Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation.

PubMed

Qin, Changbo; Jia, Yangwen; Su, Z; Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-07-29

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

PubMed Central

Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-01-01

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946

Heterogeneous Link Weight Promotes the Cooperation in Spatial Prisoner's Dilemma

NASA Astrophysics Data System (ADS)

Ma, Zhi-Qin; Xia, Cheng-Yi; Sun, Shi-Wen; Wang, Li; Wang, Huai-Bin; Wang, Juan

The spatial structure has often been identified as a prominent mechanism that substantially promotes the cooperation level in prisoner's dilemma game. In this paper we introduce a weighting mechanism into the spatial prisoner's dilemma game to explore the cooperative behaviors on the square lattice. Here, three types of weight distributions: exponential, power-law and uniform distributions are considered, and the weight is assigned to links between players. Through large-scale numerical simulations we find, compared with the traditional spatial game, that this mechanism can largely enhance the frequency of cooperators. For most ranges of b, we find that the power-law distribution enables the highest promotion of cooperation and the uniform one leads to the lowest enhancement, whereas the exponential one lies often between them. The great improvement of cooperation can be caused by the fact that the distributional link weight yields inhomogeneous interaction strength among individuals, which can facilitate the formation of cooperative clusters to resist the defector's invasion. In addition, the impact of amplitude of the undulation of weight distribution and noise strength on cooperation is also investigated for three kinds of weight distribution. Current researches can aid in the further understanding of evolutionary cooperation in biological and social science.

Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing

NASA Technical Reports Server (NTRS)

Over, Thomas, M.; Gupta, Vijay K.

1994-01-01

Under the theory of independent and identically distributed random cascades, the probability distribution of the cascade generator determines the spatial and the ensemble properties of spatial rainfall. Three sets of radar-derived rainfall data in space and time are analyzed to estimate the probability distribution of the generator. A detailed comparison between instantaneous scans of spatial rainfall and simulated cascades using the scaling properties of the marginal moments is carried out. This comparison highlights important similarities and differences between the data and the random cascade theory. Differences are quantified and measured for the three datasets. Evidence is presented to show that the scaling properties of the rainfall can be captured to the first order by a random cascade with a single parameter. The dependence of this parameter on forcing by the large-scale meteorological conditions, as measured by the large-scale spatial average rain rate, is investigated for these three datasets. The data show that this dependence can be captured by a one-to-one function. Since the large-scale average rain rate can be diagnosed from the large-scale dynamics, this relationship demonstrates an important linkage between the large-scale atmospheric dynamics and the statistical cascade theory of mesoscale rainfall. Potential application of this research to parameterization of runoff from the land surface and regional flood frequency analysis is briefly discussed, and open problems for further research are presented.

Spatial pattern of risk of common raven predation on desert tortoises

USGS Publications Warehouse

Kristan, W. B.; Boarman, W.I.

2003-01-01

Common Ravens (Corvus corax) in the Mojave Desert of California, USA are subsidized by anthropogenic resources. Large numbers of nonbreeding ravens are attracted to human developments and thus are spatially restricted, whereas breeding ravens are distributed more evenly throughout the area. We investigated whether the spatial distribution of risk of predation by ravens to juveniles of the threatened desert tortoise (Gopherus agassizii) was determined by the spatial distribution of (1) nonbreeding ravens at human developments (leading to "spillover" predation) or (2) breeding individuals throughout developed and undeveloped areas (leading to " hyperpredation"). Predation risk, measured using styrofoam models of juvenile desert tortoises, was high near places attracting large numbers of nonbreeding ravens, near successful nests, and far from successful nests when large numbers of nonbreeding ravens were present. Patterns consistent with both "spillover" predation and "hyperpredation" were thus observed, attributed to the nonbreeding and breeding segments of the population, respectively. Furthermore, because locations of successful nests changed almost annually, consistent low-predation refugia for juvenile desert tortoises were nearly nonexistent. Consequently, anthropogenic resources for ravens could indirectly lead to the suppression, decline, or even extinction of desert tortoise populations.

Spatial probability models of fire in the desert grasslands of the southwestern USA

USDA-ARS?s Scientific Manuscript database

Fire is an important driver of ecological processes in semiarid environments; however, the role of fire in desert grasslands of the Southwestern US is controversial and the regional fire distribution is largely unknown. We characterized the spatial distribution of fire in the desert grassland region...

ON ASYMPTOTIC DISTRIBUTION AND ASYMPTOTIC EFFICIENCY OF LEAST SQUARES ESTIMATORS OF SPATIAL VARIOGRAM PARAMETERS. (R827257)

EPA Science Inventory

Abstract

In this article, we consider the least-squares approach for estimating parameters of a spatial variogram and establish consistency and asymptotic normality of these estimators under general conditions. Large-sample distributions are also established under a sp...

The spatial distributions of large gap-like structure on Fe(Se,Te) single crystals observed by STM/STS

NASA Astrophysics Data System (ADS)

Sugimoto, Akira; Sakai, Yuta; Nagasaka, Kouhei; Ekino, Toshikazu

2015-11-01

The nanoscale spatial distributions of large gap-like structure on superconducting FeSe1-xTex were investigated by scanning tunneling microscopy/spectroscopy (STM/STS). The STM topography shows regular atomic lattice arrangements with the lattice spacing ∼0.38 nm, together with the randomly distributed large spots due to the excess Fe atoms. From the STS measurements, the small gap structures of Δ ∼ 7 meV were partly observed. On the other hand, the high-bias dI/dV curves exhibit the broad peak structures at the negative biases of VPG = -200 to -400 mV in the measured whole surface area. The average of these large gaps is |VPGave| ∼ 305 mV with the standard deviation of σ ∼ 48 mV. The spatial distributions of the VPG exhibit the domain structures consisting of the relatively smaller gaps (<250 meV), which correspond to the excess Fe positions. The small gap Δ ∼ 7 meV is also observed at those positions, suggesting that the excess Fe affects the electronic structures of FeSe1-xTex.

Spatial height directed microfluidic synthesis of transparent inorganic upconversion nano film

NASA Astrophysics Data System (ADS)

Liu, Xiaoxia; Zhu, Cheng; Liao, Wei; Jin, Junyang; Ni, Yaru; Lu, Chunhua; Xu, Zhongzi

2017-11-01

A microfluidic-based synthesis of an inorganic upconversion nano film has been developed with a large area of dense-distributed NaYF4 crystal grains in a silica glass micro-reactor and the film exhibits high transparence, strong upconversion luminescence and robust adhesion with the substrate. The spatial heights of micro-reactors are tuned between 31 and 227 mm, which can regulate flow regimes. The synergistic effect of spatial height and fluid regime is put forward, which influences diffusion paths and assembly ways of different precursor molecules and consequently directs final distributions and morphologies of crystal grains, as well as optical properties due to diversity of surface and thickness of films. The spatial height of 110 mm is advantageous for high transmittance of upconversion film due to the flat surface and appropriate film thickness of 67 nm. The height of 150 mm is in favor of uniform distribution of upconversion fluorescence and achieving the strongest fluorescence due to minimized optical loss. Such a transparent upconversion film with a large area of uniform distribution is promising to promote the application of upconversion materials and spatial height directed microfluidic regime have a certain significance on many microfluidic synthesis.

Conditional sampling technique to test the applicability of the Taylor hypothesis for the large-scale coherent structures

NASA Technical Reports Server (NTRS)

Hussain, A. K. M. F.

1980-01-01

Comparisons of the distributions of large scale structures in turbulent flow with distributions based on time dependent signals from stationary probes and the Taylor hypothesis are presented. The study investigated an area in the near field of a 7.62 cm circular air jet at a Re of 32,000, specifically having coherent structures through small-amplitude controlled excitation and stable vortex pairing in the jet column mode. Hot-wire and X-wire anemometry were employed to establish phase averaged spatial distributions of longitudinal and lateral velocities, coherent Reynolds stress and vorticity, background turbulent intensities, streamlines and pseudo-stream functions. The Taylor hypothesis was used to calculate spatial distributions of the phase-averaged properties, with results indicating that the usage of the local time-average velocity or streamwise velocity produces large distortions.

On spatial coalescents with multiple mergers in two dimensions.

PubMed

Heuer, Benjamin; Sturm, Anja

2013-08-01

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

Daphnia inhibits the emergence of spatial pattern in a simple consumer-resource system.

PubMed

Betini, Gustavo S; Avgar, Tal; McCann, Kevin S; Fryxell, John M

2017-04-01

Spatial self-organization can occur in many ecosystems with important effects on food web dynamics and the maintenance of biodiversity. The consumer-resource interaction is known to generate spatial patterning, but only a few empirical studies have investigated the effect of the consumer on resource distribution. Here we report results from a large aquatic mesocosm experiment used to investigate the effect of the consumer Daphnia magna on the distribution of its resource, the green algae Chlorella vulgaris. We maintained large tanks with capacity for 26 ,000 L with either algae or both algae and Daphnia in different temperature conditions. We found that the presence of D. magna inhibited spatial structure in algal distribution that arose as a consequence of increasing temperature. We conjecture that this homogenization effect might be caused by a combination of high mobility combined with high rates of algal consumption by Daphnia. Our study emphasizes the importance of both local constraints on growth and behavioral responses in either promoting or suppressing spatial self-organization in natural populations. © 2017 by the Ecological Society of America.

Reconstruction of spatial distributions of sound velocity and absorption in soft biological tissues using model ultrasonic tomographic data

NASA Astrophysics Data System (ADS)

Burov, V. A.; Zotov, D. I.; Rumyantseva, O. D.

2014-07-01

A two-step algorithm is used to reconstruct the spatial distributions of the acoustic characteristics of soft biological tissues-the sound velocity and absorption coefficient. Knowing these distributions is urgent for early detection of benign and malignant neoplasms in biological tissues, primarily in the breast. At the first stage, large-scale distributions are estimated; at the second step, they are refined with a high resolution. Results of reconstruction on the base of model initial data are presented. The principal necessity of preliminary reconstruction of large-scale distributions followed by their being taken into account at the second step is illustrated. The use of CUDA technology for processing makes it possible to obtain final images of 1024 × 1024 samples in only a few minutes.

Polymorphic mountain whitefish (Prosopium williamsoni) in a coastal riverscape: size class assemblages, distribution, and habitat associations

USGS Publications Warehouse

Starr, James C.; Torgersen, Christian E.

2015-01-01

We compared the assemblage structure, spatial distributions, and habitat associations of mountain whitefish (Prosopium williamsoni) morphotypes and size classes. We hypothesised that morphotypes would have different spatial distributions and would be associated with different habitat features based on feeding behaviour and diet. Spatially continuous sampling was conducted over a broad extent (29 km) in the Calawah River, WA (USA). Whitefish were enumerated via snorkelling in three size classes: small (10–29 cm), medium (30–49 cm), and large (≥50 cm). We identified morphotypes based on head and snout morphology: a pinocchio form that had an elongated snout and a normal form with a blunted snout. Large size classes of both morphotypes were distributed downstream of small and medium size classes, and normal whitefish were distributed downstream of pinocchio whitefish. Ordination of whitefish assemblages with nonmetric multidimensional scaling revealed that normal whitefish size classes were associated with higher gradient and depth, whereas pinocchio whitefish size classes were positively associated with pool area, distance upstream, and depth. Reach-scale generalised additive models indicated that normal whitefish relative density was associated with larger substrate size in downstream reaches (R2 = 0.64), and pinocchio whitefish were associated with greater stream depth in the reaches farther upstream (R2 = 0.87). These results suggest broad-scale spatial segregation (1–10 km), particularly between larger and more phenotypically extreme individuals. These results provide the first perspective on spatial distributions and habitat relationships of polymorphic mountain whitefish.

Restoration ecology: two-sex dynamics and cost minimization.

PubMed

Molnár, Ferenc; Caragine, Christina; Caraco, Thomas; Korniss, Gyorgy

2013-01-01

We model a spatially detailed, two-sex population dynamics, to study the cost of ecological restoration. We assume that cost is proportional to the number of individuals introduced into a large habitat. We treat dispersal as homogeneous diffusion in a one-dimensional reaction-diffusion system. The local population dynamics depends on sex ratio at birth, and allows mortality rates to differ between sexes. Furthermore, local density dependence induces a strong Allee effect, implying that the initial population must be sufficiently large to avert rapid extinction. We address three different initial spatial distributions for the introduced individuals; for each we minimize the associated cost, constrained by the requirement that the species must be restored throughout the habitat. First, we consider spatially inhomogeneous, unstable stationary solutions of the model's equations as plausible candidates for small restoration cost. Second, we use numerical simulations to find the smallest rectangular cluster, enclosing a spatially homogeneous population density, that minimizes the cost of assured restoration. Finally, by employing simulated annealing, we minimize restoration cost among all possible initial spatial distributions of females and males. For biased sex ratios, or for a significant between-sex difference in mortality, we find that sex-specific spatial distributions minimize the cost. But as long as the sex ratio maximizes the local equilibrium density for given mortality rates, a common homogeneous distribution for both sexes that spans a critical distance yields a similarly low cost.

Restoration Ecology: Two-Sex Dynamics and Cost Minimization

PubMed Central

Molnár, Ferenc; Caragine, Christina; Caraco, Thomas; Korniss, Gyorgy

2013-01-01

We model a spatially detailed, two-sex population dynamics, to study the cost of ecological restoration. We assume that cost is proportional to the number of individuals introduced into a large habitat. We treat dispersal as homogeneous diffusion in a one-dimensional reaction-diffusion system. The local population dynamics depends on sex ratio at birth, and allows mortality rates to differ between sexes. Furthermore, local density dependence induces a strong Allee effect, implying that the initial population must be sufficiently large to avert rapid extinction. We address three different initial spatial distributions for the introduced individuals; for each we minimize the associated cost, constrained by the requirement that the species must be restored throughout the habitat. First, we consider spatially inhomogeneous, unstable stationary solutions of the model’s equations as plausible candidates for small restoration cost. Second, we use numerical simulations to find the smallest rectangular cluster, enclosing a spatially homogeneous population density, that minimizes the cost of assured restoration. Finally, by employing simulated annealing, we minimize restoration cost among all possible initial spatial distributions of females and males. For biased sex ratios, or for a significant between-sex difference in mortality, we find that sex-specific spatial distributions minimize the cost. But as long as the sex ratio maximizes the local equilibrium density for given mortality rates, a common homogeneous distribution for both sexes that spans a critical distance yields a similarly low cost. PMID:24204810

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

PubMed

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

2018-03-29

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

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

PubMed

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

2015-01-01

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

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

PubMed Central

2015-01-01

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

BATSE analysis techniques for probing the GRB spatial and luminosity distributions

NASA Technical Reports Server (NTRS)

Hakkila, Jon; Meegan, Charles A.

1992-01-01

The Burst And Transient Source Experiment (BATSE) has measured homogeneity and isotropy parameters from an increasingly large sample of observed gamma-ray bursts (GRBs), while also maintaining a summary of the way in which the sky has been sampled. Measurement of both of these are necessary for any study of the BATSE data statistically, as they take into account the most serious observational selection effects known in the study of GRBs: beam-smearing and inhomogeneous, anisotropic sky sampling. Knowledge of these effects is important to analysis of GRB angular and intensity distributions. In addition to determining that the bursts are local, it is hoped that analysis of such distributions will allow boundaries to be placed on the true GRB spatial distribution and luminosity function. The technique for studying GRB spatial and luminosity distributions is direct. Results of BATSE analyses are compared to Monte Carlo models parameterized by a variety of spatial and luminosity characteristics.

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

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

Booth, T.E.

1996-01-01

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

Male group size, female distribution and changes in sexual segregation by Roosevelt elk

PubMed Central

Peterson, Leah M.

2017-01-01

Sexual segregation, or the differential use of space by males and females, is hypothesized to be a function of body size dimorphism. Sexual segregation can also manifest at small (social segregation) and large (habitat segregation) spatial scales for a variety of reasons. Furthermore, the connection between small- and large-scale sexual segregation has rarely been addressed. We studied a population of Roosevelt elk (Cervus elaphus roosevelti) across 21 years in north coastal California, USA, to assess small- and large-scale sexual segregation in winter. We hypothesized that male group size would associate with small-scale segregation and that a change in female distribution would associate with large-scale segregation. Variation in forage biomass might also be coupled to small and large-scale sexual segregation. Our findings were consistent with male group size associating with small-scale segregation and a change in female distribution associating with large-scale segregation. Females appeared to avoid large groups comprised of socially dominant males. Males appeared to occupy a habitat vacated by females because of a wider forage niche, greater tolerance to lethal risks, and, perhaps, to reduce encounters with other elk. Sexual segregation at both spatial scales was a poor predictor of forage biomass. Size dimorphism was coupled to change in sexual segregation at small and large spatial scales. Small scale segregation can seemingly manifest when all forage habitat is occupied by females and large scale segregation might happen when some forage habitat is not occupied by females. PMID:29121076

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

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

NASA Astrophysics Data System (ADS)

Li, J.

2017-12-01

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

Spatial distribution of citizen science casuistic observations for different taxonomic groups.

PubMed

Tiago, Patrícia; Ceia-Hasse, Ana; Marques, Tiago A; Capinha, César; Pereira, Henrique M

2017-10-16

Opportunistic citizen science databases are becoming an important way of gathering information on species distributions. These data are temporally and spatially dispersed and could have limitations regarding biases in the distribution of the observations in space and/or time. In this work, we test the influence of landscape variables in the distribution of citizen science observations for eight taxonomic groups. We use data collected through a Portuguese citizen science database (biodiversity4all.org). We use a zero-inflated negative binomial regression to model the distribution of observations as a function of a set of variables representing the landscape features plausibly influencing the spatial distribution of the records. Results suggest that the density of paths is the most important variable, having a statistically significant positive relationship with number of observations for seven of the eight taxa considered. Wetland coverage was also identified as having a significant, positive relationship, for birds, amphibians and reptiles, and mammals. Our results highlight that the distribution of species observations, in citizen science projects, is spatially biased. Higher frequency of observations is driven largely by accessibility and by the presence of water bodies. We conclude that efforts are required to increase the spatial evenness of sampling effort from volunteers.

Spatial distributions of biophysical conditions on the Ohio River

EPA Science Inventory

Conceptually, landscape and hydrogeomorphic features associated with large floodplain river ecosystems impose spatial organization on river biota, nutrients, and habitat. We examined whether resulting patchiness was evident in basin and riparian landcover, water chemistry, fish a...

Spatial mismatch analysis among hotspots of alien plant species, road and railway networks in Germany and Austria

PubMed Central

Morelli, Federico

2017-01-01

Road and railway networks are pervasive elements of all environments, which have expanded intensively over the last century in all European countries. These transportation infrastructures have major impacts on the surrounding landscape, representing a threat to biodiversity. Roadsides and railways may function as corridors for dispersal of alien species in fragmented landscapes. However, only few studies have explored the spread of invasive species in relationship to transport network at large spatial scales. We performed a spatial mismatch analysis, based on a spatially explicit correlation test, to investigate whether alien plant species hotspots in Germany and Austria correspond to areas of high density of roads and railways. We tested this independently of the effects of dominant environments in each spatial unit, in order to focus just on the correlation between occurrence of alien species and density of linear transportation infrastructures. We found a significant spatial association between alien plant species hotspots distribution and roads and railways density in both countries. As expected, anthropogenic landscapes, such as urban areas, harbored more alien plant species, followed by water bodies. However, our findings suggested that the distribution of neobiota is strongest correlated to road/railways density than to land use composition. This study provides new evidence, from a transnational scale, that alien plants can use roadsides and rail networks as colonization corridors. Furthermore, our approach contributes to the understanding on alien plant species distribution at large spatial scale by the combination with spatial modeling procedures. PMID:28829818

Spatial patterns of native freshwater mussels in the Upper Mississippi River

USGS Publications Warehouse

Ries, Patricia R.; DeJager, Nathan R.; Zigler, Steven J.; Newton, Teresa

2016-01-01

Multiple physical and biological factors structure freshwater mussel communities in large rivers, and their distributions have been described as clumped or patchy. However, few surveys of mussel populations have been conducted over areas large enough and at resolutions fine enough to quantify spatial patterns in their distribution. We used global and local indicators of spatial autocorrelation (i.e., Moran’s I) to quantify spatial patterns of adult and juvenile (≤5 y of age) freshwater mussels across multiple scales based on survey data from 4 reaches (navigation pools 3, 5, 6, and 18) of the Upper Mississippi River, USA. Native mussel densities were sampled at a resolution of ∼300 m and across distances ranging from 21 to 37 km, making these some of the most spatially extensive surveys conducted in a large river. Patch density and the degree and scale of patchiness varied by river reach, age group, and the scale of analysis. In all 4 pools, some patches of adults overlapped patches of juveniles, suggesting spatial and temporal persistence of adequate habitat. In pools 3 and 5, patches of juveniles were found where there were few adults, suggesting recent emergence of positive structuring mechanisms. Last, in pools 3, 5, and 6, some patches of adults were found where there were few juveniles, suggesting that negative structuring mechanisms may have replaced positive ones, leading to a lack of localized recruitment. Our results suggest that: 1) the detection of patches of freshwater mussels requires a multiscaled approach, 2) insights into the spatial and temporal dynamics of structuring mechanisms can be gained by conducting independent analyses of adults and juveniles, and 3) maps of patch distributions can be used to guide restoration and management actions and identify areas where mussels are most likely to influence ecosystem function.

Spatial discretization of large watersheds and its influence on the estimation of hillslope sediment yield

USDA-ARS?s Scientific Manuscript database

The combined use of water erosion models and geographic information systems (GIS) has facilitated soil loss estimation at the watershed scale. Tools such as the Geo-spatial interface for the Water Erosion Prediction Project (GeoWEPP) model provide a convenient spatially distributed soil loss estimat...

The spatial distribution of earthquake stress rotations following large subduction zone earthquakes

USGS Publications Warehouse

Hardebeck, Jeanne L.

2017-01-01

Rotations of the principal stress axes due to great subduction zone earthquakes have been used to infer low differential stress and near-complete stress drop. The spatial distribution of coseismic and postseismic stress rotation as a function of depth and along-strike distance is explored for three recent M ≥ 8.8 subduction megathrust earthquakes. In the down-dip direction, the largest coseismic stress rotations are found just above the Moho depth of the overriding plate. This zone has been identified as hosting large patches of large slip in great earthquakes, based on the lack of high-frequency radiated energy. The large continuous slip patches may facilitate near-complete stress drop. There is seismological evidence for high fluid pressures in the subducted slab around the Moho depth of the overriding plate, suggesting low differential stress levels in this zone due to high fluid pressure, also facilitating stress rotations. The coseismic stress rotations have similar along-strike extent as the mainshock rupture. Postseismic stress rotations tend to occur in the same locations as the coseismic stress rotations, probably due to the very low remaining differential stress following the near-complete coseismic stress drop. The spatial complexity of the observed stress changes suggests that an analytical solution for finding the differential stress from the coseismic stress rotation may be overly simplistic, and that modeling of the full spatial distribution of the mainshock static stress changes is necessary.

Using geostatistical methods to estimate snow water equivalence distribution in a mountain watershed

USGS Publications Warehouse

Balk, B.; Elder, K.; Baron, Jill S.

1998-01-01

Knowledge of the spatial distribution of snow water equivalence (SWE) is necessary to adequately forecast the volume and timing of snowmelt runoff.  In April 1997, peak accumulation snow depth and density measurements were independently taken in the Loch Vale watershed (6.6 km2), Rocky Mountain National Park, Colorado.  Geostatistics and classical statistics were used to estimate SWE distribution across the watershed.  Snow depths were spatially distributed across the watershed through kriging interpolation methods which provide unbiased estimates that have minimum variances.  Snow densities were spatially modeled through regression analysis.  Combining the modeled depth and density with snow-covered area (SCA produced an estimate of the spatial distribution of SWE.  The kriged estimates of snow depth explained 37-68% of the observed variance in the measured depths.  Steep slopes, variably strong winds, and complex energy balance in the watershed contribute to a large degree of heterogeneity in snow depth.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2018-08-01

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

Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis.

PubMed

Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

2016-08-18

The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

The Atacama Large Millimeter/submillimeter Array (alma): Early Results

NASA Astrophysics Data System (ADS)

Wootten, Alwyn

2012-06-01

New radioastronomical instruments, such as ALMA or the Jansky VLA, have increased spectral throughput by orders of magnitude over previously available capabilities. ALMA brings orders of magnitude increases in spectral sensitivity and spatial resolution over what has previously been available. These increased capabilities open new possibilities for studies of complex molecules in the interstellar medium. Complex interstellar molecules may form on the surfaces of interstellar grains, after which they may be liberated into the gas phase by shocks, radiation, or other external influences. Emission from complex molecules may be diluted owing to the large number of transitions large molecules may undergo, particularly in warm regions of interstellar clouds. High sensitivity and spatial resolution are necessary to explore the distributions and relationships of these molecules. Of particular interest are the distributions of large organic molecules. Observations which establish the relationships between various large molecules are now emerging from these new instruments and will be discussed.

Spatially distributed potential evapotranspiration modeling and climate projections.

PubMed

Gharbia, Salem S; Smullen, Trevor; Gill, Laurence; Johnston, Paul; Pilla, Francesco

2018-08-15

Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50m 2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatial Inference for Distributed Remote Sensing Data

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

'Fracking', Induced Seismicity and the Critical Earth

NASA Astrophysics Data System (ADS)

Leary, P.; Malin, P. E.

2012-12-01

Issues of 'fracking' and induced seismicity are reverse-analogous to the equally complex issues of well productivity in hydrocarbon, geothermal and ore reservoirs. In low hazard reservoir economics, poorly producing wells and low grade ore bodies are many while highly producing wells and high grade ores are rare but high pay. With induced seismicity factored in, however, the same distribution physics reverses the high/low pay economics: large fracture-connectivity systems are hazardous hence low pay, while high probability small fracture-connectivity systems are non-hazardous hence high pay. Put differently, an economic risk abatement tactic for well productivity and ore body pay is to encounter large-scale fracture systems, while an economic risk abatement tactic for 'fracking'-induced seismicity is to avoid large-scale fracture systems. Well productivity and ore body grade distributions arise from three empirical rules for fluid flow in crustal rock: (i) power-law scaling of grain-scale fracture density fluctuations; (ii) spatial correlation between spatial fluctuations in well-core porosity and the logarithm of well-core permeability; (iii) frequency distributions of permeability governed by a lognormality skewness parameter. The physical origin of rules (i)-(iii) is the universal existence of a critical-state-percolation grain-scale fracture-density threshold for crustal rock. Crustal fractures are effectively long-range spatially-correlated distributions of grain-scale defects permitting fluid percolation on mm to km scales. The rule is, the larger the fracture system the more intense the percolation throughput. As percolation pathways are spatially erratic and unpredictable on all scales, they are difficult to model with sparsely sampled well data. Phenomena such as well productivity, induced seismicity, and ore body fossil fracture distributions are collectively extremely difficult to predict. Risk associated with unpredictable reservoir well productivity and ore body distributions can be managed by operating in a context which affords many small failures for a few large successes. In reverse view, 'fracking' and induced seismicity could be rationally managed in a context in which many small successes can afford a few large failures. However, just as there is every incentive to acquire information leading to higher rates of productive well drilling and ore body exploration, there are equal incentives for acquiring information leading to lower rates of 'fracking'-induced seismicity. Current industry practice of using an effective medium approach to reservoir rock creates an uncritical sense that property distributions in rock are essentially uniform. Well-log data show that the reverse is true: the larger the length scale the greater the deviation from uniformity. Applying the effective medium approach to large-scale rock formations thus appears to be unnecessarily hazardous. It promotes the notion that large scale fluid pressurization acts against weakly cohesive but essentially uniform rock to produce large-scale quasi-uniform tensile discontinuities. Indiscriminate hydrofacturing appears to be vastly more problematic in reality than as pictured by the effective medium hypothesis. The spatial complexity of rock, especially at large scales, provides ample reason to find more controlled pressurization strategies for enhancing in situ flow.

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

PubMed

Zhang, Ling Yu; Liu, Zhao Gang

2017-12-01

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

Searches for and identification of effects of extra spatial dimensions in dilepton and diphoton production at the Large Hadron Collider

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

Pankov, A. A., E-mail: pankov@ictp.it; Serenkova, I. A., E-mail: inna.serenkova@cern.ch; Tsytrinov, A. V., E-mail: tsytrin@gstu.by

2015-06-15

Prospects of discovering and identifying effects of extra spatial dimensions in dilepton and diphoton production at the Large Hadron Collider (LHC) are studied. Such effects may be revealed by the characteristic behavior of the invariant-mass distributions of dileptons and diphotons, and their identification can be performed on the basis of an analysis of their angular distributions. The discovery and identification reaches are estimated for the scale parameter M{sub S} of the Kaluza-Klein gravitational towers, which can be determined in experiments devoted to measuring the dilepton and diphoton channels at the LHC.

Distribution of late Pleistocene ice-rich syngenetic permafrost of the Yedoma Suite in east and central Siberia, Russia

USGS Publications Warehouse

Grosse, Guido; Robinson, Joel E.; Bryant, Robin; Taylor, Maxwell D.; Harper, William; DeMasi, Amy; Kyker-Snowman, Emily; Veremeeva, Alexandra; Schirrmeister, Lutz; Harden, Jennifer

2013-01-01

This digital database is the product of collaboration between the U.S. Geological Survey, the Geophysical Institute at the University of Alaska, Fairbanks; the Los Altos Hills Foothill College GeoSpatial Technology Certificate Program; the Alfred Wegener Institute for Polar and Marine Research, Potsdam, Germany; and the Institute of Physical Chemical and Biological Problems in Soil Science of the Russian Academy of Sciences. The primary goal for creating this digital database is to enhance current estimates of soil organic carbon stored in deep permafrost, in particular the late Pleistocene syngenetic ice-rich permafrost deposits of the Yedoma Suite. Previous studies estimated that Yedoma deposits cover about 1 million square kilometers of a large region in central and eastern Siberia, but these estimates generally are based on maps with scales smaller than 1:10,000,000. Taking into account this large area, it was estimated that Yedoma may store as much as 500 petagrams of soil organic carbon, a large part of which is vulnerable to thaw and mobilization from thermokarst and erosion. To refine assessments of the spatial distribution of Yedoma deposits, we digitized 11 Russian Quaternary geologic maps. Our study focused on extracting geologic units interpreted by us as late Pleistocene ice-rich syngenetic Yedoma deposits based on lithology, ground ice conditions, stratigraphy, and geomorphological and spatial association. These Yedoma units then were merged into a single data layer across map tiles. The spatial database provides a useful update of the spatial distribution of this deposit for an approximately 2.32 million square kilometers land area in Siberia that will (1) serve as a core database for future refinements of Yedoma distribution in additional regions, and (2) provide a starting point to revise the size of deep but thaw-vulnerable permafrost carbon pools in the Arctic based on surface geology and the distribution of cryolithofacies types at high spatial resolution. However, we recognize that the extent of Yedoma deposits presented in this database is not complete for a global assessment, because Yedoma deposits also occur in the Taymyr lowlands and Chukotka, and in parts of Alaska and northwestern Canada.

Coherence area profiling in multi-spatial-mode squeezed states

DOE PAGES

Lawrie, Benjamin J.; Pooser, Raphael C.; Otterstrom, Nils T.

2015-09-12

The presence of multiple bipartite entangled modes in squeezed states generated by four-wave mixing enables ultra-trace sensing, imaging, and metrology applications that are impossible to achieve with single-spatial-mode squeezed states. For Gaussian seed beams, the spatial distribution of these bipartite entangled modes, or coherence areas, across each beam is largely dependent on the spatial modes present in the pump beam, but it has proven difficult to map the distribution of these coherence areas in frequency and space. We demonstrate an accessible method to map the distribution of the coherence areas within these twin beams. In addition, we also show thatmore » the pump shape can impart different noise properties to each coherence area, and that it is possible to select and detect coherence areas with optimal squeezing with this approach.« less

The Large -scale Distribution of Galaxies

NASA Astrophysics Data System (ADS)

Flin, Piotr

A review of the Large-scale structure of the Universe is given. A connection is made with the titanic work by Johannes Kepler in many areas of astronomy and cosmology. A special concern is made to spatial distribution of Galaxies, voids and walls (cellular structure of the Universe). Finaly, the author is concluding that the large scale structure of the Universe can be observed in much greater scale that it was thought twenty years ago.

Accuracy improvement in laser stripe extraction for large-scale triangulation scanning measurement system

NASA Astrophysics Data System (ADS)

Zhang, Yang; Liu, Wei; Li, Xiaodong; Yang, Fan; Gao, Peng; Jia, Zhenyuan

2015-10-01

Large-scale triangulation scanning measurement systems are widely used to measure the three-dimensional profile of large-scale components and parts. The accuracy and speed of the laser stripe center extraction are essential for guaranteeing the accuracy and efficiency of the measuring system. However, in the process of large-scale measurement, multiple factors can cause deviation of the laser stripe center, including the spatial light intensity distribution, material reflectivity characteristics, and spatial transmission characteristics. A center extraction method is proposed for improving the accuracy of the laser stripe center extraction based on image evaluation of Gaussian fitting structural similarity and analysis of the multiple source factors. First, according to the features of the gray distribution of the laser stripe, evaluation of the Gaussian fitting structural similarity is estimated to provide a threshold value for center compensation. Then using the relationships between the gray distribution of the laser stripe and the multiple source factors, a compensation method of center extraction is presented. Finally, measurement experiments for a large-scale aviation composite component are carried out. The experimental results for this specific implementation verify the feasibility of the proposed center extraction method and the improved accuracy for large-scale triangulation scanning measurements.

Multi-site calibration, validation, and sensitivity analysis of the MIKE SHE Model for a large watershed in northern China

Treesearch

S. Wang; Z. Zhang; G. Sun; P. Strauss; J. Guo; Y. Tang; A. Yao

2012-01-01

Model calibration is essential for hydrologic modeling of large watersheds in a heterogeneous mountain environment. Little guidance is available for model calibration protocols for distributed models that aim at capturing the spatial variability of hydrologic processes. This study used the physically-based distributed hydrologic model, MIKE SHE, to contrast a lumped...

Spatial effects in discrete generation population models.

PubMed

Carrillo, C; Fife, P

2005-02-01

A framework is developed for constructing a large class of discrete generation, continuous space models of evolving single species populations and finding their bifurcating patterned spatial distributions. Our models involve, in separate stages, the spatial redistribution (through movement laws) and local regulation of the population; and the fundamental properties of these events in a homogeneous environment are found. Emphasis is placed on the interaction of migrating individuals with the existing population through conspecific attraction (or repulsion), as well as on random dispersion. The nature of the competition of these two effects in a linearized scenario is clarified. The bifurcation of stationary spatially patterned population distributions is studied, with special attention given to the role played by that competition.

Spatially resolved spectroscopy analysis of the XMM-Newton large program on SN1006

NASA Astrophysics Data System (ADS)

Li, Jiang-Tao; Decourchelle, Anne; Miceli, Marco; Vink, Jacco; Bocchino, Fabrizio

2016-04-01

We perform analysis of the XMM-Newton large program on SN1006 based on our newly developed methods of spatially resolved spectroscopy analysis. We extract spectra from low and high resolution meshes. The former (3596 meshes) is used to roughly decompose the thermal and non-thermal components and characterize the spatial distributions of different parameters, such as temperature, abundances of different elements, ionization age, and electron density of the thermal component, as well as photon index and cutoff frequency of the non-thermal component. On the other hand, the low resolution meshes (583 meshes) focus on the interior region dominated by the thermal emission and have enough counts to well characterize the Si lines. We fit the spectra from the low resolution meshes with different models, in order to decompose the multiple plasma components at different thermal and ionization states and compare their spatial distributions. In this poster, we will present the initial results of this project.

