Large-scale ocean connectivity and planktonic body size

KAUST Repository

Villarino, Ernesto

2018-01-04

Global patterns of planktonic diversity are mainly determined by the dispersal of propagules with ocean currents. However, the role that abundance and body size play in determining spatial patterns of diversity remains unclear. Here we analyse spatial community structure - β-diversity - for several planktonic and nektonic organisms from prokaryotes to small mesopelagic fishes collected during the Malaspina 2010 Expedition. β-diversity was compared to surface ocean transit times derived from a global circulation model, revealing a significant negative relationship that is stronger than environmental differences. Estimated dispersal scales for different groups show a negative correlation with body size, where less abundant large-bodied communities have significantly shorter dispersal scales and larger species spatial turnover rates than more abundant small-bodied plankton. Our results confirm that the dispersal scale of planktonic and micro-nektonic organisms is determined by local abundance, which scales with body size, ultimately setting global spatial patterns of diversity.

Characterizing Temperature Variability and Associated Large Scale Meteorological Patterns Across South America

Science.gov (United States)

Detzer, J.; Loikith, P. C.; Mechoso, C. R.; Barkhordarian, A.; Lee, H.

2017-12-01

South America's climate varies considerably owing to its large geographic range and diverse topographical features. Spanning the tropics to the mid-latitudes and from high peaks to tropical rainforest, the continent experiences an array of climate and weather patterns. Due to this considerable spatial extent, assessing temperature variability at the continent scale is particularly challenging. It is well documented in the literature that temperatures have been increasing across portions of South America in recent decades, and while there have been many studies that have focused on precipitation variability and change, temperature has received less scientific attention. Therefore, a more thorough understanding of the drivers of temperature variability is critical for interpreting future change. First, k-means cluster analysis is used to identify four primary modes of temperature variability across the continent, stratified by season. Next, composites of large scale meteorological patterns (LSMPs) are calculated for months assigned to each cluster. Initial results suggest that LSMPs, defined using meteorological variables such as sea level pressure (SLP), geopotential height, and wind, are able to identify synoptic scale mechanisms important for driving temperature variability at the monthly scale. Some LSMPs indicate a relationship with known recurrent modes of climate variability. For example, composites of geopotential height suggest that the Southern Annular Mode is an important, but not necessarily dominant, component of temperature variability over southern South America. This work will be extended to assess the drivers of temperature extremes across South America.

Spatial dependencies between large-scale brain networks.

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Robert Leech

Full Text Available Functional neuroimaging reveals both increases (task-positive and decreases (task-negative in neural activation with many tasks. Many studies show a temporal relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidence for a spatial relationship between task positive and negative networks. There are strong spatial similarities between many reported task negative brain networks, termed the default mode network, which is typically assumed to be a spatially fixed network. However, this is not the case. The spatial structure of the DMN varies depending on what specific task is being performed. We test whether there is a fundamental spatial relationship between task positive and negative networks. Specifically, we hypothesize that the distance between task positive and negative voxels is consistent despite different spatial patterns of activation and deactivation evoked by different cognitive tasks. We show significantly reduced variability in the distance between within-condition task positive and task negative voxels than across-condition distances for four different sensory, motor and cognitive tasks--implying that deactivation patterns are spatially dependent on activation patterns (and vice versa, and that both are modulated by specific task demands. We also show a similar relationship between positively and negatively correlated networks from a third 'rest' dataset, in the absence of a specific task. We propose that this spatial relationship may be the macroscopic analogue of microscopic neuronal organization reported in sensory cortical systems, and that this organization may reflect homeostatic plasticity necessary for efficient brain function.

Spatial scale separation in regional climate modelling

Energy Technology Data Exchange (ETDEWEB)

Feser, F.

2005-07-01

In this thesis the concept of scale separation is introduced as a tool for first improving regional climate model simulations and, secondly, to explicitly detect and describe the added value obtained by regional modelling. The basic idea behind this is that global and regional climate models have their best performance at different spatial scales. Therefore the regional model should not alter the global model's results at large scales. The for this purpose designed concept of nudging of large scales controls the large scales within the regional model domain and keeps them close to the global forcing model whereby the regional scales are left unchanged. For ensemble simulations nudging of large scales strongly reduces the divergence of the different simulations compared to the standard approach ensemble that occasionally shows large differences for the individual realisations. For climate hindcasts this method leads to results which are on average closer to observed states than the standard approach. Also the analysis of the regional climate model simulation can be improved by separating the results into different spatial domains. This was done by developing and applying digital filters that perform the scale separation effectively without great computational effort. The separation of the results into different spatial scales simplifies model validation and process studies. The search for 'added value' can be conducted on the spatial scales the regional climate model was designed for giving clearer results than by analysing unfiltered meteorological fields. To examine the skill of the different simulations pattern correlation coefficients were calculated between the global reanalyses, the regional climate model simulation and, as a reference, of an operational regional weather analysis. The regional climate model simulation driven with large-scale constraints achieved a high increase in similarity to the operational analyses for medium-scale 2 meter

Considerations of scale in the analysis of spatial pattern of plant disease epidemics.

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Turechek, William W; McRoberts, Neil

2013-01-01

Scale is an important but somewhat neglected subject in plant pathology. Scale serves as an abstract concept, providing a framework for organizing observations and theoretical models, and plays a functional role in the organization of ecological communities and physical processes. Rich methodological resources are available to plant pathologists interested in considering either or both aspects of scale in their research. We summarize important concepts in both areas of the literature, particularly as they apply to the spatial pattern of plant disease, and highlight some new results that emphasize the importance of scaling on the emergence of different types of probability distribution in empirical observation. We also highlight the important links between heterogeneity and scale, which are of central importance in plant disease epidemiology and the analysis of spatial pattern. We consider statistical approaches that are available, where actual physical scale is known, and for more conceptual research on hierarchies, where scale plays a more abstract role, particularly for field-based research. For the latter, we highlight methods that plant pathologists could consider to account for the effect of scale in the design of field studies.

Limnology in the Upper Paraná River floodplain: large-scale spatial and temporal patterns, and the influence of reservoirs.

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Roberto, M C; Santana, N N; Thomaz, S M

2009-06-01

Knowledge of abiotic limnological factors is important to monitor changes caused by humans, and to explain the structure and dynamics of populations and communities in a variety of inland water ecosystems. In this study, we used a long term data-set (eight years) collected in 10 habitats with different features (river channels, and connected and isolated lakes) to describe the spatial and temporal patterns of some of the principal limnological factors. In general, the degree of connectivity of the lakes, together with the rivers to which the lakes are connected, were important determinants of their limnological characteristics. These differences are expected, because rivers entering the floodplain come from different geological regions and are subject to different human impacts. At large spatial scales, these differences contribute to the increased habitat diversity of the floodplain and thus to its high biodiversity. With regard to temporal variation, Secchi-disk transparency increased, and total phosphorus decreased in the Paraná River main channel during the last 20 years. Although these changes are directly attributed to the several reservoir cascades located upstream, the closing of the Porto Primavera dam in 1998 enhanced this effect. The increase in water transparency explains biotic changes within the floodplain. The lower-phosphorus Paraná River water probably dilutes concentrations of this element in the floodplain waterbodies during major floods, with future consequences for their productivity.

Spatial reflection patterns of iridescent wings of male pierid butterflies: curved scales reflect at a wider angle than flat scales.

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Pirih, Primož; Wilts, Bodo D; Stavenga, Doekele G

2011-10-01

The males of many pierid butterflies have iridescent wings, which presumably function in intraspecific communication. The iridescence is due to nanostructured ridges of the cover scales. We have studied the iridescence in the males of a few members of Coliadinae, Gonepteryx aspasia, G. cleopatra, G. rhamni, and Colias croceus, and in two members of the Colotis group, Hebomoia glaucippe and Colotis regina. Imaging scatterometry demonstrated that the pigmentary colouration is diffuse whereas the structural colouration creates a directional, line-shaped far-field radiation pattern. Angle-dependent reflectance measurements demonstrated that the directional iridescence distinctly varies among closely related species. The species-dependent scale curvature determines the spatial properties of the wing iridescence. Narrow beam illumination of flat scales results in a narrow far-field iridescence pattern, but curved scales produce broadened patterns. The restricted spatial visibility of iridescence presumably plays a role in intraspecific signalling.

Environmental factors at different spatial scales governing soil fauna community patterns in fragmented forests.

NARCIS (Netherlands)

Martins da Silva, P.; Berg, M.P.; Serrano, A.R.M.; Dubs, F.; Sousa, J.P.

2012-01-01

Spatial and temporal changes in community structure of soil organisms may result from a myriad of processes operating at a hierarchy of spatial scales, from small-scale habitat conditions to species movements among patches and large-sale landscape features. To disentangle the relative importance of

A spatial picture of the synthetic large-scale motion from dynamic roughness

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Huynh, David; McKeon, Beverley

2017-11-01

Jacobi and McKeon (2011) set up a dynamic roughness apparatus to excite a synthetic, travelling wave-like disturbance in a wind tunnel, boundary layer study. In the present work, this dynamic roughness has been adapted for a flat-plate, turbulent boundary layer experiment in a water tunnel. A key advantage of operating in water as opposed to air is the longer flow timescales. This makes accessible higher non-dimensional actuation frequencies and correspondingly shorter synthetic length scales, and is thus more amenable to particle image velocimetry. As a result, this experiment provides a novel spatial picture of the synthetic mode, the coupled small scales, and their streamwise development. It is demonstrated that varying the roughness actuation frequency allows for significant tuning of the streamwise wavelength of the synthetic mode, with a range of 3 δ-13 δ being achieved. Employing a phase-locked decomposition, spatial snapshots are constructed of the synthetic large scale and used to analyze its streamwise behavior. Direct spatial filtering is used to separate the synthetic large scale and the related small scales, and the results are compared to those obtained by temporal filtering that invokes Taylor's hypothesis. The support of AFOSR (Grant # FA9550-16-1-0361) is gratefully acknowledged.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

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Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

Investigating the dependence of SCM simulated precipitation and clouds on the spatial scale of large-scale forcing at SGP

Science.gov (United States)

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

2017-08-01

Large-scale forcing data, such as vertical velocity and advective tendencies, are required to drive single-column models (SCMs), cloud-resolving models, and large-eddy simulations. Previous studies suggest that some errors of these model simulations could be attributed to the lack of spatial variability in the specified domain-mean large-scale forcing. This study investigates the spatial variability of the forcing and explores its impact on SCM simulated precipitation and clouds. A gridded large-scale forcing data during the March 2000 Cloud Intensive Operational Period at the Atmospheric Radiation Measurement program's Southern Great Plains site is used for analysis and to drive the single-column version of the Community Atmospheric Model Version 5 (SCAM5). When the gridded forcing data show large spatial variability, such as during a frontal passage, SCAM5 with the domain-mean forcing is not able to capture the convective systems that are partly located in the domain or that only occupy part of the domain. This problem has been largely reduced by using the gridded forcing data, which allows running SCAM5 in each subcolumn and then averaging the results within the domain. This is because the subcolumns have a better chance to capture the timing of the frontal propagation and the small-scale systems. Other potential uses of the gridded forcing data, such as understanding and testing scale-aware parameterizations, are also discussed.

An efficient and novel computation method for simulating diffraction patterns from large-scale coded apertures on large-scale focal plane arrays

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Shrekenhamer, Abraham; Gottesman, Stephen R.

2012-10-01

A novel and memory efficient method for computing diffraction patterns produced on large-scale focal planes by largescale Coded Apertures at wavelengths where diffraction effects are significant has been developed and tested. The scheme, readily implementable on portable computers, overcomes the memory limitations of present state-of-the-art simulation codes such as Zemax. The method consists of first calculating a set of reference complex field (amplitude and phase) patterns on the focal plane produced by a single (reference) central hole, extending to twice the focal plane array size, with one such pattern for each Line-of-Sight (LOS) direction and wavelength in the scene, and with the pattern amplitude corresponding to the square-root of the spectral irradiance from each such LOS direction in the scene at selected wavelengths. Next the set of reference patterns is transformed to generate pattern sets for other holes. The transformation consists of a translational pattern shift corresponding to each hole's position offset and an electrical phase shift corresponding to each hole's position offset and incoming radiance's direction and wavelength. The set of complex patterns for each direction and wavelength is then summed coherently and squared for each detector to yield a set of power patterns unique for each direction and wavelength. Finally the set of power patterns is summed to produce the full waveband diffraction pattern from the scene. With this tool researchers can now efficiently simulate diffraction patterns produced from scenes by large-scale Coded Apertures onto large-scale focal plane arrays to support the development and optimization of coded aperture masks and image reconstruction algorithms.

Quantifying Forest Spatial Pattern Trends at Multiple Extents: An Approach to Detect Significant Changes at Different Scales

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Ludovico Frate

2014-09-01

Full Text Available We propose a procedure to detect significant changes in forest spatial patterns and relevant scales. Our approach consists of four sequential steps. First, based on a series of multi-temporal forest maps, a set of geographic windows of increasing extents are extracted. Second, for each extent and date, specific stochastic simulations that replicate real-world spatial pattern characteristics are run. Third, by computing pattern metrics on both simulated and real maps, their empirical distributions and confidence intervals are derived. Finally, multi-temporal scalograms are built for each metric. Based on cover maps (1954, 2011 with a resolution of 10 m we analyze forest pattern changes in a central Apennines (Italy reserve at multiple spatial extents (128, 256 and 512 pixels. We identify three types of multi-temporal scalograms, depending on pattern metric behaviors, describing different dynamics of natural reforestation process. The statistical distribution and variability of pattern metrics at multiple extents offers a new and powerful tool to detect forest variations over time. Similar procedures can (i help to identify significant changes in spatial patterns and provide the bases to relate them to landscape processes; (ii minimize the bias when comparing pattern metrics at a single extent and (iii be extended to other landscapes and scales.

A large-scale multi-species spatial depletion model for overwintering waterfowl

NARCIS (Netherlands)

Baveco, J.M.; Kuipers, H.; Nolet, B.A.

2011-01-01

In this paper, we develop a model to evaluate the capacity of accommodation areas for overwintering waterfowl, at a large spatial scale. Each day geese are distributed over roosting sites. Based on the energy minimization principle, the birds daily decide which surrounding fields to exploit within

The Spatial Scaling of Global Rainfall Extremes

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Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

2013-12-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities.

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Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities

Directory of Open Access Journals (Sweden)

Valerio Santangelo

2018-02-01

Full Text Available Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010 to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory in one spatial location. The analysis of the independent components (ICs revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC. The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among

[Spatial pattern analysis and associations of Quercus aquifolioides population at different growth stages in Southeast Tibet, China].

Science.gov (United States)

Shen, Zhi-qiang; Hua, Min; Dan, Qu; Lu, Jie; Fang, Jiang-ping

2016-02-01

This article analyzed the spatial pattern and its correlation of Quercus aquifolioides, Southeast Tibet at different growing stages by using Ripley' s L function in the method of point pattern, analysis. The results showed the diameter structure of Q. aquifolioides population in Southeast Tibet followed a 'single peak' shape and the saplings and medium trees predominated in number in the whole population. The population had a high regeneration rate and was of increase type. In the growth process of Q. aquifolioides from saplings to large trees, saplings and medium trees showed aggregation distribution at.small scale, while large trees showed basically random distribution at whole scale. There was significant correlation between saplings with medium or large trees at small scale, however, there was no correlation between medium and large trees. In the growth process of Q. aquifolioides population from saplings, medium trees to large trees, its spatial pattern developed from aggregative distribution to random distribution. The natural regeneration of Q. aquifolioides population was affected not only by interspecific competition, but also by intraspecific competition. In the similar natural environment, the most important factors affecting the spatial pattern of Q. aquifoioides population were its own biological and ecological characteristics.

Modelling aggregation on the large scale and regularity on the small scale in spatial point pattern datasets

DEFF Research Database (Denmark)

Lavancier, Frédéric; Møller, Jesper

We consider a dependent thinning of a regular point process with the aim of obtaining aggregation on the large scale and regularity on the small scale in the resulting target point process of retained points. Various parametric models for the underlying processes are suggested and the properties...

Large-area imaging reveals biologically driven non-random spatial patterns of corals at a remote reef

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Edwards, Clinton B.; Eynaud, Yoan; Williams, Gareth J.; Pedersen, Nicole E.; Zgliczynski, Brian J.; Gleason, Arthur C. R.; Smith, Jennifer E.; Sandin, Stuart A.

2017-12-01

For sessile organisms such as reef-building corals, differences in the degree of dispersion of individuals across a landscape may result from important differences in life-history strategies or may reflect patterns of habitat availability. Descriptions of spatial patterns can thus be useful not only for the identification of key biological and physical mechanisms structuring an ecosystem, but also by providing the data necessary to generate and test ecological theory. Here, we used an in situ imaging technique to create large-area photomosaics of 16 plots at Palmyra Atoll, central Pacific, each covering 100 m2 of benthic habitat. We mapped the location of 44,008 coral colonies and identified each to the lowest taxonomic level possible. Using metrics of spatial dispersion, we tested for departures from spatial randomness. We also used targeted model fitting to explore candidate processes leading to differences in spatial patterns among taxa. Most taxa were clustered and the degree of clustering varied by taxon. A small number of taxa did not significantly depart from randomness and none revealed evidence of spatial uniformity. Importantly, taxa that readily fragment or tolerate stress through partial mortality were more clustered. With little exception, clustering patterns were consistent with models of fragmentation and dispersal limitation. In some taxa, dispersion was linearly related to abundance, suggesting density dependence of spatial patterning. The spatial patterns of stony corals are non-random and reflect fundamental life-history characteristics of the taxa, suggesting that the reef landscape may, in many cases, have important elements of spatial predictability.

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

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Hannah L. Buckley

2014-09-01

Full Text Available 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

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

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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

Large-Scale Constraint-Based Pattern Mining

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Zhu, Feida

2009-01-01

We studied the problem of constraint-based pattern mining for three different data formats, item-set, sequence and graph, and focused on mining patterns of large sizes. Colossal patterns in each data formats are studied to discover pruning properties that are useful for direct mining of these patterns. For item-set data, we observed robustness of…

Nematode spatial and ecological patterns from tropical and temperate rainforests.

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Dorota L Porazinska

Full Text Available Large scale diversity patterns are well established for terrestrial macrobiota (e.g. plants and vertebrates, but not for microscopic organisms (e.g. nematodes. Due to small size, high abundance, and extensive dispersal, microbiota are assumed to exhibit cosmopolitan distributions with no biogeographical patterns. This assumption has been extrapolated from local spatial scale studies of a few taxonomic groups utilizing morphological approaches. Recent molecularly-based studies, however, suggest something quite opposite. Nematodes are the most abundant metazoans on earth, but their diversity patterns are largely unknown. We conducted a survey of nematode diversity within three vertical strata (soil, litter, and canopy of rainforests at two contrasting latitudes in the North American meridian (temperate: the Olympic National Forest, WA, U.S.A and tropical: La Selva Biological Station, Costa Rica using standardized sampling designs and sample processing protocols. To describe nematode diversity, we applied an ecometagenetic approach using 454 pyrosequencing. We observed that: 1 nematode communities were unique without even a single common species between the two rainforests, 2 nematode communities were unique among habitats in both rainforests, 3 total species richness was 300% more in the tropical than in the temperate rainforest, 4 80% of the species in the temperate rainforest resided in the soil, whereas only 20% in the tropics, 5 more than 90% of identified species were novel. Overall, our data provided no support for cosmopolitanism at both local (habitats and large (rainforests spatial scales. In addition, our data indicated that biogeographical patterns typical of macrobiota also exist for microbiota.

Nematode Spatial and Ecological Patterns from Tropical and Temperate Rainforests

Science.gov (United States)

Porazinska, Dorota L.; Giblin-Davis, Robin M.; Powers, Thomas O.; Thomas, W. Kelley

2012-01-01

Large scale diversity patterns are well established for terrestrial macrobiota (e.g. plants and vertebrates), but not for microscopic organisms (e.g. nematodes). Due to small size, high abundance, and extensive dispersal, microbiota are assumed to exhibit cosmopolitan distributions with no biogeographical patterns. This assumption has been extrapolated from local spatial scale studies of a few taxonomic groups utilizing morphological approaches. Recent molecularly-based studies, however, suggest something quite opposite. Nematodes are the most abundant metazoans on earth, but their diversity patterns are largely unknown. We conducted a survey of nematode diversity within three vertical strata (soil, litter, and canopy) of rainforests at two contrasting latitudes in the North American meridian (temperate: the Olympic National Forest, WA, U.S.A and tropical: La Selva Biological Station, Costa Rica) using standardized sampling designs and sample processing protocols. To describe nematode diversity, we applied an ecometagenetic approach using 454 pyrosequencing. We observed that: 1) nematode communities were unique without even a single common species between the two rainforests, 2) nematode communities were unique among habitats in both rainforests, 3) total species richness was 300% more in the tropical than in the temperate rainforest, 4) 80% of the species in the temperate rainforest resided in the soil, whereas only 20% in the tropics, 5) more than 90% of identified species were novel. Overall, our data provided no support for cosmopolitanism at both local (habitats) and large (rainforests) spatial scales. In addition, our data indicated that biogeographical patterns typical of macrobiota also exist for microbiota. PMID:22984536

Hydrometeorological variability on a large french catchment and its relation to large-scale circulation across temporal scales

Science.gov (United States)

Massei, Nicolas; Dieppois, Bastien; Fritier, Nicolas; Laignel, Benoit; Debret, Maxime; Lavers, David; Hannah, David

2015-04-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating large-scale/local-scale correlation, enmpirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the large-scale/local-scale links were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach which integrated discrete wavelet multiresolution analysis for reconstructing local hydrometeorological processes (predictand : precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector) on a monthly time-step. This approach

Estimating planktonic diversity through spatial dominance patterns in a model ocean.

Science.gov (United States)

Soccodato, Alice; d'Ovidio, Francesco; Lévy, Marina; Jahn, Oliver; Follows, Michael J; De Monte, Silvia

2016-10-01

In the open ocean, the observation and quantification of biodiversity patterns is challenging. Marine ecosystems are indeed largely composed by microbial planktonic communities whose niches are affected by highly dynamical physico-chemical conditions, and whose observation requires advanced methods for morphological and molecular classification. Optical remote sensing offers an appealing complement to these in-situ techniques. Global-scale coverage at high spatiotemporal resolution is however achieved at the cost of restrained information on the local assemblage. Here, we use a coupled physical and ecological model ocean simulation to explore one possible metrics for comparing measures performed on such different scales. We show that a large part of the local diversity of the virtual plankton ecosystem - corresponding to what accessible by genomic methods - can be inferred from crude, but spatially extended, information - as conveyed by remote sensing. Shannon diversity of the local community is indeed highly correlated to a 'seascape' index, which quantifies the surrounding spatial heterogeneity of the most abundant functional group. The error implied in drastically reducing the resolution of the plankton community is shown to be smaller in frontal regions as well as in regions of intermediate turbulent energy. On the spatial scale of hundreds of kms, patterns of virtual plankton diversity are thus largely sustained by mixing communities that occupy adjacent niches. We provide a proof of principle that in the open ocean information on spatial variability of communities can compensate for limited local knowledge, suggesting the possibility of integrating in-situ and satellite observations to monitor biodiversity distribution at the global scale. Copyright © 2016 Elsevier B.V. All rights reserved.

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

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

2018-06-01

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

Spatial patterns of fish standing biomass across Brazilian reefs.

Science.gov (United States)

Morais, R A; Ferreira, C E L; Floeter, S R

2017-12-01

A large fish-count dataset from the Brazilian province was used to describe spatial patterns in standing biomass and test if total biomass, taxonomic and functional trophic structure vary across nested spatial scales. Taxonomic and functional structure varied more among localities and sites than among regions. Total biomass was generally higher at oceanic islands and remote or protected localities along the coast. Lower level carnivores comprised a large part of the biomass at almost all localities (mean of 44%), zooplanktivores never attained more than 14% and omnivores were more representative of subtropical reefs and oceanic islands (up to 66% of total biomass). Small and large herbivores and detritivores varied greatly in their contribution to total biomass, with no clear geographical patterns. Macrocarnivores comprised less than 12% of the biomass anywhere, except for two remote localities. Top predators, such as sharks and very large groupers, were rare and restricted to a few reefs, suggesting that their ecological function might have already been lost in many Brazilian reefs. © 2017 The Fisheries Society of the British Isles.

Design of an omnidirectional single-point photodetector for large-scale spatial coordinate measurement

Science.gov (United States)

Xie, Hongbo; Mao, Chensheng; Ren, Yongjie; Zhu, Jigui; Wang, Chao; Yang, Lei

2017-10-01

In high precision and large-scale coordinate measurement, one commonly used approach to determine the coordinate of a target point is utilizing the spatial trigonometric relationships between multiple laser transmitter stations and the target point. A light receiving device at the target point is the key element in large-scale coordinate measurement systems. To ensure high-resolution and highly sensitive spatial coordinate measurement, a high-performance and miniaturized omnidirectional single-point photodetector (OSPD) is greatly desired. We report one design of OSPD using an aspheric lens, which achieves an enhanced reception angle of -5 deg to 45 deg in vertical and 360 deg in horizontal. As the heart of our OSPD, the aspheric lens is designed in a geometric model and optimized by LightTools Software, which enables the reflection of a wide-angle incident light beam into the single-point photodiode. The performance of home-made OSPD is characterized with working distances from 1 to 13 m and further analyzed utilizing developed a geometric model. The experimental and analytic results verify that our device is highly suitable for large-scale coordinate metrology. The developed device also holds great potential in various applications such as omnidirectional vision sensor, indoor global positioning system, and optical wireless communication systems.

Spatial coherence and large-scale drivers of drought

Science.gov (United States)

Svensson, Cecilia; Hannaford, Jamie

2017-04-01

Drought is a potentially widespread and generally multifaceted natural phenomenon affecting all aspects of the hydrological cycle. It mainly manifests itself at seasonal, or longer, time scales. Here, we use seasonal river flows across the climatologically and topographically diverse UK to investigate the spatial coherence of drought, and explore its oceanic and atmospheric drivers. A better understanding of the spatial characteristics and drivers will improve forecasting and help increase drought preparedness. The location of the UK in the mid-latitude belt of predominantly westerly winds, together with a pronounced topographical divide running roughly from north to south, produce strong windward and leeward effects. Weather fronts associated with storms tracking north-eastward between Scotland and Iceland typically lead to abundant precipitation in the mountainous north and west, while the south and east remain drier. In contrast, prolonged precipitation in eastern Britain tends to be associated with storms on a more southerly track, producing precipitation in onshore winds on the northern side of depressions. Persistence in the preferred storm tracks can therefore result in periods of wet/dry conditions across two main regions of the UK, a mountainous northwest region exposed to westerly winds and a more sheltered, lowland southeast region. This is reflected in cluster analyses of monthly river flow anomalies. A further division into three clusters separates out a region of highly permeable, slowly responding, catchments in the southeast. An expectation that the preferred storm tracks over seasonal time scales can be captured by atmospheric airflow indices, which in turn may be related to oceanic conditions, suggests that statistical methods may be used to describe the relationships between UK regional streamflows, and oceanic and atmospheric drivers. Such relationships may be concurrent or lagged, and the longer response time of the group of permeable

Relationship between Eurasian large-scale patterns and regional climate variability over the Black and Baltic Seas

Energy Technology Data Exchange (ETDEWEB)

Stankunavicius, G.; Pupienis, D. [Vilnius Univ. (Lithuania). Dept. of Hydrology and Climatology; Basharin, D. [National Academy of Science of Ukraine, Sevastopol (Ukraine). Sevastopol Marine Hydrophysical Inst.

2012-11-01

Using a NCEP/NCAR Reanalysis dataset and the empirical orthogonal function (EOF) analysis approach we studied interannual to decadal variabilities of the sea-level air pressure (SLP) and the surface air temperature (SAT) fields over Eurasia during the 2nd part of the 20th century. Our results agree with those of the previous studies, which conclude that Eurasian trends are the result of storm-path changes driven by the interdecadal behaviour of the NAO-like meridional dipole pattern in the Atlantic. On interannual and decadal time scales, significant synchronous correlations between correspondent modes of SAT and SLP EOF patterns were found. This fact suggests that there is a strong and stable Eurasian interrelationship between SAT and SLP large-scale fields which affects the local climate of two sub-regions: the Black and Baltic Seas. The climate variability in these sub-regions was studied in terms of Eurasian large-scale surface-temperature and air-pressure patterns responses. We concluded that the sub-regional climate variability substantially differs over the Black and Baltic Seas, and depends on different Eurasian large-scale patterns. We showed that the Baltic Sea region is influenced by the patterns arising primary from NAO-like meridional dipole, as well as Scandinavian patterns, while the Black Sea's SAT/SLP variability is influenced mainly by the second mode EOF (eastern Atlantic) and large scale tropospheric wave structures. (orig.)

SPATIALLY RESOLVED SPECTROSCOPY OF EUROPA’S LARGE-SCALE COMPOSITIONAL UNITS AT 3–4 μ m WITH KECK NIRSPEC

Energy Technology Data Exchange (ETDEWEB)

Fischer, P. D.; Brown, M. E.; Trumbo, S. K. [Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 (United States); Hand, K. P., E-mail: pfischer@caltech.edu [Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109 (United States)

2017-01-01

We present spatially resolved spectroscopic observations of Europa’s surface at 3–4 μ m obtained with the near-infrared spectrograph and adaptive optics system on the Keck II telescope. These are the highest quality spatially resolved reflectance spectra of Europa’s surface at 3–4 μ m. The observations spatially resolve Europa’s large-scale compositional units at a resolution of several hundred kilometers. The spectra show distinct features and geographic variations associated with known compositional units; in particular, large-scale leading hemisphere chaos shows a characteristic longward shift in peak reflectance near 3.7 μ m compared to icy regions. These observations complement previous spectra of large-scale chaos, and can aid efforts to identify the endogenous non-ice species.

Characterizing Spatial Neighborhoods of Refugia Following Large Fires in Northern New Mexico USA

Directory of Open Access Journals (Sweden)

Sandra L. Haire

2017-03-01

Full Text Available The spatial patterns resulting from large fires include refugial habitats that support surviving legacies and promote ecosystem recovery. To better understand the diverse ecological functions of refugia on burn mosaics, we used remotely sensed data to quantify neighborhood patterns of areas relatively unchanged following the 2011 Las Conchas fire. Spatial patterns of refugia measured within 10-ha moving windows varied across a gradient from areas of high density, clustered in space, to sparsely populated neighborhoods that occurred in the background matrix. The scaling of these patterns was related to the underlying structure of topography measured by slope, aspect and potential soil wetness, and spatially varying climate. Using a nonmetric multidimensional scaling analysis of species cover data collected post-Las Conchas, we found that trees and forest associates were present across the refugial gradient, but communities also exhibited a range of species compositions and potential functions. Spatial patterns of refugia quantified for three previous burns (La Mesa 1977, Dome 1996, Cerro Grande 2000 were dynamic between fire events, but most refugia persisted through at least two fires. Efforts to maintain burn heterogeneity and its ecological functions can begin with identifying where refugia are likely to occur, using terrain-based microclimate models, burn severity models and available field data.

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

Directory of Open Access Journals (Sweden)

C. M. R. Mateo

2017-10-01

Full Text Available Global-scale river models (GRMs are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC is assumed, simulation results deteriorate with finer spatial resolution; Nash–Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

Science.gov (United States)

Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan

2017-10-01

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

Large Scale Meteorological Pattern of Extreme Rainfall in Indonesia

Science.gov (United States)

Kuswanto, Heri; Grotjahn, Richard; Rachmi, Arinda; Suhermi, Novri; Oktania, Erma; Wijaya, Yosep

2014-05-01

Extreme Weather Events (EWEs) cause negative impacts socially, economically, and environmentally. Considering these facts, forecasting EWEs is crucial work. Indonesia has been identified as being among the countries most vulnerable to the risk of natural disasters, such as floods, heat waves, and droughts. Current forecasting of extreme events in Indonesia is carried out by interpreting synoptic maps for several fields without taking into account the link between the observed events in the 'target' area with remote conditions. This situation may cause misidentification of the event leading to an inaccurate prediction. Grotjahn and Faure (2008) compute composite maps from extreme events (including heat waves and intense rainfall) to help forecasters identify such events in model output. The composite maps show large scale meteorological patterns (LSMP) that occurred during historical EWEs. Some vital information about the EWEs can be acquired from studying such maps, in addition to providing forecaster guidance. Such maps have robust mid-latitude meteorological patterns (for Sacramento and California Central Valley, USA EWEs). We study the performance of the composite approach for tropical weather condition such as Indonesia. Initially, the composite maps are developed to identify and forecast the extreme weather events in Indramayu district- West Java, the main producer of rice in Indonesia and contributes to about 60% of the national total rice production. Studying extreme weather events happening in Indramayu is important since EWEs there affect national agricultural and fisheries activities. During a recent EWE more than a thousand houses in Indramayu suffered from serious flooding with each home more than one meter underwater. The flood also destroyed a thousand hectares of rice plantings in 5 regencies. Identifying the dates of extreme events is one of the most important steps and has to be carried out carefully. An approach has been applied to identify the

Spatial patterns of correlated scale size and scale color in relation to color pattern elements in butterfly wings.

Science.gov (United States)

Iwata, Masaki; Otaki, Joji M

2016-02-01

Complex butterfly wing color patterns are coordinated throughout a wing by unknown mechanisms that provide undifferentiated immature scale cells with positional information for scale color. Because there is a reasonable level of correspondence between the color pattern element and scale size at least in Junonia orithya and Junonia oenone, a single morphogenic signal may contain positional information for both color and size. However, this color-size relationship has not been demonstrated in other species of the family Nymphalidae. Here, we investigated the distribution patterns of scale size in relation to color pattern elements on the hindwings of the peacock pansy butterfly Junonia almana, together with other nymphalid butterflies, Vanessa indica and Danaus chrysippus. In these species, we observed a general decrease in scale size from the basal to the distal areas, although the size gradient was small in D. chrysippus. Scales of dark color in color pattern elements, including eyespot black rings, parafocal elements, and submarginal bands, were larger than those of their surroundings. Within an eyespot, the largest scales were found at the focal white area, although there were exceptional cases. Similarly, ectopic eyespots that were induced by physical damage on the J. almana background area had larger scales than in the surrounding area. These results are consistent with the previous finding that scale color and size coordinate to form color pattern elements. We propose a ploidy hypothesis to explain the color-size relationship in which the putative morphogenic signal induces the polyploidization (genome amplification) of immature scale cells and that the degrees of ploidy (gene dosage) determine scale color and scale size simultaneously in butterfly wings. Copyright © 2015 Elsevier Ltd. All rights reserved.

Large Scale Relationship between Aquatic Insect Traits and Climate.

Science.gov (United States)

Bhowmik, Avit Kumar; Schäfer, Ralf B

2015-01-01

Climate is the predominant environmental driver of freshwater assemblage pattern on large spatial scales, and traits of freshwater organisms have shown considerable potential to identify impacts of climate change. Although several studies suggest traits that may indicate vulnerability to climate change, the empirical relationship between freshwater assemblage trait composition and climate has been rarely examined on large scales. We compared the responses of the assumed climate-associated traits from six grouping features to 35 bioclimatic indices (~18 km resolution) for five insect orders (Diptera, Ephemeroptera, Odonata, Plecoptera and Trichoptera), evaluated their potential for changing distribution pattern under future climate change and identified the most influential bioclimatic indices. The data comprised 782 species and 395 genera sampled in 4,752 stream sites during 2006 and 2007 in Germany (~357,000 km² spatial extent). We quantified the variability and spatial autocorrelation in the traits and orders that are associated with the combined and individual bioclimatic indices. Traits of temperature preference grouping feature that are the products of several other underlying climate-associated traits, and the insect order Ephemeroptera exhibited the strongest response to the bioclimatic indices as well as the highest potential for changing distribution pattern. Regarding individual traits, insects in general and ephemeropterans preferring very cold temperature showed the highest response, and the insects preferring cold and trichopterans preferring moderate temperature showed the highest potential for changing distribution. We showed that the seasonal radiation and moisture are the most influential bioclimatic aspects, and thus changes in these aspects may affect the most responsive traits and orders and drive a change in their spatial distribution pattern. Our findings support the development of trait-based metrics to predict and detect climate

The spatial distribution of pollutants in pipe-scale of large-diameter pipelines in a drinking water distribution system

Energy Technology Data Exchange (ETDEWEB)

Liu, Jingqing [College of Engineering and Architecture, Zhejiang University, Hangzhou 310058 (China); Chen, Huanyu [College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058 (China); Binhai Industrial Technology Research Institute of Zhejiang University, Tianjin 300000 (China); Yao, Lingdan; Wei, Zongyuan [College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058 (China); Lou, Liping, E-mail: loulp@zju.edu.cn [College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058 (China); Shan, Yonggui; Endalkachew, Sahle-Demessie; Mallikarjuna, Nadagouda [Environmental Protection Agency, Office of Research and Development, NRMRL, Cincinnati, OH 45220 (United States); Hu, Baolan [College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058 (China); Zhou, Xiaoyan [Shaoxing Water Environmental Science Institute Co. Ltd, Zhejiang 312000 (China)

2016-11-05

Highlights: • First investigating the spatial distribution of pollutants in pipe-scale. • Spatial distribution of heavy metals indicated their sources were different. • Three main factors effete the distribution of pollutants. • Organic deposits mainly included microbial and microalgae metabolites. - Abstract: In large-diameter drinking water pipelines, spatial differences in hydraulic and physiochemical conditions may also result in spatial variations in pipe corrosion, biofilm growth and pollutant accumulation. In this article, the spatial distributions of various metals and organic contaminants in two 19-year-old grey cast iron pipes which had an internal diameter of 600 mm (DN600), were investigated and analyzed by Atomic Absorption Spectrometry, Gas Chromatography–Mass Spectrometry, Energy Dispersive Spectrometer, X-ray Diffraction, etc. The spatial distribution of heavy metals varied significantly across the pipe section, and iron, manganese, lead, copper, and chromium were highest in concentration in the upper portion pipe-scales. However, the highest aluminum and zinc content was detected in the lower portion pipe-scales. Apart from some common types of hydrocarbons formed by microbial metabolites, there were also some microalgae metabolites and exogenous contaminants accumulated in pipe-scale, which also exhibited high diversity between different spatial locations. The spatial distributions of the physical and chemical properties of pipe-scale and contaminants were quite different in large-diameter pipes. The finding put forward higher requirements on the research method about drinking water distribution system chemical safety. And the scientific community need understand trend and dynamics of drinking water pipe systems better.

The spatial distribution of pollutants in pipe-scale of large-diameter pipelines in a drinking water distribution system

International Nuclear Information System (INIS)

Liu, Jingqing; Chen, Huanyu; Yao, Lingdan; Wei, Zongyuan; Lou, Liping; Shan, Yonggui; Endalkachew, Sahle-Demessie; Mallikarjuna, Nadagouda; Hu, Baolan; Zhou, Xiaoyan

2016-01-01

Highlights: • First investigating the spatial distribution of pollutants in pipe-scale. • Spatial distribution of heavy metals indicated their sources were different. • Three main factors effete the distribution of pollutants. • Organic deposits mainly included microbial and microalgae metabolites. - Abstract: In large-diameter drinking water pipelines, spatial differences in hydraulic and physiochemical conditions may also result in spatial variations in pipe corrosion, biofilm growth and pollutant accumulation. In this article, the spatial distributions of various metals and organic contaminants in two 19-year-old grey cast iron pipes which had an internal diameter of 600 mm (DN600), were investigated and analyzed by Atomic Absorption Spectrometry, Gas Chromatography–Mass Spectrometry, Energy Dispersive Spectrometer, X-ray Diffraction, etc. The spatial distribution of heavy metals varied significantly across the pipe section, and iron, manganese, lead, copper, and chromium were highest in concentration in the upper portion pipe-scales. However, the highest aluminum and zinc content was detected in the lower portion pipe-scales. Apart from some common types of hydrocarbons formed by microbial metabolites, there were also some microalgae metabolites and exogenous contaminants accumulated in pipe-scale, which also exhibited high diversity between different spatial locations. The spatial distributions of the physical and chemical properties of pipe-scale and contaminants were quite different in large-diameter pipes. The finding put forward higher requirements on the research method about drinking water distribution system chemical safety. And the scientific community need understand trend and dynamics of drinking water pipe systems better.

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

Science.gov (United States)

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.

Spatial pattern and ecological process in the coffee agroforestry system.

Science.gov (United States)

Perfecto, Ivette; Vandermeer, John

2008-04-01

The coffee agroforestry system provides an ideal platform for the study of spatial ecology. The uniform pattern of the coffee plants and shade trees allows for the study of pattern generation through intrinsic biological forces rather than extrinsic habitat patchiness. Detailed studies, focusing on a key mutualism between an ant (Azteca instabilis) and a scale insect (Coccus viridis), conducted in a 45-ha plot in a coffee agroforestry system have provided insights into (1) the quantitative evaluation of spatial pattern of the scale insect Coccus viridis on coffee bushes, (2) the mechanisms for the generation of patterns through the combination of local satellite ant nest formation and regional control from natural enemies, and (3) the consequences of the spatial pattern for the stability of predator-prey (host-parasitoid) systems, for a key coccinelid beetle preying on the scale insects and a phorid fly parasitoid parasitizing the ant.

