered chimera states represented by stable coexisting synchrony and asynchrony domains in a lattice of coupled oscillators. After a reformulation in terms of a local order parameter, the problem can be reduced to partial differential equations. We find uniformly rotating, spatially periodic chimera patterns as solutions of a reversible ordinary differential equation, and demonstrate a plethora of such states. In the limit of neutral coupling they reduce to analytical solutions in the form of one- and two-point chimera patterns as well as localized chimera solitons. Patterns at weakly attracting coupling are characterized by virtue of a perturbative approach. Stability analysis reveals that only the simplest chimeras with one synchronous region are stable.

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.

Temporal and spatial complexity of maternal thermoregulation in tropical pythons.

PubMed

Stahlschmidt, Zachary Ross; Shine, Richard; Denardo, Dale F

2012-01-01

Parental care is a widespread adaptation that evolved independently in a broad range of taxa. Although the dynamics by which two parents meet the developmental needs of offspring are well studied in birds, we lack understanding about the temporal and spatial complexity of parental care in taxa exhibiting female-only care, the predominant mode of parental care. Thus, we examined the behavioral and physiological mechanisms by which female water pythons Liasis fuscus meet a widespread developmental need (thermoregulation) in a natural setting. Although female L. fuscus were not facultatively thermogenic, they did use behaviors on multiple spatial scales (e.g., shifts in egg-brooding postures and surface activity patterns) to balance the thermal needs of their offspring throughout reproduction (gravidity and egg brooding). Maternal behaviors in L. fuscus varied by stage within reproduction and were mediated by interindividual variation in body size and fecundity. Female pythons with relatively larger clutch sizes were cooler during egg brooding, suggesting a trade-off between reproductive quantity (size of clutch) and quality (developmental temperature). In nature, caregiving parents of all taxa must navigate both extrinsic factors (temporal and spatial complexity) and intrinsic factors (body size and fecundity) to meet the needs of their offspring. Our study used a comprehensive approach that can be used as a general template for future research examining the dynamics by which parents meet other developmental needs (e.g., predation risk or energy balance).

The Spatial Structure of Planform Migration - Curvature Relation of Meandering Rivers

NASA Astrophysics Data System (ADS)

Guneralp, I.; Rhoads, B. L.

2005-12-01

Planform dynamics of meandering rivers have been of fundamental interest to fluvial geomorphologists and engineers because of the intriguing complexity of these dynamics, the role of planform change in floodplain development and landscape evolution, and the economic and social consequences of bank erosion and channel migration. Improved understanding of the complex spatial structure of planform change and capacity to predict these changes are important for effective stream management, engineering and restoration. The planform characteristics of a meandering river channel are integral to its planform dynamics. Active meandering rivers continually change their positions and shapes as a consequence of hydraulic forces exerted on the channel banks and bed, but as the banks and bed change through sediment transport, so do the hydraulic forces. Thus far, this complex feedback between form and process is incompletely understood, despite the fact that the characteristics and the dynamics of meandering rivers have been studied extensively. Current theoretical models aimed at predicting planform dynamics relate rates of meander migration to local and upstream planform curvature where weighting of the influence of curvature on migration rate decays exponentially over distance. This theoretical relation, however, has not been rigorously evaluated empirically. Furthermore, although models based on exponential-weighting of curvature effects yield fairly realistic predictions of meander migration, such models are incapable of reproducing complex forms of bend development, such as double heading or compound looping. This study presents the development of a new methodology based on parametric cubic spline interpolation for the characterization of channel planform and the planform curvature of meandering rivers. The use of continuous mathematical functions overcomes the reliance on bend-averaged values or piece-wise discrete approximations of planform curvature - a major limitation of previous studies. Continuous curvature series can be related to measured rates of lateral migration to explore empirically the relationship between spatially extended curvature and local bend migration. The methodology is applied to a study reach along a highly sinuous section of the Embarras River in Illinois, USA, which contains double-headed asymmetrical loops. To identify patterns of channel planform and rates of lateral migration for a study reach along Embarrass River in central Illinois, geographical information systems analysis of historical aerial photography over a period from 1936 to 1998 was conducted. Results indicate that parametric cubic spline interpolation provides excellent characterization of the complex planforms and planform curvatures of meandering rivers. The findings also indicate that the spatial structure of migration rate-curvature relation may be more complex than a simple exponential distance-decay function. The study represents a first step toward unraveling the spatial structure of planform evolution of meandering rivers and for developing models of planform dynamics that accurately relate spatially extended patterns of channel curvature to local rates of lateral migration. Such knowledge is vital for improving the capacity to accurately predict planform change of meandering rivers.

Multicollinearity in spatial genetics: separating the wheat from the chaff using commonality analyses.

PubMed

Prunier, J G; Colyn, M; Legendre, X; Nimon, K F; Flamand, M C

2015-01-01

Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent complexity of genetic variation in wildlife species and are the object of many methodological developments. However, multicollinearity among explanatory variables is a systemic issue in multivariate regression analyses and is likely to cause serious difficulties in properly interpreting results of direct gradient analyses, with the risk of erroneous conclusions, misdirected research and inefficient or counterproductive conservation measures. Using simulated data sets along with linear and logistic regressions on distance matrices, we illustrate how commonality analysis (CA), a detailed variance-partitioning procedure that was recently introduced in the field of ecology, can be used to deal with nonindependence among spatial predictors. By decomposing model fit indices into unique and common (or shared) variance components, CA allows identifying the location and magnitude of multicollinearity, revealing spurious correlations and thus thoroughly improving the interpretation of multivariate regressions. Despite a few inherent limitations, especially in the case of resistance model optimization, this review highlights the great potential of CA to account for complex multicollinearity patterns in spatial genetics and identifies future applications and lines of research. We strongly urge spatial geneticists to systematically investigate commonalities when performing direct gradient analyses. © 2014 John Wiley & Sons Ltd.

Imaging Local Polarization in Ferroelectric Thin Films by Coherent X-Ray Bragg Projection Ptychography

NASA Astrophysics Data System (ADS)

Hruszkewycz, S. O.; Highland, M. J.; Holt, M. V.; Kim, Dongjin; Folkman, C. M.; Thompson, Carol; Tripathi, A.; Stephenson, G. B.; Hong, Seungbum; Fuoss, P. H.

2013-04-01

We used x-ray Bragg projection ptychography (BPP) to map spatial variations of ferroelectric polarization in thin film PbTiO3, which exhibited a striped nanoscale domain pattern on a high-miscut (001) SrTiO3 substrate. By converting the reconstructed BPP phase image to picometer-scale ionic displacements in the polar unit cell, a quantitative polarization map was made that was consistent with other characterization. The spatial resolution of 5.7 nm demonstrated here establishes BPP as an important tool for nanoscale ferroelectric domain imaging, especially in complex environments accessible with hard x rays.

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

NASA Astrophysics Data System (ADS)

Hendrikx, J.

2015-12-01

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

Fishermen Follow Fine-scaled Physical Ocean Features For Finance

NASA Astrophysics Data System (ADS)

Fuller, E.; Watson, J. R.; Samhouri, J.; Castruccio, F. S.

2016-12-01

The seascapes on which many millions of people make their living and secure food have complex and dynamic spatial features - the figurative hills and valleys - that control where and how people work at sea. Here, we quantify the physical mosaic of the surface ocean by identifying Lagrangian Coherent Structures for a whole seascape - the California Current - and assess their impact on the spatial distribution of fishing. We show that there is a mixed response: some fisheries track these physical features, and others avoid them. This spatial behavior maps to economic impacts: we find that tuna fishermen can expect to make three times more revenue per trip if fishing occurs on strong coherent structures. These results highlight a connection between the physical state of the oceans, the spatial patterns of human activity and ultimately the economic prosperity of coastal communities.

A selection criterion for patterns in reaction–diffusion systems

PubMed Central

2014-01-01

Background Alan Turing’s work in Morphogenesis has received wide attention during the past 60 years. The central idea behind his theory is that two chemically interacting diffusible substances are able to generate stable spatial patterns, provided certain conditions are met. Ever since, extensive work on several kinds of pattern-generating reaction diffusion systems has been done. Nevertheless, prediction of specific patterns is far from being straightforward, and a great deal of interest in deciphering how to generate specific patterns under controlled conditions prevails. Results Techniques allowing one to predict what kind of spatial structure will emerge from reaction–diffusion systems remain unknown. In response to this need, we consider a generalized reaction diffusion system on a planar domain and provide an analytic criterion to determine whether spots or stripes will be formed. Our criterion is motivated by the existence of an associated energy function that allows bringing in the intuition provided by phase transitions phenomena. Conclusions Our criterion is proved rigorously in some situations, generalizing well-known results for the scalar equation where the pattern selection process can be understood in terms of a potential. In more complex settings it is investigated numerically. Our work constitutes a first step towards rigorous pattern prediction in arbitrary geometries/conditions. Advances in this direction are highly applicable to the efficient design of Biotechnology and Developmental Biology experiments, as well as in simplifying the analysis of morphogenetic models. PMID:24476200

Life history determines genetic structure and evolutionary potential of host–parasite interactions

PubMed Central

Barrett, Luke G.; Thrall, Peter H.; Burdon, Jeremy J.; Linde, Celeste C.

2009-01-01

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns. PMID:18947899

Life history determines genetic structure and evolutionary potential of host-parasite interactions.

PubMed

Barrett, Luke G; Thrall, Peter H; Burdon, Jeremy J; Linde, Celeste C

2008-12-01

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns.

A Simple Model for Complex Dynamical Transitions in Epidemics

NASA Astrophysics Data System (ADS)

Earn, David J. D.; Rohani, Pejman; Bolker, Benjamin M.; Grenfell, Bryan T.

2000-01-01

Dramatic changes in patterns of epidemics have been observed throughout this century. For childhood infectious diseases such as measles, the major transitions are between regular cycles and irregular, possibly chaotic epidemics, and from regionally synchronized oscillations to complex, spatially incoherent epidemics. A simple model can explain both kinds of transitions as the consequences of changes in birth and vaccination rates. Measles is a natural ecological system that exhibits different dynamical transitions at different times and places, yet all of these transitions can be predicted as bifurcations of a single nonlinear model.

Seeing the forest for the homogeneous trees: stand-scale resource distributions emerge from tree-scale structure

Treesearch

Suzanne Boyden; Rebecca Montgomery; Peter B. Reich; Brian J. Palik

2012-01-01

Forest ecosystem processes depend on local interactions that are modified by the spatial pattern of trees and resources. Effects of resource supplies on processes such as regeneration are increasingly well understood, yet we have few tools to compare resource heterogeneity among forests that differ in structural complexity. We used a neighborhood approach to examine...

Examining conifer canopy structural complexity across forest ages and elevations with LiDAR data

Treesearch

Van R. Kane; Jonathan D. Bakker; Robert J. McGaughey; James A. Lutz; Rolf F. Gersonde; Jerry F. Franklin

2010-01-01

LiDAR measurements of canopy structure can be used to classify forest stands into structural stages to study spatial patterns of canopy structure, identify habitat, or plan management actions. A key assumption in this process is that differences in canopy structure based on forest age and elevation are consistent with predictions from models of stand development. Three...

High-resolution climate monitoring on a mountain island: the Saguaro National Park pilot study

Treesearch

Michael A. Crimmins

2005-01-01

A pilot project to identify climate monitoring needs within Saguaro National Park began in fall 2003. Nine weather stations were deployed across the complex topography of the park to provide insight into the spatial and temporal patterns of climate within the park management unit. This project will provide a valuable baseline for park management and may highlight...

Scale dependence in habitat selection: The case of the endangered brown bear (Ursus arctos) in the Cantabrian Range (NW Spain)

Treesearch

Maria C. Mateo Sanchez; Samuel A. Cushman; Santiago Saura

2013-01-01

Animals select habitat resources at multiple spatial scales. Thus, explicit attention to scale dependency in species-habitat relationships is critical to understand the habitat suitability patterns as perceived by organisms in complex landscapes. Identification of the scales at which particular environmental variables influence habitat selection may be as important as...

Central neural coding of sky polarization in insects.

PubMed

Homberg, Uwe; Heinze, Stanley; Pfeiffer, Keram; Kinoshita, Michiyo; el Jundi, Basil

2011-03-12

Many animals rely on a sun compass for spatial orientation and long-range navigation. In addition to the Sun, insects also exploit the polarization pattern and chromatic gradient of the sky for estimating navigational directions. Analysis of polarization-vision pathways in locusts and crickets has shed first light on brain areas involved in sky compass orientation. Detection of sky polarization relies on specialized photoreceptor cells in a small dorsal rim area of the compound eye. Brain areas involved in polarization processing include parts of the lamina, medulla and lobula of the optic lobe and, in the central brain, the anterior optic tubercle, the lateral accessory lobe and the central complex. In the optic lobe, polarization sensitivity and contrast are enhanced through convergence and opponency. In the anterior optic tubercle, polarized-light signals are integrated with information on the chromatic contrast of the sky. Tubercle neurons combine responses to the UV/green contrast and e-vector orientation of the sky and compensate for diurnal changes of the celestial polarization pattern associated with changes in solar elevation. In the central complex, a topographic representation of e-vector tunings underlies the columnar organization and suggests that this brain area serves as an internal compass coding for spatial directions.

Nonlinear amplification of coherent waves in media with soliton-type refractive index pattern.

PubMed

Bugaychuk, S; Conte, R

2012-08-01

We derive the complex Ginzburg-Landau equation for the dynamical self-diffraction of optical waves in a nonlinear cavity. The case of the reflection geometry of wave interaction as well as a medium that possesses the cubic nonlinearity (including a local and a nonlocal nonlinear responses) and the relaxation is considered. A stable localized spatial structure in the form of a "dark" dissipative soliton is formed in the cavity in the steady state. The envelope of the intensity pattern, as well as of the dynamical grating amplitude, takes the shape of a tanh function. The obtained complex Ginzburg-Landau equation describes the dynamics of this envelope; at the same time, the evolution of this spatial structure changes the parameters of the output waves. New effects are predicted in this system due to the transformation of the dissipative soliton which takes place during the interaction of a pulse with a continuous wave, such as retention of the pulse shape during the transmission of impulses in a long nonlinear cavity, and giant amplification of a seed pulse, which takes energy due to redistribution of the pump continuous energy into the signal.

Central neural coding of sky polarization in insects

PubMed Central

Homberg, Uwe; Heinze, Stanley; Pfeiffer, Keram; Kinoshita, Michiyo; el Jundi, Basil

2011-01-01

Many animals rely on a sun compass for spatial orientation and long-range navigation. In addition to the Sun, insects also exploit the polarization pattern and chromatic gradient of the sky for estimating navigational directions. Analysis of polarization–vision pathways in locusts and crickets has shed first light on brain areas involved in sky compass orientation. Detection of sky polarization relies on specialized photoreceptor cells in a small dorsal rim area of the compound eye. Brain areas involved in polarization processing include parts of the lamina, medulla and lobula of the optic lobe and, in the central brain, the anterior optic tubercle, the lateral accessory lobe and the central complex. In the optic lobe, polarization sensitivity and contrast are enhanced through convergence and opponency. In the anterior optic tubercle, polarized-light signals are integrated with information on the chromatic contrast of the sky. Tubercle neurons combine responses to the UV/green contrast and e-vector orientation of the sky and compensate for diurnal changes of the celestial polarization pattern associated with changes in solar elevation. In the central complex, a topographic representation of e-vector tunings underlies the columnar organization and suggests that this brain area serves as an internal compass coding for spatial directions. PMID:21282171

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...

Evaluation of Alternative Conceptual Models Using Interdisciplinary Information: An Application in Shallow Groundwater Recharge and Discharge

NASA Astrophysics Data System (ADS)

Lin, Y.; Bajcsy, P.; Valocchi, A. J.; Kim, C.; Wang, J.

2007-12-01

Natural systems are complex, thus extensive data are needed for their characterization. However, data acquisition is expensive; consequently we develop models using sparse, uncertain information. When all uncertainties in the system are considered, the number of alternative conceptual models is large. Traditionally, the development of a conceptual model has relied on subjective professional judgment. Good judgment is based on experience in coordinating and understanding auxiliary information which is correlated to the model but difficult to be quantified into the mathematical model. For example, groundwater recharge and discharge (R&D) processes are known to relate to multiple information sources such as soil type, river and lake location, irrigation patterns and land use. Although hydrologists have been trying to understand and model the interaction between each of these information sources and R&D processes, it is extremely difficult to quantify their correlations using a universal approach due to the complexity of the processes, the spatiotemporal distribution and uncertainty. There is currently no single method capable of estimating R&D rates and patterns for all practical applications. Chamberlin (1890) recommended use of "multiple working hypotheses" (alternative conceptual models) for rapid advancement in understanding of applied and theoretical problems. Therefore, cross analyzing R&D rates and patterns from various estimation methods and related field information will likely be superior to using only a single estimation method. We have developed the Pattern Recognition Utility (PRU), to help GIS users recognize spatial patterns from noisy 2D image. This GIS plug-in utility has been applied to help hydrogeologists establish alternative R&D conceptual models in a more efficient way than conventional methods. The PRU uses numerical methods and image processing algorithms to estimate and visualize shallow R&D patterns and rates. It can provide a fast initial estimate prior to planning labor intensive and time consuming field R&D measurements. Furthermore, the Spatial Pattern 2 Learn (SP2L) was developed to cross analyze results from the PRU with ancillary field information, such as land coverage, soil type, topographic maps and previous estimates. The learning process of SP2L cross examines each initially recognized R&D pattern with the ancillary spatial dataset, and then calculates a quantifiable reliability index for each R&D map using a supervised machine learning technique called decision tree. This JAVA based software package is capable of generating alternative R&D maps if the user decides to apply certain conditions recognized by the learning process. The reliability indices from SP2L will improve the traditionally subjective approach to initiating conceptual models by providing objectively quantifiable conceptual bases for further probabilistic and uncertainty analyses. Both the PRU and SP2L have been designed to be user-friendly and universal utilities for pattern recognition and learning to improve model predictions from sparse measurements by computer-assisted integration of spatially dense geospatial image data and machine learning of model dependencies.