A watershed scale spatially-distributed model for streambank erosion rate driven by channel curvature

NASA Astrophysics Data System (ADS)

McMillan, Mitchell; Hu, Zhiyong

2017-10-01

Streambank erosion is a major source of fluvial sediment, but few large-scale, spatially distributed models exist to quantify streambank erosion rates. We introduce a spatially distributed model for streambank erosion applicable to sinuous, single-thread channels. We argue that such a model can adequately characterize streambank erosion rates, measured at the outsides of bends over a 2-year time period, throughout a large region. The model is based on the widely-used excess-velocity equation and comprised three components: a physics-based hydrodynamic model, a large-scale 1-dimensional model of average monthly discharge, and an empirical bank erodibility parameterization. The hydrodynamic submodel requires inputs of channel centerline, slope, width, depth, friction factor, and a scour factor A; the large-scale watershed submodel utilizes watershed-averaged monthly outputs of the Noah-2.8 land surface model; bank erodibility is based on tree cover and bank height as proxies for root density. The model was calibrated with erosion rates measured in sand-bed streams throughout the northern Gulf of Mexico coastal plain. The calibrated model outperforms a purely empirical model, as well as a model based only on excess velocity, illustrating the utility of combining a physics-based hydrodynamic model with an empirical bank erodibility relationship. The model could be improved by incorporating spatial variability in channel roughness and the hydrodynamic scour factor, which are here assumed constant. A reach-scale application of the model is illustrated on ∼1 km of a medium-sized, mixed forest-pasture stream, where the model identifies streambank erosion hotspots on forested and non-forested bends.

Decomposing risk: landscape structure and wolf behavior generate different predation patterns in two sympatric ungulates.

PubMed

Gervasi, Vincenzo; Sand, Hakan; Zimmermann, Barbara; Mattisson, Jenny; Wabakken, Petter; Linnell, John D C

2013-10-01

Recolonizing carnivores can have a large impact on the status of wild ungulates, which have often modified their behavior in the absence of predation. Therefore, understanding the dynamics of reestablished predator-prey systems is crucial to predict their potential ecosystem effects. We decomposed the spatial structure of predation by recolonizing wolves (Canis lupus) on two sympatric ungulates, moose (Alces alces) and roe deer (Capreolus capreolus), in Scandinavia during a 10-year study. We monitored 18 wolves with GPS collars, distributed over 12 territories, and collected records from predation events. By using conditional logistic regression, we assessed the contributions of three main factors, the utilization patterns of each wolf territory, the spatial distribution of both prey species, and fine-scale landscape structure, in determining the spatial structure of moose and roe deer predation risk. The reestablished predator-prey system showed a remarkable spatial variation in kill occurrence at the intra-territorial level, with kill probabilities varying by several orders of magnitude inside the same territory. Variation in predation risk was evident also when a spatially homogeneous probability for a wolf to encounter a prey was simulated. Even inside the same territory, with the same landscape structure, and when exposed to predation by the same wolves, the two prey species experienced an opposite spatial distribution of predation risk. In particular, increased predation risk for moose was associated with open areas, especially clearcuts and young forest stands, whereas risk was lowered for roe deer in the same habitat types. Thus, fine-scale landscape structure can generate contrasting predation risk patterns in sympatric ungulates, so that they can experience large differences in the spatial distribution of risk and refuge areas when exposed to predation by a recolonizing predator. Territories with an earlier recolonization were not associated with a lower hunting success for wolves. Such constant efficiency in wolf predation during the recolonization process is in line with previous findings about the naive nature of Scandinavian moose to wolf predation. This, together with the human-dominated nature of the Scandinavian ecosystem, seems to limit the possibility for wolves to have large ecosystem effects and to establish a behaviorally mediated trophic cascade in Scandinavia.

Spatial and seasonal dynamic of abundance and distribution of guanaco and livestock: insights from using density surface and null models.

PubMed

Schroeder, Natalia M; Matteucci, Silvia D; Moreno, Pablo G; Gregorio, Pablo; Ovejero, Ramiro; Taraborelli, Paula; Carmanchahi, Pablo D

2014-01-01

Monitoring species abundance and distribution is a prerequisite when assessing species status and population viability, a difficult task to achieve for large herbivores at ecologically meaningful scales. Co-occurrence patterns can be used to infer mechanisms of community organization (such as biotic interactions), although it has been traditionally applied to binary presence/absence data. Here, we combine density surface and null models of abundance data as a novel approach to analyze the spatial and seasonal dynamics of abundance and distribution of guanacos (Lama guanicoe) and domestic herbivores in northern Patagonia, in order to visually and analytically compare the dispersion and co-occurrence pattern of ungulates. We found a marked seasonal pattern in abundance and spatial distribution of L. guanicoe. The guanaco population reached its maximum annual size and spatial dispersion in spring-summer, decreasing up to 6.5 times in size and occupying few sites of the study area in fall-winter. These results are evidence of the seasonal migration process of guanaco populations, an increasingly rare event for terrestrial mammals worldwide. The maximum number of guanacos estimated for spring (25,951) is higher than the total population size (10,000) 20 years ago, probably due to both counting methodology and population growth. Livestock were mostly distributed near human settlements, as expected by the sedentary management practiced by local people. Herbivore distribution was non-random; i.e., guanaco and livestock abundances co-varied negatively in all seasons, more than expected by chance. Segregation degree of guanaco and small-livestock (goats and sheep) was comparatively stronger than that of guanaco and large-livestock, suggesting a competition mechanism between ecologically similar herbivores, although various environmental factors could also contribute to habitat segregation. The new and compelling combination of methods used here is highly useful for researchers who conduct counts of animals to simultaneously estimate population sizes, distributions, assess temporal trends and characterize multi-species spatial interactions.

Spatial Distribution of Large Cloud Drops

NASA Technical Reports Server (NTRS)

Marshak, A.; Knyazikhin, Y.; Larsen, M.; Wiscombe, W.

2004-01-01

By analyzing aircraft measurements of individual drop sizes in clouds, we have shown in a companion paper (Knyazikhin et al., 2004) that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)) where 0 less than or equal to D(r) less than or equal to 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and therefore a Poisson distribution of cloud drops, these models show strong drop clustering, the more so the larger the drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics explaining how rain can form so fast. It also helps explain why remotely sensed cloud drop size is generally biased and why clouds absorb more sunlight than conventional radiative transfer models predict.

Spatial analysis and characteristics of pig farming in Thailand.

PubMed

Thanapongtharm, Weerapong; Linard, Catherine; Chinson, Pornpiroon; Kasemsuwan, Suwicha; Visser, Marjolein; Gaughan, Andrea E; Epprech, Michael; Robinson, Timothy P; Gilbert, Marius

2016-10-06

In Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets. Over the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed by the analysis. The very contrasted distribution of different pig production systems present opportunities for future regionalization of pig production. More specifically, the detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems.

Bridging the gap between small and large scale sediment budgets? - A scaling challenge in the Upper Rhone Basin, Switzerland

NASA Astrophysics Data System (ADS)

Schoch, Anna; Blöthe, Jan; Hoffmann, Thomas; Schrott, Lothar

2016-04-01

A large number of sediment budgets have been compiled on different temporal and spatial scales in alpine regions. Detailed sediment budgets based on the quantification of a number of sediment storages (e.g. talus cones, moraine deposits) exist only for a few small scale drainage basins (up to 10² km²). In contrast, large scale sediment budgets (> 10³ km²) consider only long term sediment sinks such as valley fills and lakes. Until now, these studies often neglect small scale sediment storages in the headwaters. However, the significance of these sediment storages have been reported. A quantitative verification whether headwaters function as sediment source regions is lacking. Despite substantial transport energy in mountain environments due to steep gradients and high relief, sediment flux in large river systems is frequently disconnected from alpine headwaters. This leads to significant storage of coarse-grained sediment along the flow path from rockwall source regions to large sedimentary sinks in major alpine valleys. To improve the knowledge on sediment budgets in large scale alpine catchments and to bridge the gap between small and large scale sediment budgets, we apply a multi-method approach comprising investigations on different spatial scales in the Upper Rhone Basin (URB). The URB is the largest inneralpine basin in the European Alps with a size of > 5400 km². It is a closed system with Lake Geneva acting as an ultimate sediment sink for suspended and clastic sediment. We examine the spatial pattern and volumes of sediment storages as well as the morphometry on the local and catchment-wide scale. We mapped sediment storages and bedrock in five sub-regions of the study area (Goms, Lötschen valley, Val d'Illiez, Vallée de la Liène, Turtmann valley) in the field and from high-resolution remote sensing imagery to investigate the spatial distribution of different sediment storage types (e.g. talus deposits, debris flow cones, alluvial fans). These sub-regions cover all three litho-tectonic units of the URB (Helvetic nappes, Penninic nappes, External massifs) and different catchment sizes to capture the inherent variability. Different parameters characterizing topography, surface characteristics, and vegetation cover are analyzed for each storage type. The data is then used in geostatistical models (PCA, stepwise logistic regression) to predict the spatial distribution of sediment storage for the whole URB. We further conduct morphometric analyses of the URB to gain information on the varying degree of glacial imprint and postglacial landscape evolution and their control on the spatial distribution of sediment storage in a large scale drainage basin. Geophysical methods (ground penetrating radar and electrical resistivity tomography) are applied on different sediment storage types on the local scale to estimate mean thicknesses. Additional data from published studies are used to complement our dataset. We integrate the local data in the statistical model on the spatial distribution of sediment storages for the whole URB. Hence, we can extrapolate the stored sediment volumes to the regional scale in order to bridge the gap between small and large scale studies.

Advanced data structures for the interpretation of image and cartographic data in geo-based information systems

NASA Technical Reports Server (NTRS)

Peuquet, D. J.

1986-01-01

A growing need to usse geographic information systems (GIS) to improve the flexibility and overall performance of very large, heterogeneous data bases was examined. The Vaster structure and the Topological Grid structure were compared to test whether such hybrid structures represent an improvement in performance. The use of artificial intelligence in a geographic/earth sciences data base context is being explored. The architecture of the Knowledge Based GIS (KBGIS) has a dual object/spatial data base and a three tier hierarchial search subsystem. Quadtree Spatial Spectra (QTSS) are derived, based on the quadtree data structure, to generate and represent spatial distribution information for large volumes of spatial data.

Probabilistic and spatially variable niches inferred from demography

Treesearch

Jeffrey M. Diez; Itamar Giladi; Robert Warren; H. Ronald Pulliam

2014-01-01

Summary 1. Mismatches between species distributions and habitat suitability are predicted by niche theory and have important implications for forecasting how species may respond to environmental changes. Quantifying these mismatches is challenging, however, due to the high dimensionality of species niches and the large spatial and temporal variability in population...

Spatial perspectives in state-and-transition models: A missing link to land management?

USDA-ARS?s Scientific Manuscript database

Conceptual models of alternative states and thresholds are based largely on observations of ecosystem processes at a few points in space. Because the distribution of alternative states in spatially-structured ecosystems is the result of variations in pattern-process interactions at different scales,...

Development of a local size hierarchy causes regular spacing of trees in an even-aged Abies forest: analyses using spatial autocorrelation and the mark correlation function.

PubMed

Suzuki, Satoshi N; Kachi, Naoki; Suzuki, Jun-Ichirou

2008-09-01

During the development of an even-aged plant population, the spatial distribution of individuals often changes from a clumped pattern to a random or regular one. The development of local size hierarchies in an Abies forest was analysed for a period of 47 years following a large disturbance in 1959. In 1980 all trees in an 8 x 8 m plot were mapped and their height growth after the disturbance was estimated. Their mortality and growth were then recorded at 1- to 4-year intervals between 1980 and 2006. Spatial distribution patterns of trees were analysed by the pair correlation function. Spatial correlations between tree heights were analysed with a spatial autocorrelation function and the mark correlation function. The mark correlation function was able to detect a local size hierarchy that could not be detected by the spatial autocorrelation function alone. The small-scale spatial distribution pattern of trees changed from clumped to slightly regular during the 47 years. Mortality occurred in a density-dependent manner, which resulted in regular spacing between trees after 1980. The spatial autocorrelation and mark correlation functions revealed the existence of tree patches consisting of large trees at the initial stage. Development of a local size hierarchy was detected within the first decade after the disturbance, although the spatial autocorrelation was not negative. Local size hierarchies that developed persisted until 2006, and the spatial autocorrelation became negative at later stages (after about 40 years). This is the first study to detect local size hierarchies as a prelude to regular spacing using the mark correlation function. The results confirm that use of the mark correlation function together with the spatial autocorrelation function is an effective tool to analyse the development of a local size hierarchy of trees in a forest.

Evaluation of fine soil moisture data from the IFloodS (NASA GPM) Ground Validation campaign using a fully-distributed ecohydrological model

NASA Astrophysics Data System (ADS)

Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.

2014-12-01

The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.

Large Scale Relationship between Aquatic Insect Traits and Climate.

PubMed

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-related changes of freshwater assemblages.

Forest fire spatial pattern analysis in Galicia (NW Spain).

PubMed

Fuentes-Santos, I; Marey-Pérez, M F; González-Manteiga, W

2013-10-15

Knowledge of fire behaviour is of key importance in forest management. In the present study, we analysed the spatial structure of forest fire with spatial point pattern analysis and inference techniques recently developed in the Spatstat package of R. Wildfires have been the primary threat to Galician forests in recent years. The district of Fonsagrada-Ancares is one of the most seriously affected by fire in the region and, therefore, the central focus of the study. Our main goal was to determine the spatial distribution of ignition points to model and predict fire occurrence. These data are of great value in establishing enhanced fire prevention and fire fighting plans. We found that the spatial distribution of wildfires is not random and that fire occurrence may depend on ownership conflicts. We also found positive interaction between small and large fires and spatial independence between wildfires in consecutive years. Copyright © 2013 Elsevier Ltd. All rights reserved.

Distribution of Wild Mammal Assemblages along an Urban–Rural–Forest Landscape Gradient in Warm-Temperate East Asia

PubMed Central

Saito, Masayuki; Koike, Fumito

2013-01-01

Urbanization may alter mammal assemblages via habitat loss, food subsidies, and other factors related to human activities. The general distribution patterns of wild mammal assemblages along urban–rural–forest landscape gradients have not been studied, although many studies have focused on a single species or taxon, such as rodents. We quantitatively evaluated the effects of the urban–rural–forest gradient and spatial scale on the distributions of large and mid-sized mammals in the world's largest metropolitan area in warm-temperate Asia using nonspecific camera-trapping along two linear transects spanning from the urban zone in the Tokyo metropolitan area to surrounding rural and forest landscapes. Many large and mid-sized species generally decreased from forest landscapes to urban cores, although some species preferred anthropogenic landscapes. Sika deer (Cervus nippon), Reeves' muntjac (Muntiacus reevesi), Japanese macaque (Macaca fuscata), Japanese squirrel (Sciurus lis), Japanese marten (Martes melampus), Japanese badger (Meles anakuma), and wild boar (Sus scrofa) generally dominated the mammal assemblage of the forest landscape. Raccoon (Procyon lotor), raccoon dog (Nyctereutes procyonoides), and Japanese hare (Lepus brachyurus) dominated the mammal assemblage in the intermediate zone (i.e., rural and suburban landscape). Cats (feral and free-roaming housecats; Felis catus) were common in the urban assemblage. The key spatial scales for forest species were more than 4000-m radius, indicating that conservation and management plans for these mammal assemblages should be considered on large spatial scales. However, small green spaces will also be important for mammal conservation in the urban landscape, because an indigenous omnivore (raccoon dog) had a smaller key spatial scale (500-m radius) than those of forest mammals. Urbanization was generally the most important factor in the distributions of mammals, and it is necessary to consider the spatial scale of management according to the degree of urbanization. PMID:23741495

Distribution of wild mammal assemblages along an urban-rural-forest landscape gradient in warm-temperate East Asia.

PubMed

Saito, Masayuki; Koike, Fumito

2013-01-01

Urbanization may alter mammal assemblages via habitat loss, food subsidies, and other factors related to human activities. The general distribution patterns of wild mammal assemblages along urban-rural-forest landscape gradients have not been studied, although many studies have focused on a single species or taxon, such as rodents. We quantitatively evaluated the effects of the urban-rural-forest gradient and spatial scale on the distributions of large and mid-sized mammals in the world's largest metropolitan area in warm-temperate Asia using nonspecific camera-trapping along two linear transects spanning from the urban zone in the Tokyo metropolitan area to surrounding rural and forest landscapes. Many large and mid-sized species generally decreased from forest landscapes to urban cores, although some species preferred anthropogenic landscapes. Sika deer (Cervus nippon), Reeves' muntjac (Muntiacus reevesi), Japanese macaque (Macaca fuscata), Japanese squirrel (Sciurus lis), Japanese marten (Martes melampus), Japanese badger (Meles anakuma), and wild boar (Sus scrofa) generally dominated the mammal assemblage of the forest landscape. Raccoon (Procyon lotor), raccoon dog (Nyctereutes procyonoides), and Japanese hare (Lepus brachyurus) dominated the mammal assemblage in the intermediate zone (i.e., rural and suburban landscape). Cats (feral and free-roaming housecats; Felis catus) were common in the urban assemblage. The key spatial scales for forest species were more than 4000-m radius, indicating that conservation and management plans for these mammal assemblages should be considered on large spatial scales. However, small green spaces will also be important for mammal conservation in the urban landscape, because an indigenous omnivore (raccoon dog) had a smaller key spatial scale (500-m radius) than those of forest mammals. Urbanization was generally the most important factor in the distributions of mammals, and it is necessary to consider the spatial scale of management according to the degree of urbanization.

A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

USGS Publications Warehouse

Irvine, Kathryn M.; Thornton, Jamie; Backus, Vickie M.; Hohmann, Matthew G.; Lehnhoff, Erik A.; Maxwell, Bruce D.; Michels, Kurt; Rew, Lisa

2013-01-01

Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

Adaptation to stimulus statistics in the perception and neural representation of auditory space.

PubMed

Dahmen, Johannes C; Keating, Peter; Nodal, Fernando R; Schulz, Andreas L; King, Andrew J

2010-06-24

Sensory systems are known to adapt their coding strategies to the statistics of their environment, but little is still known about the perceptual implications of such adjustments. We investigated how auditory spatial processing adapts to stimulus statistics by presenting human listeners and anesthetized ferrets with noise sequences in which interaural level differences (ILD) rapidly fluctuated according to a Gaussian distribution. The mean of the distribution biased the perceived laterality of a subsequent stimulus, whereas the distribution's variance changed the listeners' spatial sensitivity. The responses of neurons in the inferior colliculus changed in line with these perceptual phenomena. Their ILD preference adjusted to match the stimulus distribution mean, resulting in large shifts in rate-ILD functions, while their gain adapted to the stimulus variance, producing pronounced changes in neural sensitivity. Our findings suggest that processing of auditory space is geared toward emphasizing relative spatial differences rather than the accurate representation of absolute position.

Recurrent patterning in the daily foraging routes of hamadryas baboons (Papio hamadryas): spatial memory in large-scale versus small-scale space.

PubMed

Schreier, Amy L; Grove, Matt

2014-05-01

The benefits of spatial memory for foraging animals can be assessed on two distinct spatial scales: small-scale space (travel within patches) and large-scale space (travel between patches). While the patches themselves may be distributed at low density, within patches resources are likely densely distributed. We propose, therefore, that spatial memory for recalling the particular locations of previously visited feeding sites will be more advantageous during between-patch movement, where it may reduce the distances traveled by animals that possess this ability compared to those that must rely on random search. We address this hypothesis by employing descriptive statistics and spectral analyses to characterize the daily foraging routes of a band of wild hamadryas baboons in Filoha, Ethiopia. The baboons slept on two main cliffs--the Filoha cliff and the Wasaro cliff--and daily travel began and ended on a cliff; thus four daily travel routes exist: Filoha-Filoha, Filoha-Wasaro, Wasaro-Wasaro, Wasaro-Filoha. We use newly developed partial sum methods and distribution-fitting analyses to distinguish periods of area-restricted search from more extensive movements. The results indicate a single peak in travel activity in the Filoha-Filoha and Wasaro-Filoha routes, three peaks of travel activity in the Filoha-Wasaro routes, and two peaks in the Wasaro-Wasaro routes; and are consistent with on-the-ground observations of foraging and ranging behavior of the baboons. In each of the four daily travel routes the "tipping points" identified by the partial sum analyses indicate transitions between travel in small- versus large-scale space. The correspondence between the quantitative analyses and the field observations suggest great utility for using these types of analyses to examine primate travel patterns and especially in distinguishing between movement in small versus large-scale space. Only the distribution-fitting analyses are inconsistent with the field observations, which may be due to the scale at which these analyses were conducted. © 2013 Wiley Periodicals, Inc.

A 14 h-3 Gpc3 study of cosmic homogeneity using BOSS DR12 quasar sample

NASA Astrophysics Data System (ADS)

Laurent, Pierre; Le Goff, Jean-Marc; Burtin, Etienne; Hamilton, Jean-Christophe; Hogg, David W.; Myers, Adam; Ntelis, Pierros; Pâris, Isabelle; Rich, James; Aubourg, Eric; Bautista, Julian; Delubac, Timothée; du Mas des Bourboux, Hélion; Eftekharzadeh, Sarah; Palanque Delabrouille, Nathalie; Petitjean, Patrick; Rossi, Graziano; Schneider, Donald P.; Yeche, Christophe

2016-11-01

The BOSS quasar sample is used to study cosmic homogeneity with a 3D survey in the redshift range 2.2 < z < 2.8. We measure the count-in-sphere, N(< r), i.e. the average number of objects around a given object, and its logarithmic derivative, the fractal correlation dimension, D2(r). For a homogeneous distribution N(< r) propto r3 and D2(r) = 3. Due to the uncertainty on tracer density evolution, 3D surveys can only probe homogeneity up to a redshift dependence, i.e. they probe so-called ``spatial isotropy". Our data demonstrate spatial isotropy of the quasar distribution in the redshift range 2.2 < z < 2.8 in a model-independent way, independent of any FLRW fiducial cosmology, resulting in 3 - langleD2rangle < 1.7 × 10-3 (2 σ) over the range 250 < r < 1200 h-1 Mpc for the quasar distribution. If we assume that quasars do not have a bias much less than unity, this implies spatial isotropy of the matter distribution on large scales. Then, combining with the Copernican principle, we finally get homogeneity of the matter distribution on large scales. Alternatively, using a flat ΛCDM fiducial cosmology with CMB-derived parameters, and measuring the quasar bias relative to this ΛCDM model, our data provide a consistency check of the model, in terms of how homogeneous the Universe is on different scales. D2(r) is found to be compatible with our ΛCDM model on the whole 10 < r < 1200 h-1 Mpc range. For the matter distribution we obtain 3 - langleD2rangle < 5 × 10-5 (2 σ) over the range 250 < r < 1200 h-1 Mpc, consistent with homogeneity on large scales.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-04-03

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

Spatial Variation in the Invertebrate Macrobenthos of Three Large Missouri River Reservoirs

EPA Science Inventory

Benthic macroinvertebrates assemblages are useful indicators of ecological condition for aquatic systems. This study was conducted to characterize benthic communities of three large reservoirs on the Missouri River. The information collected on abundance, distribution and varia...

Comparison Study on the Estimation of the Spatial Distribution of Regional Soil Metal(loid)s Pollution Based on Kriging Interpolation and BP Neural Network.

PubMed

Jia, Zhenyi; Zhou, Shenglu; Su, Quanlong; Yi, Haomin; Wang, Junxiao

2017-12-26

Soil pollution by metal(loid)s resulting from rapid economic development is a major concern. Accurately estimating the spatial distribution of soil metal(loid) pollution has great significance in preventing and controlling soil pollution. In this study, 126 topsoil samples were collected in Kunshan City and the geo-accumulation index was selected as a pollution index. We used Kriging interpolation and BP neural network methods to estimate the spatial distribution of arsenic (As) and cadmium (Cd) pollution in the study area. Additionally, we introduced a cross-validation method to measure the errors of the estimation results by the two interpolation methods and discussed the accuracy of the information contained in the estimation results. The conclusions are as follows: data distribution characteristics, spatial variability, and mean square errors (MSE) of the different methods showed large differences. Estimation results from BP neural network models have a higher accuracy, the MSE of As and Cd are 0.0661 and 0.1743, respectively. However, the interpolation results show significant skewed distribution, and spatial autocorrelation is strong. Using Kriging interpolation, the MSE of As and Cd are 0.0804 and 0.2983, respectively. The estimation results have poorer accuracy. Combining the two methods can improve the accuracy of the Kriging interpolation and more comprehensively represent the spatial distribution characteristics of metal(loid)s in regional soil. The study may provide a scientific basis and technical support for the regulation of soil metal(loid) pollution.

Determinants of Spatial Distribution in a Bee Community: Nesting Resources, Flower Resources, and Body Size

PubMed Central

Torné-Noguera, Anna; Rodrigo, Anselm; Arnan, Xavier; Osorio, Sergio; Barril-Graells, Helena; da Rocha-Filho, Léo Correia; Bosch, Jordi

2014-01-01

Understanding biodiversity distribution is a primary goal of community ecology. At a landscape scale, bee communities are affected by habitat composition, anthropogenic land use, and fragmentation. However, little information is available on local-scale spatial distribution of bee communities within habitats that are uniform at the landscape scale. We studied a bee community along with floral and nesting resources over a 32 km2 area of uninterrupted Mediterranean scrubland. Our objectives were (i) to analyze floral and nesting resource composition at the habitat scale. We ask whether these resources follow a geographical pattern across the scrubland at bee-foraging relevant distances; (ii) to analyze the distribution of bee composition across the scrubland. Bees being highly mobile organisms, we ask whether bee composition shows a homogeneous distribution or else varies spatially. If so, we ask whether this variation is irregular or follows a geographical pattern and whether bees respond primarily to flower or to nesting resources; and (iii) to establish whether body size influences the response to local resource availability and ultimately spatial distribution. We obtained 6580 specimens belonging to 98 species. Despite bee mobility and the absence of environmental barriers, our bee community shows a clear geographical pattern. This pattern is mostly attributable to heterogeneous distribution of small (<55 mg) species (with presumed smaller foraging ranges), and is mostly explained by flower resources rather than nesting substrates. Even then, a large proportion (54.8%) of spatial variability remains unexplained by flower or nesting resources. We conclude that bee communities are strongly conditioned by local effects and may exhibit spatial heterogeneity patterns at a scale as low as 500–1000 m in patches of homogeneous habitat. These results have important implications for local pollination dynamics and spatial variation of plant-pollinator networks. PMID:24824445

Determinants of spatial distribution in a bee community: nesting resources, flower resources, and body size.

PubMed

Torné-Noguera, Anna; Rodrigo, Anselm; Arnan, Xavier; Osorio, Sergio; Barril-Graells, Helena; da Rocha-Filho, Léo Correia; Bosch, Jordi

2014-01-01

Understanding biodiversity distribution is a primary goal of community ecology. At a landscape scale, bee communities are affected by habitat composition, anthropogenic land use, and fragmentation. However, little information is available on local-scale spatial distribution of bee communities within habitats that are uniform at the landscape scale. We studied a bee community along with floral and nesting resources over a 32 km2 area of uninterrupted Mediterranean scrubland. Our objectives were (i) to analyze floral and nesting resource composition at the habitat scale. We ask whether these resources follow a geographical pattern across the scrubland at bee-foraging relevant distances; (ii) to analyze the distribution of bee composition across the scrubland. Bees being highly mobile organisms, we ask whether bee composition shows a homogeneous distribution or else varies spatially. If so, we ask whether this variation is irregular or follows a geographical pattern and whether bees respond primarily to flower or to nesting resources; and (iii) to establish whether body size influences the response to local resource availability and ultimately spatial distribution. We obtained 6580 specimens belonging to 98 species. Despite bee mobility and the absence of environmental barriers, our bee community shows a clear geographical pattern. This pattern is mostly attributable to heterogeneous distribution of small (<55 mg) species (with presumed smaller foraging ranges), and is mostly explained by flower resources rather than nesting substrates. Even then, a large proportion (54.8%) of spatial variability remains unexplained by flower or nesting resources. We conclude that bee communities are strongly conditioned by local effects and may exhibit spatial heterogeneity patterns at a scale as low as 500-1000 m in patches of homogeneous habitat. These results have important implications for local pollination dynamics and spatial variation of plant-pollinator networks.

Determinants of pulmonary blood flow distribution.

PubMed

Glenny, Robb W; Robertson, H Thomas

2011-01-01

The primary function of the pulmonary circulation is to deliver blood to the alveolar capillaries to exchange gases. Distributing blood over a vast surface area facilitates gas exchange, yet the pulmonary vascular tree must be constrained to fit within the thoracic cavity. In addition, pressures must remain low within the circulatory system to protect the thin alveolar capillary membranes that allow efficient gas exchange. The pulmonary circulation is engineered for these unique requirements and in turn these special attributes affect the spatial distribution of blood flow. As the largest organ in the body, the physical characteristics of the lung vary regionally, influencing the spatial distribution on large-, moderate-, and small-scale levels. © 2011 American Physiological Society.

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

NASA Astrophysics Data System (ADS)

Wang, J.; Cai, X.

2007-12-01

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

Neither biased sex ratio nor spatial segregation of the sexes in the subtropical dioecious tree Eurycorymbus cavaleriei (Sapindaceae).

PubMed

Gao, Puxin; Kang, Ming; Wang, Jing; Ye, Qigang; Huang, Hongwen

2009-06-01

Knowledge of sex ratio and spatial distribution of males and females of dioecious species is both of evolutionary interest and of crucial importance for biological conservation. Eurycorymbus cavaleriei, the only species in the genus Eurycorymbus (Sapindaceae), is a dioecious tree endemic to subtropical montane forest in South China. Sex ratios were investigated in 15 natural populations for the two defined ages (young and old). Spatial distribution of males and females was further studied in six large populations occurring in different habitats (fragmented and continuous). The study revealed a slight trend of male-biased sex ratio in both ages of E. cavaleriei, but sex ratio of most populations (13 out of 15) did not display statistically significant deviation from equality. All of the four significantly male-biased populations in the young class shifted to equality or even female-biased. The Ripley's K analysis of the distribution of males with respect to females suggested that individuals of the opposite sexes were more randomly distributed rather than spatially structured. These results suggest that the male-biased sex ratio in E. cavaleriei may result from the precocity of males and habitat heterogeneity. The sex ratio and the sex spatial distribution pattern are unlikely to constitute a serious threat to the survival of the species.

Raccoon spatial requirements and multi-scale habitat selection within an intensively managed central Appalachian forest

USGS Publications Warehouse

Owen, Sheldon F.; Berl, Jacob L.; Edwards, John W.; Ford, W. Mark; Wood, Petra Bohall

2015-01-01

We studied a raccoon (Procyon lotor) population within a managed central Appalachian hardwood forest in West Virginia to investigate the effects of intensive forest management on raccoon spatial requirements and habitat selection. Raccoon home-range (95% utilization distribution) and core-area (50% utilization distribution) size differed between sexes with males maintaining larger (2×) home ranges and core areas than females. Home-range and core-area size did not differ between seasons for either sex. We used compositional analysis to quantify raccoon selection of six different habitat types at multiple spatial scales. Raccoons selected riparian corridors (riparian management zones [RMZ]) and intact forests (> 70 y old) at the core-area spatial scale. RMZs likely were used by raccoons because they provided abundant denning resources (i.e., large-diameter trees) as well as access to water. Habitat composition associated with raccoon foraging locations indicated selection for intact forests, riparian areas, and regenerating harvest (stands <10 y old). Although raccoons were able to utilize multiple habitat types for foraging resources, a selection of intact forest and RMZs at multiple spatial scales indicates the need of mature forest (with large-diameter trees) for this species in managed forests in the central Appalachians.

Effects of dispersal, shrubs, and density-dependent morality on seed and seedling distributions in temperate forests

Treesearch

Janneke Hille Ris Lambers; James S. Clark

2003-01-01

Processes limiting recruitment of trees may have large impacts on forest dynamics. In this paper, we determined the effects of dispersal, shrubs (Rhododendron maximum), and density-dependent mortality on seed and seedling distributions of Southern Appalachian trees. We quantified the spatial distribution of seed rain, seed bank densities, first-year...

The Spatial Distribution of Dead Trees across Arkansas Timberlands

Treesearch

Martin A. Spetich; James M. Guldin

1999-01-01

Abstract -- Dead trees are an important part of the forest ecosystem and their attributes have been studied at the stand scale. However, their distribution over a large region has rarely been examined. In this study, the distribution and dynamics of sound wood in dead trees and the ratio of dead to live trees across the Arkansas landscape were...

Temporal-spatial distribution of American bison (Bison bison) in a tallgrass prairie fire mosaic

USGS Publications Warehouse

Schuler, K.L.; Leslie, David M.; Shaw, J.H.; Maichak, E.J.

2006-01-01

Fire and bison (Bison bison) are thought to be historically responsible for shaping prairie vegetation in North America. Interactions between temporal-spatial distributions of bison and prescribed burning protocols are important in current restoration of tallgrass prairies. We examined dynamics of bison distribution in a patch-burned tallgrass prairie in the south-central United States relative to bison group size and composition, and burn age and temporal distribution. Bison formed larger mixed groups during summer and smaller sexually segregated groups the rest of the year, and bison selected dormant-season burn patches in the 1st posture growing season most often during spring and summer. Large bison herds selecting recently burned areas resulted in seasonally variable and concentrated grazing pressure that may substantially alter site-specific vegetation. These dynamics must be considered when reintroducing bison and fire into tallgrass prairie because variable outcomes of floral richness and structural complexity are likely depending on temporal-spatial distribution of bison. ?? 2006 American Society of Mammalogists.

Spatial distribution of GRBs and large scale structure of the Universe

NASA Astrophysics Data System (ADS)

Bagoly, Zsolt; Rácz, István I.; Balázs, Lajos G.; Tóth, L. Viktor; Horváth, István

We studied the space distribution of the starburst galaxies from Millennium XXL database at z = 0.82. We examined the starburst distribution in the classical Millennium I (De Lucia et al. (2006)) using a semi-analytical model for the genesis of the galaxies. We simulated a starburst galaxies sample with Markov Chain Monte Carlo method. The connection between the large scale structures homogenous and starburst groups distribution (Kofman and Shandarin 1998), Suhhonenko et al. (2011), Liivamägi et al. (2012), Park et al. (2012), Horvath et al. (2014), Horvath et al. (2015)) on a defined scale were checked too.

Estimating occupancy probability of moose using hunter survey data

USGS Publications Warehouse

Crum, Nathan J.; Fuller, Angela K.; Sutherland, Christopher S.; Cooch, Evan G.; Hurst, Jeremy E.