Mapping the distribution of the denitrifier community at large scales (Invited)

Science.gov (United States)

Philippot, L.; Bru, D.; Ramette, A.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 740 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Spatial Autocorrelation Patterns of Understory Plant Species in a Subtropical Rainforest at Lanjenchi, Southern Taiwan

Directory of Open Access Journals (Sweden)

Su-Wei Fan

2010-06-01

Full Text Available Many studies described relationships between plant species and intrinsic or exogenous factors, but few quantified spatial scales of species patterns. In this study, quantitative methods were used to explore the spatial scale of understory species (including resident and transient species, in order to identify the influential factors of species distribution. Resident species (including herbaceous species, climbers and tree ferns < 1 m high were investigated on seven transects, each 5-meter wide and 300-meter long, at Lanjenchi plot in Nanjenshan Reserve, southern Taiwan. Transient species (seedling of canopy, subcanopy and shrub species < 1 cm diameter at breast height were censused in three of the seven transects. The herb coverage and seedling abundance were calculated for each 5 × 5 m quadrat along the transects, and Moran’s I and Galiano’s new local variance (NLV indices were then used to identify the spatial scale of autocorrelation for each species. Patterns of species abundance of understory layer varied among species at fine scale within 50 meters. Resident species showed a higher proportion of significant autocorrelation than the transient species. Species with large size or prolonged fronds or stems tended to show larger scales in autocorrelation. However, dispersal syndromes and fruit types did not relate to any species’ spatial patterns. Several species showed a significant autocorrelation at a 180-meter class which happened to correspond to the local replicates of topographical features in hilltops. The spatial patterns of understory species at Lanjenchi plot are mainly influenced by species’ intrinsic traits and topographical characteristics.

The spatial distribution of pollutants in pipe-scale of large-diameter pipelines in a drinking water distribution system.

Science.gov (United States)

Liu, Jingqing; Chen, Huanyu; Yao, Lingdan; Wei, Zongyuan; Lou, Liping; Shan, Yonggui; Endalkachew, Sahle-Demessie; Mallikarjuna, Nadagouda; Hu, Baolan; Zhou, Xiaoyan

2016-11-05

In large-diameter drinking water pipelines, spatial differences in hydraulic and physiochemical conditions may also result in spatial variations in pipe corrosion, biofilm growth and pollutant accumulation. In this article, the spatial distributions of various metals and organic contaminants in two 19-year-old grey cast iron pipes which had an internal diameter of 600mm (DN600), were investigated and analyzed by Atomic Absorption Spectrometry, Gas Chromatography-Mass Spectrometry, Energy Dispersive Spectrometer, X-ray Diffraction, etc. The spatial distribution of heavy metals varied significantly across the pipe section, and iron, manganese, lead, copper, and chromium were highest in concentration in the upper portion pipe-scales. However, the highest aluminum and zinc content was detected in the lower portion pipe-scales. Apart from some common types of hydrocarbons formed by microbial metabolites, there were also some microalgae metabolites and exogenous contaminants accumulated in pipe-scale, which also exhibited high diversity between different spatial locations. The spatial distributions of the physical and chemical properties of pipe-scale and contaminants were quite different in large-diameter pipes. The finding put forward higher requirements on the research method about drinking water distribution system chemical safety. And the scientific community need understand trend and dynamics of drinking water pipe systems better. Copyright © 2016 Elsevier B.V. All rights reserved.

Multi-Scale Influences of Climate, Spatial Pattern, and Positive Feedback on 20th Century Tree Establishment at Upper Treeline in the Rocky Mountains, USA

Science.gov (United States)

Elliott, G. P.

2009-12-01

The influences of 20th century climate, spatial pattern of tree establishment, and positive feedback were assessed to gain a more holistic understanding of how broad scale abiotic and local scale biotic components interact to govern upper treeline ecotonal dynamics along a latitudinal gradient (ca. 35°N-45°N) in the Rocky Mountains. Study sites (n = 22) were in the Bighorn, Medicine Bow, Front Range, and Sangre de Cristo mountain ranges. Dendroecological techniques were used for a broad scale analysis of climate at treeline. Five-year age-structure classes were compared with identical five-year bins of 20th century climate data using Spearman’s rank correlation and regime shift analysis. Local scale biotic interactions capable of ameliorating broad scale climate inputs through positive feedback were examined by using Ripley’s K to determine the spatial patterns of tree establishment above timberline. Significant correlations (p Medicine Bow and Sangre de Cristo Mountains primarily contain clustered spatial patterns of trees above timberline, which indicates a strong reliance on the amelioration of abiotic conditions through positive feedback with nearby vegetation. Although clustered spatial patterns likely originate in response to harsh abiotic conditions such as drought or constant strong winds, the local scale biotic interactions within a clustered formation of trees appears to override the immediate influence of broad scale climate. This is evidenced both by a lack of significant correlations between tree establishment and climate in these mountain ranges, as well as the considerable lag times between initial climate regime shifts and corresponding shifts in tree age structure. Taken together, this research suggests that the influence of broad scale climate on upper treeline ecotonal dynamics is contingent on the local scale spatial patterns of tree establishment and related influences of positive feedback. These findings have global implications for our

A Novel Spatial-Temporal Voronoi Diagram-Based Heuristic Approach for Large-Scale Vehicle Routing Optimization with Time Constraints

Directory of Open Access Journals (Sweden)

Wei Tu

2015-10-01

Full Text Available Vehicle routing optimization (VRO designs the best routes to reduce travel cost, energy consumption, and carbon emission. Due to non-deterministic polynomial-time hard (NP-hard complexity, many VROs involved in real-world applications require too much computing effort. Shortening computing time for VRO is a great challenge for state-of-the-art spatial optimization algorithms. From a spatial-temporal perspective, this paper presents a spatial-temporal Voronoi diagram-based heuristic approach for large-scale vehicle routing problems with time windows (VRPTW. Considering time constraints, a spatial-temporal Voronoi distance is derived from the spatial-temporal Voronoi diagram to find near neighbors in the space-time searching context. A Voronoi distance decay strategy that integrates a time warp operation is proposed to accelerate local search procedures. A spatial-temporal feature-guided search is developed to improve unpromising micro route structures. Experiments on VRPTW benchmarks and real-world instances are conducted to verify performance. The results demonstrate that the proposed approach is competitive with state-of-the-art heuristics and achieves high-quality solutions for large-scale instances of VRPTWs in a short time. This novel approach will contribute to spatial decision support community by developing an effective vehicle routing optimization method for large transportation applications in both public and private sectors.

Spatial distribution of enzyme driven reactions at micro-scales

Science.gov (United States)

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).

Large-scale patterns in Rayleigh-Benard convection

International Nuclear Information System (INIS)

Hardenberg, J. von; Parodi, A.; Passoni, G.; Provenzale, A.; Spiegel, E.A.

2008-01-01

Rayleigh-Benard convection at large Rayleigh number is characterized by the presence of intense, vertically moving plumes. Both laboratory and numerical experiments reveal that the rising and descending plumes aggregate into separate clusters so as to produce large-scale updrafts and downdrafts. The horizontal scales of the aggregates reported so far have been comparable to the horizontal extent of the containers, but it has not been clear whether that represents a limitation imposed by domain size. In this work, we present numerical simulations of convection at sufficiently large aspect ratio to ascertain whether there is an intrinsic saturation scale for the clustering process when that ratio is large enough. From a series of simulations of Rayleigh-Benard convection with Rayleigh numbers between 10 5 and 10 8 and with aspect ratios up to 12π, we conclude that the clustering process has a finite horizontal saturation scale with at most a weak dependence on Rayleigh number in the range studied

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

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Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Spatial extent of analysis influences observed patterns of population genetic structure in a widespread darter species (Percidae)

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Argentina, Jane E.; Angermeier, Paul L.; Hallerman, Eric M.; Welsh, Stuart A.

2018-01-01

Connectivity among stream fish populations allows for exchange of genetic material and helps maintain genetic diversity, adaptive potential and population stability over time. Changes in species demographics and population connectivity have the potential to permanently alter the genetic patterns of stream fish, although these changes through space and time are variable and understudied in small‐bodied freshwater fish.As a spatially widespread, common species of benthic freshwater fish, the variegate darter (Etheostoma variatum) is a model species for documenting how patterns of genetic structure and diversity respond to increasing isolation due to large dams and how scale of study may shape our understanding of these patterns. We sampled variegate darters from 34 sites across their range in the North American Ohio River basin and examined how patterns of genetic structure and diversity within and between populations responded to historical population changes and dams within and between populations.Spatial scale and configuration of genetic structure varied across the eight identified populations, from tributaries within a watershed, to a single watershed, to multiple watersheds that encompass Ohio River mainstem habitats. This multiwatershed pattern of population structuring suggests genetic dispersal across large distances was and may continue to be common, although some populations remain isolated despite no apparent structural dispersal barriers. Populations with low effective population sizes and evidence of past population bottlenecks showed low allelic richness, but diversity patterns were not related to watershed size, a surrogate for habitat availability. Pairwise genetic differentiation (FST) increased with fluvial distance and was related to both historic and contemporary processes. Genetic diversity changes were influenced by underlying population size and stability, and while instream barriers were not strong determinants of genetic structuring or

The intertidal community in West Greenland: Large-scale patterns and small-scale variation on ecosystem dynamics along a climate gradient

DEFF Research Database (Denmark)

Thyrring, Jakob; Blicher, Martin; Sejr, Mikael Kristian

are largely unknown. The West Greenland coast is north - south orientated. This provides an ideal setting to study the impact of climate change on marine species population dynamics and distribution. We investigated the latitudinal changes in the rocky intertidal community along 18° latitudes (59-77°N......) in West Greenland. Using cleared quadrats we quantified patterns in abundance, biomass and species richness in the intertidal zone. We use this data to disentangle patterns in Arctic intertidal communities at different scales. We describe the effects of different environmental drivers and species...... interactions on distribution and dynamics of intertidal species. Our results indicate that changes in distribution and abundance of foundation species can have large effects on the ecosystem. We also show that the importance of small-scale variation may be of same magnitude as large- scale variation. Only...

Herbivore-induced plant volatiles and tritrophic interactions across spatial scales.

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Aartsma, Yavanna; Bianchi, Felix J J A; van der Werf, Wopke; Poelman, Erik H; Dicke, Marcel

2017-12-01

Herbivore-induced plant volatiles (HIPVs) are an important cue used in herbivore location by carnivorous arthropods such as parasitoids. The effects of plant volatiles on parasitoids have been well characterised at small spatial scales, but little research has been done on their effects at larger spatial scales. The spatial matrix of volatiles ('volatile mosaic') within which parasitoids locate their hosts is dynamic and heterogeneous. It is shaped by the spatial pattern of HIPV-emitting plants, the concentration, chemical composition and breakdown of the emitted HIPV blends, and by environmental factors such as wind, turbulence and vegetation that affect transport and mixing of odour plumes. The volatile mosaic may be exploited differentially by different parasitoid species, in relation to species traits such as sensory ability to perceive volatiles and the physical ability to move towards the source. Understanding how HIPVs influence parasitoids at larger spatial scales is crucial for our understanding of tritrophic interactions and sustainable pest management in agriculture. However, there is a large gap in our knowledge on how volatiles influence the process of host location by parasitoids at the landscape scale. Future studies should bridge the gap between the chemical and behavioural ecology of tritrophic interactions and landscape ecology. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Spatial scale and β-diversity of terrestrial vertebrates in Mexico

OpenAIRE

Ochoa-Ochoa, Leticia M.; Munguía, Mariana; Lira-Noriega, Andrés; Sánchez-Cordero, Víctor; Flores-Villela, Oscar; Navarro-Sigüenza, Adolfo; Rodríguez, Pilar

2014-01-01

Patterns of diversity are scale dependent and beta-diversity is not the exception. Mexico is megadiverse due to its high beta diversity, but little is known if it is scale-dependent and/or taxonomic-dependent. We explored these questions based on the self-similarity hypothesis of beta-diversity across spatial scales. Using geographic distribution ranges of 2 513 species, we compared the beta-diversity patterns of 4 groups of terrestrial vertebrates, across 7 spatial scales (from ~10 km² to 16...

Multiresolution comparison of precipitation datasets for large-scale models

Science.gov (United States)

Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

2014-12-01

Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

Science.gov (United States)

Verdon-Kidd, D. C.; Kiem, A. S.

2009-04-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Simulating spatial patterns of land-use change in Rondonia, Brazil

International Nuclear Information System (INIS)

Dale, V.H.; Southworth, F.; O'Neill, R.V.; Rosen, A.

1992-01-01

Large scale deforestation in the Brazilian state of Rondonia has resulted from massive colonization and has caused increases in atmospheric CO 2 , soil degradation, loss of extractive resources, and disruption of indigenous populations. A simulation model has been developed that integrates colonization, socioeconomic, and ecological submodels to estimate spatial patterns and rates of deforestation under different immigration policies, land tenure practices, and road development scenarios. It is used to model the socioeconomic causes and ecological impacts of rapid deforestation in Rondonia. The simulation can be used to identify scenarios that might optimize economic and agricultural sustainability or reduce emigration. Spatial analysis of the simulation projections shows that very different patterns of deforestation can result depending on whether soil suitability, distance to market or lot size is the prime factor affecting a colonist's choice of a lot. Projections of the amount and pattern of deforestation under specific scenarios of land-use choice and management can be used to explore the socioeconomic and ecological implications of land-use change

Towards a taxonomy of spatial scale-dependence

DEFF Research Database (Denmark)

Sandel, Brody Steven

2015-01-01

Spatial scale-dependence is a ubiquitous feature of ecological systems. This presents a challenge for ecologists who seek to discern general principles. A solution is to search for generalities in patterns of scale-dependence – that is, what kinds of things are scale-dependent, in what ways, and ...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Spatial Patterns and the Regional Differences of Rural Settlements in Jilin Province, China

Directory of Open Access Journals (Sweden)

Xiaoyan Li

2017-11-01

Full Text Available The spatial patterns of rural settlements are important for understanding the drivers of land use change and the relationship between human activity and environmental processes. It has been suggested that the clustering of houses decreases the negative effects on the environment and promotes the development of the countryside, but few empirical studies have quantified the spatial distribution patterns of houses. Our aim was to explore the regional differences in rural settlement patterns and expand our understanding of their geographic associations, and thus contribute to land use planning and the implementation of the policy of “building a new countryside”. We used spatial statistical methods and indices of landscape metrics to investigate different settlement patterns in three typical counties within different environments in Jilin Province, Northeast China. The results indicated that rural settlements in these three counties were all clustered, but to a varied degree. Settlement density maps and landscape metrics displayed uniformity of the settlement distributions within plain, hill, and mountainous areas. Influenced by the physical environment, the scale, form, and degree of aggregation varied. Accordingly, three types of rural settlements were summarized: a low-density, large-scale and sparse type; a mass-like and point-scattered type; and a low-density and high cluster-like type. The spatial patterns of rural settlements are the result of anthropogenic and complex physical processes, and provide an important insight for the layout and management of the countryside.

Network-scale spatial and temporal variation in Chinook salmon (Oncorhynchus tshawytscha) redd distributions: patterns inferred from spatially continuous replicate surveys

Science.gov (United States)

Daniel J. Isaak; Russell F. Thurow

2006-01-01

Spatially continuous sampling designs, when temporally replicated, provide analytical flexibility and are unmatched in their ability to provide a dynamic system view. We have compiled such a data set by georeferencing the network-scale distribution of Chinook salmon (Oncorhynchus tshawytscha) redds across a large wilderness basin (7330 km2) in...

Spatial pattern evaluation of a calibrated national hydrological model - a remote-sensing-based diagnostic approach

Science.gov (United States)

Mendiguren, Gorka; Koch, Julian; Stisen, Simon

2017-11-01

Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two-source energy balance model (TSEB) driven mainly by satellite remote sensing data. Ideally, the hydrological model simulation and remote-sensing-based approach should present similar spatial patterns and driving mechanisms of ET. However, the spatial comparison showed that the differences are significant and indicate insufficient spatial pattern performance of the hydrological model.The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in six domains that are calibrated independently from each other, as it is often the case for large-scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of leaf area index (LAI), root depth (RD) and crop coefficient (Kc) for each land cover type. This zonal approach of model parameterization ignores the spatiotemporal complexity of the natural system. To overcome this limitation, this study features a modified version of the DK-model in which LAI, RD and Kc are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatiotemporal variability and spatial consistency between the six domains. The effects of these changes are analyzed by using empirical orthogonal function (EOF) analysis to evaluate spatial patterns. The EOF analysis shows that including remote-sensing-derived LAI, RD and Kc in the distributed hydrological model adds

[Spatial point pattern analysis of main trees and flowering Fargesia qinlingensis in Abies fargesii forests in Mt Taibai of the Qinling Mountains, China].

Science.gov (United States)

Li, Guo Chun; Song, Hua Dong; Li, Qi; Bu, Shu Hai

2017-11-01

In Abies fargesii forests of the giant panda's habitats in Mt. Taibai, the spatial distribution patterns and interspecific associations of main tree species and their spatial associations with the understory flowering Fargesia qinlingensis were analyzed at multiple scales by univariate and bivaria-te O-ring function in point pattern analysis. The results showed that in the A. fargesii forest, the number of A. fargesii was largest but its population structure was in decline. The population of Betula platyphylla was relatively young, with a stable population structure, while the population of B. albo-sinensis declined. The three populations showed aggregated distributions at small scales and gradually showed random distributions with increasing spatial scales. Spatial associations among tree species were mainly showed at small scales and gradually became not spatially associated with increasing scale. A. fargesii and B. platyphylla were positively associated with flowering F. qinlingensis at large and medium scales, whereas B. albo-sinensis showed negatively associated with flowering F. qinlingensis at large and medium scales. The interaction between trees and F. qinlingensis in the habitats of giant panda promoted the dynamic succession and development of forests, which changed the environment of giant panda's habitats in Qinling.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data.

Science.gov (United States)

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H

2012-11-06

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the "big data" challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce.

Analysis using large-scale ringing data

Directory of Open Access Journals (Sweden)

Baillie, S. R.

2004-06-01

Full Text Available Birds are highly mobile organisms and there is increasing evidence that studies at large spatial scales are needed if we are to properly understand their population dynamics. While classical metapopulation models have rarely proved useful for birds, more general metapopulation ideas involving collections of populations interacting within spatially structured landscapes are highly relevant (Harrison, 1994. There is increasing interest in understanding patterns of synchrony, or lack of synchrony, between populations and the environmental and dispersal mechanisms that bring about these patterns (Paradis et al., 2000. To investigate these processes we need to measure abundance, demographic rates and dispersal at large spatial scales, in addition to gathering data on relevant environmental variables. There is an increasing realisation that conservation needs to address rapid declines of common and widespread species (they will not remain so if such trends continue as well as the management of small populations that are at risk of extinction. While the knowledge needed to support the management of small populations can often be obtained from intensive studies in a few restricted areas, conservation of widespread species often requires information on population trends and processes measured at regional, national and continental scales (Baillie, 2001. While management prescriptions for widespread populations may initially be developed from a small number of local studies or experiments, there is an increasing need to understand how such results will scale up when applied across wider areas. There is also a vital role for monitoring at large spatial scales both in identifying such population declines and in assessing population recovery. Gathering data on avian abundance and demography at large spatial scales usually relies on the efforts of large numbers of skilled volunteers. Volunteer studies based on ringing (for example Constant Effort Sites [CES

Identification of large-scale meteorological patterns associated with extreme precipitation in the US northeast

Science.gov (United States)

Agel, Laurie; Barlow, Mathew; Feldstein, Steven B.; Gutowski, William J.

2018-03-01

Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. The tropopause height provides a compact representation of the upper-tropospheric potential vorticity, which is closely related to the overall evolution and intensity of weather systems. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979-2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into the overall context of patterns for all days. Six tropopause patterns are identified through KMC for extreme day precipitation: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong moisture transport preceding, and upward motion during, extreme precipitation events.

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

Science.gov (United States)

Gosme, Marie; Lucas, Philippe

2009-07-01

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

Non-stationary analysis of the frequency and intensity of heavy precipitation over Canada and their relations to large-scale climate patterns

Science.gov (United States)

Tan, Xuezhi; Gan, Thian Yew

2017-05-01

In recent years, because the frequency and severity of floods have increased across Canada, it is important to understand the characteristics of Canadian heavy precipitation. Long-term precipitation data of 463 gauging stations of Canada were analyzed using non-stationary generalized extreme value distribution (GEV), Poisson distribution and generalized Pareto (GP) distribution. Time-varying covariates that represent large-scale climate patterns such as El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific decadal oscillation (PDO) and North Pacific Oscillation (NP) were incorporated to parameters of GEV, Poisson and GP distributions. Results show that GEV distributions tend to under-estimate annual maximum daily precipitation (AMP) of western and eastern coastal regions of Canada, compared to GP distributions. Poisson regressions show that temporal clusters of heavy precipitation events in Canada are related to large-scale climate patterns. By modeling AMP time series with non-stationary GEV and heavy precipitation with non-stationary GP distributions, it is evident that AMP and heavy precipitation of Canada show strong non-stationarities (abrupt and slowly varying changes) likely because of the influence of large-scale climate patterns. AMP in southwestern coastal regions, southern Canadian Prairies and the Great Lakes tend to be higher in El Niño than in La Niña years, while AMP of other regions of Canada tends to be lower in El Niño than in La Niña years. The influence of ENSO on heavy precipitation was spatially consistent but stronger than on AMP. The effect of PDO, NAO and NP on extreme precipitation is also statistically significant at some stations across Canada.

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

Science.gov (United States)

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

2018-08-01

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

Predicting the effect of fire on large-scale vegetation patterns in North America.

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Donald McKenzie; David L. Peterson; Ernesto. Alvarado

1996-01-01

Changes in fire regimes are expected across North America in response to anticipated global climatic changes. Potential changes in large-scale vegetation patterns are predicted as a result of altered fire frequencies. A new vegetation classification was developed by condensing Kuchler potential natural vegetation types into aggregated types that are relatively...

Large-Scale Atmospheric Circulation Patterns Associated with Temperature Extremes as a Basis for Model Evaluation: Methodological Overview and Results

Science.gov (United States)

Loikith, P. C.; Broccoli, A. J.; Waliser, D. E.; Lintner, B. R.; Neelin, J. D.

2015-12-01

Anomalous large-scale circulation patterns often play a key role in the occurrence of temperature extremes. For example, large-scale circulation can drive horizontal temperature advection or influence local processes that lead to extreme temperatures, such as by inhibiting moderating sea breezes, promoting downslope adiabatic warming, and affecting the development of cloud cover. Additionally, large-scale circulation can influence the shape of temperature distribution tails, with important implications for the magnitude of future changes in extremes. As a result of the prominent role these patterns play in the occurrence and character of extremes, the way in which temperature extremes change in the future will be highly influenced by if and how these patterns change. It is therefore critical to identify and understand the key patterns associated with extremes at local to regional scales in the current climate and to use this foundation as a target for climate model validation. This presentation provides an overview of recent and ongoing work aimed at developing and applying novel approaches to identifying and describing the large-scale circulation patterns associated with temperature extremes in observations and using this foundation to evaluate state-of-the-art global and regional climate models. Emphasis is given to anomalies in sea level pressure and 500 hPa geopotential height over North America using several methods to identify circulation patterns, including self-organizing maps and composite analysis. Overall, evaluation results suggest that models are able to reproduce observed patterns associated with temperature extremes with reasonable fidelity in many cases. Model skill is often highest when and where synoptic-scale processes are the dominant mechanisms for extremes, and lower where sub-grid scale processes (such as those related to topography) are important. Where model skill in reproducing these patterns is high, it can be inferred that extremes are

20th century trends of drought conditions in the Mediterranean: the influence of large-scale circulation patterns.

Science.gov (United States)

Sousa, Pedro; Trigo, Ricardo; Garcia-Herrera, Ricardo

2010-05-01

Here we have used the Self Calibrated PDSI (scPDSI) proposed by Wells et al (2004) as a more appropriate approach to characterize drought conditions in the Mediterranean area. The scPDSI has been shown to perform better (than the original PDSI) when evaluating spatial and temporal drought characteristics for regions outside the USA (Schrier et al, 2005). Seasonal and annual trends for the 1901-2000, 1901-1950 and 1951-2000 periods were computed using the standard Mann-Kendall test for trend significance evaluation. However, statistical significance obtained with this test can be highly misleading because it does not take into account the low variability nature that dominates the seasonal evolution of scPDSI fields. We have now improved these results by employing a modified Mann-Kendall test for auto-correlated series (Hamed and Ramachandra, 1997), such as the scPDSI case. This development allowed for a better definition of the Mediterranean areas characterized by significant changes in the scPDSI, namely the largely negative trends that dominate the Mediterranean basin, with the exceptions of parts of eastern Turkey and northwestern Iberia, since initially these areas were overestimated. The spatio-temporal variability of these indices was evaluated with an EOF analysis, in order to reduce the large dimensionality of the fields under analysis. Spatial representation of the first EOF patterns shows that EOF 1 covers the entire Mediterranean basin (16.4% of EV), while EOF2 is dominated by a W-E dipole (10% EV). The following EOF patterns present smaller scale features, and explain smaller amounts of variance. The EOF patterns have also facilitated the definition of four sub-regions with large socio-economic relevance: 1) Iberia, 2) Italian Peninsula, 3) Balkans and 4) Turkey. Afterwards we perform a comprehensive analysis on the links between the scPDSI and the large-scale atmospheric circulation indices that affect the Mediterranean basin, namely; NAO, EA, and SCAND

Patterns of Spatial Variation of Assemblages Associated with Intertidal Rocky Shores: A Global Perspective

Science.gov (United States)

Cruz-Motta, Juan José; Miloslavich, Patricia; Palomo, Gabriela; Iken, Katrin; Konar, Brenda; Pohle, Gerhard; Trott, Tom; Benedetti-Cecchi, Lisandro; Herrera, César; Hernández, Alejandra; Sardi, Adriana; Bueno, Andrea; Castillo, Julio; Klein, Eduardo; Guerra-Castro, Edlin; Gobin, Judith; Gómez, Diana Isabel; Riosmena-Rodríguez, Rafael; Mead, Angela; Bigatti, Gregorio; Knowlton, Ann; Shirayama, Yoshihisa

2010-01-01

Assemblages associated with intertidal rocky shores were examined for large scale distribution patterns with specific emphasis on identifying latitudinal trends of species richness and taxonomic distinctiveness. Seventy-two sites distributed around the globe were evaluated following the standardized sampling protocol of the Census of Marine Life NaGISA project (www.nagisa.coml.org). There were no clear patterns of standardized estimators of species richness along latitudinal gradients or among Large Marine Ecosystems (LMEs); however, a strong latitudinal gradient in taxonomic composition (i.e., proportion of different taxonomic groups in a given sample) was observed. Environmental variables related to natural influences were strongly related to the distribution patterns of the assemblages on the LME scale, particularly photoperiod, sea surface temperature (SST) and rainfall. In contrast, no environmental variables directly associated with human influences (with the exception of the inorganic pollution index) were related to assemblage patterns among LMEs. Correlations of the natural assemblages with either latitudinal gradients or environmental variables were equally strong suggesting that neither neutral models nor models based solely on environmental variables sufficiently explain spatial variation of these assemblages at a global scale. Despite the data shortcomings in this study (e.g., unbalanced sample distribution), we show the importance of generating biological global databases for the use in large-scale diversity comparisons of rocky intertidal assemblages to stimulate continued sampling and analyses. PMID:21179546

Patterns of spatial variation of assemblages associated with intertidal rocky shores: a global perspective.

Directory of Open Access Journals (Sweden)

Juan José Cruz-Motta

2010-12-01

Full Text Available Assemblages associated with intertidal rocky shores were examined for large scale distribution patterns with specific emphasis on identifying latitudinal trends of species richness and taxonomic distinctiveness. Seventy-two sites distributed around the globe were evaluated following the standardized sampling protocol of the Census of Marine Life NaGISA project (www.nagisa.coml.org. There were no clear patterns of standardized estimators of species richness along latitudinal gradients or among Large Marine Ecosystems (LMEs; however, a strong latitudinal gradient in taxonomic composition (i.e., proportion of different taxonomic groups in a given sample was observed. Environmental variables related to natural influences were strongly related to the distribution patterns of the assemblages on the LME scale, particularly photoperiod, sea surface temperature (SST and rainfall. In contrast, no environmental variables directly associated with human influences (with the exception of the inorganic pollution index were related to assemblage patterns among LMEs. Correlations of the natural assemblages with either latitudinal gradients or environmental variables were equally strong suggesting that neither neutral models nor models based solely on environmental variables sufficiently explain spatial variation of these assemblages at a global scale. Despite the data shortcomings in this study (e.g., unbalanced sample distribution, we show the importance of generating biological global databases for the use in large-scale diversity comparisons of rocky intertidal assemblages to stimulate continued sampling and analyses.

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

Science.gov (United States)

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.

Precipitation patterns control the distribution and export of large wood at the catchment scale

OpenAIRE

Il Seo, Jung; Nakamura, Futoshi; Chun, Kun Woo; Kim, Suk Woo; Grant, Gordon E.

2015-01-01

Large wood (LW) plays an important role in river ecosystems, but LW-laden floods may cause serious damage to human lives and property. The relationship between precipitation patterns and variations in LW distribution and export at the watershed scale is poorly understood. To explore these linkages, we examined differences in LW distribution as a function of channel morphologies in six watersheds located in southern and northern Japan and analysed the impacts of different precipitation pattern...

Hydroclimatic variability in the Lake Mondsee region and its relationships with large-scale climate anomaly patterns

Science.gov (United States)

Rimbu, Norel; Ionita, Monica; Swierczynski, Tina; Brauer, Achim; Kämpf, Lucas; Czymzik, Markus

2017-04-01

Flood triggered detrital layers in varved sediments of Lake Mondsee, located at the northern fringe of the European Alps (47°48'N,13°23'E), provide an important archive of regional hydroclimatic variability during the mid- to late Holocene. To improve the interpretation of the flood layer record in terms of large-scale climate variability, we investigate the relationships between observational hydrological records from the region, like the Mondsee lake level, the runoff of the lake's main inflow Griesler Ache, with observed precipitation and global climate patterns. The lake level shows a strong positive linear trend during the observational period in all seasons. Additionally, lake level presents important interannual to multidecadal variations. These variations are associated with distinct seasonal atmospheric circulation patterns. A pronounced anomalous anticyclonic center over the Iberian Peninsula is associated with high lake levels values during winter. This center moves southwestward during spring, summer and autumn. In the same time, a cyclonic anomaly center is recorded over central and western Europe. This anomalous circulation extends southwestward from winter to autumn. Similar atmospheric circulation patterns are associated with river runoff and precipitation variability from the region. High lake levels are associated with positive local precipitation anomalies in all seasons as well as with negative local temperature anomalies during spring, summer and autumn. A correlation analysis reveals that lake level, runoff and precipitation variability is related to large-scale sea surface temperature anomaly patterns in all seasons suggesting a possible impact of large-scale climatic modes, like the North Atlantic Oscillation and Atlantic Multidecadal Oscillation on hydroclimatic variability in the Lake Mondsee region. The results presented in this study can be used for a more robust interpretation of the long flood layer record from Lake Mondsee sediments

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

Science.gov (United States)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of

Baseflow physical characteristics differ at multiple spatial scales in stream networks across diverse biomes

Science.gov (United States)

Janine Ruegg; Walter K. Dodds; Melinda D. Daniels; Ken R. Sheehan; Christina L. Baker; William B. Bowden; Kaitlin J. Farrell; Michael B. Flinn; Tamara K. Harms; Jeremy B. Jones; Lauren E. Koenig; John S. Kominoski; William H. McDowell; Samuel P. Parker; Amy D. Rosemond; Matt T. Trentman; Matt Whiles; Wilfred M. Wollheim

2016-01-01

ContextSpatial scaling of ecological processes is facilitated by quantifying underlying habitat attributes. Physical and ecological patterns are often measured at disparate spatial scales limiting our ability to quantify ecological processes at broader spatial scales using physical attributes.

Spatial vegetation patterns and neighborhood competition among woody plants in an East African savanna.

Science.gov (United States)

Dohn, Justin; Augustine, David J; Hanan, Niall P; Ratnam, Jayashree; Sankaran, Mahesh

2017-02-01

The majority of research on savanna vegetation dynamics has focused on the coexistence of woody and herbaceous vegetation. Interactions among woody plants in savannas are relatively poorly understood. We present data from a 10-yr longitudinal study of spatially explicit growth patterns of woody vegetation in an East African savanna following exclusion of large herbivores and in the absence of fire. We examined plant spatial patterns and quantified the degree of competition among woody individuals. Woody plants in this semiarid savanna exhibit strongly clumped spatial distributions at scales of 1-5 m. However, analysis of woody plant growth rates relative to their conspecific and heterospecific neighbors revealed evidence for strong competitive interactions at neighborhood scales of up to 5 m for most woody plant species. Thus, woody plants were aggregated in clumps despite significantly decreased growth rates in close proximity to neighbors, indicating that the spatial distribution of woody plants in this region depends on dispersal and establishment processes rather than on competitive, density-dependent mortality. However, our documentation of suppressive effects of woody plants on neighbors also suggests a potentially important role for tree-tree competition in controlling vegetation structure and indicates that the balanced-competition hypothesis may contribute to well-known patterns in maximum tree cover across rainfall gradients in Africa. © 2016 by the Ecological Society of America.

Changeable camouflage: how well can flounder resemble the colour and spatial scale of substrates in their natural habitats?

Science.gov (United States)

Akkaynak, Derya; Siemann, Liese A; Barbosa, Alexandra; Mäthger, Lydia M

2017-03-01

Flounder change colour and pattern for camouflage. We used a spectrometer to measure reflectance spectra and a digital camera to capture body patterns of two flounder species camouflaged on four natural backgrounds of different spatial scale (sand, small gravel, large gravel and rocks). We quantified the degree of spectral match between flounder and background relative to the situation of perfect camouflage in which flounder and background were assumed to have identical spectral distribution. Computations were carried out for three biologically relevant observers: monochromatic squid, dichromatic crab and trichromatic guitarfish. Our computations present a new approach to analysing datasets with multiple spectra that have large variance. Furthermore, to investigate the spatial match between flounder and background, images of flounder patterns were analysed using a custom program originally developed to study cuttlefish camouflage. Our results show that all flounder and background spectra fall within the same colour gamut and that, in terms of different observer visual systems, flounder matched most substrates in luminance and colour contrast. Flounder matched the spatial scales of all substrates except for rocks. We discuss findings in terms of flounder biology; furthermore, we discuss our methodology in light of hyperspectral technologies that combine high-resolution spectral and spatial imaging.

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

Science.gov (United States)

Tang, G.; Bartlein, P. J.

2012-08-01

Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981-2006 (R2 > 0.46, p 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH

Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics Approach

Directory of Open Access Journals (Sweden)

Junjun Yin

2016-10-01

Full Text Available Understanding human mobility patterns is of great importance for urban planning, traffic management, and even marketing campaign. However, the capability of capturing detailed human movements with fine-grained spatial and temporal granularity is still limited. In this study, we extracted high-resolution mobility data from a collection of over 1.3 billion geo-located Twitter messages. Regarding the concerns of infringement on individual privacy, such as the mobile phone call records with restricted access, the dataset is collected from publicly accessible Twitter data streams. In this paper, we employed a visual-analytics approach to studying multi-scale spatiotemporal Twitter user mobility patterns in the contiguous United States during the year 2014. Our approach included a scalable visual-analytics framework to deliver efficiency and scalability in filtering large volume of geo-located tweets, modeling and extracting Twitter user movements, generating space-time user trajectories, and summarizing multi-scale spatiotemporal user mobility patterns. We performed a set of statistical analysis to understand Twitter user mobility patterns across multi-level spatial scales and temporal ranges. In particular, Twitter user mobility patterns measured by the displacements and radius of gyrations of individuals revealed multi-scale or multi-modal Twitter user mobility patterns. By further studying such mobility patterns in different temporal ranges, we identified both consistency and seasonal fluctuations regarding the distance decay effects in the corresponding mobility patterns. At the same time, our approach provides a geo-visualization unit with an interactive 3D virtual globe web mapping interface for exploratory geo-visual analytics of the multi-level spatiotemporal Twitter user movements.

Spatial patterns of antimicrobial resistance genes in a cross-sectional sample of pig farms with indoor non-organic production of finishers

DEFF Research Database (Denmark)

Birkegård, Anna Camilla; Ersbøll, Annette Kjær; Hisham Beshara Halasa, Tariq

2017-01-01

Antimicrobial resistance (AMR) in pig populations is a public health concern. There is a lack of information of spatial distributions of AMR genes in pig populations at large scales. The objective of the study was to describe the spatial pattern of AMR genes in faecal samples from pig farms...... spatial clusters were identified for ermB, ermF, sulII and tet(W). The broad spatial trends in AMR resistance evident in the risk maps were in agreement with the results of the cluster analysis. However, they also showed that there were only small scale spatial differences in the gene levels. We conclude...

Soil respiration in Tibetan alpine grasslands: belowground biomass and soil moisture, but not soil temperature, best explain the large-scale patterns.

Directory of Open Access Journals (Sweden)

Yan Geng

Full Text Available The Tibetan Plateau is an essential area to study the potential feedback effects of soils to climate change due to the rapid rise in its air temperature in the past several decades and the large amounts of soil organic carbon (SOC stocks, particularly in the permafrost. Yet it is one of the most under-investigated regions in soil respiration (Rs studies. Here, Rs rates were measured at 42 sites in alpine grasslands (including alpine steppes and meadows along a transect across the Tibetan Plateau during the peak growing season of 2006 and 2007 in order to test whether: (1 belowground biomass (BGB is most closely related to spatial variation in Rs due to high root biomass density, and (2 soil temperature significantly influences spatial pattern of Rs owing to metabolic limitation from the low temperature in cold, high-altitude ecosystems. The average daily mean Rs of the alpine grasslands at peak growing season was 3.92 µmol CO(2 m(-2 s(-1, ranging from 0.39 to 12.88 µmol CO(2 m(-2 s(-1, with average daily mean Rs of 2.01 and 5.49 µmol CO(2 m(-2 s(-1 for steppes and meadows, respectively. By regression tree analysis, BGB, aboveground biomass (AGB, SOC, soil moisture (SM, and vegetation type were selected out of 15 variables examined, as the factors influencing large-scale variation in Rs. With a structural equation modelling approach, we found only BGB and SM had direct effects on Rs, while other factors indirectly affecting Rs through BGB or SM. Most (80% of the variation in Rs could be attributed to the difference in BGB among sites. BGB and SM together accounted for the majority (82% of spatial patterns of Rs. Our results only support the first hypothesis, suggesting that models incorporating BGB and SM can improve Rs estimation at regional scale.

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems.

Science.gov (United States)

Shen, Lili; Guo, Jiming; Wang, Lei

2018-06-06

The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC) approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC) according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS) data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

Measuring spatial patterns in floodplains: A step towards understanding the complexity of floodplain ecosystems: Chapter 6

Science.gov (United States)

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.; Gilvear, David J.; Greenwood, Malcolm T.; Thoms, Martin C.; Wood, Paul J.

2016-01-01

Floodplains can be viewed as complex adaptive systems (Levin, 1998) because they are comprised of many different biophysical components, such as morphological features, soil groups and vegetation communities as well as being sites of key biogeochemical processing (Stanford et al., 2005). Interactions and feedbacks among the biophysical components often result in additional phenomena occuring over a range of scales, often in the absence of any controlling factors (sensu Hallet, 1990). This emergence of new biophysical features and rates of processing can lead to alternative stable states which feed back into floodplain adaptive cycles (cf. Hughes, 1997; Stanford et al., 2005). Interactions between different biophysical components, feedbacks, self emergence and scale are all key properties of complex adaptive systems (Levin, 1998; Phillips, 2003; Murray et al., 2014) and therefore will influence the manner in which we study and view spatial patterns. Measuring the spatial patterns of floodplain biophysical components is a prerequisite to examining and understanding these ecosystems as complex adaptive systems. Elucidating relationships between pattern and process, which are intrinsically linked within floodplains (Ward et al., 2002), is dependent upon an understanding of spatial pattern. This knowledge can help river scientists determine the major drivers, controllers and responses of floodplain structure and function, as well as the consequences of altering those drivers and controllers (Hughes and Cass, 1997; Whited et al., 2007). Interactions and feedbacks between physical, chemical and biological components of floodplain ecosystems create and maintain a structurally diverse and dynamic template (Stanford et al., 2005). This template influences subsequent interactions between components that consequently affect system trajectories within floodplains (sensu Bak et al., 1988). Constructing and evaluating models used to predict floodplain ecosystem responses to

Large-scale Modeling of Nitrous Oxide Production: Issues of Representing Spatial Heterogeneity

Science.gov (United States)

Morris, C. K.; Knighton, J.

2017-12-01

Nitrous oxide is produced from the biological processes of nitrification and denitrification in terrestrial environments and contributes to the greenhouse effect that warms Earth's climate. Large scale modeling can be used to determine how global rate of nitrous oxide production and consumption will shift under future climates. However, accurate modeling of nitrification and denitrification is made difficult by highly parameterized, nonlinear equations. Here we show that the representation of spatial heterogeneity in inputs, specifically soil moisture, causes inaccuracies in estimating the average nitrous oxide production in soils. We demonstrate that when soil moisture is averaged from a spatially heterogeneous surface, net nitrous oxide production is under predicted. We apply this general result in a test of a widely-used global land surface model, the Community Land Model v4.5. The challenges presented by nonlinear controls on nitrous oxide are highlighted here to provide a wider context to the problem of extraordinary denitrification losses in CLM. We hope that these findings will inform future researchers on the possibilities for model improvement of the global nitrogen cycle.

Environmental controls on multiscale spatial patterns of salt marsh vegetation

DEFF Research Database (Denmark)

Kim, Daehyun; Cairns, David; Bartholdy, Jesper

2010-01-01

In coastal environments, biogeographic patterns are generally influenced by surface elevation and horizontal distance from sea water. However, it is still unclear whether these major topographic factors are significant controls of vegetation patterns across spatial scales at which different physi...

Spatial patterns and temporal dynamics of global scale climate-groundwater interactions

Science.gov (United States)

Cuthbert, M. O.; Gleeson, T. P.; Moosdorf, N.; Schneider, A. C.; Hartmann, J.; Befus, K. M.; Lehner, B.