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.

Shifts in wind energy potential following land-use driven vegetation dynamics in complex terrain.

PubMed

Fang, Jiannong; Peringer, Alexander; Stupariu, Mihai-Sorin; Pǎtru-Stupariu, Ileana; Buttler, Alexandre; Golay, Francois; Porté-Agel, Fernando

2018-10-15

Many mountainous regions with high wind energy potential are characterized by multi-scale variabilities of vegetation in both spatial and time dimensions, which strongly affect the spatial distribution of wind resource and its time evolution. To this end, we developed a coupled interdisciplinary modeling framework capable of assessing the shifts in wind energy potential following land-use driven vegetation dynamics in complex mountain terrain. It was applied to a case study area in the Romanian Carpathians. The results show that the overall shifts in wind energy potential following the changes of vegetation pattern due to different land-use policies can be dramatic. This suggests that the planning of wind energy project should be integrated with the land-use planning at a specific site to ensure that the expected energy production of the planned wind farm can be reached over its entire lifetime. Moreover, the changes in the spatial distribution of wind and turbulence under different scenarios of land-use are complex, and they must be taken into account in the micro-siting of wind turbines to maximize wind energy production and minimize fatigue loads (and associated maintenance costs). The proposed new modeling framework offers, for the first time, a powerful tool for assessing long-term variability in local wind energy potential that emerges from land-use change driven vegetation dynamics over complex terrain. Following a previously unexplored pathway of cause-effect relationships, it demonstrates a new linkage of agro- and forest policies in landscape development with an ultimate trade-off between renewable energy production and biodiversity targets. Moreover, it can be extended to study the potential effects of micro-climatic changes associated with wind farms on vegetation development (growth and patterning), which could in turn have a long-term feedback effect on wind resource distribution in mountainous regions. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Characterizing China's energy consumption with selective economic factors and energy-resource endowment: a spatial econometric approach

NASA Astrophysics Data System (ADS)

Jiang, Lei; Ji, Minhe; Bai, Ling

2015-06-01

Coupled with intricate regional interactions, the provincial disparity of energy-resource endowment and other economic conditions in China have created spatially complex energy consumption patterns that require analyses beyond the traditional ones. To distill the spatial effect out of the resource and economic factors on China's energy consumption, this study recast the traditional econometric model in a spatial context. Several analytic steps were taken to reveal different aspects of the issue. Per capita energy consumption (AVEC) at the provincial level was first mapped to reveal spatial clusters of high energy consumption being located in either well developed or energy resourceful regions. This visual spatial autocorrelation pattern of AVEC was quantitatively tested to confirm its existence among Chinese provinces. A Moran scatterplot was employed to further display a relatively centralized trend occurring in those provinces that had parallel AVEC, revealing a spatial structure with attraction among high-high or low-low regions and repellency among high-low or low-high regions. By a comparison between the ordinary least square (OLS) model and its spatial econometric counterparts, a spatial error model (SEM) was selected to analyze the impact of major economic determinants on AVEC. While the analytic results revealed a significant positive correlation between AVEC and economic development, other determinants showed some intricate influential patterns. The provinces endowed with rich energy reserves were inclined to consume much more energy than those otherwise, whereas changing the economic structure by increasing the proportion of secondary and tertiary industries also tended to consume more energy. Both situations seem to underpin the fact that these provinces were largely trapped in the economies that were supported by technologies of low energy efficiency during the period, while other parts of the country were rapidly modernized by adopting advanced technologies and more efficient industries. On the other hand, institutional change (i.e., marketization) and innovation (i.e., technological progress) exerted positive impacts on AVEC improvement, as always expected in this and other studies. Finally, the model comparison indicated that SEM was capable of separating spatial effect from the error term of OLS, so as to improve goodness-of-fit and the significance level of individual determinants.

A review of visual perception mechanisms that regulate rapid adaptive camouflage in cuttlefish.

PubMed

Chiao, Chuan-Chin; Chubb, Charles; Hanlon, Roger T

2015-09-01

We review recent research on the visual mechanisms of rapid adaptive camouflage in cuttlefish. These neurophysiologically complex marine invertebrates can camouflage themselves against almost any background, yet their ability to quickly (0.5-2 s) alter their body patterns on different visual backgrounds poses a vexing challenge: how to pick the correct body pattern amongst their repertoire. The ability of cuttlefish to change appropriately requires a visual system that can rapidly assess complex visual scenes and produce the motor responses-the neurally controlled body patterns-that achieve camouflage. Using specifically designed visual backgrounds and assessing the corresponding body patterns quantitatively, we and others have uncovered several aspects of scene variation that are important in regulating cuttlefish patterning responses. These include spatial scale of background pattern, background intensity, background contrast, object edge properties, object contrast polarity, object depth, and the presence of 3D objects. Moreover, arm postures and skin papillae are also regulated visually for additional aspects of concealment. By integrating these visual cues, cuttlefish are able to rapidly select appropriate body patterns for concealment throughout diverse natural environments. This sensorimotor approach of studying cuttlefish camouflage thus provides unique insights into the mechanisms of visual perception in an invertebrate image-forming eye.

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 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...

Gradual and contingent evolutionary emergence of leaf mimicry in butterfly wing patterns.

PubMed

Suzuki, Takao K; Tomita, Shuichiro; Sezutsu, Hideki

2014-11-25

Special resemblance of animals to natural objects such as leaves provides a representative example of evolutionary adaptation. The existence of such sophisticated features challenges our understanding of how complex adaptive phenotypes evolved. Leaf mimicry typically consists of several pattern elements, the spatial arrangement of which generates the leaf venation-like appearance. However, the process by which leaf patterns evolved remains unclear. In this study we show the evolutionary origin and process for the leaf pattern in Kallima (Nymphalidae) butterflies. Using comparative morphological analyses, we reveal that the wing patterns of Kallima and 45 closely related species share the same ground plan, suggesting that the pattern elements of leaf mimicry have been inherited across species with lineage-specific changes of their character states. On the basis of these analyses, phylogenetic comparative methods estimated past states of the pattern elements and enabled reconstruction of the wing patterns of the most recent common ancestor. This analysis shows that the leaf pattern has evolved through several intermediate patterns. Further, we use Bayesian statistical methods to estimate the temporal order of character-state changes in the pattern elements by which leaf mimesis evolved, and show that the pattern elements changed their spatial arrangement (e.g., from a curved line to a straight line) in a stepwise manner and finally establish a close resemblance to a leaf venation-like appearance. Our study provides the first evidence for stepwise and contingent evolution of leaf mimicry.　 Leaf mimicry patterns evolved in a gradual, rather than a sudden, manner from a non-mimetic ancestor. Through a lineage of Kallima butterflies, the leaf patterns evolutionarily originated through temporal accumulation of orchestrated changes in multiple pattern elements.

Generalized reproduction numbers and the prediction of patterns in waterborne disease

PubMed Central

Gatto, Marino; Mari, Lorenzo; Bertuzzo, Enrico; Casagrandi, Renato; Righetto, Lorenzo; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2012-01-01

Understanding, predicting, and controlling outbreaks of waterborne diseases are crucial goals of public health policies, but pose challenging problems because infection patterns are influenced by spatial structure and temporal asynchrony. Although explicit spatial modeling is made possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here we show that the requirement that all the local reproduction numbers be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix , explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number (the dominant eigenvalue of ) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of . Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology, and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections. PMID:23150538

Spatial and Seasonal Dynamics of Water Environmental Capacity in Mountainous Rivers of the Southeastern Coast, China

PubMed Central

Jiang, Jingang; Jing, Changwei

2018-01-01

The south-east littoral is one of the most populous and developed regions in China suffering from serious water pollution problems, and the Xian-Jiang Basin in the mid of this region is among the most polluted watersheds. Critical information is needed but lacking for improved pollution control and water quality assessment, among which water environmental capacity (WEC) is the most important variable but is difficult to calculate. In this study, a one-dimensional water quality model combined with a matrix calculation algorithm was first developed and calibrated with in-situ observations in the Xian-Jiang basin. Then, the model was applied to analyze the spatial and temporal patterns of WEC of the entire basin. The results indicated that, in 2015, the total pollutant discharges into the river reached 6719.68 t/yr, 488.12 t/yr, and 128.57 t/yr for COD, NH3-N and TP, respectively. The spatial pattern suggested a strong correlation between these water contaminants and industrial enterprises, residential areas, and land-use types in the basin. Furthermore, it was noticed that there was a significant seasonal pattern in WEC that the dry season pollution is much greater than that in the plum season, while that in the typhoon season appears to be the weakest among all seasons. The WEC differed significantly among the 24 sub-basins during the dry season but varied to a smaller extent in other seasons, suggesting differential complex spatial-temporal dependency of the WEC. PMID:29315265

A study of optimal model lag and spatial inputs to artificial neural network for rainfall forecasting

NASA Astrophysics Data System (ADS)

Luk, K. C.; Ball, J. E.; Sharma, A.

2000-01-01

Artificial neural networks (ANNs), which emulate the parallel distributed processing of the human nervous system, have proven to be very successful in dealing with complicated problems, such as function approximation and pattern recognition. Due to their powerful capability and functionality, ANNs provide an alternative approach for many engineering problems that are difficult to solve by conventional approaches. Rainfall forecasting has been a difficult subject in hydrology due to the complexity of the physical processes involved and the variability of rainfall in space and time. In this study, ANNs were adopted to forecast short-term rainfall for an urban catchment. The ANNs were trained to recognise historical rainfall patterns as recorded from a number of gauges in the study catchment for reproduction of relevant patterns for new rainstorm events. The primary objective of this paper is to investigate the effect of temporal and spatial information on short-term rainfall forecasting. To achieve this aim, a comparison test on the forecast accuracy was made among the ANNs configured with different orders of lag and different numbers of spatial inputs. In developing the ANNs with alternative configurations, the ANNs were trained to an optimal level to achieve good generalisation of data. It was found in this study that the ANNs provided the most accurate predictions when an optimum number of spatial inputs was included into the network, and that the network with lower lag consistently produced better performance.

Investigating flow patterns and related dynamics in multi-instability turbulent plasmas using a three-point cross-phase time delay estimation velocimetry scheme

NASA Astrophysics Data System (ADS)

Brandt, C.; Thakur, S. C.; Tynan, G. R.

2016-04-01

Complexities of flow patterns in the azimuthal cross-section of a cylindrical magnetized helicon plasma and the corresponding plasma dynamics are investigated by means of a novel scheme for time delay estimation velocimetry. The advantage of this introduced method is the capability of calculating the time-averaged 2D velocity fields of propagating wave-like structures and patterns in complex spatiotemporal data. It is able to distinguish and visualize the details of simultaneously present superimposed entangled dynamics and it can be applied to fluid-like systems exhibiting frequently repeating patterns (e.g., waves in plasmas, waves in fluids, dynamics in planetary atmospheres, etc.). The velocity calculations are based on time delay estimation obtained from cross-phase analysis of time series. Each velocity vector is unambiguously calculated from three time series measured at three different non-collinear spatial points. This method, when applied to fast imaging, has been crucial to understand the rich plasma dynamics in the azimuthal cross-section of a cylindrical linear magnetized helicon plasma. The capabilities and the limitations of this velocimetry method are discussed and demonstrated for two completely different plasma regimes, i.e., for quasi-coherent wave dynamics and for complex broadband wave dynamics involving simultaneously present multiple instabilities.

Investigating flow patterns and related dynamics in multi-instability turbulent plasmas using a three-point cross-phase time delay estimation velocimetry scheme

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

Brandt, C.; Max-Planck-Institute for Plasma Physics, Wendelsteinstr. 1, D-17491 Greifswald; Thakur, S. C.

2016-04-15

Complexities of flow patterns in the azimuthal cross-section of a cylindrical magnetized helicon plasma and the corresponding plasma dynamics are investigated by means of a novel scheme for time delay estimation velocimetry. The advantage of this introduced method is the capability of calculating the time-averaged 2D velocity fields of propagating wave-like structures and patterns in complex spatiotemporal data. It is able to distinguish and visualize the details of simultaneously present superimposed entangled dynamics and it can be applied to fluid-like systems exhibiting frequently repeating patterns (e.g., waves in plasmas, waves in fluids, dynamics in planetary atmospheres, etc.). The velocity calculationsmore » are based on time delay estimation obtained from cross-phase analysis of time series. Each velocity vector is unambiguously calculated from three time series measured at three different non-collinear spatial points. This method, when applied to fast imaging, has been crucial to understand the rich plasma dynamics in the azimuthal cross-section of a cylindrical linear magnetized helicon plasma. The capabilities and the limitations of this velocimetry method are discussed and demonstrated for two completely different plasma regimes, i.e., for quasi-coherent wave dynamics and for complex broadband wave dynamics involving simultaneously present multiple instabilities.« less

Surface temperature patterns in complex terrain: Daily variations and long-term change in the central Sierra Nevada, California

USGS Publications Warehouse

Lundquist, J.D.; Cayan, D.R.

2007-01-01

A realistic description of how temperatures vary with elevation is crucial for ecosystem studies and for models of basin-scale snowmelt and spring streamflow. This paper explores surface temperature variability using temperature data from an array of 37 sensors, called the Yosemite network, which traverses both slopes of the Sierra Nevada in the vicinity of Yosemite National Park, California. These data indicate that a simple lapse rate is often a poor description of the spatial temperature structure. Rather, the spatial pattern of temperature over the Yosemite network varies considerably with synoptic conditions. Empirical orthogonal functions (EOFs) were used to identify the dominant spatial temperature patterns and how they vary in time. Temporal variations of these surface temperature patterns were correlated with large-scale weather conditions, as described by National Centers for Environmental Prediction-National Center for Atmospheric Research Reanalysis data. Regression equations were used to downscale larger-scale weather parameters, such as Reanalysis winds and pressure, to the surface temperature structure over the Yosemite network. These relationships demonstrate that strong westerly winds are associated with relatively warmer temperatures on the east slope and cooler temperatures on the west slope of the Sierra, and weaker westerly winds are associated with the opposite pattern. Reanalysis data from 1948 to 2005 indicate weakening westerlies over this time period, a trend leading to relatively cooler temperatures on the east slope over decadal timescale's. This trend also appears in long-term observations and demonstrates the need to consider topographic effects when examining long-term changes in mountain regions. Copyright 2007 by the American Geophysical Union.

Spatial and temporal selectivity patterns of fires in Attika, Greece from 1984 to 2015 delineated from Landsat time series satellite images

NASA Astrophysics Data System (ADS)

Stamos, Zoi; Koutsias, Nikos

2017-04-01

The aim of this study is to assess spatial and temporalfire selectivity patterns in the region of Attica - Greece from 1984 to 2015. Our work is implemented in two distinct phases: the first consists of the accurate delineation of the fire perimeter using satellite remote sensing technology, and the second consists of the application of suitable GIS supported analyses to develop thematic layers that optimally summarised the spatial and temporal information of fire occurrence. Fire perimeters of wildland fires occurred within the time window 1984-2015 were delineated from freely available Landsat images from USGS and ESA sources.More than three thousands satellite images were processed in order to extract fire perimeters and create maps of fire frequency and fire return interval. In total one thousand and one hundred twenty fire perimeters were recorded during this thirty years' period. Fire perimeters within each year of fire occurrence were compared against the available to burn under complete random processes to identify selectivity patterns over (i) CORINE land use/land cover, (ii) fire frequency and (iii) time since last firemaps. For example, non- irrigated arable lands, complex cultivation patterns and discontinuous urban fabrics are negative related with fires, while coniferous forests, sclerophyllous vegetation and transitional woodlands seem to be preferable by the fires. Additionally, it seems that fires prefer their old burnings (two and three times burned) and also places with different patterns of time since last fire depending on the time needed by the type of vegetation to recover and thus to re-burn.

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.

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.

EMGAN: A computer program for time and frequency domain reduction of electromyographic data

NASA Technical Reports Server (NTRS)

Hursta, W. N.

1975-01-01

An experiment in electromyography utilizing surface electrode techniques was developed for the Apollo-Soyuz test project. This report describes the computer program, EMGAN, which was written to provide first order data reduction for the experiment. EMG signals are produced by the membrane depolarization of muscle fibers during a muscle contraction. Surface electrodes detect a spatially summated signal from a large number of muscle fibers commonly called an interference pattern. An interference pattern is usually so complex that analysis through signal morphology is extremely difficult if not impossible. It has become common to process EMG interference patterns in the frequency domain. Muscle fatigue and certain myopathic conditions are recognized through changes in muscle frequency spectra.

Network structure of subway passenger flows

NASA Astrophysics Data System (ADS)

Xu, Q.; Mao, B. H.; Bai, Y.

2016-03-01

The results of transportation infrastructure network analyses have been used to analyze complex networks in a topological context. However, most modeling approaches, including those based on complex network theory, do not fully account for real-life traffic patterns and may provide an incomplete view of network functions. This study utilizes trip data obtained from the Beijing Subway System to characterize individual passenger movement patterns. A directed weighted passenger flow network was constructed from the subway infrastructure network topology by incorporating trip data. The passenger flow networks exhibit several properties that can be characterized by power-law distributions based on flow size, and log-logistic distributions based on the fraction of boarding and departing passengers. The study also characterizes the temporal patterns of in-transit and waiting passengers and provides a hierarchical clustering structure for passenger flows. This hierarchical flow organization varies in the spatial domain. Ten cluster groups were identified, indicating a hierarchical urban polycentric structure composed of large concentrated flows at urban activity centers. These empirical findings provide insights regarding urban human mobility patterns within a large subway network.

Scale effects on spatially varying relationships between urban landscape patterns and water quality.