2017-01-01

Monitoring rare species can be difficult, especially across large spatial extents, making conventional methods of population monitoring costly and logistically challenging. Citizen science has the potential to produce observational data across large areas that can be used to monitor wildlife distributions using occupancy models. We used citizen science (i.e., hunter surveys) to facilitate monitoring of moose (Alces alces) populations, an especially important endeavor because of their recent apparent declines in the northeastern and upper midwestern regions of the United States. To better understand patterns of occurrence of moose in New York, we used data collected through an annual survey of approximately 11,000 hunters between 2012 and 2014 that recorded detection–non-detection data of moose and other species. We estimated patterns of occurrence of moose in relation to land cover characteristics, climate effects, and interspecific interactions using occupancy models to analyze spatially referenced moose observations. Coniferous and deciduous forest with low prevalence of white-tailed deer (Odocoileus virginianus) had the highest probability of moose occurrence. This study highlights the potential of data collected using citizen science for understanding the spatial distribution of low-density species across large spatial extents and providing key information regarding where and when future research and management activities should be focused.

High Resolution Insights into Snow Distribution Provided by Drone Photogrammetry

NASA Astrophysics Data System (ADS)

Redpath, T.; Sirguey, P. J.; Cullen, N. J.; Fitzsimons, S.

2017-12-01

Dynamic in time and space, New Zealand's seasonal snow is largely confined to remote alpine areas, complicating ongoing in situ measurement and characterisation. Improved understanding and modeling of the seasonal snowpack requires fine scale resolution of snow distribution and spatial variability. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial and temporal variability of snow depth and water equivalent in a New Zealand alpine catchment is assessed in the Pisa Range, Central Otago. This approach yielded orthophotomosaics and digital surface models (DSM) at 0.05 and 0.15 m spatial resolution, respectively. An autumn reference DSM allowed mapping of winter (02/08/2016) and spring (10/09/2016) snow depth at 0.15 m spatial resolution, via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by comparison of snow-free regions of the spring and autumn DSMs, while accuracy of RPAS retrieved snow depth was assessed with 86 in situ snow probe measurements. Results show a mean vertical residual of 0.024 m between DSMs acquired in autumn and spring. This residual approximated a Laplace distribution, reflecting the influence of large outliers on the small overall bias. Propagation of errors associated with successive DSMs saw snow depth mapped with an accuracy of ± 0.09 m (95% c.l.). Comparing RPAS and in situ snow depth measurements revealed the influence of geo-location uncertainty and interactions between vegetation and the snowpack on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine scale spatial variability. Despite limitations accompanying RPAS photogrammetry, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological basin ( 0.5 km2), at high resolution. Resolving snowpack features associated with re-distribution and preferential accumulation and ablation, snow depth maps provide geostatistically robust insights into seasonal snow processes, with unprecedented detail. Such data may enhance understanding of physical processes controlling spatial and temporal distribution of seasonal snow, and their relative importance at varying spatial and temporal scales.

Morphological classification and spatial distribution of Philippine volcanoes

NASA Astrophysics Data System (ADS)

Paguican, E. M. R.; Kervyn, M.; Grosse, P.

2016-12-01

The Philippines is an island arc composed of two major blocks: the aseismic Palawan microcontinental block and the Philippine mobile belt. It is bounded by opposing subduction zones, with the left-lateral Philippine Fault running north-south. This setting is ideal for volcano formation and growth, making it one of the best places to study the controls on island arc volcano morphometry and evolution. In this study, we created a database of volcanic edifices and structures identified on the SRTM 30 m digital elevation models (DEM). We computed the morphometry of each edifice using MORVOLC, an IDL code for generating quantitative parameters based on a defined volcano base and DEM. Morphometric results illustrate the large range of sizes and volumes of Philippine volcanoes. Heirarchical classification by principal component analysis distinguishes between large massifs, large cones/sub-cones, small shields/sub-cones, and small cones, based mainly on size (volume, basal width) and steepness (height/basal width ratio, average slopes). Poisson Nearest Neighbor analysis was used to examine the spatial distribution of volcano centroids. Spatial distribution of the different types of volcanoes suggests that large volcanic massifs formed on thickened crust. Although all the volcanic fields and arcs are a response to tectonic activity such as subduction or rifting, only West Luzon, North and South Mindanao, and Eastern Philippines volcanic arcs and Basilan, Macolod, and Maramag volcanic fields present a statistical clustering of volcanic centers. Spatial distribution and preferential alignment of edifices in all volcanic fields confirm that regional structures had some control on their formation. Volcanoes start either as steep cones or as less steep sub-cones and shields. They then grow into large cones, sub-cones and eventually into massifs as eruption focus shifts within the volcano and new eruptive material is deposited on the slopes. Examination of the directions of volcano collapse scars and erosional amphitheater valleys suggests that, during their development, volcano growth is affected by movement of underlying tectonic structures, weight and stability of the growing edifice, structure and composition of the substrata, and intense erosion associated with tropical rainfall.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe.

PubMed

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe

PubMed Central

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes. PMID:27074044

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

PubMed

Gosme, Marie; Lucas, Philippe

2009-07-01

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

Landscape-scale spatial abundance distributions discriminate core from random components of boreal lake bacterioplankton.

PubMed

Niño-García, Juan Pablo; Ruiz-González, Clara; Del Giorgio, Paul A

2016-12-01

Aquatic bacterial communities harbour thousands of coexisting taxa. To meet the challenge of discriminating between a 'core' and a sporadically occurring 'random' component of these communities, we explored the spatial abundance distribution of individual bacterioplankton taxa across 198 boreal lakes and their associated fluvial networks (188 rivers). We found that all taxa could be grouped into four distinct categories based on model statistical distributions (normal like, bimodal, logistic and lognormal). The distribution patterns across lakes and their associated river networks showed that lake communities are composed of a core of taxa whose distribution appears to be linked to in-lake environmental sorting (normal-like and bimodal categories), and a large fraction of mostly rare bacteria (94% of all taxa) whose presence appears to be largely random and linked to downstream transport in aquatic networks (logistic and lognormal categories). These rare taxa are thus likely to reflect species sorting at upstream locations, providing a perspective of the conditions prevailing in entire aquatic networks rather than only in lakes. © 2016 John Wiley & Sons Ltd/CNRS.

Exploring the role of movement in determining the global distribution of marine biomass using a coupled hydrodynamic - Size-based ecosystem model

NASA Astrophysics Data System (ADS)

Watson, James R.; Stock, Charles A.; Sarmiento, Jorge L.

2015-11-01

Modeling the dynamics of marine populations at a global scale - from phytoplankton to fish - is necessary if we are to quantify how climate change and other broad-scale anthropogenic actions affect the supply of marine-based food. Here, we estimate the abundance and distribution of fish biomass using a simple size-based food web model coupled to simulations of global ocean physics and biogeochemistry. We focus on the spatial distribution of biomass, identifying highly productive regions - shelf seas, western boundary currents and major upwelling zones. In the absence of fishing, we estimate the total ocean fish biomass to be ∼ 2.84 ×109 tonnes, similar to previous estimates. However, this value is sensitive to the choice of parameters, and further, allowing fish to move had a profound impact on the spatial distribution of fish biomass and the structure of marine communities. In particular, when movement is implemented the viable range of large predators is greatly increased, and stunted biomass spectra characterizing large ocean regions in simulations without movement, are replaced with expanded spectra that include large predators. These results highlight the importance of considering movement in global-scale ecological models.

Statistical Maps of Ground Magnetic Disturbance Derived from Global Geospace Models

NASA Astrophysics Data System (ADS)

Rigler, E. J.; Wiltberger, M. J.; Love, J. J.

2017-12-01

Electric currents in space are the principal driver of magnetic variations measured at Earth's surface. These in turn induce geoelectric fields that present a natural hazard for technological systems like high-voltage power distribution networks. Modern global geospace models can reasonably simulate large-scale geomagnetic response to solar wind variations, but they are less successful at deterministic predictions of intense localized geomagnetic activity that most impacts technological systems on the ground. Still, recent studies have shown that these models can accurately reproduce the spatial statistical distributions of geomagnetic activity, suggesting that their physics are largely correct. Since the magnetosphere is a largely externally driven system, most model-measurement discrepancies probably arise from uncertain boundary conditions. So, with realistic distributions of solar wind parameters to establish its boundary conditions, we use the Lyon-Fedder-Mobarry (LFM) geospace model to build a synthetic multivariate statistical model of gridded ground magnetic disturbance. From this, we analyze the spatial modes of geomagnetic response, regress on available measurements to fill in unsampled locations on the grid, and estimate the global probability distribution of extreme magnetic disturbance. The latter offers a prototype geomagnetic "hazard map", similar to those used to characterize better-known geophysical hazards like earthquakes and floods.

Using Historical Atlas Data to Develop High-Resolution Distribution Models of Freshwater Fishes

PubMed Central

Huang, Jian; Frimpong, Emmanuel A.

2015-01-01

Understanding the spatial pattern of species distributions is fundamental in biogeography, and conservation and resource management applications. Most species distribution models (SDMs) require or prefer species presence and absence data for adequate estimation of model parameters. However, observations with unreliable or unreported species absences dominate and limit the implementation of SDMs. Presence-only models generally yield less accurate predictions of species distribution, and make it difficult to incorporate spatial autocorrelation. The availability of large amounts of historical presence records for freshwater fishes of the United States provides an opportunity for deriving reliable absences from data reported as presence-only, when sampling was predominantly community-based. In this study, we used boosted regression trees (BRT), logistic regression, and MaxEnt models to assess the performance of a historical metacommunity database with inferred absences, for modeling fish distributions, investigating the effect of model choice and data properties thereby. With models of the distribution of 76 native, non-game fish species of varied traits and rarity attributes in four river basins across the United States, we show that model accuracy depends on data quality (e.g., sample size, location precision), species’ rarity, statistical modeling technique, and consideration of spatial autocorrelation. The cross-validation area under the receiver-operating-characteristic curve (AUC) tended to be high in the spatial presence-absence models at the highest level of resolution for species with large geographic ranges and small local populations. Prevalence affected training but not validation AUC. The key habitat predictors identified and the fish-habitat relationships evaluated through partial dependence plots corroborated most previous studies. The community-based SDM framework broadens our capability to model species distributions by innovatively removing the constraint of lack of species absence data, thus providing a robust prediction of distribution for stream fishes in other regions where historical data exist, and for other taxa (e.g., benthic macroinvertebrates, birds) usually observed by community-based sampling designs. PMID:26075902

The large-scale distribution of galaxies

NASA Technical Reports Server (NTRS)

Geller, Margaret J.

1989-01-01

The spatial distribution of galaxies in the universe is characterized on the basis of the six completed strips of the Harvard-Smithsonian Center for Astrophysics redshift-survey extension. The design of the survey is briefly reviewed, and the results are presented graphically. Vast low-density voids similar to the void in Bootes are found, almost completely surrounded by thin sheets of galaxies. Also discussed are the implications of the results for the survey sampling problem, the two-point correlation function of the galaxy distribution, the possibility of detecting large-scale coherent flows, theoretical models of large-scale structure, and the identification of groups and clusters of galaxies.

MODELING THE POTENTIAL SPATIAL DISTRIBUTION OF BEEF CATTLE GRAZING USING A GEOGRAPHIC INFORMATION SYSTEM

EPA Science Inventory

Data regarding grazing utilization in the western United States are typically compiled within administrative boundaries(e.g. allotment,pasture). For large areas, an assumption of uniform distribution is seldom valid. Previous studies show that vegetation type, degree of slope, an...

A three-dimensional point process model for the spatial distribution of disease occurrence in relation to an exposure source.

PubMed

Grell, Kathrine; Diggle, Peter J; Frederiksen, Kirsten; Schüz, Joachim; Cardis, Elisabeth; Andersen, Per K

2015-10-15

We study methods for how to include the spatial distribution of tumours when investigating the relation between brain tumours and the exposure from radio frequency electromagnetic fields caused by mobile phone use. Our suggested point process model is adapted from studies investigating spatial aggregation of a disease around a source of potential hazard in environmental epidemiology, where now the source is the preferred ear of each phone user. In this context, the spatial distribution is a distribution over a sample of patients rather than over multiple disease cases within one geographical area. We show how the distance relation between tumour and phone can be modelled nonparametrically and, with various parametric functions, how covariates can be included in the model and how to test for the effect of distance. To illustrate the models, we apply them to a subset of the data from the Interphone Study, a large multinational case-control study on the association between brain tumours and mobile phone use. Copyright © 2015 John Wiley & Sons, Ltd.

Temporal and spatial variability in thalweg profiles of a gravel-bed river

USGS Publications Warehouse

Madej, Mary Ann

1999-01-01

This study used successive longitudinal thalweg profiles in gravel-bed rivers to monitor changes in bed topography following floods and associated large sediment inputs. Variations in channel bed elevations, distributions of residual water depths, percentage of channel length occupied by riffles, and a spatial autocorrelation coefficient (Moran's I) were used to quantify changes in morphological diversity and spatial structure in Redwood Creek basin, northwestern California. Bed topography in Redwood Creek and its major tributaries consists primarily of a series of pools and riffles. The size, frequency and spatial distribution of the pools and riffles have changed significantly during the past 20 years. Following large floods and high sediment input in Redwood Creek and its tributaries in 1975, variation in channel bed elevations was low and the percentage of the channel length occupied by riffles was high. Over the next 20 years, variation in bed elevations increased while the length of channel occupied by riffles decreased. An index [(standard deviation of residual water depth/bankfull depth) × 100] was developed to compare variations in bed elevation over a range of stream sizes, with a higher index being indicative of greater morphological diversity. Spatial autocorrelation in the bed elevation data was apparent at both fine and coarse scales in many of the thalweg profiles and the observed spatial pattern of bed elevations was found to be related to the dominant channel material and the time since disturbance. River reaches in which forced pools dominated, and in which large woody debris and bed particles could not be easily mobilized, exhibited a random distribution of bed elevations. In contrast, in reaches where alternate bars dominated, and both wood and gravel were readily transported, regularly spaced bed topography developed at a spacing that increased with time since disturbance. This pattern of regularly spaced bed features was reversed following a 12-year flood when bed elevations became more randomly arranged.

Regional-scale drivers of marine nematode distribution in Southern Ocean continental shelf sediments

NASA Astrophysics Data System (ADS)

Hauquier, Freija; Verleyen, Elie; Tytgat, Bjorn; Vanreusel, Ann

2018-07-01

Many marine meiofauna taxa seem to possess cosmopolitan species distributions, despite their endobenthic lifestyle and restricted long-distance dispersal capacities. In light of this paradox we used a metacommunity framework to study spatial turnover in free-living nematode distribution and assess the importance of local environmental conditions in explaining differences between communities in surface and subsurface sediments of the Southern Ocean continental shelf. We analysed nematode community structure in two sediment layers (0-3 cm and 3-5 cm) of locations maximum 2400 km apart. We first focused on a subset of locations to evaluate whether the genus level is sufficiently taxonomically fine-grained to study large-scale patterns in nematode community structure. We subsequently used redundancy and variation partitioning analyses to quantify the unique and combined effects of local environmental conditions and spatial descriptors on genus-level community composition. Macroecological patterns in community structure were highly congruent at the genus and species level. Nematode community composition was highly divergent between both depth strata, likely as a result of local abiotic conditions. Variation in community structure between the different regions largely stemmed from turnover (i.e. genus/species replacement) rather than nestedness (i.e. genus/species loss). The level of turnover among communities increased with geographic distance and was more pronounced in subsurface layers compared to surface sediments. Variation partitioning analysis revealed that both environmental and spatial predictors significantly explained variation in community structure. Moreover, the shared fraction of both sets of variables was high, which suggested a substantial amount of spatially structured environmental variation. Additionally, the effect of space independent of environment was much higher than the effect of environment independent of space, which shows the importance of including spatial descriptors in meiofauna and nematode community ecology. Large-scale assessment of free-living nematode diversity and abundance in the Southern Ocean shelf zone revealed strong horizontal and vertical spatial structuring in response to local environmental conditions, in combination with (most likely) dispersal limitation.

Soil organic carbon - a large scale paired catchment assessment

NASA Astrophysics Data System (ADS)

Kunkel, V.; Hancock, G. R.; Wells, T.

2016-12-01

Soil organic carbon (SOC) concentration can vary both spatially and temporally driven by differences in soil properties, topography and climate. However most studies have focused on point scale data sets with a paucity of studies examining larger scale catchments. Here we examine the spatial and temporal distribution of SOC for two large catchments. The Krui (575 km2) and Merriwa River (675km2) catchments (New South Wales, Australia). Both have similar shape, soils, topography and orientation. We show that SOC distribution is very similar for both catchments and that elevation (and associated increase in soil moisture) is a major influence on SOC. We also show that there is little change in SOC from the initial assessment in 2006 to 2015 despite a major drought from 2003 to 2010 and extreme rainfall events in 2007 and 2010 -therefore SOC concentration appears robust. However, we found significant relationships between erosion and deposition patterns (as quantified using 137Cs) and SOC for both catchments again demonstrating a strong geomorphic relationship. Vegetation across the catchments was assessed using remote sensing (Landsat and MODIS). Vegetation patterns were temporally consistent with above ground biomass increasing with elevation. SOC could be predicted using both these low and high resolution remote sensing platforms. Results indicate that, although moderate resolution (250 m) allows for reasonable prediction of the spatial distribution of SOC, the higher resolution (30 m) improved the strength of the SOC-NDVI relationship. The relationship between SOC and 137Cs, as a surrogate for the erosion and deposition of SOC, suggested that sediment transport and deposition influences the distribution of SOC within the catchment. The findings demonstrate that over the large catchment scale and at the decadal time scale that SOC is relatively constant and can largely be predicted by topography.

Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Famiglietti, J. S.; Wood, Eric F.

1993-01-01

A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.

Analysis of stratocumulus cloud fields using LANDSAT imagery: Size distributions and spatial separations

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1990-01-01

Stratocumulus cloud fields in the FIRE IFO region are analyzed using LANDSAT Thematic Mapper imagery. Structural properties such as cloud cell size distribution, cell horizontal aspect ratio, fractional coverage and fractal dimension are determined. It is found that stratocumulus cloud number densities are represented by a power law. Cell horizontal aspect ratio has a tendency to increase at large cell sizes, and cells are bi-fractal in nature. Using LANDSAT Multispectral Scanner imagery for twelve selected stratocumulus scenes acquired during previous years, similar structural characteristics are obtained. Cloud field spatial organization also is analyzed. Nearest-neighbor spacings are fit with a number of functions, with Weibull and Gamma distributions providing the best fits. Poisson tests show that the spatial separations are not random. Second order statistics are used to examine clustering.

Spatial and Temporal Distribution of Tuberculosis in the State of Mexico, Mexico

PubMed Central

Zaragoza Bastida, Adrian; Hernández Tellez, Marivel; Bustamante Montes, Lilia P.; Medina Torres, Imelda; Jaramillo Paniagua, Jaime Nicolás; Mendoza Martínez, Germán David; Ramírez Durán, Ninfa

2012-01-01

Tuberculosis (TB) is one of the oldest human diseases that still affects large population groups. According to the World Health Organization (WHO), there were approximately 9.4 million new cases worldwide in the year 2010. In Mexico, there were 18,848 new cases of TB of all clinical variants in 2010. The identification of clusters in space-time is of great interest in epidemiological studies. The objective of this research was to identify the spatial and temporal distribution of TB during the period 2006–2010 in the State of Mexico, using geographic information system (GIS) and SCAN statistics program. Nine significant clusters (P < 0.05) were identified using spatial and space-time analysis. The conclusion is that TB in the State of Mexico is not randomly distributed but is concentrated in areas close to Mexico City. PMID:22919337

Laser interferometry for the determination of thickness distributions of low absorbing films and their spatial and thickness resolutions.

PubMed

Mishima, T; Kao, K C

1982-03-15

New laser interferometry has been developed, based on the principle that a 2-D fringe pattern can be produced by interference of spatially coherent light beams. To avoid the effect of reflection from the back surface of the substrate, the Brewster angle of incidence is adopted; to suppress the effect of diffraction, a lens or a lens system is used. This laser interferometry is an efficient nondestructive technique for the determination of thickness distributions or uniformities of low absorbing films on transparent substrates over a large area without involving laborious computations. The limitation of spatial resolution, thickness resolution, and visibility of fringes is fully analyzed.

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

PubMed

Kihal-Talantikite, Wahida; Deguen, Séverine; Padilla, Cindy; Siebert, Muriel; Couchoud, Cécile; Vigneau, Cécile; Bayat, Sahar

2015-02-01

Several studies have investigated the implication of biological and environmental factors on geographic variations of end-stage renal disease (ESRD) incidence at large area scales, but none of them assessed the implication of neighbourhood characteristics (healthcare supply, socio-economic level and urbanization degree) on spatial repartition of ESRD. We evaluated the spatial implications of adjustment for neighbourhood characteristics on the spatial distribution of ESRD incidence at the smallest geographic unit in France. All adult patients living in Bretagne and beginning renal replacement therapy during the 2004-09 period were included. Their residential address was geocoded at the census block level. Each census block was characterized by socio-economic deprivation index, healthcare supply and rural/urban typology. Using a spatial scan statistic, we examined whether there were significant clusters of high risk of ESRD incidence. The ESRD incidence was non-randomly spatially distributed, with a cluster of high risk in the western Bretagne region (relative risk, RR = 1.28, P-value = 0.0003). Adjustment for sex, age and neighbourhood characteristics induced cluster shifts. After these adjustments, a significant cluster (P = 0.013) persisted. Our spatial analysis of ESRD incidence at a fine scale, across a mixed rural/urban area, indicated that, beyond age and sex, neighbourhood characteristics explained a great part of spatial distribution of ESRD incidence. However, to better understand spatial variation of ESRD incidence, it would be necessary to research and adjust for other determinants of ESRD.

Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

USGS Publications Warehouse

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

2004-01-01

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

Comparison Study on the Estimation of the Spatial Distribution of Regional Soil Metal(loid)s Pollution Based on Kriging Interpolation and BP Neural Network

PubMed Central

Zhou, Shenglu; Su, Quanlong; Yi, Haomin

2017-01-01

Soil pollution by metal(loid)s resulting from rapid economic development is a major concern. Accurately estimating the spatial distribution of soil metal(loid) pollution has great significance in preventing and controlling soil pollution. In this study, 126 topsoil samples were collected in Kunshan City and the geo-accumulation index was selected as a pollution index. We used Kriging interpolation and BP neural network methods to estimate the spatial distribution of arsenic (As) and cadmium (Cd) pollution in the study area. Additionally, we introduced a cross-validation method to measure the errors of the estimation results by the two interpolation methods and discussed the accuracy of the information contained in the estimation results. The conclusions are as follows: data distribution characteristics, spatial variability, and mean square errors (MSE) of the different methods showed large differences. Estimation results from BP neural network models have a higher accuracy, the MSE of As and Cd are 0.0661 and 0.1743, respectively. However, the interpolation results show significant skewed distribution, and spatial autocorrelation is strong. Using Kriging interpolation, the MSE of As and Cd are 0.0804 and 0.2983, respectively. The estimation results have poorer accuracy. Combining the two methods can improve the accuracy of the Kriging interpolation and more comprehensively represent the spatial distribution characteristics of metal(loid)s in regional soil. The study may provide a scientific basis and technical support for the regulation of soil metal(loid) pollution. PMID:29278363

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

PubMed

Wilson, Adam M; Jetz, Walter

2016-03-01

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

Large Scale Density Estimation of Blue and Fin Whales: Utilizing Sparse Array Data to Develop and Implement a New Method for Estimating Blue and Fin Whale Density

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Large Scale Density Estimation of Blue and Fin Whales ...Utilizing Sparse Array Data to Develop and Implement a New Method for Estimating Blue and Fin Whale Density Len Thomas & Danielle Harris Centre...to develop and implement a new method for estimating blue and fin whale density that is effective over large spatial scales and is designed to cope

Relative importance of management, meteorological and environmental factors in the spatial distribution of Fasciola hepatica in dairy cattle in a temperate climate zone.

PubMed

Bennema, S C; Ducheyne, E; Vercruysse, J; Claerebout, E; Hendrickx, G; Charlier, J

2011-02-01

Fasciola hepatica, a trematode parasite with a worldwide distribution, is the cause of important production losses in the dairy industry. Diagnosis is hampered by the fact that the infection is mostly subclinical. To increase awareness and develop regionally adapted control methods, knowledge on the spatial distribution of economically important infection levels is needed. Previous studies modelling the spatial distribution of F. hepatica are mostly based on single cross-sectional samplings and have focussed on climatic and environmental factors, often ignoring management factors. This study investigated the associations between management, climatic and environmental factors affecting the spatial distribution of infection with F. hepatica in dairy herds in a temperate climate zone (Flanders, Belgium) over three consecutive years. A bulk-tank milk antibody ELISA was used to measure F. hepatica infection levels in a random sample of 1762 dairy herds in the autumns of 2006, 2007 and 2008. The infection levels were included in a Geographic Information System together with meteorological, environmental and management parameters. Logistic regression models were used to determine associations between possible risk factors and infection levels. The prevalence and spatial distribution of F. hepatica was relatively stable, with small interannual differences in prevalence and location of clusters. The logistic regression model based on both management and climatic/environmental factors included the factors: annual rainfall, mowing of pastures, proportion of grazed grass in the diet and length of grazing season as significant predictors and described the spatial distribution of F. hepatica better than the model based on climatic/environmental factors only (annual rainfall, elevation and slope, soil type), with an Area Under the Curve of the Receiver Operating Characteristic of 0.68 compared with 0.62. The results indicate that in temperate climate zones without large climatic and environmental variation, management factors affect the spatial distribution of F. hepatica, and should be included in future spatial distribution models. Copyright © 2010 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Using an index of habitat patch proximity for landscape design

Treesearch

Eric J. Gustafson; George R. Parker

1994-01-01

A proximity index (PX) inspired by island biogeography theory is described which quantifies the spatial context of a habitat patch in relation to its neighbors. The index distinguishes sparse distributions of small habitat patches from clusters of large patches. An evaluation of the relationship between PX and variation in the spatial characteristics of clusters of...

Spatially Resolved Analysis of Amines Using a Fluorescence Molecular Probe: Molecular Analysis of IDPs

NASA Technical Reports Server (NTRS)

Clemett, S. J.; Messenger, S.; Thomas-Keprta, K. L.; Wentworth, S. J.; Robinson, G. A.; McKay, D. S.

2002-01-01

Some Interplanetary Dust Particles (IDPs) have large isotope anomalies in H and N. To address the nature of the carrier phase, we are developing a procedure to spatially resolve the distribution of organic species on IDP thin sections utilizing fluorescent molecular probes. Additional information is contained in the original extended abstract.

Predicting above-ground density and distribution of small mammal prey species at large spatial scales

Treesearch

Lucretia E. Olson; John R. Squires; Robert J. Oakleaf; Zachary P. Wallace; Patricia L. Kennedy

2017-01-01

Grassland and shrub-steppe ecosystems are increasingly threatened by anthropogenic activities. Loss of native habitats may negatively impact important small mammal prey species. Little information, however, is available on the impact of habitat variability on density of small mammal prey species at broad spatial scales. We examined the relationship between small mammal...

Uncertainty in determining extreme precipitation thresholds

NASA Astrophysics Data System (ADS)

Liu, Bingjun; Chen, Junfan; Chen, Xiaohong; Lian, Yanqing; Wu, Lili

2013-10-01

Extreme precipitation events are rare and occur mostly on a relatively small and local scale, which makes it difficult to set the thresholds for extreme precipitations in a large basin. Based on the long term daily precipitation data from 62 observation stations in the Pearl River Basin, this study has assessed the applicability of the non-parametric, parametric, and the detrended fluctuation analysis (DFA) methods in determining extreme precipitation threshold (EPT) and the certainty to EPTs from each method. Analyses from this study show the non-parametric absolute critical value method is easy to use, but unable to reflect the difference of spatial rainfall distribution. The non-parametric percentile method can account for the spatial distribution feature of precipitation, but the problem with this method is that the threshold value is sensitive to the size of rainfall data series and is subjected to the selection of a percentile thus make it difficult to determine reasonable threshold values for a large basin. The parametric method can provide the most apt description of extreme precipitations by fitting extreme precipitation distributions with probability distribution functions; however, selections of probability distribution functions, the goodness-of-fit tests, and the size of the rainfall data series can greatly affect the fitting accuracy. In contrast to the non-parametric and the parametric methods which are unable to provide information for EPTs with certainty, the DFA method although involving complicated computational processes has proven to be the most appropriate method that is able to provide a unique set of EPTs for a large basin with uneven spatio-temporal precipitation distribution. The consistency between the spatial distribution of DFA-based thresholds with the annual average precipitation, the coefficient of variation (CV), and the coefficient of skewness (CS) for the daily precipitation further proves that EPTs determined by the DFA method are more reasonable and applicable for the Pearl River Basin.

Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river

USGS Publications Warehouse

Smith, D.R.; Rogala, J.T.; Gray, B.R.; Zigler, S.J.; Newton, T.J.

2011-01-01

Reliable estimates of abundance are needed to assess consequences of proposed habitat restoration and enhancement projects on freshwater mussels in the Upper Mississippi River (UMR). Although there is general guidance on sampling techniques for population assessment of freshwater mussels, the actual performance of sampling designs can depend critically on the population density and spatial distribution at the project site. To evaluate various sampling designs, we simulated sampling of populations, which varied in density and degree of spatial clustering. Because of logistics and costs of large river sampling and spatial clustering of freshwater mussels, we focused on adaptive and non-adaptive versions of single and two-stage sampling. The candidate designs performed similarly in terms of precision (CV) and probability of species detection for fixed sample size. Both CV and species detection were determined largely by density, spatial distribution and sample size. However, designs did differ in the rate that occupied quadrats were encountered. Occupied units had a higher probability of selection using adaptive designs than conventional designs. We used two measures of cost: sample size (i.e. number of quadrats) and distance travelled between the quadrats. Adaptive and two-stage designs tended to reduce distance between sampling units, and thus performed better when distance travelled was considered. Based on the comparisons, we provide general recommendations on the sampling designs for the freshwater mussels in the UMR, and presumably other large rivers.

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

PubMed Central

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

2015-01-01

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

An evaluation of semi-automated methods for collecting ecosystem-level data in temperate marine systems.

PubMed

Griffin, Kingsley J; Hedge, Luke H; González-Rivero, Manuel; Hoegh-Guldberg, Ove I; Johnston, Emma L

2017-07-01

Historically, marine ecologists have lacked efficient tools that are capable of capturing detailed species distribution data over large areas. Emerging technologies such as high-resolution imaging and associated machine-learning image-scoring software are providing new tools to map species over large areas in the ocean. Here, we combine a novel diver propulsion vehicle (DPV) imaging system with free-to-use machine-learning software to semi-automatically generate dense and widespread abundance records of a habitat-forming algae over ~5,000 m 2 of temperate reef. We employ replicable spatial techniques to test the effectiveness of traditional diver-based sampling, and better understand the distribution and spatial arrangement of one key algal species. We found that the effectiveness of a traditional survey depended on the level of spatial structuring, and generally 10-20 transects (50 × 1 m) were required to obtain reliable results. This represents 2-20 times greater replication than have been collected in previous studies. Furthermore, we demonstrate the usefulness of fine-resolution distribution modeling for understanding patterns in canopy algae cover at multiple spatial scales, and discuss applications to other marine habitats. Our analyses demonstrate that semi-automated methods of data gathering and processing provide more accurate results than traditional methods for describing habitat structure at seascape scales, and therefore represent vastly improved techniques for understanding and managing marine seascapes.

Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

DOE PAGES

McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.; ...

2015-02-03

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less

Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

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

McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less

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

PubMed

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

2017-10-30

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

Facilitating political decisions using species distribution models to assess restoration measures in heavily modified estuaries.

PubMed

Heuner, Maike; Weber, Arnd; Schröder, Uwe; Kleinschmit, Birgit; Schröder, Boris

2016-09-15

The European Water Framework Directive requires a good ecological potential for heavily modified water bodies. This standard has not been reached for most large estuaries by 2015. Management plans for estuaries fall short in linking implementations between restoration measures and underlying spatial analyses. The distribution of emergent macrophytes - as an indicator of habitat quality - is here used to assess the ecological potential. Emergent macrophytes are capable of settling on gentle tidal flats where hydrodynamic stress is comparatively low. Analyzing their habitats based on spatial data, we set up species distribution models with 'elevation relative to mean high water', 'mean bank slope', and 'length of bottom friction' from shallow water up to the vegetation belt as key predictors representing hydrodynamic stress. Effects of restoration scenarios on habitats were assessed applying these models. Our findings endorse species distribution models as crucial spatial planning tools for implementing restoration measures in modified estuaries. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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

2007-05-02

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

a Novel Approach of Indexing and Retrieving Spatial Polygons for Efficient Spatial Region Queries

NASA Astrophysics Data System (ADS)

Zhao, J. H.; Wang, X. Z.; Wang, F. Y.; Shen, Z. H.; Zhou, Y. C.; Wang, Y. L.

2017-10-01

Spatial region queries are more and more widely used in web-based applications. Mechanisms to provide efficient query processing over geospatial data are essential. However, due to the massive geospatial data volume, heavy geometric computation, and high access concurrency, it is difficult to get response in real time. Spatial indexes are usually used in this situation. In this paper, based on k-d tree, we introduce a distributed KD-Tree (DKD-Tree) suitbable for polygon data, and a two-step query algorithm. The spatial index construction is recursive and iterative, and the query is an in memory process. Both the index and query methods can be processed in parallel, and are implemented based on HDFS, Spark and Redis. Experiments on a large volume of Remote Sensing images metadata have been carried out, and the advantages of our method are investigated by comparing with spatial region queries executed on PostgreSQL and PostGIS. Results show that our approach not only greatly improves the efficiency of spatial region query, but also has good scalability, Moreover, the two-step spatial range query algorithm can also save cluster resources to support a large number of concurrent queries. Therefore, this method is very useful when building large geographic information systems.

Fractional Fourier transform of Lorentz-Gauss vortex beams

NASA Astrophysics Data System (ADS)

Zhou, GuoQuan; Wang, XiaoGang; Chu, XiuXiang

2013-08-01

An analytical expression for a Lorentz-Gauss vortex beam passing through a fractional Fourier transform (FRFT) system is derived. The influences of the order of the FRFT and the topological charge on the normalized intensity distribution, the phase distribution, and the orbital angular momentum density of a Lorentz-Gauss vortex beam in the FRFT plane are examined. The order of the FRFT controls the beam spot size, the orientation of the beam spot, the spiral direction of the phase distribution, the spatial orientation of the two peaks in the orbital angular momentum density distribution, and the magnitude of the orbital angular momentum density. The increase of the topological charge not only results in the dark-hollow region becoming large, but also brings about detail changes in the beam profile. The spatial orientation of the two peaks in the orbital angular momentum density distribution and the phase distribution also depend on the topological charge.

Sandy beaches: state of the art of nematode ecology.

PubMed

Maria, Tatiana F; Vanaverbeke, Jan; Vanreusel, Ann; Esteves, André M

2016-01-01

In this review, we summarize existing knowledge of the ecology of sandy-beach nematodes, in relation to spatial distribution, food webs, pollution and climate change. We attempt to discuss spatial scale patterns (macro-, meso- and microscale) according to their degree of importance in structuring sandy-beach nematode assemblages. This review will provide a substantial background on current knowledge of sandy-beach nematodes, and can be used as a starting point to delineate further investigations in this field. Over decades, sandy beaches have been the scene of studies focusing on community and population ecology, both related to morphodynamic models. The combination of physical factors (e.g. grain size, tidal exposure) and biological interactions (e.g. trophic relationships) is responsible for the spatial distribution of nematodes. In other words, the physical factors are more important in structuring nematodes communities over large scale of distribution while biological interactions are largely important in finer-scale distributions. It has been accepted that biological interactions are assumed to be of minor importance because physical factors overshadow the biological interactions in sandy beach sediments; however, the most recent results from in-situ and ex-situ experimental investigations on behavior and biological factors on a microscale have shown promise for understanding the mechanisms underlying larger-scale patterns and processes. Besides nematodes are very promising organisms used to understand the effects of pollution and climate changes although these subjects are less studied in sandy beaches than distribution patterns.