2017-12-01

The interactions between groundwater and climate are important to resolve in both space and time as they influence mass and energy transfers at Earth's land surface. Despite the significance of these processes, little is known about the spatio-temporal distribution of such interactions globally, and many large-scale climate, hydrological and land surface models oversimplify groundwater or exclude it completely. In this study we bring together diverse global geomatic data sets to map spatial patterns in the sensitivity and degree of connectedness between the water table and the land surface, and use the output from a global groundwater model to assess the locations where the lateral import or export of groundwater is significant. We also quantify the groundwater response time, the characteristic time for groundwater systems to respond to a change in boundary conditions, and map its distribution globally to assess the likely dynamics of groundwater's interaction with climate. We find that more than half of the global land surface significantly exports or imports groundwater laterally. Nearly 40% of Earth's landmass has water tables that are strongly coupled to topography with water tables shallow enough to enable a bi-directional exchange of moisture with the climate system. However, only a small proportion (around 12%) of such regions have groundwater response times of 100 years or less and have groundwater fluxes that would significantly respond to rapid environmental changes over this timescale. We last explore fundamental relationships between aridity, groundwater response times and groundwater turnover times. Our results have wide ranging implications for understanding and modelling changes in Earth's water and energy balance and for informing robust future water management and security decisions.

The Relationship between Spatial and Temporal Magnitude Estimation of Scientific Concepts at Extreme Scales

Science.gov (United States)

Price, Aaron; Lee, H.

2010-01-01

Many astronomical objects, processes, and events exist and occur at extreme scales of spatial and temporal magnitudes. Our research draws upon the psychological literature, replete with evidence of linguistic and metaphorical links between the spatial and temporal domains, to compare how students estimate spatial and temporal magnitudes associated with objects and processes typically taught in science class.. We administered spatial and temporal scale estimation tests, with many astronomical items, to 417 students enrolled in 12 undergraduate science courses. Results show that while the temporal test was more difficult, students’ overall performance patterns between the two tests were mostly similar. However, asymmetrical correlations between the two tests indicate that students think of the extreme ranges of spatial and temporal scales in different ways, which is likely influenced by their classroom experience. When making incorrect estimations, students tended to underestimate the difference between the everyday scale and the extreme scales on both tests. This suggests the use of a common logarithmic mental number line for both spatial and temporal magnitude estimation. However, there are differences between the two tests in the errors student make in the everyday range. Among the implications discussed is the use of spatio-temporal reference frames, instead of smooth bootstrapping, to help students maneuver between scales of magnitude and the use of logarithmic transformations between reference frames. Implications for astronomy range from learning about spectra to large scale galaxy structure.

Spatial Scaling of Global Rainfall and Flood Extremes

Science.gov (United States)

Devineni, Naresh; Lall, Upmanu; Xi, Chen; Ward, Philip

2014-05-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration and spatial extent of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (up to 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances and floods. We present the first ever results on a global analysis of the scaling characteristics of extreme rainfall and flood event duration, volumes and contiguous flooded areas as a result of large scale organization of long duration rainfall events. Results are organized by latitude and with reference to the phases of ENSO, and reveal surprising invariance across latitude. Speculation as to the potential relation to the dynamical factors is presented

Spatial Patterns in Biofilm Diversity across Hierarchical Levels of River-Floodplain Landscapes.

Directory of Open Access Journals (Sweden)

Marc Peipoch

Full Text Available River-floodplain systems are among the most diverse and productive ecosystems, but the effects of biophysical complexity at multiple scales on microbial biodiversity have not been studied. Here, we investigated how the hierarchical organization of river systems (i.e., region, floodplain, zone, habitats, and microhabitats influences epilithic biofilm community assemblage patterns by characterizing microbial communities using 16S rRNA gene sequence data and analyzing bacterial species distribution across local and regional scales. Results indicate that regional and local environmental filters concurrently sort bacterial species, suggesting that spatial configuration of epilithic biofilms resembles patterns of larger organisms in floodplain ecosystems. Along the hierarchical organization of fluvial systems, floodplains constitute a vector of maximum environmental heterogeneity and consequently act as a major landscape filter for biofilm species. Thus, river basins and associated floodplains may simply reflect very large scale 'patches' within which environmental conditions select for community composition of epilithic biofilms.

Interspecific interference competition at the resource patch scale: do large herbivores spatially avoid elephants while accessing water?

Science.gov (United States)

Ferry, Nicolas; Dray, Stéphane; Fritz, Hervé; Valeix, Marion

2016-11-01

Animals may anticipate and try to avoid, at some costs, physical encounters with other competitors. This may ultimately impact their foraging distribution and intake rates. Such cryptic interference competition is difficult to measure in the field, and extremely little is known at the interspecific level. We tested the hypothesis that smaller species avoid larger ones because of potential costs of interference competition and hence expected them to segregate from larger competitors at the scale of a resource patch. We assessed fine-scale spatial segregation patterns between three African herbivore species (zebra Equus quagga, kudu Tragelaphus strepsiceros and giraffe Giraffa camelopardalis) and a megaherbivore, the African elephant Loxodonta africana, at the scale of water resource patches in the semi-arid ecosystem of Hwange National Park, Zimbabwe. Nine waterholes were monitored every two weeks during the dry season of a drought year, and observational scans of the spatial distribution of all herbivores were performed every 15 min. We developed a methodological approach to analyse such fine-scale spatial data. Elephants increasingly used waterholes as the dry season progressed, as did the probability of co-occurrence and agonistic interaction with elephants for the three study species. All three species segregated from elephants at the beginning of the dry season, suggesting a spatial avoidance of elephants and the existence of costs of being close to them. However, contrarily to our expectations, herbivores did not segregate from elephants the rest of the dry season but tended to increasingly aggregate with elephants as the dry season progressed. We discuss these surprising results and the existence of a trade-off between avoidance of interspecific interference competition and other potential factors such as access to quality water, which may have relative associated costs that change with the time of the year. © 2016 The Authors. Journal of Animal Ecology �

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems

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Lili Shen

2018-06-01

Full Text Available The network real-time kinematic (RTK technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI, and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs, robotic equipment, etc. require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

Voronoi tessellations and the cosmic web : Spatial patterns and clustering across the universe

NARCIS (Netherlands)

van de Weygaert, Rien; Gold, CM

2007-01-01

The spatial cosmic matter distribution on scales of a few up to more than a hundred Megaparsec(1) displays a salient and pervasive foamlike pattern. Voronoi tessellations are a versatile and flexible mathematical model for such weblike spatial patterns. They would be the natural result of an

Tidal-induced large-scale regular bed form patterns in a three-dimensional shallow water model

NARCIS (Netherlands)

Hulscher, Suzanne J.M.H.

1996-01-01

The three-dimensional model presented in this paper is used to study how tidal currents form wave-like bottom patterns. Inclusion of vertical flow structure turns out to be necessary to describe the formation, or absence, of all known large-scale regular bottom features. The tide and topography are

Large-Scale Patterns in a Minimal Cognitive Flocking Model: Incidental Leaders, Nematic Patterns, and Aggregates

Science.gov (United States)

Barberis, Lucas; Peruani, Fernando

2016-12-01

We study a minimal cognitive flocking model, which assumes that the moving entities navigate using the available instantaneous visual information exclusively. The model consists of active particles, with no memory, that interact by a short-ranged, position-based, attractive force, which acts inside a vision cone (VC), and lack velocity-velocity alignment. We show that this active system can exhibit—due to the VC that breaks Newton's third law—various complex, large-scale, self-organized patterns. Depending on parameter values, we observe the emergence of aggregates or millinglike patterns, the formation of moving—locally polar—files with particles at the front of these structures acting as effective leaders, and the self-organization of particles into macroscopic nematic structures leading to long-ranged nematic order. Combining simulations and nonlinear field equations, we show that position-based active models, as the one analyzed here, represent a new class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems. The reported results are of prime importance in the study, interpretation, and modeling of collective motion patterns in living and nonliving active systems.

First Mile Challenges for Large-Scale IoT

KAUST Repository

Bader, Ahmed; Elsawy, Hesham; Gharbieh, Mohammad; Alouini, Mohamed-Slim; Adinoyi, Abdulkareem; Alshaalan, Furaih

2017-01-01

The Internet of Things is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the sheer scale of spatial traffic intensity that must be accommodated, primarily in the uplink direction. To that end

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

Directory of Open Access Journals (Sweden)

G. Tang

2012-08-01

Full Text Available Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i modify a DGVM for simulating land surface water balances; (ii evaluate the modified model in simulating actual evapotranspiration (ET, soil moisture, and surface runoff at regional or watershed scales; and (iii gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ DGVM. To evaluate the model we ran LH using historical (1981–2006 climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981–2006 (R² > 0.46, p < 0.01; Nash-Sutcliffe Coefficient > 0.52. The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences < 15% with observed values for these rivers. Compared to a degree-day method for snowmelt computation, the addition of the solar radiation effect on snowmelt

Variation in the macrofaunal community over large temporal and spatial scales in the southern Yellow Sea

Science.gov (United States)

Xu, Yong; Sui, Jixing; Yang, Mei; Sun, Yue; Li, Xinzheng; Wang, Hongfa; Zhang, Baolin

2017-09-01

To detect large, temporal- and spatial-scale variations in the macrofaunal community in the southern Yellow Sea, data collected along the western, middle and eastern regions of the southern Yellow Sea from 1958 to 2014 were organized and analyzed. Statistical methods such as cluster analysis, non-metric multidimensional scaling ordination (nMDS), permutational multivariate analysis of variance (PERMANOVA), redundancy analysis (RDA) and canonical correspondence analysis (CCA) were applied. The abundance of polychaetes increased in the western region but decreased in the eastern region from 1958 to 2014, whereas the abundance of echinoderms showed an opposite trend. For the entire macrofaunal community, Margalef's richness (d), the Shannon-Wiener index (H‧) and Pielou's evenness (J‧) were significantly lower in the eastern region when compared with the other two regions. No significant temporal differences were found for d and H‧, but there were significantly lower values of J‧ in 2014. Considerable variation in the macrofaunal community structure over the past several decades and among the geographical regions at the species, genus and family levels were observed. The species, genera and families that contributed to the temporal variation in each region were also identified. The most conspicuous pattern was the increase in the species Ophiura sarsii vadicola in the eastern region. In the western region, five polychaetes (Ninoe palmata, Notomastus latericeus, Paralacydonia paradoxa, Paraprionospio pinnata and Sternaspis scutata) increased consistently from 1958 to 2014. The dominance curves showed that both the species diversity and the dominance patterns were relatively stable in the western and middle regions. Environmental parameters such as depth, temperature and salinity could only partially explain the observed biological variation in the southern Yellow Sea. Anthropogenic activities such as demersal fishing and other unmeasured environmental variables

SPATIALLY RESOLVED GAS KINEMATICS WITHIN A Lyα NEBULA: EVIDENCE FOR LARGE-SCALE ROTATION

Energy Technology Data Exchange (ETDEWEB)

Prescott, Moire K. M. [Dark Cosmology Centre, Niels Bohr Institute, University of Copenhagen, Juliane Maries Vej 30, DK-2100 Copenhagen (Denmark); Martin, Crystal L. [Department of Physics, Broida Hall, Mail Code 9530, University of California, Santa Barbara, CA 93106 (United States); Dey, Arjun, E-mail: mkmprescott@dark-cosmology.dk [National Optical Astronomy Observatory, 950 North Cherry Avenue, Tucson, AZ 85719 (United States)

2015-01-20

We use spatially extended measurements of Lyα as well as less optically thick emission lines from an ≈80 kpc Lyα nebula at z ≈ 1.67 to assess the role of resonant scattering and to disentangle kinematic signatures from Lyα radiative transfer effects. We find that the Lyα, C IV, He II, and C III] emission lines all tell a similar story in this system, and that the kinematics are broadly consistent with large-scale rotation. First, the observed surface brightness profiles are similar in extent in all four lines, strongly favoring a picture in which the Lyα photons are produced in situ instead of being resonantly scattered from a central source. Second, we see low kinematic offsets between Lyα and the less optically thick He II line (∼100-200 km s{sup –1}), providing further support for the argument that the Lyα and other emission lines are all being produced within the spatially extended gas. Finally, the full velocity field of the system shows coherent velocity shear in all emission lines: ≈500 km s{sup –1} over the central ≈50 kpc of the nebula. The kinematic profiles are broadly consistent with large-scale rotation in a gas disk that is at least partially stable against collapse. These observations suggest that the Lyα nebula represents accreting material that is illuminated by an offset, hidden active galactic nucleus or distributed star formation, and that is undergoing rotation in a clumpy and turbulent gas disk. With an implied mass of M(large Milky Way mass galaxy or galaxy group.

Growth of wrinkle-free graphene on texture-controlled platinum films and thermal-assisted transfer of large-scale patterned graphene.

Science.gov (United States)

Choi, Jae-Kyung; Kwak, Jinsung; Park, Soon-Dong; Yun, Hyung Duk; Kim, Se-Yang; Jung, Minbok; Kim, Sung Youb; Park, Kibog; Kang, Seoktae; Kim, Sung-Dae; Park, Dong-Yeon; Lee, Dong-Su; Hong, Suk-Kyoung; Shin, Hyung-Joon; Kwon, Soon-Yong

2015-01-27

Growth of large-scale patterned, wrinkle-free graphene and the gentle transfer technique without further damage are most important requirements for the practical use of graphene. Here we report the growth of wrinkle-free, strictly uniform monolayer graphene films by chemical vapor deposition on a platinum (Pt) substrate with texture-controlled giant grains and the thermal-assisted transfer of large-scale patterned graphene onto arbitrary substrates. The designed Pt surfaces with limited numbers of grain boundaries and improved surface perfectness as well as small thermal expansion coefficient difference to graphene provide a venue for uniform growth of monolayer graphene with wrinkle-free characteristic. The thermal-assisted transfer technique allows the complete transfer of large-scale patterned graphene films onto arbitrary substrates without any ripples, tears, or folds. The transferred graphene shows high crystalline quality with an average carrier mobility of ∼ 5500 cm(2) V(-1) s(-1) at room temperature. Furthermore, this transfer technique shows a high tolerance to variations in types and morphologies of underlying substrates.

Response of spatial point pattern of halostachys caspica population to ground water depth

International Nuclear Information System (INIS)

Niu, P.; Wang, M.; Jiang, P.; Li, M.; Chu, G.

2017-01-01

We subjected Halostachys caspica populations to three groundwater depths: shallow ( 4.5 m) in the sample plots, at the diluvial fan of the South Junggar Basin. Both the spatial pattern and spatial association of the population among all three groundwater depths and four growth stages were studied to investigate the impact of groundwater depth on the formation and persistence mechanism of the spatial pattern of Halostachys caspica populations. In this study, Ripley's K function was utilized to characterize spatial patterns and intraspecific associations of H. caspica in three 1-ha plots, as well as to study their relationship with groundwater depth. The seedling supplement severely decreased with increasing groundwater depth, and the population structure changed noticeably due to increased amount of dead standing plants. Different growth stages of the H. caspica population all had aggregated distributions at small scale in the three groundwater depth areas. With increasing scales, the aggregation intensity weakened in all growth stages. Distribution was aggregated at 50 m scales in both the shallow and middle groundwater depth areas, while the deep groundwater depth area followed a random distribution. (author)

Large-Scale Pattern Discovery in Music

Science.gov (United States)

Bertin-Mahieux, Thierry

This work focuses on extracting patterns in musical data from very large collections. The problem is split in two parts. First, we build such a large collection, the Million Song Dataset, to provide researchers access to commercial-size datasets. Second, we use this collection to study cover song recognition which involves finding harmonic patterns from audio features. Regarding the Million Song Dataset, we detail how we built the original collection from an online API, and how we encouraged other organizations to participate in the project. The result is the largest research dataset with heterogeneous sources of data available to music technology researchers. We demonstrate some of its potential and discuss the impact it already has on the field. On cover song recognition, we must revisit the existing literature since there are no publicly available results on a dataset of more than a few thousand entries. We present two solutions to tackle the problem, one using a hashing method, and one using a higher-level feature computed from the chromagram (dubbed the 2DFTM). We further investigate the 2DFTM since it has potential to be a relevant representation for any task involving audio harmonic content. Finally, we discuss the future of the dataset and the hope of seeing more work making use of the different sources of data that are linked in the Million Song Dataset. Regarding cover songs, we explain how this might be a first step towards defining a harmonic manifold of music, a space where harmonic similarities between songs would be more apparent.

Regular pattern formation in real ecosystems

NARCIS (Netherlands)

Rietkerk, Max; Koppel, Johan van de

2008-01-01

Localized ecological interactions can generate striking large-scale spatial patterns in ecosystems through spatial self-organization. Possible mechanisms include oscillating consumer–resource interactions, localized disturbance-recovery processes and scale-dependent feedback. Despite abundant

Spatially explicit shallow landslide susceptibility mapping over large areas

Science.gov (United States)

Bellugi, Dino; Dietrich, William E.; Stock, Jonathan D.; McKean, Jim; Kazian, Brian; Hargrove, Paul

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.

Abiotic and biotic controls of spatial pattern at alpine treeline

Science.gov (United States)

Malanson, George P.; Xiao, Ningchuan; Alftine, K.J.; Bekker, Mathew; Butler, David R.; Brown, Daniel G.; Cairns, David M.; Fagre, Daniel; Walsh, Stephen J.

2000-01-01

At alpine treeline, trees and krummholz forms affect the environment in ways that increase their growth and reproduction. We assess the way in which these positive feedbacks combine in spatial patterns to alter the environment in the neighborhood of existing plants. The research is significant because areas of alpine tundra are susceptible to encroachment by woody species as climate changes. Moreover, understanding the general processes of plant invasion is important. The importance of spatial pattern has been recognized, but the spatial pattern of positive feedbacks per se has not been explored in depth. We present a linked set of models of vegetation change at an alpine forest-tundra ecotone. Our aim is to create models that are as simple as possible in order to test specific hypotheses. We present results from a model of the resource averaging hypothesis and the positive feedback switch hypothesis of treelines. We compare the patterns generated by the models to patterns observed in fine scale remotely sensed data.

Quantifying spatial scaling patterns and their local and regional correlates in headwater streams: Implications for resilience

Science.gov (United States)

Gothe, Emma; Sandin, Leonard; Allen, Craig R.; Angeler, David G.

2014-01-01

The distribution of functional traits within and across spatiotemporal scales has been used to quantify and infer the relative resilience across ecosystems. We use explicit spatial modeling to evaluate within- and cross-scale redundancy in headwater streams, an ecosystem type with a hierarchical and dendritic network structure. We assessed the cross-scale distribution of functional feeding groups of benthic invertebrates in Swedish headwater streams during two seasons. We evaluated functional metrics, i.e., Shannon diversity, richness, and evenness, and the degree of redundancy within and across modeled spatial scales for individual feeding groups. We also estimated the correlates of environmental versus spatial factors of both functional composition and the taxonomic composition of functional groups for each spatial scale identified. Measures of functional diversity and within-scale redundancy of functions were similar during both seasons, but both within- and cross-scale redundancy were low. This apparent low redundancy was partly attributable to a few dominant taxa explaining the spatial models. However, rare taxa with stochastic spatial distributions might provide additional information and should therefore be considered explicitly for complementing future resilience assessments. Otherwise, resilience may be underestimated. Finally, both environmental and spatial factors correlated with the scale-specific functional and taxonomic composition. This finding suggests that resilience in stream networks emerges as a function of not only local conditions but also regional factors such as habitat connectivity and invertebrate dispersal.

Shifting patterns of Aedes aegypti fine scale spatial clustering in Iquitos, Peru.

Science.gov (United States)

LaCon, Genevieve; Morrison, Amy C; Astete, Helvio; Stoddard, Steven T; Paz-Soldan, Valerie A; Elder, John P; Halsey, Eric S; Scott, Thomas W; Kitron, Uriel; Vazquez-Prokopec, Gonzalo M

2014-08-01

Empiric evidence shows that Aedes aegypti abundance is spatially heterogeneous and that some areas and larval habitats produce more mosquitoes than others. There is a knowledge gap, however, with regards to the temporal persistence of such Ae. aegypti abundance hotspots. In this study, we used a longitudinal entomologic dataset from the city of Iquitos, Peru, to (1) quantify the spatial clustering patterns of adult Ae. aegypti and pupae counts per house, (2) determine overlap between clusters, (3) quantify the temporal stability of clusters over nine entomologic surveys spaced four months apart, and (4) quantify the extent of clustering at the household and neighborhood levels. Data from 13,662 household entomological visits performed in two Iquitos neighborhoods differing in Ae. aegypti abundance and dengue virus transmission was analyzed using global and local spatial statistics. The location and extent of Ae. aegypti pupae and adult hotspots (i.e., small groups of houses with significantly [pentomologic surveys. The extent of clustering was used to quantify the probability of finding spatially correlated populations. Our analyses indicate that Ae. aegypti distribution was highly focal (most clusters do not extend beyond 30 meters) and that hotspots of high vector abundance were common on every survey date, but they were temporally unstable over the period of study. Our findings have implications for understanding Ae. aegypti distribution and for the design of surveillance and control activities relying on household-level data. In settings like Iquitos, where there is a relatively low percentage of Ae. aegypti in permanent water-holding containers, identifying and targeting key premises will be significantly challenged by shifting hotspots of Ae. aegypti infestation. Focusing efforts in large geographic areas with historically high levels of transmission may be more effective than targeting Ae. aegypti hotspots.

Shifting patterns of Aedes aegypti fine scale spatial clustering in Iquitos, Peru.

Directory of Open Access Journals (Sweden)

Genevieve LaCon

2014-08-01

Full Text Available Empiric evidence shows that Aedes aegypti abundance is spatially heterogeneous and that some areas and larval habitats produce more mosquitoes than others. There is a knowledge gap, however, with regards to the temporal persistence of such Ae. aegypti abundance hotspots. In this study, we used a longitudinal entomologic dataset from the city of Iquitos, Peru, to (1 quantify the spatial clustering patterns of adult Ae. aegypti and pupae counts per house, (2 determine overlap between clusters, (3 quantify the temporal stability of clusters over nine entomologic surveys spaced four months apart, and (4 quantify the extent of clustering at the household and neighborhood levels.Data from 13,662 household entomological visits performed in two Iquitos neighborhoods differing in Ae. aegypti abundance and dengue virus transmission was analyzed using global and local spatial statistics. The location and extent of Ae. aegypti pupae and adult hotspots (i.e., small groups of houses with significantly [p<0.05] high mosquito abundance were calculated for each of the 9 entomologic surveys. The extent of clustering was used to quantify the probability of finding spatially correlated populations. Our analyses indicate that Ae. aegypti distribution was highly focal (most clusters do not extend beyond 30 meters and that hotspots of high vector abundance were common on every survey date, but they were temporally unstable over the period of study.Our findings have implications for understanding Ae. aegypti distribution and for the design of surveillance and control activities relying on household-level data. In settings like Iquitos, where there is a relatively low percentage of Ae. aegypti in permanent water-holding containers, identifying and targeting key premises will be significantly challenged by shifting hotspots of Ae. aegypti infestation. Focusing efforts in large geographic areas with historically high levels of transmission may be more effective than

Topographically Engineered Large Scale Nanostructures for Plasmonic Biosensing

Science.gov (United States)

Xiao, Bo; Pradhan, Sangram K.; Santiago, Kevin C.; Rutherford, Gugu N.; Pradhan, Aswini K.

2016-04-01

We demonstrate that a nanostructured metal thin film can achieve enhanced transmission efficiency and sharp resonances and use a large-scale and high-throughput nanofabrication technique for the plasmonic structures. The fabrication technique combines the features of nanoimprint and soft lithography to topographically construct metal thin films with nanoscale patterns. Metal nanogratings developed using this method show significantly enhanced optical transmission (up to a one-order-of-magnitude enhancement) and sharp resonances with full width at half maximum (FWHM) of ~15nm in the zero-order transmission using an incoherent white light source. These nanostructures are sensitive to the surrounding environment, and the resonance can shift as the refractive index changes. We derive an analytical method using a spatial Fourier transformation to understand the enhancement phenomenon and the sensing mechanism. The use of real-time monitoring of protein-protein interactions in microfluidic cells integrated with these nanostructures is demonstrated to be effective for biosensing. The perpendicular transmission configuration and large-scale structures provide a feasible platform without sophisticated optical instrumentation to realize label-free surface plasmon resonance (SPR) sensing.

Detecting the Land-Cover Changes Induced by Large-Physical Disturbances Using Landscape Metrics, Spatial Sampling, Simulation and Spatial Analysis

Directory of Open Access Journals (Sweden)

Hone-Jay Chu

2009-08-01

Full Text Available The objectives of the study are to integrate the conditional Latin Hypercube Sampling (cLHS, sequential Gaussian simulation (SGS and spatial analysis in remotely sensed images, to monitor the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial heterogeneity and variability. The multiple NDVI images demonstrate that spatial patterns of disturbed landscapes were successfully delineated by spatial analysis such as variogram, Moran’I and landscape metrics in the study area. The hybrid method delineates the spatial patterns and spatial variability of landscapes caused by these large disturbances. The cLHS approach is applied to select samples from Normalized Difference Vegetation Index (NDVI images from SPOT HRV images in the Chenyulan watershed of Taiwan, and then SGS with sufficient samples is used to generate maps of NDVI images. In final, the NDVI simulated maps are verified using indexes such as the correlation coefficient and mean absolute error (MAE. Therefore, the statistics and spatial structures of multiple NDVI images present a very robust behavior, which advocates the use of the index for the quantification of the landscape spatial patterns and land cover change. In addition, the results transferred by Open Geospatial techniques can be accessed from web-based and end-user applications of the watershed management.

Environmental Impacts of Large Scale Biochar Application Through Spatial Modeling

Science.gov (United States)

Huber, I.; Archontoulis, S.

2017-12-01

In an effort to study the environmental (emissions, soil quality) and production (yield) impacts of biochar application at regional scales we coupled the APSIM-Biochar model with the pSIMS parallel platform. So far the majority of biochar research has been concentrated on lab to field studies to advance scientific knowledge. Regional scale assessments are highly needed to assist decision making. The overall objective of this simulation study was to identify areas in the USA that have the most gain environmentally from biochar's application, as well as areas which our model predicts a notable yield increase due to the addition of biochar. We present the modifications in both APSIM biochar and pSIMS components that were necessary to facilitate these large scale model runs across several regions in the United States at a resolution of 5 arcminutes. This study uses the AgMERRA global climate data set (1980-2010) and the Global Soil Dataset for Earth Systems modeling as a basis for creating its simulations, as well as local management operations for maize and soybean cropping systems and different biochar application rates. The regional scale simulation analysis is in progress. Preliminary results showed that the model predicts that high quality soils (particularly those common to Iowa cropping systems) do not receive much, if any, production benefit from biochar. However, soils with low soil organic matter ( 0.5%) do get a noteworthy yield increase of around 5-10% in the best cases. We also found N2O emissions to be spatial and temporal specific; increase in some areas and decrease in some other areas due to biochar application. In contrast, we found increases in soil organic carbon and plant available water in all soils (top 30 cm) due to biochar application. The magnitude of these increases (% change from the control) were larger in soil with low organic matter (below 1.5%) and smaller in soils with high organic matter (above 3%) and also dependent on biochar

Quantifying spatial scaling patterns and their local and regional correlates in headwater streams: implications for resilience

Directory of Open Access Journals (Sweden)

Emma Göthe

2014-09-01

Full Text Available The distribution of functional traits within and across spatiotemporal scales has been used to quantify and infer the relative resilience across ecosystems. We use explicit spatial modeling to evaluate within- and cross-scale redundancy in headwater streams, an ecosystem type with a hierarchical and dendritic network structure. We assessed the cross-scale distribution of functional feeding groups of benthic invertebrates in Swedish headwater streams during two seasons. We evaluated functional metrics, i.e., Shannon diversity, richness, and evenness, and the degree of redundancy within and across modeled spatial scales for individual feeding groups. We also estimated the correlates of environmental versus spatial factors of both functional composition and the taxonomic composition of functional groups for each spatial scale identified. Measures of functional diversity and within-scale redundancy of functions were similar during both seasons, but both within- and cross-scale redundancy were low. This apparent low redundancy was partly attributable to a few dominant taxa explaining the spatial models. However, rare taxa with stochastic spatial distributions might provide additional information and should therefore be considered explicitly for complementing future resilience assessments. Otherwise, resilience may be underestimated. Finally, both environmental and spatial factors correlated with the scale-specific functional and taxonomic composition. This finding suggests that resilience in stream networks emerges as a function of not only local conditions but also regional factors such as habitat connectivity and invertebrate dispersal.

Continental-scale patterns of canopy tree composition and function across Amazonia

Science.gov (United States)

Ter Steege, Hans; Pitman, Nigel C. A.; Phillips, Oliver L.; Chave, Jerome; Sabatier, Daniel; Duque, Alvaro; Molino, Jean-François; Prévost, Marie-Françoise; Spichiger, Rodolphe; Castellanos, Hernán; von Hildebrand, Patricio; Vásquez, Rodolfo

2006-09-01

The world's greatest terrestrial stores of biodiversity and carbon are found in the forests of northern South America, where large-scale biogeographic patterns and processes have recently begun to be described. Seven of the nine countries with territory in the Amazon basin and the Guiana shield have carried out large-scale forest inventories, but such massive data sets have been little exploited by tropical plant ecologists. Although forest inventories often lack the species-level identifications favoured by tropical plant ecologists, their consistency of measurement and vast spatial coverage make them ideally suited for numerical analyses at large scales, and a valuable resource to describe the still poorly understood spatial variation of biomass, diversity, community composition and forest functioning across the South American tropics. Here we show, by using the seven forest inventories complemented with trait and inventory data collected elsewhere, two dominant gradients in tree composition and function across the Amazon, one paralleling a major gradient in soil fertility and the other paralleling a gradient in dry season length. The data set also indicates that the dominance of Fabaceae in the Guiana shield is not necessarily the result of root adaptations to poor soils (nodulation or ectomycorrhizal associations) but perhaps also the result of their remarkably high seed mass there as a potential adaptation to low rates of disturbance.

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

Science.gov (United States)

Gong, L.; Halldin, S.; Xu, C.-Y.

2011-08-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the

Spatial extreme value analysis to project extremes of large-scale indicators for severe weather.

Science.gov (United States)

Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

2013-09-01

Concurrently high values of the maximum potential wind speed of updrafts ( W max ) and 0-6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd.

Understanding relationships among ecosystem services across spatial scales and over time

Science.gov (United States)

Qiu, Jiangxiao; Carpenter, Stephen R.; Booth, Eric G.; Motew, Melissa; Zipper, Samuel C.; Kucharik, Christopher J.; Loheide, Steven P., II; Turner, Monica G.

2018-05-01

Sustaining ecosystem services (ES), mitigating their tradeoffs and avoiding unfavorable future trajectories are pressing social-environmental challenges that require enhanced understanding of their relationships across scales. Current knowledge of ES relationships is often constrained to one spatial scale or one snapshot in time. In this research, we integrated biophysical modeling with future scenarios to examine changes in relationships among eight ES indicators from 2001–2070 across three spatial scales—grid cell, subwatershed, and watershed. We focused on the Yahara Watershed (Wisconsin) in the Midwestern United States—an exemplar for many urbanizing agricultural landscapes. Relationships among ES indicators changed over time; some relationships exhibited high interannual variations (e.g. drainage vs. food production, nitrate leaching vs. net ecosystem exchange) and even reversed signs over time (e.g. perennial grass production vs. phosphorus yield). Robust patterns were detected for relationships among some regulating services (e.g. soil retention vs. water quality) across three spatial scales, but other relationships lacked simple scaling rules. This was especially true for relationships of food production vs. water quality, and drainage vs. number of days with runoff >10 mm, which differed substantially across spatial scales. Our results also showed that local tradeoffs between food production and water quality do not necessarily scale up, so reducing local tradeoffs may be insufficient to mitigate such tradeoffs at the watershed scale. We further synthesized these cross-scale patterns into a typology of factors that could drive changes in ES relationships across scales: (1) effects of biophysical connections, (2) effects of dominant drivers, (3) combined effects of biophysical linkages and dominant drivers, and (4) artificial scale effects, and concluded with management implications. Our study highlights the importance of taking a dynamic

The impact of large-scale circulation patterns on summer crop yields in IP

Science.gov (United States)

Capa Morocho, Mirian; Rodríguez Fonseca, Belén; Ruiz Ramos, Margarita

2014-05-01

Large-scale circulations patterns (ENSO, NAO) have been shown to have a significant impact on seasonal weather, and therefore on crop yield over many parts of the world(Garnett and Khandekar, 1992; Aasa et al., 2004; Rozas and Garcia-Gonzalez, 2012). In this study, we analyze the influence of large-scale circulation patterns and regional climate on the principal components of maize yield variability in Iberian Peninsula (IP) using reanalysis datasets. Additionally, we investigate the modulation of these relationships by multidecadal patterns. This study is performed analyzing long time series of maize yield, only climate dependent, computed with the crop model CERES-maize (Jones and Kiniry, 1986) included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5). To simulate yields, reanalysis daily data of radiation, maximum and minimum temperature and precipitation were used. The reanalysis climate data were obtained from National Center for Environmental Prediction (20th Century and NCEP) and European Centre for Medium-Range Weather Forecasts (ECMWF) data server (ERA 40 and ERA Interim). Simulations were run at five locations: Lugo (northwestern), Lerida (NE), Madrid (central), Albacete (southeastern) and Córdoba (S IP) (Gabaldón et al., 2013). From these time series standardized anomalies were calculated. Afterwards, time series were time filtered to focus on the interannual-to-multiannual variability, splitting up in two components: low frequency (LF) and high frequency (HF) time scales. The principal components of HF yield anomalies in IP were compared with a set of documented patterns. These relationships were compared with multidecadal patterns, as Atlanctic Multidecadal Oscillations (AMO) and Interdecadal Pacific Oscillations (IPO). The results of this study have important implications in crop forecasting. In this way, it may have a positive impact on both public (agricultural planning) and private (decision support to farmers, insurance

Complex modular structure of large-scale brain networks

Science.gov (United States)

Valencia, M.; Pastor, M. A.; Fernández-Seara, M. A.; Artieda, J.; Martinerie, J.; Chavez, M.

2009-06-01

Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large scale (voxel level) extracted from functional magnetic resonance imaging signals. By using a random-walk-based method, we unveil the modularity of brain webs and show modules with a spatial distribution that matches anatomical structures with functional significance. The functional role of each node in the network is studied by analyzing its patterns of inter- and intramodular connections. Results suggest that the modular architecture constitutes the structural basis for the coexistence of functional integration of distant and specialized brain areas during normal brain activities at rest.

What spatial scales are believable for climate model projections of sea surface temperature?

Science.gov (United States)

Kwiatkowski, Lester; Halloran, Paul R.; Mumby, Peter J.; Stephenson, David B.

2014-09-01

Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (coral bleaching frequency and other marine processes linked to SST warming.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

OpenAIRE

D. C. Verdon-Kidd; A. S. Kiem

2009-01-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a cl...

Large-scale double-patterning compliant layouts for DP engine and design rule development

Science.gov (United States)

Cork, Christopher; Lucas, Kevin; Hapli, John; Raffard, Herve; Barnes, Levi

2009-03-01

Double Patterning is seen as the prime technology to keep Moore's law on path while EUV technology is still maturing into production worthiness. As previously seen for alternating-Phase Shift Mask technology[1], layout compliance of double patterning is not trivial [2,3] and blind shrinks of anything but the most simplistic existing layouts, will not be directly suitable for double patterning. Evaluating a production worthy double patterning engine with highly non-compliant layouts would put unrealistic expectations on that engine and provide metrics with poor applicability for eventual large designs. The true production use-case would be for designs that have at least some significant double patterning compliance already enforced at the design stage. With this in mind a set of ASIC design blocks of different sizes and complexities were created that were double patterning compliant. To achieve this, a set of standard cells were generated, which individually and in isolation were double patterning compliant, for multiple layers simultaneously. This was done using the automated Standard Cell creation tool CadabraTM [4]. To create a full ASIC, however, additional constraints were added to make sure compliance would not be broken across the boundaries between standard cells when placed next to each other [5]. These standard cells were then used to create a variety of double patterning compliant ASICs using iCCompilerTM to place the cells correctly. Now with a compliant layout, checks were made to see if the constraints made at the micro level really do ensure a fully compliant layout on the whole chip and if the coloring engine could cope with such large datasets. A production worthy double patterning engine is ideally distributable over multiple processors [6,7] so that fast turn-around time can be achievable on even the largest designs. We demonstrate the degree of linearity of scaling achievable with our double patterning engine. These results can be understood

The Influence of Large-scale Bank Roughness and Floodplain Composition on Spatial and Temporal Variations in Bank Erosion

Science.gov (United States)

Hackney, C. R.; Darby, S. E.; Leyland, J.; Aalto, R. E.; Best, J.; Parsons, D. R.; Nicholas, A. P.

2016-12-01

Knowledge of bank erosion processes and rates along the world's largest rivers remains incomplete, primarily due to the difficulties of obtaining data pertaining to the key driving processes (i.e., during the floods that drive most bank retreat). Recently, larger scale bank roughness elements (slump blocks and embayments) have been shown to impact upon rates and locations of bank erosion. However, a complete understanding of the way such features affect rates of bank erosion is currently hindered by the lack of detailed concurrent observations of slump block geometry, embayment geometry and flow at formative discharges in natural environments. Here, we report on high spatial resolution topographic (Terrestrial Laser Scanner and Multibeam Echo Souder) and flow (Acoustic Doppler Current Profiler) surveys undertaken on the Mekong River, Cambodia, from which we extract the geometric properties of roughness elements across a range of scales. We combine this data with sub-bottom profile data, revealing the composition of the surrounding floodplain, to link, for the first time, scales of bank roughness to bank material composition. Through the categorisation of a series of cut river banks by roughness geometry, we show how rates and locations of bank erosion are dependent on that roughness and associated bank material changes. We test how observed patterns of bank erosion conform to previously detailed models of embayment development, and provide new insight into processes affecting the retreat of large river banks.

Upscaling of Large-Scale Transport in Spatially Heterogeneous Porous Media Using Wavelet Transformation

Science.gov (United States)

Moslehi, M.; de Barros, F.; Ebrahimi, F.; Sahimi, M.

2015-12-01

Modeling flow and solute transport in large-scale heterogeneous porous media involves substantial computational burdens. A common approach to alleviate this complexity is to utilize upscaling methods. These processes generate upscaled models with less complexity while attempting to preserve the hydrogeological properties comparable to the original fine-scale model. We use Wavelet Transformations (WT) of the spatial distribution of aquifer's property to upscale the hydrogeological models and consequently transport processes. In particular, we apply the technique to a porous formation with broadly distributed and correlated transmissivity to verify the performance of the WT. First, transmissivity fields are coarsened using WT in such a way that the high transmissivity zones, in which more important information is embedded, mostly remain the same, while the low transmissivity zones are averaged out since they contain less information about the hydrogeological formation. Next, flow and non-reactive transport are simulated in both fine-scale and upscaled models to predict both the concentration breakthrough curves at a control location and the large-scale spreading of the plume around its centroid. The results reveal that the WT of the fields generates non-uniform grids with an average of 2.1% of the number of grid blocks in the original fine-scale models, which eventually leads to a significant reduction in the computational costs. We show that the upscaled model obtained through the WT reconstructs the concentration breakthrough curves and the spreading of the plume at different times accurately. Furthermore, the impacts of the Hurst coefficient, size of the flow domain and the orders of magnitude difference in transmissivity values on the results have been investigated. It is observed that as the heterogeneity and the size of the domain increase, better agreement between the results of fine-scale and upscaled models can be achieved. Having this framework at hand aids

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity.

Science.gov (United States)

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others' facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition.

Emerging spatial patterns in Antarctic prokaryotes.

Science.gov (United States)

Chong, Chun-Wie; Pearce, David A; Convey, Peter

2015-01-01

. Based on our synthesis, it is clear that spatial patterns of Antarctic prokaryotes can be unique at local scales, while the limited evidence available to date supports the group exhibiting overall regional biogeographical patterns similar to the eukaryotes. We further consider the applicability of the concept of "functional redundancy" for the Antarctic microbial community and highlight the requirements for proper consideration of their important and distinctive roles in Antarctic terrestrial ecosystems.

Large-scale derived flood frequency analysis based on continuous simulation

Science.gov (United States)

Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several

Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

Science.gov (United States)

Kashid, Satishkumar S.; Maity, Rajib

2012-08-01

SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different

Effects of local and large-scale climate patterns on estuarine resident fishes: The example of Pomatoschistus microps and Pomatoschistus minutus

Science.gov (United States)

Nyitrai, Daniel; Martinho, Filipe; Dolbeth, Marina; Rito, João; Pardal, Miguel A.

2013-12-01

Large-scale and local climate patterns are known to influence several aspects of the life cycle of marine fish. In this paper, we used a 9-year database (2003-2011) to analyse the populations of two estuarine resident fishes, Pomatoschistus microps and Pomatoschistus minutus, in order to determine their relationships with varying environmental stressors operating over local and large scales. This study was performed in the Mondego estuary, Portugal. Firstly, the variations in abundance, growth, population structure and secondary production were evaluated. These species appeared in high densities in the beginning of the study period, with subsequent occasional high annual density peaks, while their secondary production was lower in dry years. The relationships between yearly fish abundance and the environmental variables were evaluated separately for both species using Spearman correlation analysis, considering the yearly abundance peaks for the whole population, juveniles and adults. Among the local climate patterns, precipitation, river runoff, salinity and temperature were used in the analyses, and North Atlantic Oscillation (NAO) index and sea surface temperature (SST) were tested as large-scale factors. For P. microps, precipitation and NAO were the significant factors explaining abundance of the whole population, the adults and the juveniles as well. Regarding P. minutus, for the whole population, juveniles and adults river runoff was the significant predictor. The results for both species suggest a differential influence of climate patterns on the various life cycle stages, confirming also the importance of estuarine resident fishes as indicators of changes in local and large-scale climate patterns, related to global climate change.

Patterns of disturbance at multiple scales in real and simulated landscapes

Science.gov (United States)

Giovanni Zurlini; Kurt H. Riitters; Nicola Zaccarelli; Irene Petrosoillo

2007-01-01

We describe a framework to characterize and interpret the spatial patterns of disturbances at multiple scales in socio-ecological systems. Domains of scale are defined in pattern metric space and mapped in geographic space, which can help to understand how anthropogenic disturbances might impact biodiversity through habitat modification. The approach identifies typical...

Using landscape ecology to test hypotheses about large-scale abundance patterns in migratory birds

Science.gov (United States)

Flather, C.H.; Sauer, J.R.