PubMed

Sun, Yanwei; Guo, Qinghai; Liu, Jian; Wang, Run

2014-08-01

Scientific interpretation of the relationships between urban landscape patterns and water quality is important for sustainable urban planning and watershed environmental protection. This study applied the ordinary least squares regression model and the geographically weighted regression model to examine the spatially varying relationships between 12 explanatory variables (including three topographical factors, four land use parameters, and five landscape metrics) and 15 water quality indicators in watersheds of Yundang Lake, Maluan Bay, and Xinglin Bay with varying levels of urbanization in Xiamen City, China. A local and global investigation was carried out at the watershed-level, with 50 and 200 m riparian buffer scales. This study found that topographical features and landscape metrics are the dominant factors of water quality, while land uses are too weak to be considered as a strong influential factor on water quality. Such statistical results may be related with the characteristics of land use compositions in our study area. Water quality variations in the 50 m buffer were dominated by topographical variables. The impact of landscape metrics on water quality gradually strengthen with expanding buffer zones. The strongest relationships are obtained in entire watersheds, rather than in 50 and 200 m buffer zones. Spatially varying relationships and effective buffer zones were verified in this study. Spatially varying relationships between explanatory variables and water quality parameters are more diversified and complex in less urbanized areas than in highly urbanized areas. This study hypothesizes that all these varying relationships may be attributed to the heterogeneity of landscape patterns in different urban regions. Adjustment of landscape patterns in an entire watershed should be the key measure to successfully improving urban lake water quality.

Urbanization and the Resulting Peripheralization in Solo Raya, Indonesia

NASA Astrophysics Data System (ADS)

Pradoto, W.; Mardiansjah, F. H.; Manullang, O. R.; Putra, A. A.

2018-02-01

Dynamic urbanization in Solo Raya, a local term for Surakarta Metropolitan, amongst rapid regional based-urbanization in Indonesia, shows the unbalance pattern of growth. A number of Surakarta City’s peripherals become the newly growing area which is characterized by a well-facilitated region, while the former urbanized areas next to the city center present the declining process. Different socioeconomic development triggers a unique mosaic of socio-spatial pattern, on which the phenomena of peripheralization could be investigated. Urban investment that boosted by the political will of both the national and local government has led to a shift in demographic condition. A relatively massive in-migration has been attracted to the peripheral and creates the new landscape of urban-rural society. Complex dynamic of metropolitan growth and the resulting peripheralization reminds that socio-spatial pattern calls the challenges for managing the rapid change of land use and space use. The pattern of urbanization that differs upon the surrounding areas of Surakarta City would be interesting to be explored. This paper will discuss the conceptual framework of peripheral urbanization and the methodological approach. It is actually the part of ongoing research on peripheralisation in Solo Raya.

Trophic pathways supporting juvenile Chinook and Coho salmon in the glacial Susitna River, Alaska: patterns of freshwater, marine, and terrestrial resource use across a seasonally dynamic habitat mosaic

USGS Publications Warehouse

Rine, Kristin M.; Wipfli, Mark S.; Schoen, Erik R.; Nightengale, Timothy L.; Stricker, Craig A.

2016-01-01

Contributions of terrestrial-, freshwater-, and marine-derived prey resources to stream fishes vary over time and space, altering the energy pathways that regulate production. In this study, we determined large-scale use of these resources by juvenile Chinook and coho salmon (Oncorhynchus tshawytscha and Oncorhynchus kisutch, respectively) in the glacial Susitna River, Alaska. We resolved spatial and temporal trophic patterns among multiple macrohabitat types along a 97 km segment of the river corridor via stable isotope and stomach content analyses. Juvenile salmon were supported primarily by freshwater-derived resources and secondarily by marine and terrestrial sources. The relative contribution of marine-derived prey to rearing salmon was greatest in the fall within off-channel macrohabitats, whereas the contributions of terrestrial invertebrate prey were generally greatest during midsummer, across all macrohabitats. No longitudinal (upstream–downstream) diet pattern was discernable. These results highlight large-scale spatial and seasonal patterns of energy flow and the dynamic interplay of pulsed marine and terrestrial prey subsidies to juvenile Chinook and coho salmon in a large, complex, and relatively pristine glacial river.

Influence of Biological Factors on Connectivity Patterns for Concholepas concholepas (loco) in Chile.

PubMed

Garavelli, Lysel; Colas, François; Verley, Philippe; Kaplan, David Michael; Yannicelli, Beatriz; Lett, Christophe

2016-01-01

In marine benthic ecosystems, larval connectivity is a major process influencing the maintenance and distribution of invertebrate populations. Larval connectivity is a complex process to study as it is determined by several interacting factors. Here we use an individual-based, biophysical model, to disentangle the effects of such factors, namely larval vertical migration, larval growth, larval mortality, adults fecundity, and habitat availability, for the marine gastropod Concholepas concholepas (loco) in Chile. Lower transport success and higher dispersal distances are observed including larval vertical migration in the model. We find an overall decrease in larval transport success to settlement areas from northern to southern Chile. This spatial gradient results from the combination of current direction and intensity, seawater temperature, and available habitat. From our simulated connectivity patterns we then identify subpopulations of loco along the Chilean coast, which could serve as a basis for spatial management of this resource in the future.

Influence of Biological Factors on Connectivity Patterns for Concholepas concholepas (loco) in Chile

PubMed Central

Garavelli, Lysel; Colas, François; Verley, Philippe; Kaplan, David Michael; Yannicelli, Beatriz; Lett, Christophe

2016-01-01

In marine benthic ecosystems, larval connectivity is a major process influencing the maintenance and distribution of invertebrate populations. Larval connectivity is a complex process to study as it is determined by several interacting factors. Here we use an individual-based, biophysical model, to disentangle the effects of such factors, namely larval vertical migration, larval growth, larval mortality, adults fecundity, and habitat availability, for the marine gastropod Concholepas concholepas (loco) in Chile. Lower transport success and higher dispersal distances are observed including larval vertical migration in the model. We find an overall decrease in larval transport success to settlement areas from northern to southern Chile. This spatial gradient results from the combination of current direction and intensity, seawater temperature, and available habitat. From our simulated connectivity patterns we then identify subpopulations of loco along the Chilean coast, which could serve as a basis for spatial management of this resource in the future. PMID:26751574

Controlled evaporative self-assembly of confined microfluids: A route to complex ordered structures

NASA Astrophysics Data System (ADS)

Byun, Myunghwan

The evaporative self-assembly of nonvolatile solutes such as polymers, nanocrystals, and carbon nanotubes has been widely recognized as a non-lithographic means of producing a diverse range of intriguing complex structures. Due to the spatial variation of evaporative flux and possible convection, however, these non-equilibrium dissipative structures (e.g., fingering patterns and polygonal network structures) are often irregularly and stochastically organized. Yet for many applications in microelectronics, data storage devices, and biotechnology, it is highly desirable to achieve surface patterns having a well-controlled spatial arrangement. To date, only a few elegant studies have centered on precise control over the evaporation process to produce ordered structures. In a remarked comparison with conventional lithography techniques, surface patterning by controlled solvent evaporation is simple and cost-effective, offering a lithography- and external field-free means to organize nonvolatile materials into ordered microscopic structures over large surface areas. The ability to engineer an evaporative self-assembly process that yields a wide range of complex, self-organizing structures over large areas offers tremendous potential for applications in electronics, optoelectronics, and bio- or chemical sensors. We developed a facile, robust tool for evaporating polymer, nanoparticle, or DNA solutions in curve-on-flat geometries to create versatile, highly regular microstructures, including hierarchically structured polymer blend rings, conjugated polymer "snake-skins", block copolymer stripes, and punch-hole-like meshes, biomolecular microring arrays, etc. The mechanism of structure formation was elucidated both experimentally and theoretically. Our method further enhances current fabrication approaches to creating highly ordered structures in a simple and cost-effective manner, envisioning the potential to be tailored for use in photonics, optoelectronics, microfluidic devices, nanotechnology and biotechnology, etc.

Spatial and temporal patterns in preterm birth in the United States.

PubMed

Byrnes, John; Mahoney, Richard; Quaintance, Cele; Gould, Jeffrey B; Carmichael, Suzan; Shaw, Gary M; Showen, Amy; Phibbs, Ciaran; Stevenson, David K; Wise, Paul H

2015-06-01

Despite years of research, the etiologies of preterm birth remain unclear. In order to help generate new research hypotheses, this study explored spatial and temporal patterns of preterm birth in a large, total-population dataset. Data on 145 million US births in 3,000 counties from the Natality Files of the National Center for Health Statistics for 1971-2011 were examined. State trends in early (<34 wk) and late (34-36 wk) preterm birth rates were compared. K-means cluster analyses were conducted to identify gestational age distribution patterns for all US counties over time. A weak association was observed between state trends in <34 wk birth rates and the initial absolute <34 wk birth rate. Significant associations were observed between trends in <34 wk and 34-36 wk birth rates and between white and African American <34 wk births. Periodicity was observed in county-level trends in <34 wk birth rates. Cluster analyses identified periods of significant heterogeneity and homogeneity in gestational age distributional trends for US counties. The observed geographic and temporal patterns suggest periodicity and complex, shared influences among preterm birth rates in the United States. These patterns could provide insight into promising hypotheses for further research.

Effect of pattern complexity on the visual span for Chinese and alphabet characters

PubMed Central

Wang, Hui; He, Xuanzi; Legge, Gordon E.

2014-01-01

The visual span for reading is the number of letters that can be recognized without moving the eyes and is hypothesized to impose a sensory limitation on reading speed. Factors affecting the size of the visual span have been studied using alphabet letters. There may be common constraints applying to recognition of other scripts. The aim of this study was to extend the concept of the visual span to Chinese characters and to examine the effect of the greater complexity of these characters. We measured visual spans for Chinese characters and alphabet letters in the central vision of bilingual subjects. Perimetric complexity was used as a metric to quantify the pattern complexity of binary character images. The visual span tests were conducted with four sets of stimuli differing in complexity—lowercase alphabet letters and three groups of Chinese characters. We found that the size of visual spans decreased with increasing complexity, ranging from 10.5 characters for alphabet letters to 4.5 characters for the most complex Chinese characters studied. A decomposition analysis revealed that crowding was the dominant factor limiting the size of the visual span, and the amount of crowding increased with complexity. Errors in the spatial arrangement of characters (mislocations) had a secondary effect. We conclude that pattern complexity has a major effect on the size of the visual span, mediated in large part by crowding. Measuring the visual span for Chinese characters is likely to have high relevance to understanding visual constraints on Chinese reading performance. PMID:24993020

Domain growth of carbon nanotubes assisted by dewetting of thin catalyst precursor films

NASA Astrophysics Data System (ADS)

Srivastava, Alok Kumar; Sachan, Priyanka; Samanta, Chandan; Mukhopadhyay, Kingsuk; Sharma, Ashutosh

2014-01-01

We explore self-organized dewetting of ultrathin films of a novel metal complex as a one step surface patterning method to create nanoislands of iron, using which spatially separated carbon nanostructures were synthesized. Dewetting of ultrathin metal complex films was induced by two different methods: liquid solvent exposure and thermal annealing to engender surface patterning. For thermal dewetting, thin films of the iron oleate complex were dewetted at high temperature. In the case of liquid solvent assisted dewetting, the metal complex, mixed with a sacrificial polymer (polystyrene) was spin coated as thin films (<40 nm) and then dewetted under an optimal solution mixture consisting of methyl ethyl ketone, acetone and water. The carrier polymer was then selectively removed to produce the iron metal islands. These metal islands were used for selective growth of discrete patches of multiwall CNTs and CNFs by a chemical vapor deposition (CVD) process. Solvent induced dewetting showed clear advantages over thermal dewetting owing to reduced size of catalyst domains formed by dewetting, an improved control over CNT growth as well as in its ability to immobilize the seed particles. The generic solution mediated dewetting and pattern generation in thin films of various catalytic precursors can thus be a powerful method for selective domain growth of a variety of functional nanomaterials.

Spatial distribution of polycyclic aromatic hydrocarbon and polychlorinated biphenyl sources in the Nakdong River Estuary, South Korea.

PubMed

Lee, Jun H; Woo, Han J; Jeong, Kap S; Kang, Jeong W; Choi, Jae U; Jeong, Eun J; Park, Kap S; Lee, Dong H

2017-10-15

Our research team investigated the elemental composition and the presence of various toxic organic compounds, such as polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs), in estuary surface sediments to trace the spatial distribution of the sources of pollution deposited in Nakdong River, Busan, South Korea. The spatial patterns of elemental composition and toxic organic compounds were determined from the measurements of total organic carbon (TOC), total nitrogen, total sulfur, PAHs, and PCBs. The sediments had TOC contents of between 0.02 and 1.80 wt% (avg. 0.34 wt%), depending on the amount of clay-sized particles. The concentrations of PAHs and PCBs (10.8-167.7 ng g -1 dry wt and 197.0-754.0 pg g -1 dry wt, respectively) in surface sediments revealed different spatial patterns for these compounds, suggesting that they partially originated from the combustion of fossil fuels and from the use of commercial PCB products at adjacent industrial complexes. Although these concentrations were far below the Sediment Quality Guideline (SQG) of the National Oceanic and Atmospheric Administration (NOAA), the sediments at one site contained PCBs at concentrations close to the response level (754.0 pg g -1 dry wt), and were dominated by low-molecular-weight PAHs. The PAHs and PCBs in Nakdong River Estuary sediments were likely to have originated from the combustion of fossil fuels and biomass at the adjacent industrial complexes. The primarily analyzed results determined that PAHs originated from the combustion of fossil fuels and biomass, and overall concentrations were related to the contributions of individual PAHs in most sediment samples. Based on the SQG of the NOAA, our results indicate that the anthropogenic activity should be considered on the future-sustainable management of this estuary system.

Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

PubMed

Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

2015-04-01

Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for epidemiological surveillance.

Programming curvature using origami tessellations

NASA Astrophysics Data System (ADS)

Dudte, Levi H.; Vouga, Etienne; Tachi, Tomohiro; Mahadevan, L.

2016-05-01

Origami describes rules for creating folded structures from patterns on a flat sheet, but does not prescribe how patterns can be designed to fit target shapes. Here, starting from the simplest periodic origami pattern that yields one-degree-of-freedom collapsible structures--we show that scale-independent elementary geometric constructions and constrained optimization algorithms can be used to determine spatially modulated patterns that yield approximations to given surfaces of constant or varying curvature. Paper models confirm the feasibility of our calculations. We also assess the difficulty of realizing these geometric structures by quantifying the energetic barrier that separates the metastable flat and folded states. Moreover, we characterize the trade-off between the accuracy to which the pattern conforms to the target surface, and the effort associated with creating finer folds. Our approach enables the tailoring of origami patterns to drape complex surfaces independent of absolute scale, as well as the quantification of the energetic and material cost of doing so.

Impact of Spatial Pumping Patterns on Groundwater Management

NASA Astrophysics Data System (ADS)

Yin, J.; Tsai, F. T. C.

2017-12-01

Challenges exist to manage groundwater resources while maintaining a balance between groundwater quantity and quality because of anthropogenic pumping activities as well as complex subsurface environment. In this study, to address the impact of spatial pumping pattern on groundwater management, a mixed integer nonlinear multi-objective model is formulated by integrating three objectives within a management framework to: (i) maximize total groundwater withdrawal from potential wells; (ii) minimize total electricity cost for well pumps; and (iii) attain groundwater level at selected monitoring locations as close as possible to the target level. Binary variables are used in the groundwater management model to control the operative status of pumping wells. The NSGA-II is linked with MODFLOW to solve the multi-objective problem. The proposed method is applied to a groundwater management problem in the complex Baton Rouge aquifer system, southeastern Louisiana. Results show that (a) non-dominated trade-off solutions under various spatial distributions of active pumping wells can be achieved. Each solution is optimal with regard to its corresponding objectives; (b) operative status, locations and pumping rates of pumping wells are significant to influence the distribution of hydraulic head, which in turn influence the optimization results; (c) A wide range of optimal solutions is obtained such that decision makers can select the most appropriate solution through negotiation with different stakeholders. This technique is beneficial to finding out the optimal extent to which three objectives including water supply concern, energy concern and subsidence concern can be balanced.

Emergent 1d Ising Behavior in AN Elementary Cellular Automaton Model

NASA Astrophysics Data System (ADS)

Kassebaum, Paul G.; Iannacchione, Germano S.

The fundamental nature of an evolving one-dimensional (1D) Ising model is investigated with an elementary cellular automaton (CA) simulation. The emergent CA simulation employs an ensemble of cells in one spatial dimension, each cell capable of two microstates interacting with simple nearest-neighbor rules and incorporating an external field. The behavior of the CA model provides insight into the dynamics of coupled two-state systems not expressible by exact analytical solutions. For instance, state progression graphs show the causal dynamics of a system through time in relation to the system's entropy. Unique graphical analysis techniques are introduced through difference patterns, diffusion patterns, and state progression graphs of the 1D ensemble visualizing the evolution. All analyses are consistent with the known behavior of the 1D Ising system. The CA simulation and new pattern recognition techniques are scalable (in both dimension, complexity, and size) and have many potential applications such as complex design of materials, control of agent systems, and evolutionary mechanism design.

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

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

PubMed

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

2009-11-01

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

Spatial patterns of throughfall isotopic composition at the event and seasonal timescales

NASA Astrophysics Data System (ADS)

Allen, Scott T.; Keim, Richard F.; McDonnell, Jeffrey J.

2015-03-01

Spatial variability of throughfall isotopic composition in forests is indicative of complex processes occurring in the canopy and remains insufficiently understood to properly characterize precipitation inputs to the catchment water balance. Here we investigate variability of throughfall isotopic composition with the objectives: (1) to quantify the spatial variability in event-scale samples, (2) to determine if there are persistent controls over the variability and how these affect variability of seasonally accumulated throughfall, and (3) to analyze the distribution of measured throughfall isotopic composition associated with varying sampling regimes. We measured throughfall over two, three-month periods in western Oregon, USA under a Douglas-fir canopy. The mean spatial range of δ18O for each event was 1.6‰ and 1.2‰ through Fall 2009 (11 events) and Spring 2010 (7 events), respectively. However, the spatial pattern of isotopic composition was not temporally stable causing season-total throughfall to be less variable than event throughfall (1.0‰; range of cumulative δ18O for Fall 2009). Isotopic composition was not spatially autocorrelated and not explained by location relative to tree stems. Sampling error analysis for both field measurements and Monte-Carlo simulated datasets representing different sampling schemes revealed the standard deviation of differences from the true mean as high as 0.45‰ (δ18O) and 1.29‰ (d-excess). The magnitude of this isotopic variation suggests that small sample sizes are a source of substantial experimental error.