Initial results of the spatial distribution of rubber trees in Peninsular Malaysia using remotely sensed data for biomass estimate

NASA Astrophysics Data System (ADS)

Shidiq, I. P. A.; Ismail, M. H.; Kamarudin, N.

2014-02-01

The preservation and sustainable management of forest and other land cover ecosystems such as rubber trees will help addressing two major recent issues: climate change and bio-resource energy. The rubber trees are dominantly distributed in the Negeri Sembilan and Kedah on the west coast side of Peninsular Malaysia. This study is aimed to analyse the spatial distribution and biomass of rubber trees in Peninsular Malaysia with special emphasis in Negeri Sembilan State. Geospatial data from remote sensors are used to tackle the time and labour consuming problem due to the large spatial coverage and the need of continuous temporal data. Remote sensing imagery used in this study is a Landsat 5 TM. The image from optical sensor was used to sense the rubber trees and further classified rubber tree by different age.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Development of an automated procedure for estimation of the spatial variation of runoff in large river basins

USDA-ARS?s Scientific Manuscript database

The use of distributed parameter models to address water resource management problems has increased in recent years. Calibration is necessary to reduce the uncertainties associated with model input parameters. Manual calibration of a distributed parameter model is a very time consuming effort. There...

Evaluating sample allocation and effort in detecting population differentiation for discrete and continuously distributed individuals

Treesearch

Erin L. Landguth; Michael K. Schwartz

2014-01-01

One of the most pressing issues in spatial genetics concerns sampling. Traditionally, substructure and gene flow are estimated for individuals sampled within discrete populations. Because many species may be continuously distributed across a landscape without discrete boundaries, understanding sampling issues becomes paramount. Given large-scale, geographically broad...

Grid-based mapping: A method for rapidly determining the spatial distributions of small features over very large areas

NASA Astrophysics Data System (ADS)

Ramsdale, Jason D.; Balme, Matthew R.; Conway, Susan J.; Gallagher, Colman; van Gasselt, Stephan A.; Hauber, Ernst; Orgel, Csilla; Séjourné, Antoine; Skinner, James A.; Costard, Francois; Johnsson, Andreas; Losiak, Anna; Reiss, Dennis; Swirad, Zuzanna M.; Kereszturi, Akos; Smith, Isaac B.; Platz, Thomas

2017-06-01

The increased volume, spatial resolution, and areal coverage of high-resolution images of Mars over the past 15 years have led to an increased quantity and variety of small-scale landform identifications. Though many such landforms are too small to represent individually on regional-scale maps, determining their presence or absence across large areas helps form the observational basis for developing hypotheses on the geological nature and environmental history of a study area. The combination of improved spatial resolution and near-continuous coverage significantly increases the time required to analyse the data. This becomes problematic when attempting regional or global-scale studies of metre and decametre-scale landforms. Here, we describe an approach for mapping small features (from decimetre to kilometre scale) across large areas, formulated for a project to study the northern plains of Mars, and provide context on how this method was developed and how it can be implemented. Rather than ;mapping; with points and polygons, grid-based mapping uses a ;tick box; approach to efficiently record the locations of specific landforms (we use an example suite of glacial landforms; including viscous flow features, the latitude dependant mantle and polygonised ground). A grid of squares (e.g. 20 km by 20 km) is created over the mapping area. Then the basemap data are systematically examined, grid-square by grid-square at full resolution, in order to identify the landforms while recording the presence or absence of selected landforms in each grid-square to determine spatial distributions. The result is a series of grids recording the distribution of all the mapped landforms across the study area. In some ways, these are equivalent to raster images, as they show a continuous distribution-field of the various landforms across a defined (rectangular, in most cases) area. When overlain on context maps, these form a coarse, digital landform map. We find that grid-based mapping provides an efficient solution to the problems of mapping small landforms over large areas, by providing a consistent and standardised approach to spatial data collection. The simplicity of the grid-based mapping approach makes it extremely scalable and workable for group efforts, requiring minimal user experience and producing consistent and repeatable results. The discrete nature of the datasets, simplicity of approach, and divisibility of tasks, open up the possibility for citizen science in which crowdsourcing large grid-based mapping areas could be applied.

Spatial and temporal variation in the abundance of Culicoides biting midges (Diptera: Ceratopogonidae) in nine European countries.

PubMed

Cuéllar, Ana Carolina; Kjær, Lene Jung; Kirkeby, Carsten; Skovgard, Henrik; Nielsen, Søren Achim; Stockmarr, Anders; Andersson, Gunnar; Lindstrom, Anders; Chirico, Jan; Lühken, Renke; Steinke, Sonja; Kiel, Ellen; Gethmann, Jörn; Conraths, Franz J; Larska, Magdalena; Hamnes, Inger; Sviland, Ståle; Hopp, Petter; Brugger, Katharina; Rubel, Franz; Balenghien, Thomas; Garros, Claire; Rakotoarivony, Ignace; Allène, Xavier; Lhoir, Jonathan; Chavernac, David; Delécolle, Jean-Claude; Mathieu, Bruno; Delécolle, Delphine; Setier-Rio, Marie-Laure; Venail, Roger; Scheid, Bethsabée; Chueca, Miguel Ángel Miranda; Barceló, Carlos; Lucientes, Javier; Estrada, Rosa; Mathis, Alexander; Tack, Wesley; Bødker, Rene

2018-02-27

Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are vectors of bluetongue virus (BTV), African horse sickness virus and Schmallenberg virus (SBV). Outbreaks of both BTV and SBV have affected large parts of Europe. The spread of these diseases depends largely on vector distribution and abundance. The aim of this analysis was to identify and quantify major spatial patterns and temporal trends in the distribution and seasonal variation of observed Culicoides abundance in nine countries in Europe. We gathered existing Culicoides data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. In total, 31,429 Culicoides trap collections were available from 904 ruminant farms across these countries between 2007 and 2013. The Obsoletus ensemble was distributed widely in Europe and accounted for 83% of all 8,842,998 Culicoides specimens in the dataset, with the highest mean monthly abundance recorded in France, Germany and southern Norway. The Pulicaris ensemble accounted for only 12% of the specimens and had a relatively southerly and easterly spatial distribution compared to the Obsoletus ensemble. Culicoides imicola Kieffer was only found in Spain and the southernmost part of France. There was a clear spatial trend in the accumulated annual abundance from southern to northern Europe, with the Obsoletus ensemble steadily increasing from 4000 per year in southern Europe to 500,000 in Scandinavia. The Pulicaris ensemble showed a very different pattern, with an increase in the accumulated annual abundance from 1600 in Spain, peaking at 41,000 in northern Germany and then decreasing again toward northern latitudes. For the two species ensembles and C. imicola, the season began between January and April, with later start dates and increasingly shorter vector seasons at more northerly latitudes. We present the first maps of seasonal Culicoides abundance in large parts of Europe covering a gradient from southern Spain to northern Scandinavia. The identified temporal trends and spatial patterns are useful for planning the allocation of resources for international prevention and surveillance programmes in the European Union.

Spatial variation in spawning habitat of cutthroat trout in a sediment-rich basin

Treesearch

James P. Magee; Thomas E. McMahon; Russell F. Thurow

1996-01-01

We examined distribution and habitat characteristics of spawning sites of cutthroat trout Oncorhynchus clarki at various spatial scales to assess effects of sedimentation within a large basin in Montana. Redd density varied widely across the basin; nearly all (99%) of the 362 redds observed occurred in two high-elevation headwater tributaries. Redd density at the reach...

A Method for Mapping Future Urbanization in the United States

NASA Technical Reports Server (NTRS)

Bounoua, Lahouari; Nigro, Joseph; Thome, Kurtis; Zhang, Ping; Fathi, Najlaa; Lachir, Asia

2018-01-01

Cities are poised to absorb additional people. Their sustainability, or ability to accommodate a population increase without depleting resources or compromising future growth, depends on whether they harness the efficiency gains from urban land management. Population is often projected as a bulk national number without details about spatial distribution. We use Landsat and population data in a methodology to project and map U.S. urbanization for the year 2020 and document its spatial pattern. This methodology is important to spatially disaggregate projected population and assist land managers to monitor land use, assess infrastructure and distribute resources. We found the U.S. west coast urban areas to have the fastest population growth with relatively small land consumption resulting in future decrease in per capita land use. Except for Miami (FL), most other U.S. large urban areas, especially in the Midwest, are growing spatially faster than their population and inadvertently consuming land needed for ecosystem services. In large cities, such as New York, Chicago, Houston and Miami, land development is expected more in suburban zones than urban cores. In contrast, in Los Angeles land development within the city core is greater than in its suburbs.

Optimal synchronization in space

NASA Astrophysics Data System (ADS)

Brede, Markus

2010-02-01

In this Rapid Communication we investigate spatially constrained networks that realize optimal synchronization properties. After arguing that spatial constraints can be imposed by limiting the amount of “wire” available to connect nodes distributed in space, we use numerical optimization methods to construct networks that realize different trade offs between optimal synchronization and spatial constraints. Over a large range of parameters such optimal networks are found to have a link length distribution characterized by power-law tails P(l)∝l-α , with exponents α increasing as the networks become more constrained in space. It is also shown that the optimal networks, which constitute a particular type of small world network, are characterized by the presence of nodes of distinctly larger than average degree around which long-distance links are centered.

Spatial and seasonal dynamics of brook trout populations inhabiting a central Appalachian watershed

USGS Publications Warehouse

Petty, J.T.; Lamothe, P.J.; Mazik, P.M.

2005-01-01

We quantified the watershed-scale spatial population dynamics of brook trout Salvelinus fontinalis in the Second Fork, a third-order tributary of Shavers Fork in eastern West Virginia. We used visual surveys, electrofishing, and mark-recapture techniques to quantify brook trout spawning intensity, population density, size structure, and demographic rates (apparent survival and immigration) throughout the watershed. Our analyses produced the following results. Spawning by brook trout was concentrated in streams with small basin areas (i.e., segments draining less than 3 km2), relatively high alkalinity (>10 mg CaCO3/L), and high amounts of instream cover. The spatial distribution of juvenile and small-adult brook trout within the watershed was relatively stable and was significantly correlated with spawning intensity. However, no such relationship was observed for large adults, which exhibited highly variable distribution patterns related to seasonally important habitat features, including instream cover, stream depth and width, and riparian canopy cover. Brook trout survival and immigration rates varied seasonally, spatially, and among size-classes. Differential survival and immigration tended to concentrate juveniles and small adults in small, alkaline streams, whereas dispersal tended to redistribute large adults at the watershed scale. Our results suggest that spatial and temporal variations in spawning, survival, and movement interact to determine the distribution, abundance, and size structure of brook trout populations at a watershed scale. These results underscore the importance of small tributaries for the persistence of brook trout in this watershed and the need to consider watershed-scale processes when designing management plans for Appalachian brook trout populations. ?? Copyright by the American Fisheries Society 2005.

Scene-based nonuniformity correction using local constant statistics.

PubMed

Zhang, Chao; Zhao, Wenyi

2008-06-01

In scene-based nonuniformity correction, the statistical approach assumes all possible values of the true-scene pixel are seen at each pixel location. This global-constant-statistics assumption does not distinguish fixed pattern noise from spatial variations in the average image. This often causes the "ghosting" artifacts in the corrected images since the existing spatial variations are treated as noises. We introduce a new statistical method to reduce the ghosting artifacts. Our method proposes a local-constant statistics that assumes that the temporal signal distribution is not constant at each pixel but is locally true. This considers statistically a constant distribution in a local region around each pixel but uneven distribution in a larger scale. Under the assumption that the fixed pattern noise concentrates in a higher spatial-frequency domain than the distribution variation, we apply a wavelet method to the gain and offset image of the noise and separate out the pattern noise from the spatial variations in the temporal distribution of the scene. We compare the results to the global-constant-statistics method using a clean sequence with large artificial pattern noises. We also apply the method to a challenging CCD video sequence and a LWIR sequence to show how effective it is in reducing noise and the ghosting artifacts.

Local pressure and matrix component effects on verteporfin distribution in pancreatic tumors (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nieskoski, Michael D.; Marra, Kayla; Gunn, Jason R.; Doyley, Marvin; Samkoe, Kimberly S.; Pereira, Stephen P.; Trembly, B. Stuart; Pogue, Brian W.

2017-02-01

Pancreatic tumors are characterized by large interstitial hypertension from enhanced deposition of extracellular matrix components, resulting in widespread vascular collapse and reduced molecular uptake of systemically delivered therapies. Although the origins of hypoperfusion is debated amongst researchers, spatial distribution of collagen density and hyaluronic acid content have shown to be a key metric in understanding the lack of efficacy for both acute and chronic therapies in these tumors. In this study, the AsPC-1 tumor model was used both subcutaneously and orthotopically to study the measurable factors which are related to this. A conventional piezoelectric pressure catheter was used to measure total tissue pressure (TTP), defined as a combination of solid stress (SS) and interstitial fluid pressure (IFP), TTP = SS + IFP, in multiple locations within the tumor interstitium. Matrix components such as collagen and hyaluronic acid were scored using masson's trichrome stain and hyaluronic acid binding protein (HABP), respectively, and co-registered with values of TTP. The results show that these key measurements are related to the spatial distribution of verteporfin in the same tumors. Photodynamic treatment with verteporfin is known to ablate large regions of tumor tissue and also allow better permeability for chemotherapies. The study of spatial distribution of verteporfin in relation to stromal content and TTP will help us better control these types of combination therapies.

Spatial relationships of sector-specific fossil fuel CO2 emissions in the United States

NASA Astrophysics Data System (ADS)

Zhou, Yuyu; Gurney, Kevin Robert

2011-09-01

Quantification of the spatial distribution of sector-specific fossil fuel CO2 emissions provides strategic information to public and private decision makers on climate change mitigation options and can provide critical constraints to carbon budget studies being performed at the national to urban scales. This study analyzes the spatial distribution and spatial drivers of total and sectoral fossil fuel CO2 emissions at the state and county levels in the United States. The spatial patterns of absolute versus per capita fossil fuel CO2 emissions differ substantially and these differences are sector-specific. Area-based sources such as those in the residential and commercial sectors are driven by a combination of population and surface temperature with per capita emissions largest in the northern latitudes and continental interior. Emission sources associated with large individual manufacturing or electricity producing facilities are heterogeneously distributed in both absolute and per capita metrics. The relationship between surface temperature and sectoral emissions suggests that the increased electricity consumption due to space cooling requirements under a warmer climate may outweigh the savings generated by lessened space heating. Spatial cluster analysis of fossil fuel CO2 emissions confirms that counties with high (low) CO2 emissions tend to be clustered close to other counties with high (low) CO2 emissions and some of the spatial clustering extends to multistate spatial domains. This is particularly true for the residential and transportation sectors, suggesting that emissions mitigation policy might best be approached from the regional or multistate perspective. Our findings underscore the potential for geographically focused, sector-specific emissions mitigation strategies and the importance of accurate spatial distribution of emitting sources when combined with atmospheric monitoring via aircraft, satellite and in situ measurements.

Urban-scale mapping of PM2.5 distribution via data fusion between high-density sensor network and MODIS Aerosol Optical Depth

NASA Astrophysics Data System (ADS)

Ba, Yu Tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Tang, Yu jia; Zhang, Da wei

2017-04-01

High-resolution mapping of PM2.5 is the prerequisite for precise analytics and subsequent anti-pollution interventions. Considering the large variances of particulate distribution, urban-scale mapping is challenging either with ground-based fixed stations, with satellites or via models. In this study, a dynamic fusion method between high-density sensor network and MODIS Aerosol Optical Depth (AOD) was introduced. The sensor network was deployed in Beijing ( > 1000 fixed monitors across 16000 km2 area) to provide raw observations with high temporal resolution (sampling interval < 1 hour), high spatial resolution in flat areas ( < 1 km), and low spatial resolution in mountainous areas ( > 5 km). The MODIS AOD was calibrated to provide distribution map with low temporal resolution (daily) and moderate spatial resolution ( = 3 km). By encoding the data quality and defects (e.g. could, reflectance, abnormal), a hybrid interpolation procedure with cross-validation generated PM2.5 distribution with both high temporal and spatial resolution. Several no-pollutant and high-pollution periods were tested to validate the proposed fusion method for capturing the instantaneous patterns of PM2.5 emission.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Landscape-scale distribution and persistence of genetically modified oilseed rape (Brassica napus) in Manitoba, Canada.

PubMed

Knispel, Alexis L; McLachlan, Stéphane M

2010-01-01

Genetically modified herbicide-tolerant (GMHT) oilseed rape (OSR; Brassica napus L.) was approved for commercial cultivation in Canada in 1995 and currently represents over 95% of the OSR grown in western Canada. After a decade of widespread cultivation, GMHT volunteers represent an increasing management problem in cultivated fields and are ubiquitous in adjacent ruderal habitats, where they contribute to the spread of transgenes. However, few studies have considered escaped GMHT OSR populations in North America, and even fewer have been conducted at large spatial scales (i.e. landscape scales). In particular, the contribution of landscape structure and large-scale anthropogenic dispersal processes to the persistence and spread of escaped GMHT OSR remains poorly understood. We conducted a multi-year survey of the landscape-scale distribution of escaped OSR plants adjacent to roads and cultivated fields. Our objective was to examine the long-term dynamics of escaped OSR at large spatial scales and to assess the relative importance of landscape and localised factors to the persistence and spread of these plants outside of cultivation. From 2005 to 2007, we surveyed escaped OSR plants along roadsides and field edges at 12 locations in three agricultural landscapes in southern Manitoba where GMHT OSR is widely grown. Data were analysed to examine temporal changes at large spatial scales and to determine factors affecting the distribution of escaped OSR plants in roadside and field edge habitats within agricultural landscapes. Additionally, we assessed the potential for seed dispersal between escaped populations by comparing the relative spatial distribution of roadside and field edge OSR. Densities of escaped OSR fluctuated over space and time in both roadside and field edge habitats, though the proportion of GMHT plants was high (93-100%). Escaped OSR was positively affected by agricultural landscape (indicative of cropping intensity) and by the presence of an adjacent field planted to OSR. Within roadside habitats, escaped OSR was also strongly associated with large-scale variables, including road surface (indicative of traffic intensity) and distance to the nearest grain elevator. Conversely, within field edges, OSR density was affected by localised crop management practices such as mowing, soil disturbance and herbicide application. Despite the proximity of roadsides and field edges, there was little evidence of spatial aggregation among escaped OSR populations in these two habitats, especially at very fine spatial scales (i.e. <100 m), suggesting that natural propagule exchange is infrequent. Escaped OSR populations were persistent at large spatial and temporal scales, and low density in a given landscape or year was not indicative of overall extinction. As a result of ongoing cultivation and transport of OSR crops, escaped GMHT traits will likely remain predominant in agricultural landscapes. While escaped OSR in field edge habitats generally results from local seeding and management activities occurring at the field-scale, distribution patterns within roadside habitats are determined in large part by seed transport occurring at the landscape scale and at even larger regional scales. Our findings suggest that these large-scale anthropogenic dispersal processes are sufficient to enable persistence despite limited natural seed dispersal. This widespread dispersal is likely to undermine field-scale management practices aimed at eliminating escaped and in-field GMHT OSR populations. Agricultural transport and landscape-scale cropping patterns are important determinants of the distribution of escaped GM crops. At the regional level, these factors ensure ongoing establishment and spread of escaped GMHT OSR despite limited local seed dispersal. Escaped populations thus play an important role in the spread of transgenes and have substantial implications for the coexistence of GM and non-GM production systems. Given the large-scale factors driving the spread of escaped transgenes, localised co-existence measures may be impracticable where they are not commensurate with regional dispersal mechanisms. To be effective, strategies aimed at reducing contamination from GM crops should be multi-scale in approach and be developed and implemented at both farm and landscape levels of organisation. Multiple stakeholders should thus be consulted, including both GM and non-GM farmers, as well as seed developers, processors, transporters and suppliers. Decisions to adopt GM crops require thoughtful and inclusive consideration of the risks and responsibilities inherent in this new technology.

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

NASA Astrophysics Data System (ADS)

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 HydroSHEDS dataset with a resolution of 3" (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

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

NASA Astrophysics Data System (ADS)

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

2010-09-01

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 a 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. TGR 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 HydroSHEDS dataset with a resolution of 3'' (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

Comparative ecology of widely distributed pelagic fish species in the North Atlantic: Implications for modelling climate and fisheries impacts

NASA Astrophysics Data System (ADS)

Trenkel, V. M.; Huse, G.; MacKenzie, B. R.; Alvarez, P.; Arrizabalaga, H.; Castonguay, M.; Goñi, N.; Grégoire, F.; Hátún, H.; Jansen, T.; Jacobsen, J. A.; Lehodey, P.; Lutcavage, M.; Mariani, P.; Melvin, G. D.; Neilson, J. D.; Nøttestad, L.; Óskarsson, G. J.; Payne, M. R.; Richardson, D. E.; Senina, I.; Speirs, D. C.

2014-12-01

This paper reviews the current knowledge on the ecology of widely distributed pelagic fish stocks in the North Atlantic basin with emphasis on their role in the food web and the factors determining their relationship with the environment. We consider herring (Clupea harengus), mackerel (Scomber scombrus), capelin (Mallotus villosus), blue whiting (Micromesistius poutassou), and horse mackerel (Trachurus trachurus), which have distributions extending beyond the continental shelf and predominantly occur on both sides of the North Atlantic. We also include albacore (Thunnus alalunga), bluefin tuna (Thunnus thynnus), swordfish (Xiphias gladius), and blue marlin (Makaira nigricans), which, by contrast, show large-scale migrations at the basin scale. We focus on the links between life history processes and the environment, horizontal and vertical distribution, spatial structure and trophic role. Many of these species carry out extensive migrations from spawning grounds to nursery and feeding areas. Large oceanographic features such as the North Atlantic subpolar gyre play an important role in determining spatial distributions and driving variations in stock size. Given the large biomasses of especially the smaller species considered here, these stocks can exert significant top-down pressures on the food web and are important in supporting higher trophic levels. The review reveals commonalities and differences between the ecology of widely distributed pelagic fish in the NE and NW Atlantic basins, identifies knowledge gaps and modelling needs that the EURO-BASIN project attempts to address.

Characterization of anthropogenic impacts in a large urban center by examining the spatial distribution of halogenated flame retardants.

PubMed

Wei, Yan-Li; Bao, Lian-Jun; Wu, Chen-Chou; Zeng, Eddy Y

2016-08-01

Anthropogenic impacts have continuously intensified in mega urban centers with increasing urbanization and growing population. The spatial distribution pattern of such impacts can be assessed with soil halogenated flame retardants (HFRs) as HFRs are mostly derived from the production and use of various consumer products. In the present study, soil samples were collected from the Pearl River Delta (PRD), a large urbanized region in southern China, and its surrounding areas and analyzed for a group of HFRs, i.e., polybrominated diphenyl ethers (PBDEs), decabromodiphenyl ethane, bis(hexachlorocyclopentadieno)cyclooctane (DP) and hexabromobenzene. The sum concentrations of HFRs and PBDEs were in the ranges of 0.66-6500 and 0.37-5700 (mean: 290 and 250) ng g(-1) dry weight, respectively, around the middle level of the global range. BDE-209 was the predominant compound likely due to the huge amounts of usage and its persistence. The concentrations of HFRs were greater in the land-use types of residency, industry and landfill than in agriculture, forestry and drinking water source, and were also greater in the central PRD than in its surrounding areas. The concentrations of HFRs were moderately significantly (r(2) = 0.32-0.57; p < 0.05) correlated with urbanization levels, population densities and gross domestic productions in fifteen administrative districts. The spatial distribution of DP isomers appeared to be stereoselective as indicated by the similarity in the spatial patterns for the ratio of anti-DP versus the sum of DP isomers (fanti-DP) and DP concentrations. Finally, the concentrations of HFRs sharply decreased with increasing distance from an e-waste recycling site, indicating that e-waste derived HFRs largely remained in local soil. Copyright © 2016 Elsevier Ltd. All rights reserved.

A comparative study of spatially clustered distribution of jumbo flying squid ( Dosidicus gigas) offshore Peru

NASA Astrophysics Data System (ADS)

Feng, Yongjiu; Cui, Li; Chen, Xinjun; Liu, Yu

2017-06-01

We examined spatially clustered distribution of jumbo flying squid ( Dosidicus gigas) in the offshore waters of Peru bounded by 78°-86°W and 8°-20°S under 0.5°×0.5° fishing grid. The study is based on the catch-per-unit-effort (CPUE) and fishing effort from Chinese mainland squid jigging fleet in 2003-2004 and 2006-2013. The data for all years as well as the eight years (excluding El Niño events) were studied to examine the effect of climate variation on the spatial distribution of D. gigas. Five spatial clusters reflecting the spatial distribution were computed using K-means and Getis-Ord Gi* for a detailed comparative study. Our results showed that clusters identified by the two methods were quite different in terms of their spatial patterns, and K-means was not as accurate as Getis-Ord Gi*, as inferred from the agreement degree and receiver operating characteristic. There were more areas of hot and cold spots in years without the impact of El Niño, suggesting that such large-scale climate variations could reduce the clustering level of D. gigas. The catches also showed that warm El Niño conditions and high water temperature were less favorable for D. gigas offshore Peru. The results suggested that the use of K-means is preferable if the aim is to discover the spatial distribution of each sub-region (cluster) of the study area, while Getis-Ord Gi* is preferable if the aim is to identify statistically significant hot spots that may indicate the central fishing ground.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

PubMed Central

Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian

2013-01-01

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km2 to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere. PMID:22686347

A 14 h {sup −3} Gpc{sup 3} study of cosmic homogeneity using BOSS DR12 quasar sample

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

Laurent, Pierre; Goff, Jean-Marc Le; Burtin, Etienne

2016-11-01

The BOSS quasar sample is used to study cosmic homogeneity with a 3D survey in the redshift range 2.2 < z < 2.8. We measure the count-in-sphere, N (< r ), i.e. the average number of objects around a given object, and its logarithmic derivative, the fractal correlation dimension, D {sub 2}( r ). For a homogeneous distribution N (< r ) ∝ r {sup 3} and D {sub 2}( r ) = 3. Due to the uncertainty on tracer density evolution, 3D surveys can only probe homogeneity up to a redshift dependence, i.e. they probe so-called ''spatial isotropy'. Ourmore » data demonstrate spatial isotropy of the quasar distribution in the redshift range 2.2 < z < 2.8 in a model-independent way, independent of any FLRW fiducial cosmology, resulting in 3 − ( D {sub 2}) < 1.7 × 10{sup −3} (2 σ) over the range 250 < r < 1200 h {sup −1} Mpc for the quasar distribution. If we assume that quasars do not have a bias much less than unity, this implies spatial isotropy of the matter distribution on large scales. Then, combining with the Copernican principle, we finally get homogeneity of the matter distribution on large scales. Alternatively, using a flat ΛCDM fiducial cosmology with CMB-derived parameters, and measuring the quasar bias relative to this ΛCDM model, our data provide a consistency check of the model, in terms of how homogeneous the Universe is on different scales. D {sub 2}( r ) is found to be compatible with our ΛCDM model on the whole 10 < r < 1200 h {sup −1} Mpc range. For the matter distribution we obtain 3 − ( D {sub 2}) < 5 × 10{sup −5} (2 σ) over the range 250 < r < 1200 h {sup −1} Mpc, consistent with homogeneity on large scales.« less

Additional studies of forest classification accuracy as influenced by multispectral scanner spatial resolution

NASA Technical Reports Server (NTRS)

Sadowski, F. E.; Sarno, J. E.

1976-01-01

First, an analysis of forest feature signatures was used to help explain the large variation in classification accuracy that can occur among individual forest features for any one case of spatial resolution and the inconsistent changes in classification accuracy that were demonstrated among features as spatial resolution was degraded. Second, the classification rejection threshold was varied in an effort to reduce the large proportion of unclassified resolution elements that previously appeared in the processing of coarse resolution data when a constant rejection threshold was used for all cases of spatial resolution. For the signature analysis, two-channel ellipse plots showing the feature signature distributions for several cases of spatial resolution indicated that the capability of signatures to correctly identify their respective features is dependent on the amount of statistical overlap among signatures. Reductions in signature variance that occur in data of degraded spatial resolution may not necessarily decrease the amount of statistical overlap among signatures having large variance and small mean separations. Features classified by such signatures may thus continue to have similar amounts of misclassified elements in coarser resolution data, and thus, not necessarily improve in classification accuracy.

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

PubMed

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

2011-10-01

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

Locally adaptive, spatially explicit projection of US population for 2030 and 2050.

PubMed

McKee, Jacob J; Rose, Amy N; Bright, Edward A; Huynh, Timmy; Bhaduri, Budhendra L

2015-02-03

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Building on the spatial interpolation technique previously developed for high-resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically informed spatial distribution of projected population of the contiguous United States for 2030 and 2050, depicting one of many possible population futures. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modeled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the US Census's projection methodology, with the US Census's official projection as the benchmark. Applications of our model include incorporating multiple various scenario-driven events to produce a range of spatially explicit population futures for suitability modeling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.

On the use of distributed sensing in control of large flexible spacecraft

NASA Technical Reports Server (NTRS)

Montgomery, Raymond C.; Ghosh, Dave

1990-01-01

Distributed processing technology is being developed to process signals from distributed sensors using distributed computations. Thiw work presents a scheme for calculating the operators required to emulate a conventional Kalman filter and regulator using such a computer. The scheme makes use of conventional Kalman theory as applied to the control of large flexible structures. The required computation of the distributed operators given the conventional Kalman filter and regulator is explained. A straightforward application of this scheme may lead to nonsmooth operators whose convergence is not apparent. This is illustrated by application to the Mini-Mast, a large flexible truss at the Langley Research Center used for research in structural dynamics and control. Techniques for developing smooth operators are presented. These involve spatial filtering as well as adjusting the design constants in the Kalman theory. Results are presented that illustrate the degree of smoothness achieved.

Video quality pooling adaptive to perceptual distortion severity.

PubMed

Park, Jincheol; Seshadrinathan, Kalpana; Lee, Sanghoon; Bovik, Alan Conrad

2013-02-01

It is generally recognized that severe video distortions that are transient in space and/or time have a large effect on overall perceived video quality. In order to understand this phenomena, we study the distribution of spatio-temporally local quality scores obtained from several video quality assessment (VQA) algorithms on videos suffering from compression and lossy transmission over communication channels. We propose a content adaptive spatial and temporal pooling strategy based on the observed distribution. Our method adaptively emphasizes "worst" scores along both the spatial and temporal dimensions of a video sequence and also considers the perceptual effect of large-area cohesive motion flow such as egomotion. We demonstrate the efficacy of the method by testing it using three different VQA algorithms on the LIVE Video Quality database and the EPFL-PoliMI video quality database.

Large-scale geographic variation in distribution and abundance of Australian deep-water kelp forests.

PubMed

Marzinelli, Ezequiel M; Williams, Stefan B; Babcock, Russell C; Barrett, Neville S; Johnson, Craig R; Jordan, Alan; Kendrick, Gary A; Pizarro, Oscar R; Smale, Dan A; Steinberg, Peter D

2015-01-01

Despite the significance of marine habitat-forming organisms, little is known about their large-scale distribution and abundance in deeper waters, where they are difficult to access. Such information is necessary to develop sound conservation and management strategies. Kelps are main habitat-formers in temperate reefs worldwide; however, these habitats are highly sensitive to environmental change. The kelp Ecklonia radiate is the major habitat-forming organism on subtidal reefs in temperate Australia. Here, we provide large-scale ecological data encompassing the latitudinal distribution along the continent of these kelp forests, which is a necessary first step towards quantitative inferences about the effects of climatic change and other stressors on these valuable habitats. We used the Autonomous Underwater Vehicle (AUV) facility of Australia's Integrated Marine Observing System (IMOS) to survey 157,000 m2 of seabed, of which ca 13,000 m2 were used to quantify kelp covers at multiple spatial scales (10-100 m to 100-1,000 km) and depths (15-60 m) across several regions ca 2-6° latitude apart along the East and West coast of Australia. We investigated the large-scale geographic variation in distribution and abundance of deep-water kelp (>15 m depth) and their relationships with physical variables. Kelp cover generally increased with latitude despite great variability at smaller spatial scales. Maximum depth of kelp occurrence was 40-50 m. Kelp latitudinal distribution along the continent was most strongly related to water temperature and substratum availability. This extensive survey data, coupled with ongoing AUV missions, will allow for the detection of long-term shifts in the distribution and abundance of habitat-forming kelp and the organisms they support on a continental scale, and provide information necessary for successful implementation and management of conservation reserves.

Upper Washita River experimental watersheds: Multiyear stability of soil water content profiles

USDA-ARS?s Scientific Manuscript database

Scaling in situ soil water content time series data to a large spatial domain is a key element of watershed environmental monitoring and modeling. The primary method of estimating and monitoring large-scale soil water content distributions is via in situ networks. It is critical to establish the s...

Biophysical, infrastructural and social heterogeneities explain spatial distribution of waterborne gastrointestinal disease burden in Mexico City

NASA Astrophysics Data System (ADS)

Baeza, Andrés; Estrada-Barón, Alejandra; Serrano-Candela, Fidel; Bojórquez, Luis A.; Eakin, Hallie; Escalante, Ana E.

2018-06-01

Due to unplanned growth, large extension and limited resources, most megacities in the developing world are vulnerable to hydrological hazards and infectious diseases caused by waterborne pathogens. Here we aim to elucidate the extent of the relation between the spatial heterogeneity of physical and socio-economic factors associated with hydrological hazards (flooding and scarcity) and the spatial distribution of gastrointestinal disease in Mexico City, a megacity with more than 8 million people. We applied spatial statistics and multivariate regression analyses to high resolution records of gastrointestinal diseases during two time frames (2007–2009 and 2010–2014). Results show a pattern of significant association between water flooding events and disease incidence in the city center (lowlands). We also found that in the periphery (highlands), higher incidence is generally associated with household infrastructure deficiency. Our findings suggest the need for integrated and spatially tailored interventions by public works and public health agencies, aimed to manage socio-hydrological vulnerability in Mexico City.

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

PubMed Central

Wilson, Adam M.; Jetz, Walter

2016-01-01

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

Tropical forest carbon balance: effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass

NASA Astrophysics Data System (ADS)

Di Vittorio, Alan V.; Negrón-Juárez, Robinson I.; Higuchi, Niro; Chambers, Jeffrey Q.

2014-03-01

Debate continues over the adequacy of existing field plots to sufficiently capture Amazon forest dynamics to estimate regional forest carbon balance. Tree mortality dynamics are particularly uncertain due to the difficulty of observing large, infrequent disturbances. A recent paper (Chambers et al 2013 Proc. Natl Acad. Sci. 110 3949-54) reported that Central Amazon plots missed 9-17% of tree mortality, and here we address ‘why’ by elucidating two distinct mortality components: (1) variation in annual landscape-scale average mortality and (2) the frequency distribution of the size of clustered mortality events. Using a stochastic-empirical tree growth model we show that a power law distribution of event size (based on merged plot and satellite data) is required to generate spatial clustering of mortality that is consistent with forest gap observations. We conclude that existing plots do not sufficiently capture losses because their placement, size, and longevity assume spatially random mortality, while mortality is actually distributed among differently sized events (clusters of dead trees) that determine the spatial structure of forest canopies.