1996-01-01

The hypothesis that Neotropical migrant birds may be undergoing widespread declines due to land use activities on the breeding grounds has been examined primarily by synthesizing results from local studies. Growing concern for the cumulative influence of land use activities on ecological systems has heightened the need for large-scale studies to complement what has been observed at local scales. We investigated possible landscape effects on Neotropical migrant bird populations for the eastern United States by linking two large-scale inventories designed to monitor breeding-bird abundances and land use patterns. The null hypothesis of no relation between landscape structure and Neotropical migrant abundance was tested by correlating measures of landscape structure with bird abundance, while controlling for the geographic distance among samples. Neotropical migrants as a group were more 'sensitive' to landscape structure than either temperate migrants or permanent residents. Neotropical migrants tended to be more abundant in landscapes with a greater proportion of forest and wetland habitats, fewer edge habitats, large forest patches, and with forest habitats well dispersed throughout the scene. Permanent residents showed few correlations with landscape structure and temperate migrants were associated with habitat diversity and edge attributes rather than with the amount, size, and dispersion of forest habitats. The association between Neotropical migrant abundance and forest fragmentation differed among physiographic strata, suggesting that land-scape context affects observed relations between bird abundance and landscape structure. Finally, associations between landscape structure and temporal trends in Neotropical migrant abundance were negatively correlated with forest habitats. These results suggest that extrapolation of patterns observed in some landscapes is not likely to hold regionally, and that conservation policies must consider the variation in landscape

Regime Behavior in Paleo-Reconstructed Streamflow: Attributions to Atmospheric Dynamics, Synoptic Circulation and Large-Scale Climate Teleconnection Patterns

Science.gov (United States)

Ravindranath, A.; Devineni, N.

2017-12-01

Studies have shown that streamflow behavior and dynamics have a significant link with climate and climate variability. Patterns of persistent regime behavior from extended streamflow records in many watersheds justify investigating large-scale climate mechanisms as potential drivers of hydrologic regime behavior and streamflow variability. Understanding such streamflow-climate relationships is crucial to forecasting/simulation systems and the planning and management of water resources. In this study, hidden Markov models are used with reconstructed streamflow to detect regime-like behaviors - the hidden states - and state transition phenomena. Individual extreme events and their spatial variability across the basin are then verified with the identified states. Wavelet analysis is performed to examine the signals over time in the streamflow records. Joint analyses of the climatic data in the 20th century and the identified states are undertaken to better understand the hydroclimatic connections within the basin as well as important teleconnections that influence water supply. Compositing techniques are used to identify atmospheric circulation patterns associated with identified states of streamflow. The grouping of such synoptic patterns and their frequency are then examined. Sliding time-window correlation analysis and cross-wavelet spectral analysis are performed to establish the synchronicity of basin flows to the identified synoptic and teleconnection patterns. The Missouri River Basin (MRB) is examined in this study, both as a means of better understanding the synoptic climate controls in this important watershed and as a case study for the techniques developed here. Initial wavelet analyses of reconstructed streamflow at major gauges in the MRB show multidecadal cycles in regime behavior.

Continental-scale patterns of Cecropia reproductive phenology: evidence from herbarium specimens.

Science.gov (United States)

Zalamea, Paul-Camilo; Munoz, François; Stevenson, Pablo R; Paine, C E Timothy; Sarmiento, Carolina; Sabatier, Daniel; Heuret, Patrick

2011-08-22

Plant phenology is concerned with the timing of recurring biological events. Though phenology has traditionally been studied using intensive surveys of a local flora, results from such surveys are difficult to generalize to broader spatial scales. In this study, contrastingly, we assembled a continental-scale dataset of herbarium specimens for the emblematic genus of Neotropical pioneer trees, Cecropia, and applied Fourier spectral and cospectral analyses to investigate the reproductive phenology of 35 species. We detected significant annual, sub-annual and continuous patterns, and discuss the variation in patterns within and among climatic regions. Although previous studies have suggested that pioneer species generally produce flowers continually throughout the year, we found that at least one third of Cecropia species are characterized by clear annual flowering behaviour. We further investigated the relationships between phenology and climate seasonality, showing strong associations between phenology and seasonal variations in precipitation and temperature. We also verified our results against field survey data gathered from the literature. Our findings indicate that herbarium material is a reliable resource for use in the investigation of large-scale patterns in plant phenology, offering a promising complement to local intensive field studies.

Spatially explicit shallow landslide susceptibility mapping over large areas

Science.gov (United States)

Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so...

Exploring spatial patterns and hotspots of diarrhea in Chiang Mai, Thailand

Directory of Open Access Journals (Sweden)

Tripathi Nitin K

2009-06-01

Full Text Available Abstract Background Diarrhea is a major public health problem in Thailand. The Ministry of Public Health, Thailand, has been trying to monitor and control this disease for many years. The methodology and the results from this study could be useful for public health officers to develop a system to monitor and prevent diarrhea outbreaks. Methods The objective of this study was to analyse the epidemic outbreak patterns of diarrhea in Chiang Mai province, Northern Thailand, in terms of their geographical distributions and hotspot identification. The data of patients with diarrhea at village level and the 2001–2006 population censuses were collected to achieve the objective. Spatial analysis, using geographic information systems (GIS and other methods, was used to uncover the hidden phenomena from the data. In the data analysis section, spatial statistics such as quadrant analysis (QA, nearest neighbour analysis (NNA, and spatial autocorrelation analysis (SAA, were used to identify the spatial patterns of diarrhea in Chiang Mai province. In addition, local indicators of spatial association (LISA and kernel density (KD estimation were used to detect diarrhea hotspots using data at village level. Results The hotspot maps produced by the LISA and KD techniques showed spatial trend patterns of diarrhea diffusion. Villages in the middle and northern regions revealed higher incidences. Also, the spatial patterns of diarrhea during the years 2001 and 2006 were found to represent spatially clustered patterns, both at global and local scales. Conclusion Spatial analysis methods in GIS revealed the spatial patterns and hotspots of diarrhea in Chiang Mai province from the year 2001 to 2006. To implement specific and geographically appropriate public health risk-reduction programs, the use of such spatial analysis tools may become an integral component in the epidemiologic description, analysis, and risk assessment of diarrhea.

Spatial-Scale Characteristics of Precipitation Simulated by Regional Climate Models and the Implications for Hydrological Modeling

DEFF Research Database (Denmark)

Rasmussen, S.H.; Christensen, J. H.; Drews, Martin

2012-01-01

Precipitation simulated by regional climate models (RCMs) is generally biased with respect to observations, especially at the local scale of a few tens of kilometers. This study investigates how well two different RCMs are able to reproduce the spatial correlation patterns of observed summer...... length scales on the order of 130 km are found in both observed data and RCM simulations. When simulations and observations are aggregated to different grid sizes, the pattern correlation significantly decreases when the aggregation length is less than roughly 100 km. Furthermore, the intermodel standard......, reflecting larger predictive certainty of the RCMs at larger scales. The findings on aggregated grid scales are shown to be largely independent of the underlying RCMs grid resolutions but not of the overall size of RCM domain. With regard to hydrological modeling applications, these findings indicate...

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

Science.gov (United States)

Martin, D. J.

2013-12-01

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

Effect of Variable Spatial Scales on USLE-GIS Computations

Science.gov (United States)

Patil, R. J.; Sharma, S. K.

2017-12-01

Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

Algorithms for large scale singular value analysis of spatially variant tomography systems

International Nuclear Information System (INIS)

Cao-Huu, Tuan; Brownell, G.; Lachiver, G.

1996-01-01

The problem of determining the eigenvalues of large matrices occurs often in the design and analysis of modem tomography systems. As there is an interest in solving systems containing an ever-increasing number of variables, current research effort is being made to create more robust solvers which do not depend on some special feature of the matrix for convergence (e.g. block circulant), and to improve the speed of already known and understood solvers so that solving even larger systems in a reasonable time becomes viable. Our standard techniques for singular value analysis are based on sparse matrix factorization and are not applicable when the input matrices are large because the algorithms cause too much fill. Fill refers to the increase of non-zero elements in the LU decomposition of the original matrix A (the system matrix). So we have developed iterative solutions that are based on sparse direct methods. Data motion and preconditioning techniques are critical for performance. This conference paper describes our algorithmic approaches for large scale singular value analysis of spatially variant imaging systems, and in particular of PCR2, a cylindrical three-dimensional PET imager 2 built at the Massachusetts General Hospital (MGH) in Boston. We recommend the desirable features and challenges for the next generation of parallel machines for optimal performance of our solver

Using Unmanned Aerial Vehicles (UAV to Quantify Spatial Gap Patterns in Forests

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Stephan Getzin

2014-07-01

Full Text Available Gap distributions in forests reflect the spatial impact of man-made tree harvesting or naturally-induced patterns of tree death being caused by windthrow, inter-tree competition, disease or senescence. Gap sizes can vary from large (>100 m2 to small (<10 m2, and they may have contrasting spatial patterns, such as being aggregated or regularly distributed. However, very small gaps cannot easily be recorded with conventional aerial or satellite images, which calls for new and cost-effective methodologies of forest monitoring. Here, we used an unmanned aerial vehicle (UAV and very high-resolution images to record the gaps in 10 temperate managed and unmanaged forests in two regions of Germany. All gaps were extracted for 1-ha study plots and subsequently analyzed with spatially-explicit statistics, such as the conventional pair correlation function (PCF, the polygon-based PCF and the mark correlation function. Gap-size frequency was dominated by small gaps of an area <5 m2, which were particularly frequent in unmanaged forests. We found that gap distances showed a variety of patterns. However, the polygon-based PCF was a better descriptor of patterns than the conventional PCF, because it showed randomness or aggregation for cases when the conventional PCF showed small-scale regularity; albeit, the latter was only a mathematical artifact. The mark correlation function revealed that gap areas were in half of the cases negatively correlated and in the other half independent. Negative size correlations may likely be the result of single-tree harvesting or of repeated gap formation, which both lead to nearby small gaps. Here, we emphasize the usefulness of UAV to record forest gaps of a very small size. These small gaps may originate from repeated gap-creating disturbances, and their spatial patterns should be monitored with spatially-explicit statistics at recurring intervals in order to further insights into forest dynamics.

Evidence of Territoriality and Species Interactions from Spatial Point-Pattern Analyses of Subarctic-Nesting Geese

Science.gov (United States)

Reiter, Matthew E.; Andersen, David E.

2013-01-01

Quantifying spatial patterns of bird nests and nest fate provides insights into processes influencing a species’ distribution. At Cape Churchill, Manitoba, Canada, recent declines in breeding Eastern Prairie Population Canada geese (Branta canadensis interior) has coincided with increasing populations of nesting lesser snow geese (Chen caerulescens caerulescens) and Ross’s geese (Chen rossii). We conducted a spatial analysis of point patterns using Canada goose nest locations and nest fate, and lesser snow goose nest locations at two study areas in northern Manitoba with different densities and temporal durations of sympatric nesting Canada and lesser snow geese. Specifically, we assessed (1) whether Canada geese exhibited territoriality and at what scale and nest density; and (2) whether spatial patterns of Canada goose nest fate were associated with the density of nesting lesser snow geese as predicted by the protective-association hypothesis. Between 2001 and 2007, our data suggest that Canada geese were territorial at the scale of nearest neighbors, but were aggregated when considering overall density of conspecifics at slightly broader spatial scales. The spatial distribution of nest fates indicated that lesser snow goose nest proximity and density likely influence Canada goose nest fate. Our analyses of spatial point patterns suggested that continued changes in the distribution and abundance of breeding lesser snow geese on the Hudson Bay Lowlands may have impacts on the reproductive performance of Canada geese, and subsequently the spatial distribution of Canada goose nests. PMID:24312520

Burstiness in Viral Bursts: How Stochasticity Affects Spatial Patterns in Virus-Microbe Dynamics

Science.gov (United States)

Lin, Yu-Hui; Taylor, Bradford P.; Weitz, Joshua S.

Spatial patterns emerge in living systems at the scale of microbes to metazoans. These patterns can be driven, in part, by the stochasticity inherent to the birth and death of individuals. For microbe-virus systems, infection and lysis of hosts by viruses results in both mortality of hosts and production of viral progeny. Here, we study how variation in the number of viral progeny per lysis event affects the spatial clustering of both viruses and microbes. Each viral ''burst'' is initially localized at a near-cellular scale. The number of progeny in a single lysis event can vary in magnitude between tens and thousands. These perturbations are not accounted for in mean-field models. Here we developed individual-based models to investigate how stochasticity affects spatial patterns in virus-microbe systems. We measured the spatial clustering of individuals using pair correlation functions. We found that increasing the burst size of viruses while maintaining the same production rate led to enhanced clustering. In this poster we also report on preliminary analysis on the evolution of the burstiness of viral bursts given a spatially distributed host community.

Large-scale runoff generation – parsimonious parameterisation using high-resolution topography

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L. Gong

2011-08-01

Full Text Available World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm

Large Scale Frequent Pattern Mining using MPI One-Sided Model

Energy Technology Data Exchange (ETDEWEB)

Vishnu, Abhinav; Agarwal, Khushbu

2015-09-08

In this paper, we propose a work-stealing runtime --- Library for Work Stealing LibWS --- using MPI one-sided model for designing scalable FP-Growth --- {\\em de facto} frequent pattern mining algorithm --- on large scale systems. LibWS provides locality efficient and highly scalable work-stealing techniques for load balancing on a variety of data distributions. We also propose a novel communication algorithm for FP-growth data exchange phase, which reduces the communication complexity from state-of-the-art O(p) to O(f + p/f) for p processes and f frequent attributed-ids. FP-Growth is implemented using LibWS and evaluated on several work distributions and support counts. An experimental evaluation of the FP-Growth on LibWS using 4096 processes on an InfiniBand Cluster demonstrates excellent efficiency for several work distributions (87\\% efficiency for Power-law and 91% for Poisson). The proposed distributed FP-Tree merging algorithm provides 38x communication speedup on 4096 cores.

Direction of information flow in large-scale resting-state networks is frequency-dependent.

Science.gov (United States)

Hillebrand, Arjan; Tewarie, Prejaas; van Dellen, Edwin; Yu, Meichen; Carbo, Ellen W S; Douw, Linda; Gouw, Alida A; van Straaten, Elisabeth C W; Stam, Cornelis J

2016-04-05

Normal brain function requires interactions between spatially separated, and functionally specialized, macroscopic regions, yet the directionality of these interactions in large-scale functional networks is unknown. Magnetoencephalography was used to determine the directionality of these interactions, where directionality was inferred from time series of beamformer-reconstructed estimates of neuronal activation, using a recently proposed measure of phase transfer entropy. We observed well-organized posterior-to-anterior patterns of information flow in the higher-frequency bands (alpha1, alpha2, and beta band), dominated by regions in the visual cortex and posterior default mode network. Opposite patterns of anterior-to-posterior flow were found in the theta band, involving mainly regions in the frontal lobe that were sending information to a more distributed network. Many strong information senders in the theta band were also frequent receivers in the alpha2 band, and vice versa. Our results provide evidence that large-scale resting-state patterns of information flow in the human brain form frequency-dependent reentry loops that are dominated by flow from parieto-occipital cortex to integrative frontal areas in the higher-frequency bands, which is mirrored by a theta band anterior-to-posterior flow.

Patterns at Multi-Spatial Scales on Tropical Island Stream Insect Assemblages: Gorgona Island Natural National Park, Colombia, Tropical Eastern Pacific

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Magnolia Longo

2014-02-01

Full Text Available Tropical Eastern Pacific island streams (TEPis differ from other neotropical streams in their rainy climate, mixed sedimentary-volcanic geology and faunal composition. Yet, their relationships between environmental characteristics and stream biota remain unexplored. We analyzed the environmental subject at three spatial scales using a fully nested sampling design (6 streams, 2 reaches within each stream, 2 habitats within each reach, and 4 replicates per habitat on Gorgona Island (Colombia. Sampling was carried out in two months with contrasting rainfall during early 2009. We studied the spatial variation of assemblage composition and density along with 27 independent variables within two contrasting rainfall conditions. Five stream-scale variables, two reach-scale variables, and five habitat-scale variables were selected using a Canonical Correspondence Analysis (CCA. A partial CCA showed that the total variance explained was 13.98%, while stream- and habitat-scale variables explained the highest proportion of the variance (5.74 and 5.01%, respectively. Dissolved oxygen (as affected by rainfall, high-density use zone (a management category, and sedimentary geology were the best descriptors of insect assemblages. The two latter descriptors affected fine-scale variables such as total benthic organic matter and gravel substratum, respectively. A Nested ANOVA showed significant differences in total density and richness among streams and habitats, and significant differences between the two sampling months regardless of the spatial scale. The evenness showed a significant stream- and habitat-dependent temporal variability. These results suggested that rainfall regime in Gorgona Island might be a driver of insect assemblage dynamics mediated by water chemistry and substratum properties. Spatial assemblage variability here is greater within habitats (among samples, and a minor fraction occurs at habitat- and stream-scales, while no longitudinal

Updating Geospatial Data from Large Scale Data Sources

Science.gov (United States)

Zhao, R.; Chen, J.; Wang, D.; Shang, Y.; Wang, Z.; Li, X.; Ai, T.

2011-08-01

In the past decades, many geospatial databases have been established at national, regional and municipal levels over the world. Nowadays, it has been widely recognized that how to update these established geo-spatial database and keep them up to date is most critical for the value of geo-spatial database. So, more and more efforts have been devoted to the continuous updating of these geospatial databases. Currently, there exist two main types of methods for Geo-spatial database updating: directly updating with remote sensing images or field surveying materials, and indirectly updating with other updated data result such as larger scale newly updated data. The former method is the basis because the update data sources in the two methods finally root from field surveying and remote sensing. The later method is often more economical and faster than the former. Therefore, after the larger scale database is updated, the smaller scale database should be updated correspondingly in order to keep the consistency of multi-scale geo-spatial database. In this situation, it is very reasonable to apply map generalization technology into the process of geo-spatial database updating. The latter is recognized as one of most promising methods of geo-spatial database updating, especially in collaborative updating environment in terms of map scale, i.e , different scale database are produced and maintained separately by different level organizations such as in China. This paper is focused on applying digital map generalization into the updating of geo-spatial database from large scale in the collaborative updating environment for SDI. The requirements of the application of map generalization into spatial database updating are analyzed firstly. A brief review on geospatial data updating based digital map generalization is then given. Based on the requirements analysis and review, we analyze the key factors for implementing updating geospatial data from large scale including technical

Up, down, and all around: scale-dependent spatial variation in rocky-shore communities of Fildes Peninsula, King George Island, Antarctica.

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Nelson Valdivia

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

Analysis of small scale turbulent structures and the effect of spatial scales on gas transfer

Science.gov (United States)

Schnieders, Jana; Garbe, Christoph

2014-05-01

The exchange of gases through the air-sea interface strongly depends on environmental conditions such as wind stress and waves which in turn generate near surface turbulence. Near surface turbulence is a main driver of surface divergence which has been shown to cause highly variable transfer rates on relatively small spatial scales. Due to the cool skin of the ocean, heat can be used as a tracer to detect areas of surface convergence and thus gather information about size and intensity of a turbulent process. We use infrared imagery to visualize near surface aqueous turbulence and determine the impact of turbulent scales on exchange rates. Through the high temporal and spatial resolution of these types of measurements spatial scales as well as surface dynamics can be captured. The surface heat pattern is formed by distinct structures on two scales - small-scale short lived structures termed fish scales and larger scale cold streaks that are consistent with the footprints of Langmuir Circulations. There are two key characteristics of the observed surface heat patterns: 1. The surface heat patterns show characteristic features of scales. 2. The structure of these patterns change with increasing wind stress and surface conditions. In [2] turbulent cell sizes have been shown to systematically decrease with increasing wind speed until a saturation at u* = 0.7 cm/s is reached. Results suggest a saturation in the tangential stress. Similar behaviour has been observed by [1] for gas transfer measurements at higher wind speeds. In this contribution a new model to estimate the heat flux is applied which is based on the measured turbulent cell size und surface velocities. This approach allows the direct comparison of the net effect on heat flux of eddies of different sizes and a comparison to gas transfer measurements. Linking transport models with thermographic measurements, transfer velocities can be computed. In this contribution, we will quantify the effect of small scale

Tree Regeneration Spatial Patterns in Ponderosa Pine Forests Following Stand-Replacing Fire: Influence of Topography and Neighbors

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Justin P. Ziegler

2017-10-01

Full Text Available Shifting fire regimes alter forest structure assembly in ponderosa pine forests and may produce structural heterogeneity following stand-replacing fire due, in part, to fine-scale variability in growing environments. We mapped tree regeneration in eighteen plots 11 to 15 years after stand-replacing fire in Colorado and South Dakota, USA. We used point pattern analyses to examine the spatial pattern of tree locations and heights as well as the influence of tree interactions and topography on tree patterns. In these sparse, early-seral forests, we found that all species were spatially aggregated, partly attributable to the influence of (1 aspect and slope on conifers; (2 topographic position on quaking aspen; and (3 interspecific attraction between ponderosa pine and other species. Specifically, tree interactions were related to finer-scale patterns whereas topographic effects influenced coarse-scale patterns. Spatial structures of heights revealed conspecific size hierarchies with taller trees in denser neighborhoods. Topography and heterospecific tree interactions had nominal effect on tree height spatial structure. Our results demonstrate how stand-replacing fires create heterogeneous forest structures and suggest that scale-dependent, and often facilitatory, rather than competitive, processes act on regenerating trees. These early-seral processes will establish potential pathways of stand development, affecting future forest dynamics and management options.

Estuarine habitat quality reflects urbanization at large spatial scales in South Carolina's coastal zone.

Science.gov (United States)

Van Dolah, Robert F; Riekerk, George H M; Bergquist, Derk C; Felber, Jordan; Chestnut, David E; Holland, A Fredrick

2008-02-01

analyses support the hypotheses that estuarine habitat quality reflects upland development patterns at large spatial scales, and that upland urbanization can result in increased risk of biological degradation and reduced safe human use of South Carolina's coastal resources.

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

Science.gov (United States)

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.

Landscapes for Energy and Wildlife: Conservation Prioritization for Golden Eagles across Large Spatial Scales.

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Jason D Tack

Full Text Available Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publically available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development.

Spatial scaling of bacterial community diversity at shallow hydrothermal vents: a global comparison

Science.gov (United States)

Pop Ristova, P.; Hassenrueck, C.; Molari, M.; Fink, A.; Bühring, S. I.

2016-02-01

Marine shallow hydrothermal vents are extreme environments, often characterized by discharge of fluids with e.g. high temperatures, low pH, and laden with elements toxic to higher organisms. They occur at continental margins around the world's oceans, but represent fragmented, isolated habitats of locally small areal coverage. Microorganisms contribute the main biomass at shallow hydrothermal vent ecosystems and build the basis of the food chain by autotrophic fixation of carbon both via chemosynthesis and photosynthesis, occurring simultaneously. Despite their importance and unique capacity to adapt to these extreme environments, little is known about the spatial scales on which the alpha- and beta-diversity of microbial communities vary at shallow vents, and how the geochemical habitat heterogeneity influences shallow vent biodiversity. Here for the first time we investigated the spatial scaling of microbial biodiversity patterns and their interconnectivity at geochemically diverse shallow vents on a global scale. This study presents data on the comparison of bacterial community structures on large (> 1000 km) and small (0.1 - 100 m) spatial scales as derived from ARISA and Illumina sequencing. Despite the fragmented global distribution of shallow hydrothermal vents, similarity of vent bacterial communities decreased with geographic distance, confirming the ubiquity of distance-decay relationship. Moreover, at all investigated vents, pH was the main factor locally structuring these communities, while temperature influenced both the alpha- and beta-diversity.

Spatial pattern enhances ecosystem functioning in an African savanna.

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Robert M Pringle

2010-05-01

Full Text Available The finding that regular spatial patterns can emerge in nature from local interactions between organisms has prompted a search for the ecological importance of these patterns. Theoretical models have predicted that patterning may have positive emergent effects on fundamental ecosystem functions, such as productivity. We provide empirical support for this prediction. In dryland ecosystems, termite mounds are often hotspots of plant growth (primary productivity. Using detailed observations and manipulative experiments in an African savanna, we show that these mounds are also local hotspots of animal abundance (secondary and tertiary productivity: insect abundance and biomass decreased with distance from the nearest termite mound, as did the abundance, biomass, and reproductive output of insect-eating predators. Null-model analyses indicated that at the landscape scale, the evenly spaced distribution of termite mounds produced dramatically greater abundance, biomass, and reproductive output of consumers across trophic levels than would be obtained in landscapes with randomly distributed mounds. These emergent properties of spatial pattern arose because the average distance from an arbitrarily chosen point to the nearest feature in a landscape is minimized in landscapes where the features are hyper-dispersed (i.e., uniformly spaced. This suggests that the linkage between patterning and ecosystem functioning will be common to systems spanning the range of human management intensities. The centrality of spatial pattern to system-wide biomass accumulation underscores the need to conserve pattern-generating organisms and mechanisms, and to incorporate landscape patterning in efforts to restore degraded habitats and maximize the delivery of ecosystem services.

Spatial pattern enhances ecosystem functioning in an African savanna.

Science.gov (United States)

Pringle, Robert M; Doak, Daniel F; Brody, Alison K; Jocqué, Rudy; Palmer, Todd M

2010-05-25

The finding that regular spatial patterns can emerge in nature from local interactions between organisms has prompted a search for the ecological importance of these patterns. Theoretical models have predicted that patterning may have positive emergent effects on fundamental ecosystem functions, such as productivity. We provide empirical support for this prediction. In dryland ecosystems, termite mounds are often hotspots of plant growth (primary productivity). Using detailed observations and manipulative experiments in an African savanna, we show that these mounds are also local hotspots of animal abundance (secondary and tertiary productivity): insect abundance and biomass decreased with distance from the nearest termite mound, as did the abundance, biomass, and reproductive output of insect-eating predators. Null-model analyses indicated that at the landscape scale, the evenly spaced distribution of termite mounds produced dramatically greater abundance, biomass, and reproductive output of consumers across trophic levels than would be obtained in landscapes with randomly distributed mounds. These emergent properties of spatial pattern arose because the average distance from an arbitrarily chosen point to the nearest feature in a landscape is minimized in landscapes where the features are hyper-dispersed (i.e., uniformly spaced). This suggests that the linkage between patterning and ecosystem functioning will be common to systems spanning the range of human management intensities. The centrality of spatial pattern to system-wide biomass accumulation underscores the need to conserve pattern-generating organisms and mechanisms, and to incorporate landscape patterning in efforts to restore degraded habitats and maximize the delivery of ecosystem services.

Large-Scale Spatial Dynamics of Intertidal Mussel (

NARCIS (Netherlands)

Folmer, E.O.; Drent, J.; Troost, K.; Büttger, H.; Dankers, N.; Jansen, J.; van Stralen, M.; Millat, G.; Herlyn, M.; Philippart, C.J.M.

2014-01-01

Intertidal blue mussel beds are important for the functioning and community composition of coastal ecosystems. Modeling spatial dynamics of intertidal mussel beds is complicated because suitable habitat is spatially heterogeneously distributed and recruitment and loss are hard to predict. To get

Spatial patterns and links between microbial community composition and function in cyanobacterial mats

KAUST Repository

Alnajjar, Mohammad Ahmad; Ramette, Alban; Kü hl, Michael; Hamza, Waleed; Klatt, Judith M.; Polerecky, Lubos

2014-01-01

We imaged reflectance and variable fluorescence in 25 cyanobacterial mats from four distant sites around the globe to assess, at different scales of resolution, spatial variabilities in the physiological parameters characterizing their photosynthetic capacity, including the absorptivity by chlorophyll a (Achl), maximum quantum yield of photosynthesis (Ymax), and light acclimation irradiance (Ik). Generally, these parameters significantly varied within individual mats on a sub-millimeter scale, with about 2-fold higher variability in the vertical than in the horizontal direction. The average vertical profiles of Ymax and Ik decreased with depth in the mat, while Achl exhibited a sub-surface maximum. The within-mat variability was comparable to, but often larger than, the between-sites variability, whereas the within-site variabilities (i.e., between samples from the same site) were generally lowest. When compared based on averaged values of their photosynthetic parameters, mats clustered according to their site of origin. Similar clustering was found when the community composition of the mats' cyanobacterial layers were compared by automated ribosomal intergenic spacer analysis (ARISA), indicating a significant link between the microbial community composition and function. Although this link is likely the result of community adaptation to the prevailing site-specific environmental conditions, our present data is insufficient to identify the main factors determining these patterns. Nevertheless, this study demonstrates that the spatial variability in the photosynthetic capacity and light acclimation of benthic phototrophic microbial communities is at least as large on a sub-millimeter scale as it is on a global scale, and suggests that this pattern of variability scaling is similar for the microbial community composition. © 2014 Al-Najjar, Ramette, Kühl, Hamza, Klatt and Polerecky.

Spatial patterns and links between microbial community composition and function in cyanobacterial mats

KAUST Repository

Alnajjar, Mohammad Ahmad

2014-08-06

We imaged reflectance and variable fluorescence in 25 cyanobacterial mats from four distant sites around the globe to assess, at different scales of resolution, spatial variabilities in the physiological parameters characterizing their photosynthetic capacity, including the absorptivity by chlorophyll a (Achl), maximum quantum yield of photosynthesis (Ymax), and light acclimation irradiance (Ik). Generally, these parameters significantly varied within individual mats on a sub-millimeter scale, with about 2-fold higher variability in the vertical than in the horizontal direction. The average vertical profiles of Ymax and Ik decreased with depth in the mat, while Achl exhibited a sub-surface maximum. The within-mat variability was comparable to, but often larger than, the between-sites variability, whereas the within-site variabilities (i.e., between samples from the same site) were generally lowest. When compared based on averaged values of their photosynthetic parameters, mats clustered according to their site of origin. Similar clustering was found when the community composition of the mats\\' cyanobacterial layers were compared by automated ribosomal intergenic spacer analysis (ARISA), indicating a significant link between the microbial community composition and function. Although this link is likely the result of community adaptation to the prevailing site-specific environmental conditions, our present data is insufficient to identify the main factors determining these patterns. Nevertheless, this study demonstrates that the spatial variability in the photosynthetic capacity and light acclimation of benthic phototrophic microbial communities is at least as large on a sub-millimeter scale as it is on a global scale, and suggests that this pattern of variability scaling is similar for the microbial community composition. © 2014 Al-Najjar, Ramette, Kühl, Hamza, Klatt and Polerecky.

Understanding the Functionality of Human Activity Hotspots from Their Scaling Pattern Using Trajectory Data

Directory of Open Access Journals (Sweden)

Tao Jia

2017-11-01

Full Text Available Human activity hotspots are the clusters of activity locations in space and time, and a better understanding of their functionality would be useful for urban land use planning and transportation. In this article, using trajectory data, we aim to infer the functionality of human activity hotspots from their scaling pattern in a reliable way. Specifically, a large number of stopping locations are extracted from trajectory data, which are then aggregated into activity hotspots. Activity hotspots are found to display scaling patterns in terms of the sublinear scaling relationships between the number of stopping locations and the number of points of interest (POIs, which indicates economies of scale of human interactions with urban land use. Importantly, this scaling pattern remains stable over time. This finding inspires us to devise an allometric ruler to identify the activity hotspots, whose functionality could be reliably estimated using the stopping locations. Thereafter, a novel Bayesian inference model is proposed to infer their urban functionality, which examines the spatial and temporal information of stopping locations covering 75 days. Experimental results suggest that the functionality of identified activity hotspots are reliably inferred by stopping locations, such as the railway station.

Spatial modeling of agricultural land use change at global scale

Science.gov (United States)

Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

2014-11-01

Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling

[Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.

Science.gov (United States)

Yu, Ya Ping; Yin, Hai Wei; Kong, Fan Hua; Wang, Jing Jing; Xu, Wen Bin

2016-07-01

Based on ArcGIS, Erdas, GuidosToolbox, Conefor and other software platforms, using morphological spatial pattern analysis (MSPA) and landscape connectivity analysis methods, this paper quantitatively analysed the scale effect, edge effect and distance effect of the Nanjing urban green infrastructure network pattern in 2013 by setting different pixel sizes (P) and edge widths in MSPA analysis, and setting different dispersal distance thresholds in landscape connectivity analysis. The results showed that the type of landscape acquired based on the MSPA had a clear scale effect and edge effect, and scale effects only slightly affected landscape types, whereas edge effects were more obvious. Different dispersal distances had a great impact on the landscape connectivity, 2 km or 2.5 km dispersal distance was a critical threshold for Nanjing. When selecting the pixel size 30 m of the input data and the edge wide 30 m used in the morphological model, we could get more detailed landscape information of Nanjing UGI network. Based on MSPA and landscape connectivity, analysis of the scale effect, edge effect, and distance effect on the landscape types of the urban green infrastructure (UGI) network was helpful for selecting the appropriate size, edge width, and dispersal distance when developing these networks, and for better understanding the spatial pattern of UGI networks and the effects of scale and distance on the ecology of a UGI network. This would facilitate a more scientifically valid set of design parameters for UGI network spatiotemporal pattern analysis. The results of this study provided an important reference for Nanjing UGI networks and a basis for the analysis of the spatial and temporal patterns of medium-scale UGI landscape networks in other regions.

Modeling the spatial distribution of crop cultivated areas at a large regional scale combining system dynamics and a modified Dyna-CLUE: A case from Iran

Energy Technology Data Exchange (ETDEWEB)

Mesgari, I.; Saeed Jabalameli, M.

2017-07-01

Agricultural land use pattern is affected by many factors at different scales and effects that are separated by time and space. This will lead to simulation models that optimize or project the cropping pattern changes and incorporate complexities in terms of details and dynamics. Combining System Dynamics (SD) and a modified Conversion of Land Use and its Effects (CLUE) modelling framework, this paper suggests a new dynamic approach for assessing the demand of different crops at country-level and for predicting the spatial distribution of cultivated areas at provincial scale. As example, a case study is presented for Iran, where we have simulated a scenario of future cropping pattern changes during 2015–2040.The results indicated a change in the spatial distribution of cultivated areas during the next years. An increase in the proportion of rice is expected in northern Iran, whereas the proportion of wheat is increasing in the mountainous western areas. Wheat and barley crops are expected to become dominant within the cropping system throughout the country regions.

Spatial Patterns of Development Drive Water Use

Science.gov (United States)

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.

Spatial patterns of development drive water use

Science.gov (United States)

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 pattern of Amazonian timber species using cartesian and spatial coordinates method

Directory of Open Access Journals (Sweden)

Tiago Monteiro Condé

2016-06-01

Full Text Available Geographic information system (GIS applied to forest analysis permit the recognition and analysis of spatial patterns of species in two and three dimensional. The aim of this study to demonstrate the efficiency of cartesian and spatial coordinates method (MCCE, method of correcting UTM coordinates of trees location in accordance with the location of field or Cartesian (X ,Y, combined with natural neighbor index (ANND in recognition and analysis of spatial distribution patterns of four commercial timber species in forest management in Caracaraí, Roraima State, Brazil. Simulations were performed on 9 ha, divided into 100 plots of 100 m2 each. Collected data were DBH > 10 cm, commercial and total heights, cartesian coordinates (X,Y and spatial coordinates (UTM. Random spatial patterns were observed in Eschweilera bracteosa and Manilkara huberi. The dispersed and rare spatial patterns were observed in Dinizia excelsa and Cedrelinga cateniformis. MCCE proved to be an efficient method in the recognition and analysis of spatial patterns of native species from Amazon rain forest, as forest planning becomes easier by 2D and 3D simulations.

Deep-UV patterning of commercial grade PMMA for low-cost, large-scale microfluidics

International Nuclear Information System (INIS)

Haiducu, M; Rahbar, M; Foulds, I G; Johnstone, R W; Sameoto, D; Parameswaran, M

2008-01-01

Although PMMA can be exposed using a variety of exposure sources, deep-UV at 254 nm is of interest because it is relatively inexpensive. Additionally, deep-UV sources can be readily scaled to large area exposures. Moreover, this paper will show that depths of over 100µm can be created in commercial grade PMMA using an uncollimated source. These depths are sufficient for creating microfluidic channels. This paper will provide measurements of the dissolution depth of commercial grade PMMA as a function of the exposure dose and etch time, using an IPA:H 2 O developer. Additionally, experiments were run to characterize the dependence of the dissolution rate on temperature and agitation. The patterned substrates were thermally bonded to blank PMMA pieces to enclose the channels and ports were drilled into the reservoirs. The resulting fluidic systems were then tested for leakage. The work herein presents the patterning, development and system behaviour of a complete microfluidics system based on commercial grade PMMA

EFFECTS OF HETEROGENIETY ON SPATIAL PATTERN ANALYSIS OF WILD PISTACHIO TREES IN ZAGROS WOODLANDS, IRAN

Directory of Open Access Journals (Sweden)

Y. Erfanifard

2014-10-01

Full Text Available Vegetation heterogeneity biases second-order summary statistics, e.g., Ripley's K-function, applied for spatial pattern analysis in ecology. Second-order investigation based on Ripley's K-function and related statistics (i.e., L- and pair correlation function g is widely used in ecology to develop hypothesis on underlying processes by characterizing spatial patterns of vegetation. The aim of this study was to demonstrate effects of underlying heterogeneity of wild pistachio (Pistacia atlantica Desf. trees on the second-order summary statistics of point pattern analysis in a part of Zagros woodlands, Iran. The spatial distribution of 431 wild pistachio trees was accurately mapped in a 40 ha stand in the Wild Pistachio & Almond Research Site, Fars province, Iran. Three commonly used second-order summary statistics (i.e., K-, L-, and g-functions were applied to analyse their spatial pattern. The two-sample Kolmogorov-Smirnov goodness-of-fit test showed that the observed pattern significantly followed an inhomogeneous Poisson process null model in the study region. The results also showed that heterogeneous pattern of wild pistachio trees biased the homogeneous form of K-, L-, and g-functions, demonstrating a stronger aggregation of the trees at the scales of 0–50 m than actually existed and an aggregation at scales of 150–200 m, while regularly distributed. Consequently, we showed that heterogeneity of point patterns may bias the results of homogeneous second-order summary statistics and we also suggested applying inhomogeneous summary statistics with related null models for spatial pattern analysis of heterogeneous vegetations.

Effects of Heterogeniety on Spatial Pattern Analysis of Wild Pistachio Trees in Zagros Woodlands, Iran

Science.gov (United States)

Erfanifard, Y.; Rezayan, F.

2014-10-01

Vegetation heterogeneity biases second-order summary statistics, e.g., Ripley's K-function, applied for spatial pattern analysis in ecology. Second-order investigation based on Ripley's K-function and related statistics (i.e., L- and pair correlation function g) is widely used in ecology to develop hypothesis on underlying processes by characterizing spatial patterns of vegetation. The aim of this study was to demonstrate effects of underlying heterogeneity of wild pistachio (Pistacia atlantica Desf.) trees on the second-order summary statistics of point pattern analysis in a part of Zagros woodlands, Iran. The spatial distribution of 431 wild pistachio trees was accurately mapped in a 40 ha stand in the Wild Pistachio & Almond Research Site, Fars province, Iran. Three commonly used second-order summary statistics (i.e., K-, L-, and g-functions) were applied to analyse their spatial pattern. The two-sample Kolmogorov-Smirnov goodness-of-fit test showed that the observed pattern significantly followed an inhomogeneous Poisson process null model in the study region. The results also showed that heterogeneous pattern of wild pistachio trees biased the homogeneous form of K-, L-, and g-functions, demonstrating a stronger aggregation of the trees at the scales of 0-50 m than actually existed and an aggregation at scales of 150-200 m, while regularly distributed. Consequently, we showed that heterogeneity of point patterns may bias the results of homogeneous second-order summary statistics and we also suggested applying inhomogeneous summary statistics with related null models for spatial pattern analysis of heterogeneous vegetations.

Large scale patterns in vertical distribution and behaviour of mesopelagic scattering layers

KAUST Repository

Klevjer, Thor Aleksander

2016-01-27

Recent studies suggest that previous estimates of mesopelagic biomasses are severely biased, with the new, higher estimates underlining the need to unveil behaviourally mediated coupling between shallow and deep ocean habitats. We analysed vertical distribution and diel vertical migration (DVM) of mesopelagic acoustic scattering layers (SLs) recorded at 38 kHz across oceanographic regimes encountered during the circumglobal Malaspina expedition. Mesopelagic SLs were observed in all areas covered, but vertical distributions and DVM patterns varied markedly. The distribution of mesopelagic backscatter was deepest in the southern Indian Ocean (weighted mean daytime depth: WMD 590 m) and shallowest at the oxygen minimum zone in the eastern Pacific (WMD 350 m). DVM was evident in all areas covered, on average ~50% of mesopelagic backscatter made daily excursions from mesopelagic depths to shallow waters. There were marked differences in migrating proportions between the regions, ranging from ~20% in the Indian Ocean to ~90% in the Eastern Pacific. Overall the data suggest strong spatial gradients in mesopelagic DVM patterns, with implied ecological and biogeochemical consequences. Our results suggest that parts of this spatial variability can be explained by horizontal patterns in physical-chemical properties of water masses, such as oxygen, temperature and turbidity.

Phylogeny and palm diversity across scales

DEFF Research Database (Denmark)

Eiserhardt, Wolf L.; Svenning, J.-C.; Baker, William J.

spatial scales. Among others, we ask the following questions: To what extent can niche conservatism explain large-scale distribution patterns? Which assembly mechanisms are responsible for palm community composition on different spatial scales? What is the role of phylogenetic history for spatial patterns...... clustering. On a continental scale in the New World, we inferred from phylogenetic turnover that palms diversified mainly within seven biogeographic regions. This pattern of in situ diversification is strongly driven by a combination of phylogenetic niche conservatism, environmental filtering and dispersal...... limitation. Niche conservatism with respect to temperature seasonality and extremes emerges as an important determinant of palm species and clade distributions and thus there is concern that palms might be considerably vulnerable to climate change. On a regional to local scale in the Western Amazon...