Development of Maps of Simple and Complex Cells in the Primary Visual Cortex

PubMed Central

Antolík, Ján; Bednar, James A.

2011-01-01

Hubel and Wiesel (1962) classified primary visual cortex (V1) neurons as either simple, with responses modulated by the spatial phase of a sine grating, or complex, i.e., largely phase invariant. Much progress has been made in understanding how simple-cells develop, and there are now detailed computational models establishing how they can form topographic maps ordered by orientation preference. There are also models of how complex cells can develop using outputs from simple cells with different phase preferences, but no model of how a topographic orientation map of complex cells could be formed based on the actual connectivity patterns found in V1. Addressing this question is important, because the majority of existing developmental models of simple-cell maps group neurons selective to similar spatial phases together, which is contrary to experimental evidence, and makes it difficult to construct complex cells. Overcoming this limitation is not trivial, because mechanisms responsible for map development drive receptive fields (RF) of nearby neurons to be highly correlated, while co-oriented RFs of opposite phases are anti-correlated. In this work, we model V1 as two topographically organized sheets representing cortical layer 4 and 2/3. Only layer 4 receives direct thalamic input. Both sheets are connected with narrow feed-forward and feedback connectivity. Only layer 2/3 contains strong long-range lateral connectivity, in line with current anatomical findings. Initially all weights in the model are random, and each is modified via a Hebbian learning rule. The model develops smooth, matching, orientation preference maps in both sheets. Layer 4 units become simple cells, with phase preference arranged randomly, while those in layer 2/3 are primarily complex cells. To our knowledge this model is the first explaining how simple cells can develop with random phase preference, and how maps of complex cells can develop, using only realistic patterns of connectivity. PMID:21559067

Common Neural Representations for Visually Guided Reorientation and Spatial Imagery

PubMed Central

Vass, Lindsay K.; Epstein, Russell A.

2017-01-01

Abstract Spatial knowledge about an environment can be cued from memory by perception of a visual scene during active navigation or by imagination of the relationships between nonvisible landmarks, such as when providing directions. It is not known whether these different ways of accessing spatial knowledge elicit the same representations in the brain. To address this issue, we scanned participants with fMRI, while they performed a judgment of relative direction (JRD) task that required them to retrieve real-world spatial relationships in response to either pictorial or verbal cues. Multivoxel pattern analyses revealed several brain regions that exhibited representations that were independent of the cues to access spatial memory. Specifically, entorhinal cortex in the medial temporal lobe and the retrosplenial complex (RSC) in the medial parietal lobe coded for the heading assumed on a particular trial, whereas the parahippocampal place area (PPA) contained information about the starting location of the JRD. These results demonstrate the existence of spatial representations in RSC, ERC, and PPA that are common to visually guided navigation and spatial imagery. PMID:26759482

Defect Localization Capabilities of a Global Detection Scheme: Spatial Pattern Recognition Using Full-field Vibration Test Data in Plates

NASA Technical Reports Server (NTRS)

Saleeb, A. F.; Prabhu, M.; Arnold, S. M. (Technical Monitor)

2002-01-01

Recently, a conceptually simple approach, based on the notion of defect energy in material space has been developed and extensively studied (from the theoretical and computational standpoints). The present study focuses on its evaluation from the viewpoint of damage localization capabilities in case of two-dimensional plates; i.e., spatial pattern recognition on surfaces. To this end, two different experimental modal test results are utilized; i.e., (1) conventional modal testing using (white noise) excitation and accelerometer-type sensors and (2) pattern recognition using Electronic speckle pattern interferometry (ESPI), a full field method capable of analyzing the mechanical vibration of complex structures. Unlike the conventional modal testing technique (using contacting accelerometers), these emerging ESPI technologies operate in a non-contacting mode, can be used even under hazardous conditions with minimal or no presence of noise and can simultaneously provide measurements for both translations and rotations. Results obtained have clearly demonstrated the robustness and versatility of the global NDE scheme developed. The vectorial character of the indices used, which enabled the extraction of distinct patterns for localizing damages proved very useful. In the context of the targeted pattern recognition paradigm, two algorithms were developed for the interrogation of test measurements; i.e., intensity contour maps for the damaged index, and the associated defect energy vector field plots.

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

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...

SPARQL Query Re-writing Using Partonomy Based Transformation Rules

NASA Astrophysics Data System (ADS)

Jain, Prateek; Yeh, Peter Z.; Verma, Kunal; Henson, Cory A.; Sheth, Amit P.

Often the information present in a spatial knowledge base is represented at a different level of granularity and abstraction than the query constraints. For querying ontology's containing spatial information, the precise relationships between spatial entities has to be specified in the basic graph pattern of SPARQL query which can result in long and complex queries. We present a novel approach to help users intuitively write SPARQL queries to query spatial data, rather than relying on knowledge of the ontology structure. Our framework re-writes queries, using transformation rules to exploit part-whole relations between geographical entities to address the mismatches between query constraints and knowledge base. Our experiments were performed on completely third party datasets and queries. Evaluations were performed on Geonames dataset using questions from National Geographic Bee serialized into SPARQL and British Administrative Geography Ontology using questions from a popular trivia website. These experiments demonstrate high precision in retrieval of results and ease in writing queries.

Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

PubMed

Cannon, Jonathan; Kopell, Nancy; Gardner, Timothy; Markowitz, Jeffrey

2015-11-01

Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

Molecular insights into seed dispersal mutualisms driving plant population recruitment

NASA Astrophysics Data System (ADS)

García, Cristina; Grivet, Delphine

2011-11-01

Most plant species require mutualistic interactions with animals to fulfil their demographic cycle. In this regard frugivory (i.e., the intake of fruits by animals) enhances natural regeneration by mobilizing a large amount of seeds from source trees to deposition sites across the landscape. By doing so, frugivores move propagules, and the genotypes they harbour creating the spatial, ecological, and genetic environment under which subsequent recruitment proceeds. Recruitment patterns can be envisioned as the result of two density- and distance-dependent processes: seed dispersal and seed/seedling survival (the Janzen-Connell model). Population genetic studies add another layer of complexity for understanding the fate of dispersed propagules: the genetic relatedness among neighbouring seeds within a seed clump, a major outcome of frugivore activity, modifies their chances of germinating and surviving. Yet, we virtually ignore how the spatial distribution of maternal progenies and recruitment patterns relate with each other in frugivore-generated seed rains. Here we focus on the critical role of frugivore-mediated seed dispersal in shaping the spatial distribution of maternal progenies in the seed rain. We first examine which genetic mechanisms underlying recruitment are influenced by the spatial distribution of maternal progenies. Next, we examine those studies depicting the spatial distribution of maternal progenies in a frugivore-generated seed rain. In doing so, we briefly review the most suitable analytical approaches applied to track the contribution of fruiting trees to the seed rain based on molecular data. Then we look more specifically at the role of distinct frugivore guilds in determining maternal genetic correlations and their expected consequences for recruitment patterns. Finally we posit some general conclusions and suggest future research directions that would provide a more comprehensive understanding of the ecological and evolutionary consequences of dispersal mutualisms in plant populations.

A geovisual analytic approach to understanding geo-social relationships in the international trade network.

PubMed

Luo, Wei; Yin, Peifeng; Di, Qian; Hardisty, Frank; MacEachren, Alan M

2014-01-01

The world has become a complex set of geo-social systems interconnected by networks, including transportation networks, telecommunications, and the internet. Understanding the interactions between spatial and social relationships within such geo-social systems is a challenge. This research aims to address this challenge through the framework of geovisual analytics. We present the GeoSocialApp which implements traditional network analysis methods in the context of explicitly spatial and social representations. We then apply it to an exploration of international trade networks in terms of the complex interactions between spatial and social relationships. This exploration using the GeoSocialApp helps us develop a two-part hypothesis: international trade network clusters with structural equivalence are strongly 'balkanized' (fragmented) according to the geography of trading partners, and the geographical distance weighted by population within each network cluster has a positive relationship with the development level of countries. In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics. We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above.

A Geovisual Analytic Approach to Understanding Geo-Social Relationships in the International Trade Network

PubMed Central

Luo, Wei; Yin, Peifeng; Di, Qian; Hardisty, Frank; MacEachren, Alan M.

2014-01-01

The world has become a complex set of geo-social systems interconnected by networks, including transportation networks, telecommunications, and the internet. Understanding the interactions between spatial and social relationships within such geo-social systems is a challenge. This research aims to address this challenge through the framework of geovisual analytics. We present the GeoSocialApp which implements traditional network analysis methods in the context of explicitly spatial and social representations. We then apply it to an exploration of international trade networks in terms of the complex interactions between spatial and social relationships. This exploration using the GeoSocialApp helps us develop a two-part hypothesis: international trade network clusters with structural equivalence are strongly ‘balkanized’ (fragmented) according to the geography of trading partners, and the geographical distance weighted by population within each network cluster has a positive relationship with the development level of countries. In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics. We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above. PMID:24558409

Physical, Spatial, and Molecular Aspects of Extracellular Matrix of In Vivo Niches and Artificial Scaffolds Relevant to Stem Cells Research

PubMed Central

Akhmanova, Maria; Osidak, Egor; Domogatsky, Sergey; Rodin, Sergey; Domogatskaya, Anna

2015-01-01

Extracellular matrix can influence stem cell choices, such as self-renewal, quiescence, migration, proliferation, phenotype maintenance, differentiation, or apoptosis. Three aspects of extracellular matrix were extensively studied during the last decade: physical properties, spatial presentation of adhesive epitopes, and molecular complexity. Over 15 different parameters have been shown to influence stem cell choices. Physical aspects include stiffness (or elasticity), viscoelasticity, pore size, porosity, amplitude and frequency of static and dynamic deformations applied to the matrix. Spatial aspects include scaffold dimensionality (2D or 3D) and thickness; cell polarity; area, shape, and microscale topography of cell adhesion surface; epitope concentration, epitope clustering characteristics (number of epitopes per cluster, spacing between epitopes within cluster, spacing between separate clusters, cluster patterns, and level of disorder in epitope arrangement), and nanotopography. Biochemical characteristics of natural extracellular matrix molecules regard diversity and structural complexity of matrix molecules, affinity and specificity of epitope interaction with cell receptors, role of non-affinity domains, complexity of supramolecular organization, and co-signaling by growth factors or matrix epitopes. Synergy between several matrix aspects enables stem cells to retain their function in vivo and may be a key to generation of long-term, robust, and effective in vitro stem cell culture systems. PMID:26351461

Morphology, spatial pattern and sediment of Nitraria tangutorum nebkhas in barchans interdune areas at the southeast margin of the Badain Jaran Desert, China

NASA Astrophysics Data System (ADS)

Yang, YanYan; Liu, LianYou; Shi, PeiJun; Zhang, GuoMing; Qu, ZhiQiang; Tang, Yan; Lei, Jie; Wen, HaiMing; Xiong, YiYing; Wang, JingPu; Shen, LingLing

2015-03-01

To understand the characteristics of the nebkhas in barchan interdune areas, isolated barchan dunes at the southeast margin of the Badain Jaran Desert in China and Nitraria tangutorun nebkhas in the interdune areas were selected, and the morphometric parameters, spatial patterns, and granulometric characteristics of the nebkhas in various interdune zones were compared. According to the locations relative to barchan dunes, the interdune areas were divided into three zones: the windward interdune zone (Zw), the leeward interdune zone (Zl), and the horn interdune zone (Zh). The zone that is proximal to barchan dunes and has never been disturbed by barchan dunes was also selected (Zi). The morphometric parameters were measured through a satellite image and field investigation. The population density and spatial patterns were analyzed using the satellite image, and surface sediment samples of the nebkhas and barchan dunes were collected for grain size analysis. The morphometric parameters of Nitraria tangutorun nebkhas in the interdune zones differ significantly. The nebkhas in Zh are larger than those observed in the other zones, and the nebkhas are the smallest in Zl. In all of the zones, the long-axis orientation of the nebkhas is perpendicular to the prevailing wind direction. The population density of the nebkhas in Zw is relatively higher, whereas the density in Zh and Zl becomes obviously lower. The spatial distribution of nebkhas in all of the zones can be categorized as a dispersed pattern. The sediments of the nebkhas are coarsest in Zh and finest in Zl. In addition, the sediments of the nebkhas in all of the zones are finer than those of barchan dunes. The amount of sand captured by the nebkhas in the interdune areas is approximately 20% of the volume of barchan dunes. The variations of the nebkhas' sizes, spatial pattern and sediment are subjected to migration, flow field and sand transport of barchan dunes and sand accumulation with plant growth in the interdune areas, which suggest complex mutual interactions between barchan dunes and the nebkhas in the interdune areas.

Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

USGS Publications Warehouse

Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

PubMed Central

Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

Spatiotemporal chaos in the dynamics of buoyantly and diffusively unstable chemical fronts

NASA Astrophysics Data System (ADS)

Baroni, M. P. M. A.; Guéron, E.; De Wit, A.

2012-03-01

Nonlinear dynamics resulting from the interplay between diffusive and buoyancy-driven Rayleigh-Taylor (RT) instabilities of autocatalytic traveling fronts are analyzed numerically for various values of the relevant parameters. These are the Rayleigh numbers of the reactant A and autocatalytic product B solutions as well as the ratio D =DB/DA between the diffusion coefficients of the two key chemical species. The interplay between the coarsening dynamics characteristic of the RT instability and the constant short wavelength modulation of the diffusive instability can lead in some regimes to complex dynamics dominated by irregular succession of birth and death of fingers. By using spectral entropy measurements, we characterize the transition between order and spatial disorder in this system. The analysis of the power spectrum and autocorrelation function, moreover, identifies similarities between the various spatial patterns. The contribution of the diffusive instability to the complex dynamics is discussed.

Understanding the effects of predictability, duration, and spatial pattern of drying on benthic invertebrate assemblages in two contrasting intermittent streams

PubMed Central

von Schiller, Daniel; Barberá, Gonzalo G.; Díaz, Angela M.; Arce, Maria Isabel; del Campo, Rubén; Tockner, Klement

2018-01-01

In the present study, we examined the effects of different drying conditions on the composition, structure and function of benthic invertebrate assemblages. We approached this objective by comparing invertebrate assemblages in perennial and intermittent sites along two intermittent Mediterranean streams with contrasting predictability, duration, and spatial patterns of drying: Fuirosos (high predictability, short duration, downstream drying pattern) and Rogativa (low predictability, long duration, patchy drying pattern). Specifically, we quantified the contribution of individual taxa to those differences, the degree of nestedness, and shifts in the composition, structure and function of benthic invertebrate assemblages along flow intermittence gradients. We observed greater effects of drying on the benthic invertebrate composition in Fuirosos than in Rogativa, resulting in a higher dissimilarity of assemblages between perennial and intermittent sites, as well as a lower degree of nestedness. Furthermore, a higher number of biotic metrics related to richness, abundance and biological traits were significantly different between perennial and intermittent sites in Fuirosos, despite a shorter dry period compared to Rogativa. At the same time, slightly different responses were detected during post-drying (autumn) than pre-drying (spring) conditions in this stream. In Rogativa, shifts in benthic invertebrate assemblages along increasing gradients of flow intermittence were found for three metrics (Ephemeroptera, Plecoptera and Trichoptera (EPT) and Odonata, Coleoptera and Heteroptera (OCH) abundances and aerial active dispersal. Furthermore, we demonstrated that combined gradients of dry period duration and distance to nearest perennial reach can generate complex, and different, responses of benthic invertebrate assemblages, depending on the flow intermittence metric. Our study advances the notion that special attention should be paid to the predictability, duration and spatial patterns of drying in intermittent streams in order to disentangle the effects of drying on benthic invertebrate assemblages, in particular in areas subject to high spatial heterogeneity and temporal variability in drying conditions. PMID:29590140

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.

Temporal and Spatial Patterns of Preferential Flow Occurrence in the Shale Hills Catchment: From the Hillslope to the Catchment Scales

NASA Astrophysics Data System (ADS)

Liu, H.; Lin, H.

2013-12-01

Understanding temporal and spatial patterns of preferential flow (PF) occurrence is important in revealing hillslope and catchment hydrologic and biogeochemical processes. Quantitative assessment of the frequency and control of PF occurrence in the field, however, has been limited, especially at the landscape scale of hillslope and catchment. By using 5.5-years' (2007-2012) real-time soil moisture at 10 sites response to 323 precipitation events, we tested the temporal consistency of PF occurrence at the hillslope scale in the forested Shale Hills Catchment; and by using 25 additional sites with at least 1-year data (2011-2012), we evaluated the spatial patterns of PF occurrence across the catchment. To explore the potential effects of PF occurrence on catchment hydrology, wavelet analysis was performed on the recorded time series of hydrological signals (i.e., precipitation, soil moisture, catchment discharge). Considerable temporal consistence was observed in both the frequency and the main controls of PF occurrence at the hillslope scale, which was attributed largely to the statistical stability of precipitation pattern over the monitoring period and the relatively stable subsurface preferential pathways. Preferential flow tended to occur more often in response to intense rainfall events, and favored the conditions at dry hilltop or wet valley floor sites. When upscaling to the entire catchment, topographic control on the PF occurrence was amplified remarkably, leading to the identification of a subsurface PF network in the catchment. Higher frequency of PF occurrence was observed at the valley floor (average 48%), hilltop (average 46%), and swales/hillslopes near the stream (average 40%), while the hillslopes in the eastern part of the catchment were least likely to experience PF (0-20%). No clear relationship, however, was observed between terrain attributes and PF occurrence, because the initiation and persistency of PF in this catchment was controlled jointly by complex interactions among landform units, soil types, initial soil moisture, precipitation features, and season. Through the wavelet method (coherence spectrum and phase differences), dual-pore filtering effects of soil system were proven, rendering it possible to further infer characteristic properties of the underlying hydrological processes in the subsurface. We found that preferential flow dominates the catchment discharge response at short-time periods (< 3 days), while the matrix flow may dominate the discharge response at the time scales of around 10-12 days. The temporal and spatial patterns of PF occurrence revealed in this study can help advance the modeling and prediction of complex PF dynamics in this and other similar landscapes.