Heterogeneous game resource distributions promote cooperation in spatial prisoner's dilemma game

NASA Astrophysics Data System (ADS)

Cui, Guang-Hai; Wang, Zhen; Yang, Yan-Cun; Tian, Sheng-Wen; Yue, Jun

2018-01-01

In social networks, individual abilities to establish interactions are always heterogeneous and independent of the number of topological neighbors. We here study the influence of heterogeneous distributions of abilities on the evolution of individual cooperation in the spatial prisoner's dilemma game. First, we introduced a prisoner's dilemma game, taking into account individual heterogeneous abilities to establish games, which are determined by the owned game resources. Second, we studied three types of game resource distributions that follow the power-law property. Simulation results show that the heterogeneous distribution of individual game resources can promote cooperation effectively, and the heterogeneous level of resource distributions has a positive influence on the maintenance of cooperation. Extensive analysis shows that cooperators with large resource capacities can foster cooperator clusters around themselves. Furthermore, when the temptation to defect is high, cooperator clusters in which the central pure cooperators have larger game resource capacities are more stable than other cooperator clusters.

Snowpack spatial variability: Towards understanding its effect on remote sensing measurements and snow slope stability

NASA Astrophysics Data System (ADS)

Marshall, Hans-Peter

The distribution of water in the snow-covered areas of the world is an important climate change indicator, and it is a vital component of the water cycle. At local and regional scales, the snow water equivalent (SWE), the amount of liquid water a given area of the snowpack represents, is very important for water resource management, flood forecasting, and prediction of available hydropower energy. Measurements from only a few automatic weather stations, such as the SNOTEL network, or sparse manual snowpack measurements are typically extrapolated for estimating SWE over an entire basin. Widespread spatial variability in the distribution of SWE and snowpack stratigraphy at local scales causes large errors in these basin estimates. Remote sensing measurements offer a promising alternative, due to their large spatial coverage and high temporal resolution. Although snow cover extent can currently be estimated from remote sensing data, accurately quantifying SWE from remote sensing measurements has remained difficult, due to a high sensitivity to variations in grain size and stratigraphy. In alpine snowpacks, the large degree of spatial variability of snowpack properties and geometry, caused by topographic, vegetative, and microclimatic effects, also makes prediction of snow avalanches very difficult. Ground-based radar and penetrometer measurements can quickly and accurately characterize snowpack properties and SWE in the field. A portable lightweight radar was developed, and allows a real-time estimate of SWE to within 10%, as well as measurements of depths of all major density transitions within the snowpack. New analysis techniques developed in this thesis allow accurate estimates of mechanical properties and an index of grain size to be retrieved from the SnowMicroPenetrometer. These two tools together allow rapid characterization of the snowpack's geometry, mechanical properties, and SWE, and are used to guide a finite element model to study the stress distribution on a slope. The ability to accurately characterize snowpack properties at much higher resolutions and spatial extent than previously possible will hopefully help lead to a more complete understanding of spatial variability, its effect on remote sensing measurements and snow slope stability, and result in improvements in avalanche prediction and accuracy of SWE estimates from space.

Investigation of Spatial Control Strategies for AHWR: A Comparative Study

NASA Astrophysics Data System (ADS)

Munje, R. K.; Patre, B. M.; Londhe, P. S.; Tiwari, A. P.; Shimjith, S. R.

2016-04-01

Large nuclear reactors such as the Advanced Heavy Water Reactor (AHWR), are susceptible to xenon-induced spatial oscillations in which, though the core average power remains constant, the power distribution may be nonuniform as well as it might experience unstable oscillations. Such oscillations influence the operation and control philosophy and could also drive safety issues. Therefore, large nuclear reactors are equipped with spatial controllers which maintain the core power distribution close to desired distribution during all the facets of operation and following disturbances. In this paper, the case of AHWR has been considered, for which a number of different types of spatial controllers have been designed during the last decade. Some of these designs are based on output feedback while the others are based on state feedback. Also, both the conventional and modern control concepts, such as linear quadratic regulator theory, sliding mode control, multirate output feedback control and fuzzy control have been investigated. The designs of these different controllers for the AHWR have been carried out using a 90th order model, which is highly stiff. Hence, direct application of design methods suffers with numerical ill-conditioning. Singular perturbation and time-scale methods have been applied whereby the design problem for the original higher order system is decoupled into two or three subproblems, each of which is solved separately. Nonlinear simulations have been carried out to obtain the transient responses of the system with different types of controllers and their performances have been compared.

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

NASA Astrophysics Data System (ADS)

Huang, Dong; Liu, Yangang

2014-12-01

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost, allowing for more realistic representation of cloud radiation interactions in large-scale models.

Hexabromocyclododecanes (HBCDDs) in surface soils from coastal cities in North China: Correlation between diastereoisomer profiles and industrial activities.

PubMed

Zhang, Yueqing; Li, Qifeng; Lu, Yonglong; Jones, Kevin; Sweetman, Andrew J

2016-04-01

Hexabromocyclododecane (HBCDD) is a brominated flame retardant with a wide range of industrial applications, although little is known about its patterns of spatial distribution in soils in relation to industrial emissions. This study has undertaken a large-scale investigation around an industrialized coastal area of China, exploring the concentrations, spatial distribution and diastereoisomer profiles of HBCDD in 188 surface soils from 21 coastal cities in North China. The detection frequency was 100% and concentrations of total HBCDD in the surface soils ranged from 0.123 to 363 ng g(-1) and averaged 7.20 ng g(-1), showing its ubiquitous existence at low levels. The spatial distribution of HBCDD exhibited a correlation with the location of known manufacturing facilities in Weifang, suggesting the production of HBCDD as major emission source. Diastereoisomer profiles varied in different cities. Diastereoisomer compositions in soils were compared with emissions from HBCDD industrial activities, and correlations were found between them, which has the potential for source identification. Although the contemporary concentrations of HBCDD in soils from the study were relatively low, HBCDD-containing products (expanded/extruded polystyrene insulation boards) would be a potential source after its service life, and attention needs to be paid to prioritizing large-scale waste management efforts. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effect of Variable Spatial Scales on USLE-GIS Computations

NASA Astrophysics Data System (ADS)

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.

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

PubMed Central

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

2007-01-01

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

IRAS galaxies and the large-scale structure in the CfA slice

NASA Technical Reports Server (NTRS)

Babul, Arif; Postman, Marc

1990-01-01

The spatial distributions of the IRAS and the optical galaxies in the first CfA slice are compared. The IRAS galaxies are generally less clustered than optical ones, but their distribution is essentially identical to that of late-type optical galaxies. The discrepancy between the clustering properties of the IRAS and optical samples in the CfA slice region is found to be entirely due to the paucity of IRAS galaxies in the core of the Coma cluster. The spatial distributions of the IRAS and the optical galaxies, both late and early types, outside the dense core of the Coma cluster are entirely consistent with each other. This conflicts with the prediction of the linear biasing scenario.

Macroecology of unicellular organisms - patterns and processes.

PubMed

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.

Spatial Downscaling of Alien Species Presences using Machine Learning

NASA Astrophysics Data System (ADS)

Daliakopoulos, Ioannis N.; Katsanevakis, Stelios; Moustakas, Aristides

2017-07-01

Large scale, high-resolution data on alien species distributions are essential for spatially explicit assessments of their environmental and socio-economic impacts, and management interventions for mitigation. However, these data are often unavailable. This paper presents a method that relies on Random Forest (RF) models to distribute alien species presence counts at a finer resolution grid, thus achieving spatial downscaling. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The method is tested with an approximately 8×8 km2 grid containing floral alien species presence and several indices of climatic, habitat, land use covariates for the Mediterranean island of Crete, Greece. Alien species presence is aggregated at 16×16 km2 and used as a predictor of presence at the original resolution, thus simulating spatial downscaling. Potential explanatory variables included habitat types, land cover richness, endemic species richness, soil type, temperature, precipitation, and freshwater availability. Uncertainty assessment of the spatial downscaling of alien species’ occurrences was also performed and true/false presences and absences were quantified. The approach is promising for downscaling alien species datasets of larger spatial scale but coarse resolution, where the underlying environmental information is available at a finer resolution than the alien species data. Furthermore, the RF architecture allows for tuning towards operationally optimal sensitivity and specificity, thus providing a decision support tool for designing a resource efficient alien species census.

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

NASA Astrophysics Data System (ADS)

Guenther, A. B.; Duhl, T.

2011-12-01

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

Spatial Distribution and Relationship of T1ρ and T2 Relaxation Times in Knee Cartilage With Osteoarthritis

PubMed Central

Li, Xiaojuan; Pai, Alex; Blumenkrantz, Gabrielle; Carballido-Gamio, Julio; Link, Thomas; Ma, Benjamin; Ries, Michael; Majumdar, Sharmila

2009-01-01

T1ρ and T2 relaxation time constants have been proposed to probe biochemical changes in osteoarthritic cartilage. This study aimed to evaluate the spatial correlation and distribution of T1ρ and T2 values in osteoarthritic cartilage. Ten patients with osteoarthritis (OA) and 10 controls were studied at 3T. The spatial correlation of T1ρ and T2 values was investigated using Z-scores. The spatial variation of T1ρ and T2 values in patellar cartilage was studied in different cartilage layers. The distribution of these relaxation time constants was measured using texture analysis parameters based on gray-level co-occurrence matrices (GLCM). The mean Z-scores for T1ρ and T2 values were significantly higher in OA patients vs. controls (P < 0.05). Regional correlation coefficients of T1ρ and T2 Z-scores showed a large range in both controls and OA patients (0.2– 0.7). OA patients had significantly greater GLCM contrast and entropy of T1ρ values than controls (P < 0.05). In summary, T1ρ and T2 values are not only increased but are also more heterogeneous in osteoarthritic cartilage. T1ρ and T2 values show different spatial distributions and may provide complementary information regarding cartilage degeneration in OA. PMID:19319904

Assessing species distribution using Google Street View: a pilot study with the Pine Processionary Moth.

PubMed

Rousselet, Jérôme; Imbert, Charles-Edouard; Dekri, Anissa; Garcia, Jacques; Goussard, Francis; Vincent, Bruno; Denux, Olivier; Robinet, Christelle; Dorkeld, Franck; Roques, Alain; Rossi, Jean-Pierre

2013-01-01

Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google Street View could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google Street View. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google Street View were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google Street View network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant.

Assessing Species Distribution Using Google Street View: A Pilot Study with the Pine Processionary Moth

PubMed Central

Dekri, Anissa; Garcia, Jacques; Goussard, Francis; Vincent, Bruno; Denux, Olivier; Robinet, Christelle; Dorkeld, Franck; Roques, Alain; Rossi, Jean-Pierre

2013-01-01

Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google street view could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google street view. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google street view were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google street view network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant. PMID:24130675

Validation of a simple distributed sediment delivery approach in selected sub-basins of the River Inn catchment area

NASA Astrophysics Data System (ADS)

Reid, Lucas; Kittlaus, Steffen; Scherer, Ulrike

2015-04-01

For large areas without highly detailed data the empirical Universal Soil Loss Equation (USLE) is widely used to quantify soil loss. The problem though is usually the quantification of actual sediment influx into the rivers. As the USLE provides long-term mean soil loss rates, it is often combined with spatially lumped models to estimate the sediment delivery ratio (SDR). But it gets difficult with spatially lumped approaches in large catchment areas where the geographical properties have a wide variance. In this study we developed a simple but spatially distributed approach to quantify the sediment delivery ratio by considering the characteristics of the flow paths in the catchments. The sediment delivery ratio was determined using an empirical approach considering the slope, morphology and land use properties along the flow path as an estimation of travel time of the eroded particles. The model was tested against suspended solids measurements in selected sub-basins of the River Inn catchment area in Germany and Austria, ranging from the high alpine south to the Molasse basin in the northern part.

Application and Analysis of Measurement Model for Calibrating Spatial Shear Surface in Triaxial Test

NASA Astrophysics Data System (ADS)

Zhang, Zhihua; Qiu, Hongsheng; Zhang, Xiedong; Zhang, Hang

2017-12-01

Discrete element method has great advantages in simulating the contacts, fractures, large displacement and deformation between particles. In order to analyze the spatial distribution of the shear surface in the three-dimensional triaxial test, a measurement model is inserted in the numerical triaxial model which is generated by weighted average assembling method. Due to the non-visibility of internal shear surface in laboratory, it is largely insufficient to judge the trend of internal shear surface only based on the superficial cracks of sheared sample, therefore, the measurement model is introduced. The trend of the internal shear zone is analyzed according to the variations of porosity, coordination number and volumetric strain in each layer. It shows that as a case study on confining stress of 0.8 MPa, the spatial shear surface is calibrated with the results of the rotated particle distribution and the theoretical value with the specific characteristics of the increase of porosity, the decrease of coordination number, and the increase of volumetric strain, which represents the measurement model used in three-dimensional model is applicable.

Spatial and temporal variability in the R-5 infiltration data set: Déjà vu and rainfall-runoff simulations

NASA Astrophysics Data System (ADS)

Loague, Keith; Kyriakidis, Phaedon C.

1997-12-01

This paper is a continuation of the event-based rainfall-runoff model evaluation study reported by Loague and Freeze [1985[. Here we reevaluate the performance of a quasi-physically based rainfall-runoff model for three large events from the well-known R-5 catchment. Five different statistical criteria are used to quantitatively judge model performance. Temporal variability in the large R-5 infiltration data set [Loague and Gander, 1990] is filtered by working in terms of permeability. The transformed data set is reanalyzed via geostatistical methods to model the spatial distribution of permeability across the R-5 catchment. We present new estimates of the spatial distribution of infiltration that are in turn used in our rainfall-runoff simulations with the Horton rainfall-runoff model. The new rainfall-runoff simulations, complicated by reinfiltration impacts at the smaller scales of characterization, indicate that the near-surface hydrologic response of the R-5 catchment is most probably dominated by a combination of the Horton and Dunne overland flow mechanisms.

Metamaterial devices for molding the flow of diffuse light (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wegener, Martin

2016-09-01

Much of optics in the ballistic regime is about designing devices to mold the flow of light. This task is accomplished via specific spatial distributions of the refractive index or the refractive-index tensor. For light propagating in turbid media, a corresponding design approach has not been applied previously. Here, we review our corresponding recent work in which we design spatial distributions of the light diffusivity or the light-diffusivity tensor to accomplish specific tasks. As an application, we realize cloaking of metal contacts on large-area OLEDs, eliminating the contacts' shadows, thereby homogenizing the diffuse light emission. In more detail, metal contacts on large-area organic light-emitting diodes (OLEDs) are mandatory electrically, but they cast optical shadows, leading to unwanted spatially inhomogeneous diffuse light emission. We show that the contacts can be made invisible either by (i) laminate metamaterials designed by coordinate transformations of the diffusion equation or by (ii) triangular-shaped regions with piecewise constant diffusivity, hence constant concentration of scattering centers. These structures are post-optimized in regard to light throughput by Monte-Carlo ray-tracing simulations and successfully validated by model experiments.

Spatial distribution of defect luminescence in GaN nanowires.

PubMed

Li, Qiming; Wang, George T

2010-05-12

The spatial distribution of defect-related and band-edge luminescence from GaN nanowires grown by metal-organic chemical vapor deposition was studied by spatially resolved cathodoluminescence imaging and spectroscopy. A surface layer exhibiting strong yellow luminescence (YL) near 566 nm in the nanowires was revealed, compared to weak YL in the bulk. In contrast, other defect-related luminescence near 428 nm (blue luminescence) and 734 nm (red luminescence), in addition to band-edge luminescence (BEL) at 366 nm, were observed in the bulk of the nanowires but were largely absent at the surface. As the nanowire width approaches a critical dimension, the surface YL layer completely quenches the BEL. The surface YL is attributed to the diffusion and piling up of mobile point defects, likely isolated gallium vacancies, at the surface during growth.

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

PubMed

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 dataset mergers, such as the one exemplified here, can serve as a baseline towards comprehensive species distribution datasets.

Distribution of Large Wood Within River Corridors in Relation to Flow Regime in the Semiarid Western US

NASA Astrophysics Data System (ADS)

Wohl, Ellen; Cadol, Daniel; Pfeiffer, Andrew; Jackson, Karen; Laurel, DeAnna

2018-03-01

The cumulative volume and spatial distribution of large wood (LW) along river corridors (channels and floodplains) reflect interactions between rates and volumes of LW recruitment and channel transport capacity through time. Rivers of the semiarid interior western US can have relatively low-magnitude disturbances associated with annual snowmelt or relatively high-magnitude disturbances associated with episodic rainfall runoff, especially following wildfires. We use characteristics of LW from 25 river segments in four regions of New Mexico and Colorado to analyze wood loads and spatial patterns of wood distribution in relation to disturbance regime. High-magnitude disturbances move LW onto floodplains and create longitudinally nonuniform LW distributions with aggregated (closer together than random) LW pieces and abundant LW jams in the floodplain. Sites with low-magnitude disturbances have a greater proportion of LW in the channel and much of this wood is within segregated (farther apart than random) jams. These results imply that river management, which typically focuses on LW within channels, should focus on floodplain as well as in-channel LW in rivers with high-magnitude disturbances. The results also indicate that the proportions of LW loads in channels versus floodplains can differ significantly among rivers with different disturbance regimes that are otherwise similar in terms of forest type or drainage area. This is particularly relevant to mountainous regions with elevation-related changes in flow and disturbance regime. River management that reintroduces LW to river corridors will be most effective if it incorporates the mobility and spatial distribution of LW.

Environmental characteristics drive variation in Amazonian understorey bird assemblages

PubMed Central

Magnusson, William E.; Anderson, Marti J.; Schlegel, Martin; Pe’er, Guy; Henle, Klaus

2017-01-01

Tropical bird assemblages display patterns of high alpha and beta diversity and, as tropical birds exhibit strong habitat specificity, their spatial distributions are generally assumed to be driven primarily by environmental heterogeneity and interspecific interactions. However, spatial distributions of some Amazonian forest birds are also often restricted by large rivers and other large-scale topographic features, suggesting that dispersal limitation may also play a role in driving species’ turnover. In this study, we evaluated the effects of environmental characteristics, topographic and spatial variables on variation in local assemblage structure and diversity of birds in an old-growth forest in central Amazonia. Birds were mist-netted in 72 plots distributed systematically across a 10,000 ha reserve in each of three years. Alpha diversity remained stable through time, but species composition changed. Spatial variation in bird-assemblage structure was significantly related to environmental and topographic variables but not strongly related to spatial variables. At a broad scale, we found bird assemblages to be significantly distinct between two watersheds that are divided by a central ridgeline. We did not detect an effect of the ridgeline per se in driving these patterns, indicating that most birds are able to fly across it, and that differences in assemblage structure between watersheds may be due to unmeasured environmental variables or unique combinations of measured variables. Our study indicates that complex geography and landscape features can act together with environmental variables to drive changes in the diversity and composition of tropical bird assemblages at local scales, but highlights that we still know very little about what makes different parts of tropical forest suitable for different species. PMID:28225774

The methane distribution on Titan: high resolution spectroscopy in the near-IR with Keck NIRSPEC/AO

NASA Astrophysics Data System (ADS)

Adamkovics, Mate; Mitchell, Jonathan L.

2014-11-01

The distribution of methane on Titan is a diagnostic of regional scale meteorology and large scale atmospheric circulation. The observed formation of clouds and the transport of heat through the atmosphere both depend on spatial and temporal variations in methane humidity. We have performed observations to measure the the distribution on methane Titan using high spectral resolution near-IR (H-band) observations made with NIRSPEC, with adaptive optics, at Keck Observatory in July 2014. This work builds on previous attempts at this measurement with improvement in the observing protocol and data reduction, together with increased integration times. Radiative transfer models using line-by-line calculation of methane opacities from the HITRAN2012 database are used to retrieve methane abundances. We will describe analysis of the reduced observations, which show latitudinal spatial variation in the region the spectrum that is thought to be sensitive to methane abundance. Quantifying the methane abundance variation requires models that include the spatial variation in surface albedo and meridional haze gradient; we will describe (currently preliminary) analysis of the the methane distribution and uncertainties in the retrieval.

Clustering, randomness, and regularity in cloud fields: 2. Cumulus cloud fields

NASA Astrophysics Data System (ADS)

Zhu, T.; Lee, J.; Weger, R. C.; Welch, R. M.

1992-12-01

During the last decade a major controversy has been brewing concerning the proper characterization of cumulus convection. The prevailing view has been that cumulus clouds form in clusters, in which cloud spacing is closer than that found for the overall cloud field and which maintains its identity over many cloud lifetimes. This "mutual protection hypothesis" of Randall and Huffman (1980) has been challenged by the "inhibition hypothesis" of Ramirez et al. (1990) which strongly suggests that the spatial distribution of cumuli must tend toward a regular distribution. A dilemma has resulted because observations have been reported to support both hypotheses. The present work reports a detailed analysis of cumulus cloud field spatial distributions based upon Landsat, Advanced Very High Resolution Radiometer, and Skylab data. Both nearest-neighbor and point-to-cloud cumulative distribution function statistics are investigated. The results show unequivocally that when both large and small clouds are included in the cloud field distribution, the cloud field always has a strong clustering signal. The strength of clustering is largest at cloud diameters of about 200-300 m, diminishing with increasing cloud diameter. In many cases, clusters of small clouds are found which are not closely associated with large clouds. As the small clouds are eliminated from consideration, the cloud field typically tends towards regularity. Thus it would appear that the "inhibition hypothesis" of Ramirez and Bras (1990) has been verified for the large clouds. However, these results are based upon the analysis of point processes. A more exact analysis also is made which takes into account the cloud size distributions. Since distinct clouds are by definition nonoverlapping, cloud size effects place a restriction upon the possible locations of clouds in the cloud field. The net effect of this analysis is that the large clouds appear to be randomly distributed, with only weak tendencies towards regularity. For clouds less than 1 km in diameter, the average nearest-neighbor distance is equal to 3-7 cloud diameters. For larger clouds, the ratio of cloud nearest-neighbor distance to cloud diameter increases sharply with increasing cloud diameter. This demonstrates that large clouds inhibit the growth of other large clouds in their vicinity. Nevertheless, this leads to random distributions of large clouds, not regularity.

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

NASA Astrophysics Data System (ADS)

Xiao, F.

2018-04-01

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

The Influence of Sex and Season on Conspecific Spatial Overlap in a Large, Actively-Foraging Colubrid Snake

PubMed Central

Bauder, Javan M.; Breininger, David R.; Bolt, M. Rebecca; Legare, Michael L.; Jenkins, Christopher L.; Rothermel, Betsie B.; McGarigal, Kevin

2016-01-01

Understanding the factors influencing the degree of spatial overlap among conspecifics is important for understanding multiple ecological processes. Compared to terrestrial carnivores, relatively little is known about the factors influencing conspecific spatial overlap in snakes, although across snake taxa there appears to be substantial variation in conspecific spatial overlap. In this study, we described conspecific spatial overlap of eastern indigo snakes (Drymarchon couperi) in peninsular Florida and examined how conspecific spatial overlap varied by sex and season (breeding season vs. non-breeding season). We calculated multiple indices of spatial overlap using 6- and 3-month utilization distributions (UD) of dyads of simultaneously adjacent telemetered snakes. We also measured conspecific UD density values at each telemetry fix and modeled the distribution of those values as a function of overlap type, sex, and season using generalized Pareto distributions. Home range overlap between males and females was significantly greater than overlap between individuals of the same sex and male home ranges often completely contained female home ranges. Male home ranges overlapped little during both seasons, whereas females had higher levels of overlap during the non-breeding season. The spatial patterns observed in our study are consistent with those seen in many mammalian carnivores, in which low male-male overlap and high inter-sexual overlap provides males with greater access to females. We encourage additional research on the influence of prey availability on conspecific spatial overlap in snakes as well as the behavioral mechanisms responsible for maintaining the low levels of overlap we observed. PMID:27490346

Spatial Relationships of Sector-Specific Fossil-fuel CO2 Emissions in the United States

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

Zhou, Yuyu; Gurney, Kevin R.

2011-07-01

Quantification of the spatial distribution of sector-specific fossil fuel CO2 emissions provides strategic information to public and private decision-makers on climate change mitigation options and can provide critical constraints to carbon budget studies being performed at the national to urban scales. This study analyzes the spatial distribution and spatial drivers of total and sectoral fossil fuel CO2 emissions at the state and county levels in the United States. The spatial patterns of absolute versus per capita fossil fuel CO2 emissions differ substantially and these differences are sector-specific. Area-based sources such as those in the residential and commercial sectors are drivenmore » by a combination of population and surface temperature with per capita emissions largest in the northern latitudes and continental interior. Emission sources associated with large individual manufacturing or electricity producing facilities are heterogeneously distributed in both absolute and per capita metrics. The relationship between surface temperature and sectoral emissions suggests that the increased electricity consumption due to space cooling requirements under a warmer climate may outweigh the savings generated by lessened space heating. Spatial cluster analysis of fossil fuel CO2 emissions confirms that counties with high (low) CO2 emissions tend to be clustered close to other counties with high (low) CO2 emissions and some of the spatial clustering extends to multi-state spatial domains. This is particularly true for the residential and transportation sectors, suggesting that emissions mitigation policy might best be approached from the regional or multi-state perspective. Our findings underscore the potential for geographically focused, sector-specific emissions mitigation strategies and the importance of accurate spatial distribution of emitting sources when combined with atmospheric monitoring via aircraft, satellite and in situ measurements. Keywords: Fossil-fuel; Carbon dioxide emissions; Sectoral; Spatial cluster; Emissions mitigation policy« less

Learning from Massive Distributed Data Sets (Invited)

NASA Astrophysics Data System (ADS)

Kang, E. L.; Braverman, A. J.

2013-12-01

Technologies for remote sensing and ever-expanding computer experiments in climate science are generating massive data sets. Meanwhile, it has been common in all areas of large-scale science to have these 'big data' distributed over multiple different physical locations, and moving large amounts of data can be impractical. In this talk, we will discuss efficient ways for us to summarize and learn from distributed data. We formulate a graphical model to mimic the main characteristics of a distributed-data network, including the size of the data sets and speed of moving data. With this nominal model, we investigate the trade off between prediction accurate and cost of data movement, theoretically and through simulation experiments. We will also discuss new implementations of spatial and spatio-temporal statistical methods optimized for distributed data.

A mathematical model of a large open fire

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

Community- Weighted Mean Plant Traits Predict Small Scale Distribution of Insect Root Herbivore Abundance

PubMed Central

Jeltsch, Florian; Wurst, Susanne

2015-01-01

Small scale distribution of insect root herbivores may promote plant species diversity by creating patches of different herbivore pressure. However, determinants of small scale distribution of insect root herbivores, and impact of land use intensity on their small scale distribution are largely unknown. We sampled insect root herbivores and measured vegetation parameters and soil water content along transects in grasslands of different management intensity in three regions in Germany. We calculated community-weighted mean plant traits to test whether the functional plant community composition determines the small scale distribution of insect root herbivores. To analyze spatial patterns in plant species and trait composition and insect root herbivore abundance we computed Mantel correlograms. Insect root herbivores mainly comprised click beetle (Coleoptera, Elateridae) larvae (43%) in the investigated grasslands. Total insect root herbivore numbers were positively related to community-weighted mean traits indicating high plant growth rates and biomass (specific leaf area, reproductive- and vegetative plant height), and negatively related to plant traits indicating poor tissue quality (leaf C/N ratio). Generalist Elaterid larvae, when analyzed independently, were also positively related to high plant growth rates and furthermore to root dry mass, but were not related to tissue quality. Insect root herbivore numbers were not related to plant cover, plant species richness and soil water content. Plant species composition and to a lesser extent plant trait composition displayed spatial autocorrelation, which was not influenced by land use intensity. Insect root herbivore abundance was not spatially autocorrelated. We conclude that in semi-natural grasslands with a high share of generalist insect root herbivores, insect root herbivores affiliate with large, fast growing plants, presumably because of availability of high quantities of food. Affiliation of insect root herbivores with large, fast growing plants may counteract dominance of those species, thus promoting plant diversity. PMID:26517119

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

PubMed Central

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

Spatial embedding of structural similarity in the cerebral cortex

PubMed Central

Song, H. Francis; Kennedy, Henry; Wang, Xiao-Jing

2014-01-01

Recent anatomical tracing studies have yielded substantial amounts of data on the areal connectivity underlying distributed processing in cortex, yet the fundamental principles that govern the large-scale organization of cortex remain unknown. Here we show that functional similarity between areas as defined by the pattern of shared inputs or outputs is a key to understanding the areal network of cortex. In particular, we report a systematic relation in the monkey, human, and mouse cortex between the occurrence of connections from one area to another and their similarity distance. This characteristic relation is rooted in the wiring distance dependence of connections in the brain. We introduce a weighted, spatially embedded random network model that robustly gives rise to this structure, as well as many other spatial and topological properties observed in cortex. These include features that were not accounted for in any previous model, such as the wide range of interareal connection weights. Connections in the model emerge from an underlying distribution of spatially embedded axons, thereby integrating the two scales of cortical connectivity—individual axons and interareal pathways—into a common geometric framework. These results provide insights into the origin of large-scale connectivity in cortex and have important implications for theories of cortical organization. PMID:25368200

Galaxy clusters in the cosmic web

NASA Astrophysics Data System (ADS)

Acebrón, A.; Durret, F.; Martinet, N.; Adami, C.; Guennou, L.

2014-12-01

Simulations of large scale structure formation in the universe predict that matter is essentially distributed along filaments at the intersection of which lie galaxy clusters. We have analysed 9 clusters in the redshift range 0.4

Species Distribution Modelling: Contrasting presence-only models with plot abundance data.

PubMed

Gomes, Vitor H F; IJff, Stéphanie D; Raes, Niels; Amaral, Iêda Leão; Salomão, Rafael P; de Souza Coelho, Luiz; de Almeida Matos, Francisca Dionízia; Castilho, Carolina V; de Andrade Lima Filho, Diogenes; López, Dairon Cárdenas; Guevara, Juan Ernesto; Magnusson, William E; Phillips, Oliver L; Wittmann, Florian; de Jesus Veiga Carim, Marcelo; Martins, Maria Pires; Irume, Mariana Victória; Sabatier, Daniel; Molino, Jean-François; Bánki, Olaf S; da Silva Guimarães, José Renan; Pitman, Nigel C A; Piedade, Maria Teresa Fernandez; Mendoza, Abel Monteagudo; Luize, Bruno Garcia; Venticinque, Eduardo Martins; de Leão Novo, Evlyn Márcia Moraes; Vargas, Percy Núñez; Silva, Thiago Sanna Freire; Manzatto, Angelo Gilberto; Terborgh, John; Reis, Neidiane Farias Costa; Montero, Juan Carlos; Casula, Katia Regina; Marimon, Beatriz S; Marimon, Ben-Hur; Coronado, Euridice N Honorio; Feldpausch, Ted R; Duque, Alvaro; Zartman, Charles Eugene; Arboleda, Nicolás Castaño; Killeen, Timothy J; Mostacedo, Bonifacio; Vasquez, Rodolfo; Schöngart, Jochen; Assis, Rafael L; Medeiros, Marcelo Brilhante; Simon, Marcelo Fragomeni; Andrade, Ana; Laurance, William F; Camargo, José Luís; Demarchi, Layon O; Laurance, Susan G W; de Sousa Farias, Emanuelle; Nascimento, Henrique Eduardo Mendonça; Revilla, Juan David Cardenas; Quaresma, Adriano; Costa, Flavia R C; Vieira, Ima Célia Guimarães; Cintra, Bruno Barçante Ladvocat; Castellanos, Hernán; Brienen, Roel; Stevenson, Pablo R; Feitosa, Yuri; Duivenvoorden, Joost F; Aymard C, Gerardo A; Mogollón, Hugo F; Targhetta, Natalia; Comiskey, James A; Vicentini, Alberto; Lopes, Aline; Damasco, Gabriel; Dávila, Nállarett; García-Villacorta, Roosevelt; Levis, Carolina; Schietti, Juliana; Souza, Priscila; Emilio, Thaise; Alonso, Alfonso; Neill, David; Dallmeier, Francisco; Ferreira, Leandro Valle; Araujo-Murakami, Alejandro; Praia, Daniel; do Amaral, Dário Dantas; Carvalho, Fernanda Antunes; de Souza, Fernanda Coelho; Feeley, Kenneth; Arroyo, Luzmila; Pansonato, Marcelo Petratti; Gribel, Rogerio; Villa, Boris; Licona, Juan Carlos; Fine, Paul V A; Cerón, Carlos; Baraloto, Chris; Jimenez, Eliana M; Stropp, Juliana; Engel, Julien; Silveira, Marcos; Mora, Maria Cristina Peñuela; Petronelli, Pascal; Maas, Paul; Thomas-Caesar, Raquel; Henkel, Terry W; Daly, Doug; Paredes, Marcos Ríos; Baker, Tim R; Fuentes, Alfredo; Peres, Carlos A; Chave, Jerome; Pena, Jose Luis Marcelo; Dexter, Kyle G; Silman, Miles R; Jørgensen, Peter Møller; Pennington, Toby; Di Fiore, Anthony; Valverde, Fernando Cornejo; Phillips, Juan Fernando; Rivas-Torres, Gonzalo; von Hildebrand, Patricio; van Andel, Tinde R; Ruschel, Ademir R; Prieto, Adriana; Rudas, Agustín; Hoffman, Bruce; Vela, César I A; Barbosa, Edelcilio Marques; Zent, Egleé L; Gonzales, George Pepe Gallardo; Doza, Hilda Paulette Dávila; de Andrade Miranda, Ires Paula; Guillaumet, Jean-Louis; Pinto, Linder Felipe Mozombite; de Matos Bonates, Luiz Carlos; Silva, Natalino; Gómez, Ricardo Zárate; Zent, Stanford; Gonzales, Therany; Vos, Vincent A; Malhi, Yadvinder; Oliveira, Alexandre A; Cano, Angela; Albuquerque, Bianca Weiss; Vriesendorp, Corine; Correa, Diego Felipe; Torre, Emilio Vilanova; van der Heijden, Geertje; Ramirez-Angulo, Hirma; Ramos, José Ferreira; Young, Kenneth R; Rocha, Maira; Nascimento, Marcelo Trindade; Medina, Maria Natalia Umaña; Tirado, Milton; Wang, Ophelia; Sierra, Rodrigo; Torres-Lezama, Armando; Mendoza, Casimiro; Ferreira, Cid; Baider, Cláudia; Villarroel, Daniel; Balslev, Henrik; Mesones, Italo; Giraldo, Ligia Estela Urrego; Casas, Luisa Fernanda; Reategui, Manuel Augusto Ahuite; Linares-Palomino, Reynaldo; Zagt, Roderick; Cárdenas, Sasha; Farfan-Rios, William; Sampaio, Adeilza Felipe; Pauletto, Daniela; Sandoval, Elvis H Valderrama; Arevalo, Freddy Ramirez; Huamantupa-Chuquimaco, Isau; Garcia-Cabrera, Karina; Hernandez, Lionel; Gamarra, Luis Valenzuela; Alexiades, Miguel N; Pansini, Susamar; Cuenca, Walter Palacios; Milliken, William; Ricardo, Joana; Lopez-Gonzalez, Gabriela; Pos, Edwin; Ter Steege, Hans

2018-01-17

Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species' area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.