Seed harvesting by a generalist consumer is context-dependent: Interactive effects across multiple spatial scales

Science.gov (United States)

Ostoja, Steven M.; Schupp, Eugene W.; Klinger, Rob

2013-01-01

Granivore foraging decisions affect consumer success and determine the quantity and spatial pattern of seed survival. These decisions are influenced by environmental variation at spatial scales ranging from landscapes to local foraging patches. In a field experiment, the effects of seed patch variation across three spatial scales on seed removal by western harvester ants Pogonomyrmex occidentalis were evaluated. At the largest scale we assessed harvesting in different plant communities, at the intermediate scale we assessed harvesting at different distances from ant mounds, and at the smallest scale we assessed the effects of interactions among seed species in local seed neighborhoods on seed harvesting (i.e. resource–consumer interface). Selected seed species were presented alone (monospecific treatment) and in mixture with Bromus tectorum (cheatgrass; mixture treatment) at four distances from P. occidentalis mounds in adjacent intact sagebrush and non-native cheatgrass-dominated communities in the Great Basin, Utah, USA. Seed species differed in harvest, with B. tectorum being least preferred. Large and intermediate scale variation influenced harvest. More seeds were harvested in sagebrush than in cheatgrass-dominated communities (largest scale), and the quantity of seed harvested varied with distance from mounds (intermediate-scale), although the form of the distance effect differed between plant communities. At the smallest scale, seed neighborhood affected harvest, but the patterns differed among seed species considered. Ants harvested fewer seeds from mixed-seed neighborhoods than from monospecific neighborhoods, suggesting context dependence and potential associational resistance. Further, the effects of plant community and distance from mound on seed harvest in mixtures differed from their effects in monospecific treatments. Beyond the local seed neighborhood, selection of seed resources is better understood by simultaneously evaluating removal at

Detection of macro-ecological patterns in South American hummingbirds is affected by spatial scale

DEFF Research Database (Denmark)

Rahbek, Carsten; Graves, Gary R.

2000-01-01

Scale is widely recognized as a fundamental conceptual problem in biology, but the question of whether species-richness patterns vary with scale is often ignored in macro-ecological analyses, despite the increasing application of such data in international conservation programmes. We tested for s...... peaks, decreasing the power of statistical tests to discriminate the causal agents of regional richness gradients. Ideally, the scale of analysis should be varied systematically to provide the optimal resolution of macro-ecological pattern....

Large-scale spatial and interspecies differences in trace elements and stable isotopes in marine wild fish from Chinese waters

International Nuclear Information System (INIS)

Zhang, Wei; Wang, Wen-Xiong

2012-01-01

Highlights: ► A large-scale study on trace element levels in marine wild fish from Chinese waters. ► Spatial variation found for Al, As, Cd, Cr, Fe, Ni, Pb, but not for Ag, Cu, Mo, Se and Zn. ► The Pearl River Estuary contained the highest concentrations of Al, Cr, Ni, and Pb. ► No biomagnification occurred for any of the trace elements studied in marine fish. ► No obvious health risk from the intake of trace elements through fish consumption. - Abstract: We conducted a large scale investigation of twelve trace element levels and stable isotopes (δ 13 C and δ 15 N) in twenty-nine marine wild fish species collected from Chinese coastal waters. Trace element levels varied significantly with species. Clear spatial variations were found for Al, As, Cd, Cr, Fe, Ni, and Pb, whereas Ag, Cu, Mo, Se and Zn did not show much spatial variation. The Pearl River Estuary contained the highest concentrations of Al, Cr, Ni, and Pb, whereas the most southern waters (Haikou) contained the lowest concentrations of Al, Fe, and Pb. There was no correlation between log-transformed trace elements concentrations and δ 15 N values or δ 13 C values, indicating no biomagnification among these trace elements. The calculated hazard quotients (HQ) of 10 elements were less than 1, thus there was no obvious health risk from the intake of trace elements through marine wild fish consumption.

Spatially patterned matrix elasticity directs stem cell fate

Science.gov (United States)

Yang, Chun; DelRio, Frank W.; Ma, Hao; Killaars, Anouk R.; Basta, Lena P.; Kyburz, Kyle A.; Anseth, Kristi S.

2016-08-01

There is a growing appreciation for the functional role of matrix mechanics in regulating stem cell self-renewal and differentiation processes. However, it is largely unknown how subcellular, spatial mechanical variations in the local extracellular environment mediate intracellular signal transduction and direct cell fate. Here, the effect of spatial distribution, magnitude, and organization of subcellular matrix mechanical properties on human mesenchymal stem cell (hMSCs) function was investigated. Exploiting a photodegradation reaction, a hydrogel cell culture substrate was fabricated with regions of spatially varied and distinct mechanical properties, which were subsequently mapped and quantified by atomic force microscopy (AFM). The variations in the underlying matrix mechanics were found to regulate cellular adhesion and transcriptional events. Highly spread, elongated morphologies and higher Yes-associated protein (YAP) activation were observed in hMSCs seeded on hydrogels with higher concentrations of stiff regions in a dose-dependent manner. However, when the spatial organization of the mechanically stiff regions was altered from a regular to randomized pattern, lower levels of YAP activation with smaller and more rounded cell morphologies were induced in hMSCs. We infer from these results that irregular, disorganized variations in matrix mechanics, compared with regular patterns, appear to disrupt actin organization, and lead to different cell fates; this was verified by observations of lower alkaline phosphatase (ALP) activity and higher expression of CD105, a stem cell marker, in hMSCs in random versus regular patterns of mechanical properties. Collectively, this material platform has allowed innovative experiments to elucidate a novel spatial mechanical dosing mechanism that correlates to both the magnitude and organization of spatial stiffness.

Large-Scale Ocean Circulation-Cloud Interactions Reduce the Pace of Transient Climate Change

Science.gov (United States)

Trossman, D. S.; Palter, J. B.; Merlis, T. M.; Huang, Y.; Xia, Y.

2016-01-01

Changes to the large scale oceanic circulation are thought to slow the pace of transient climate change due, in part, to their influence on radiative feedbacks. Here we evaluate the interactions between CO2-forced perturbations to the large-scale ocean circulation and the radiative cloud feedback in a climate model. Both the change of the ocean circulation and the radiative cloud feedback strongly influence the magnitude and spatial pattern of surface and ocean warming. Changes in the ocean circulation reduce the amount of transient global warming caused by the radiative cloud feedback by helping to maintain low cloud coverage in the face of global warming. The radiative cloud feedback is key in affecting atmospheric meridional heat transport changes and is the dominant radiative feedback mechanism that responds to ocean circulation change. Uncertainty in the simulated ocean circulation changes due to CO2 forcing may contribute a large share of the spread in the radiative cloud feedback among climate models.

Spatial Patterns of Inshore Marine Soundscapes.

Science.gov (United States)

McWilliam, Jamie

2016-01-01

Passive acoustic monitoring was employed to investigate spatial patterns of soundscapes within a marine reserve. High energy level broadband snaps dominated nearly all habitat soundscapes. Snaps, the principal acoustic feature of soundscapes, were primarily responsible for the observed spatial patterns, and soundscapes appeared to retain a level of compositional and configurational stability. In the presence of high-level broadband snaps, soundscape composition was more influenced by geographic location than habitat type. Future research should focus on investigating the spatial patterns of soundscapes across a wider range of coastal and offshore seascapes containing a variety of distinct ecosystems and habitats.

Spatial implications of covariate adjustment on patterns of risk

DEFF Research Database (Denmark)

Sabel, Clive Eric; Wilson, Jeff Gaines; Kingham, Simon

2007-01-01

Epidemiological studies that examine the relationship between environmental exposures and health often address other determinants of health that may influence the relationship being studied by adjusting for these factors as covariates. While disease surveillance methods routinely control...... for covariates such as deprivation, there has been limited investigative work on the spatial movement of risk at the intraurban scale due to the adjustment. It is important that the nature of any spatial relocation be well understood as a relocation to areas of increased risk may also introduce additional...... localised factors that influence the exposure-response relationship. This paper examines the spatial patterns of relative risk and clusters of hospitalisations based on an illustrative small-area example from Christchurch, New Zealand. A four-stage test of the spatial relocation effects of covariate...

Double inflation: A possible resolution of the large-scale structure problem

International Nuclear Information System (INIS)

Turner, M.S.; Villumsen, J.V.; Vittorio, N.; Silk, J.; Juszkiewicz, R.

1986-11-01

A model is presented for the large-scale structure of the universe in which two successive inflationary phases resulted in large small-scale and small large-scale density fluctuations. This bimodal density fluctuation spectrum in an Ω = 1 universe dominated by hot dark matter leads to large-scale structure of the galaxy distribution that is consistent with recent observational results. In particular, large, nearly empty voids and significant large-scale peculiar velocity fields are produced over scales of ∼100 Mpc, while the small-scale structure over ≤ 10 Mpc resembles that in a low density universe, as observed. Detailed analytical calculations and numerical simulations are given of the spatial and velocity correlations. 38 refs., 6 figs

High Arctic Nitrous Oxide Emissions Found on Large Spatial Scales

Science.gov (United States)

Wilkerson, J. P.; Sayres, D. S.; Dobosy, R.; Anderson, J. G.

2017-12-01

As the planet warms, greenhouse gas emissions from thawing permafrost can potentially increase the net radiative forcing in our climate structure. However, knowledge about Arctic N2O emissions is particularly sparse. Increasing evidence suggests emissions from permafrost thaw may be a significant natural source of N2O. This evidence, though, is either based on lab experiments or in situ chamber studies, which have extremely limited spatial coverage. Consequently, it has not been confirmed to what extent these high emissions are representative of broader arctic regions. Using an airborne eddy covariance flux technique, we measured N2O fluxes over large regions of Alaska in August 2013. From these measurements, we directly show that large areas of this Arctic region have high N2O emissions.

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

Science.gov (United States)

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.

Large sample hydrology in NZ: Spatial organisation in process diagnostics

Science.gov (United States)

McMillan, H. K.; Woods, R. A.; Clark, M. P.

2013-12-01

A key question in hydrology is how to predict the dominant runoff generation processes in any given catchment. This knowledge is vital for a range of applications in forecasting hydrological response and related processes such as nutrient and sediment transport. A step towards this goal is to map dominant processes in locations where data is available. In this presentation, we use data from 900 flow gauging stations and 680 rain gauges in New Zealand, to assess hydrological processes. These catchments range in character from rolling pasture, to alluvial plains, to temperate rainforest, to volcanic areas. By taking advantage of so many flow regimes, we harness the benefits of large-sample and comparative hydrology to study patterns and spatial organisation in runoff processes, and their relationship to physical catchment characteristics. The approach we use to assess hydrological processes is based on the concept of diagnostic signatures. Diagnostic signatures in hydrology are targeted analyses of measured data which allow us to investigate specific aspects of catchment response. We apply signatures which target the water balance, the flood response and the recession behaviour. We explore the organisation, similarity and diversity in hydrological processes across the New Zealand landscape, and how these patterns change with scale. We discuss our findings in the context of the strong hydro-climatic gradients in New Zealand, and consider the implications for hydrological model building on a national scale.

Large scale spatially explicit modeling of blue and green water dynamics in a temperate mid-latitude basin

Science.gov (United States)

Du, Liuying; Rajib, Adnan; Merwade, Venkatesh

2018-07-01

Looking only at climate change impacts provides partial information about a changing hydrologic regime. Understanding the spatio-temporal nature of change in hydrologic processes, and the explicit contributions from both climate and land use drivers, holds more practical value for water resources management and policy intervention. This study presents a comprehensive assessment on the spatio-temporal trend of Blue Water (BW) and Green Water (GW) in a 490,000 km2 temperate mid-latitude basin (Ohio River Basin) over the past 80 years (1935-2014), and from thereon, quantifies the combined as well as relative contributions of climate and land use changes. The Soil and Water Assessment Tool (SWAT) is adopted to simulate hydrologic fluxes. Mann-Kendall and Theil-Sen statistical tests are performed on the modeled outputs to detect respectively the trend and magnitude of changes at three different spatial scales - the entire basin, regional level, and sub-basin level. Despite the overall volumetric increase of both BW and GW in the entire basin, changes in their annual average values during the period of simulation reveal a distinctive spatial pattern. GW has increased significantly in the upper and lower parts of the basin, which can be related to the prominent land use change in those areas. BW has increased significantly only in the lower part, likely being associated with the notable precipitation change there. Furthermore, the simulation under a time-varying climate but constant land use scenario identifies climate change in the Ohio River Basin to be influential on BW, while the impact is relatively nominal on GW; whereas, land use change increases GW remarkably, but is counterproductive on BW. The approach to quantify combined/relative effects of climate and land use change as shown in this study can be replicated to understand BW-GW dynamics in similar large basins around the globe.

Spatial scale of similarity as an indicator of metacommunity stability in exploited marine systems.

Science.gov (United States)

Shackell, Nancy L; Fisher, Jonathan A D; Frank, Kenneth T; Lawton, Peter

2012-01-01

The spatial scale of similarity among fish communities is characteristically large in temperate marine systems: connectivity is enhanced by high rates of dispersal during the larval/juvenile stages and the increased mobility of large-bodied fish. A larger spatial scale of similarity (low beta diversity) is advantageous in heavily exploited systems because locally depleted populations are more likely to be "rescued" by neighboring areas. We explored whether the spatial scale of similarity changed from 1970 to 2006 due to overfishing of dominant, large-bodied groundfish across a 300 000-km2 region of the Northwest Atlantic. Annually, similarities among communities decayed slowly with increasing geographic distance in this open system, but through time the decorrelation distance declined by 33%, concomitant with widespread reductions in biomass, body size, and community evenness. The decline in connectivity stemmed from an erosion of community similarity among local subregions separated by distances as small as 100 km. Larger fish, of the same species, contribute proportionally more viable offspring, so observed body size reductions will have affected maternal output. The cumulative effect of nonlinear maternal influences on egg/larval quality may have compromised the spatial scale of effective larval dispersal, which may account for the delayed recovery of certain member species. Our study adds strong support for using the spatial scale of similarity as an indicator of metacommunity stability both to understand the spatial impacts of exploitation and to refine how spatial structure is used in management plans.

Large-scale spatial and interspecies differences in trace elements and stable isotopes in marine wild fish from Chinese waters

Energy Technology Data Exchange (ETDEWEB)

Zhang, Wei [Key Laboratory of Marine Bio-resources Sustainable Utilization, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301 (China); Graduate School, Chinese Academy of Sciences, Beijing 100049 (China); Wang, Wen-Xiong, E-mail: wwang@ust.hk [Division of Life Science, HKUST, Clear Water Bay, Kowloon (Hong Kong)

2012-05-15

Highlights: Black-Right-Pointing-Pointer A large-scale study on trace element levels in marine wild fish from Chinese waters. Black-Right-Pointing-Pointer Spatial variation found for Al, As, Cd, Cr, Fe, Ni, Pb, but not for Ag, Cu, Mo, Se and Zn. Black-Right-Pointing-Pointer The Pearl River Estuary contained the highest concentrations of Al, Cr, Ni, and Pb. Black-Right-Pointing-Pointer No biomagnification occurred for any of the trace elements studied in marine fish. Black-Right-Pointing-Pointer No obvious health risk from the intake of trace elements through fish consumption. - Abstract: We conducted a large scale investigation of twelve trace element levels and stable isotopes ({delta}{sup 13}C and {delta}{sup 15}N) in twenty-nine marine wild fish species collected from Chinese coastal waters. Trace element levels varied significantly with species. Clear spatial variations were found for Al, As, Cd, Cr, Fe, Ni, and Pb, whereas Ag, Cu, Mo, Se and Zn did not show much spatial variation. The Pearl River Estuary contained the highest concentrations of Al, Cr, Ni, and Pb, whereas the most southern waters (Haikou) contained the lowest concentrations of Al, Fe, and Pb. There was no correlation between log-transformed trace elements concentrations and {delta}{sup 15}N values or {delta}{sup 13}C values, indicating no biomagnification among these trace elements. The calculated hazard quotients (HQ) of 10 elements were less than 1, thus there was no obvious health risk from the intake of trace elements through marine wild fish consumption.

Interaction of valleys and circulation patterns (CPs on spatial precipitation patterns in southern Germany

Directory of Open Access Journals (Sweden)

M. Liu

2013-11-01

Full Text Available Topography exerts influence on the spatial precipitation distribution over different scales, known typically at the large scale as the orographic effect, and at the small scale as the wind-drift rainfall (WDR effect. At the intermediate scale (1~10 km, which is characterized by secondary mountain valleys, topography also demonstrates some effect on the precipitation pattern. This paper investigates such intermediate-scale topographic effects on precipitation patterns, focusing on narrow-steep valleys in the complex terrain of southern Germany, based on the daily observations over a 48 yr period (1960~2007 from a high-density rain-gauge network covering two sub-areas, Baden-Wuerttemberg (BW and Bavaria (BY. Precipitation data at the valley and non-valley stations are compared under consideration of the daily general circulation patterns (CPs classified by a fuzzy rule-based algorithm. Scatter plots of precipitation against elevation demonstrate a different behavior of valley stations comparing to non-valley stations. A detailed study of the precipitation time series for selected station triplets, each consisting of a valley station, a mountain station and an open station have been investigated by statistical analysis with the Kolmogorov–Smirnov (KS test supplemented by the One-way analysis of variance (One-way ANOVA and a graphical comparison of the mean precipitation amounts. The results show an interaction of valley orientation and the direction of the CPs at the intermediate scale, i.e. when the valley is shielded from the CP which carries the precipitation, the precipitation amount within the valley is comparable to that on the mountain crest, and both larger than the precipitation at the open station. When the valley is open to the CP, the precipitation within the valley is similar to the open station but much less than that on the mountain. Such phenomenon where the precipitation is "blind" to the valleys at the intermediate scale

A critical look at spatial scale choices in satellite-based aerosol indirect effect studies

Science.gov (United States)

Grandey, B. S.; Stier, P.

2010-12-01

Analysing satellite datasets over large regions may introduce spurious relationships between aerosol and cloud properties due to spatial variations in aerosol type, cloud regime and synoptic regime climatologies. Using MODerate resolution Imaging Spectroradiometer data, we calculate relationships between aerosol optical depth τa derived liquid cloud droplet effective number concentration Ne and liquid cloud droplet effective radius re at different spatial scales. Generally, positive values of font-size: 10px; color: #000;">dlnNefont-size: 10px; color: #000;">dlnτa are found for ocean regions, whilst negative values occur for many land regions. The spatial distribution of font-size: 10px; color: #000;">dlnrefont-size: 10px; color: #000;">dlnτa shows approximately the opposite pattern, with generally postive values for land regions and negative values for ocean regions. We find that for region sizes larger than 4° × 4°, spurious spatial variations in retrieved cloud and aerosol properties can introduce widespread significant errors to calculations of font-size: 10px; color: #000;">dlnNefont-size: 10px; color: #000;">dlnτa and font-size: 10px; color: #000;">dlnrefont-size: 10px; color: #000;">dlnτa. For regions on the scale of 60° × 60°, these methodological errors may lead to an overestimate in global cloud albedo effect radiative forcing of order 80% relative to that calculated for regions on the scale of 1° × 1°.

Spatial pattern of ASG-EUPOS sites

Science.gov (United States)

Calka, Beata; Bielecka, Elzbieta; Figurski, Mariusz

2017-12-01

The article presents the spatial pattern analysis of the ASG-EUPOS permanent GNSS stations in Poland. Using different methods and tools (nearest neighbour, Riplay's K-function, morphology of Thiessen polygons) we proved that the station distribution model changes within scales. At short distances up to 65 km, which are typical lengths in the network, stations are irregularly dispersed. Increasing this distance to 130 km and over could result in a clustered pattern. The Thiessen polygon area in 72% depends on the level of urbanization, especially coverage of forested and built-up areas as well as the density of the transportation network. The smallest density of the ASG-EUPOS sites is one station over 10,000 sq. km, which is two times more than is stated in the national regulations. The mean distance from ASG-EUPOS location to the nearest station is about 41.5 km.

Fires in large scale ventilation systems

International Nuclear Information System (INIS)

Gregory, W.S.; Martin, R.A.; White, B.W.; Nichols, B.D.; Smith, P.R.; Leslie, I.H.; Fenton, D.L.; Gunaji, M.V.; Blythe, J.P.

1991-01-01

This paper summarizes the experience gained simulating fires in large scale ventilation systems patterned after ventilation systems found in nuclear fuel cycle facilities. The series of experiments discussed included: (1) combustion aerosol loading of 0.61x0.61 m HEPA filters with the combustion products of two organic fuels, polystyrene and polymethylemethacrylate; (2) gas dynamic and heat transport through a large scale ventilation system consisting of a 0.61x0.61 m duct 90 m in length, with dampers, HEPA filters, blowers, etc.; (3) gas dynamic and simultaneous transport of heat and solid particulate (consisting of glass beads with a mean aerodynamic diameter of 10μ) through the large scale ventilation system; and (4) the transport of heat and soot, generated by kerosene pool fires, through the large scale ventilation system. The FIRAC computer code, designed to predict fire-induced transients in nuclear fuel cycle facility ventilation systems, was used to predict the results of experiments (2) through (4). In general, the results of the predictions were satisfactory. The code predictions for the gas dynamics, heat transport, and particulate transport and deposition were within 10% of the experimentally measured values. However, the code was less successful in predicting the amount of soot generation from kerosene pool fires, probably due to the fire module of the code being a one-dimensional zone model. The experiments revealed a complicated three-dimensional combustion pattern within the fire room of the ventilation system. Further refinement of the fire module within FIRAC is needed. (orig.)

spsann - optimization of sample patterns using spatial simulated annealing

Science.gov (United States)

Samuel-Rosa, Alessandro; Heuvelink, Gerard; Vasques, Gustavo; Anjos, Lúcia

2015-04-01

There are many algorithms and computer programs to optimize sample patterns, some private and others publicly available. A few have only been presented in scientific articles and text books. This dispersion and somewhat poor availability is holds back to their wider adoption and further development. We introduce spsann, a new R-package for the optimization of sample patterns using spatial simulated annealing. R is the most popular environment for data processing and analysis. Spatial simulated annealing is a well known method with widespread use to solve optimization problems in the soil and geo-sciences. This is mainly due to its robustness against local optima and easiness of implementation. spsann offers many optimizing criteria for sampling for variogram estimation (number of points or point-pairs per lag distance class - PPL), trend estimation (association/correlation and marginal distribution of the covariates - ACDC), and spatial interpolation (mean squared shortest distance - MSSD). spsann also includes the mean or maximum universal kriging variance (MUKV) as an optimizing criterion, which is used when the model of spatial variation is known. PPL, ACDC and MSSD were combined (PAN) for sampling when we are ignorant about the model of spatial variation. spsann solves this multi-objective optimization problem scaling the objective function values using their maximum absolute value or the mean value computed over 1000 random samples. Scaled values are aggregated using the weighted sum method. A graphical display allows to follow how the sample pattern is being perturbed during the optimization, as well as the evolution of its energy state. It is possible to start perturbing many points and exponentially reduce the number of perturbed points. The maximum perturbation distance reduces linearly with the number of iterations. The acceptance probability also reduces exponentially with the number of iterations. R is memory hungry and spatial simulated annealing is a

Multi-scale temporal and spatial variation in genotypic composition of Cladophora-borne Escherichia coli populations in Lake Michigan.

Science.gov (United States)

Badgley, Brian D; Ferguson, John; Vanden Heuvel, Amy; Kleinheinz, Gregory T; McDermott, Colleen M; Sandrin, Todd R; Kinzelman, Julie; Junion, Emily A; Byappanahalli, Muruleedhara N; Whitman, Richard L; Sadowsky, Michael J

2011-01-01

High concentrations of Escherichia coli in mats of Cladophora in the Great Lakes have raised concern over the continued use of this bacterium as an indicator of microbial water quality. Determining the impacts of these environmentally abundant E. coli, however, necessitates a better understanding of their ecology. In this study, the population structure of 4285 Cladophora-borne E. coli isolates, obtained over multiple three day periods from Lake Michigan Cladophora mats in 2007-2009, was examined by using DNA fingerprint analyses. In contrast to previous studies that have been done using isolates from attached Cladophora obtained over large time scales and distances, the extensive sampling done here on free-floating mats over successive days at multiple sites provided a large dataset that allowed for a detailed examination of changes in population structure over a wide range of spatial and temporal scales. While Cladophora-borne E. coli populations were highly diverse and consisted of many unique isolates, multiple clonal groups were also present and accounted for approximately 33% of all isolates examined. Patterns in population structure were also evident. At the broadest scales, E. coli populations showed some temporal clustering when examined by year, but did not show good spatial distinction among sites. E. coli population structure also showed significant patterns at much finer temporal scales. Populations were distinct on an individual mat basis at a given site, and on individual days within a single mat. Results of these studies indicate that Cladophora-borne E. coli populations consist of a mixture of stable, and possibly naturalized, strains that persist during the life of the mat, and more unique, transient strains that can change over rapid time scales. It is clear that further study of microbial processes at fine spatial and temporal scales is needed, and that caution must be taken when interpolating short term microbial dynamics from results obtained

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

Science.gov (United States)

Barnes, R S K; Hamylton, Sarah

2015-05-01

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

A large-scale forest fragmentation experiment: the Stability of Altered Forest Ecosystems Project

Science.gov (United States)

Ewers, Robert M.; Didham, Raphael K.; Fahrig, Lenore; Ferraz, Gonçalo; Hector, Andy; Holt, Robert D.; Kapos, Valerie; Reynolds, Glen; Sinun, Waidi; Snaddon, Jake L.; Turner, Edgar C.

2011-01-01

Opportunities to conduct large-scale field experiments are rare, but provide a unique opportunity to reveal the complex processes that operate within natural ecosystems. Here, we review the design of existing, large-scale forest fragmentation experiments. Based on this review, we develop a design for the Stability of Altered Forest Ecosystems (SAFE) Project, a new forest fragmentation experiment to be located in the lowland tropical forests of Borneo (Sabah, Malaysia). The SAFE Project represents an advance on existing experiments in that it: (i) allows discrimination of the effects of landscape-level forest cover from patch-level processes; (ii) is designed to facilitate the unification of a wide range of data types on ecological patterns and processes that operate over a wide range of spatial scales; (iii) has greater replication than existing experiments; (iv) incorporates an experimental manipulation of riparian corridors; and (v) embeds the experimentally fragmented landscape within a wider gradient of land-use intensity than do existing projects. The SAFE Project represents an opportunity for ecologists across disciplines to participate in a large initiative designed to generate a broad understanding of the ecological impacts of tropical forest modification. PMID:22006969

A large-scale forest fragmentation experiment: the Stability of Altered Forest Ecosystems Project.

Science.gov (United States)

Ewers, Robert M; Didham, Raphael K; Fahrig, Lenore; Ferraz, Gonçalo; Hector, Andy; Holt, Robert D; Kapos, Valerie; Reynolds, Glen; Sinun, Waidi; Snaddon, Jake L; Turner, Edgar C

2011-11-27

Opportunities to conduct large-scale field experiments are rare, but provide a unique opportunity to reveal the complex processes that operate within natural ecosystems. Here, we review the design of existing, large-scale forest fragmentation experiments. Based on this review, we develop a design for the Stability of Altered Forest Ecosystems (SAFE) Project, a new forest fragmentation experiment to be located in the lowland tropical forests of Borneo (Sabah, Malaysia). The SAFE Project represents an advance on existing experiments in that it: (i) allows discrimination of the effects of landscape-level forest cover from patch-level processes; (ii) is designed to facilitate the unification of a wide range of data types on ecological patterns and processes that operate over a wide range of spatial scales; (iii) has greater replication than existing experiments; (iv) incorporates an experimental manipulation of riparian corridors; and (v) embeds the experimentally fragmented landscape within a wider gradient of land-use intensity than do existing projects. The SAFE Project represents an opportunity for ecologists across disciplines to participate in a large initiative designed to generate a broad understanding of the ecological impacts of tropical forest modification.

Spatial pattern recognition of seismic events in South West Colombia

Science.gov (United States)

Benítez, Hernán D.; Flórez, Juan F.; Duque, Diana P.; Benavides, Alberto; Lucía Baquero, Olga; Quintero, Jiber

2013-09-01

Recognition of seismogenic zones in geographical regions supports seismic hazard studies. This recognition is usually based on visual, qualitative and subjective analysis of data. Spatial pattern recognition provides a well founded means to obtain relevant information from large amounts of data. The purpose of this work is to identify and classify spatial patterns in instrumental data of the South West Colombian seismic database. In this research, clustering tendency analysis validates whether seismic database possesses a clustering structure. A non-supervised fuzzy clustering algorithm creates groups of seismic events. Given the sensitivity of fuzzy clustering algorithms to centroid initial positions, we proposed a methodology to initialize centroids that generates stable partitions with respect to centroid initialization. As a result of this work, a public software tool provides the user with the routines developed for clustering methodology. The analysis of the seismogenic zones obtained reveals meaningful spatial patterns in South-West Colombia. The clustering analysis provides a quantitative location and dispersion of seismogenic zones that facilitates seismological interpretations of seismic activities in South West Colombia.

Exploring the Linkage between Urban Flood Risk and Spatial Patterns in Small Urbanized Catchments of Beijing, China

Directory of Open Access Journals (Sweden)

Lei Yao

2017-02-01

Full Text Available In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area (TIA, Directly Connected Impervious Area (DCIA, and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth (Qt and Qp were simulated by using Strom Water Management Model (SWMM. The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1 imperviousness acts as an effective indicator in affecting both Qt and Qp; (2 reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3 different spatial concentrations of impervious surfaces have inherent influences on Qp. These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management.

Exploring the Linkage between Urban Flood Risk and Spatial Patterns in Small Urbanized Catchments of Beijing, China

Science.gov (United States)

Yao, Lei; Chen, Liding; Wei, Wei

2017-01-01

In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area (TIA), Directly Connected Impervious Area (DCIA), and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth (Qt and Qp) were simulated by using Strom Water Management Model (SWMM). The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1) imperviousness acts as an effective indicator in affecting both Qt and Qp; (2) reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3) different spatial concentrations of impervious surfaces have inherent influences on Qp. These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management. PMID:28264521

Spatial ecology across scales.

Science.gov (United States)

Hastings, Alan; Petrovskii, Sergei; Morozov, Andrew

2011-04-23

The international conference 'Models in population dynamics and ecology 2010: animal movement, dispersal and spatial ecology' took place at the University of Leicester, UK, on 1-3 September 2010, focusing on mathematical approaches to spatial population dynamics and emphasizing cross-scale issues. Exciting new developments in scaling up from individual level movement to descriptions of this movement at the macroscopic level highlighted the importance of mechanistic approaches, with different descriptions at the microscopic level leading to different ecological outcomes. At higher levels of organization, different macroscopic descriptions of movement also led to different properties at the ecosystem and larger scales. New developments from Levy flight descriptions to the incorporation of new methods from physics and elsewhere are revitalizing research in spatial ecology, which will both increase understanding of fundamental ecological processes and lead to tools for better management.

Understanding Adherence and Prescription Patterns Using Large-Scale Claims Data.

Science.gov (United States)

Bjarnadóttir, Margrét V; Malik, Sana; Onukwugha, Eberechukwu; Gooden, Tanisha; Plaisant, Catherine

2016-02-01

Advanced computing capabilities and novel visual analytics tools now allow us to move beyond the traditional cross-sectional summaries to analyze longitudinal prescription patterns and the impact of study design decisions. For example, design decisions regarding gaps and overlaps in prescription fill data are necessary for measuring adherence using prescription claims data. However, little is known regarding the impact of these decisions on measures of medication possession (e.g., medication possession ratio). The goal of the study was to demonstrate the use of visualization tools for pattern discovery, hypothesis generation, and study design. We utilized EventFlow, a novel discrete event sequence visualization software, to investigate patterns of prescription fills, including gaps and overlaps, utilizing large-scale healthcare claims data. The study analyzes data of individuals who had at least two prescriptions for one of five hypertension medication classes: ACE inhibitors, angiotensin II receptor blockers, beta blockers, calcium channel blockers, and diuretics. We focused on those members initiating therapy with diuretics (19.2%) who may have concurrently or subsequently take drugs in other classes as well. We identified longitudinal patterns in prescription fills for antihypertensive medications, investigated the implications of decisions regarding gap length and overlaps, and examined the impact on the average cost and adherence of the initial treatment episode. A total of 790,609 individuals are included in the study sample, 19.2% (N = 151,566) of whom started on diuretics first during the study period. The average age was 52.4 years and 53.1% of the population was female. When the allowable gap was zero, 34% of the population had continuous coverage and the average length of continuous coverage was 2 months. In contrast, when the allowable gap was 30 days, 69% of the population showed a single continuous prescription period with an average length of 5

Patterns of coexistence of two species of freshwater turtles are affected by spatial scale

DEFF Research Database (Denmark)

Segurado, P.; Kunin, W.E.; Filipe, A.F.

2012-01-01

Inferring biotic interactions from the examination of patterns of species occurrences has been a central tenet in community ecology, and it has recently gained interest in the context of single-species distribution modelling. However, understanding of how spatial extent and grain size affect such...

Deterministic patterned growth of high-mobility large-crystal graphene: a path towards wafer scale integration

Science.gov (United States)

Miseikis, Vaidotas; Bianco, Federica; David, Jérémy; Gemmi, Mauro; Pellegrini, Vittorio; Romagnoli, Marco; Coletti, Camilla

2017-06-01

We demonstrate rapid deterministic (seeded) growth of large single-crystals of graphene by chemical vapour deposition (CVD) utilising pre-patterned copper substrates with chromium nucleation sites. Arrays of graphene single-crystals as large as several hundred microns are grown with a periodicity of up to 1 mm. The graphene is transferred to target substrates using aligned and contamination- free semi-dry transfer. The high quality of the synthesised graphene is confirmed by Raman spectroscopy and transport measurements, demonstrating room-temperature carrier mobility of 21 000 cm2 V-1 s-1 when transferred on top of hexagonal boron nitride. By tailoring the nucleation of large single-crystals according to the desired device geometry, it will be possible to produce complex device architectures based on single-crystal graphene, thus paving the way to the adoption of CVD graphene in wafer-scale fabrication.

Spatial structure and scaling of macropores in hydrological process at small catchment scale

Science.gov (United States)

Silasari, Rasmiaditya; Broer, Martine; Blöschl, Günter

2013-04-01

During rainfall events, the formation of overland flow can occur under the circumstances of saturation excess and/or infiltration excess. These conditions are affected by the soil moisture state which represents the soil water content in micropores and macropores. Macropores act as pathway for the preferential flows and have been widely studied locally. However, very little is known about their spatial structure and conductivity of macropores and other flow characteristic at the catchment scale. This study will analyze these characteristics to better understand its importance in hydrological processes. The research will be conducted in Petzenkirchen Hydrological Open Air Laboratory (HOAL), a 64 ha catchment located 100 km west of Vienna. The land use is divided between arable land (87%), pasture (5%), forest (6%) and paved surfaces (2%). Video cameras will be installed on an agricultural field to monitor the overland flow pattern during rainfall events. A wireless soil moisture network is also installed within the monitored area. These field data will be combined to analyze the soil moisture state and the responding surface runoff occurrence. The variability of the macropores spatial structure of the observed area (field scale) then will be assessed based on the topography and soil data. Soil characteristics will be supported with laboratory experiments on soil matrix flow to obtain proper definitions of the spatial structure of macropores and its variability. A coupled physically based distributed model of surface and subsurface flow will be used to simulate the variability of macropores spatial structure and its effect on the flow behaviour. This model will be validated by simulating the observed rainfall events. Upscaling from field scale to catchment scale will be done to understand the effect of macropores variability on larger scales by applying spatial stochastic methods. The first phase in this study is the installation and monitoring configuration of video

Large-scale distribution patterns of mangrove nematodes: A global meta-analysis.

Science.gov (United States)

Brustolin, Marco C; Nagelkerken, Ivan; Fonseca, Gustavo

2018-05-01

Mangroves harbor diverse invertebrate communities, suggesting that macroecological distribution patterns of habitat-forming foundation species drive the associated faunal distribution. Whether these are driven by mangrove biogeography is still ambiguous. For small-bodied taxa, local factors and landscape metrics might be as important as macroecology. We performed a meta-analysis to address the following questions: (1) can richness of mangrove trees explain macroecological patterns of nematode richness? and (2) do local landscape attributes have equal or higher importance than biogeography in structuring nematode richness? Mangrove areas of Caribbean-Southwest Atlantic, Western Indian, Central Indo-Pacific, and Southwest Pacific biogeographic regions. We used random-effects meta-analyses based on natural logarithm of the response ratio (lnRR) to assess the importance of macroecology (i.e., biogeographic regions, latitude, longitude), local factors (i.e., aboveground mangrove biomass and tree richness), and landscape metrics (forest area and shape) in structuring nematode richness from 34 mangroves sites around the world. Latitude, mangrove forest area, and forest shape index explained 19% of the heterogeneity across studies. Richness was higher at low latitudes, closer to the equator. At local scales, richness increased slightly with landscape complexity and decreased with forest shape index. Our results contrast with biogeographic diversity patterns of mangrove-associated taxa. Global-scale nematode diversity may have evolved independently of mangrove tree richness, and diversity of small-bodied metazoans is probably more closely driven by latitude and associated climates, rather than local, landscape, or global biogeographic patterns.

A Multi-Resolution Spatial Model for Large Datasets Based on the Skew-t Distribution

KAUST Repository

Tagle, Felipe

2017-12-06

Large, non-Gaussian spatial datasets pose a considerable modeling challenge as the dependence structure implied by the model needs to be captured at different scales, while retaining feasible inference. Skew-normal and skew-t distributions have only recently begun to appear in the spatial statistics literature, without much consideration, however, for the ability to capture dependence at multiple resolutions, and simultaneously achieve feasible inference for increasingly large data sets. This article presents the first multi-resolution spatial model inspired by the skew-t distribution, where a large-scale effect follows a multivariate normal distribution and the fine-scale effects follow a multivariate skew-normal distributions. The resulting marginal distribution for each region is skew-t, thereby allowing for greater flexibility in capturing skewness and heavy tails characterizing many environmental datasets. Likelihood-based inference is performed using a Monte Carlo EM algorithm. The model is applied as a stochastic generator of daily wind speeds over Saudi Arabia.

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

Directory of Open Access Journals (Sweden)

Nicholas R Vaughn

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

Fine-scale spatial distribution of orchid mycorrhizal fungi in the soil of host-rich grasslands.

Science.gov (United States)

Voyron, Samuele; Ercole, Enrico; Ghignone, Stefano; Perotto, Silvia; Girlanda, Mariangela

2017-02-01

Mycorrhizal fungi are essential for the survival of orchid seedlings under natural conditions. The distribution of these fungi in soil can constrain the establishment and resulting spatial arrangement of orchids at the local scale, but the actual extent of occurrence and spatial patterns of orchid mycorrhizal (OrM) fungi in soil remain largely unknown. We addressed the fine-scale spatial distribution of OrM fungi in two orchid-rich Mediterranean grasslands by means of high-throughput sequencing of fungal ITS2 amplicons, obtained from soil samples collected either directly beneath or at a distance from adult Anacamptis morio and Ophrys sphegodes plants. Like ectomycorrhizal and arbuscular mycobionts, OrM fungi (tulasnelloid, ceratobasidioid, sebacinoid and pezizoid fungi) exhibited significant horizontal spatial autocorrelation in soil. However, OrM fungal read numbers did not correlate with distance from adult orchid plants, and several of these fungi were extremely sporadic or undetected even in the soil samples containing the orchid roots. Orchid mycorrhizal 'rhizoctonias' are commonly regarded as unspecialized saprotrophs. The sporadic occurrence of mycobionts of grassland orchids in host-rich stands questions the view of these mycorrhizal fungi as capable of sustained growth in soil. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

Science.gov (United States)

Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

2016-04-01

Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under

Geo-spatial Cognition on Human's Social Activity Space Based on Multi-scale Grids

Directory of Open Access Journals (Sweden)

ZHAI Weixin

2016-12-01

Full Text Available Widely applied location aware devices, including mobile phones and GPS receivers, have provided great convenience for collecting large volume individuals' geographical information. The researches on the human's society behavior space has attracts an increasingly number of researchers. In our research, based on location-based Flickr data From 2004 to May, 2014 in China, we choose five levels of spatial grids to form the multi-scale frame for investigate the correlation between the scale and the geo-spatial cognition on human's social activity space. The HT-index is selected as the fractal inspired by Alexander to estimate the maturity of the society activity on different scales. The results indicate that that the scale characteristics are related to the spatial cognition to a certain extent. It is favorable to use the spatial grid as a tool to control scales for geo-spatial cognition on human's social activity space.

Spatial Patterns and Interspecific Associations of Three Canopy Species at Different Life Stages in a Subtropical Forest,China

Institute of Scientific and Technical Information of China (English)

Lin Li; Shi-Guang Wei; Zhong-Liang Huang; Wan-Hui Ye; Hong-Lin Cao

2008-01-01

Spatial patterns of species at different life stages are an important aspect for understanding causal mechanisms that facilitate species co-existence.Using Ripley's univariate L(t) and bivariate L12(t) functions,we analyzed the spatial patterns and interspecific associations of three canopy species at different life history stages in a 20-ha subtropical forest plot in Dinghushan Nature Reserve.Based on diameter at breast height (DBH),four life stages were distinguished.Castanopsis chinensis and Schima superba showed a unimodal DBH distribution.Engelhardtia roxburghiana showed a bimodal curve.L(t) function analysis showed significantly aggregated distributions of all three species at later life stages and random distribution at early life stages at some scales.From the analysis of L12(t) function,the results showed the positive association was a dominant pattern for most species pairs at most scales but the intensity of association decreases with the increase of life stages.Juveniles of the three species had no negative intra- and interspecific associations with the older life stages.Only premature trees were suppressed by overmature trees at some scales.Considering these results,we found three canopy-dominant species that lacked regeneration.There was no direct competition occurring between understorey individuals.Young trees can grow well under conspecific species with two other species.Longevity and lack of regeneration led to a large number of trees stored in mature and overmature stages,therefore,intra-and inter-competition can be strong at later life stages.