[Spatial pattern of land surface dead combustible fuel load in Huzhong forest area in Great Xing'an Mountains].

PubMed

Liu, Zhi-Hua; Chang, Yu; Chen, Hong-Wei; Zhou, Rui; Jing, Guo-Zhi; Zhang, Hong-Xin; Zhang, Chang-Meng

2008-03-01

By using geo-statistics and based on time-lag classification standard, a comparative study was made on the land surface dead combustible fuels in Huzhong forest area in Great Xing'an Mountains. The results indicated that the first level land surface dead combustible fuel, i. e., 1 h time-lag dead fuel, presented stronger spatial auto-correlation, with an average of 762.35 g x m(-2) and contributing to 55.54% of the total load. Its determining factors were species composition and stand age. The second and third levels land surface dead combustible fuel, i. e., 10 h and 100 h time-lag dead fuels, had a sum of 610.26 g x m(-2), and presented weaker spatial auto-correlation than 1 h time-lag dead fuel. Their determining factor was the disturbance history of forest stand. The complexity and heterogeneity of the factors determining the quality and quantity of forest land surface dead combustible fuels were the main reasons for the relatively inaccurate interpolation. However, the utilization of field survey data coupled with geo-statistics could easily and accurately interpolate the spatial pattern of forest land surface dead combustible fuel loads, and indirectly provide a practical basis for forest management.

Control of complex dynamics and chaos in distributed parameter systems

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

Chakravarti, S.; Marek, M.; Ray, W.H.

This paper discusses a methodology for controlling complex dynamics and chaos in distributed parameter systems. The reaction-diffusion system with Brusselator kinetics, where the torus-doubling or quasi-periodic (two characteristic incommensurate frequencies) route to chaos exists in a defined range of parameter values, is used as an example. Poincare maps are used for characterization of quasi-periodic and chaotic attractors. The dominant modes or topos, which are inherent properties of the system, are identified by means of the Singular Value Decomposition. Tested modal feedback control schemas based on identified dominant spatial modes confirm the possibility of stabilization of simple quasi-periodic trajectories in themore » complex quasi-periodic or chaotic spatiotemporal patterns.« less

Ablation of multi-wavelet re-entry: general principles and in silico analyses.

PubMed

Spector, Peter S; Correa de Sa, Daniel D; Tischler, Ethan S; Thompson, Nathaniel C; Habel, Nicole; Stinnett-Donnelly, Justin; Benson, Bryce E; Bielau, Philipp; Bates, Jason H T

2012-11-01

Catheter ablation strategies for treatment of cardiac arrhythmias are quite successful when targeting spatially constrained substrates. Complex, dynamic, and spatially varying substrates, however, pose a significant challenge for ablation, which delivers spatially fixed lesions. We describe tissue excitation using concepts of surface topology which provides a framework for addressing this challenge. The aim of this study was to test the efficacy of mechanism-based ablation strategies in the setting of complex dynamic substrates. We used a computational model of propagation through electrically excitable tissue to test the effects of ablation on excitation patterns of progressively greater complexity, from fixed rotors to multi-wavelet re-entry. Our results indicate that (i) focal ablation at a spiral-wave core does not result in termination; (ii) termination requires linear lesions from the tissue edge to the spiral-wave core; (iii) meandering spiral-waves terminate upon collision with a boundary (linear lesion or tissue edge); (iv) the probability of terminating multi-wavelet re-entry is proportional to the ratio of total boundary length to tissue area; (v) the efficacy of linear lesions varies directly with the regional density of spiral-waves. We establish a theoretical framework for re-entrant arrhythmias that explains the requirements for their successful treatment. We demonstrate the inadequacy of focal ablation for spatially fixed spiral-waves. Mechanistically guided principles for ablating multi-wavelet re-entry are provided. The potential to capitalize upon regional heterogeneity of spiral-wave density for improved ablation efficacy is described.

Dyke-sill relationships in Karoo dolerites as indicators of propagation and emplacement processes of mafic magmas in the shallow crust

NASA Astrophysics Data System (ADS)

Coetzee, A.; Kisters, A. F. M.

2017-04-01

This paper describes the spatial and temporal relationships between Karoo-age (ca. 180 Ma) dolerite dykes and a regional-scale saucer-sill complex from the Secunda (coal mine) Complex in the northeastern parts of the Karoo Basin of South Africa. Unlike parallel dyke swarms of regional extensional settings, mafic dykes commonly show curved geometries and highly variable orientations, short strike extents and complex cross-cutting and intersecting relationships. Importantly, the dyke networks originate from the upper contacts of the first-order dolerite sill-saucer structure and are not the feeders of the saucer complex. Cross-cutting relationships indicate the largely contemporaneous formation of dykes and the inner sill and inclined sheets of the underlying saucer. Systematic dykes form a distinct boxwork-type pattern of two high-angle, interconnected dyke sets. The formation and orientation of this dyke set is interpreted to be related to the stretching of roof strata above elongated magma lobes that facilitated the propagation of the inner sill, similar to the "cracked lid" model described for large saucer complexes in Antarctica. Dyke patterns generally reflect the saucer emplacement process and the associated deformation of wall rocks rather than far-field regional stresses.

Biofilm three-dimensional architecture influences in situ pH distribution pattern on the human enamel surface

PubMed Central

Xiao, Jin; Hara, Anderson T; Kim, Dongyeop; Zero, Domenick T; Koo, Hyun; Hwang, Geelsu

2017-01-01

To investigate how the biofilm three-dimensional (3D) architecture influences in situ pH distribution patterns on the enamel surface. Biofilms were formed on human tooth enamel in the presence of 1% sucrose or 0.5% glucose plus 0.5% fructose. At specific time points, biofilms were exposed to a neutral pH buffer to mimic the buffering of saliva and subsequently pulsed with 1% glucose to induce re-acidification. Simultaneous 3D pH mapping and architecture of intact biofilms was performed using two-photon confocal microscopy. The enamel surface and mineral content characteristics were examined successively via optical profilometry and microradiography analyses. Sucrose-mediated biofilm formation created spatial heterogeneities manifested by complex networks of bacterial clusters (microcolonies). Acidic regions (pH<5.5) were found only in the interior of microcolonies, which impedes rapid neutralization (taking more than 120 min for neutralization). Glucose exposure rapidly re-created the acidic niches, indicating formation of diffusion barriers associated with microcolonies structure. Enamel demineralization (white spots), rougher surface, deeper lesion and more mineral loss appeared to be associated with the localization of these bacterial clusters at the biofilm-enamel interface. Similar 3D architecture was observed in plaque-biofilms formed in vivo in the presence of sucrose. The formation of complex 3D architectures creates spatially heterogeneous acidic microenvironments in close proximity of enamel surface, which might correlate with the localized pattern of the onset of carious lesions (white spot like) on teeth. PMID:28452377

Numerical simulations of significant orographic precipitation in Madeira island

NASA Astrophysics Data System (ADS)

Couto, Flavio Tiago; Ducrocq, Véronique; Salgado, Rui; Costa, Maria João

2016-03-01

High-resolution simulations of high precipitation events with the MESO-NH model are presented, and also used to verify that increasing horizontal resolution in zones of complex orography, such as in Madeira island, improve the simulation of the spatial distribution and total precipitation. The simulations succeeded in reproducing the general structure of the cloudy systems over the ocean in the four periods considered of significant accumulated precipitation. The accumulated precipitation over the Madeira was better represented with the 0.5 km horizontal resolution and occurred under four distinct synoptic situations. Different spatial patterns of the rainfall distribution over the Madeira have been identified.

Spatially modulated laser pulses for printing electronics.

PubMed

Auyeung, Raymond C Y; Kim, Heungsoo; Mathews, Scott; Piqué, Alberto

2015-11-01

The use of a digital micromirror device (DMD) in laser-induced forward transfer (LIFT) is reviewed. Combining this technique with high-viscosity donor ink (silver nanopaste) results in laser-printed features that are highly congruent in shape and size to the incident laser beam spatial profile. The DMD empowers LIFT to become a highly parallel, rapidly reconfigurable direct-write technology. By adapting half-toning techniques to the DMD bitmap image, the laser transfer threshold fluence for 10 μm features can be reduced using an edge-enhanced beam profile. The integration of LIFT with this beam-shaping technique allows the printing of complex large-area patterns with a single laser pulse.

Spatial inventory integrating raster databases and point sample data. [Geographic Information System for timber inventory

NASA Technical Reports Server (NTRS)

Strahler, A. H.; Woodcock, C. E.; Logan, T. L.

1983-01-01

A timber inventory of the Eldorado National Forest, located in east-central California, provides an example of the use of a Geographic Information System (GIS) to stratify large areas of land for sampling and the collection of statistical data. The raster-based GIS format of the VICAR/IBIS software system allows simple and rapid tabulation of areas, and facilitates the selection of random locations for ground sampling. Algorithms that simplify the complex spatial pattern of raster-based information, and convert raster format data to strings of coordinate vectors, provide a link to conventional vector-based geographic information systems.

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

[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

Quantum image median filtering in the spatial domain

NASA Astrophysics Data System (ADS)

Li, Panchi; Liu, Xiande; Xiao, Hong

2018-03-01

Spatial filtering is one principal tool used in image processing for a broad spectrum of applications. Median filtering has become a prominent representation of spatial filtering because its performance in noise reduction is excellent. Although filtering of quantum images in the frequency domain has been described in the literature, and there is a one-to-one correspondence between linear spatial filters and filters in the frequency domain, median filtering is a nonlinear process that cannot be achieved in the frequency domain. We therefore investigated the spatial filtering of quantum image, focusing on the design method of the quantum median filter and applications in image de-noising. To this end, first, we presented the quantum circuits for three basic modules (i.e., Cycle Shift, Comparator, and Swap), and then, we design two composite modules (i.e., Sort and Median Calculation). We next constructed a complete quantum circuit that implements the median filtering task and present the results of several simulation experiments on some grayscale images with different noise patterns. Although experimental results show that the proposed scheme has almost the same noise suppression capacity as its classical counterpart, the complexity analysis shows that the proposed scheme can reduce the computational complexity of the classical median filter from the exponential function of image size n to the second-order polynomial function of image size n, so that the classical method can be speeded up.

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.

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...

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

A new mechanism for spatial pattern formation via lateral and protrusion-mediated lateral signalling

PubMed Central

Hunter, Ginger L.; Baum, Buzz

2016-01-01

Tissue organization and patterning are critical during development when genetically identical cells take on different fates. Lateral signalling plays an important role in this process by helping to generate self-organized spatial patterns in an otherwise uniform collection of cells. Recent data suggest that lateral signalling can be mediated both by junctional contacts between neighbouring cells and via cellular protrusions that allow non-neighbouring cells to interact with one another at a distance. However, it remains unclear precisely how signalling mediated by these distinct types of cell–cell contact can physically contribute to the generation of complex patterns without the assistance of diffusible morphogens or pre-patterns. To explore this question, in this work we develop a model of lateral signalling based on a single receptor/ligand pair as exemplified by Notch and Delta. We show that allowing the signalling kinetics to differ at junctional versus protrusion-mediated contacts, an assumption inspired by recent data which show that the cleavage of Notch in several systems requires both Delta binding and the application of mechanical force, permits individual cells to act to promote both lateral activation and lateral inhibition. Strikingly, under this model, in which Delta can sequester Notch, a variety of patterns resembling those typical of reaction–diffusion systems is observed, together with more unusual patterns that arise when we consider changes in signalling kinetics, and in the length and distribution of protrusions. Importantly, these patterns are self-organizing—so that local interactions drive tissue-scale patterning. Together, these data show that protrusions can, in principle, generate different types of patterns in addition to contributing to long-range signalling and to pattern refinement. PMID:27807273

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.

Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition

PubMed Central

Cui, Zhiming; Zhao, Pengpeng

2014-01-01

A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target. Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets. Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering. It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix. Then, it clusters sample data points into different clusters. After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed. The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness. The real-world application verified its feasibility and the validity. PMID:24605045

Unmanned Aircraft Systems for Studying Spatial Abundance of Ungulates: Relevance to Spatial Epidemiology

PubMed Central

Barasona, José A.; Mulero-Pázmány, Margarita; Acevedo, Pelayo; Negro, Juan J.; Torres, María J.; Gortázar, Christian; Vicente, Joaquín

2014-01-01

Complex ecological and epidemiological systems require multidisciplinary and innovative research. Low cost unmanned aircraft systems (UAS) can provide information on the spatial pattern of hosts’ distribution and abundance, which is crucial as regards modelling the determinants of disease transmission and persistence on a fine spatial scale. In this context we have studied the spatial epidemiology of tuberculosis (TB) in the ungulate community of Doñana National Park (South-western Spain) by modelling species host (red deer, fallow deer and cattle) abundance at fine spatial scale. The use of UAS high-resolution images has allowed us to collect data to model the environmental determinants of host abundance, and in a further step to evaluate their relationships with the spatial risk of TB throughout the ungulate community. We discuss the ecological, epidemiological and logistic conditions under which UAS may contribute to study the wildlife/livestock sanitary interface, where the spatial aggregation of hosts becomes crucial. These findings are relevant for planning and implementing research, fundamentally when managing disease in multi-host systems, and focusing on risky areas. Therefore, managers should prioritize the implementation of control strategies to reduce disease of conservation, economic and social relevance. PMID:25551673

Scale dependency of forest functional diversity assessed using imaging spectroscopy and airborne laser scanning

NASA Astrophysics Data System (ADS)

Schneider, F. D.; Morsdorf, F.; Schmid, B.; Petchey, O. L.; Hueni, A.; Schimel, D.; Schaepman, M. E.

2016-12-01

Forest functional traits offer a mechanistic link between ecological processes and community structure and assembly rules. However, measuring functional traits of forests in a continuous and consistent way is particularly difficult due to the complexity of in-situ measurements and geo-referencing. New imaging spectroscopy measurements overcome these limitations allowing to map physiological traits on broad spatial scales. We mapped leaf chlorophyll, carotenoids and leaf water content over 900 ha of temperate mixed forest (Fig. 1a). The selected traits are functionally important because they are indicating the photosynthetic potential of trees, leaf longevity and protection, as well as tree water and drought stress. Spatially continuous measurements on the scale of individual tree crowns allowed to assess functional diversity patterns on a range of ecological extents. We used indexes of functional richness, divergence and evenness to map different aspects of diversity. Fig. 1b shows an example of physiological richness at an extent of 240 m radius. We compared physiological to morphological diversity patterns, derived based on plant area index, canopy height and foliage height diversity. Our results show that patterns of physiological and morphological diversity generally agree, independently measured by airborne imaging spectroscopy and airborne laser scanning, respectively. The occurrence of disturbance areas and mixtures of broadleaf and needle trees were the main drivers of the observed diversity patterns. Spatial patterns at varying extents and richness-area relationships indicated that environmental filtering is the predominant community assembly process. Our results demonstrate the potential for mapping physiological and morphological diversity in a temperate mixed forest between and within species on scales relevant to study community assembly and structure from space and test the corresponding measurement schemes.

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.

Spatial and temporal heterogeneity of infectious hematopoietic necrosis virus in Pacific Northwest salmonids

USGS Publications Warehouse

Breyta, Rachel; Black, Allison; Kaufman, John; Kurath, Gael

2016-01-01

The aquatic rhaboviral pathogen infectious hematopoietic necrosis virus (IHNV) causes acute disease in juvenile fish of a number of populations of Pacific salmonid species. Heavily managed in both marine and freshwater environments, these fish species are cultured during the juvenile stage in freshwater conservation hatcheries, where IHNV is one of the top three infectious diseases that cause serious morbidity and mortality. Therefore, a comprehensive study of viral genetic surveillance data representing 2590 field isolates collected between 1958 and 2014 was conducted to determine the spatial and temporal patterns of IHNV in the Pacific Northwest of the contiguous United States. Prevalence of infection varied over time, fluctuating over a rough 5–7 year cycle. The genetic analysis revealed numerous subgroups of IHNV, each of which exhibited spatial heterogeneity. Within all subgroups, dominant genetic types were apparent, though the temporal patterns of emergence of these types varied among subgroups. Finally, the affinity or fidelity of subgroups to specific host species also varied, where UC subgroup viruses exhibited a more generalist profile and all other subgroups exhibited a specialist profile. These complex patterns are likely synergistically driven by numerous ecological, pathobiological, and anthropogenic factors. Since only a few anthropogenic factors are candidates for managed intervention aimed at improving the health of threatened or endangered salmonid fish populations, determining the relative impact of these factors is a high priority for future studies.

Estimation and mapping of wet and dry mercury deposition across northeastern North America

USGS Publications Warehouse

Miller, E.K.; Vanarsdale, A.; Keeler, G.J.; Chalmers, A.; Poissant, L.; Kamman, N.C.; Brulotte, R.