Recent warming leads to a rapid borealization of fish communities in the Arctic

NASA Astrophysics Data System (ADS)

Fossheim, Maria; Primicerio, Raul; Johannesen, Edda; Ingvaldsen, Randi B.; Aschan, Michaela M.; Dolgov, Andrey V.

2015-07-01

Arctic marine ecosystems are warming twice as fast as the global average. As a consequence of warming, many incoming species experience increasing abundances and expanding distribution ranges in the Arctic. The Arctic is expected to have the largest species turnover with regard to invading and locally extinct species, with a modelled invasion intensity of five times the global average. Studies in this region might therefore give valuable insights into community-wide shifts of species driven by climate warming. We found that the recent warming in the Barents Sea has led to a change in spatial distribution of fish communities, with boreal communities expanding northwards at a pace reflecting the local climate velocities. Increased abundance and distribution areas of large, migratory fish predators explain the observed community-wide distributional shifts. These shifts change the ecological interactions experienced by Arctic fish species. The Arctic shelf fish community retracted northwards to deeper areas bordering the deep polar basin. Depth might limit further retraction of some of the fish species in the Arctic shelf community. We conclude that climate warming is inducing structural change over large spatial scales at high latitudes, leading to a borealization of fish communities in the Arctic.

Scalable parallel distance field construction for large-scale applications

DOE PAGES

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan -Liu; ...

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. Anew distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking overtime, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate itsmore » efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. In conclusion, our work greatly extends the usability of distance fields for demanding applications.« less

Scalable Parallel Distance Field Construction for Large-Scale Applications.

PubMed

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan-Liu; Kolla, Hemanth; Chen, Jacqueline H

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.

The Applications of Model-Based Geostatistics in Helminth Epidemiology and Control

PubMed Central

Magalhães, Ricardo J. Soares; Clements, Archie C.A.; Patil, Anand P.; Gething, Peter W.; Brooker, Simon

2011-01-01

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes. PMID:21295680

AP-MALDI Mass Spectrometry Imaging of Gangliosides Using 2,6-Dihydroxyacetophenone

NASA Astrophysics Data System (ADS)

Jackson, Shelley N.; Muller, Ludovic; Roux, Aurelie; Oktem, Berk; Moskovets, Eugene; Doroshenko, Vladimir M.; Woods, Amina S.

2018-03-01

Matrix-assisted laser/desorption ionization (MALDI) mass spectrometry imaging (MSI) is widely used as a unique tool to record the distribution of a large range of biomolecules in tissues. 2,6-Dihydroxyacetophenone (DHA) matrix has been shown to provide efficient ionization of lipids, especially gangliosides. The major drawback for DHA as it applies to MS imaging is that it sublimes under vacuum (low pressure) at the extended time necessary to complete both high spatial and mass resolution MSI studies of whole organs. To overcome the problem of sublimation, we used an atmospheric pressure (AP)-MALDI source to obtain high spatial resolution images of lipids in the brain using a high mass resolution mass spectrometer. Additionally, the advantages of atmospheric pressure and DHA for imaging gangliosides are highlighted. The imaging of [M-H]- and [M-H2O-H]- mass peaks for GD1 gangliosides showed different distribution, most likely reflecting the different spatial distribution of GD1a and GD1b species in the brain. [Figure not available: see fulltext.

Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution.

PubMed

Gangnon, Ronald E

2012-03-01

The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, whereas rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. © 2011, The International Biometric Society.

Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution

PubMed Central

Gangnon, Ronald E.

2011-01-01

Summary The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, while rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. PMID:21762118

[Interdependence of plankton spatial distribution and plancton biomass temporal oscillations: mathematical simulation].

PubMed

Medvedinskiĭ, A B; Tikhonova, I A; Li, B L; Malchow, H

2003-01-01

The dynamics of aquatic biological communities in a patchy environment is of great interest in respect to interrelations between phenomena at various spatial and time scales. To study the complex plankton dynamics in relation to variations of such a biologically essential parameter as the fish predation rate, we use a simple reaction-diffusion model of trophic interactions between phytoplankton, zooplankton, and fish. We suggest that plankton is distributed between two habitats one of which is fish-free due to hydrological inhomogeneity, while the other is fish-populated. We show that temporal variations in the fish predation rate do not violate the strong correspondence between the character of spatial distribution of plankton and changes of plankton biomass in time: regular temporal oscillations of plankton biomass correspond to large-scale plankton patches, while chaotic oscillations correspond to small-scale plankton patterns. As in the case of the constant fish predation rate, the chaotic plankton dynamics is characterized by coexistence of the chaotic attractor and limit cycle.

Spatial distribution of heavy metals in surficial sediments from Guanabara Bay: Rio de Janeiro, Brazil

NASA Astrophysics Data System (ADS)

Neto, José Antônio Baptista; Gingele, Franz Xaver; Leipe, Thomas; Brehme, Isa

2006-04-01

Ninety-two surface sediment samples were collected in Guanabara Bay, one of the most prominent urban bays in SE Brazil, to investigate the spatial distribution of anthropogenic pollutants. The concentrations of heavy metals, organic carbon and particle size were examined in all samples. Large spatial variations of heavy metals and particle size were observed. The highest concentrations of heavy metals were found in the muddy sediments from the north western region of the bay near the main outlets of the most polluted rivers, municipal waste drainage systems and one of the major oil refineries. Another anomalous concentration of metals was found adjacent to Rio de Janeiro Harbour. The heavy metal concentrations decrease to the northeast, due to intact rivers and the mangrove systems in this area, and to the south where the sand fraction and open-marine processes dominate. The geochemical normalization of metal data to Li or Al has also demonstrated that the anthropogenic input of heavy metals have altered the natural sediment heavy metal distribution.

Study of diffusion and local structure of sodium-silicate liquid: the molecular dynamic simulation

NASA Astrophysics Data System (ADS)

Hung, Pham Khac; Noritake, Fumiya; San, Luyen Thi; Van, To Ba; Vinh, Le The

2017-10-01

A systematic analysis on sodium-silicate melt with various silica contents was carried out. The simulation revealed two diffusion mechanisms occurred in the melt: the bond-breaking and hopping between sites. The local structure was analyzed through T-simplexes. It was revealed that T-clusters have a non-spherical shape and represent the diffusion channel, in which Na atoms are dominant, but no any O atoms are located. The SiO2-poor melt acquires a long channel. In contrast, the SiO2-rich melt consists of unconnected short channels. The simulation also revealed the immobile and mobile regions which differ in local structure and constituent composition. We propose a new CL-function to characterizing the spatial distribution of different atom component. The spatial distribution of mobile and immobile atoms is found quite different. In particular, the immobile atoms are concentrated in high-density regions possessing very large density of immobile atoms. The spatial distribution of mobile atoms in contrast is more homogeneous.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Modelling spatial distribution of Patagonian toothfish through life-stages and sex and its implications for the fishery on the Kerguelen Plateau

NASA Astrophysics Data System (ADS)

Péron, Clara; Welsford, Dirk C.; Ziegler, Philippe; Lamb, Timothy D.; Gasco, Nicolas; Chazeau, Charlotte; Sinègre, Romain; Duhamel, Guy

2016-02-01

Size and sex specific habitat preferences are common in animal populations and can have important implications for sound spatial management of harvested species. Patagonian toothfish (Dissostichus eleginoides) is a commercially exploited fish species characterised by its longevity (>50 yo) and its extremely broad distribution in depths ranging from 10 m to 2500 m on most of the Plateaux, banks and seamounts of the Southern Ocean. As many bentho-pelagic fish species, Patagonian toothfish exhibits sexual dimorphism and ontogenetic habitat shift towards deeper waters as they grow. In this study, we modelled the spatial structure of Patagonian toothfish population (median total length and sex composition) in a data-rich area, the Kerguelen Plateau (Southern Indian Ocean), to better understand the ecological drivers of their distributional patterns and inform current and future fishery management strategies. We applied spatially-explicit statistical models to quantify and predict the effects of the complex topography of the Kerguelen Plateau in structuring the spatial distribution of Patagonian toothfish total length and sex ratio, while controlling for gear selectivity and season. Model predictions showed that juvenile toothfish live in shallow regions (shelf and banks) and move downward progressively up to 600 m while they grow. Between 600 m and 1200 m, the downward movement stops and fish settle at their preferred depths. While in this depth range, fish are ∼75 cm long and most vulnerable to fisheries. As they approach maturity large fish move downward to deep-sea habitats (from 1200 m to >2300 m) and head towards the spawning grounds on the western side of the plateau and around Skiff Bank. Importantly, the sex ratio was not evenly distributed across the Plateau; prediction maps revealed a higher proportion of females in the South whereas a strong male-bias sex ratio (70%) occurred in the North-West. Large-scale prediction maps derived from our models assisted in developing hypotheses regarding ecological drivers of Patagonian toothfish habitat-use and movement across different life stages and sex. Such hypotheses are crucial to inform management strategies of this multijurisdictional fishery (France and Australia) at the spatial and temporal scales over which natural processes and fishery extend.

Fish depth distributions in the Lower Mississippi River

USGS Publications Warehouse

Killgore, K. J.; Miranda, Leandro E.

2014-01-01

A substantial body of literature exists about depth distribution of fish in oceans, lakes and reservoirs, but less is known about fish depth distribution in large rivers. Most of the emphasis on fish distributions in rivers has focused on longitudinal and latitudinal spatial distributions. Knowledge on depth distribution is necessary to understand species and community habitat needs. Considering this void, our goal was to identify patterns in fish benthic distribution along depth gradients in the Lower Mississippi River. Fish were collected over 14 years in depths down to 27 m. Fish exhibited non-random depth distributions that varied seasonally and according to species. Species richness was highest in shallow water, with about 50% of the 62 species detected no longer collected in water deeper than 8 m and about 75% no longer collected in water deeper than 12 m. Although richness was highest in shallow water, most species were not restricted to shallow water. Rather, most species used a wide range of depths. A weak depth zonation occurred, not as strong as that reported for deep oceans and lakes. Larger fish tended to occur in deeper water during the high-water period of an annual cycle, but no correlation was evident during the low-water period. The advent of landscape ecology has guided river research to search for spatial patterns along the length of the river and associated floodplains. Our results suggest that fish assemblages in large rivers are also structured vertically. 

Temporal and spatial variations of Gutenberg-Richter parameter and fractal dimension in Western Anatolia, Turkey

NASA Astrophysics Data System (ADS)

Bayrak, Erdem; Yılmaz, Şeyda; Bayrak, Yusuf

2017-05-01

The temporal and spatial variations of Gutenberg-Richter parameter (b-value) and fractal dimension (DC) during the period 1900-2010 in Western Anatolia was investigated. The study area is divided into 15 different source zones based on their tectonic and seismotectonic regimes. We calculated the temporal variation of b and DC values in each region using Zmap. The temporal variation of these parameters for the prediction of major earthquakes was calculated. The spatial distribution of these parameters is related to the stress levels of the faults. We observed that b and DC values change before the major earthquakes in the 15 seismic regions. To evaluate the spatial distribution of b and DC values, 0.50° × 0.50° grid interval were used. The b-values smaller than 0.70 are related to the Aegean Arc and Eskisehir Fault. The highest values are related to Sultandağı and Sandıklı Faults. Fractal correlation dimension varies from 1.65 to 2.60, which shows that the study area has a higher DC value. The lowest DC values are related to the joining area between Aegean and Cyprus arcs, Burdur-Fethiye fault zone. Some have concluded that b-values drop instantly before large shocks. Others suggested that temporally stable low b value zones identify future large earthquake locations. The results reveal that large earthquakes occur when b decreases and DC increases, suggesting that variation of b and DC can be used as an earthquake precursor. Mapping of b and DC values provide information about the state of stress in the region, i.e. lower b and higher DC values associated with epicentral areas of large earthquakes.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

PubMed

Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian

2013-02-01

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere. © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society.

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

PubMed

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.

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

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

Huang, Dong; Liu, Yangang

2014-12-18

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost,more » allowing for more realistic representation of cloud radiation interactions in large-scale models.« less

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities.

PubMed

Frelat, Romain; Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs.

THE DEPENDENCE OF PRESTELLAR CORE MASS DISTRIBUTIONS ON THE STRUCTURE OF THE PARENTAL CLOUD

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

Parravano, Antonio; Sanchez, Nestor; Alfaro, Emilio J.

2012-08-01

The mass distribution of prestellar cores is obtained for clouds with arbitrary internal mass distributions using a selection criterion based on the thermal and turbulent Jeans mass and applied hierarchically from small to large scales. We have checked this methodology by comparing our results for a log-normal density probability distribution function with the theoretical core mass function (CMF) derived by Hennebelle and Chabrier, namely a power law at large scales and a log-normal cutoff at low scales, but our method can be applied to any mass distributions representing a star-forming cloud. This methodology enables us to connect the parental cloudmore » structure with the mass distribution of the cores and their spatial distribution, providing an efficient tool for investigating the physical properties of the molecular clouds that give rise to the prestellar core distributions observed. Simulated fractional Brownian motion (fBm) clouds with the Hurst exponent close to the value H = 1/3 give the best agreement with the theoretical CMF derived by Hennebelle and Chabrier and Chabrier's system initial mass function. Likewise, the spatial distribution of the cores derived from our methodology shows a surface density of companions compatible with those observed in Trapezium and Ophiucus star-forming regions. This method also allows us to analyze the properties of the mass distribution of cores for different realizations. We found that the variations in the number of cores formed in different realizations of fBm clouds (with the same Hurst exponent) are much larger than the expected root N statistical fluctuations, increasing with H.« less

The Dependence of Prestellar Core Mass Distributions on the Structure of the Parental Cloud

NASA Astrophysics Data System (ADS)

Parravano, Antonio; Sánchez, Néstor; Alfaro, Emilio J.

2012-08-01

The mass distribution of prestellar cores is obtained for clouds with arbitrary internal mass distributions using a selection criterion based on the thermal and turbulent Jeans mass and applied hierarchically from small to large scales. We have checked this methodology by comparing our results for a log-normal density probability distribution function with the theoretical core mass function (CMF) derived by Hennebelle & Chabrier, namely a power law at large scales and a log-normal cutoff at low scales, but our method can be applied to any mass distributions representing a star-forming cloud. This methodology enables us to connect the parental cloud structure with the mass distribution of the cores and their spatial distribution, providing an efficient tool for investigating the physical properties of the molecular clouds that give rise to the prestellar core distributions observed. Simulated fractional Brownian motion (fBm) clouds with the Hurst exponent close to the value H = 1/3 give the best agreement with the theoretical CMF derived by Hennebelle & Chabrier and Chabrier's system initial mass function. Likewise, the spatial distribution of the cores derived from our methodology shows a surface density of companions compatible with those observed in Trapezium and Ophiucus star-forming regions. This method also allows us to analyze the properties of the mass distribution of cores for different realizations. We found that the variations in the number of cores formed in different realizations of fBm clouds (with the same Hurst exponent) are much larger than the expected root {\\cal N} statistical fluctuations, increasing with H.

Imaging the distribution of transient viscosity after the 2016 Mw 7.1 Kumamoto earthquake

NASA Astrophysics Data System (ADS)

Moore, James D. P.; Yu, Hang; Tang, Chi-Hsien; Wang, Teng; Barbot, Sylvain; Peng, Dongju; Masuti, Sagar; Dauwels, Justin; Hsu, Ya-Ju; Lambert, Valère; Nanjundiah, Priyamvada; Wei, Shengji; Lindsey, Eric; Feng, Lujia; Shibazaki, Bunichiro

2017-04-01

The deformation of mantle and crustal rocks in response to stress plays a crucial role in the distribution of seismic and volcanic hazards, controlling tectonic processes ranging from continental drift to earthquake triggering. However, the spatial variation of these dynamic properties is poorly understood as they are difficult to measure. We exploited the large stress perturbation incurred by the 2016 earthquake sequence in Kumamoto, Japan, to directly image localized and distributed deformation. The earthquakes illuminated distinct regions of low effective viscosity in the lower crust, notably beneath the Mount Aso and Mount Kuju volcanoes, surrounded by larger-scale variations of viscosity across the back-arc. This study demonstrates a new potential for geodesy to directly probe rock rheology in situ across many spatial and temporal scales.

Spatial dynamics of large-scale, multistage crab (Callinectes sapidus) dispersal: Determinants and consequences for recruitment

USGS Publications Warehouse

Etherington, L.L.; Eggleston, D.B.

2003-01-01

We assessed determinants and consequences of multistage dispersal on spatial recruitment of the blue crab, Callinectes sapidus, within the Croatan, Albemarle, Pamlico Estuarine System (CAPES), North Carolina, U.S.A. Large-scale sampling of early juvenile crabs over 4 years indicated that spatial abundance patterns were size-dependent and resulted from primary post-larval dispersal (pre-settlement) and secondary juvenile dispersal (early post-settlement). In general, primary dispersal led to high abundances within more seaward habitats, whereas secondary dispersal (which was relatively consistent) expanded the distribution of juveniles, potentially increasing the estuarine nursery capacity. There were strong relationships between juvenile crab density and specific wind characteristics; however, these patterns were spatially explicit. Various physical processes (e.g., seasonal wind events, timing and magnitude of tropical cyclones) interacted to influence dispersal during multiple stages and determined crab recruitment patterns. Our results suggest that the nursery value of different habitats is highly dependent on the dispersal potential (primary and secondary dispersal) to and from these areas, which is largely determined by the relative position of habitats within the estuarine landscape.

Spatial Patterns Study for Sediments from Lake Michigan

EPA Science Inventory

Accurately understanding the distribution of sediment measurements within large water bodies such as Lake Michigan is critical for modeling and understanding of carbon, nitrogen, silica and phosphorus dynamics. Several water quality models have been formulated and applied to the ...

Domain-Adapted Convolutional Networks for Satellite Image Classification: A Large-Scale Interactive Learning Workflow

DOE PAGES

Lunga, Dalton D.; Yang, Hsiuhan Lexie; Reith, Andrew E.; ...

2018-02-06

Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address themore » negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.« less

Domain-Adapted Convolutional Networks for Satellite Image Classification: A Large-Scale Interactive Learning Workflow

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

Lunga, Dalton D.; Yang, Hsiuhan Lexie; Reith, Andrew E.

Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address themore » negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.« less

Spatial estimation from remotely sensed data via empirical Bayes models

NASA Technical Reports Server (NTRS)

Hill, J. R.; Hinkley, D. V.; Kostal, H.; Morris, C. N.

1984-01-01

Multichannel satellite image data, available as LANDSAT imagery, are recorded as a multivariate time series (four channels, multiple passovers) in two spatial dimensions. The application of parametric empirical Bayes theory to classification of, and estimating the probability of, each crop type at each of a large number of pixels is considered. This theory involves both the probability distribution of imagery data, conditional on crop types, and the prior spatial distribution of crop types. For the latter Markov models indexed by estimable parameters are used. A broad outline of the general theory reveals several questions for further research. Some detailed results are given for the special case of two crop types when only a line transect is analyzed. Finally, the estimation of an underlying continuous process on the lattice is discussed which would be applicable to such quantities as crop yield.

Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

The Effect of Velocity Correlation on the Spatial Evolution of Breakthrough Curves in Heterogeneous Media

NASA Astrophysics Data System (ADS)

Massoudieh, A.; Dentz, M.; Le Borgne, T.

2017-12-01

In heterogeneous media, the velocity distribution and the spatial correlation structure of velocity for solute particles determine the breakthrough curves and how they evolve as one moves away from the solute source. The ability to predict such evolution can help relating the spatio-statistical hydraulic properties of the media to the transport behavior and travel time distributions. While commonly used non-local transport models such as anomalous dispersion and classical continuous time random walk (CTRW) can reproduce breakthrough curve successfully by adjusting the model parameter values, they lack the ability to relate model parameters to the spatio-statistical properties of the media. This in turns limits the transferability of these models. In the research to be presented, we express concentration or flux of solutes as a distribution over their velocity. We then derive an integrodifferential equation that governs the evolution of the particle distribution over velocity at given times and locations for a particle ensemble, based on a presumed velocity correlation structure and an ergodic cross-sectional velocity distribution. This way, the spatial evolution of breakthrough curves away from the source is predicted based on cross-sectional velocity distribution and the connectivity, which is expressed by the velocity transition probability density. The transition probability is specified via a copula function that can help construct a joint distribution with a given correlation and given marginal velocities. Using this approach, we analyze the breakthrough curves depending on the velocity distribution and correlation properties. The model shows how the solute transport behavior evolves from ballistic transport at small spatial scales to Fickian dispersion at large length scales relative to the velocity correlation length.

Auditory spectral versus spatial temporal order judgment: Threshold distribution analysis.

PubMed

Fostick, Leah; Babkoff, Harvey

2017-05-01

Some researchers suggested that one central mechanism is responsible for temporal order judgments (TOJ), within and across sensory channels. This suggestion is supported by findings of similar TOJ thresholds in same modality and cross-modality TOJ tasks. In the present study, we challenge this idea by analyzing and comparing the threshold distributions of the spectral and spatial TOJ tasks. In spectral TOJ, the tones differ in their frequency ("high" and "low") and are delivered either binaurally or monaurally. In spatial (or dichotic) TOJ, the two tones are identical but are presented asynchronously to the two ears and thus differ with respect to which ear received the first tone and which ear received the second tone ("left"/"left"). Although both tasks are regarded as measures of auditory temporal processing, a review of data published in the literature suggests that they trigger different patterns of response. The aim of the current study was to systematically examine spectral and spatial TOJ threshold distributions across a large number of studies. Data are based on 388 participants in 13 spectral TOJ experiments, and 222 participants in 9 spatial TOJ experiments. None of the spatial TOJ distributions deviated significantly from the Gaussian; while all of the spectral TOJ threshold distributions were skewed to the right, with more than half of the participants accurately judging temporal order at very short interstimulus intervals (ISI). The data do not support the hypothesis that 1 central mechanism is responsible for all temporal order judgments. We suggest that different perceptual strategies are employed when performing spectral TOJ than when performing spatial TOJ. We posit that the spectral TOJ paradigm may provide the opportunity for two-tone masking or temporal integration, which is sensitive to the order of the tones and thus provides perceptual cues that may be used to judge temporal order. This possibility should be considered when interpreting spectral TOJ data, especially in the context of comparing different populations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Land cover mapping at sub-pixel scales

NASA Astrophysics Data System (ADS)

Makido, Yasuyo Kato

One of the biggest drawbacks of land cover mapping from remotely sensed images relates to spatial resolution, which determines the level of spatial details depicted in an image. Fine spatial resolution images from satellite sensors such as IKONOS and QuickBird are now available. However, these images are not suitable for large-area studies, since a single image is very small and therefore it is costly for large area studies. Much research has focused on attempting to extract land cover types at sub-pixel scale, and little research has been conducted concerning the spatial allocation of land cover types within a pixel. This study is devoted to the development of new algorithms for predicting land cover distribution using remote sensory imagery at sub-pixel level. The "pixel-swapping" optimization algorithm, which was proposed by Atkinson for predicting sub-pixel land cover distribution, is investigated in this study. Two limitations of this method, the arbitrary spatial range value and the arbitrary exponential model of spatial autocorrelation, are assessed. Various weighting functions, as alternatives to the exponential model, are evaluated in order to derive the optimum weighting function. Two different simulation models were employed to develop spatially autocorrelated binary class maps. In all tested models, Gaussian, Exponential, and IDW, the pixel swapping method improved classification accuracy compared with the initial random allocation of sub-pixels. However the results suggested that equal weight could be used to increase accuracy and sub-pixel spatial autocorrelation instead of using these more complex models of spatial structure. New algorithms for modeling the spatial distribution of multiple land cover classes at sub-pixel scales are developed and evaluated. Three methods are examined: sequential categorical swapping, simultaneous categorical swapping, and simulated annealing. These three methods are applied to classified Landsat ETM+ data that has been resampled to 210 meters. The result suggested that the simultaneous method can be considered as the optimum method in terms of accuracy performance and computation time. The case study employs remote sensing imagery at the following sites: tropical forests in Brazil and temperate multiple land mosaic in East China. Sub-areas for both sites are used to examine how the characteristics of the landscape affect the ability of the optimum technique. Three types of measurement: Moran's I, mean patch size (MPS), and patch size standard deviation (STDEV), are used to characterize the landscape. All results suggested that this technique could increase the classification accuracy more than traditional hard classification. The methods developed in this study can benefit researchers who employ coarse remote sensing imagery but are interested in detailed landscape information. In many cases, the satellite sensor that provides large spatial coverage has insufficient spatial detail to identify landscape patterns. Application of the super-resolution technique described in this dissertation could potentially solve this problem by providing detailed land cover predictions from the coarse resolution satellite sensor imagery.

The effect of radiation pressure on spatial distribution of dust inside H II regions

NASA Astrophysics Data System (ADS)

Ishiki, Shohei; Okamoto, Takashi; Inoue, Akio K.

2018-02-01

We investigate the impact of radiation pressure on spatial dust distribution inside H II regions using one-dimensional radiation hydrodynamic simulations, which include absorption and re-emission of photons by dust. In order to investigate grain-size effects as well, we introduce two additional fluid components describing large and small dust grains in the simulations. Relative velocity between dust and gas strongly depends on the drag force. We include collisional drag force and coulomb drag force. We find that, in a compact H II region, a dust cavity region is formed by radiation pressure. Resulting dust cavity sizes (˜0.2 pc) agree with observational estimates reasonably well. Since dust inside an H II region is strongly charged, relative velocity between dust and gas is mainly determined by the coulomb drag force. Strength of the coulomb drag force is about 2 order of magnitude larger than that of the collisional drag force. In addition, in a cloud of mass 105 M⊙, we find that the radiation pressure changes the grain-size distribution inside H II regions. Since large (0.1 μm) dust grains are accelerated more efficiently than small (0.01 μm) grains, the large-to-small grain mass ratio becomes smaller by an order of magnitude compared with the initial one. Resulting dust-size distributions depend on the luminosity of the radiation source. The large and small grain segregation becomes weaker when we assume stronger radiation source, since dust grain charges become larger under stronger radiation and hence coulomb drag force becomes stronger.

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

PubMed

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

2017-10-01

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

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

PubMed

Wang, Bao-Zhen; Chen, Zhi

2013-01-01

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

Spatio-Temporal Variability of Groundwater Storage in India

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Spatio-temporal variability of groundwater storage in India.

PubMed

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

2017-01-01

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

Open star clusters and Galactic structure

NASA Astrophysics Data System (ADS)

Joshi, Yogesh C.

2018-04-01

In order to understand the Galactic structure, we perform a statistical analysis of the distribution of various cluster parameters based on an almost complete sample of Galactic open clusters yet available. The geometrical and physical characteristics of a large number of open clusters given in the MWSC catalogue are used to study the spatial distribution of clusters in the Galaxy and determine the scale height, solar offset, local mass density and distribution of reddening material in the solar neighbourhood. We also explored the mass-radius and mass-age relations in the Galactic open star clusters. We find that the estimated parameters of the Galactic disk are largely influenced by the choice of cluster sample.

Temporal acceleration of spatially distributed kinetic Monte Carlo simulations

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

Chatterjee, Abhijit; Vlachos, Dionisios G.

The computational intensity of kinetic Monte Carlo (KMC) simulation is a major impediment in simulating large length and time scales. In recent work, an approximate method for KMC simulation of spatially uniform systems, termed the binomial {tau}-leap method, was introduced [A. Chatterjee, D.G. Vlachos, M.A. Katsoulakis, Binomial distribution based {tau}-leap accelerated stochastic simulation, J. Chem. Phys. 122 (2005) 024112], where molecular bundles instead of individual processes are executed over coarse-grained time increments. This temporal coarse-graining can lead to significant computational savings but its generalization to spatially lattice KMC simulation has not been realized yet. Here we extend the binomial {tau}-leapmore » method to lattice KMC simulations by combining it with spatially adaptive coarse-graining. Absolute stability and computational speed-up analyses for spatial systems along with simulations provide insights into the conditions where accuracy and substantial acceleration of the new spatio-temporal coarse-graining method are ensured. Model systems demonstrate that the r-time increment criterion of Chatterjee et al. obeys the absolute stability limit for values of r up to near 1.« less

Large Fluctuations for Spatial Diffusion of Cold Atoms

NASA Astrophysics Data System (ADS)

Aghion, Erez; Kessler, David A.; Barkai, Eli

2017-06-01

We use a new approach to study the large fluctuations of a heavy-tailed system, where the standard large-deviations principle does not apply. Large-deviations theory deals with tails of probability distributions and the rare events of random processes, for example, spreading packets of particles. Mathematically, it concerns the exponential falloff of the density of thin-tailed systems. Here we investigate the spatial density Pt(x ) of laser-cooled atoms, where at intermediate length scales the shape is fat tailed. We focus on the rare events beyond this range, which dominate important statistical properties of the system. Through a novel friction mechanism induced by the laser fields, the density is explored with the recently proposed non-normalized infinite-covariant density approach. The small and large fluctuations give rise to a bifractal nature of the spreading packet. We derive general relations which extend our theory to a class of systems with multifractal moments.

Atlas of the global distribution of atmospheric heating during the global weather experiment

NASA Technical Reports Server (NTRS)

Schaack, Todd K.; Johnson, Donald R.

1991-01-01

Global distributions of atmospheric heating for the annual cycle of the Global Weather Experiment are estimated from the European Centre for Medium-Range Weather Forecasts (ECMWF) Level 3b data set. Distributions of monthly, seasonally, and annually averaged heating are presented for isentropic and isobaric layers within the troposphere and for the troposphere as a whole. The distributions depict a large-scale structure of atmospheric heating that appears spatially and temporally consistent with known features of the global circulation and the seasonal evolution.

Understanding the spectral hardenings and radial distribution of Galactic cosmic rays and Fermi diffuse γ rays with spatially-dependent propagation

NASA Astrophysics Data System (ADS)

Guo, Yi-Qing; Yuan, Qiang

2018-03-01

Recent direct measurements of Galactic cosmic ray spectra by balloon/space-borne detectors reveal spectral hardenings of all major nucleus species at rigidities of a few hundred GV. The all-sky diffuse γ -ray emissions measured by the Fermi Large Area Telescope also show spatial variations of the intensities and spectral indices of cosmic rays. These new observations challenge the traditional simple acceleration and/or propagation scenario of Galactic cosmic rays. In this work, we propose a spatially dependent diffusion scenario to explain all these phenomena. The diffusion coefficient is assumed to be anticorrelated with the source distribution, which is a natural expectation from the charged particle transportation in a turbulent magnetic field. The spatially dependent diffusion model also gives a lower level of anisotropies of cosmic rays, which are consistent with observations by underground muons and air shower experiments. The spectral variations of cosmic rays across the Galaxy can be properly reproduced by this model.

Contaminant transport in wetland flows with bulk degradation and bed absorption

NASA Astrophysics Data System (ADS)

Wang, Ping; Chen, G. Q.

2017-09-01

Ecological degradation and absorption are ubiquitous and exert considerable influence on the contaminant transport in natural and constructed wetland flows. It creates an increased demand on models to accurately characterize the spatial concentration distribution of the transport process. This work extends a method of spatial concentration moments by considering the non-uniform longitudinal solute displacements along the vertical direction, and analytically determines the spatial concentration distribution in the very initial stage since source release with effects of bulk degradation and bed absorption. The present method is demonstrated to bear a more accurate prediction especially in the initial stage through convergence analysis of Hermite polynomials. Results reveal that contaminant cloud shows to be more contracted and reformed by bed absorption with increasing damping factor of wetland flows. Tremendous vertical concentration variation especially in the downstream of the contaminant cloud remains great even at asymptotic large times. Spatial concentration evolution by the extended method other than the mean by previous studies is potential for various implements associated with contaminant transport with strict environmental standards.

Effect of a fish stock's demographic structure on offspring survival and sensitivity to climate.

PubMed

Stige, Leif Christian; Yaragina, Natalia A; Langangen, Øystein; Bogstad, Bjarte; Stenseth, Nils Chr; Ottersen, Geir

2017-02-07

Commercial fishing generally removes large and old individuals from fish stocks, reducing mean age and age diversity among spawners. It is feared that these demographic changes lead to lower and more variable recruitment to the stocks. A key proposed pathway is that juvenation and reduced size distribution causes reduced ranges in spawning period, spawning location, and egg buoyancy; this is proposed to lead to reduced spatial distribution of fish eggs and larvae, more homogeneous ambient environmental conditions within each year-class, and reduced buffering against negative environmental influences. However, few, if any, studies have confirmed a causal link from spawning stock demographic structure through egg and larval distribution to year class strength at recruitment. We here show that high mean age and size in the spawning stock of Barents Sea cod (Gadus morhua) is positively associated with high abundance and wide spatiotemporal distribution of cod eggs. We find, however, no support for the hypothesis that a wide egg distribution leads to higher recruitment or a weaker recruitment-temperature correlation. These results are based on statistical analyses of a spatially resolved data set on cod eggs covering a period (1959-1993) with large changes in biomass and demographic structure of spawners. The analyses also account for significant effects of spawning stock biomass and a liver condition index on egg abundance and distribution. Our results suggest that the buffering effect of a geographically wide distribution of eggs and larvae on fish recruitment may be insignificant compared with other impacts.

Development of an Asset Value Map for Disaster Risk Assessment in China by Spatial Disaggregation Using Ancillary Remote Sensing Data.

PubMed

Wu, Jidong; Li, Ying; Li, Ning; Shi, Peijun

2018-01-01

The extent of economic losses due to a natural hazard and disaster depends largely on the spatial distribution of asset values in relation to the hazard intensity distribution within the affected area. Given that statistical data on asset value are collected by administrative units in China, generating spatially explicit asset exposure maps remains a key challenge for rapid postdisaster economic loss assessment. The goal of this study is to introduce a top-down (or downscaling) approach to disaggregate administrative-unit level asset value to grid-cell level. To do so, finding the highly correlated "surrogate" indicators is the key. A combination of three data sets-nighttime light grid, LandScan population grid, and road density grid, is used as ancillary asset density distribution information for spatializing the asset value. As a result, a high spatial resolution asset value map of China for 2015 is generated. The spatial data set contains aggregated economic value at risk at 30 arc-second spatial resolution. Accuracy of the spatial disaggregation reflects redistribution errors introduced by the disaggregation process as well as errors from the original ancillary data sets. The overall accuracy of the results proves to be promising. The example of using the developed disaggregated asset value map in exposure assessment of watersheds demonstrates that the data set offers immense analytical flexibility for overlay analysis according to the hazard extent. This product will help current efforts to analyze spatial characteristics of exposure and to uncover the contributions of both physical and social drivers of natural hazard and disaster across space and time. © 2017 Society for Risk Analysis.

North Atlantic Tropical Cyclone Precipitation and Climate Interactions Using a High-Resolution Dataset for the Eastern United States, 1948-2015.

NASA Astrophysics Data System (ADS)

Bregy, J. C.; Maxwell, J. T.; Robeson, S. M.