Spatially-explicit estimation of geographical representation in large-scale species distribution datasets.

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Kalwij, Jesse M; Robertson, Mark P; Ronk, Argo; Zobel, Martin; Pärtel, Meelis

2014-01-01

Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution

Ecological hierarchies and self-organisation - Pattern analysis, modelling and process integration across scales

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Reuter, H.; Jopp, F.; Blanco-Moreno, J. M.; Damgaard, C.; Matsinos, Y.; DeAngelis, D.L.

2010-01-01

A continuing discussion in applied and theoretical ecology focuses on the relationship of different organisational levels and on how ecological systems interact across scales. We address principal approaches to cope with complex across-level issues in ecology by applying elements of hierarchy theory and the theory of complex adaptive systems. A top-down approach, often characterised by the use of statistical techniques, can be applied to analyse large-scale dynamics and identify constraints exerted on lower levels. Current developments are illustrated with examples from the analysis of within-community spatial patterns and large-scale vegetation patterns. A bottom-up approach allows one to elucidate how interactions of individuals shape dynamics at higher levels in a self-organisation process; e.g., population development and community composition. This may be facilitated by various modelling tools, which provide the distinction between focal levels and resulting properties. For instance, resilience in grassland communities has been analysed with a cellular automaton approach, and the driving forces in rodent population oscillations have been identified with an agent-based model. Both modelling tools illustrate the principles of analysing higher level processes by representing the interactions of basic components.The focus of most ecological investigations on either top-down or bottom-up approaches may not be appropriate, if strong cross-scale relationships predominate. Here, we propose an 'across-scale-approach', closely interweaving the inherent potentials of both approaches. This combination of analytical and synthesising approaches will enable ecologists to establish a more coherent access to cross-level interactions in ecological systems. ?? 2010 Gesellschaft f??r ??kologie.

URBAN LANDSCAPE SPATIAL PATTERN ESTIMATION OF CITIES IN SHANDONG PROVINCE USING NIGHTTIME LUMINOSITY DATA

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J. Fan

2017-09-01

Full Text Available China’s cities have been undergoing rapid and intense urbanization processes in the past few decades. Shandong is a coastal province which is located in East China with big economy and population scales, and which also plays an important role in the rapid process of China’s modernization. The DMSP/OLS dataset has been widely used for the urban development assessments in long time-series and large spatial scales situations. In this paper, we used a time series of nighttime light data to estimate the landscape spatial pattern changes of cities in Shandong province from 1994 to 2012. Nine landscape metrics were calculated and analyzed to figure out the spatial patterns of urban area developments of the cities in Shandong province. The landscape metrics include the number of patches (NP, the landscape total area (TA, the aggregation index (AI, the largest patch index (LPI, the mean patch area (AREA_MN, the landscape shape index (LSI, the total edge length (TE, the edge density (ED, and the mean radius of gyration (GYRATE_MN. The experimental results reveal that, in 1994–2012, the total urban area of cities in Shandong province expanded for 1.17 times, the average urban area increased by about 93.00%, the average annual growth rate of the TE metric is 2.67 %, while the ED metric decreased about 1.44 % annually. Bigger cities in this area show relative slower urbanization development processes, such as Jinan and Qingdao. Coastal cities represented much more rapid expansion velocities than inland cities. In the middle area of Shandong province, the connectivity between developed urban areas was constantly increased.

Urban Landscape Spatial Pattern Estimation of Cities in Shandong Province Using Nighttime Luminosity Data

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Fan, J.; He, H.; Hu, T.; Li, G.; Gao, H.; Zhao, X.

2017-09-01

China's cities have been undergoing rapid and intense urbanization processes in the past few decades. Shandong is a coastal province which is located in East China with big economy and population scales, and which also plays an important role in the rapid process of China's modernization. The DMSP/OLS dataset has been widely used for the urban development assessments in long time-series and large spatial scales situations. In this paper, we used a time series of nighttime light data to estimate the landscape spatial pattern changes of cities in Shandong province from 1994 to 2012. Nine landscape metrics were calculated and analyzed to figure out the spatial patterns of urban area developments of the cities in Shandong province. The landscape metrics include the number of patches (NP), the landscape total area (TA), the aggregation index (AI), the largest patch index (LPI), the mean patch area (AREA_MN), the landscape shape index (LSI), the total edge length (TE), the edge density (ED), and the mean radius of gyration (GYRATE_MN). The experimental results reveal that, in 1994-2012, the total urban area of cities in Shandong province expanded for 1.17 times, the average urban area increased by about 93.00%, the average annual growth rate of the TE metric is 2.67 %, while the ED metric decreased about 1.44 % annually. Bigger cities in this area show relative slower urbanization development processes, such as Jinan and Qingdao. Coastal cities represented much more rapid expansion velocities than inland cities. In the middle area of Shandong province, the connectivity between developed urban areas was constantly increased.

Genetic structuring of northern myotis (Myotis septentrionalis) at multiple spatial scales

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Johnson, Joshua B.; Roberts, James H.; King, Timothy L.; Edwards, John W.; Ford, W. Mark; Ray, David A.

2014-01-01

Although groups of bats may be genetically distinguishable at large spatial scales, the effects of forest disturbances, particularly permanent land use conversions on fine-scale population structure and gene flow of summer aggregations of philopatric bat species are less clear. We genotyped and analyzed variation at 10 nuclear DNA microsatellite markers in 182 individuals of the forest-dwelling northern myotis (Myotis septentrionalis) at multiple spatial scales, from within first-order watersheds scaling up to larger regional areas in West Virginia and New York. Our results indicate that groups of northern myotis were genetically indistinguishable at any spatial scale we considered, and the collective population maintained high genetic diversity. It is likely that the ability to migrate, exploit small forest patches, and use networks of mating sites located throughout the Appalachian Mountains, Interior Highlands, and elsewhere in the hibernation range have allowed northern myotis to maintain high genetic diversity and gene flow regardless of forest disturbances at local and regional spatial scales. A consequence of maintaining high gene flow might be the potential to minimize genetic founder effects following population declines caused currently by the enzootic White-nose Syndrome.

Exploring the Ecological Coherence between the Spatial and Temporal Patterns of Bacterioplankton in Boreal Lakes

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Juan Pablo Niño-García

2017-04-01

Full Text Available One of the major contemporary challenges in microbial ecology has been to discriminate the reactive core from the random, unreactive components of bacterial communities. In previous work we used the spatial abundance distributions of bacterioplankton across boreal lakes of Québec to group taxa into four distinct categories that reflect either hydrology-mediated dispersal along the aquatic network or environmental selection mechanisms within lakes. Here, we test whether this categorization derived from the spatial distribution of taxa is maintained over time, by analyzing the temporal dynamics of the operational taxonomic units (OTUs within those spatially derived categories along an annual cycle in the oligotrophic lake Croche (Québec, Canada, and assessing the coherence in the patterns of abundance, occurrence, and environmental range of these OTUs over space and time. We report that the temporal dynamics of most taxa within a single lake are largely coherent with those derived from their spatial distribution over large spatial scales, suggesting that these properties must be intrinsic of particular taxa. We also identified a set of rare taxa cataloged as having a random occupancy based on their spatial distribution, but which showed clear seasonality and abundance peaks along the year, yet these comprised a very small fraction of the total rare OTUs. We conclude that the presence of most rare bacterioplankton taxa in boreal lakes is random, since both their temporal and spatial dynamics suggest links to passive downstream transport and persistence in freshwater networks, rather than environmental selection.

A medium-spatial scale distribution pattern of Pseudoscorpionida (Arachnida in a gradient of topography (altitude and inclination, soil factors, and litter in a central Amazonia forest reserve, Brazil

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N. O. Aguiar

Full Text Available In Amazonia, nothing is known about the distribution of the invertebrates on a medium-spatial scale pattern. In a trail system of 64 km² at Ducke Reserve, we sampled 72 transects using the hand-sorting method and Berlese-Tullgren extraction. The reserve possesses ecosystems of "terra-firme" forest and the trail system represents a gradient of topographic soil factors and vegetation, avoiding categorizations. Considering the abundance and diversity of Pseudoscorpionida, we investigated the relation of the community to environmental factors tested (topography, clay percentage, litter, and soil pH, to the two major drainage basins of the reserve, and if these invertebrates can be used as biological indicators to monitor changes. We registered two species for the first time in the reserve, increasing the known diversity to 17 species. The lack of correlation with the predictor variables and the large home range, indicate that pseudoscorpions are not good biological indicators in the reserve. As the eastern and western watersheds are not separate management units for the community, our results show that they are generalist predators. In spite of our results and lack of knowledge concerning their biology, life history and taxonomy, pseudoscorpions are cosmopolitan and easy to find and measure. Compared with previous studies in the reserve, they have a consistent pattern of abundance and diversity throughout the years showing the stability of the community which can be checked mainly by comparison with environmental changes that would occur in the reserve. An investigation on a medium-spatial scale pattern and over a long-term period including other habitats, and also other predictor variables, like humidity, the structure of the vegetation and canopy closure, will be necessary to reinforce the observed tendencies.

Mapping spatial patterns with morphological image processing

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Peter Vogt; Kurt H. Riitters; Christine Estreguil; Jacek Kozak; Timothy G. Wade; James D. Wickham

2006-01-01

We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as 'perforated,' 'edge,' 'patch,' and 'core' with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the...

Physically-based modeling of topographic effects on spatial evapotranspiration and soil moisture patterns through radiation and wind

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M. Liu

2012-02-01

Full Text Available In this paper, simulations with the Soil Water Atmosphere Plant (SWAP model are performed to quantify the spatial variability of both potential and actual evapotranspiration (ET, and soil moisture content (SMC caused by topography-induced spatial wind and radiation differences. To obtain the spatially distributed ET/SMC patterns, the field scale SWAP model is applied in a distributed way for both pointwise and catchment wide simulations. An adapted radiation model from r.sun and the physically-based meso-scale wind model METRAS PC are applied to obtain the spatial radiation and wind patterns respectively, which show significant spatial variation and correlation with aspect and elevation respectively. Such topographic dependences and spatial variations further propagate to ET/SMC. A strong spatial, seasonal-dependent, scale-relevant intra-catchment variability in daily/annual ET and less variability in SMC can be observed from the numerical experiments. The study concludes that topography has a significant effect on ET/SMC in the humid region where ET is a energy limited rather than water availability limited process. It affects the spatial runoff generation through spatial radiation and wind, therefore should be applied to inform hydrological model development. In addition, the methodology used in the study can serve as a general method for physically-based ET estimation for data sparse regions.

Selection of fire-created snags at two spatial scales by cavity-nesting birds

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Victoria A. Saab; Ree Brannon; Jonathan Dudley; Larry Donohoo; Dave Vanderzanden; Vicky Johnson; Henry Lachowski

2002-01-01

We examined the use of snag stands by seven species of cavity-nesting birds from 1994-1998. Selection of snags was studied in logged and unlogged burned forests at two spatial scales: microhabitat (local vegetation characteristics) and landscape (composition and patterning of surrounding vegetation types). We modeled nest occurrence at the landscape scale by using...

Spatial structure of ion-scale plasma turbulence

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Yasuhito eNarita

2014-03-01

Full Text Available Spatial structure of small-scale plasma turbulence is studied under different conditions of plasma parameter beta directly in the three-dimensional wave vector domain. Two independent approaches are taken: observations of turbulent magnetic field fluctuations in the solar wind measured by four Cluster spacecraft, and direct numerical simulations of plasma turbulence using the hybrid code AIKEF, both resolving turbulence on the ion kinetic scales. The two methods provide independently evidence of wave vector anisotropy as a function of beta. Wave vector anisotropy is characterized primarily by an extension of the energy spectrum in the direction perpendicular to the large-scale magnetic field. The spectrum is strongly anisotropic at lower values of beta, and is more isotropic at higher values of beta. Cluster magnetic field data analysis also provides evidence of axial asymmetry of the spectrum in the directions around the large-scale field. Anisotropy is interpreted as filament formation as plasma evolves into turbulence. Axial asymmetry is interpreted as the effect of radial expansion of the solar wind from the corona.

Spatial patterns of soil organic carbon stocks in Estonian arable soils

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Suuster, Elsa; Astover, Alar; Kõlli, Raimo; Roostalu, Hugo; Reintam, Endla; Penu, Priit

2010-05-01

Soil organic carbon (SOC) determines ecosystem functions, influencing soil fertility, soil physical, chemical and biological properties and crop productivity. Therefore the spatial pattern of SOC stocks and its appropriate management is important at various scales. Due to climate change and the contribution of carbon store in the soils, the national estimates of soil carbon stocks should be determined. Estonian soils have been well studied and mapped at a scale 1:10,000. Previous studies have estimated SOC stocks based on combinations of large groups of Estonian soils and the mean values of the soil profile database, but were not embedded into the geo-referenced databases. These studies have estimated SOC stocks of Estonian arable soils 122.3 Tg. Despite of available soil maps and databases, this information is still very poorly used for spatial soil modelling. The aim of current study is to assess and model spatial pattern of SOC stocks of arable soils on a pilot area Tartu County (area 3089 sq km). Estonian digital soil map and soil monitoring databases are providing a good opportunity to assess SOC stocks at various scales. The qualitative nature of the initial data from a soil map prohibits any straightforward use in modelling. Thus we have used several databases to construct models and linkages between soil properties that can be integrated into soil map. First step was to reorganize the soil map database (44,046 mapping units) so it can be used as an input to modelling. Arable areas were distinguished by a field layer of Agricultural Registers and Information Board, which provides precise information of current land use as it is the basis of paying CAP subsidies. The estimates of SOC content were found by using the arable land evaluation database of Tartu from the Estonian Land Board (comprising 950 sq km and 31,226 fields), where each soil type was assessed separately and average SOC content grouped by texture was derived. SOC content of epipedon varies in

Spatial and temporal patterns of stranded intertidal marine debris: is there a picture of global change?

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Browne, Mark Anthony; Chapman, M Gee; Thompson, Richard C; Amaral Zettler, Linda A; Jambeck, Jenna; Mallos, Nicholas J

2015-06-16

Floating and stranded marine debris is widespread. Increasing sea levels and altered rainfall, solar radiation, wind speed, waves, and oceanic currents associated with climatic change are likely to transfer more debris from coastal cities into marine and coastal habitats. Marine debris causes economic and ecological impacts, but understanding the scope of these requires quantitative information on spatial patterns and trends in the amounts and types of debris at a global scale. There are very few large-scale programs to measure debris, but many peer-reviewed and published scientific studies of marine debris describe local patterns. Unfortunately, methods of defining debris, sampling, and interpreting patterns in space or time vary considerably among studies, yet if data could be synthesized across studies, a global picture of the problem may be avaliable. We analyzed 104 published scientific papers on marine debris in order to determine how to evaluate this. Although many studies were well designed to answer specific questions, definitions of what constitutes marine debris, the methods used to measure, and the scale of the scope of the studies means that no general picture can emerge from this wealth of data. These problems are detailed to guide future studies and guidelines provided to enable the collection of more comparable data to better manage this growing problem.

Characterizing the spatial variations and correlations of large rainstorms for landslide study

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L. Gao

2017-09-01

Full Text Available Rainfall is the primary trigger of landslides in Hong Kong; hence, rainstorm spatial distribution is an important piece of information in landslide hazard analysis. The primary objective of this paper is to quantify spatial correlation characteristics of three landslide-triggering large storms in Hong Kong. The spatial maximum rolling rainfall is represented by a rotated ellipsoid trend surface and a random field of residuals. The maximum rolling 4, 12, 24, and 36 h rainfall amounts of these storms are assessed via surface trend fitting, and the spatial correlation of the detrended residuals is determined through studying the scales of fluctuation along eight directions. The principal directions of the surface trend are between 19 and 43°, and the major and minor axis lengths are 83–386 and 55–79 km, respectively. The scales of fluctuation of the residuals are found between 5 and 30 km. The spatial distribution parameters for the three large rainstorms are found to be similar to those for four ordinary rainfall events. The proposed rainfall spatial distribution model and parameters help define the impact area, rainfall intensity and local topographic effects for landslide hazard evaluation in the future.

Parameter Scaling for Epidemic Size in a Spatial Epidemic Model with Mobile Individuals.

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Chiyori T Urabe

Full Text Available In recent years, serious infectious diseases tend to transcend national borders and widely spread in a global scale. The incidence and prevalence of epidemics are highly influenced not only by pathogen-dependent disease characteristics such as the force of infection, the latent period, and the infectious period, but also by human mobility and contact patterns. However, the effect of heterogeneous mobility of individuals on epidemic outcomes is not fully understood. Here, we aim to elucidate how spatial mobility of individuals contributes to the final epidemic size in a spatial susceptible-exposed-infectious-recovered (SEIR model with mobile individuals in a square lattice. After illustrating the interplay between the mobility parameters and the other parameters on the spatial epidemic spreading, we propose an index as a function of system parameters, which largely governs the final epidemic size. The main contribution of this study is to show that the proposed index is useful for estimating how parameter scaling affects the final epidemic size. To demonstrate the effectiveness of the proposed index, we show that there is a positive correlation between the proposed index computed with the real data of human airline travels and the actual number of positive incident cases of influenza B in the entire world, implying that the growing incidence of influenza B is attributed to increased human mobility.

Spatial Heterogeneity, Scale, Data Character and Sustainable Transport in the Big Data Era

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Jiang, Bin

2018-04-01

In light of the emergence of big data, I have advocated and argued for a paradigm shift from Tobler's law to scaling law, from Euclidean geometry to fractal geometry, from Gaussian statistics to Paretian statistics, and - more importantly - from Descartes' mechanistic thinking to Alexander's organic thinking. Fractal geometry falls under the third definition of fractal - that is, a set or pattern is fractal if the scaling of far more small things than large ones recurs multiple times (Jiang and Yin 2014) - rather than under the second definition of fractal, which requires a power law between scales and details (Mandelbrot 1982). The new fractal geometry is more towards living geometry that "follows the rules, constraints, and contingent conditions that are, inevitably, encountered in the real world" (Alexander et al. 2012, p. 395), not only for understanding complexity, but also for creating complex or living structure (Alexander 2002-2005). This editorial attempts to clarify why the paradigm shift is essential and to elaborate on several concepts, including spatial heterogeneity (scaling law), scale (or the fourth meaning of scale), data character (in contrast to data quality), and sustainable transport in the big data era.

Post-fire spatial patterns of soil nitrogen mineralization and microbial abundance.

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Erica A H Smithwick

Full Text Available 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 21(st Century.

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

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

2018-01-01

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

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

International Nuclear Information System (INIS)

Li Yu-Ye; Ding Xue-Li

2014-01-01

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. (interdisciplinary physics and related areas of science and technology)

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

Science.gov (United States)

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.

Local and regional effects of large scale atmospheric circulation patterns on winter wind power output in Western Europe

Science.gov (United States)

Zubiate, Laura; McDermott, Frank; Sweeney, Conor; O'Malley, Mark

2014-05-01

Recent studies (Brayshaw, 2009, Garcia-Bustamante, 2010, Garcia-Bustamante, 2013) have drawn attention to the sensitivity of wind speed distributions and likely wind energy power output in Western Europe to changes in low-frequency, large scale atmospheric circulation patterns such as the North Atlantic Oscillation (NAO). Wind speed variations and directional shifts as a function of the NAO state can be larger or smaller depending on the North Atlantic region that is considered. Wind speeds in Ireland and the UK for example are approximately 20 % higher during NAO + phases, and up to 30 % lower during NAO - phases relative to the long-term (30 year) climatological means. By contrast, in southern Europe, wind speeds are 15 % lower than average during NAO + phases and 15 % higher than average during NAO - phases. Crucially however, some regions such as Brittany in N.W. France have been identified in which there is negligible variability in wind speeds as a function of the NAO phase, as observed in the ERA-Interim 0.5 degree gridded reanalysis database. However, the magnitude of these effects on wind conditions is temporally and spatially non-stationary. As described by Comas-Bru and McDermott (2013) for temperature and precipitation, such non-stationarity is caused by the influence of two other patterns, the East Atlantic pattern, (EA), and the Scandinavian pattern, (SCA), which modulate the position of the NAO dipole. This phenomenon has also implications for wind speeds and directions, which has been assessed using the ERA-Interim reanalysis dataset and the indices obtained from the PC analysis of sea level pressure over the Atlantic region. In order to study the implications for power production, the interaction of the NAO and the other teleconnection patterns with local topography was also analysed, as well as how these interactions ultimately translate into wind power output. The objective is to have a better defined relationship between wind speed and power

North Atlantic cyclones; trends, impacts and links to large-scale variability

Science.gov (United States)

Trigo, R. M.; Trigo, I. F.; Ramos, A. M.; Paredes, D.; Garcia-Herrera, R.; Liberato, M. L. R.; Valente, M. A.

2009-04-01

Based on the cyclone detection and tracking algorithm previously developed (Trigo, 2006) we have assessed the inter-annual variability and cyclone frequency trends between 1960 and 2000 for the Euro-Atlantic sector using the highest spatial resolution available (1.125° x 1.125°) from the ERA-40 Surface Level Pressure. Additionally, trends for the u and v wind speed components are also computed at the monthly and seasonal scales, using the same dataset. All cyclone and wind speed trend maps were computed with the corresponding statistical significance field. Results reveal a significant frequency decrease (increase) in the western Mediterranean (Greenland and Scandinavia), particularly in December, February and March. Seasonal and monthly analysis of wind speed trends shows similar spatial patterns. We show that these changes in the frequency of low pressure centers and the associated wind patterns are partially responsible for trends of the significant height of waves. Throughout the extended winter months (ONDJFM), regions with positive (negative) wind magnitude trends, of up to 5 cm/s per year, often correspond to regions of positive (negative) significant wave height trends. The cyclone and wind speed trends computed for the JFM months are well matched by the corresponding trends in significant wave height, with February being the month with the highest trends (negative south of 50°N up to -3 cm/year, and positive up to 5cm/year just north of Scotland). Using precipitation data from ECMWF reanalyses and a CRU high resolution dataset we show the impact of these trends in cyclone frequencies upon the corresponding precipitation trends in the influenced areas. It is also shown that these changes are partially linked to major shifts on the indices of large-scale patterns modes, namely the North Atlantic Oscillation (NAO), the Eastern Atlantic (EA) and the Scandinavian Patterns (SCAN). Trigo, I. F. 2006: Climatology and Interannual Variability of Storm-Tracks in

Large scale electrolysers

International Nuclear Information System (INIS)

B Bello; M Junker

2006-01-01

Hydrogen production by water electrolysis represents nearly 4 % of the world hydrogen production. Future development of hydrogen vehicles will require large quantities of hydrogen. Installation of large scale hydrogen production plants will be needed. In this context, development of low cost large scale electrolysers that could use 'clean power' seems necessary. ALPHEA HYDROGEN, an European network and center of expertise on hydrogen and fuel cells, has performed for its members a study in 2005 to evaluate the potential of large scale electrolysers to produce hydrogen in the future. The different electrolysis technologies were compared. Then, a state of art of the electrolysis modules currently available was made. A review of the large scale electrolysis plants that have been installed in the world was also realized. The main projects related to large scale electrolysis were also listed. Economy of large scale electrolysers has been discussed. The influence of energy prices on the hydrogen production cost by large scale electrolysis was evaluated. (authors)

Large-scale movements in European badgers: has the tail of the movement kernel been underestimated?

Science.gov (United States)

Byrne, Andrew W; Quinn, John L; O'Keeffe, James J; Green, Stuart; Sleeman, D Paddy; Martin, S Wayne; Davenport, John

2014-07-01

Characterizing patterns of animal movement is a major aim in population ecology, and yet doing so at an appropriate spatial scale remains a major challenge. Estimating the frequency and distances of movements is of particular importance when species are implicated in the transmission of zoonotic diseases. European badgers (Meles meles) are classically viewed as exhibiting limited dispersal, and yet their movements bring them into conflict with farmers due to their potential to spread bovine tuberculosis in parts of their range. Considerable uncertainty surrounds the movement potential of badgers, and this may be related to the spatial scale of previous empirical studies. We conducted a large-scale mark-recapture study (755 km(2); 2008-2012; 1935 capture events; 963 badgers) to investigate movement patterns in badgers, and undertook a comparative meta-analysis using published data from 15 European populations. The dispersal movement (>1 km) kernel followed an inverse power-law function, with a substantial 'tail' indicating the occurrence of rare long-distance dispersal attempts during the study period. The mean recorded distance from this distribution was 2.6 km, the 95 percentile was 7.3 km and the longest recorded was 22.1 km. Dispersal frequency distributions were significantly different between genders; males dispersed more frequently than females, but females made proportionally more long-distance dispersal attempts than males. We used a subsampling approach to demonstrate that the appropriate minimum spatial scale to characterize badger movements in our study population was 80 km(2), substantially larger than many previous badger studies. Furthermore, the meta-analysis indicated a significant association between maximum movement distance and study area size, while controlling for population density. Maximum long-distance movements were often only recorded by chance beyond the boundaries of study areas. These findings suggest that the tail of the badger

Spatial patterns of development drive water use

Science.gov (United States)

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

2018-01-01

Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land...

Macroecology of unicellular organisms - patterns and processes.

Science.gov (United States)

Soininen, Janne

2012-02-01

Macroecology examines the relationship between organisms and their environment at large spatial (and temporal) scales. Typically, macroecologists explain the large-scale patterns of abundance, distribution and diversity. Despite the difficulties in sampling and characterizing microbial diversity, macroecologists have recently also been interested in unicellular organisms. Here, I review the current advances made in microbial macroecology, as well as discuss related ecosystem functions. Overall, it seems that microorganisms suit surprisingly well to known species abundance distributions and show positive relationship between distribution and adundance. Microbial species-area and distance-decay relationships tend to be weaker than for macroorganisms, but nonetheless significant. Few findings on altitudinal gradients in unicellular taxa seem to differ greatly from corresponding findings for larger taxa, whereas latitudinal gradients among microorganisms have either been clearly evident or absent depending on the context. Literature also strongly emphasizes the role of spatial scale for the patterns of diversity and suggests that patterns are affected by species traits as well as ecosystem characteristics. Finally, I discuss the large role of local biotic and abiotic variables driving the community assembly in unicellular taxa and eventually dictating how multiple ecosystem processes are performed. Present review highlights the fact that most microorganisms may not differ fundamentally from larger taxa in their large-scale distribution patterns. Yet, review also shows that many aspects of microbial macroecology are still relatively poorly understood and specific patterns depend on focal taxa and ecosystem concerned. © 2011 Society for Applied Microbiology and Blackwell Publishing Ltd.

Homogenization of Large-Scale Movement Models in Ecology

Science.gov (United States)

Garlick, M.J.; Powell, J.A.; Hooten, M.B.; McFarlane, L.R.

2011-01-01

A difficulty in using diffusion models to predict large scale animal population dispersal is that individuals move differently based on local information (as opposed to gradients) in differing habitat types. This can be accommodated by using ecological diffusion. However, real environments are often spatially complex, limiting application of a direct approach. Homogenization for partial differential equations has long been applied to Fickian diffusion (in which average individual movement is organized along gradients of habitat and population density). We derive a homogenization procedure for ecological diffusion and apply it to a simple model for chronic wasting disease in mule deer. Homogenization allows us to determine the impact of small scale (10-100 m) habitat variability on large scale (10-100 km) movement. The procedure generates asymptotic equations for solutions on the large scale with parameters defined by small-scale variation. The simplicity of this homogenization procedure is striking when compared to the multi-dimensional homogenization procedure for Fickian diffusion,and the method will be equally straightforward for more complex models. ?? 2010 Society for Mathematical Biology.

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

Science.gov (United States)

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

Approaches to large scale unsaturated flow in heterogeneous, stratified, and fractured geologic media

International Nuclear Information System (INIS)

Ababou, R.

1991-08-01

This report develops a broad review and assessment of quantitative modeling approaches and data requirements for large-scale subsurface flow in radioactive waste geologic repository. The data review includes discussions of controlled field experiments, existing contamination sites, and site-specific hydrogeologic conditions at Yucca Mountain. Local-scale constitutive models for the unsaturated hydrodynamic properties of geologic media are analyzed, with particular emphasis on the effect of structural characteristics of the medium. The report further reviews and analyzes large-scale hydrogeologic spatial variability from aquifer data, unsaturated soil data, and fracture network data gathered from the literature. Finally, various modeling strategies toward large-scale flow simulations are assessed, including direct high-resolution simulation, and coarse-scale simulation based on auxiliary hydrodynamic models such as single equivalent continuum and dual-porosity continuum. The roles of anisotropy, fracturing, and broad-band spatial variability are emphasized. 252 refs

Human seizures couple across spatial scales through travelling wave dynamics

Science.gov (United States)

Martinet, L.-E.; Fiddyment, G.; Madsen, J. R.; Eskandar, E. N.; Truccolo, W.; Eden, U. T.; Cash, S. S.; Kramer, M. A.

2017-04-01

Epilepsy--the propensity toward recurrent, unprovoked seizures--is a devastating disease affecting 65 million people worldwide. Understanding and treating this disease remains a challenge, as seizures manifest through mechanisms and features that span spatial and temporal scales. Here we address this challenge through the analysis and modelling of human brain voltage activity recorded simultaneously across microscopic and macroscopic spatial scales. We show that during seizure large-scale neural populations spanning centimetres of cortex coordinate with small neural groups spanning cortical columns, and provide evidence that rapidly propagating waves of activity underlie this increased inter-scale coupling. We develop a corresponding computational model to propose specific mechanisms--namely, the effects of an increased extracellular potassium concentration diffusing in space--that support the observed spatiotemporal dynamics. Understanding the multi-scale, spatiotemporal dynamics of human seizures--and connecting these dynamics to specific biological mechanisms--promises new insights to treat this devastating disease.

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

Science.gov (United States)

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

2018-01-01

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

West African spatial patterns of economic activities

DEFF Research Database (Denmark)

Walther, Olivier; Howard, Allen; Retaillé, Denis

2015-01-01

Over the last 30 years, two different bodies of literature developed by both US historians and francophone geographers have moved toward similar conclusions regarding West African economic spatial patterns. Despite their different backgrounds, both the ‘spatial factor’ approach promoted by histor......Over the last 30 years, two different bodies of literature developed by both US historians and francophone geographers have moved toward similar conclusions regarding West African economic spatial patterns. Despite their different backgrounds, both the ‘spatial factor’ approach promoted...... by historians and the ‘mobile space’ approach developed by geographers view exchange centres as nodes of transnational trade networks and places in production territories, and perceive spatial dynamics as highly dependent on shifts of trade flows and production activities. The objective of this article...

Learning scale-variant and scale-invariant features for deep image classification

NARCIS (Netherlands)

van Noord, Nanne; Postma, Eric

Convolutional Neural Networks (CNNs) require large image corpora to be trained on classification tasks. The variation in image resolutions, sizes of objects and patterns depicted, and image scales, hampers CNN training and performance, because the task-relevant information varies over spatial

Spatial correlations, clustering and percolation-like transitions in homicide crimes

Science.gov (United States)

Alves, L. G. A.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2015-07-01

The spatial dynamics of criminal activities has been recently studied through statistical physics methods; however, models and results have been focusing on local scales (city level) and much less is known about these patterns at larger scales, e.g. at a country level. Here we report on a characterization of the spatial dynamics of the homicide crimes along the Brazilian territory using data from all cities (˜5000) in a period of more than thirty years. Our results show that the spatial correlation function in the per capita homicides decays exponentially with the distance between cities and that the characteristic correlation length displays an acute increasing trend in the latest years. We also investigate the formation of spatial clusters of cities via a percolation-like analysis, where clustering of cities and a phase-transition-like behavior describing the size of the largest cluster as a function of a homicide threshold are observed. This transition-like behavior presents evolutive features characterized by an increasing in the homicide threshold (where the transitions occur) and by a decreasing in the transition magnitudes (length of the jumps in the cluster size). We believe that our work sheds new light on the spatial patterns of criminal activities at large scales, which may contribute for better political decisions and resources allocation as well as opens new possibilities for modeling criminal activities by setting up fundamental empirical patterns at large scales.

Long-term Observations of Intense Precipitation Small-scale Spatial Variability in a Semi-arid Catchment

Science.gov (United States)

Cropp, E. L.; Hazenberg, P.; Castro, C. L.; Demaria, E. M.

2017-12-01

In the southwestern US, the summertime North American Monsoon (NAM) provides about 60% of the region's annual precipitation. Recent research using high-resolution atmospheric model simulations and retrospective predictions has shown that since the 1950's, and more specifically in the last few decades, the mean daily precipitation in the southwestern U.S. during the NAM has followed a decreasing trend. Furthermore, days with more extreme precipitation have intensified. The current work focuses the impact of these long-term changes on the observed small-scale spatial variability of intense precipitation. Since limited long-term high-resolution observational data exist to support such climatological-induced spatial changes in precipitation frequency and intensity, the current work utilizes observations from the USDA-ARS Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Within this 150 km^2 catchment over 90 rain gauges have been installed since the 1950s, measuring at sub-hourly resolution. We have applied geospatial analyses and the kriging interpolation technique to identify long-term changes in the spatial and temporal correlation and anisotropy of intense precipitation. The observed results will be compared with the previously model simulated results, as well as related to large-scale variations in climate patterns, such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO).

Spatial patterns in accretion on barrier-island salt marshes

NARCIS (Netherlands)

Groot, de A.V.; Veeneklaas, R.M.; Kuijper, D.P.J.; Bakker, J.P.

2011-01-01

On minerogenic barrier-island salt marshes, sedimentation is spatially heterogeneous. Although the main forcing factors for sedimentation are known, much less is known about the characteristic sizes of this spatial patterning. Such patterning gives information on the spatial component of salt-marsh

Environment and host as large-scale controls of ectomycorrhizal fungi.

Science.gov (United States)

van der Linde, Sietse; Suz, Laura M; Orme, C David L; Cox, Filipa; Andreae, Henning; Asi, Endla; Atkinson, Bonnie; Benham, Sue; Carroll, Christopher; Cools, Nathalie; De Vos, Bruno; Dietrich, Hans-Peter; Eichhorn, Johannes; Gehrmann, Joachim; Grebenc, Tine; Gweon, Hyun S; Hansen, Karin; Jacob, Frank; Kristöfel, Ferdinand; Lech, Paweł; Manninger, Miklós; Martin, Jan; Meesenburg, Henning; Merilä, Päivi; Nicolas, Manuel; Pavlenda, Pavel; Rautio, Pasi; Schaub, Marcus; Schröck, Hans-Werner; Seidling, Walter; Šrámek, Vít; Thimonier, Anne; Thomsen, Iben Margrete; Titeux, Hugues; Vanguelova, Elena; Verstraeten, Arne; Vesterdal, Lars; Waldner, Peter; Wijk, Sture; Zhang, Yuxin; Žlindra, Daniel; Bidartondo, Martin I

2018-06-06

Explaining the large-scale diversity of soil organisms that drive biogeochemical processes-and their responses to environmental change-is critical. However, identifying consistent drivers of belowground diversity and abundance for some soil organisms at large spatial scales remains problematic. Here we investigate a major guild, the ectomycorrhizal fungi, across European forests at a spatial scale and resolution that is-to our knowledge-unprecedented, to explore key biotic and abiotic predictors of ectomycorrhizal diversity and to identify dominant responses and thresholds for change across complex environmental gradients. We show the effect of 38 host, environment, climate and geographical variables on ectomycorrhizal diversity, and define thresholds of community change for key variables. We quantify host specificity and reveal plasticity in functional traits involved in soil foraging across gradients. We conclude that environmental and host factors explain most of the variation in ectomycorrhizal diversity, that the environmental thresholds used as major ecosystem assessment tools need adjustment and that the importance of belowground specificity and plasticity has previously been underappreciated.

Investigating Spatial Patterns of Persistent Scatterer Interferometry Point Targets and Landslide Occurrences in the Arno River Basin

Directory of Open Access Journals (Sweden)

Ping Lu

2014-07-01

Full Text Available Persistent Scatterer Interferometry (PSI has been widely used for landslide studies in recent years. This paper investigated the spatial patterns of PSI point targets and landslide occurrences in the Arno River basin in Central Italy. The main purpose is to analyze whether spatial patterns of Persistent Scatterers (PS can be recognized as indicators of landslide occurrences throughout the whole basin. The bivariate K-function was employed to assess spatial relationships between PS and landslides. The PSI point targets were acquired from almost 4 years (from March 2003 to January 2007 of RADARSAT-1 images. The landslide inventory was collected from 15 years (from 1992–2007 of surveying and mapping data, mainly including remote sensing data, topographic maps and field investigations. The proposed approach is able to assess spatial patterns between a variety of PS and landslides, in particular, to understand if PSI point targets are spatially clustered (spatial attraction or randomly distributed (spatial independency on various types of landslides across the basin. Additionally, the degree and scale distances of PS clustering on a variety of landslides can be characterized. The results rejected the null hypothesis that PSI point targets appear to cluster similarly on four types of landslides (slides, flows, falls and creeps in the Arno River basin. Significant influence of PS velocities and acquisition orbits can be noticed on detecting landslides with different states of activities. Despite that the assessment may be influenced by the quality of landslide inventory and Synthetic Aperture Radar (SAR images, the proposed approach is expected to provide guidelines for studies trying to detect and investigate landslide occurrences at a regional scale through spatial statistical analysis of PS, for which an advanced understanding of the impact of scale distances on landslide clustering is fundamentally needed.

Large grazers modify effects of aboveground-belowground interactions on small-scale plant community composition

NARCIS (Netherlands)

Veen, G. F. (Ciska); Geuverink, Elzemiek; Olff, Han; Schmid, Bernhard

Aboveground and belowground organisms influence plant community composition by local interactions, and their scale of impact may vary from millimeters belowground to kilometers aboveground. However, it still poorly understood how large grazers that select their forage on large spatial scales

Large grazers modify effects of aboveground–belowground interactions on small-scale plant community composition

NARCIS (Netherlands)

Veen, G.F.; Geuverink, E.; Olff, H.

2012-01-01

Aboveground and belowground organisms influence plant community composition by local interactions, and their scale of impact may vary from millimeters belowground to kilometers aboveground. However, it still poorly understood how large grazers that select their forage on large spatial scales

Spatial Pattern, Transportation and Air Quality Nexus: The Case of Iskandar Malaysia

Directory of Open Access Journals (Sweden)

Azalia Mohd Yusop

2016-09-01

Full Text Available Spatial pattern, transportation, and air quality are three development entities which significantly affecting one another. This nexus exhibits the urbanization imprint accouter transportation generating air pollution as a reflection of spatial distribution. The integration among them is a vital part of development as it affects the societal living environment. It provides unfavorable air quality and directly cause health problems. The developing region of Iskandar Malaysia exhibits huge spatial distribution transformation accompanied by large percentage of urbanization rate, but seems less integration of land use and transportation planning which causes the exaggeration of air pollution. We carry out the research on the nexus of spatial distribution, transportation and air quality in Iskandar Malaysia by analyzing and evaluating the interconnectivity of these three entities. The spatial analysis and evaluation on the land use development pattern and spatial policy shows that the Iskandar development region are growing in the polycentric manners, where the spatial development policy drives the distributional growth of new sub-centers. We undertook a household-based travel survey that reveals the poly-centricity reflected by the de-concentration of workplaces which shifted from the single point towards multiple centers. On the other hand, this phenomenon has created a distributional traffic pattern amid the high dependency on the private vehicles of the citizens in Iskandar Malaysia. With a predominantly fossil fuel consuming vehicles, this has generated air pollution. Based on the traffic survey and the dependency of the citizens on private cars for their daily mobility, the concentration of air pollution is seemingly at risk. This research reflects that Iskandar Malaysia development region currently undergoes towards polycentric development with some new urban centers. We found that land use and transportation planning policies require serious

N2O emission hotspots at different spatial scales and governing factors for small scale hotspots

International Nuclear Information System (INIS)

Heuvel, R.N. van den; Hefting, M.M.; Tan, N.C.G.; Jetten, M.S.M.; Verhoeven, J.T.A.

2009-01-01

Chronically nitrate-loaded riparian buffer zones show high N 2 O emissions. Often, a large part of the N 2 O is emitted from small surface areas, resulting in high spatial variability in these buffer zones. These small surface areas with high N 2 O emissions (hotspots) need to be investigated to generate knowledge on the factors governing N 2 O emissions. In this study the N 2 O emission variability was investigated at different spatial scales. Therefore N 2 O emissions from three 32 m 2 grids were determined in summer and winter. Spatial variation and total emission were determined on three different scales (0.3 m 2 , 0.018 m 2 and 0.0013 m 2 ) at plots with different levels of N 2 O emissions. Spatial variation was high at all scales determined and highest at the smallest scale. To test possible factors inducing small scale hotspots, soil samples were collected for slurry incubation to determine responses to increased electron donor/acceptor availability. Acetate addition did increase N 2 O production, but nitrate addition failed to increase total denitrification or net N 2 O production. N 2 O production was similar in all soil slurries, independent of their origin from high or low emission soils, indicating that environmental conditions (including physical factors like gas diffusion) rather than microbial community composition governed N 2 O emission rates

A multitracer approach to assess the spatial contamination pattern of hake (Merluccius merluccius) in the French Mediterranean.

Science.gov (United States)

Cresson, Pierre; Bouchoucha, Marc; Morat, Fabien; Miralles, Francoise; Chavanon, Fabienne; Loizeau, Veronique; Cossa, Daniel

2015-11-01

Chemical contamination levels and stable isotope ratios provide integrated information about contaminant exposure, trophic position and also biological and environmental influences on marine organisms. By combining these approaches with otolith shape analyses, the aim of the present study was to document the spatial variability of Hg and PCB contamination of the European hake (Merluccius merluccius) in the French Mediterranean, hypothesizing that local contaminant sources, environmental conditions and biological specificities lead to site-specific contamination patterns. High Hg concentrations discriminated Corsica (average: 1.36 ± 0.80 μg g(-1) dm) from the Gulf of Lions (average valuesLions, whatever the sex of the individuals, whereas the highest values in Corsica were 6.75 ± 4.22 ng g(-1) dm. Otolith shape discriminated juveniles and adults, due to their different habitats. The use of combined ecotracers was revealed as a powerful tool to discriminate between fish populations at large and small spatial scale, and to enable understanding of the environmental and biological influences on contamination patterns. Copyright © 2015 Elsevier B.V. All rights reserved.