2005-01-01

Whereas many ecosystem characteristics and processes influence mercury accumulation in higher trophic-level organisms, the mercury flux from the atmosphere to a lake and its watershed is a likely factor in potential risk to biota. Atmospheric deposition clearly affects mercury accumulation in soils and lake sediments. Thus, knowledge of spatial patterns in atmospheric deposition may provide information for assessing the relative risk for ecosystems to exhibit excessive biotic mercury contamination. Atmospheric mercury concentrations in aerosol, vapor, and liquid phases from four observation networks were used to estimate regional surface concentration fields. Statistical models were developed to relate sparsely measured mercury vapor and aerosol concentrations to the more commonly measured mercury concentration in precipitation. High spatial resolution deposition velocities for different phases (precipitation, cloud droplets, aerosols, and reactive gaseous mercury (RGM)) were computed using inferential models. An empirical model was developed to estimate gaseous elemental mercury (GEM) deposition. Spatial patterns of estimated total mercury deposition were complex. Generally, deposition was higher in the southwest and lower in the northeast. Elevation, land cover, and proximity to urban areas modified the general pattern. The estimated net GEM and RGM fluxes were each greater than or equal to wet deposition in many areas. Mercury assimilation by plant foliage may provide a substantial input of methyl-mercury (MeHg) to ecosystems. ?? 2005 Springer Science+Business Media, Inc.

Ordering Transitions in Liquid Crystals Permit Imaging of Spatial and Temporal Patterns Formed by Proteins Penetrating into Lipid-Laden Interfaces

PubMed Central

Daschner De Tercero, Maren; Abbott, Nicholas L.

2013-01-01

Recent studies have reported that full monolayers of L-α-dilaurylphosphatidylcholine (L-DLPC) and D-α-dipalmitoylphosphatidylcholine (D-DPPC) formed at interfaces between thermotropic liquid crystals (LCs) and aqueous phases lead to homeotropic (perpendicular) orientations of nematic LCs and that specific binding of proteins to these interfaces (such as phospholipase A2 binding to D-DPPC) can trigger orientational ordering transitions in the liquid crystals. We report on the nonspecific interactions of proteins with aqueous-LC interfaces decorated with partial monolayer coverage of L-DLPC. Whereas nonspecific interactions of four proteins (cytochrome c, bovine serum albumin,immunoglobulins, and neutravidin) do not perturb the ordering of the LC when a full monolayer of L-DLPC is assembled at the aqueous-LC interface, we observe patterned orientational transitions in the LC that reflect penetration of proteins into the interface of the LC with partial monolayer coverage of L-DLPC. The spatial patterns formed by the proteins and lipids at the interface are surprisingly complex, and in some cases the protein domains are found to compartmentalize lipid within the interfaces. These results suggest that phospholipid-decorated interfaces between thermotropic liquid crystals and aqueous phases offer the basis of a simple and versatile tool to study the spatial organization and dynamics ofprotein networks formed at mobile, lipid-decorated interfaces. PMID:23671353

Generalized reproduction numbers and the prediction of patterns in waterborne disease.

PubMed

Gatto, Marino; Mari, Lorenzo; Bertuzzo, Enrico; Casagrandi, Renato; Righetto, Lorenzo; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2012-11-27

Understanding, predicting, and controlling outbreaks of waterborne diseases are crucial goals of public health policies, but pose challenging problems because infection patterns are influenced by spatial structure and temporal asynchrony. Although explicit spatial modeling is made possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here we show that the requirement that all the local reproduction numbers R0 be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix G0, explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number Λ0 (the dominant eigenvalue of G0) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of G0. Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of G0 provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology, and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections.

Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Werban, Ulrike; Zacharias, Steffen; Pohle, Marco; Dietrich, Peter; Wollschläger, Ute

2017-01-01

Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ, with particular focus on the temporal variability of the spatial patterns of ECa and θ. To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ, and (iii) the ECa-θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ, and the use of EMI-based ECa data with respect to hydrological applications.

Probing quantum correlation functions through energy-absorption interferometry

NASA Astrophysics Data System (ADS)

Withington, S.; Thomas, C. N.; Goldie, D. J.

2017-08-01

An interferometric technique is described for determining the spatial forms of the individual degrees of freedom through which a many-body system can absorb energy from its environment. The method separates out the spatial forms of the coherent excitations present at any single frequency; it is not necessary to sweep the frequency and then infer the spatial forms of possible excitations from resonant absorption features. The system under test is excited with two external sources, which create generalized forces, and the fringe in the total power dissipated is measured as the relative phase between the sources is varied. If the complex fringe visibility is measured for different pairs of source locations, the anti-Hermitian part of the complex-valued nonlocal correlation tensor can be determined, which can then be decomposed to give the natural dynamical modes of the system and their relative responsivities. If each source in the interferometer creates a different kind of force, the spatial forms of the individual excitations that are responsible for cross-correlated response can be found. The technique is related to holography, but measures the state of coherence to which the system is maximally sensitive. It can be applied across a wide range of wavelengths, in a variety of ways, to homogeneous media, thin films, patterned structures, and components such as sensors, detectors, and energy-harvesting absorbers.

Ionic wave propagation and collision in an excitable circuit model of microtubules

NASA Astrophysics Data System (ADS)

Guemkam Ghomsi, P.; Tameh Berinyoh, J. T.; Moukam Kakmeni, F. M.

2018-02-01

In this paper, we report the propensity to excitability of the internal structure of cellular microtubules, modelled as a relatively large one-dimensional spatial array of electrical units with nonlinear resistive features. We propose a model mimicking the dynamics of a large set of such intracellular dynamical entities as an excitable medium. We show that the behavior of such lattices can be described by a complex Ginzburg-Landau equation, which admits several wave solutions, including the plane waves paradigm. A stability analysis of the plane waves solutions of our dynamical system is conducted both analytically and numerically. It is observed that perturbed plane waves will always evolve toward promoting the generation of localized periodic waves trains. These modes include both stationary and travelling spatial excitations. They encompass, on one hand, localized structures such as solitary waves embracing bright solitons, dark solitons, and bisolitonic impulses with head-on collisions phenomena, and on the other hand, the appearance of both spatially homogeneous and spatially inhomogeneous stationary patterns. This ability exhibited by our array of proteinic elements to display several states of excitability exposes their stunning biological and physical complexity and is of high relevance in the description of the developmental and informative processes occurring on the subcellular scale.

Ionic wave propagation and collision in an excitable circuit model of microtubules.

PubMed

Guemkam Ghomsi, P; Tameh Berinyoh, J T; Moukam Kakmeni, F M

2018-02-01

In this paper, we report the propensity to excitability of the internal structure of cellular microtubules, modelled as a relatively large one-dimensional spatial array of electrical units with nonlinear resistive features. We propose a model mimicking the dynamics of a large set of such intracellular dynamical entities as an excitable medium. We show that the behavior of such lattices can be described by a complex Ginzburg-Landau equation, which admits several wave solutions, including the plane waves paradigm. A stability analysis of the plane waves solutions of our dynamical system is conducted both analytically and numerically. It is observed that perturbed plane waves will always evolve toward promoting the generation of localized periodic waves trains. These modes include both stationary and travelling spatial excitations. They encompass, on one hand, localized structures such as solitary waves embracing bright solitons, dark solitons, and bisolitonic impulses with head-on collisions phenomena, and on the other hand, the appearance of both spatially homogeneous and spatially inhomogeneous stationary patterns. This ability exhibited by our array of proteinic elements to display several states of excitability exposes their stunning biological and physical complexity and is of high relevance in the description of the developmental and informative processes occurring on the subcellular scale.

Uncomfortable images in art and nature.

PubMed

Fernandez, Dominic; Wilkins, Arnold J

2008-01-01

The ratings of discomfort from a wide variety of images can be predicted from the energy at different spatial scales in the image, as measured by the Fourier amplitude spectrum of the luminance. Whereas comfortable images show the regression of Fourier amplitude against spatial frequency common in natural scenes, uncomfortable images show a regression with disproportionately greater amplitude at spatial frequencies within two octaves of 3 cycles deg(-1). In six studies, the amplitude in this spatial frequency range relative to that elsewhere in the spectrum explains variance in judgments of discomfort from art, from images constructed from filtered noise, and from art in which the phase or amplitude spectra have been altered. Striped patterns with spatial frequency within the above range are known to be uncomfortable and capable of provoking headaches and seizures in susceptible persons. The present findings show for the first time that, even in more complex images, the energy in this spatial-frequency range is associated with aversion. We propose a simple measurement that can predict aversion to those works of art that have reached the national media because of negative public reaction.

Uncomfortable images in art and nature

PubMed Central

Fernandez, Dominic; Wilkins, Arnold J.

2008-01-01

We find that the ratings of discomfort from a wide variety of images can be predicted from the energy at different spatial scales in the image, as measured by the Fourier amplitude spectrum of the luminance. Whereas comfortable images show the regression of Fourier amplitude against spatial frequency common in natural scenes, uncomfortable images show a regression with disproportionately greater amplitude at spatial frequencies within two octaves of 3 cycles per degree. In six studies, the amplitude at this spatial frequency relative to that 3 octaves below explains variance in judgments of discomfort from art, from images constructed from filtered noise and from art in which the phase or amplitude spectra have been altered. Striped patterns with spatial frequency within the above range are known to be uncomfortable and capable of provoking headaches and seizures in susceptible persons. The present findings show for the first time that even in more complex images the energy in this spatial frequency range is associated with aversion. We propose a simple measurement that can predict aversion to those works of art that have reached the national media because of negative public reaction. PMID:18773732

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…

The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers.

PubMed

Amalric, Marie; Wang, Liping; Pica, Pierre; Figueira, Santiago; Sigman, Mariano; Dehaene, Stanislas

2017-01-01

During language processing, humans form complex embedded representations from sequential inputs. Here, we ask whether a "geometrical language" with recursive embedding also underlies the human ability to encode sequences of spatial locations. We introduce a novel paradigm in which subjects are exposed to a sequence of spatial locations on an octagon, and are asked to predict future locations. The sequences vary in complexity according to a well-defined language comprising elementary primitives and recursive rules. A detailed analysis of error patterns indicates that primitives of symmetry and rotation are spontaneously detected and used by adults, preschoolers, and adult members of an indigene group in the Amazon, the Munduruku, who have a restricted numerical and geometrical lexicon and limited access to schooling. Furthermore, subjects readily combine these geometrical primitives into hierarchically organized expressions. By evaluating a large set of such combinations, we obtained a first view of the language needed to account for the representation of visuospatial sequences in humans, and conclude that they encode visuospatial sequences by minimizing the complexity of the structured expressions that capture them.

The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers

PubMed Central

Amalric, Marie; Wang, Liping; Figueira, Santiago; Sigman, Mariano; Dehaene, Stanislas

2017-01-01

During language processing, humans form complex embedded representations from sequential inputs. Here, we ask whether a “geometrical language” with recursive embedding also underlies the human ability to encode sequences of spatial locations. We introduce a novel paradigm in which subjects are exposed to a sequence of spatial locations on an octagon, and are asked to predict future locations. The sequences vary in complexity according to a well-defined language comprising elementary primitives and recursive rules. A detailed analysis of error patterns indicates that primitives of symmetry and rotation are spontaneously detected and used by adults, preschoolers, and adult members of an indigene group in the Amazon, the Munduruku, who have a restricted numerical and geometrical lexicon and limited access to schooling. Furthermore, subjects readily combine these geometrical primitives into hierarchically organized expressions. By evaluating a large set of such combinations, we obtained a first view of the language needed to account for the representation of visuospatial sequences in humans, and conclude that they encode visuospatial sequences by minimizing the complexity of the structured expressions that capture them. PMID:28125595

Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

NASA Astrophysics Data System (ADS)

Santos, Monica; Fragoso, Marcelo

2010-05-01

Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude, latitude, distance from sea and distance to the highest orographic barrier) on the rainfall behaviours described by the studied variables. The techniques of spatial interpolation evaluated include univariate and multivariate methods: cokriging, kriging, IDW (inverse distance weighted) and multiple linear regression. Validation procedures were used, assessing the estimated errors in the analysis of descriptive statistics of the models. Multiple linear regression models produced satisfactory results in relation to 70% of the rainfall parameters, suggested by lower average percentage of error. However, the results also demonstrates that there is no an unique and ideal model, depending on the rainfall parameter in consideration. Probably, the unsatisfactory results obtained in relation to some rainfall parameters was motivated by constraints as the spatial complexity of the precipitation patterns, as well as to the deficient spatial coverage of the territory by the rain-gauges network. References Diodato, N. (2005). The influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain. Internacional Journal of Climatology, 25(3), 351-363. Goovaerts, P. (2000). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228, 113 - 129.

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.

The humpbacked species richness-curve: A contingent rule for community ecology

USGS Publications Warehouse

Graham, John H.; Duda, Jeffrey J.

2011-01-01

Functional relationships involving species richness may be unimodal, monotonically increasing, monotonically decreasing, bimodal, multimodal, U-shaped, or with no discernable pattern. The unimodal relationships are the most interesting because they suggest dynamic, nonequilibrium community processes. For that reason, they are also contentious. In this paper, we provide a wide-ranging review of the literature on unimodal (humpbacked) species richness-relationships. Though not as widespread as previously thought, unimodal patterns of species richness are often associated with disturbance, predation and herbivory, productivity, spatial heterogeneity, environmental gradients, time, and latitude. These unimodal patterns are contingent on organism and environment; we examine unimodal species richness-curves involving plants, invertebrates, vertebrates, plankton, and microbes in marine, lacustrine, and terrestrial habitats. A goal of future research is to understand the contingent patterns and the complex, interacting processes that generate them.

Putting humans in ecology: consistency in science and management.

PubMed

Hobbs, Larry; Fowler, Charles W

2008-03-01

Normal and abnormal levels of human participation in ecosystems can be revealed through the use of macro-ecological patterns. Such patterns also provide consistent and objective guidance that will lead to achieving and maintaining ecosystem health and sustainability. This paper focuses on the consistency of this type of guidance and management. Such management, in sharp contrast to current management practices, ensures that our actions as individuals, institutions, political groups, societies, and as a species are applied consistently across all temporal, spatial, and organizational scales. This approach supplants management of today, where inconsistency results from debate, politics, and legal and religious polarity. Consistency is achieved when human endeavors are guided by natural patterns. Pattern-based management meets long-standing demands for enlightened management that requires humans to participate in complex systems in consistent and sustainable ways.

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity

PubMed Central

Bennett, James E. M.; Bair, Wyeth

2015-01-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli. PMID:26308406

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity.

PubMed

Bennett, James E M; Bair, Wyeth

2015-08-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli.

Spatial-temporal clustering of tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2016-12-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Spatial-Temporal Clustering of Tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2017-04-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Geologic structures related to New Madrid earthquakes near Memphis, Tennessee, based on gravity and magnetic interpretations

USGS Publications Warehouse

Hildenbrand, T.G.; Stuart, W.D.; Talwani, P.

2001-01-01

New inversions of gravity and magnetic data in the region north of memphis. Tennessee, and south of latitude 36?? define boundaries of regional structures and igneous complexes in the upper crust. Microseismicity patterns near interpreted boundaries suggest that igneous complexes influence the locations of microseismicity. A weak seismicity cluster occurs near one intrusion (Covington pluton), at the intersection of the southwest margin of the Missouri batholith and the southeast margin of the Reelfoot rift. A narrow seismicity trend along the Reelfoot rift axis becomes diffuse near a second intrusion (Osceola intrusive complex) and changes direction to an area along the northwest flank of the intrusion. The axial seismicity trend also contains a tight cluster of earthquakes located just outside the Osceola intrusive complex. The mechanical explanation of the two seismicity patterns is uncertain, but the first cluster may be caused by stress concentration due to the high elastic stiffness and strength of the Covington intrusion. The spatially changing seismicity pattern near the Osceola complex may be caused by the preceding factors plus interaction with faulting along the rift axis. The axial seismicity strand itself is one of several connected and interacting active strands that may produce stress concentrations at strand ends and junctions. The microseismicity clusters at the peripheries of the two intrusions lead us to conclude that these stress concentrations or stressed volumes may be locations of future moderate to large earthquakes near Memphis. Published by Elsevier Science B.V.

Spatio-temporal patterns of hazards and their use in risk assessment and mitigation. Case study of road accidents in Romania

NASA Astrophysics Data System (ADS)

Catalin Stanga, Iulian

2013-04-01

Road accidents are among the leading causes of death in many world countries, partly as an inherent consequence of the increasing mobility of today society. The World Health Organization estimates that 1.3 million people died in road accidents in 2011, which means 186 deaths per million. The tragic picture is completed by millions of peoples experiencing different physical injuries or by the enormous social and economic costs that these events imply. Romania has one of the most unsafe road networks within the European Union, with annual averages of 9400 accidents, 8300 injuries and almost 2680 fatalities (2007-2012). An average of 141 death per million is more than twice the average fatality rate in European Union (about 60 death per million). Other specific indicators (accidents or fatalities reported to the road length, vehicle fleet size, driving license owners or adult population etc.) are even worst in the same European context. Road accidents are caused by a complex series of factors, some of them being a relatively constant premise, while others act as catalyzing factors or triggering agent: road features and quality, vehicle technical state, weather conditions, human related factors etc. All these lead to a complex equation with too many unknown variables, making almost impossible a probabilistic approach. However, the high concentration of accidents in a region or in some road sectors is caused by the existence of a specific context, created by factors with permanent or repetitive character, and leads to the idea of a spatial autocorrelation between locations of different adjoining accident. In the same way, the increasing frequency of road accidents and of their causes repeatability in different periods of the year would allow to identify those black timeframes with higher incidence of road accidents. Identifying and analyzing the road blackspots (hotspots) and black zones would help to improve road safety by acting against the common causes that create the spatial or temporal clustering of crash accidents. Since the 1990's, Geographical Informational Systems (GIS) became a very important tool for traffic and road safety management, allowing not only the spatial and multifactorial analysis, but also graphical and non-graphical outputs. The current paper presents an accessible GIS methodology to study the spatio-temporal pattern of injury related road accidents, to identify the high density accidents zones, to make a cluster analysis, to create multicriterial typologies, to identify spatial and temporal similarities and to explain them. In this purpose, a Geographical Information System was created, allowing a complex analysis that involves not only the events, but also a large set of interrelated and spatially linked attributes. The GIS includes the accidents as georeferenced point elements with a spatially linked attribute database: identification information (date, location details); accident type; main, secondary and aggravating causes; data about driver; vehicle information; consequences (damages, injured peoples and fatalities). Each attribute has its own number code that allows both the statistical analysis and the spatial interrogation. The database includes those road accidents that led to physical injuries and loss of human lives between 2007 and 2012 and the spatial analysis was realized using TNTmips 7.3 software facilities. Data aggregation and processing allowed creating the spatial pattern of injury related road accidents through Kernel density estimation at three different levels (national - Romania; county level - Iasi County; local level - Iasi town). Spider graphs were used to create the temporal pattern or road accidents at three levels (daily, weekly and monthly) directly related to their causes. Moreover the spatial and temporal database relates the natural hazards (glazed frost, fog, and blizzard) with the human made ones, giving the opportunity to evaluate the nature of uncertainties in risk assessment. At the end, this paper provides a clustering methodology based on several environmental indicators intended to classify the spatial and temporal hotspots of road traffic insecurity. The results are a useful guide for planners and decision makers in developing effective road safety strategies and measures.