2017-12-01

Tropical cyclone (TC) impacts are typically concentrated along the coast, yet some TC hazards have wider spatial distributions and affect inland regions. For example, large volumes of TC precipitation (TCP) can cause severe inland flooding, initiate slope failure, and create large sinkholes. Previous studies show that TCP contributes substantially to seasonal precipitation budgets in the eastern United States. However, present knowledge of TCP climatology in the US is limited by the spatial coverage of weather stations. Here we develop a new high resolution (0.25°x0.25°) TCP climatology using HURDAT2 and CPC US Unified Precipitation data (1948-2015). From June to November (JJASON), maximum total TCP for the study period ranges from 2200 to 3800 mm along much of the coast and decreases inland. Likewise, spatial patterns of TCP contribution to total JJASON precipitation largely mirror those of total TCP, with maxima (6-8%) located in coastal Texas and North Carolina. Similar spatial patterns are seen in the mean JJASON TCP and mean TCP contribution over the study period, with maxima extending beyond coastal Texas and North Carolina. JJASON TCP (total, mean, and contribution) was correlated with mean annual JJASON values for the Bermuda High Index (BHI), El Niño-Southern Oscillation combined Niño3.4/Southern Oscillation Index (ENSO-BEST), and North Atlantic Oscillation (NAO). Correlations between climate indices and JJASON TCP show the degree to which BHI, ENSO-BEST, and NAO influence spatiotemporal changes in TCP. Of the three indices, the BHI had the strongest and most spatially consistent correlation with TCP, with significant correlations in the interior of the southeast. These results indicate a strong regional relationship between the North Atlantic Subtropical High (NASH; represented by the BHI) and regional TCP distribution. TCP distribution depends on TC track direction, and is therefore connected to the NASH, which acts as a steering mechanism for TCs. Our derived high resolution TCP climatology further aids our understanding of TC-climate interactions. Moreover, it can be used to understand hazards associated with TCs, serving as an invaluable tool in hazard mitigation efforts.

Effects of habitat fragmentation on passerine birds breeding in Intermountain shrubsteppe

USGS Publications Warehouse

Knick, S.T.; Rotenberry, J.T.

2002-01-01

Habitat fragmentation and loss strongly influence the distribution and abundance of passerine birds breeding in Intermountain shrubsteppe. Wildfires, human activities, and change in vegetation communities often are synergistic in these systems and can result in radical conversion from shrubland to grasslands dominated by exotic annuals at large temporal and spatial scales from which recovery to native conditions is unlikely. As a result, populations of 5 of the 12 species in our review of Intermountain shrubsteppe birds are undergoing significant declines; 5 species are listed as at-risk or as candidates for protection in at least one state. The process by which fragmentation affects bird distributions in these habitats remains unknown because most research has emphasized the detection of population trends and patterns of habitat associations at relatively large spatial scales. Our research indicates that the distribution of shrubland-obligate species, such as Brewer's Sparrows (Spizella breweri), Sage Sparrows (Amphispiza belli), and Sage Thrashers (Oreoscoptes montanus), was highly sensitive to fragmentation of shrublands at spatial scales larger than individual home ranges. In contrast, the underlying mechanisms for both habitat change and bird population dynamics may operate independently of habitat boundaries. We propose alternative, but not necessarily exclusive, mechanisms to explain the relationship between habitat fragmentation and bird distribution and abundance. Fragmentation might influence productivity through differences in breeding density, nesting success, or predation. However, local and landscape variables were not significant determinants either of success, number fledged, or probability of predation or parasitism (although our tests had relatively low statistical power). Alternatively, relative absence of natal philopatry and redistribution by individuals among habitats following fledging or post-migration could account for the pattern of distribution and abundance. Thus, boundary dynamics may be important in determining the distribution of shrubland-obligate species but insignificant relative to the mechanisms causing the pattern of habitat and bird distribution. Because of the dichotomy in responses, Intermountain shrubsteppe systems present a unique challenge in understanding how landscape composition, configuration, and change influence bird population dynamics.

Optical beam forming techniques for phased array antennas

NASA Technical Reports Server (NTRS)

Wu, Te-Kao; Chandler, C.

1993-01-01

Conventional phased array antennas using waveguide or coax for signal distribution are impractical for large scale implementation on satellites or spacecraft because they exhibit prohibitively large system size, heavy weight, high attenuation loss, limited bandwidth, sensitivity to electromagnetic interference (EMI) temperature drifts and phase instability. However, optical beam forming systems are smaller, lighter, and more flexible. Three optical beam forming techniques are identified as applicable to large spaceborne phased array antennas. They are (1) the optical fiber replacement of conventional RF phased array distribution and control components, (2) spatial beam forming, and (3) optical beam splitting with integrated quasi-optical components. The optical fiber replacement and the spatial beam forming approaches were pursued by many organizations. Two new optical beam forming architectures are presented. Both architectures involve monolithic integration of the antenna radiating elements with quasi-optical grid detector arrays. The advantages of the grid detector array in the optical process are the higher power handling capability and the dynamic range. One architecture involves a modified version of the original spatial beam forming approach. The basic difference is the spatial light modulator (SLM) device for controlling the aperture field distribution. The original liquid crystal light valve SLM is replaced by an optical shuffling SLM, which was demonstrated for the 'smart pixel' technology. The advantages are the capability of generating the agile beams of a phased array antenna and to provide simultaneous transmit and receive functions. The second architecture considered is the optical beam splitting approach. This architecture involves an alternative amplitude control for each antenna element with an optical beam power divider comprised of mirrors and beam splitters. It also implements the quasi-optical grid phase shifter for phase control and grid amplifier for RF power. The advantages are no SLM is required for this approach, and the complete antenna system is capable of full monolithic integration.

Smoothing effect for spatially distributed renewable resources and its impact on power grid robustness.

PubMed

Nagata, Motoki; Hirata, Yoshito; Fujiwara, Naoya; Tanaka, Gouhei; Suzuki, Hideyuki; Aihara, Kazuyuki

2017-03-01

In this paper, we show that spatial correlation of renewable energy outputs greatly influences the robustness of the power grids against large fluctuations of the effective power. First, we evaluate the spatial correlation among renewable energy outputs. We find that the spatial correlation of renewable energy outputs depends on the locations, while the influence of the spatial correlation of renewable energy outputs on power grids is not well known. Thus, second, by employing the topology of the power grid in eastern Japan, we analyze the robustness of the power grid with spatial correlation of renewable energy outputs. The analysis is performed by using a realistic differential-algebraic equations model. The results show that the spatial correlation of the energy resources strongly degrades the robustness of the power grid. Our results suggest that we should consider the spatial correlation of the renewable energy outputs when estimating the stability of power grids.

Earthquakes induced by fluid injection and explosion

USGS Publications Warehouse

Healy, J.H.; Hamilton, R.M.; Raleigh, C.B.

1970-01-01

Earthquakes generated by fluid injection near Denver, Colorado, are compared with earthquakes triggered by nuclear explosion at the Nevada Test Site. Spatial distributions of the earthquakes in both cases are compatible with the hypothesis that variation of fluid pressure in preexisting fractures controls the time distribution of the seismic events in an "aftershock" sequence. We suggest that the fluid pressure changes may also control the distribution in time and space of natural aftershock sequences and of earthquakes that have been reported near large reservoirs. ?? 1970.

Fruit availability drives the distribution of a folivorous-frugivorous primate within a large forest remnant.

PubMed

Camaratta, Danielle; Chaves, Óscar M; Bicca-Marques, Júlio César

2017-03-01

Understanding the ecological factors that influence the presence, abundance, and distribution of species within their habitats is critical for ensuring their long-term conservation. In the case of primary consumers, such as most primates, the availability and richness of plant foods are considered key drivers of population density at these variables influence the spatial distribution of social units within a finer, habitat patch level scale. We tested the hypothesis that the spatiotemporal availability and richness of plant foods, drive the spatial distribution of brown howler monkeys (Alouatta guariba clamitans) at a fine spatial scale. We established five line transects (2.6-4.3 km long) to census the population of brown howlers in Morro São Pedro, a 1,200 ha Atlantic forest remnant in southern Brazil, every 2 weeks from January to June 2015. We used data from tree inventories performed in sighting and control plots, and phenological surveys of 17 top food tree species to estimate bi-weekly food availability. We recorded a total of 95 sightings. The number of sightings per sampling period ranged from 2 to 12. The availability of fruit (ripe and unripe) was higher in sighting than in control plots, whereas leaf availability and the richness of food tree species was similar. We conclude that the spatial distribution of fruiting trees and the availability of fruit drive the pattern of habitat use, and spacing of brown howler groups in Morro São Pedro. © 2017 Wiley Periodicals, Inc.

MAPPING THE RELEASE OF VOLATILES IN THE INNER COMAE OF COMETS C/2012 F6 (LEMMON) AND C/2012 S1 (ISON) USING THE ATACAMA LARGE MILLIMETER/SUBMILLIMETER ARRAY

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

Cordiner, M. A.; Milam, S. N.; Mumma, M. J.

2014-09-01

Results are presented from the first cometary observations using the Atacama Large Millimeter/Submillimeter Array (ALMA), including measurements of the spatially resolved distributions of HCN, HNC, H{sub 2}CO, and dust within the comae of two comets: C/2012 F6 (Lemmon) and C/2012 S1 (ISON), observed at heliocentric distances of 1.5 AU and 0.54 AU, respectively. These observations (with angular resolution ≈0.''5), reveal an unprecedented level of detail in the distributions of these fundamental cometary molecules, and demonstrate the power of ALMA for quantitative measurements of the distributions of molecules and dust in the inner comae of typical bright comets. In both comets, HCN ismore » found to originate from (or within a few hundred kilometers of) the nucleus, with a spatial distribution largely consistent with spherically symmetric, uniform outflow. By contrast, the HNC distributions are clumpy and asymmetrical, with peaks at cometocentric radii ∼500-1000 km, consistent with release of HNC in collimated outflow(s). Compared to HCN, the H{sub 2}CO distribution in comet Lemmon is very extended. The interferometric visibility amplitudes are consistent with coma production of H{sub 2}CO and HNC from unidentified precursor material(s) in both comets. Adopting a Haser model, the H{sub 2}CO parent scale length is found to be a few thousand kilometers in Lemmon and only a few hundred kilometers in ISON, consistent with the destruction of the precursor by photolysis or thermal degradation at a rate that scales in proportion to the solar radiation flux.« less

Atomic-level spatial distributions of dopants on silicon surfaces: toward a microscopic understanding of surface chemical reactivity

NASA Astrophysics Data System (ADS)

Hamers, Robert J.; Wang, Yajun; Shan, Jun

1996-11-01

We have investigated the interaction of phosphine (PH 3) and diborane (B 2H 6) with the Si(001) surface using scanning tunneling microscopy, infrared spectroscopy, and ab initio molecular orbital calculations. Experiment and theory show that the formation of PSi heterodimers is energetically favorable compared with formation of PP dimers. The stability of the heterodimers arises from a large strain energy associated with formation of PP dimers. At moderate P coverages, the formation of PSi heterodimers leaves the surface with few locations where there are two adjacent reactive sites. This in turn modifies the chemical reactivity toward species such as PH 3, which require only one site to adsorb but require two adjacent sites to dissociate. Boron on Si(001) strongly segregates into localized regions of high boron concentration, separated by large regions of clean Si. This leads to a spatially-modulated chemical reactivity which during subsequent growth by chemical vapor deposition (CVD) leads to formation of a rough surface. The implications of the atomic-level spatial distribution of dopants on the rates and mechanisms of CVD growth processes are discussed.

Spatial distribution of allergenic pollen through a large metropolitan area.

PubMed

Werchan, Barbora; Werchan, Matthias; Mücke, Hans-Guido; Gauger, Ulrich; Simoleit, Anke; Zuberbier, Torsten; Bergmann, Karl-Christian

2017-04-01

For nearly a decade, the majority of the world's population has been living in cities, including a considerable percentage of people suffering from pollen allergy. The increasing concentration of people in cities results in larger populations being exposed to allergenic pollen at the same time. There is almost no information about spatial distribution of pollen within cities as well as a lack of information about the possible impact to human health. To obtain this increasing need for pollen exposure studies on an intra-urban scale, a novelty screening network of 14 weekly changed pollen traps was established within a large metropolitan area-Berlin, Germany. Gravimetric pollen traps were placed at a uniform street-level height from March until October 2014. Three important allergenic pollen types for Central Europe-birch (Betula), grasses (Poaceae), and mugwort (Artemisia)-were monitored. Remarkable spatial and temporal variations of pollen sedimentation within the city and the influences by urban local sources are shown. The observed differences between the trap with the overall highest and the trap with the overall lowest amount of pollen sedimentation were in the case of birch pollen 245%, grass pollen 306%, and mugwort pollen 1962%. Differences of this magnitude can probably lead to different health impacts on allergy sufferers in one city. Therefore, pollen should be monitored preferably in two or more appropriate locations within large cities and as a part of natural air quality regulations.

On the Fidelity of Semi-distributed Hydrologic Model Simulations for Large Scale Catchment Applications

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.; Lakshmi, V.

2017-12-01

Application of semi-distributed hydrologic modeling frameworks is a viable alternative to fully distributed hyper-resolution hydrologic models due to computational efficiency and resolving fine-scale spatial structure of hydrologic fluxes and states. However, fidelity of semi-distributed model simulations is impacted by (1) formulation of hydrologic response units (HRUs), and (2) aggregation of catchment properties for formulating simulation elements. Here, we evaluate the performance of a recently developed Soil Moisture and Runoff simulation Toolkit (SMART) for large catchment scale simulations. In SMART, topologically connected HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are equivalent cross sections (ECS) representative of a hillslope in first order sub-basins. Earlier investigations have shown that formulation of ECSs at the scale of a first order sub-basin reduces computational time significantly without compromising simulation accuracy. However, the implementation of this approach has not been fully explored for catchment scale simulations. To assess SMART performance, we set-up the model over the Little Washita watershed in Oklahoma. Model evaluations using in-situ soil moisture observations show satisfactory model performance. In addition, we evaluated the performance of a number of soil moisture disaggregation schemes recently developed to provide spatially explicit soil moisture outputs at fine scale resolution. Our results illustrate that the statistical disaggregation scheme performs significantly better than the methods based on topographic data. Future work is focused on assessing the performance of SMART using remotely sensed soil moisture observations using spatially based model evaluation metrics.

Rupture Propagation for Stochastic Fault Models

NASA Astrophysics Data System (ADS)

Favreau, P.; Lavallee, D.; Archuleta, R.

2003-12-01

The inversion of strong motion data of large earhquakes give the spatial distribution of pre-stress on the ruptured faults and it can be partially reproduced by stochastic models, but a fundamental question remains: how rupture propagates, constrained by the presence of spatial heterogeneity? For this purpose we investigate how the underlying random variables, that control the pre-stress spatial variability, condition the propagation of the rupture. Two stochastic models of prestress distributions are considered, respectively based on Cauchy and Gaussian random variables. The parameters of the two stochastic models have values corresponding to the slip distribution of the 1979 Imperial Valley earthquake. We use a finite difference code to simulate the spontaneous propagation of shear rupture on a flat fault in a 3D continuum elastic body. The friction law is the slip dependent friction law. The simulations show that the propagation of the rupture front is more complex, incoherent or snake-like for a prestress distribution based on Cauchy random variables. This may be related to the presence of a higher number of asperities in this case. These simulations suggest that directivity is stronger in the Cauchy scenario, compared to the smoother rupture of the Gauss scenario.

Nonmydriatic fluorescence-based quantitative imaging of human macular pigment distributions

NASA Astrophysics Data System (ADS)

Sharifzadeh, Mohsen; Bernstein, Paul S.; Gellermann, Werner

2006-10-01

We have developed a CCD-camera-based nonmydriatic instrument that detects fluorescence from retinal lipofuscin chromophores ("autofluorescence") as a means to indirectly quantify and spatially image the distribution of macular pigment (MP). The lipofuscin fluorescence intensity is reduced at all retinal locations containing MP, since MP has a competing absorption in the blue-green wavelength region. Projecting a large diameter, 488 nm excitation spot onto the retina, centered on the fovea, but extending into the macular periphery, and comparing lipofuscin fluorescence intensities outside and inside the foveal area, it is possible to spatially map out the distribution of MP. Spectrally selective detection of the lipofuscin fluorescence reveals an important wavelength dependence of the obtainable image contrast and deduced MP optical density levels, showing that it is important to block out interfering fluorescence contributions in the detection setup originating from ocular media such as the lens. Measuring 70 healthy human volunteer subjects with no ocular pathologies, we find widely varying spatial extent of MP, distinctly differing distribution patterns of MP, and strongly differing absolute MP levels among individuals. Our population study suggests that MP imaging based on lipofuscin fluorescence is useful as a relatively simple, objective, and quantitative noninvasive optical technique suitable to rapidly screen MP levels and distributions in healthy humans with undilated pupils.

Large-Scale Geographic Variation in Distribution and Abundance of Australian Deep-Water Kelp Forests

PubMed Central

Marzinelli, Ezequiel M.; Williams, Stefan B.; Babcock, Russell C.; Barrett, Neville S.; Johnson, Craig R.; Jordan, Alan; Kendrick, Gary A.; Pizarro, Oscar R.; Smale, Dan A.; Steinberg, Peter D.

2015-01-01

Despite the significance of marine habitat-forming organisms, little is known about their large-scale distribution and abundance in deeper waters, where they are difficult to access. Such information is necessary to develop sound conservation and management strategies. Kelps are main habitat-formers in temperate reefs worldwide; however, these habitats are highly sensitive to environmental change. The kelp Ecklonia radiate is the major habitat-forming organism on subtidal reefs in temperate Australia. Here, we provide large-scale ecological data encompassing the latitudinal distribution along the continent of these kelp forests, which is a necessary first step towards quantitative inferences about the effects of climatic change and other stressors on these valuable habitats. We used the Autonomous Underwater Vehicle (AUV) facility of Australia’s Integrated Marine Observing System (IMOS) to survey 157,000 m2 of seabed, of which ca 13,000 m2 were used to quantify kelp covers at multiple spatial scales (10–100 m to 100–1,000 km) and depths (15–60 m) across several regions ca 2–6° latitude apart along the East and West coast of Australia. We investigated the large-scale geographic variation in distribution and abundance of deep-water kelp (>15 m depth) and their relationships with physical variables. Kelp cover generally increased with latitude despite great variability at smaller spatial scales. Maximum depth of kelp occurrence was 40–50 m. Kelp latitudinal distribution along the continent was most strongly related to water temperature and substratum availability. This extensive survey data, coupled with ongoing AUV missions, will allow for the detection of long-term shifts in the distribution and abundance of habitat-forming kelp and the organisms they support on a continental scale, and provide information necessary for successful implementation and management of conservation reserves. PMID:25693066

The cosmological principle is not in the sky

NASA Astrophysics Data System (ADS)

Park, Chan-Gyung; Hyun, Hwasu; Noh, Hyerim; Hwang, Jai-chan

2017-08-01

The homogeneity of matter distribution at large scales, known as the cosmological principle, is a central assumption in the standard cosmological model. The case is testable though, thus no longer needs to be a principle. Here we perform a test for spatial homogeneity using the Sloan Digital Sky Survey Luminous Red Galaxies (LRG) sample by counting galaxies within a specified volume with the radius scale varying up to 300 h-1 Mpc. We directly confront the large-scale structure data with the definition of spatial homogeneity by comparing the averages and dispersions of galaxy number counts with allowed ranges of the random distribution with homogeneity. The LRG sample shows significantly larger dispersions of number counts than the random catalogues up to 300 h-1 Mpc scale, and even the average is located far outside the range allowed in the random distribution; the deviations are statistically impossible to be realized in the random distribution. This implies that the cosmological principle does not hold even at such large scales. The same analysis of mock galaxies derived from the N-body simulation, however, suggests that the LRG sample is consistent with the current paradigm of cosmology, thus the simulation is also not homogeneous in that scale. We conclude that the cosmological principle is neither in the observed sky nor demanded to be there by the standard cosmological world model. This reveals the nature of the cosmological principle adopted in the modern cosmology paradigm, and opens a new field of research in theoretical cosmology.

Large tree diameter distribution modelling using sparse airborne laser scanning data in a subtropical forest in Nepal

NASA Astrophysics Data System (ADS)

Rana, Parvez; Vauhkonen, Jari; Junttila, Virpi; Hou, Zhengyang; Gautam, Basanta; Cawkwell, Fiona; Tokola, Timo

2017-12-01

Large-diameter trees (taking DBH > 30 cm to define large trees) dominate the dynamics, function and structure of a forest ecosystem. The aim here was to employ sparse airborne laser scanning (ALS) data with a mean point density of 0.8 m-2 and the non-parametric k-most similar neighbour (k-MSN) to predict tree diameter at breast height (DBH) distributions in a subtropical forest in southern Nepal. The specific objectives were: (1) to evaluate the accuracy of the large-tree fraction of the diameter distribution; and (2) to assess the effect of the number of training areas (sample size, n) on the accuracy of the predicted tree diameter distribution. Comparison of the predicted distributions with empirical ones indicated that the large tree diameter distribution can be derived in a mixed species forest with a RMSE% of 66% and a bias% of -1.33%. It was also feasible to downsize the sample size without losing the interpretability capacity of the model. For large-diameter trees, even a reduction of half of the training plots (n = 250), giving a marginal increase in the RMSE% (1.12-1.97%) was reported compared with the original training plots (n = 500). To be consistent with these outcomes, the sample areas should capture the entire range of spatial and feature variability in order to reduce the occurrence of error.

Using spatial patterns in illegal wildlife uses to reveal connections between subsistence hunting and trade.

PubMed

Sánchez-Mercado, Ada; Asmüssen, Marianne; Rodríguez-Clark, Kathryn M; Rodríguez, Jon Paul; Jedrzejewski, Wlodzimierz

2016-12-01

Although most often considered independently, subsistence hunting, domestic trade, and international trade as components of illegal wildlife use (IWU) may be spatially correlated. Understanding how and where subsistence and commercial uses may co-occur has important implications for the design and implementation of effective conservation actions. We analyzed patterns in the joint geographical distribution of illegal commercial and subsistence use of multiple wildlife species in Venezuela and evaluated whether available data were sufficient to provide accurate estimates of the magnitude, scope, and detectability of IWU. We compiled records of illegal subsistence hunting and trade from several sources and fitted a random-forest classification model to predict the spatial distribution of IWUs. From 1969 to 2014, 404 species and 8,340,921 specimens were involved in IWU, for a mean extraction rate of 185,354 individuals/year. Birds were the most speciose group involved (248 spp.), but reptiles had the highest extraction rates (126,414 individuals/year vs. 3,133 individuals/year for birds). Eighty-eight percent of international trade records spatially overlapped with domestic trade, especially in the north and along the coast but also in western inland areas. The distribution of domestic trade was broadly distributed along roads, suggesting that domestic trade does not depend on large markets in cities. Seventeen percent of domestic trade records overlapped with subsistence hunting, but the spatial distribution of this overlap covered a much larger area than between commercial uses. Domestic trade seems to respond to demand from rural more than urban communities. Our approach will be useful for understanding how IWU works at national scales in other parts of the world. © 2016 Society for Conservation Biology.

Spatial Variability of CCN Sized Aerosol Particles

NASA Astrophysics Data System (ADS)

Asmi, A.; Väänänen, R.

2014-12-01

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

Imaging the distribution of transient viscosity after the 2016 Mw 7.1 Kumamoto earthquake.

PubMed

Moore, James D P; Yu, Hang; Tang, Chi-Hsien; Wang, Teng; Barbot, Sylvain; Peng, Dongju; Masuti, Sagar; Dauwels, Justin; Hsu, Ya-Ju; Lambert, Valère; Nanjundiah, Priyamvada; Wei, Shengji; Lindsey, Eric; Feng, Lujia; Shibazaki, Bunichiro

2017-04-14

The deformation of mantle and crustal rocks in response to stress plays a crucial role in the distribution of seismic and volcanic hazards, controlling tectonic processes ranging from continental drift to earthquake triggering. However, the spatial variation of these dynamic properties is poorly understood as they are difficult to measure. We exploited the large stress perturbation incurred by the 2016 earthquake sequence in Kumamoto, Japan, to directly image localized and distributed deformation. The earthquakes illuminated distinct regions of low effective viscosity in the lower crust, notably beneath the Mount Aso and Mount Kuju volcanoes, surrounded by larger-scale variations of viscosity across the back-arc. This study demonstrates a new potential for geodesy to directly probe rock rheology in situ across many spatial and temporal scales. Copyright © 2017, American Association for the Advancement of Science.

The Spatial Scaling of Global Rainfall Extremes

NASA Astrophysics Data System (ADS)

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.

Spatial and temporal distributions of benthic green macroalgae in Yaquina bay, Oregon

EPA Science Inventory

Coastal estuaries of Oregon, USA, typically support relatively large accumulations of benthic green macroalgae (BGM) during the summer/early fall growing season. This raises questions regarding possible (positive and negative) effects on eelgrass and benthic epifauna and infauna...

EnviroAtlas Cyanobacteria Assessment Network (CyAN) Dashboard: A Tool for Data Visualization and Exploratory Analysis

EPA Science Inventory

Economic, health, and environmental impacts of cyanobacteria and associated harmful algal blooms are increasingly recognized by policymakers, managers, and scientific researchers. However, spatially-distributed, long-term data on cyanobacteria blooms are largely unavailable. The ...

Scheduling policies of intelligent sensors and sensor/actuators in flexible structures

NASA Astrophysics Data System (ADS)

Demetriou, Michael A.; Potami, Raffaele

2006-03-01

In this note, we revisit the problem of actuator/sensor placement in large civil infrastructures and flexible space structures within the context of spatial robustness. The positioning of these devices becomes more important in systems employing wireless sensor and actuator networks (WSAN) for improved control performance and for rapid failure detection. The ability of the sensing and actuating devices to possess the property of spatial robustness results in reduced control energy and therefore the spatial distribution of disturbances is integrated into the location optimization measures. In our studies, the structure under consideration is a flexible plate clamped at all sides. First, we consider the case of sensor placement and the optimization scheme attempts to produce those locations that minimize the effects of the spatial distribution of disturbances on the state estimation error; thus the sensor locations produce state estimators with minimized disturbance-to-error transfer function norms. A two-stage optimization procedure is employed whereby one first considers the open loop system and the spatial distribution of disturbances is found that produces the maximal effects on the entire open loop state. Once this "worst" spatial distribution of disturbances is found, the optimization scheme subsequently finds the locations that produce state estimators with minimum transfer function norms. In the second part, we consider the collocated actuator/sensor pairs and the optimization scheme produces those locations that result in compensators with the smallest norms of the disturbance-to-state transfer functions. Going a step further, an intelligent control scheme is presented which, at each time interval, activates a subset of the actuator/sensor pairs in order provide robustness against spatiotemporally moving disturbances and minimize power consumption by keeping some sensor/actuators in sleep mode.

A nearest-neighbor imputation approach to mapping tree species over large areas using forest inventory plots and moderate resolution raster data

Treesearch

B. Tyler Wilson; Andrew J. Lister; Rachel I. Riemann

2012-01-01

The paper describes an efficient approach for mapping multiple individual tree species over large spatial domains. The method integrates vegetation phenology derived from MODIS imagery and raster data describing relevant environmental parameters with extensive field plot data of tree species basal area to create maps of tree species abundance and distribution at a 250-...

Spatial computation of intratumoral T cells correlates with survival of patients with pancreatic cancer.

PubMed

Carstens, Julienne L; Correa de Sampaio, Pedro; Yang, Dalu; Barua, Souptik; Wang, Huamin; Rao, Arvind; Allison, James P; LeBleu, Valerie S; Kalluri, Raghu

2017-04-27

The exact nature and dynamics of pancreatic ductal adenocarcinoma (PDAC) immune composition remains largely unknown. Desmoplasia is suggested to polarize PDAC immunity. Therefore, a comprehensive evaluation of the composition and distribution of desmoplastic elements and T-cell infiltration is necessary to delineate their roles. Here we develop a novel computational imaging technology for the simultaneous evaluation of eight distinct markers, allowing for spatial analysis of distinct populations within the same section. We report a heterogeneous population of infiltrating T lymphocytes. Spatial distribution of cytotoxic T cells in proximity to cancer cells correlates with increased overall patient survival. Collagen-I and αSMA + fibroblasts do not correlate with paucity in T-cell accumulation, suggesting that PDAC desmoplasia may not be a simple physical barrier. Further exploration of this technology may improve our understanding of how specific stromal composition could impact T-cell activity, with potential impact on the optimization of immune-modulatory therapies.

Carrying capacity in a heterogeneous environment with habitat connectivity.

PubMed

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

2017-09-01

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

Combined use of remote sensing and continuous monitoring to analyse the variability of suspended-sediment concentrations in San Francisco Bay, California

USGS Publications Warehouse

Ruhl, C.A.; Schoellhamer, D.H.; Stumpf, R.P.; Lindsay, C.L.

2001-01-01

Analysis of suspended-sediment concentration data in San Francisco Bay is complicated by spatial and temporal variability. In situ optical backscatterance sensors provide continuous suspended-sediment concentration data, but inaccessibility, vandalism, and cost limit the number of potential monitoring stations. Satellite imagery reveals the spatial distribution of surficial-suspended sediment concentrations in the Bay; however, temporal resolution is poor. Analysis of the in situ sensor data in conjunction with the satellite reflectance data shows the effects of physical processes on both the spatial and temporal distribution of suspended sediment in San Francisco Bay. Plumes can be created by large freshwater flows. Zones of high suspended-sediment concentrations in shallow subembayments are associated with wind-wave resuspension and the spring-neap cycle. Filaments of clear and turbid water are caused by different transport processes in deep channels, as opposed to adjacent shallow water.

Carrying capacity in a heterogeneous environment with habitat connectivity

USGS Publications Warehouse

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

2017-01-01

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

Insights into a spatially embedded social network from a large-scale snowball sample

NASA Astrophysics Data System (ADS)

Illenberger, J.; Kowald, M.; Axhausen, K. W.; Nagel, K.

2011-12-01

Much research has been conducted to obtain insights into the basic laws governing human travel behaviour. While the traditional travel survey has been for a long time the main source of travel data, recent approaches to use GPS data, mobile phone data, or the circulation of bank notes as a proxy for human travel behaviour are promising. The present study proposes a further source of such proxy-data: the social network. We collect data using an innovative snowball sampling technique to obtain details on the structure of a leisure-contacts network. We analyse the network with respect to its topology, the individuals' characteristics, and its spatial structure. We further show that a multiplication of the functions describing the spatial distribution of leisure contacts and the frequency of physical contacts results in a trip distribution that is consistent with data from the Swiss travel survey.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Producing fractional rangeland component predictions in a sagebrush ecosystem, a Wyoming sensitivity analysis

USGS Publications Warehouse

Xian, George; Homer, Collin G.; Granneman, Brian; Meyer, Debra K.

2012-01-01

Remote sensing information has been widely used to monitor vegetation condition and variations in a variety of ecosystems, including shrublands. Careful application of remotely sensed imagery can provide additional spatially explicit, continuous, and extensive data on the composition and condition of shrubland ecosystems. Historically, the most widely available remote sensing information has been collected by Landsat, which has offered large spatial coverage and moderate spatial resolution data globally for nearly three decades. Such medium-resolution satellite remote sensing information can quantify the distribution and variation of terrestrial ecosystems. Landsat imagery has been frequently used with other high-resolution remote sensing data to classify sagebrush components and quantify their spatial distributions (Ramsey and others, 2004; Seefeldt and Booth, 2004; Stow and others, 2008; Underwood and others, 2007). Modeling algorithms have been developed to use field measurements and satellite remote sensing data to quantify the extent and evaluate the quality of shrub ecosystem components in large geographic areas (Homer and others, 2009). The percent cover of sagebrush ecosystem components, including bare-ground, herbaceous, litter, sagebrush, and shrub, have been quantified for entire western states (Homer and others, 2012). Furthermore, research has demonstrated the use of current measurements with historical archives of Landsat imagery to quantify the variations of these components for the last two decades (Xian and others, 2012). The modeling method used to quantify the extent and spatial distribution of sagebrush components over a large area also has required considerable amounts of training data to meet targeted accuracy requirements. These training data have maintained product accuracy by ensuring that they are derived from good quality field measurements collected during appropriate ecosystem phenology and subsequently maximized by extrapolation on high-resolution remote sensing data (Homer and others, 2012). This method has proven its utility; however, to develop these products across even larger areas will require additional cost efficiencies to ensure that an adequate product can be developed for the lowest cost possible. Given the vast geographic extent of shrubland ecosystems in the western United States, identifying cost efficiencies with optimal training data development and subsequent application to medium resolution satellite imagery provide the most likely areas for methodological efficiency gains. The primary objective of this research was to conduct a series of sensitivity tests to evaluate the most optimal and practical way to develop Landsat scale information for estimating the extent and distribution of sagebrush ecosystem components over large areas in the conterminous United States. An existing dataset of sagebrush components developed from extensive field measurements, high-resolution satellite imagery, and medium resolution Landsat imagery in Wyoming was used as the reference database (Homer and others, 2012). Statistical analysis was performed to analyze the relation between the accuracy of sagebrush components and the amount and distribution of training data on Landsat scenes needed to obtain accurate predictions.

Development of Automated Objective Meteorological Techniques.

DTIC Science & Technology

1980-11-30

differences are due largely to the nature and spatial distribution of the atmospheric data chosen as input for the model . The data for initial values and...technique. This report fo,-uses on results of theoretical investigations and data analyses performed oy SASC during the period May, 1979 to June, 1980...the sampling period, at a given point in space, the various size particles composing the particle distribution ex- hibit different velocities from each

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Quantifying hyporheic exchange dynamics in a highly regulated large river reach.

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

Hammond, Glenn Edward; Zhou, T; Huang, M

Hyporheic exchange is an important mechanism taking place in riverbanks and riverbed sediments, where river water and shallow groundwater mix and interact with each other. The direction, magnitude, and residence time of the hyporheic flux that penetrates the river bed are critical for biogeochemical processes such as carbon and nitrogen cycling, and biodegradation of organic contaminants. Many approaches including field measurements and numerical methods have been developed to quantify the hyporheic exchanges in relatively small rivers. However, the spatial and temporal distributions of hyporheic exchanges in a large, regulated river reach remain less explored due to the large spatial domains,more » complexity of geomorphologic features and subsurface properties, and the great pressure gradient variations at the riverbed created by dam operations.« less

Confocal laser induced fluorescence with comparable spatial localization to the conventional method

NASA Astrophysics Data System (ADS)

Thompson, Derek S.; Henriquez, Miguel F.; Scime, Earl E.; Good, Timothy N.

2017-10-01

We present measurements of ion velocity distributions obtained by laser induced fluorescence (LIF) using a single viewport in an argon plasma. A patent pending design, which we refer to as the confocal fluorescence telescope, combines large objective lenses with a large central obscuration and a spatial filter to achieve high spatial localization along the laser injection direction. Models of the injection and collection optics of the two assemblies are used to provide a theoretical estimate of the spatial localization of the confocal arrangement, which is taken to be the full width at half maximum of the spatial optical response. The new design achieves approximately 1.4 mm localization at a focal length of 148.7 mm, improving on previously published designs by an order of magnitude and approaching the localization achieved by the conventional method. The confocal method, however, does so without requiring a pair of separated, perpendicular optical paths. The confocal technique therefore eases the two window access requirement of the conventional method, extending the application of LIF to experiments where conventional LIF measurements have been impossible or difficult, or where multiple viewports are scarce.

Spatial distribution of tropospheric ozone in western Washington, USA

USGS Publications Warehouse

Cooper, S.M.; Peterson, D.L.