Spatial epidemiological techniques in cholera mapping and analysis towards a local scale predictive modelling

Science.gov (United States)

Rasam, A. R. A.; Ghazali, R.; Noor, A. M. M.; Mohd, W. M. N. W.; Hamid, J. R. A.; Bazlan, M. J.; Ahmad, N.

2014-02-01

Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia.

Spatial epidemiological techniques in cholera mapping and analysis towards a local scale predictive modelling

International Nuclear Information System (INIS)

Rasam, A R A; Ghazali, R; Noor, A M M; Mohd, W M N W; Hamid, J R A; Bazlan, M J; Ahmad, N

2014-01-01

Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia

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

Directory of Open Access Journals (Sweden)

M. C. Demirel

2018-02-01

Full Text Available 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

Source/sink patterns of disturbance and cross-scale mismatches in a panarchy of social-ecological landscapes

Science.gov (United States)

Nicola Zaccarelli; Irene Petrosillo; Giovanni Zurlini; Kurt H. Riitters

2008-01-01

Land-use change is one of the major factors affecting global environmental change and represents a primary human effect on natural systems. Taking into account the scales and patterns of human land uses as source/sink disturbance systems, we describe a framework to characterize and interpret the spatial patterns of disturbances along a continuum of scales in a panarchy...

Response of coral assemblages to thermal stress: are bleaching intensity and spatial patterns consistent between events?

Science.gov (United States)

Penin, Lucie; Vidal-Dupiol, Jeremie; Adjeroud, Mehdi

2013-06-01

Mass bleaching events resulting in coral mortality are among the greatest threats to coral reefs, and are projected to increase in frequency and intensity with global warming. Achieving a better understanding of the consistency of the response of coral assemblages to thermal stress, both spatially and temporally, is essential to determine which reefs are more able to tolerate climate change. We compared variations in spatial and taxonomic patterns between two bleaching events at the scale of an island (Moorea Island, French Polynesia). Despite similar thermal stress and light conditions, bleaching intensity was significantly lower in 2007 (approximately 37 % of colonies showed signs of bleaching) than in 2002, when 55 % of the colonies bleached. Variations in the spatial patterns of bleaching intensity were consistent between the two events. Among nine sampling stations at three locations and three depths, the stations at which the bleaching response was lowest in 2002 were those that showed the lowest levels of bleaching in 2007. The taxonomic patterns of susceptibility to bleaching were also consistent between the two events. These findings have important implications for conservation because they indicate that corals are capable of acclimatization and/or adaptation and that, even at small spatial scales, some areas are consistently more susceptible to bleaching than others.

Scaling local species-habitat relations to the larger landscape with a hierarchical spatial count model

Science.gov (United States)

Thogmartin, W.E.; Knutson, M.G.

2007-01-01

Much of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species. ?? 2006 Springer Science+Business Media B.V.

First Mile Challenges for Large-Scale IoT

KAUST Repository

Bader, Ahmed

2017-03-16

The Internet of Things is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the sheer scale of spatial traffic intensity that must be accommodated, primarily in the uplink direction. To that end, cellular networks are indeed a strong first mile candidate to accommodate the data tsunami to be generated by the IoT. However, IoT devices are required in the cellular paradigm to undergo random access procedures as a precursor to resource allocation. Such procedures impose a major bottleneck that hinders cellular networks\\' ability to support large-scale IoT. In this article, we shed light on the random access dilemma and present a case study based on experimental data as well as system-level simulations. Accordingly, a case is built for the latent need to revisit random access procedures. A call for action is motivated by listing a few potential remedies and recommendations.

Large-scale transportation network congestion evolution prediction using deep learning theory.

Science.gov (United States)

Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

2015-01-01

Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

Community turnover of wood-inhabiting fungi across hierarchical spatial scales.

Directory of Open Access Journals (Sweden)

Nerea Abrego

Full Text Available For efficient use of conservation resources it is important to determine how species diversity changes across spatial scales. In many poorly known species groups little is known about at which spatial scales the conservation efforts should be focused. Here we examined how the community turnover of wood-inhabiting fungi is realised at three hierarchical levels, and how much of community variation is explained by variation in resource composition and spatial proximity. The hierarchical study design consisted of management type (fixed factor, forest site (random factor, nested within management type and study plots (randomly placed plots within each study site. To examine how species richness varied across the three hierarchical scales, randomized species accumulation curves and additive partitioning of species richness were applied. To analyse variation in wood-inhabiting species and dead wood composition at each scale, linear and Permanova modelling approaches were used. Wood-inhabiting fungal communities were dominated by rare and infrequent species. The similarity of fungal communities was higher within sites and within management categories than among sites or between the two management categories, and it decreased with increasing distance among the sampling plots and with decreasing similarity of dead wood resources. However, only a small part of community variation could be explained by these factors. The species present in managed forests were in a large extent a subset of those species present in natural forests. Our results suggest that in particular the protection of rare species requires a large total area. As managed forests have only little additional value complementing the diversity of natural forests, the conservation of natural forests is the key to ecologically effective conservation. As the dissimilarity of fungal communities increases with distance, the conserved natural forest sites should be broadly distributed in space, yet

Initial condition effects on large scale structure in numerical simulations of plane mixing layers

Science.gov (United States)

McMullan, W. A.; Garrett, S. J.

2016-01-01

In this paper, Large Eddy Simulations are performed on the spatially developing plane turbulent mixing layer. The simulated mixing layers originate from initially laminar conditions. The focus of this research is on the effect of the nature of the imposed fluctuations on the large-scale spanwise and streamwise structures in the flow. Two simulations are performed; one with low-level three-dimensional inflow fluctuations obtained from pseudo-random numbers, the other with physically correlated fluctuations of the same magnitude obtained from an inflow generation technique. Where white-noise fluctuations provide the inflow disturbances, no spatially stationary streamwise vortex structure is observed, and the large-scale spanwise turbulent vortical structures grow continuously and linearly. These structures are observed to have a three-dimensional internal geometry with branches and dislocations. Where physically correlated provide the inflow disturbances a "streaky" streamwise structure that is spatially stationary is observed, with the large-scale turbulent vortical structures growing with the square-root of time. These large-scale structures are quasi-two-dimensional, on top of which the secondary structure rides. The simulation results are discussed in the context of the varying interpretations of mixing layer growth that have been postulated. Recommendations are made concerning the data required from experiments in order to produce accurate numerical simulation recreations of real flows.

Spatial patterns of agricultural expansion determine impacts on biodiversity and carbon storage.

Science.gov (United States)

Chaplin-Kramer, Rebecca; Sharp, Richard P; Mandle, Lisa; Sim, Sarah; Johnson, Justin; Butnar, Isabela; Milà I Canals, Llorenç; Eichelberger, Bradley A; Ramler, Ivan; Mueller, Carina; McLachlan, Nikolaus; Yousefi, Anahita; King, Henry; Kareiva, Peter M

2015-06-16

The agricultural expansion and intensification required to meet growing food and agri-based product demand present important challenges to future levels and management of biodiversity and ecosystem services. Influential actors such as corporations, governments, and multilateral organizations have made commitments to meeting future agricultural demand sustainably and preserving critical ecosystems. Current approaches to predicting the impacts of agricultural expansion involve calculation of total land conversion and assessment of the impacts on biodiversity or ecosystem services on a per-area basis, generally assuming a linear relationship between impact and land area. However, the impacts of continuing land development are often not linear and can vary considerably with spatial configuration. We demonstrate what could be gained by spatially explicit analysis of agricultural expansion at a large scale compared with the simple measure of total area converted, with a focus on the impacts on biodiversity and carbon storage. Using simple modeling approaches for two regions of Brazil, we find that for the same amount of land conversion, the declines in biodiversity and carbon storage can vary two- to fourfold depending on the spatial pattern of conversion. Impacts increase most rapidly in the earliest stages of agricultural expansion and are more pronounced in scenarios where conversion occurs in forest interiors compared with expansion into forests from their edges. This study reveals the importance of spatially explicit information in the assessment of land-use change impacts and for future land management and conservation.

Large-scale Flow and Transport of Magnetic Flux in the Solar ...

Indian Academy of Sciences (India)

tribpo

Abstract. Horizontal large-scale velocity field describes horizontal displacement of the photospheric magnetic flux in zonal and meridian directions. The flow systems of solar plasma, constructed according to the velocity field, create the large-scale cellular-like patterns with up-flow in the center and the down-flow on the ...

Toward seamless hydrologic predictions across spatial scales

NARCIS (Netherlands)

Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin; Warrach-Sagi, Kirsten; Attinger, Sabine

2017-01-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the

Integrating spatial and numerical structure in mathematical patterning

Science.gov (United States)

Ni’mah, K.; Purwanto; Irawan, E. B.; Hidayanto, E.

2018-03-01

This paper reports a study monitoring the integrating spatial and numerical structure in mathematical patterning skills of 30 students grade 7th of junior high school. The purpose of this research is to clarify the processes by which learners construct new knowledge in mathematical patterning. Findings indicate that: (1) students are unable to organize the structure of spatial and numerical, (2) students were only able to organize the spatial structure, but the numerical structure is still incorrect, (3) students were only able to organize numerical structure, but its spatial structure is still incorrect, (4) students were able to organize both of the spatial and numerical structure.

Spatial self-organized patterning in seagrasses along a depth gradient of an intertidal ecosystem

NARCIS (Netherlands)

van der Heide, Tjisse; Bouma, Tjeerd J.; Nes, Egbert H. van; van de Koppel, Johan; Scheffer, Marten; Roelofs, Jan G.M.; Katwijk, Marieke M. van; Smolders, Alfons J.P.

2010-01-01

The spatial structure of seagrass landscapes is typically ascribed to the direct influence of physical factors such as hydrodynamics, light, and sediment transport. We studied regularly interspaced banded patterns, formed by elongated patches of seagrass, in a small-scale intertidal ecosystem. We

Geo-ecological spatial pattern analysis of the island of Fogo (Cape Verde)

Science.gov (United States)

Olehowski, C.; Naumann, S.; Fischer, D.; Siegmund, A.

2008-12-01

With its small-scale climatic, floristic and geo-ecological differentiation, the island of Fogo is an optimal research area for understanding semi-arid island ecosystems in the marginal tropics. Because of the high variability in precipitation, the archipelago of Cape Verde has a potentially high ecological vulnerability, which is caused mainly by population growth, intensification of agricultural land use and increasing tourism. In this context, a geo-ecological spatial pattern analysis has been conducted for Fogo, including several types of geo-ecological layers like vegetation, elevation, aspect, soil and geology. The different kinds of spatial patterns that are detected can be used as a first tool to display distinctive levels of ecological vulnerability. These levels could constitute a base for sustainable land use planning and the redevelopment of agricultural strategies.

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

Science.gov (United States)

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

2016-04-01

(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.

Multi-scale spatial controls of understory vegetation in Douglas-fir–western hemlock forests of western Oregon, USA

Science.gov (United States)

Julia I. Burton; Lisa M. Ganio; Klaus J. Puettmann

2014-01-01

Forest understory vegetation is influenced by broad-scale variation in climate, intermediate scale variation in topography, disturbance and neighborhood interactions. However, little is known about how these multi-scale controls interact to influence observed spatial patterns. We examined relationships between the aggregated cover of understory plant species (%...

Spatial patterns of dengue cases in Brazil.

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Fernando Jose Antonio

Full Text Available Dengue infection plays a central role in our society, since it is the most prevalent vector-borne viral disease affecting humans. We statistically investigated patterns concerning the spatial spreading of dengue epidemics in Brazil, as well as their temporal evolution in all Brazilian municipalities for a period of 12 years. We showed that the distributions of cases in municipalities follow power laws persistent in time and that the infection scales linearly with the population of the municipalities. We also found that the average number of dengue cases does not have a clear dependence on the longitudinal position of municipalities. On the other hand, we found that the average distribution of cases varies with the latitudinal position of municipalities, displaying an almost constant growth from high latitudes until reaching the Tropic of Capricorn leveling to a plateau closer to the Equator. We also characterized the spatial correlation of the number of dengue cases between pairs of municipalities, where our results showed that the spatial correlation function decays with the increase of distance between municipalities, following a power-law with an exponential cut-off. This regime leads to a typical dengue traveling distance. Finally, we considered modeling this last behaviour within the framework of a Edwards-Wilkinson equation with a fractional derivative on space.

Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications

Science.gov (United States)

Rastogi, Bharat; Williams, A. Park; Fischer, Douglas T.; Iacobellis, Sam F.; McEachern, A. Kathryn; Carvalho, Leila; Jones, Charles Leslie; Baguskas, Sara A.; Still, Christopher J.

2016-01-01

The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in coastal California where forests are frequently shaded by low-lying clouds or immersed in fog during otherwise warm and dry summer months. Summer fog and stratus can ameliorate summer drought stress and enhance soil water budgets, and often have different spatial and temporal patterns. Here we use remote sensing datasets to characterize the spatial and temporal patterns of cloud cover over California’s northern Channel Islands. We found marine stratus to be persistent from May through September across the years 2001-2012. Stratus clouds were both most frequent and had the greatest spatial extent in July. Clouds typically formed in the evening, and dissipated by the following early afternoon. We present a novel method to downscale satellite imagery using atmospheric observations and discriminate patterns of fog from those of stratus and help explain patterns of fog deposition previously studied on the islands. The outcomes of this study contribute significantly to our ability to quantify the occurrence of coastal fog at biologically meaningful spatial and temporal scales that can improve our understanding of cloud-ecosystem interactions, species distributions and coastal ecohydrology.

Development of Spatial Distribution Patterns by Biofilm Cells

DEFF Research Database (Denmark)

Haagensen, Janus Anders Juul; Hansen, Susse Kirkelund; Bak Christensen, Bjarke

2015-01-01

-pattern by Acinetobacter sp. C6. Ecological spatial pattern analyses revealed that the microcolonies were not entirely randomly distributed, and instead arranged in a uniform pattern. Detailed time-lapse confocal microscopy at the single cell level demonstrated that the spatial pattern was the result of an intriguing self......-organization: Small multicellular clusters moved along the surface to fuse with one another to form microcolonies. This active distribution capability was dependent on environmental factors (carbon source, oxygen) and historical contingency (formation of phenotypic variants). The findings of this study are discussed...

Large Scale Emerging Properties from Non Hamiltonian Complex Systems

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Marco Bianucci

2017-06-01

Full Text Available The concept of “large scale” depends obviously on the phenomenon we are interested in. For example, in the field of foundation of Thermodynamics from microscopic dynamics, the spatial and time large scales are order of fraction of millimetres and microseconds, respectively, or lesser, and are defined in relation to the spatial and time scales of the microscopic systems. In large scale oceanography or global climate dynamics problems the time scales of interest are order of thousands of kilometres, for space, and many years for time, and are compared to the local and daily/monthly times scales of atmosphere and ocean dynamics. In all the cases a Zwanzig projection approach is, at least in principle, an effective tool to obtain class of universal smooth “large scale” dynamics for few degrees of freedom of interest, starting from the complex dynamics of the whole (usually many degrees of freedom system. The projection approach leads to a very complex calculus with differential operators, that is drastically simplified when the basic dynamics of the system of interest is Hamiltonian, as it happens in Foundation of Thermodynamics problems. However, in geophysical Fluid Dynamics, Biology, and in most of the physical problems the building block fundamental equations of motions have a non Hamiltonian structure. Thus, to continue to apply the useful projection approach also in these cases, we exploit the generalization of the Hamiltonian formalism given by the Lie algebra of dissipative differential operators. In this way, we are able to analytically deal with the series of the differential operators stemming from the projection approach applied to these general cases. Then we shall apply this formalism to obtain some relevant results concerning the statistical properties of the El Niño Southern Oscillation (ENSO.

Spatial patterning and floral synchrony among trillium populations with contrasting histories of herbivory

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Christopher R. Webster

2015-02-01

Full Text Available We investigated the spatial patterning and floral synchrony within and among populations of a non-clonal, forest understory herb, Trillium catesbaei. Two populations of T. catesbaei within Great Smoky Mountains National Park were monitored for five years: Cades Cove (high deer abundance and Whiteoak Sink (low deer abundance. All individuals within each population were mapped during year one and five. Only flowering and single-leaf juveniles were mapped during intervening years. Greater distances between flowering plants (plants currently in flower and substantially lower population densities and smaller patch sizes were observed at Cades Cove versus Whiteoak Sink. However, with the exception of flowering plants, contrasting histories of herbivory did not appear to fundamentally alter the spatial patterning of the T. catesbaei population at Cades Cove, an area with a long and well-documented history of deer overabundance. Regardless of browse history, non-flowering life stages were significantly clustered at all spatial scales examined. Flowering plants were clustered in all years at Whiteoak Sink, but more often randomly distributed at Cades Cove, possibly as a result of their lower abundance. Between years, however, there was a positive spatial association between the locations of flowering plants at both sites. Flowering rate was synchronous between sites, but lagged a year behind favorable spring growing conditions, which likely allowed plants to allocate photosynthate from a favorable year towards flowering the subsequent year. Collectively, our results suggest that chronically high levels of herbivory may be associated with spatial patterning of flowering within populations of a non-clonal plant. They also highlight the persistence of underlying spatial patterns, as evidenced by high levels of spatial clustering among non-flowering individuals, and the pervasive, although muted in a population subjected to chronic herbivory, influence of

The pattern of spatial flood disaster region in DKI Jakarta

Science.gov (United States)

Tambunan, M. P.

2017-02-01

The study of disaster flood area was conducted in DKI Jakarta Province, Indonesia. The aim of this research is: to study the spatial distribution of potential and actual of flood area The flood was studied from the geographic point of view using spatial approach, while the study of the location, the distribution, the depth and the duration of flooding was conducted using geomorphologic approach and emphasize on the detailed landform unit as analysis unit. In this study the landforms in DKI Jakarta have been a diversity, as well as spatial and temporal pattern of the actual and potential flood area. Landform at DKI Jakarta has been largely used as built up area for settlement and it facilities, thus affecting the distribution pattern of flooding area. The collection of the physical condition of landform in DKI Jakarta data prone were conducted through interpretation of the topographic map / RBI map and geological map. The flood data were obtained by survey and secondary data from Kimpraswil (Public Work) of DKI Jakarta Province for 3 years (1996, 2002, and 2007). Data of rainfall were obtained from BMKG and land use data were obtained from BPN DKI Jakarta. The analysis of the causal factors and distribution of flooding was made spatially and temporally using geographic information system. This study used survey method with a pragmatic approach. In this study landform as result from the analytical survey was settlement land use as result the synthetic survey. The primary data consist of landform, and the flood characteristic obtained by survey. The samples were using purposive sampling. Landform map was composed by relief, structure and material stone, and process data Landform map was overlay with flood map the flood prone area in DKI Jakarta Province in scale 1:50,000 to show. Descriptive analysis was used the spatial distribute of the flood prone area. The result of the study show that actual of flood prone area in the north, west and east of Jakarta lowland both

Revealing the Driving Forces of Mid-Cities Urban Growth Patterns Using Spatial Modeling: a Case Study of Los Ángeles, Chile

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Mauricio I. Aguayo

2007-06-01

Full Text Available City growth and changes in land-use patterns cause various important social and environmental impacts. To understand the spatial and temporal dynamics of these processes, the factors that drive urban development must be identified and analyzed, especially those factors that can be used to predict future changes and their potential environmental effects. Our objectives were to quantify the relationship between urban growth and its driving forces and to predict the spatial growth pattern based on historical land-use changes for the city of Los Ángeles in central Chile. This involved the analysis of images from 1978, 1992, and 1998 and characterization of the spatial pattern of land-use change; the construction of digital coverage in GIS; the selection of predictive variables through univariate analysis; the construction of logistic regression models using growth vs. nongrowth for 1978-1992 as the dependent variable; and the prediction of the probability of land-use change by applying the regression model to the 1992-1998 period. To investigate the influence of spatial scale, we constructed several sets of models that contained (1 only distance variables, e.g., distance to highways; (2 only scale-dependent density variables, e.g., density of urban area within a 600-m radius; (3 both distance and density variables; and (4 both distance and density variables at several spatial scales. The environmental variables were included in all models. The combination of distance and density variables at several scales is required to appropriately capture the multiscale urban growth process. The best models correctly predict ~90% of the observed land-use changes for 1992-1998. The distance to access roads, densities of the urban road system and urbanized area at various scales, and soil type were the strongest predictors of the growth pattern. Other variables were less important or not significant in explaining the urban growth process. Our approach, which

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh.

Science.gov (United States)

Bi, Qifang; Azman, Andrew S; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S; Lessler, Justin

2016-02-01

Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh.

Directory of Open Access Journals (Sweden)

Qifang Bi

2016-02-01

Full Text Available Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98, type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00, and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00 exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a

Optimizing spatial patterns with sparse filter bands for motor-imagery based brain-computer interface.

Science.gov (United States)

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

2015-11-30

Common spatial pattern (CSP) has been most popularly applied to motor-imagery (MI) feature extraction for classification in brain-computer interface (BCI) application. Successful application of CSP depends on the filter band selection to a large degree. However, the most proper band is typically subject-specific and can hardly be determined manually. This study proposes a sparse filter band common spatial pattern (SFBCSP) for optimizing the spatial patterns. SFBCSP estimates CSP features on multiple signals that are filtered from raw EEG data at a set of overlapping bands. The filter bands that result in significant CSP features are then selected in a supervised way by exploiting sparse regression. A support vector machine (SVM) is implemented on the selected features for MI classification. Two public EEG datasets (BCI Competition III dataset IVa and BCI Competition IV IIb) are used to validate the proposed SFBCSP method. Experimental results demonstrate that SFBCSP help improve the classification performance of MI. The optimized spatial patterns by SFBCSP give overall better MI classification accuracy in comparison with several competing methods. The proposed SFBCSP is a potential method for improving the performance of MI-based BCI. Copyright © 2015 Elsevier B.V. All rights reserved.

Mining the Relationship between Spatial Mobility Patterns and POIs

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Liping Huang

2018-01-01

Full Text Available Passengers move between urban places for diverse interests and drive the metropolitan regions as the aggregation of urban places to group into network communities. This paper aims to examine the relationship between the spatial patterns (represented by the network communities of mobility flows and places of interest (POIs. Furtherly, it intends to identify the categories of POIs that play the most significant role in shaping the spatial patterns of mobility flows. To achieve these purposes, we partition the study area into disjoint regions and construct the network with each partitioned region as a node and connection between them as links weighted by the mobility flows. The community detection algorithm is implemented on the network to discover spatial mobility patterns, and the multiclass classification based on the logistic regression method is adopted to classify spatial communities featured by POIs. Taking the taxi systems of Shanghai and Beijing as examples, we detect spatial communities based on the movement strengths among regions. Then we investigate their correlations with POIs. It finds that communities’ modularity correlates linearly with POIs; particularly governments, hotels, and the traffic facilities are of the most significance for generating the mobility patterns. This study can provide valuable insight into understanding the spatial mobility patterns from the perspective of POIs.

Spatial patterns and scale-dependent relationships between macrozooplankton and fish in the Bay of Biscay: an acoustic study

KAUST Repository

Lezama-Ochoa, A

2011-10-20

Macrozooplankton plays a key role in pelagic ecosystems as a link between lower trophic levels and fish. However, although its ecological role is usually considered in polar ecosystems, it is rarely considered in temperate ones. To obtain comprehensive information on the macrozooplankton distribution in the Bay of Biscay we adapted a bi-frequency acoustic method developed for the Humboldt Current system. This method can be used to extract continuous and simultaneous high-resolution information on the spatiotemporal patterns of biomass distributions of macrozooplankton and pelagic fish throughout the diel cycle. The 2 distributions were mapped using geostatistical techniques. We applied kriging with external drifts, which accounts for both diel and across-shore changes in macrozooplankton biomass. We then used a cross-variogram to determine the scale-dependent relationships between macrozooplankton and fish. The results show how macrozooplankton and fish are distributed according to the different ecological domains (coast, shelf, shelf-break and offshore) along the Spanish and French coasts. Specific macrozooplankton hotspots were observed, but macrozooplankton was generally more abundant offshore than inshore, whereas fish showed the opposite trend. This pattern was confirmed by the aggregation sizes, which increased towards oceanic waters for macrozooplankton and decreased for fish. Finally, the correlation between fish and macrozooplankton was positive on a small scale (<30 nautical miles) and negative on a large scale (>30 nautical miles).

A Stream Tilling Approach to Surface Area Estimation for Large Scale Spatial Data in a Shared Memory System

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Liu Jiping

2017-12-01

Full Text Available Surface area estimation is a widely used tool for resource evaluation in the physical world. When processing large scale spatial data, the input/output (I/O can easily become the bottleneck in parallelizing the algorithm due to the limited physical memory resources and the very slow disk transfer rate. In this paper, we proposed a stream tilling approach to surface area estimation that first decomposed a spatial data set into tiles with topological expansions. With these tiles, the one-to-one mapping relationship between the input and the computing process was broken. Then, we realized a streaming framework towards the scheduling of the I/O processes and computing units. Herein, each computing unit encapsulated a same copy of the estimation algorithm, and multiple asynchronous computing units could work individually in parallel. Finally, the performed experiment demonstrated that our stream tilling estimation can efficiently alleviate the heavy pressures from the I/O-bound work, and the measured speedup after being optimized have greatly outperformed the directly parallel versions in shared memory systems with multi-core processors.

Large-scale modeling of rain fields from a rain cell deterministic model

Science.gov (United States)

FéRal, Laurent; Sauvageot, Henri; Castanet, Laurent; Lemorton, JoëL.; Cornet, FréDéRic; Leconte, Katia

2006-04-01

A methodology to simulate two-dimensional rain rate fields at large scale (1000 × 1000 km2, the scale of a satellite telecommunication beam or a terrestrial fixed broadband wireless access network) is proposed. It relies on a rain rate field cellular decomposition. At small scale (˜20 × 20 km2), the rain field is split up into its macroscopic components, the rain cells, described by the Hybrid Cell (HYCELL) cellular model. At midscale (˜150 × 150 km2), the rain field results from the conglomeration of rain cells modeled by HYCELL. To account for the rain cell spatial distribution at midscale, the latter is modeled by a doubly aggregative isotropic random walk, the optimal parameterization of which is derived from radar observations at midscale. The extension of the simulation area from the midscale to the large scale (1000 × 1000 km2) requires the modeling of the weather frontal area. The latter is first modeled by a Gaussian field with anisotropic covariance function. The Gaussian field is then turned into a binary field, giving the large-scale locations over which it is raining. This transformation requires the definition of the rain occupation rate over large-scale areas. Its probability distribution is determined from observations by the French operational radar network ARAMIS. The coupling with the rain field modeling at midscale is immediate whenever the large-scale field is split up into midscale subareas. The rain field thus generated accounts for the local CDF at each point, defining a structure spatially correlated at small scale, midscale, and large scale. It is then suggested that this approach be used by system designers to evaluate diversity gain, terrestrial path attenuation, or slant path attenuation for different azimuth and elevation angle directions.

Evaluating patterns of a white-band disease (WBD outbreak in Acropora palmata using spatial analysis: a comparison of transect and colony clustering.

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Jennifer A Lentz

Full Text Available BACKGROUND: Despite being one of the first documented, there is little known of the causative agent or environmental stressors that promote white-band disease (WBD, a major disease of Caribbean Acropora palmata. Likewise, there is little known about the spatiality of outbreaks. We examined the spatial patterns of WBD during a 2004 outbreak at Buck Island Reef National Monument in the US Virgin Islands. METHODOLOGY/PRINCIPAL FINDINGS: Ripley's K statistic was used to measure spatial dependence of WBD across scales. Localized clusters of WBD were identified using the DMAP spatial filtering technique. Statistics were calculated for colony- (number of A. palmata colonies with and without WBD within each transect and transect-level (presence/absence of WBD within transects data to evaluate differences in spatial patterns at each resolution of coral sampling. The Ripley's K plots suggest WBD does cluster within the study area, and approached statistical significance (p = 0.1 at spatial scales of 1100 m or less. Comparisons of DMAP results suggest the transect-level overestimated the prevalence and spatial extent of the outbreak. In contrast, more realistic prevalence estimates and spatial patterns were found by weighting each transect by the number of individual A. palmata colonies with and without WBD. CONCLUSIONS: As the search for causation continues, surveillance and proper documentation of the spatial patterns may inform etiology, and at the same time assist reef managers in allocating resources to tracking the disease. Our results indicate that the spatial scale of data collected can drastically affect the calculation of prevalence and spatial distribution of WBD outbreaks. Specifically, we illustrate that higher resolution sampling resulted in more realistic disease estimates. This should assist in selecting appropriate sampling designs for future outbreak investigations. The spatial techniques used here can be used to facilitate other

Evaluating patterns of a white-band disease (WBD) outbreak in Acropora palmata using spatial analysis: a comparison of transect and colony clustering.

Science.gov (United States)

Lentz, Jennifer A; Blackburn, Jason K; Curtis, Andrew J

2011-01-01

Despite being one of the first documented, there is little known of the causative agent or environmental stressors that promote white-band disease (WBD), a major disease of Caribbean Acropora palmata. Likewise, there is little known about the spatiality of outbreaks. We examined the spatial patterns of WBD during a 2004 outbreak at Buck Island Reef National Monument in the US Virgin Islands. Ripley's K statistic was used to measure spatial dependence of WBD across scales. Localized clusters of WBD were identified using the DMAP spatial filtering technique. Statistics were calculated for colony- (number of A. palmata colonies with and without WBD within each transect) and transect-level (presence/absence of WBD within transects) data to evaluate differences in spatial patterns at each resolution of coral sampling. The Ripley's K plots suggest WBD does cluster within the study area, and approached statistical significance (p = 0.1) at spatial scales of 1100 m or less. Comparisons of DMAP results suggest the transect-level overestimated the prevalence and spatial extent of the outbreak. In contrast, more realistic prevalence estimates and spatial patterns were found by weighting each transect by the number of individual A. palmata colonies with and without WBD. As the search for causation continues, surveillance and proper documentation of the spatial patterns may inform etiology, and at the same time assist reef managers in allocating resources to tracking the disease. Our results indicate that the spatial scale of data collected can drastically affect the calculation of prevalence and spatial distribution of WBD outbreaks. Specifically, we illustrate that higher resolution sampling resulted in more realistic disease estimates. This should assist in selecting appropriate sampling designs for future outbreak investigations. The spatial techniques used here can be used to facilitate other coral disease studies, as well as, improve reef conservation and management.

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

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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.

Large Scale EOF Analysis of Climate Data

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Prabhat, M.; Gittens, A.; Kashinath, K.; Cavanaugh, N. R.; Mahoney, M.

2016-12-01

We present a distributed approach towards extracting EOFs from 3D climate data. We implement the method in Apache Spark, and process multi-TB sized datasets on O(1000-10,000) cores. We apply this method to latitude-weighted ocean temperature data from CSFR, a 2.2 terabyte-sized data set comprising ocean and subsurface reanalysis measurements collected at 41 levels in the ocean, at 6 hour intervals over 31 years. We extract the first 100 EOFs of this full data set and compare to the EOFs computed simply on the surface temperature field. Our analyses provide evidence of Kelvin and Rossy waves and components of large-scale modes of oscillation including the ENSO and PDO that are not visible in the usual SST EOFs. Further, they provide information on the the most influential parts of the ocean, such as the thermocline, that exist below the surface. Work is ongoing to understand the factors determining the depth-varying spatial patterns observed in the EOFs. We will experiment with weighting schemes to appropriately account for the differing depths of the observations. We also plan to apply the same distributed approach to analysis of analysis of 3D atmospheric climatic data sets, including multiple variables. Because the atmosphere changes on a quicker time-scale than the ocean, we expect that the results will demonstrate an even greater advantage to computing 3D EOFs in lieu of 2D EOFs.

Large-scale patterns of turnover and Basal area change in Andean forests.

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Selene Báez

Full Text Available General patterns of forest dynamics and productivity in the Andes Mountains are poorly characterized. Here we present the first large-scale study of Andean forest dynamics using a set of 63 permanent forest plots assembled over the past two decades. In the North-Central Andes tree turnover (mortality and recruitment and tree growth declined with increasing elevation and decreasing temperature. In addition, basal area increased in Lower Montane Moist Forests but did not change in Higher Montane Humid Forests. However, at higher elevations the lack of net basal area change and excess of mortality over recruitment suggests negative environmental impacts. In North-Western Argentina, forest dynamics appear to be influenced by land use history in addition to environmental variation. Taken together, our results indicate that combinations of abiotic and biotic factors that vary across elevation gradients are important determinants of tree turnover and productivity in the Andes. More extensive and longer-term monitoring and analyses of forest dynamics in permanent plots will be necessary to understand how demographic processes and woody biomass are responding to changing environmental conditions along elevation gradients through this century.

Evaluating the use of local ecological knowledge to monitor hunted tropical-forest wildlife over large spatial scales

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Luke Parry

2015-09-01

Full Text Available Monitoring the distribution and abundance of hunted wildlife is critical to achieving sustainable resource use, yet adequate data are sparse for most tropical regions. Conventional methods for monitoring hunted forest-vertebrate species require intensive in situ survey effort, which severely constrains spatial and temporal replication. Integrating local ecological knowledge (LEK into monitoring and management is appealing because it can be cost-effective, enhance community participation, and provide novel insights into sustainable resource use. We develop a technique to monitor population depletion of hunted forest wildlife in the Brazilian Amazon, based on the local ecological knowledge of rural hunters. We performed rapid interview surveys to estimate the landscape-scale depletion of ten large-bodied vertebrate species around 161 Amazonian riverine settlements. We assessed the explanatory and predictive power of settlement and landscape characteristics and were able to develop robust estimates of local faunal depletion. By identifying species-specific drivers of depletion and using secondary data on human population density, land form, and physical accessibility, we then estimated landscape- and regional-scale depletion. White-lipped peccary (Tayassu pecari, for example, were estimated to be absent from 17% of their putative range in Brazil's largest state (Amazonas, despite 98% of the original forest cover remaining intact. We found evidence that bushmeat consumption in small urban centers has far-reaching impacts on some forest species, including severe depletion well over 100 km from urban centers. We conclude that LEK-based approaches require further field validation, but have significant potential for community-based participatory monitoring as well as cost-effective, large-scale monitoring of threatened forest species.

Static analysis of large-scale multibody system using joint coordinates and spatial algebra operator.

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Omar, Mohamed A

2014-01-01

Initial transient oscillations inhibited in the dynamic simulations responses of multibody systems can lead to inaccurate results, unrealistic load prediction, or simulation failure. These transients could result from incompatible initial conditions, initial constraints violation, and inadequate kinematic assembly. Performing static equilibrium analysis before the dynamic simulation can eliminate these transients and lead to stable simulation. Most exiting multibody formulations determine the static equilibrium position by minimizing the system potential energy. This paper presents a new general purpose approach for solving the static equilibrium in large-scale articulated multibody. The proposed approach introduces an energy drainage mechanism based on Baumgarte constraint stabilization approach to determine the static equilibrium position. The spatial algebra operator is used to express the kinematic and dynamic equations of the closed-loop multibody system. The proposed multibody system formulation utilizes the joint coordinates and modal elastic coordinates as the system generalized coordinates. The recursive nonlinear equations of motion are formulated using the Cartesian coordinates and the joint coordinates to form an augmented set of differential algebraic equations. Then system connectivity matrix is derived from the system topological relations and used to project the Cartesian quantities into the joint subspace leading to minimum set of differential equations.

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

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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.

Use of large-scale acoustic monitoring to assess anthropogenic pressures on Orthoptera communities.

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Penone, Caterina; Le Viol, Isabelle; Pellissier, Vincent; Julien, Jean-François; Bas, Yves; Kerbiriou, Christian

2013-10-01

Biodiversity monitoring at large spatial and temporal scales is greatly needed in the context of global changes. Although insects are a species-rich group and are important for ecosystem functioning, they have been largely neglected in conservation studies and policies, mainly due to technical and methodological constraints. Sound detection, a nondestructive method, is easily applied within a citizen-science framework and could be an interesting solution for insect monitoring. However, it has not yet been tested at a large scale. We assessed the value of a citizen-science program in which Orthoptera species (Tettigoniidae) were monitored acoustically along roads. We used Bayesian model-averaging analyses to test whether we could detect widely known patterns of anthropogenic effects on insects, such as the negative effects of urbanization or intensive agriculture on Orthoptera populations and communities. We also examined site-abundance correlations between years and estimated the biases in species detection to evaluate and improve the protocol. Urbanization and intensive agricultural landscapes negatively affected Orthoptera species richness, diversity, and abundance. This finding is consistent with results of previous studies of Orthoptera, vertebrates, carabids, and butterflies. The average mass of communities decreased as urbanization increased. The dispersal ability of communities increased as the percentage of agricultural land and, to a lesser extent, urban area increased. Despite changes in abundances over time, we found significant correlations between yearly abundances. We identified biases linked to the protocol (e.g., car speed or temperature) that can be accounted for ease in analyses. We argue that acoustic monitoring of Orthoptera along roads offers several advantages for assessing Orthoptera biodiversity at large spatial and temporal extents, particularly in a citizen science framework. © 2013 Society for Conservation Biology.

The spatial patterns of directional phenotypic selection

KAUST Repository

Siepielski, Adam M.; Gotanda, Kiyoko M.; Morrissey, Michael B.; Diamond, Sarah E.; DiBattista, Joseph; Carlson, Stephanie Marie

2013-01-01

the spatial patterns of selection, namely the extent of variation among populations in the strength and direction of selection. Here, we analyse a data set of spatially replicated studies of directional phenotypic selection from natural populations. The data

Global direct pressures on biodiversity by large-scale metal mining: Spatial distribution and implications for conservation.

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Murguía, Diego I; Bringezu, Stefan; Schaldach, Rüdiger

2016-09-15

Biodiversity loss is widely recognized as a serious global environmental change process. While large-scale metal mining activities do not belong to the top drivers of such change, these operations exert or may intensify pressures on biodiversity by adversely changing habitats, directly and indirectly, at local and regional scales. So far, analyses of global spatial dynamics of mining and its burden on biodiversity focused on the overlap between mines and protected areas or areas of high value for conservation. However, it is less clear how operating metal mines are globally exerting pressure on zones of different biodiversity richness; a similar gap exists for unmined but known mineral deposits. By using vascular plants' diversity as a proxy to quantify overall biodiversity, this study provides a first examination of the global spatial distribution of mines and deposits for five key metals across different biodiversity zones. The results indicate that mines and deposits are not randomly distributed, but concentrated within intermediate and high diversity zones, especially bauxite and silver. In contrast, iron, gold, and copper mines and deposits are closer to a more proportional distribution while showing a high concentration in the intermediate biodiversity zone. Considering the five metals together, 63% and 61% of available mines and deposits, respectively, are located in intermediate diversity zones, comprising 52% of the global land terrestrial surface. 23% of mines and 20% of ore deposits are located in areas of high plant diversity, covering 17% of the land. 13% of mines and 19% of deposits are in areas of low plant diversity, comprising 31% of the land surface. Thus, there seems to be potential for opening new mines in areas of low biodiversity in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir.

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Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-09-23

The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies.

Temporal and spatial heterogeneity in lacustrine δ13CDIC and δ18ODO signatures in a large mid-latitude temperate lake

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Jane DRUMMOND

2010-08-01

Full Text Available Modelling limnetic carbon processes is necessary for accurate global carbon models and stable isotope analysis can provide additional insight of carbon flow pathways. This research examined the spatial and temporal complexity of carbon cycling in a large temperate lake. Dissolved inorganic carbon (DIC is utilised by photosynthetic organisms and dissolved oxygen (DO is used by heterotrophic organisms during respiration. Thus the spatial heterogeneity in the pelagic metabolic balance in Loch Lomond, Scotland was investigated using a combined natural abundance isotope technique. The isotopic signatures of dissolved inorganic carbon (δ13CDIC and dissolved oxygen (δ18ODO were measured concurrently on four different dates between November 2004 and September 2005. We measured isotopic variation over small and large spatial scales, both horizontal distance and depth. δ13CDIC and δ18ODO changed over a seasonal cycle, becoming concurrently more positive (negative in the summer (winter months, responding to increased photosynthetic and respiratory rates, respectively. With increasing depth, δ13CDIC became more negative and δ18ODO more positive, reflecting the shift to a respiration-dominated system. The horizontal distribution of δ13CDIC and δ18ODO in the epilimnion was heterogeneous. In general, the south basin had the most positive δ13CDIC, becoming more negative with increasing latitude, except in winter when the opposite pattern was observed. Areas of local variation were often observed near inflows. Clearly δ13CDIC and δ18ODO can show large spatial heterogeneity, as a result of varying metabolic balance coupled with inflow proximity and thus single point sampling to extrapolate whole lake metabolic patterns can result in error when modelling large lake systems Whilst we advise caution when using single point representation, we also show that this combined isotopic approach has potential to assist in constructing detailed lake carbon models.

A framework for the assessment of the spatial and temporal patterns of threatened coastal delphinids.

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Wang, Jingzhen; Yang, Yingting; Yang, Feng; Li, Yuelin; Li, Lianjie; Lin, Derun; He, Tangtian; Liang, Bo; Zhang, Tao; Lin, Yao; Li, Ping; Liu, Wenhua

2016-01-25

The massively accelerated biodiversity loss rate in the Anthropocene calls for an efficient and effective way to identify the spatial and temporal dynamics of endangered species. To this end, we developed a useful identification framework based on a case study of locally endangered Sousa chinensis by combining both LEK (local ecological knowledge) evaluation and regional boat-based survey methods. Our study investigated the basic ecological information of Sousa chinensis in the estuaries of eastern Guangdong that had previously been neglected, which could guide the future study and conservation. Based on the statistical testing of reported spatial and temporal dolphins sighting data from fishermen and the ecological monitoring analyses, including sighting rate, site fidelity and residence time estimations, some of the current Sousa chinensis units are likely to be geographically isolated and critically endangered, which calls for much greater conservation efforts. Given the accelerated population extinction rate and increasing budgetary constraints, our survey pattern can be applied in a timely and economically acceptable manner to the spatial and temporal assessment of other threatened coastal delphinids, particularly when population distributions are on a large scale and traditional sampling methods are difficult to implement.