Field-scale Prediction of Enhanced DNAPL Dissolution Using Partitioning Tracers and Flow Pattern Effects

NASA Astrophysics Data System (ADS)

Wang, F.; Annable, M. D.; Jawitz, J. W.

2012-12-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a PCE-contaminated dry cleaner site, located in Jacksonville, Florida. The EST is an analytical solution with field-measurable input parameters. Here, measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ alcohol (ethanol) flood. In addition, a simulated partitioning tracer test from a calibrated spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The ethanol prediction based on both the field partitioning tracer test and the UTCHEM tracer test simulation closely matched the field data. The PCE EST prediction showed a peak shift to an earlier arrival time that was concluded to be caused by well screen interval differences between the field tracer test and alcohol flood. This observation was based on a modeling assessment of potential factors that may influence predictions by using UTCHEM simulations. The imposed injection and pumping flow pattern at this site for both the partitioning tracer test and alcohol flood was more complex than the natural gradient flow pattern (NGFP). Both the EST model and UTCHEM were also used to predict PCE dissolution under natural gradient conditions, with much simpler flow patterns than the forced-gradient double five spot of the alcohol flood. The NGFP predictions based on parameters determined from tracer tests conducted with complex flow patterns underestimated PCE concentrations and total mass removal. This suggests that the flow patterns influence aqueous dissolution and that the aqueous dissolution under the NGFP is more efficient than dissolution under complex flow patterns.

Temporal and spatial evolution characteristics of gas-liquid two-phase flow pattern based on image texture spectrum descriptor

NASA Astrophysics Data System (ADS)

Zhou, Xi-Guo; Jin, Ning-De; Wang, Zhen-Ya; Zhang, Wen-Yin

2009-11-01

The dynamic image information of typical gas-liquid two-phase flow patterns in vertical upward pipe is captured by a highspeed dynamic camera. The texture spectrum descriptor is used to describe the texture characteristics of the processed images whose content is represented in the form of texture spectrum histogram, and four time-varying characteristic parameter indexes which represent image texture structure of different flow patterns are extracted. The study results show that the amplitude fluctuation of texture characteristic parameter indexes of bubble flow is lowest and shows very random complex dynamic behavior; the amplitude fluctuation of slug flow is higher and shows intermittent motion behavior between gas slug and liquid slug, and the amplitude fluctuation of churn flow is the highest and shows better periodicity; the amplitude fluctuation of bubble-slug flow is from low to high and oscillating frequence is higher than that of slug flow, and includes the features of both slug flow and bubble flow; the slug-churn flow loses the periodicity of slug flow and churn flow, and the amplitude fluctuation is high. The results indicate that the image texture characteristic parameter indexes of different flow pattern can reflect the flow characteristics of gas-liquid two-phase flow, which provides a new approach to understand the temporal and spatial evolution of flow pattern dynamics.

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

Effects of spatial heterogeneity and material anisotropy on the fracture pattern and macroscopic effective toughness of Mancos Shale in Brazilian tests

NASA Astrophysics Data System (ADS)

Na, SeonHong; Sun, WaiChing; Ingraham, Mathew D.; Yoon, Hongkyu

2017-08-01

For assessing energy-related activities in the subsurface, it is important to investigate the impact of the spatial variability and anisotropy on the geomechanical behavior of shale. The Brazilian test, an indirect tensile-splitting method, is performed in this work, and the evolution of strain field is obtained using digital image correlation. Experimental results show the significant impact of local heterogeneity and lamination on the crack pattern characteristics. For numerical simulations, a phase field method is used to simulate the brittle fracture behavior under various Brazilian test conditions. In this study, shale is assumed to consist of two constituents including the stiff and soft layers to which the same toughness but different elastic moduli are assigned. Microstructural heterogeneity is simplified to represent mesoscale (e.g., millimeter scale) features such as layer orientation, thickness, volume fraction, and defects. The effect of these structural attributes on the onset, propagation, and coalescence of cracks is explored. The simulation results show that spatial heterogeneity and material anisotropy highly affect crack patterns and effective fracture toughness, and the elastic contrast of two constituents significantly alters the effective toughness. However, the complex crack patterns observed in the experiments cannot completely be accounted for by either an isotropic or transversely isotropic effective medium approach. This implies that cracks developed in the layered system may coalesce in complicated ways depending on the local heterogeneity, and the interaction mechanisms between the cracks using two-constituent systems may explain the wide range of effective toughness of shale reported in the literature.

Effects of spatial heterogeneity and material anisotropy on the fracture pattern and macroscopic effective toughness of Mancos Shale in Brazilian tests

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

Na, SeonHong; Sun, WaiChing; Ingraham, Mathew D.

For assessing energy-related activities in the subsurface, it is important to investigate the impact of the spatial variability and anisotropy on the geomechanical behavior of shale. The Brazilian test, an indirect tensile-splitting method, is performed in this work, and the evolution of strain field is obtained using digital image correlation. Experimental results show the significant impact of local heterogeneity and lamination on the crack pattern characteristics. For numerical simulations, a phase field method is used to simulate the brittle fracture behavior under various Brazilian test conditions. In this study, shale is assumed to consist of two constituents including the stiffmore » and soft layers to which the same toughness but different elastic moduli are assigned. Microstructural heterogeneity is simplified to represent mesoscale (e.g., millimeter scale) features such as layer orientation, thickness, volume fraction, and defects. The effect of these structural attributes on the onset, propagation, and coalescence of cracks is explored. The simulation results show that spatial heterogeneity and material anisotropy highly affect crack patterns and effective fracture toughness, and the elastic contrast of two constituents significantly alters the effective toughness. However, the complex crack patterns observed in the experiments cannot completely be accounted for by either an isotropic or transversely isotropic effective medium approach. In conclusion, this implies that cracks developed in the layered system may coalesce in complicated ways depending on the local heterogeneity, and the interaction mechanisms between the cracks using two-constituent systems may explain the wide range of effective toughness of shale reported in the literature.« less

Movement patterns of silvertip sharks ( Carcharhinus albimarginatus) on coral reefs

NASA Astrophysics Data System (ADS)

Espinoza, Mario; Heupel, Michelle. R.; Tobin, Andrew J.; Simpfendorfer, Colin A.

2015-09-01

Understanding how sharks use coral reefs is essential for assessing risk of exposure to fisheries, habitat loss, and climate change. Despite a wide Indo-Pacific distribution, little is known about the spatial ecology of silvertip sharks ( Carcharhinus albimarginatus), compromising the ability to effectively manage their populations. We examined the residency and movements of silvertip sharks in the central Great Barrier Reef (GBR). An array of 56 VR2W acoustic receivers was used to monitor shark movements on 17 semi-isolated reefs. Twenty-seven individuals tagged with acoustic transmitters were monitored from 70 to 731 d. Residency index to the study site ranged from 0.05 to 0.97, with a mean residency (±SD) of 0.57 ± 0.26, but most individuals were detected at or near their tagging reef. Clear seasonal patterns were apparent, with fewer individuals detected between September and February. A large proportion of the tagged population (>71 %) moved regularly between reefs. Silvertip sharks were detected less during daytime and exhibited a strong diel pattern in depth use, which may be a strategy for optimizing energetic budgets and foraging opportunities. This study provides the first detailed examination of the spatial ecology and behavior of silvertip sharks on coral reefs. Silvertip sharks remained resident at coral reef habitats over long periods, but our results also suggest this species may have more complex movement patterns and use larger areas of the GBR than common reef shark species. Our findings highlight the need to further understand the movement ecology of silvertip sharks at different spatial and temporal scales, which is critical for developing effective management approaches.

Effects of spatial heterogeneity and material anisotropy on the fracture pattern and macroscopic effective toughness of Mancos Shale in Brazilian tests

DOE PAGES

Na, SeonHong; Sun, WaiChing; Ingraham, Mathew D.; ...

2017-07-31

For assessing energy-related activities in the subsurface, it is important to investigate the impact of the spatial variability and anisotropy on the geomechanical behavior of shale. The Brazilian test, an indirect tensile-splitting method, is performed in this work, and the evolution of strain field is obtained using digital image correlation. Experimental results show the significant impact of local heterogeneity and lamination on the crack pattern characteristics. For numerical simulations, a phase field method is used to simulate the brittle fracture behavior under various Brazilian test conditions. In this study, shale is assumed to consist of two constituents including the stiffmore » and soft layers to which the same toughness but different elastic moduli are assigned. Microstructural heterogeneity is simplified to represent mesoscale (e.g., millimeter scale) features such as layer orientation, thickness, volume fraction, and defects. The effect of these structural attributes on the onset, propagation, and coalescence of cracks is explored. The simulation results show that spatial heterogeneity and material anisotropy highly affect crack patterns and effective fracture toughness, and the elastic contrast of two constituents significantly alters the effective toughness. However, the complex crack patterns observed in the experiments cannot completely be accounted for by either an isotropic or transversely isotropic effective medium approach. In conclusion, this implies that cracks developed in the layered system may coalesce in complicated ways depending on the local heterogeneity, and the interaction mechanisms between the cracks using two-constituent systems may explain the wide range of effective toughness of shale reported in the literature.« less

Holocene monsoon variability as resolved in small complex networks from palaeodata

NASA Astrophysics Data System (ADS)

Rehfeld, K.; Marwan, N.; Breitenbach, S.; Kurths, J.

2012-04-01

To understand the impacts of Holocene precipitation and/or temperature changes in the spatially extensive and complex region of Asia, it is promising to combine the information from palaeo archives, such as e.g. stalagmites, tree rings and marine sediment records from India and China. To this end, complex networks present a powerful and increasingly popular tool for the description and analysis of interactions within complex spatially extended systems in the geosciences and therefore appear to be predestined for this task. Such a network is typically constructed by thresholding a similarity matrix which in turn is based on a set of time series representing the (Earth) system dynamics at different locations. Looking into the pre-instrumental past, information about the system's processes and thus its state is available only through the reconstructed time series which -- most often -- are irregularly sampled in time and space. Interpolation techniques are often used for signal reconstruction, but they introduce additional errors, especially when records have large gaps. We have recently developed and extensively tested methods to quantify linear (Pearson correlation) and non-linear (mutual information) similarity in presence of heterogeneous and irregular sampling. To illustrate our approach we derive small networks from significantly correlated, linked, time series which are supposed to capture the underlying Asian Monsoon dynamics. We assess and discuss whether and where links and directionalities in these networks from irregularly sampled time series can be soundly detected. Finally, we investigate the role of the Northern Hemispheric temperature with respect to the correlation patterns and find that those derived from warm phases (e.g. Medieval Warm Period) are significantly different from patterns found in cold phases (e.g. Little Ice Age).

Spatial and temporal dynamics of lake whitefish (Coregonus clupeaformis) health indicators: linking individual-based indicators to a management-relevant endpoint

USGS Publications Warehouse

Wagner, Tyler; Jones, Michael L.; Ebener, Mark P.; Arts, Michael T.; Brenden, Travis O.; Honeyfield, Dale C.; Wright, Gregory M.; Faisal, Mohamed

2010-01-01

We examined the spatial and temporal dynamics of health indicators in four lake whitefish (Coregonus clupeaformis) stocks located in northern lakes Michigan and Huron from 2003 to 2006. The specific objectives were to (1) quantify spatial and temporal variability in health indicators; (2) examine relationships among nutritional indicators and stock-specific spatial and temporal dynamics of pathogen prevalence and intensity of infection; and (3) examine relationships between indicators measured on individual fish and stock-specific estimates of natural mortality. The percent of the total variation attributed to spatial and temporal sources varied greatly depending on the health indicator examined. The most notable pattern was a downward trend in the concentration of highly unsaturated fatty acids (HUFAs), observed in all stocks, in the polar lipid fraction of lake whitefish dorsal muscle tissue over the three study years. Variation among stocks and years for some indicators were correlated with the prevalence and intensity of the swimbladder nematode Cystidicola farionis, suggesting that our measures of fish health were related, at some level, with disease dynamics. We did not find relationships between spatial patterns in fish health indicators and estimates of natural mortality rates for the stocks. Our research highlights the complexity of the interactions between fish nutritional status, disease dynamics, and natural mortality in wild fish populations. Additional research that identifies thresholds of health indicators, below (or above) which survival may be reduced, will greatly help in understanding the relationship between indicators measured on individual fish and potential population-level effects.

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...

Creation of Synthetic Surface Temperature and Precipitation Ensembles Through A Computationally Efficient, Mixed Method Approach

NASA Astrophysics Data System (ADS)

Hartin, C.; Lynch, C.; Kravitz, B.; Link, R. P.; Bond-Lamberty, B. P.

2017-12-01

Typically, uncertainty quantification of internal variability relies on large ensembles of climate model runs under multiple forcing scenarios or perturbations in a parameter space. Computationally efficient, standard pattern scaling techniques only generate one realization and do not capture the complicated dynamics of the climate system (i.e., stochastic variations with a frequency-domain structure). In this study, we generate large ensembles of climate data with spatially and temporally coherent variability across a subselection of Coupled Model Intercomparison Project Phase 5 (CMIP5) models. First, for each CMIP5 model we apply a pattern emulation approach to derive the model response to external forcing. We take all the spatial and temporal variability that isn't explained by the emulator and decompose it into non-physically based structures through use of empirical orthogonal functions (EOFs). Then, we perform a Fourier decomposition of the EOF projection coefficients to capture the input fields' temporal autocorrelation so that our new emulated patterns reproduce the proper timescales of climate response and "memory" in the climate system. Through this 3-step process, we derive computationally efficient climate projections consistent with CMIP5 model trends and modes of variability, which address a number of deficiencies inherent in the ability of pattern scaling to reproduce complex climate model behavior.

Pattern formation in Dictyostelium discoideum aggregates in confined microenvironments

NASA Astrophysics Data System (ADS)

Hallou, Adrien; Hersen, Pascal; di Meglio, Jean-Marc; Kabla, Alexandre

Dictyostelium Discoideum (Dd) is often viewed as a model system to study the complex collective cell behaviours which shape an embryo. Under starvation, Dd cells form multicellular aggregates which soon elongate, starting to display an anterior-posterior axis by differentiating into two distinct cell populations; prestalk (front) and prespore (rear) cells zones. Different models, either based on positional information or on differentiation followed up by cell sorting, have been proposed to explain the origin and the regulation of this spatial pattern.To decipher between the proposed hypotheses, we have developed am experimental platform where aggregates, made of genetically engineered Dd cells to express fluorescent reporters of cell differentiation in either prestalk or prespore cells, are allowed to develop in 20 to 400 μm wide hydrogel channels. Such a setup allows us to both mimic Dd confined natural soil environment and to follow the patterning dynamics using time-lapse microscopy. Tracking cell lineage commitments and positions in space and time, we demonstrate that Dd cells differentiate first into prestalk and prespore cells prior to sorting into an organized spatial pattern on the basis of collective motions based on differential motility and adhesion mechanisms. A. Hallou would like to thank the University of Cambridge for the Award of an ``Oliver Gatty Studentship in Biophysical and Colloid Science''.

Combining chemometric tools for assessing hazard sources and factors acting simultaneously in contaminated areas. Case study: "Mar Piccolo" Taranto (South Italy).

PubMed

Mali, Matilda; Dell'Anna, Maria Michela; Notarnicola, Michele; Damiani, Leonardo; Mastrorilli, Piero

2017-10-01

Almost all marine coastal ecosystems possess complex structural and dynamic characteristics, which are influenced by anthropogenic causes and natural processes as well. Revealing the impact of sources and factors controlling the spatial distributions of contaminants within highly polluted areas is a fundamental propaedeutic step of their quality evaluation. Combination of different pattern recognition techniques, applied to one of the most polluted Mediterranean coastal basin, resulted in a more reliable hazard assessment. PCA/CA and factorial ANOVA were exploited as complementary techniques for apprehending the impact of multi-sources and multi-factors acting simultaneously and leading to similarities or differences in the spatial contamination pattern. The combination of PCA/CA and factorial ANOVA allowed, on one hand to determine the main processes and factors controlling the contamination trend within different layers and different basins, and, on the other hand, to ascertain possible synergistic effects. This approach showed the significance of a spatially representative overview given by the combination of PCA-CA/ANOVA in inferring the historical anthropogenic sources loading on the area. Copyright © 2017 Elsevier Ltd. All rights reserved.

The geography of spatial synchrony.

PubMed

Walter, Jonathan A; Sheppard, Lawrence W; Anderson, Thomas L; Kastens, Jude H; Bjørnstad, Ottar N; Liebhold, Andrew M; Reuman, Daniel C

2017-07-01

Spatial synchrony, defined as correlated temporal fluctuations among populations, is a fundamental feature of population dynamics, but many aspects of synchrony remain poorly understood. Few studies have examined detailed geographical patterns of synchrony; instead most focus on how synchrony declines with increasing linear distance between locations, making the simplifying assumption that distance decay is isotropic. By synthesising and extending prior work, we show how geography of synchrony, a term which we use to refer to detailed spatial variation in patterns of synchrony, can be leveraged to understand ecological processes including identification of drivers of synchrony, a long-standing challenge. We focus on three main objectives: (1) showing conceptually and theoretically four mechanisms that can generate geographies of synchrony; (2) documenting complex and pronounced geographies of synchrony in two important study systems; and (3) demonstrating a variety of methods capable of revealing the geography of synchrony and, through it, underlying organism ecology. For example, we introduce a new type of network, the synchrony network, the structure of which provides ecological insight. By documenting the importance of geographies of synchrony, advancing conceptual frameworks, and demonstrating powerful methods, we aim to help elevate the geography of synchrony into a mainstream area of study and application. © 2017 John Wiley & Sons Ltd/CNRS.