Temporal and spatial scaling impacts on extreme precipitation

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Eggert, B.; Berg, P.; Haerter, J. O.; Jacob, D.; Moseley, C.

2015-01-01

Both in the current climate and in the light of climate change, understanding of the causes and risk of precipitation extremes is essential for protection of human life and adequate design of infrastructure. Precipitation extreme events depend qualitatively on the temporal and spatial scales at which they are measured, in part due to the distinct types of rain formation processes that dominate extremes at different scales. To capture these differences, we first filter large datasets of high-resolution radar measurements over Germany (5 min temporally and 1 km spatially) using synoptic cloud observations, to distinguish convective and stratiform rain events. In a second step, for each precipitation type, the observed data are aggregated over a sequence of time intervals and spatial areas. The resulting matrix allows a detailed investigation of the resolutions at which convective or stratiform events are expected to contribute most to the extremes. We analyze where the statistics of the two types differ and discuss at which resolutions transitions occur between dominance of either of the two precipitation types. We characterize the scales at which the convective or stratiform events will dominate the statistics. For both types, we further develop a mapping between pairs of spatially and temporally aggregated statistics. The resulting curve is relevant when deciding on data resolutions where statistical information in space and time is balanced. Our study may hence also serve as a practical guide for modelers, and for planning the space-time layout of measurement campaigns. We also describe a mapping between different pairs of resolutions, possibly relevant when working with mismatched model and observational resolutions, such as in statistical bias correction.

Spatial variability and macro‐scale drivers of growth for native and introduced Flathead Catfish populations

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Massie, Danielle L.; Smith, Geoffrey; Bonvechio, Timothy F.; Bunch, Aaron J.; Lucchesi, David O.; Wagner, Tyler

2018-01-01

Quantifying spatial variability in fish growth and identifying large‐scale drivers of growth are fundamental to many conservation and management decisions. Although fish growth studies often focus on a single population, it is becoming increasingly clear that large‐scale studies are likely needed for addressing transboundary management needs. This is particularly true for species with high recreational value and for those with negative ecological consequences when introduced outside of their native range, such as the Flathead Catfish Pylodictis olivaris. This study quantified growth variability of the Flathead Catfish across a large portion of its contemporary range to determine whether growth differences existed between habitat types (i.e., reservoirs and rivers) and between native and introduced populations. Additionally, we investigated whether growth parameters varied as a function of latitude and time since introduction (for introduced populations). Length‐at‐age data from 26 populations across 11 states in the USA were modeled using a Bayesian hierarchical von Bertalanffy growth model. Population‐specific growth trajectories revealed large variation in Flathead Catfish growth and relatively high uncertainty in growth parameters for some populations. Relatively high uncertainty was also evident when comparing populations and when quantifying large‐scale patterns. Growth parameters (Brody growth coefficient [K] and theoretical maximum average length [L∞]) were not different (based on overlapping 90% credible intervals) between habitat types or between native and introduced populations. For populations within the introduced range of Flathead Catfish, latitude was negatively correlated with K. For native populations, we estimated an 85% probability that L∞ estimates were negatively correlated with latitude. Contrary to predictions, time since introduction was not correlated with growth parameters in introduced populations of Flathead Catfish

The Signature of Southern Hemisphere Atmospheric Circulation Patterns in Antarctic Precipitation.

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Marshall, Gareth J; Thompson, David W J; van den Broeke, Michiel R

2017-11-28

We provide the first comprehensive analysis of the relationships between large-scale patterns of Southern Hemisphere climate variability and the detailed structure of Antarctic precipitation. We examine linkages between the high spatial resolution precipitation from a regional atmospheric model and four patterns of large-scale Southern Hemisphere climate variability: the southern baroclinic annular mode, the southern annular mode, and the two Pacific-South American teleconnection patterns. Variations in all four patterns influence the spatial configuration of precipitation over Antarctica, consistent with their signatures in high-latitude meridional moisture fluxes. They impact not only the mean but also the incidence of extreme precipitation events. Current coupled-climate models are able to reproduce all four patterns of atmospheric variability but struggle to correctly replicate their regional impacts on Antarctic climate. Thus, linking these patterns directly to Antarctic precipitation variability may allow a better estimate of future changes in precipitation than using model output alone.

Geo-spatial aspects of acceptance of illegal hunting of large carnivores in Scandinavia.

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Gangaas, Kristin E; Kaltenborn, Bjørn P; Andreassen, Harry P

2013-01-01

Human-carnivore conflicts are complex and are influenced by: the spatial distribution of the conflict species; the organisation and intensity of management measures such as zoning; historical experience with wildlife; land use patterns; and local cultural traditions. We have used a geographically stratified sampling of social values and attitudes to provide a novel perspective to the human - wildlife conflict. We have focused on acceptance by and disagreements between residents (measured as Potential Conflict Index; PCI) towards illegal hunting of four species of large carnivores (bear, lynx, wolf, wolverine). The study is based on surveys of residents in every municipality in Sweden and Norway who were asked their opinion on illegal hunting. Our results show how certain social values are associated with acceptance of poaching, and how these values differ geographically independent of carnivore abundance. Our approach differs from traditional survey designs, which are often biased towards urban areas. Although these traditional designs intend to be representative of a region (i.e. a random sample from a country), they tend to receive relatively few respondents from rural areas that experience the majority of conflict with carnivores. Acceptance of poaching differed significantly between Norway (12.7-15.7% of respondents) and Sweden (3.3-4.1% of respondents). We found the highest acceptance of illegal hunting in rural areas with free-ranging sheep and strong hunting traditions. Disagreements between residents (as measured by PCI) were highest in areas with intermediate population density. There was no correlation between carnivore density and either acceptance of illegal hunting or PCI. A strong positive correlation between acceptance of illegal hunting and PCI showed that areas with high acceptance of illegal hunting are areas with high potential conflict between people. Our results show that spatially-stratified surveys are required to reveal the large scale

Storm-tracks interannual variability and large-scale climate modes

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Liberato, Margarida L. R.; Trigo, Isabel F.; Trigo, Ricardo M.

2013-04-01

In this study we focus on the interannual variability and observed changes in northern hemisphere mid-latitude storm-tracks and relate them to large scale atmospheric circulation variability modes. Extratropical storminess, cyclones dominant paths, frequency and intensity have long been the object of climatological studies. The analysis of storm characteristics and historical trends presented here is based on the cyclone detecting and tracking algorithm first developed for the Mediterranean region (Trigo et al. 1999) and recently extended to a larger Euro-Atlantic region (Trigo 2006). The objective methodology, which identifies and follows individual lows as minima in SLP fields, fulfilling a set of conditions regarding the central pressure and the pressure gradient, is applied to the northern hemisphere 6-hourly geopotential data at 1000 hPa from the 20th Century Reanalyses (20CRv2) project and from reanalyses datasets provided by the European Centre for Medium-Range Weather Forecasts (ECMWF): ERA-40 and ERA Interim reanalyses. First, we assess the interannual variability and cyclone frequency trends for each of the datasets, for the 20th century and for the period between 1958 and 2002 using the highest spatial resolution available (1.125° x 1.125°) from the ERA-40 data. Results show that winter variability of storm paths, cyclone frequency and travel times is in agreement with the reported variability in a number of large-scale climate patterns (including the North Atlantic Oscillation, the East Atlantic Pattern and the Scandinavian Pattern). In addition, three storm-track databases are built spanning the common available extended winter seasons from October 1979 to March 2002. Although relatively short, this common period allows a comparison of systems represented in reanalyses datasets with distinct horizontal resolutions. This exercise is mostly focused on the key areas of cyclogenesis and cyclolysis and main cyclone characteristics over the northern

Large-scale transportation network congestion evolution prediction using deep learning theory.

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Xiaolei Ma

Full Text Available Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS and Internet of Things (IoT, transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

Spatial connectivity, scaling, and temporal trajectories as emergent urban stormwater impacts

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Jovanovic, T.; Gironas, J. A.; Hale, R. L.; Mejia, A.

2016-12-01

Urban watersheds are structurally complex systems comprised of multiple components (e.g., streets, pipes, ponds, vegetated swales, wetlands, riparian corridors, etc.). These multiple engineered components interact in unanticipated and nontrivial ways with topographic conditions, climate variability, land use/land cover changes, and the underlying eco-hydrogeomorphic dynamics. Such interactions can result in emergent urban stormwater impacts with cascading effects that can negatively influence the overall functioning of the urban watershed. For example, the interaction among many detention ponds has been shown, in some situations, to synchronize flow volumes and ultimately lead to downstream flow amplifications and increased pollutant mobilization. Additionally, interactions occur at multiple temporal and spatial scales requiring that urban stormwater dynamics be represented at the long-term temporal (decadal) and across spatial scales (from the single lot to the watershed scale). In this study, we develop and implement an event-based, high-resolution, network hydro-engineering model (NHEM), and demonstrate an approach to reconstruct the long-term regional infrastructure and land use/land cover conditions of an urban watershed. As the study area, we select an urban watershed in the metropolitan area of Scottsdale, Arizona. Using the reconstructed landscapes to drive the NHEM, we find that distinct surficial, hydrologic connectivity patterns result from the intersection of hydrologic processes, infrastructure, and land use/land cover arrangements. These spatial patters, in turn, exhibit scaling characteristics. For example, the scaling of urban watershed dispersion mechanisms shows altered scaling exponents with respect to pre-urban conditions. For example, the scaling exponent associated with geomorphic dispersion tends to increase for urban conditions, reflecting increased surficial path heterogeneity. Both the connectivity and scaling results can be used to

Spatially nonrandom tree mortality and ingrowth maintain equilibrium pattern in an old-growth Pseudotsuga-Tsuga forest.

Science.gov (United States)

Lutz, James A; Larson, Andrew J; Furniss, Tucker J; Donato, Daniel C; Freund, James A; Swanson, Mark E; Bible, Kenneth J; Chen, Jiquan; Franklin, Jerry F

2014-08-01

Mortality processes in old-growth forests are generally assumed to be driven by gap-scale disturbance, with only a limited role ascribed to density-dependent mortality, but these assumptions are rarely tested with data sets incorporating repeated measurements. Using a 12-ha spatially explicit plot censused 13 years apart in an approximately 500-year-old Pseudotsuga-Tsuga forest, we demonstrate significant density-dependent mortality and spatially aggregated tree recruitment. However, the combined effect of these strongly nonrandom demographic processes was to maintain tree patterns in a state of dynamic equilibrium. Density-dependent mortality was most pronounced for the dominant late-successional species, Tsuga heterophylla. The long-lived, early-seral Pseudotsuga menziesii experienced an annual stem mortality rate of 0.84% and no new recruitment. Late-seral species Tsuga and Abies amabilis had nearly balanced demographic rates of ingrowth and mortality. The 2.34% mortality rate for Taxus brevifolia was higher than expected, notably less than ingrowth, and strongly affected by proximity to Tsuga. Large-diameter Tsuga structured both the regenerating conspecific and heterospecific cohorts with recruitment of Tsuga and Abies unlikely in neighborhoods crowded with large-diameter competitors (P old-growth forests.

The Hamburg large scale geostrophic ocean general circulation model. Cycle 1

International Nuclear Information System (INIS)

Maier-Reimer, E.; Mikolajewicz, U.

1992-02-01

The rationale for the Large Scale Geostrophic ocean circulation model (LSG-OGCM) is based on the observations that for a large scale ocean circulation model designed for climate studies, the relevant characteristic spatial scales are large compared with the internal Rossby radius throughout most of the ocean, while the characteristic time scales are large compared with the periods of gravity modes and barotropic Rossby wave modes. In the present version of the model, the fast modes have been filtered out by a conventional technique of integrating the full primitive equations, including all terms except the nonlinear advection of momentum, by an implicit time integration method. The free surface is also treated prognostically, without invoking a rigid lid approximation. The numerical scheme is unconditionally stable and has the additional advantage that it can be applied uniformly to the entire globe, including the equatorial and coastal current regions. (orig.)

Geographical Pattern and Environmental Correlates of Regional-Scale General Flowering in Peninsular Malaysia

Science.gov (United States)

Numata, Shinya; Yasuda, Masatoshi; Suzuki, Ryo O.; Hosaka, Tetsuro; Noor, Nur Supardi Md.; Fletcher, Christine D.; Hashim, Mazlan

2013-01-01

In South-East Asian dipterocarp forests, many trees synchronize their reproduction at the community level, but irregularly, in a phenomenon known as general flowering (GF). Several proximate cues have been proposed as triggers for the synchronization of Southeast Asian GF, but the debate continues, as many studies have not considered geographical variation in climate and flora. We hypothesized that the spatial pattern of GF forests is explained by previously proposed climatic cues if there are common cues for GF among regions. During the study, GF episodes occurred every year, but the spatial occurrence varied considerably from just a few forests to the whole of Peninsular Malaysia. In 2001, 2002 and 2005, minor and major GF occurred widely throughout Peninsular Malaysia (GF2001, GF2002, and GF2005), and the geographical patterns of GF varied between the episodes. In the three regional-scale GF episodes, most major events occurred in regions where prolonged drought (PD) had been recorded prior, and significant associations between GF scores and PD were found in GF2001 and GF2002. However, the frequency of PD was higher than that of GF throughout the peninsula. In contrast, low temperature (LT) was observed during the study period only before GF2002 and GF2005, but there was no clear spatial relationship between GF and LT in the regional-scale episodes. There was also no evidence that last GF condition influenced the magnitude of GF. Thus, our results suggest that PD would be essential to trigger regional-scale GF in the peninsula, but also that PD does not fully explain the spatial and temporal patterns of GF. The coarse relationships between GF and the proposed climatic cues may be due to the geographical variation in proximate cues for GF, and the climatic and floristic geographical variations should be considered to understand the proximate factors of GF. PMID:24260159

Detecting spatial patterns with the cumulant function – Part 2: An application to El Niño

Directory of Open Access Journals (Sweden)

P. Yiou

2008-02-01

Full Text Available The spatial coherence of a measured variable (e.g. temperature or pressure is often studied to determine the regions of high variability or to find teleconnections, i.e. correlations between specific regions. While usual methods to find spatial patterns, such as Principal Components Analysis (PCA, are constrained by linear symmetries, the dependence of variables such as temperature or pressure at different locations is generally nonlinear. In particular, large deviations from the sample mean are expected to be strongly affected by such nonlinearities. Here we apply a newly developed nonlinear technique (Maxima of Cumulant Function, MCF for detection of typical spatial patterns that largely deviate from the mean. In order to test the technique and to introduce the methodology, we focus on the El Niño/Southern Oscillation and its spatial patterns. We find nonsymmetric temperature patterns corresponding to El Niño and La Niña, and we compare the results of MCF with other techniques, such as the symmetric solutions of PCA, and the nonsymmetric solutions of Nonlinear PCA (NLPCA. We found that MCF solutions are more reliable than the NLPCA fits, and can capture mixtures of principal components. Finally, we apply Extreme Value Theory on the temporal variations extracted from our methodology. We find that the tails of the distribution of extreme temperatures during La Niña episodes is bounded, while the tail during El Niños is less likely to be bounded. This implies that the mean spatial patterns of the two phases are asymmetric, as well as the behaviour of their extremes.

Spatial analysis of weed patterns

NARCIS (Netherlands)

Heijting, S.

2007-01-01

Keywords: Spatial analysis, weed patterns, Mead’s test, space-time correlograms, 2-D correlograms, dispersal, Generalized Linear Models, heterogeneity, soil, Taylor’s power law. Weeds in agriculture occur in patches. This thesis is a contribution to the characterization of this patchiness, to its

Recent history of trends in vegetation greenness and large-scale ecosystem disturbances in Eurasia

International Nuclear Information System (INIS)

Potter, Christopher; Nemani, Ramakrishna; Kumar, Vipin; Klooster, Steven

2007-01-01

Recent patterns of land cover and vegetation dynamics on the Euasian continent have been linked to changes in the global carbon cycle. Our study was conducted to evaluate patterns in a 19-yr record of global satellite observations of terrestrial vegetation from the Advanced Very High Resolution Radiometer (AVHRR) as a means to characterize major trends in both vegetation 'greenness' and ecosystem disturbance. The fraction absorbed of photosynthetically active radiation (FPAR) by vegetation canopies worldwide has been computed from the AVHRR at a monthly time interval from 1982 to 2000 and gridded at a spatial resolution of 8 km globally. Unlike previous studies of the AVHRR multiyear time-series of vegetation dynamics, the 8-km spatial resolution makes it possible to compare disturbance events and greenness trends at the same level of spatial detail. Positive trends in FPAR were detected throughout a major greenbelt of central-eastern Europe starting in the mid-1980s. This Eurasian greenbelt extended in a wide swath over the Urals, into the vicinity of Lake Baykal south of the central Siberian plateau, mainly along a latitude belt from 55 deg N to 65 deg N. There was also significantly positive greening in relatively large areas of Great Britain, Italy, Greece, Turkey, the Caucasus and southern India. Nonetheless, a strong downward trend in the FPAR time-series over most of Eurasia was observed by the end of the 1990s. Throughout the 19-yr time period, Eurasia was also impacted by many notable droughts and other disturbance events that could have substantially offset decadal carbon gains attributed to satellite-observed greening. Large-scale ecosystems disturbance events were identified in the FPAR time-series by locating anomalously low values (FPAR-LO) that lasted longer than 12 consecutive months at any 8-km pixel. We find verifiable evidence of numerous disturbance types across Eurasia, including regional patterns of severe droughts, forest fires and insect

Spatial pattern in Antarctica: what can we learn from Antarctic bacterial isolates?

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Chong, Chun Wie; Goh, Yuh Shan; Convey, Peter; Pearce, David; Tan, Irene Kit Ping

2013-09-01

A range of small- to moderate-scale studies of patterns in bacterial biodiversity have been conducted in Antarctica over the last two decades, most suggesting strong correlations between the described bacterial communities and elements of local environmental heterogeneity. However, very few of these studies have advanced interpretations in terms of spatially associated patterns, despite increasing evidence of patterns in bacterial biogeography globally. This is likely to be a consequence of restricted sampling coverage, with most studies to date focusing only on a few localities within a specific Antarctic region. Clearly, there is now a need for synthesis over a much larger spatial to consolidate the available data. In this study, we collated Antarctic bacterial culture identities based on the 16S rRNA gene information available in the literature and the GenBank database (n > 2,000 sequences). In contrast to some recent evidence for a distinct Antarctic microbiome, our phylogenetic comparisons show that a majority (~75 %) of Antarctic bacterial isolates were highly similar (≥99 % sequence similarity) to those retrieved from tropical and temperate regions, suggesting widespread distribution of eurythermal mesophiles in Antarctic environments. However, across different Antarctic regions, the dominant bacterial genera exhibit some spatially distinct diversity patterns analogous to those recently proposed for Antarctic terrestrial macroorganisms. Taken together, our results highlight the threat of cross-regional homogenisation in Antarctic biodiversity, and the imperative to include microbiota within the framework of biosecurity measures for Antarctica.

Spatial relationships and movement patterns of the air cargo industry in airport regions

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Petrus J. van V. Coetzee

2017-05-01

Full Text Available Background: During the past few years, with the increase in air traffic and the expansion of airports, very few industries had such a large spatial development and movement impact as that of airport-related clusters or airport regions. Although much research was done on the various impacts of the airport industry, very little research was done on the air cargo industry in airport regions. Objectives: This article specifically explored the unique spatial relationships, impacts, trends and movement patterns of the air cargo industry within a typical airport region. Method: The article focused on the OR Tambo International Airport in Gauteng, South Africa, as a case study and was informed by an extensive quantitative spatial and land use analysis and modelling of the study area. Results: The article presented findings and insights on the movement patterns and relationships between (1 the airport facility and (2 the spatial configuration of air cargo industries in the particular airport region. These findings also provided some framework for a possible spatial model and guideline that could assist in steering and managing development and movement patterns in airport regions. Conclusion: The article provided new insights and understanding on the spatial dynamics of airport regions and the air cargo industry, ultimately addressing some gaps in this knowledge field. The article in the end highlighted the need for a different and novel approach to the planning and management of the air cargo industry in airport regions and a basis for further research.

Concepts: Integrating population survey data from different spatial scales, sampling methods, and species

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Dorazio, Robert; Delampady, Mohan; Dey, Soumen; Gopalaswamy, Arjun M.; Karanth, K. Ullas; Nichols, James D.

2017-01-01

Conservationists and managers are continually under pressure from the public, the media, and political policy makers to provide “tiger numbers,” not just for protected reserves, but also for large spatial scales, including landscapes, regions, states, nations, and even globally. Estimating the abundance of tigers within relatively small areas (e.g., protected reserves) is becoming increasingly tractable (see Chaps. 9 and 10), but doing so for larger spatial scales still presents a formidable challenge. Those who seek “tiger numbers” are often not satisfied by estimates of tiger occupancy alone, regardless of the reliability of the estimates (see Chaps. 4 and 5). As a result, wherever tiger conservation efforts are underway, either substantially or nominally, scientists and managers are frequently asked to provide putative large-scale tiger numbers based either on a total count or on an extrapolation of some sort (see Chaps. 1 and 2).

Mapping spatial patterns of people's risk perception of landslides

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Kofler, Christian; Pedoth, Lydia; Elzbieta Stawinoga, Agnieszka; Schneiderbauer, Stefan

2016-04-01

The resilience of communities against natural hazards is largely influenced by how the individuals perceive risk. A good understanding of people's risk perception, awareness and hazard knowledge is crucial for developing and improving risk management and communication strategies between authorities and the affected population. A lot of research has been done in investigating the social aspects of risks to natural hazards by means of interviews or questionnaires. However, there is still a lack of research in the investigation of the influence of the spatial distance to a hazard event on peoples risk perception. While the spatial dimension of a natural hazard event is always assessed in works with a natural science approach, it is often neglected in works on social aspects of natural hazards. In the present study, we aimed to overcome these gaps by combining methods from different disciplines and assessing and mapping the spatial pattern of risk perception through multivariate statistical approaches based on empirical data from questionnaires. We will present results from a case study carried out in Badia, located in the Province of South Tyrol- Italy, where in December 2012 a landslide destroyed four residential buildings and led to the evacuation of 36 people. By means of questionnaires distributed to all adults living in the case study area we assessed people's risk perception and asked respondents to allocate their place of residence on a map of the case study area subdivided in 7 zones. Based on the data of the questionnaire results we developed a risk perception factor in order to express various assessed aspects linked to risk perception with one metric. We analyzed and mapped this factor according to the different zones reflecting the spatial distance to the event. Furthermore, a cluster analysis identified various risk behavior profiles within the population. We also investigated the spatial patterns of these risk profiles. We revealed that the residential

Spatial occupancy models for large data sets

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Johnson, Devin S.; Conn, Paul B.; Hooten, Mevin B.; Ray, Justina C.; Pond, Bruce A.

2013-01-01

Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit-normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced-dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open-source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km2) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open-source software allows for a facile and stable implementation of spatial occupancy models for large data sets.

Spatial and temporal variance in fatty acid and stable isotope signatures across trophic levels in large river systems

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Fritts, Andrea; Knights, Brent C.; Lafrancois, Toben D.; Bartsch, Lynn; Vallazza, Jon; Bartsch, Michelle; Richardson, William B.; Karns, Byron N.; Bailey, Sean; Kreiling, Rebecca

2018-01-01

Fatty acid and stable isotope signatures allow researchers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were to evaluate variance structures for fatty acids and stable isotopes (i.e. δ13C and δ15N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegill across spatial scales (10s-100s km) in large rivers of the Upper Mississippi River Basin, USA that were sampled annually for two years, and to evaluate the implications of this variance on the design and interpretation of trophic studies. The highest variance for both isotopes was present at the largest spatial scale for all taxa (except seston δ15N) indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local-scale alterations. Conversely, the highest variance for fatty acids was present at the smallest spatial scale (i.e. among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable to assess ecological questions at larger spatial scales.

Spatially Different Tissue-Scale Diffusivity Shapes ANGUSTIFOLIA3 Gradient in Growing Leaves.

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Kawade, Kensuke; Tanimoto, Hirokazu; Horiguchi, Gorou; Tsukaya, Hirokazu

2017-09-05

The spatial gradient of signaling molecules is pivotal for establishing developmental patterns of multicellular organisms. It has long been proposed that these gradients could arise from the pure diffusion process of signaling molecules between cells, but whether this simplest mechanism establishes the formation of the tissue-scale gradient remains unclear. Plasmodesmata are unique channel structures in plants that connect neighboring cells for molecular transport. In this study, we measured cellular- and tissue-scale kinetics of molecular transport through plasmodesmata in Arabidopsis thaliana developing leaf primordia by fluorescence recovery assays. These trans-scale measurements revealed biophysical properties of diffusive molecular transport through plasmodesmata and revealed that the tissue-scale diffusivity, but not the cellular-scale diffusivity, is spatially different along the leaf proximal-to-distal axis. We found that the gradient in cell size along the developmental axis underlies this spatially different tissue-scale diffusivity. We then asked how this diffusion-based framework functions in establishing a signaling gradient of endogenous molecules. ANGUSTIFOLIA3 (AN3) is a transcriptional co-activator, and as we have shown here, it forms a long-range signaling gradient along the leaf proximal-to-distal axis to determine a cell-proliferation domain. By genetically engineering AN3 mobility, we assessed each contribution of cell-to-cell movement and tissue growth to the distribution of the AN3 gradient. We constructed a diffusion-based theoretical model using these quantitative data to analyze the AN3 gradient formation and demonstrated that it could be achieved solely by the diffusive molecular transport in a growing tissue. Our results indicate that the spatially different tissue-scale diffusivity is a core mechanism for AN3 gradient formation. This provides evidence that the pure diffusion process establishes the formation of the long-range signaling

Integrating cross-scale analysis in the spatial and temporal domains for classification of behavioral movement

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Ali Soleymani

2014-06-01

Full Text Available Since various behavioral movement patterns are likely to be valid within different, unique ranges of spatial and temporal scales (e.g., instantaneous, diurnal, or seasonal with the corresponding spatial extents, a cross-scale approach is needed for accurate classification of behaviors expressed in movement. Here, we introduce a methodology for the characterization and classification of behavioral movement data that relies on computing and analyzing movement features jointly in both the spatial and temporal domains. The proposed methodology consists of three stages. In the first stage, focusing on the spatial domain, the underlying movement space is partitioned into several zonings that correspond to different spatial scales, and features related to movement are computed for each partitioning level. In the second stage, concentrating on the temporal domain, several movement parameters are computed from trajectories across a series of temporal windows of increasing sizes, yielding another set of input features for the classification. For both the spatial and the temporal domains, the ``reliable scale'' is determined by an automated procedure. This is the scale at which the best classification accuracy is achieved, using only spatial or temporal input features, respectively. The third stage takes the measures from the spatial and temporal domains of movement, computed at the corresponding reliable scales, as input features for behavioral classification. With a feature selection procedure, the most relevant features contributing to known behavioral states are extracted and used to learn a classification model. The potential of the proposed approach is demonstrated on a dataset of adult zebrafish (Danio rerio swimming movements in testing tanks, following exposure to different drug treatments. Our results show that behavioral classification accuracy greatly increases when firstly cross-scale analysis is used to determine the best analysis scale, and

Sizing and scaling requirements of a large-scale physical model for code validation

International Nuclear Information System (INIS)

Khaleel, R.; Legore, T.

1990-01-01

Model validation is an important consideration in application of a code for performance assessment and therefore in assessing the long-term behavior of the engineered and natural barriers of a geologic repository. Scaling considerations relevant to porous media flow are reviewed. An analysis approach is presented for determining the sizing requirements of a large-scale, hydrology physical model. The physical model will be used to validate performance assessment codes that evaluate the long-term behavior of the repository isolation system. Numerical simulation results for sizing requirements are presented for a porous medium model in which the media properties are spatially uncorrelated

Assessing Human Modifications to Floodplains using Large-Scale Hydrogeomorphic Floodplain Modeling

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Morrison, R. R.; Scheel, K.; Nardi, F.; Annis, A.

2017-12-01

Human modifications to floodplains for water resource and flood management purposes have significantly transformed river-floodplain connectivity dynamics in many watersheds. Bridges, levees, reservoirs, shifts in land use, and other hydraulic engineering works have altered flow patterns and caused changes in the timing and extent of floodplain inundation processes. These hydrogeomorphic changes have likely resulted in negative impacts to aquatic habitat and ecological processes. The availability of large-scale topographic datasets at high resolution provide an opportunity for detecting anthropogenic impacts by means of geomorphic mapping. We have developed and are implementing a methodology for comparing a hydrogeomorphic floodplain mapping technique to hydraulically-modeled floodplain boundaries to estimate floodplain loss due to human activities. Our hydrogeomorphic mapping methodology assumes that river valley morphology intrinsically includes information on flood-driven erosion and depositional phenomena. We use a digital elevation model-based algorithm to identify the floodplain as the area of the fluvial corridor laying below water reference levels, which are estimated using a simplified hydrologic model. Results from our hydrogeomorphic method are compared to hydraulically-derived flood zone maps and spatial datasets of levee protected-areas to explore where water management features, such as levees, have changed floodplain dynamics and landscape features. Parameters associated with commonly used F-index functions are quantified and analyzed to better understand how floodplain areas have been reduced within a basin. Preliminary results indicate that the hydrogeomorphic floodplain model is useful for quickly delineating floodplains at large watershed scales, but further analyses are needed to understand the caveats for using the model in determining floodplain loss due to levees. We plan to continue this work by exploring the spatial dependencies of the F

Balancing geo-privacy and spatial patterns in epidemiological studies

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Chien-Chou Chen

2017-11-01

Full Text Available To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-spatial tool (GeoMasker intended to mask the residential locations of patients or cases in a geographic information system (GIS. To elucidate the effects of geo-masking parameters, we applied 2010 dengue epidemic data from Taiwan testing the tool’s performance in an empirical situation. The similarity of pre- and post-spatial patterns was measured by D statistics under a 95% confidence interval. In the empirical study, different magnitudes of anonymisation (estimated Kanonymity ≥10 and 100 were achieved and different degrees of agreement on the pre- and post-patterns were evaluated. The application is beneficial for public health workers and researchers when processing data with individuals’ spatial information.

Temporal and Spatial Scales Matter: Circannual Habitat Selection by Bird Communities in Vineyards.

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Claire Guyot

Full Text Available Vineyards are likely to be regionally important for wildlife, but we lack biodiversity studies in this agroecosystem which is undergoing a rapid management revolution. As vine cultivation is restricted to arid and warm climatic regions, biodiversity-friendly management would promote species typical of southern biomes. Vineyards are often intensively cultivated, mostly surrounded by few natural features and offering a fairly mineral appearance with little ground vegetation cover. Ground vegetation cover and composition may further strongly vary with respect to season, influencing patterns of habitat selection by ecological communities. We investigated season-specific bird-habitat associations to highlight the importance of semi-natural habitat features and vineyard ground vegetation cover throughout the year. Given that avian habitat selection varies according to taxa, guilds and spatial scale, we modelled bird-habitat associations in all months at two spatial scales using mixed effects regression models. At the landscape scale, birds were recorded along 10 1-km long transects in Southwestern Switzerland (February 2014 -January 2015. At the field scale, we compared the characteristics of visited and unvisited vineyard fields (hereafter called parcels. Bird abundance in vineyards tripled in winter compared to summer. Vineyards surrounded by a greater amount of hedges and small woods harboured higher bird abundance, species richness and diversity, especially during the winter season. Regarding ground vegetation, birds showed a season-specific habitat selection pattern, notably a marked preference for ground-vegetated parcels in winter and for intermediate vegetation cover in spring and summer. These season-specific preferences might be related to species-specific life histories: more insectivorous, ground-foraging species occur during the breeding season whereas granivores predominate in winter. These results highlight the importance of

A bio-inspired spatial patterning circuit.

Science.gov (United States)

Chen, Kai-Yuan; Joe, Danial J; Shealy, James B; Land, Bruce R; Shen, Xiling

2014-01-01

Lateral Inhibition (LI) is a widely conserved patterning mechanism in biological systems across species. Distinct from better-known Turing patterns, LI depend on cell-cell contact rather than diffusion. We built an in silico genetic circuit model to analyze the dynamic properties of LI. The model revealed that LI amplifies differences between neighboring cells to push them into opposite states, hence forming stable 2-D patterns. Inspired by this insight, we designed and implemented an electronic circuit that recapitulates LI patterning dynamics. This biomimetic system serve as a physical model to elucidate the design principle of generating robust patterning through spatial feedback, regardless of the underlying devices being biological or electrical.

Large Scale Processes and Extreme Floods in Brazil

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Ribeiro Lima, C. H.; AghaKouchak, A.; Lall, U.

2016-12-01

Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).

DYNAMIC MATHEMATICAL MODEL OF URBAN SPATIAL PATTERN (RESIDENTIAL CHOICE OF LOCATION: MOBILITY VS EXTERNALITY

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Rahma Fitriani

2015-01-01

Full Text Available Household’s residential choice of location determines urban spatial pattern (e.g sprawl. The static model which assumes that the choice has been affected by distance to the CBD and location specific externality, fails to capture the evoution of the pattern over time. Therefore this study proposes a dynamic version of the model. It analyses the effects of externalities on the optimal solution of development decision as function of time. It also derives the effect of mobility and externality on the rate of change of development pattern through time. When the increasing rate of utility is not as significant as the increasing rate of income, the externalities will delay the change of urban spatial pattern over time. If the mobility costs increase by large amount relative to the increase of income and inflation rate, then the mobility effect dominates the effects of externalities in delaying the urban expansion.

Inferring processes from spatial patterns: the role of directional and non-directional forces in shaping fish larvae distribution in a freshwater lake system.

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Andrea Bertolo

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

Resource heterogeneity and foraging behaviour of cattle across spatial scales

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Demment Montague W

2009-04-01

Full Text Available Abstract Background Understanding the mechanisms that influence grazing selectivity in patchy environments is vital to promote sustainable production and conservation of cultivated and natural grasslands. To better understand how patch size and spatial dynamics influence selectivity in cattle, we examined grazing selectivity under 9 different treatments by offering alfalfa and fescue in patches of 3 sizes spaced with 1, 4, and 8 m between patches along an alley. We hypothesized that (1 selectivity is driven by preference for the forage species that maximizes forage intake over feeding scales ranging from single bites to patches along grazing paths, (2 that increasing patch size enhances selectivity for the preferred species, and that (3 increasing distances between patches restricts selectivity because of the aggregation of scale-specific behaviours across foraging scales. Results Cows preferred and selected alfalfa, the species that yielded greater short-term intake rates (P Conclusion We conclude that patch size and spacing affect components of intake rate and, to a lesser extent, the selectivity of livestock at lower hierarchies of the grazing process, particularly by enticing livestock to make more even use of the available species as patches are spaced further apart. Thus, modifications in the spatial pattern of plant patches along with reductions in the temporal and spatial allocation of grazing may offer opportunities to improve uniformity of grazing by livestock and help sustain biodiversity and stability of plant communities.

Using Remote Sensing to Determine the Spatial Scales of Estuaries

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Davis, C. O.; Tufillaro, N.; Nahorniak, J.

2016-02-01

One challenge facing Earth system science is to understand and quantify the complexity of rivers, estuaries, and coastal zone regions. Earlier studies using data from airborne hyperspectral imagers (Bissett et al., 2004, Davis et al., 2007) demonstrated from a very limited data set that the spatial scales of the coastal ocean could be resolved with spatial sampling of 100 m Ground Sample Distance (GSD) or better. To develop a much larger data set (Aurin et al., 2013) used MODIS 250 m data for a wide range of coastal regions. Their conclusion was that farther offshore 500 m GSD was adequate to resolve large river plume features while nearshore regions (a few kilometers from the coast) needed higher spatial resolution data not available from MODIS. Building on our airborne experience, the Hyperspectral Imager for the Coastal Ocean (HICO, Lucke et al., 2011) was designed to provide hyperspectral data for the coastal ocean at 100 m GSD. HICO operated on the International Space Station for 5 years and collected over 10,000 scenes of the coastal ocean and other regions around the world. Here we analyze HICO data from an example set of major river delta regions to assess the spatial scales of variability in those systems. In one system, the San Francisco Bay and Delta, we also analyze Landsat 8 OLI data at 30 m and 15 m to validate the 100 m GSD sampling scale for the Bay and assess spatial sampling needed as you move up river.

Termites Are Resistant to the Effects of Fire at Multiple Spatial Scales.

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Sarah C Avitabile

Full Text Available Termites play an important ecological role in many ecosystems, particularly in nutrient-poor arid and semi-arid environments. We examined the distribution and occurrence of termites in the fire-prone, semi-arid mallee region of south-eastern Australia. In addition to periodic large wildfires, land managers use fire as a tool to achieve both asset protection and ecological outcomes in this region. Twelve taxa of termites were detected by using systematic searches and grids of cellulose baits at 560 sites, clustered in 28 landscapes selected to represent different fire mosaic patterns. There was no evidence of a significant relationship between the occurrence of termite species and time-since-fire at the site scale. Rather, the occurrence of species was related to habitat features such as the density of mallee trees and large logs (>10 cm diameter. Species richness was greater in chenopod mallee vegetation on heavier soils in swales, rather than Triodia mallee vegetation of the sandy dune slopes. At the landscape scale, there was little evidence that the frequency of occurrence of termite species was related to fire, and no evidence that habitat heterogeneity generated by fire influenced termite species richness. The most influential factor at the landscape scale was the environmental gradient represented by average annual rainfall. Although termites may be associated with flammable habitat components (e.g. dead wood, they appear to be buffered from the effects of fire by behavioural traits, including nesting underground, and the continued availability of dead wood after fire. There is no evidence to support the hypothesis that a fine-scale, diverse mosaic of post-fire age-classes will enhance the diversity of termites. Rather, termites appear to be resistant to the effects of fire at multiple spatial scales.

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

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

2018-03-29

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

HFSB-seeding for large-scale tomographic PIV in wind tunnels

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Caridi, Giuseppe Carlo Alp; Ragni, Daniele; Sciacchitano, Andrea; Scarano, Fulvio

2016-12-01

A new system for large-scale tomographic particle image velocimetry in low-speed wind tunnels is presented. The system relies upon the use of sub-millimetre helium-filled soap bubbles as flow tracers, which scatter light with intensity several orders of magnitude higher than micron-sized droplets. With respect to a single bubble generator, the system increases the rate of bubbles emission by means of transient accumulation and rapid release. The governing parameters of the system are identified and discussed, namely the bubbles production rate, the accumulation and release times, the size of the bubble injector and its location with respect to the wind tunnel contraction. The relations between the above parameters, the resulting spatial concentration of tracers and measurement of dynamic spatial range are obtained and discussed. Large-scale experiments are carried out in a large low-speed wind tunnel with 2.85 × 2.85 m2 test section, where a vertical axis wind turbine of 1 m diameter is operated. Time-resolved tomographic PIV measurements are taken over a measurement volume of 40 × 20 × 15 cm3, allowing the quantitative analysis of the tip-vortex structure and dynamical evolution.

Algorithmic foundation of multi-scale spatial representation

CERN Document Server

Li, Zhilin

2006-01-01

With the widespread use of GIS, multi-scale representation has become an important issue in the realm of spatial data handling. However, no book to date has systematically tackled the different aspects of this discipline. Emphasizing map generalization, Algorithmic Foundation of Multi-Scale Spatial Representation addresses the mathematical basis of multi-scale representation, specifically, the algorithmic foundation.Using easy-to-understand language, the author focuses on geometric transformations, with each chapter surveying a particular spatial feature. After an introduction to the essential operations required for geometric transformations as well as some mathematical and theoretical background, the book describes algorithms for a class of point features/clusters. It then examines algorithms for individual line features, such as the reduction of data points, smoothing (filtering), and scale-driven generalization, followed by a discussion of algorithms for a class of line features including contours, hydrog...

Spatial and temporal patterns of bank failure during extreme flood events: Evidence of nonlinearity and self-organised criticality at the basin scale?

Science.gov (United States)

Thompson, C. J.; Croke, J. C.; Grove, J. R.

2012-04-01

Non-linearity in physical systems provides a conceptual framework to explain complex patterns and form that are derived from complex internal dynamics rather than external forcings, and can be used to inform modeling and improve landscape management. One process that has been investigated previously to explore the existence of self-organised critical system (SOC) in river systems at the basin-scale is bank failure. Spatial trends in bank failure have been previously quantified to determine if the distribution of bank failures at the basin scale exhibit the necessary power law magnitude/frequency distributions. More commonly bank failures are investigated at a small-scale using several cross-sections with strong emphasis on local-scale factors such as bank height, cohesion and hydraulic properties. Advancing our understanding of non-linearity in such processes, however, requires many more studies where both the spatial and temporal measurements of the process can be used to investigate the existence or otherwise of non-linearity and self-organised criticality. This study presents measurements of bank failure throughout the Lockyer catchment in southeast Queensland, Australia, which experienced an extreme flood event in January 2011 resulting in the loss of human lives and geomorphic channel change. The most dominant form of fluvial adjustment consisted of changes in channel geometry and notably widespread bank failures, which were readily identifiable as 'scalloped' shaped failure scarps. The spatial extents of these were mapped using high-resolution LiDAR derived digital elevation model and were verified by field surveys and air photos. Pre-flood event LiDAR coverage for the catchment also existed allowing direct comparison of the magnitude and frequency of bank failures from both pre and post-flood time periods. Data were collected and analysed within a GIS framework and investigated for power-law relationships. Bank failures appeared random and occurred

Data, data everywhere: detecting spatial patterns in fine-scale ecological information collected across a continent

Science.gov (United States)

Kevin M. Potter; Frank H. Koch; Christopher M. Oswalt; Basil V. Iannone

2016-01-01

Context Fine-scale ecological data collected across broad regions are becoming increasingly available. Appropriate geographic analyses of these data can help identify locations of ecological concern. Objectives We present one such approach, spatial association of scalable hexagons (SASH), whichidentifies locations where ecological phenomena occur at greater...

Potential climatic impacts and reliability of large-scale offshore wind farms