The Effect of Spatial Aggregation on the Skill of Seasonal Precipitation Forecasts.

NASA Astrophysics Data System (ADS)

Gong, Xiaofeng; Barnston, Anthony G.; Ward, M. Neil

2003-09-01

Skillful forecasts of 3-month total precipitation would be useful for decision making in hydrology, agriculture, public health, and other sectors of society. However, with some exceptions, the skill of seasonal precipitation outlooks is modest, leaving uncertainty in how to best make use of them. Seasonal precipitation forecast skill is generally lower than the skill of forecasts for temperature or atmospheric circulation patterns for the same location and time. This is attributable to the smaller-scale, more complex physics of precipitation, resulting in its `noisier' and hence less predictable character. By contrast, associated temperature and circulation patterns are larger scale, in keeping with the anomalous boundary conditions (e.g., sea surface temperature) that often give rise to them.Using two atmospheric general circulation models forced by observed sea surface temperature anomalies, the skill of simulations of total seasonal precipitation is examined as a function of the size of the spatial domain over which the precipitation total is averaged. Results show that spatial aggregation increases skill and, by the skill measures used here, does so to a greater extent for precipitation than for temperature. Corroborative results are presented in an observational framework at smaller spatial scales for gauge rainfalls in northeast Brazil.The findings imply that when seasonal forecasts for precipitation are issued, the accompanying guidance on their expected skills should explicitly specify to which spatial aggregation level the skills apply. Information about skills expected at other levels of aggregation should be supplied for users who may work at such levels.

Constellation of phase singularities in a speckle-like pattern for optical vortex metrology applied to biological kinematic analysis.

PubMed

Wang, Wei; Qiao, Yu; Ishijima, Reika; Yokozeki, Tomoaki; Honda, Daigo; Matsuda, Akihiro; Hanson, Steen G; Takeda, Mitsuo

2008-09-01

A novel technique for biological kinematic analysis is proposed that makes use of the pseudophase singularities in a complex signal generated from a speckle-like pattern. In addition to the information about the locations and the anisotropic core structures of the pseudophase singularities, we also detect the spatial structures of a cluster of phase singularities, which serves as a unique constellation characterizing the mutual position relation between the individual pseudophase singularities. Experimental results of in vivo measurements for a swimming fish along with its kinematic analysis are presented, which demonstrate the validity of the proposed technique.

Spatial Orientation from Motion-Produced Blur Patterns: Detection of Curvature Change.

DTIC Science & Technology

1978-08-01

3.0 2.3 1.6 1.1 .8 16 3.8 3.0 2.3 1.4 1.1 300 Le f t Fixation Frequency (he r t z ) Veloci ty (°/sec) 1/4 1/2 1 2 4 4 2.8 2.4 1.8 1.3 1.2 8 4.0 3.0... principle of minimum object change which implies that the perceptual tendency in a case like this is to see a rigid object moving in translation, neither...stretching nor binding nor twisting as a helical pattern would be required to do. Johansson notes that the principle may not hold up for complex

Differential flank growth

NASA Astrophysics Data System (ADS)

Zieschang, H. E.; Sievers, A.

1994-08-01

With the mathematical basis for the precise analysis of developmental processes in plants, the patterns of growth in phototropic and gravitropic responses have become better understood. A detailed temporal and spatial quantification of a growth process is an important tool for evaluating hypotheses about the underlying physiological mechanisms. Studies of growth rates and curvature show that the original Cholodny-Went hypothesis cannot explain the complex growth patterns during tropic responses of shoots and roots. In addition, regulating factors other than the lateral redistribution of hormones must be taken into account. Electrophysiological studies on roots led to a modification of the Cholodny-Went hypothesis in that redistributions of bioelectrical activities are observed.

Chimera states in complex networks: interplay of fractal topology and delay

NASA Astrophysics Data System (ADS)

Sawicki, Jakub; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

2017-06-01

Chimera states are an example of intriguing partial synchronization patterns emerging in networks of identical oscillators. They consist of spatially coexisting domains of coherent (synchronized) and incoherent (desynchronized) dynamics. We analyze chimera states in networks of Van der Pol oscillators with hierarchical connectivities, and elaborate the role of time delay introduced in the coupling term. In the parameter plane of coupling strength and delay time we find tongue-like regions of existence of chimera states alternating with regions of existence of coherent travelling waves. We demonstrate that by varying the time delay one can deliberately stabilize desired spatio-temporal patterns in the system.

Spatial Metadata for Global Change Investigations Using Remote Sensing

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Quattrochi, Dale A.; Lam, Nina Siu-Ngan; Arnold, James E. (Technical Monitor)

2002-01-01

Satellite and aircraft-borne remote sensors have gathered petabytes of data over the past 30+ years. These images are an important resource for establishing cause and effect relationships between human-induced land cover changes and alterations in climate and other biophysical patterns at local to global scales. However, the spatial, temporal, and spectral characteristics of these datasets vary, thus complicating long-term studies involving several types of imagery. As the geographical and temporal coverage, the spectral and spatial resolution, and the number of individual sensors increase, the sheer volume and complexity of available data sets will complicate management and use of the rapidly growing archive of earth imagery. Mining this vast data resource for images that provide the necessary information for climate change studies becomes more difficult as more sensors are launched and more imagery is obtained.

Defense Mechanisms of Empathetic Players in the Spatial Ultimatum Game

NASA Astrophysics Data System (ADS)

Szolnoki, Attila; Perc, Matjaž; Szabó, György

2012-08-01

Experiments on the ultimatum game have revealed that humans are remarkably fond of fair play. When asked to share an amount of money, unfair offers are rare and their acceptance rate small. While empathy and spatiality may lead to the evolution of fairness, thus far considered continuous strategies have precluded the observation of solutions that would be driven by pattern formation. Here we introduce a spatial ultimatum game with discrete strategies, and we show that this simple alteration opens the gate to fascinatingly rich dynamical behavior. In addition to mixed stationary states, we report the occurrence of traveling waves and cyclic dominance, where one strategy in the cycle can be an alliance of two strategies. The highly webbed phase diagram, entailing continuous and discontinuous phase transitions, reveals hidden complexity in the pursuit of human fair play.

Multifractal analysis of mobile social networks

NASA Astrophysics Data System (ADS)

Zheng, Wei; Zhang, Zifeng; Deng, Yufan

2017-09-01

As Wireless Fidelity (Wi-Fi)-enabled handheld devices have been widely used, the mobile social networks (MSNs) has been attracting extensive attention. Fractal approaches have also been widely applied to characterierize natural networks as useful tools to depict their spatial distribution and scaling properties. Moreover, when the complexity of the spatial distribution of MSNs cannot be properly charaterized by single fractal dimension, multifractal analysis is required. For further research, we introduced a multifractal analysis method based on box-covering algorithm to describe the structure of MSNs. Using this method, we find that the networks are multifractal at different time interval. The simulation results demonstrate that the proposed method is efficient for analyzing the multifractal characteristic of MSNs, which provides a distribution of singularities adequately describing both the heterogeneity of fractal patterns and the statistics of measurements across spatial scales in MSNs.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Spatio-temporal analysis of irregular vocal fold oscillations: Biphonation due to desynchronization of spatial modes

NASA Astrophysics Data System (ADS)

Neubauer, Jürgen; Mergell, Patrick; Eysholdt, Ulrich; Herzel, Hanspeter

2001-12-01

This report is on direct observation and modal analysis of irregular spatio-temporal vibration patterns of vocal fold pathologies in vivo. The observed oscillation patterns are described quantitatively with multiline kymograms, spectral analysis, and spatio-temporal plots. The complex spatio-temporal vibration patterns are decomposed by empirical orthogonal functions into independent vibratory modes. It is shown quantitatively that biphonation can be induced either by left-right asymmetry or by desynchronized anterior-posterior vibratory modes, and the term ``AP (anterior-posterior) biphonation'' is introduced. The presented phonation examples show that for normal phonation the first two modes sufficiently explain the glottal dynamics. The spatio-temporal oscillation pattern associated with biphonation due to left-right asymmetry can be explained by the first three modes. Higher-order modes are required to describe the pattern for biphonation induced by anterior-posterior vibrations. Spatial irregularity is quantified by an entropy measure, which is significantly higher for irregular phonation than for normal phonation. Two asymmetry measures are introduced: the left-right asymmetry and the anterior-posterior asymmetry, as the ratios of the fundamental frequencies of left and right vocal fold and of anterior-posterior modes, respectively. These quantities clearly differentiate between left-right biphonation and anterior-posterior biphonation. This paper proposes methods to analyze quantitatively irregular vocal fold contour patterns in vivo and complements previous findings of desynchronization of vibration modes in computer modes and in in vitro experiments.

Two-Dimensional Micropatterns of Self-Assembled Poly(N-isopropylacrylamide) Microgels for Patterned Adhesion and Temperature-Responsive Detachment of Fibroblasts

PubMed Central

Tsai, Hsin-Yi; Vats, Kanika; Yates, Matthew Z.; Benoit, Danielle S. W.

2013-01-01

Thermoresponsive poly(N-isopropyl acrylamide) (PNIPAM) microgels were patterned on polystyrene substrates via dip coating, creating cytocompatible substrates that provided spatial control over cell adhesion. This simple dip coating method, which exploits variable substrate withdrawal speeds form particle suspension formed stripes of densely-packed PNIPAM microgels, while spacings between the stripes contained sparsely-distributed PNIPAM microgels. The assembly of three different PNIPAM microgel patterns, namely patterns composed of 50 μm stripes/50 μm spacings, 50 μm stripes/100 μm spacings, and 100 μm stripes/100 μm spacings was verified using high-resolution optical micrographs and ImageJ analysis. PNIPAM microgels existed as monolayers within stripes and spacings, as revealed by atomic force microscopy (AFM). Upon cell seeding on PNIPAM micropatterned substrates, NIH3T3 fibroblast cells preferentially adhered within spacings to form cell patterns. Three days after cell seeding, cells proliferated to form confluent cell layers. The thermoresponsiveness of the underlying PNIPAM microgels was then utilized to recover fibroblast cell sheets from substrates simply by lowering the temperature, without disrupting the underlying PNIPAM microgel patterns. Harvested cell sheets similar to these have been used for multiple tissue engineering applications. Also, this simple, low cost, template-free dip coating technique can be utilized to micropattern multifunctional PNIPAM microgels, generating complex stimuli-responsive substrates to study cell-material interactions and allow drug delivery to cells in a spatially and temporally-controlled manners. PMID:23968193

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.

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.

Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend

USGS Publications Warehouse

Engel, Frank; Rhoads, Bruce L.

2016-01-01

Compound meander bends with multiple lobes of maximum curvature are common in actively evolving lowland rivers. Interaction among spatial patterns of mean flow, turbulence, bed morphology, bank failures and channel migration in compound bends is poorly understood. In this paper, acoustic Doppler current profiler (ADCP) measurements of the three-dimensional (3D) flow velocities in a compound bend are examined to evaluate the influence of channel curvature and hydrologic variability on the structure of flow within the bend. Flow structure at various flow stages is related to changes in bed morphology over the study timeframe. Increases in local curvature within the upstream lobe of the bend reduce outer bank velocities at morphologically significant flows, creating a region that protects the bank from high momentum flow and high bed shear stresses. The dimensionless radius of curvature in the upstream lobe is one-third less than that of the downstream lobe, with average bank erosion rates less than half of the erosion rates for the downstream lobe. Higher bank erosion rates within the downstream lobe correspond to the shift in a core of high velocity and bed shear stresses toward the outer bank as flow moves through the two lobes. These erosion patterns provide a mechanism for continued migration of the downstream lobe in the near future. Bed material size distributions within the bend correspond to spatial patterns of bed shear stress magnitudes, indicating that bed material sorting within the bend is governed by bed shear stress. Results suggest that patterns of flow, sediment entrainment, and planform evolution in compound meander bends are more complex than in simple meander bends. Moreover, interactions among local influences on the flow, such as woody debris, local topographic steering, and locally high curvature, tend to cause compound bends to evolve toward increasing planform complexity over time rather than stable configurations.

Integrability of the coupled cubic-quintic complex Ginzburg-Landau equations and multiple-soliton solutions via mathematical methods

NASA Astrophysics Data System (ADS)

Selima, Ehab S.; Seadawy, Aly R.; Yao, Xiaohua; Essa, F. A.

2018-02-01

This paper is devoted to study the (1+1)-dimensional coupled cubic-quintic complex Ginzburg-Landau equations (cc-qcGLEs) with complex coefficients. This equation can be used to describe the nonlinear evolution of slowly varying envelopes of periodic spatial-temporal patterns in a convective binary fluid. Dispersion relation and properties of cc-qcGLEs are constructed. Painlevé analysis is used to check the integrability of cc-qcGLEs and to establish the Bäcklund transformation form. New traveling wave solutions and a general form of multiple-soliton solutions of cc-qcGLEs are obtained via the Bäcklund transformation and simplest equation method with Bernoulli, Riccati and Burgers’ equations as simplest equations.

Patterned corneal collagen crosslinking for astigmatism: Computational modeling study

PubMed Central

Seven, Ibrahim; Roy, Abhijit Sinha; Dupps, William J.

2014-01-01

PURPOSE To test the hypothesis that spatially selective corneal stromal stiffening can alter corneal astigmatism and assess the effects of treatment orientation, pattern, and material model complexity in computational models using patient-specific geometries. SETTING Cornea and Refractive Surgery Service, Academic Eye Institute, Cleveland, Ohio, USA. DESIGN Computational modeling study. METHODS Three-dimensional corneal geometries from 10 patients with corneal astigmatism were exported from a clinical tomography system (Pentacam). Corneoscleral finite element models of each eye were generated. Four candidate treatment patterns were simulated, and the effects of treatment orientation and magnitude of stiffening on anterior curvature and aberrations were studied. The effect of material model complexity on simulated outcomes was also assessed. RESULTS Pretreatment anterior corneal astigmatism ranged from 1.22 to 3.92 diopters (D) in a series that included regular and irregular astigmatic patterns. All simulated treatment patterns oriented on the flat axis resulted in mean reductions in corneal astigmatism and depended on the pattern geometry. The linear bow-tie pattern produced a greater mean reduction in astigmatism (1.08 D ± 0.13 [SD]; range 0.74 to 1.23 D) than other patterns tested under an assumed 2-times increase in corneal stiffness, and it had a nonlinear relationship to the degree of stiffening. The mean astigmatic effect did not change significantly with a fiber- or depth-dependent model, but it did affect the coupling ratio. CONCLUSIONS In silico simulations based on patient-specific geometries suggest that clinically significant reductions in astigmatism are possible with patterned collagen crosslinking. Effect magnitude was dependent on patient-specific geometry, effective stiffening pattern, and treatment orientation. PMID:24767795

Women match men when learning a spatial skill.

PubMed

Spence, Ian; Yu, Jingjie Jessica; Feng, Jing; Marshman, Jeff

2009-07-01

Meta-analytic studies have concluded that although training improves spatial cognition in both sexes, the male advantage generally persists. However, because some studies run counter to this pattern, a closer examination of the anomaly is warranted. The authors investigated the acquisition of a basic skill (spatial selective attention) using a matched-pair two-wave longitudinal design. Participants were screened with the use of an attentional visual field task, with the objective of selecting and matching 10 male-female pairs, over a wide range (30% to 57% correct). Subsequently, 20 participants 17-23 years of age (selected from 43 screened) were trained for 10 hr (distributed over several sessions) by playing a first-person shooter video game. This genre is known to be highly effective in enhancing spatial skills. All 20 participants improved, with matched members of the male-female pairs achieving very similar gains, independent of starting level. This is consistent with the hypothesis that the learning trajectory of women is not inferior to that of men when acquiring a basic spatial skill. Training methods that develop basic spatial skills may be essential to achieve gender parity in both basic and complex spatial tasks.

An Assessment of Stream Confluence Flow Dynamics using Large Scale Particle Image Velocimetry Captured from Unmanned Aerial Systems

NASA Astrophysics Data System (ADS)

Lewis, Q. W.; Rhoads, B. L.

2017-12-01

The merging of rivers at confluences results in complex three-dimensional flow patterns that influence sediment transport, bed morphology, downstream mixing, and physical habitat conditions. The capacity to characterize comprehensively flow at confluences using traditional sensors, such as acoustic Doppler velocimeters and profiles, is limited by the restricted spatial resolution of these sensors and difficulties in measuring velocities simultaneously at many locations within a confluence. This study assesses two-dimensional surficial patterns of flow structure at a small stream confluence in Illinois, USA, using large scale particle image velocimetry (LSPIV) derived from videos captured by unmanned aerial systems (UAS). The method captures surface velocity patterns at high spatial and temporal resolution over multiple scales, ranging from the entire confluence to details of flow within the confluence mixing interface. Flow patterns at high momentum ratio are compared to flow patterns when the two incoming flows have nearly equal momentum flux. Mean surface flow patterns during the two types of events provide details on mean patterns of surface flow in different hydrodynamic regions of the confluence and on changes in these patterns with changing momentum flux ratio. LSPIV data derived from the highest resolution imagery also reveal general characteristics of large-scale vortices that form along the shear layer between the flows during the high-momentum ratio event. The results indicate that the use of LSPIV and UAS is well-suited for capturing in detail mean surface patterns of flow at small confluences, but that characterization of evolving turbulent structures is limited by scale considerations related to structure size, image resolution, and camera instability. Complementary methods, including camera platforms mounted at fixed positions close to the water surface, provide opportunities to accurately characterize evolving turbulent flow structures in confluences.