2000-01-01

We quantified the distribution of tropospheric ozone in topographically complex western Washington state, USA (total area a??6000 km2), using passive ozone samplers along nine river drainages to measure ozone exposure from near sea level to high-elevation mountain sites. Weekly average ozone concentrations were higher with increasing distance from the urban core and at higher elevations, increasing a mean of 1.3 ppbv per 100 m elevation gain for all mountain transects. Weekly average ozone concentrations were generally highest in Cascade Mountains drainages east and southeast of Seattle (maximum=55a??67 pbv) and in the Columbia River Gorge east of Portland (maximum=59 ppbv), and lowest in the western Olympic Peninsula (maximum=34 ppbv). Higher ozone concentrations in the Cascade Mountains and Columbia River locations downwind of large cities indicate that significant quantities of ozone and ozone precursors are being transported eastward toward rural wildland areas by prevailing westerly winds. In addition, temporal (week to week) variation in ozone distribution is synchronous within and between all drainages sampled, which indicates that there is regional coherence in air pollution detectable with weekly averages. These data provide insight on large-scale spatial variation of ozone distribution in western Washington, and will help regulatory agencies optimize future monitoring networks and identify locations where human health and natural resources could be at risk.

Spatial distribution of Dactylogyrus wunderi Bychowsky on gills of Abramis brama orientalis Berg (Leuciscinae) in Irtysh River, China

NASA Astrophysics Data System (ADS)

Hao, Cuilan; Yue, Cheng; Yao, Weijian; Yin, Jianguo; Jiao, Li; Zhu, Mengying; Jia, Shu'an; Wang, Na; Wang, Xin

2013-09-01

The spatial distribution of the monogenean Dactylogyrus wunderi Bychowsky, 1931 on the gill filaments of the bream Abramis brama orientalis Berg (Leuciscinae) inhabiting the Irtysh River of Xinjiang, China was investigated from June to July 2012. D. wunderi was identified by sequencing a fragment of its ITS rDNA region. Sixty-five fish were examined, with 55% testing positive for monogenean infection. The prevalence of the parasite in the left and right gill arches was 46% and 48%, respectively. In fish with a large body length, the prevalence of the parasite and the infection intensity did not significantly differ between the right and left gill arches but both were slightly higher in the former. Among the three size groups of fish (small, medium and large) the prevalence and the intensity of infection were lowest in fish with small body lengths. The distribution of the monogenean population in the host gills showed an aggregate distribution, with little change in the degree of aggregation, suggesting that most hosts were either not or only slightly infected by D. wunderi and that the parasite infected only a few hosts. In addition, differences in D. wunderi infections between gill arches of A. brama orientalis were not significant ( P>0.05).

Spatial structure and distribution of small pelagic fish in the northwestern Mediterranean Sea.

PubMed

Saraux, Claire; Fromentin, Jean-Marc; Bigot, Jean-Louis; Bourdeix, Jean-Hervé; Morfin, Marie; Roos, David; Van Beveren, Elisabeth; Bez, Nicolas

2014-01-01

Understanding the ecological and anthropogenic drivers of population dynamics requires detailed studies on habitat selection and spatial distribution. Although small pelagic fish aggregate in large shoals and usually exhibit important spatial structure, their dynamics in time and space remain unpredictable and challenging. In the Gulf of Lions (north-western Mediterranean), sardine and anchovy biomasses have declined over the past 5 years causing an important fishery crisis while sprat abundance rose. Applying geostatistical tools on scientific acoustic surveys conducted in the Gulf of Lions, we investigated anchovy, sardine and sprat spatial distributions and structures over 10 years. Our results show that sardines and sprats were more coastal than anchovies. The spatial structure of the three species was fairly stable over time according to variogram outputs, while year-to-year variations in kriged maps highlighted substantial changes in their location. Support for the McCall's basin hypothesis (covariation of both population density and presence area with biomass) was found only in sprats, the most variable of the three species. An innovative method to investigate species collocation at different scales revealed that globally the three species strongly overlap. Although species often co-occurred in terms of presence/absence, their biomass density differed at local scale, suggesting potential interspecific avoidance or different sensitivity to local environmental characteristics. Persistent favourable areas were finally detected, but their environmental characteristics remain to be determined.

Visualizing Distributions from Multi-Return Lidar Data to Understand Forest Structure

NASA Technical Reports Server (NTRS)

Kao, David L.; Kramer, Marc; Luo, Alison; Dungan, Jennifer; Pang, Alex

2004-01-01

Spatially distributed probability density functions (pdfs) are becoming relevant to the Earth scientists and ecologists because of stochastic models and new sensors that provide numerous realizations or data points per unit area. One source of these data is from multi-return airborne lidar, a type of laser that records multiple returns for each pulse of light sent towards the ground. Data from multi-return lidar is a vital tool in helping us understand the structure of forest canopies over large extents. This paper presents several new visualization tools that allow scientists to rapidly explore, interpret and discover characteristic distributions within the entire spatial field. The major contribution from-this work is a paradigm shift which allows ecologists to think of and analyze their data in terms of the distribution. This provides a way to reveal information on the modality and shape of the distribution previously not possible. The tools allow the scientists to depart from traditional parametric statistical analyses and to associate multimodal distribution characteristics to forest structures. Examples are given using data from High Island, southeast Alaska.

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

PubMed Central

Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O.; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A.; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs. PMID:29136658

Linking Spatial Structure and Community-Level Biotic Interactions through Cooccurrence and Time Series Modeling of the Human Intestinal Microbiota.

PubMed

de Muinck, Eric J; Lundin, Knut E A; Trosvik, Pål

2017-01-01

The gastrointestinal (GI) microbiome is a densely populated ecosystem where dynamics are determined by interactions between microbial community members, as well as host factors. The spatial organization of this system is thought to be important in human health, yet this aspect of our resident microbiome is still poorly understood. In this study, we report significant spatial structure of the GI microbiota, and we identify general categories of spatial patterning in the distribution of microbial taxa along a healthy human GI tract. We further estimate the biotic interaction structure in the GI microbiota, both through time series and cooccurrence modeling of microbial community data derived from a large number of sequentially collected fecal samples. Comparison of these two approaches showed that species pairs involved in significant negative interactions had strong positive contemporaneous correlations and vice versa, while for species pairs without significant interactions, contemporaneous correlations were distributed around zero. We observed similar patterns when comparing these models to the spatial correlations between taxa identified in the adherent microbiota. This suggests that colocalization of microbial taxon pairs, and thus the spatial organization of the GI microbiota, is driven, at least in part, by direct or indirect biotic interactions. Thus, our study can provide a basis for an ecological interpretation of the biogeography of the human gut. IMPORTANCE The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial structure relates to biotic interactions on the community level. We further describe general categories of spatial distribution patterns and identify taxa conforming to these categories. To our knowledge, this is the first study combining spatial and temporal analyses of the human gut microbiome. This type of analysis can be used for identifying candidate probiotics and designing strategies for clinical intervention.

A space-time multiscale modelling of Earth's gravity field variations

NASA Astrophysics Data System (ADS)

Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric

2017-04-01

The mass distribution within the Earth varies over a wide range of spatial and temporal scales, generating variations in the Earth's gravity field in space and time. These variations are monitored by satellites as the GRACE mission, with a 400 km spatial resolution and 10 days to 1 month temporal resolution. They are expressed in the form of gravity field models, often with a fixed spatial or temporal resolution. The analysis of these models allows us to study the mass transfers within the Earth system. Here, we have developed space-time multi-scale models of the gravity field, in order to optimize the estimation of gravity signals resulting from local processes at different spatial and temporal scales, and to adapt the time resolution of the model to its spatial resolution according to the satellites sampling. For that, we first build a 4D wavelet family combining spatial Poisson wavelets with temporal Haar wavelets. Then, we set-up a regularized inversion of inter-satellites gravity potential differences in a bayesian framework, to estimate the model parameters. To build the prior, we develop a spectral analysis, localized in time and space, of geophysical models of mass transport and associated gravity variations. Finally, we test our approach to the reconstruction of space-time variations of the gravity field due to hydrology. We first consider a global distribution of observations along the orbit, from a simplified synthetic hydrology signal comprising only annual variations at large spatial scales. Then, we consider a regional distribution of observations in Africa, and a larger number of spatial and temporal scales. We test the influence of an imperfect prior and discuss our results.

Spatio-temporal precipitation climatology over complex terrain using a censored additive regression model.

PubMed

Stauffer, Reto; Mayr, Georg J; Messner, Jakob W; Umlauf, Nikolaus; Zeileis, Achim

2017-06-15

Flexible spatio-temporal models are widely used to create reliable and accurate estimates for precipitation climatologies. Most models are based on square root transformed monthly or annual means, where a normal distribution seems to be appropriate. This assumption becomes invalid on a daily time scale as the observations involve large fractions of zero observations and are limited to non-negative values. We develop a novel spatio-temporal model to estimate the full climatological distribution of precipitation on a daily time scale over complex terrain using a left-censored normal distribution. The results demonstrate that the new method is able to account for the non-normal distribution and the large fraction of zero observations. The new climatology provides the full climatological distribution on a very high spatial and temporal resolution, and is competitive with, or even outperforms existing methods, even for arbitrary locations.

Macromolecular Crowding Induces Spatial Correlations That Control Gene Expression Bursting Patterns.

PubMed

Norred, S Elizabeth; Caveney, Patrick M; Chauhan, Gaurav; Collier, Lauren K; Collier, C Patrick; Abel, Steven M; Simpson, Michael L

2018-05-18

Recent superresolution microscopy studies in E. coli demonstrate that the cytoplasm has highly variable local concentrations where macromolecular crowding plays a central role in establishing membrane-less compartmentalization. This spatial inhomogeneity significantly influences molecular transport and association processes central to gene expression. Yet, little is known about how macromolecular crowding influences gene expression bursting-the episodic process where mRNA and proteins are produced in bursts. Here, we simultaneously measured mRNA and protein reporters in cell-free systems, showing that macromolecular crowding decoupled the well-known relationship between fluctuations in the protein population (noise) and mRNA population statistics. Crowded environments led to a 10-fold increase in protein noise even though there were only modest changes in the mRNA population and fluctuations. Instead, cell-like macromolecular crowding created an inhomogeneous spatial distribution of mRNA ("spatial noise") that led to large variability in the protein production burst size. As a result, the mRNA spatial noise created large temporal fluctuations in the protein population. These results highlight the interplay between macromolecular crowding, spatial inhomogeneities, and the resulting dynamics of gene expression, and provide insights into using these organizational principles in both cell-based and cell-free synthetic biology.

The applications of model-based geostatistics in helminth epidemiology and control.

PubMed

Magalhães, Ricardo J Soares; Clements, Archie C A; Patil, Anand P; Gething, Peter W; Brooker, Simon

2011-01-01

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Characterizing spatial heterogeneity based on the b-value and fractal analyses of the 2015 Nepal earthquake sequence

NASA Astrophysics Data System (ADS)

Nampally, Subhadra; Padhy, Simanchal; Dimri, Vijay P.

2018-01-01

The nature of spatial distribution of heterogeneities in the source area of the 2015 Nepal earthquake is characterized based on the seismic b-value and fractal analysis of its aftershocks. The earthquake size distribution of aftershocks gives a b-value of 1.11 ± 0.08, possibly representing the highly heterogeneous and low stress state of the region. The aftershocks exhibit a fractal structure characterized by a spectrum of generalized dimensions, Dq varying from D2 = 1.66 to D22 = 0.11. The existence of a fractal structure suggests that the spatial distribution of aftershocks is not a random phenomenon, but it self-organizes into a critical state, exhibiting a scale-independent structure governed by a power-law scaling, where a small perturbation in stress is sufficient enough to trigger aftershocks. In order to obtain the bias in fractal dimensions resulting from finite data size, we compared the multifractal spectrum for the real data and random simulations. On comparison, we found that the lower limit of bias in D2 is 0.44. The similarity in their multifractal spectra suggests the lack of long-range correlation in the data, with an only weakly multifractal or a monofractal with a single correlation dimension D2 characterizing the data. The minimum number of events required for a multifractal process with an acceptable error is discussed. We also tested for a possible correlation between changes in D2 and energy released during the earthquakes. The values of D2 rise during the two largest earthquakes (M > 7.0) in the sequence. The b- and D2 values are related by D2 = 1.45 b that corresponds to the intermediate to large earthquakes. Our results provide useful constraints on the spatial distribution of b- and D2-values, which are useful for seismic hazard assessment in the aftershock area of a large earthquake.

Spatial Patterns of Soil Organic Carbon Relative to Tree Size and Canopy Distribution in a Semi-Desert Grassland

NASA Astrophysics Data System (ADS)

Throop, H. L.; Archer, S.

2004-12-01

The abundance of woody species in grasslands and savannas has increased globally over the past century. Recent estimates suggest that this proliferation of woody plants may account for a significant fraction of the Northern Hemisphere C sink, although a large degree of uncertainty exists in the magnitude and spatial distribution of these plant and soil pools. While field-based inventories have made progress in assessing the role of aboveground woody growth in ecosystem C inventories, the effect of woody proliferation on soil organic carbon (SOC) remains controversial, despite the fact that the majority of ecosystem C in these systems is typically belowground. Elevated levels of SOC underneath woody plant canopies have been widely reported, but little is known about the spatial distribution of SOC relative to tree canopies. Understanding the spatial distribution of SOC is critical, however, to developing accurate landscape-scale assessments of woody proliferation impacts on ecosystem C pools. We quantified the influence of encroaching mesquite trees (Fabaceae: Prosopis velutina) on the concentration of SOC and total nitrogen (TN) in a semi-desert grassland in southern Arizona. SOC concentrations near the boles of large trees (basal diameter 85-102 cm) were approximately double that of SOC in intercanopy zones (0.9% vs. 0.4% SOC by weight). SOC declined moving out from the bole to the canopy edge, at which point it was equivalent to inter-canopy spaces. Small to medium-sized trees (basal diameters less than 85 cm) had minimal influence on SOC concentrations. Patterns of TN values mirrored those of SOC in all cases, although TN values were roughly an order of magnitude lower than SOC values. These data suggest that accurate accounting of landscape-level SOC stocks will require developing area-weighting algorithms that account for tree size and bole-to-canopy gradients.

Assessing modelled spatial distributions of ice water path using satellite data

NASA Astrophysics Data System (ADS)

Eliasson, S.; Buehler, S. A.; Milz, M.; Eriksson, P.; John, V. O.

2010-05-01

The climate models used in the IPCC AR4 show large differences in monthly mean cloud ice. The most valuable source of information that can be used to potentially constrain the models is global satellite data. For this, the data sets must be long enough to capture the inter-annual variability of Ice Water Path (IWP). PATMOS-x was used together with ISCCP for the annual cycle evaluation in Fig. 7 while ECHAM-5 was used for the correlation with other models in Table 3. A clear distinction between ice categories in satellite retrievals, as desired from a model point of view, is currently impossible. However, long-term satellite data sets may still be used to indicate the climatology of IWP spatial distribution. We evaluated satellite data sets from CloudSat, PATMOS-x, ISCCP, MODIS and MSPPS in terms of monthly mean IWP, to determine which data sets can be used to evaluate the climate models. IWP data from CloudSat cloud profiling radar provides the most advanced data set on clouds. As CloudSat data are too short to evaluate the model data directly, it was mainly used here to evaluate IWP from the other satellite data sets. ISCCP and MSPPS were shown to have comparatively low IWP values. ISCCP shows particularly low values in the tropics, while MSPPS has particularly low values outside the tropics. MODIS and PATMOS-x were in closest agreement with CloudSat in terms of magnitude and spatial distribution, with MODIS being the best of the two. As PATMOS-x extends over more than 25 years and is in fairly close agreement with CloudSat, it was chosen as the reference data set for the model evaluation. In general there are large discrepancies between the individual climate models, and all of the models show problems in reproducing the observed spatial distribution of cloud-ice. Comparisons consistently showed that ECHAM-5 is the GCM from IPCC AR4 closest to satellite observations.

Multi-scale geophysical study to model the distribution and development of fractures in relation to the knickpoint in the Luquillo Critical Zone Observatory (Puerto Rico)

NASA Astrophysics Data System (ADS)

Comas, X.; Wright, W. J.; Hynek, S. A.; Ntarlagiannis, D.; Terry, N.; Job, M. J.; Fletcher, R. C.; Brantley, S.

2017-12-01

Previous studies in the Rio Icacos watershed in the Luquillo Mountains (Puerto Rico) have shown that regolith materials are rapidly developed from the alteration of quartz diorite bedrock, and create a blanket on top of the bedrock with a thickness that decreases with proximity to the knickpoint. The watershed is also characterized by a system of heterogeneous fractures that likely drive bedrock weathering and the formation of corestones and associated spheroidal fracturing and rindlets. Previous efforts to characterize the spatial distribution of fractures were based on aerial images that did not account for the architecture of the critical zone below the subsurface. In this study we use an array of near-surface geophysical methods at multiple scales to better understand how the spatial distribution and density of fractures varies with topography and proximity to the knickpoint. Large km-scale surveys using ground penetrating radar (GPR), terrain conductivity, and capacitively coupled resistivity, were combined with smaller scale surveys (10-100 m) using electrical resistivity imaging (ERI), and shallow seismics, and were directly constrained with boreholes from previous studies. Geophysical results were compared to theoretical models of compressive stress as due to gravity and regional compression, and showed consistency at describing increased dilation of fractures with proximity to the knickpoint. This study shows the potential of multidisciplinary approaches to model critical zone processes at multiple scales of measurement and high spatial resolution. The approach can be particularly efficient at large km-scales when applying geophysical methods that allow for rapid data acquisition (i.e. walking pace) at high spatial resolution (i.e. cm scales).

ESSG-based global spatial reference frame for datasets interrelation

NASA Astrophysics Data System (ADS)

Yu, J. Q.; Wu, L. X.; Jia, Y. J.

2013-10-01

To know well about the highly complex earth system, a large volume of, as well as a large variety of, datasets on the planet Earth are being obtained, distributed, and shared worldwide everyday. However, seldom of existing systems concentrates on the distribution and interrelation of different datasets in a common Global Spatial Reference Frame (GSRF), which holds an invisble obstacle to the data sharing and scientific collaboration. Group on Earth Obeservation (GEO) has recently established a new GSRF, named Earth System Spatial Grid (ESSG), for global datasets distribution, sharing and interrelation in its 2012-2015 WORKING PLAN.The ESSG may bridge the gap among different spatial datasets and hence overcome the obstacles. This paper is to present the implementation of the ESSG-based GSRF. A reference spheroid, a grid subdvision scheme, and a suitable encoding system are required to implement it. The radius of ESSG reference spheroid was set to the double of approximated Earth radius to make datasets from different areas of earth system science being covered. The same paramerters of positioning and orienting as Earth Centred Earth Fixed (ECEF) was adopted for the ESSG reference spheroid to make any other GSRFs being freely transformed into the ESSG-based GSRF. Spheroid degenerated octree grid with radius refiment (SDOG-R) and its encoding method were taken as the grid subdvision and encoding scheme for its good performance in many aspects. A triple (C, T, A) model is introduced to represent and link different datasets based on the ESSG-based GSRF. Finally, the methods of coordinate transformation between the ESSGbased GSRF and other GSRFs were presented to make ESSG-based GSRF operable and propagable.

Measuring Te inclusion uniformity over large areas for CdTe/CZT imaging and spectrometry sensors

NASA Astrophysics Data System (ADS)

Bolke, Joe; O'Brien, Kathryn; Wall, Peter; Spicer, Mike; Gélinas, Guillaume; Beaudry, Jean-Nicolas; Alexander, W. Brock

2017-09-01

CdTe and CZT materials are technologies for gamma and x-ray imaging for applications in industry, homeland security, defense, space, medical, and astrophysics. There remain challenges in uniformity over large detector areas (50 75 mm) due to a combination of material purity, handling, growth process, grown in defects, doping/compensation, and metal contacts/surface states. The influence of these various factors has yet to be explored at the large substrate level required for devices with higher resolution both spatially and spectroscopically. In this study, we looked at how the crystal growth processes affect the size and density distributions of microscopic Te inclusion defects. We were able to grow single crystals as large as 75 mm in diameter and spatially characterize three-dimensional defects and map the uniformity using IR microscopy. We report on the pattern of observed defects within wafers and its relation to instabilities at the crystal growth interface.

PP-SWAT: A phython-based computing software for efficient multiobjective callibration of SWAT

USDA-ARS?s Scientific Manuscript database

With enhanced data availability, distributed watershed models for large areas with high spatial and temporal resolution are increasingly used to understand water budgets and examine effects of human activities and climate change/variability on water resources. Developing parallel computing software...

The steady-state mosaic of disturbance and succession across an old-growth Central Amazon forest landscape.

PubMed

Chambers, Jeffrey Q; Negron-Juarez, Robinson I; Marra, Daniel Magnabosco; Di Vittorio, Alan; Tews, Joerg; Roberts, Dar; Ribeiro, Gabriel H P M; Trumbore, Susan E; Higuchi, Niro

2013-03-05

Old-growth forest ecosystems comprise a mosaic of patches in different successional stages, with the fraction of the landscape in any particular state relatively constant over large temporal and spatial scales. The size distribution and return frequency of disturbance events, and subsequent recovery processes, determine to a large extent the spatial scale over which this old-growth steady state develops. Here, we characterize this mosaic for a Central Amazon forest by integrating field plot data, remote sensing disturbance probability distribution functions, and individual-based simulation modeling. Results demonstrate that a steady state of patches of varying successional age occurs over a relatively large spatial scale, with important implications for detecting temporal trends on plots that sample a small fraction of the landscape. Long highly significant stochastic runs averaging 1.0 Mg biomass⋅ha(-1)⋅y(-1) were often punctuated by episodic disturbance events, resulting in a sawtooth time series of hectare-scale tree biomass. To maximize the detection of temporal trends for this Central Amazon site (e.g., driven by CO2 fertilization), plots larger than 10 ha would provide the greatest sensitivity. A model-based analysis of fractional mortality across all gap sizes demonstrated that 9.1-16.9% of tree mortality was missing from plot-based approaches, underscoring the need to combine plot and remote-sensing methods for estimating net landscape carbon balance. Old-growth tropical forests can exhibit complex large-scale structure driven by disturbance and recovery cycles, with ecosystem and community attributes of hectare-scale plots exhibiting continuous dynamic departures from a steady-state condition.

Spatial distribution of soil moisture obtained from gravimetric and TDR methods for SMOS validation, at the Polesie test site SVRT 3275, in Poland

NASA Astrophysics Data System (ADS)

Usowicz, B.; Marczewski, W.; Lipiec, J.; Usowicz, J. B.; Sokolowska, Z.; Dabkowska-Naskret, H.; Hajnos, M.; Lukowski, M. I.

2009-04-01

The purpose is obtaining trustful ground based measurement data of SM (Soil Moisture) for validating SMOS, respectively to spatial and temporal distribution and variations. A use of Time Domain Reflectometric (TDR) method is fast, simple and less destructive, to the soil matter, than a usual standard gravimetric method. TDR tools operate efficiently, enable nearly instant measurements, and allow on collecting many measurements from numerous sites, even when operated manually in short time intervals. The method enables also very frequent sampling of SM at few selected fixed sites, when long terms of temporal variations are needed. In effect one obtains reasonably large data base for determining spatial and temporal distributions of SM. The study is devoted to determining a plan on collecting TDR data, in the scales of small and large field areas, and checking their relevance to those available from gravimetric methods. Finally, the ground based SM distributions are needed for validating other SM distributions, available remotely in larger scales, from the satellite data of ENVISAT-ASAR, and from SMOS (Soil Moisture and Ocean Salinity Mission) when it becomes operational. The ground based evaluations are served mainly by geo-statistical analysis. The space borne estimations are retrieved by image processing and physical models, proper to relevant Remote Sensing (RS) instruments on the orbit. Finally, validation must engage again the geo-statistical evaluations, to assess the agreement between direct and remote sensing means, and provide a measure of trust for extending the limited scales of the ground based data, on concluding the agreement in scales proper to the satellite data. The study is focused mainly on trustful evaluating data from the ground, provided independently on satellite data sources. SM ground based data are collected permanently at 2 selected tests sites, and temporary in areas around the tests sites, in one day sessions, repeated several times per vegetation season. Permanent measurements are provided in profiles, down to 50 cm below surface. Temporary SM measurements are collected by hand held TDR (FOM/mts type, Easy Test Ltd., Lublin, Poland) from the top surface layer (1-6 cm), in a grid covering small and large areas, containing few hundred sites. The same places are served by collecting soil samples for the gravimetric analysis of SM, bulk density, other physical and textural characteristics. Sessions on measurement in large areas on the scale of community are repeated for separate days. The two methods used were compared with correlation coefficient, regression equation and differences of values. The spatial variability of soil moisture from gravimetric and TDR measurements were analyzed using geostatistical methods. The semivariogram parameters were determined and mathematical functions were fitted to empirically derived semivariograms. These functions were used for estimation of spatial distribution of soil moisture in cultivated fields by the kriging method. The results showed that spatial distribution patterns of topsoil soil moisture in the investigated areas obtained from TDR and gravimetric methods were in general similar to each other. The TDR soil moisture contents were dependent on bulk density and texture of soil. In areas with fine-textured soils of lower soil bulk densities (approximately below 1.35 Mg m^-3) we observed that TDR soil moisture and spatial differentiation were greater compared to those with gravimetric method. However at higher bulk densities the inverse was true. The spatial patterns were further modified in areas with domination of coarse-textured soils. Decrease of measurement points results in smoothing soil moisture pattern and at the same time in a greater estimation error. The TDR method can be useful tool for ground moisture measurements and validation of satellite data. The use of specific calibration or correction for soil bulk density and texture with respect to the reflectometric method is recommended. The study is a contribution to the project SWEX (AO-3275) and funded by the Polish Ministry of Science and Higher Education (in part by Grant No. N305 046 31/1707 and in part by Grant No. N305 107 32/3865).

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

Stewart, J; Lindsay, P; University of Toronto, Toronto

Purpose: Recent progress in small animal radiotherapy systems has provided the foundation for delivering the heterogeneous, millimeter scale dose distributions demanded by preclinical radiobiology investigations. Despite advances in preclinical dose planning, delivery of highly heterogeneous dose distributions is constrained by the fixed collimation systems and large x-ray focal spot common in small animal radiotherapy systems. This work proposes a dual focal spot dose optimization and delivery method with a large x-ray focal spot used to deliver homogeneous dose regions and a small focal spot to paint spatially heterogeneous dose regions. Methods: Two-dimensional dose kernels were measured for a 1 mmmore » circular collimator with radiochromic film at 10 mm depth in a solid water phantom for the small and large x-ray focal spots on a recently developed small animal microirradiator. These kernels were used in an optimization framework which segmented a desired dose distribution into low- and high-spatial frequency regions for delivery by the large and small focal spot, respectively. For each region, the method determined an optimal set of stage positions and beam-on times. The method was demonstrated by optimizing a bullseye pattern consisting of 0.75 mm radius circular target and 0.5 and 1.0 mm wide rings alternating between 0 and 2 Gy. Results: Compared to a large focal spot technique, the dual focal spot technique improved the optimized dose distribution: 69.2% of the optimized dose was within 0.5 Gy of the intended dose for the large focal spot, compared to 80.6% for the dual focal spot method. The dual focal spot design required 14.0 minutes of optimization, and will require 178.3 minutes for automated delivery. Conclusion: The dual focal spot optimization and delivery framework is a novel option for delivering conformal and heterogeneous dose distributions at the preclinical level and provides a new experimental option for unique radiobiological investigations. Funding Support: this work is supported by funding the National Sciences and Engineering Research Council of Canada, and a Mitacs-accelerate fellowship. Conflict of Interest: Dr. Lindsay and Dr. Jaffray are listed as inventors of the small animal microirradiator described herein. This system has been licensed for commercial development.« less

Prevalence of somatic mitochondrial mutations and spatial distribution of mitochondria in non-small cell lung cancer.

PubMed

Kazdal, Daniel; Harms, Alexander; Endris, Volker; Penzel, Roland; Kriegsmann, Mark; Eichhorn, Florian; Muley, Thomas; Stenzinger, Albrecht; Pfarr, Nicole; Weichert, Wilko; Warth, Arne

2017-07-11

Mitochondria are considered relevant players in many tumour entities and first data indicate beneficial effects of mitochondria-targeted antioxidants in both cancer prevention and anticancer therapies. To further dissect the potential roles of mitochondria in NSCLC we comprehensively analysed somatic mitochondrial mutations, determined the spatial distribution of mitochondrial DNA within complete tumour sections and investigated the mitochondrial load in a large-scale approach. Whole mitochondrial genome sequencing of 26 matched tumour and non-neoplastic tissue samples extended by reviewing published data of 326 cases. Systematical stepwise real-time PCR quantification of mitochondrial DNA covering 16 whole surgical tumour sections. Immunohistochemical determination of the mitochondrial load in 171 adenocarcinoma and 145 squamous cell carcinoma. Our results demonstrate very low recurrences (max. 1.7%) and a broad distribution of 456 different somatic mitochondrial mutations. Large inter- and intra-tumour heterogeneity were seen for mitochondrial DNA copy numbers in conjunction with a correlation to the predominant histological growth pattern. Furthermore, tumour cells had significantly higher mitochondrial level compared to adjacent stroma, whereas differences between tumour entities were negligible. Non-evident somatic mitochondrial mutations and highly varying mitochondrial DNA level delineate challenges for the approach of mitochondria-targeted anticancer therapies in NSCLC.

Spatial Distribution of Coffee Wilt Disease Under Roguing and Replanting Conditions: A Case Study from Kaweri Estate in Uganda.

PubMed

Pinard, F; Makune, S E; Campagne, P; Mwangi, J

2016-11-01

Based on time and spatial dynamic considerations, this study evaluates the potential role of short- and long-distance dispersal in the spread of coffee wilt disease (CWD) in a large commercial Robusta coffee estate in Uganda (Kaweri, 1,755 ha) over a 4-year period (2008 to 2012). In monthly surveys, total disease incidence, expansion of infection foci, and the occurrence of isolated infected trees were recorded and submitted to spatial analysis. Incidence was higher and disease progression faster in old coffee plantings compared with young plantings, indicating a lack of efficiency of roguing for reducing disease development in old plantings. At large spatial scale (approximately 1 km), Moran indices (both global and local) revealed the existence of clusters characterized by contrasting disease incidences. This suggested that local environmental conditions were heterogeneous or there were spatial interactions among blocks. At finer spatial scale (approximately 200 m), O-ring statistics revealed positive correlation between distant infection sites across distances as great as 60 m. Although these observations indicate the role of short-distance dispersal in foci expansion, dispersal at greater distances (>20 m) appeared to also contribute to both initiation of new foci and disease progression at coarser spatial scales. Therefore, our results suggested the role of aerial dispersal in CWD progression.

Effect of a fish stock's demographic structure on offspring survival and sensitivity to climate

PubMed Central

Stige, Leif Christian; Yaragina, Natalia A.; Langangen, Øystein; Bogstad, Bjarte; Stenseth, Nils Chr.; Ottersen, Geir

2017-01-01

Commercial fishing generally removes large and old individuals from fish stocks, reducing mean age and age diversity among spawners. It is feared that these demographic changes lead to lower and more variable recruitment to the stocks. A key proposed pathway is that juvenation and reduced size distribution causes reduced ranges in spawning period, spawning location, and egg buoyancy; this is proposed to lead to reduced spatial distribution of fish eggs and larvae, more homogeneous ambient environmental conditions within each year-class, and reduced buffering against negative environmental influences. However, few, if any, studies have confirmed a causal link from spawning stock demographic structure through egg and larval distribution to year class strength at recruitment. We here show that high mean age and size in the spawning stock of Barents Sea cod (Gadus morhua) is positively associated with high abundance and wide spatiotemporal distribution of cod eggs. We find, however, no support for the hypothesis that a wide egg distribution leads to higher recruitment or a weaker recruitment–temperature correlation. These results are based on statistical analyses of a spatially resolved data set on cod eggs covering a period (1959−1993) with large changes in biomass and demographic structure of spawners. The analyses also account for significant effects of spawning stock biomass and a liver condition index on egg abundance and distribution. Our results suggest that the buffering effect of a geographically wide distribution of eggs and larvae on fish recruitment may be insignificant compared with other impacts. PMID:28115694

Comparisons of ionospheric electron density distributions reconstructed by GPS computerized tomography, backscatter ionograms, and vertical ionograms

NASA Astrophysics Data System (ADS)

Zhou, Chen; Lei, Yong; Li, Bofeng; An, Jiachun; Zhu, Peng; Jiang, Chunhua; Zhao, Zhengyu; Zhang, Yuannong; Ni, Binbin; Wang, Zemin; Zhou, Xuhua

2015-12-01

Global Positioning System (GPS) computerized ionosphere tomography (CIT) and ionospheric sky wave ground backscatter radar are both capable of measuring the large-scale, two-dimensional (2-D) distributions of ionospheric electron density (IED). Here we report the spatial and temporal electron density results obtained by GPS CIT and backscatter ionogram (BSI) inversion for three individual experiments. Both the GPS CIT and BSI inversion techniques demonstrate the capability and the consistency of reconstructing large-scale IED distributions. To validate the results, electron density profiles obtained from GPS CIT and BSI inversion are quantitatively compared to the vertical ionosonde data, which clearly manifests that both methods output accurate information of ionopsheric electron density and thereby provide reliable approaches to ionospheric soundings. Our study can improve current understanding of the capability and insufficiency of these two methods on the large-scale IED reconstruction.

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

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Evaluating ecosystem-based management options: Effects of trawling in Torres Strait, Australia

NASA Astrophysics Data System (ADS)

Ellis, Nick; Pantus, Francis; Welna, Andrzej; Butler, Alan

2008-09-01

A suite of management options for a prawn trawl fishery in Torres Strait, Australia was assessed for impacts on the benthic fauna using a dynamic management strategy evaluation approach. The specification of the management options was gained through consultation with stakeholders. Data for the model was drawn from several sources: the fleet data from fishery logbooks and satellite vessel monitoring systems, benthic depletion rates from trawl-down experiments, benthic recovery rates from post-experiment recovery monitoring studies, and benthic distribution from large-scale benthic surveys. Although there were large uncertainties in the resulting indicators, robust measures relevant to management were obtained by taking ratios relative to the status quo. The management control with the biggest effect was total effort; reducing trawl effort always led to increases in benthic faunal density of up to 10%. Spatial closures had a smaller benefit of up to 2%. The effect of closing a set of buffer zones around reefs to trawling was indistinguishable from the status quo option. Closing a larger area, however, was largely beneficial especially for sea cucumbers. When the spatial distributions of fauna prior to fishing were accounted for, fauna with distributions positively correlated with effort improved relative to those negatively correlated. The reduction in prawn catch under effort reduction scenarios could be ameliorated by introducing temporal closures over the full-moon period.

Large-Scale Overlays and Trends: Visually Mining, Panning and Zooming the Observable Universe.

PubMed

Luciani, Timothy Basil; Cherinka, Brian; Oliphant, Daniel; Myers, Sean; Wood-Vasey, W Michael; Labrinidis, Alexandros; Marai, G Elisabeta

2014-07-01

We introduce a web-based computing infrastructure to assist the visual integration, mining and interactive navigation of large-scale astronomy observations. Following an analysis of the application domain, we design a client-server architecture to fetch distributed image data and to partition local data into a spatial index structure that allows prefix-matching of spatial objects. In conjunction with hardware-accelerated pixel-based overlays and an online cross-registration pipeline, this approach allows the fetching, displaying, panning and zooming of gigabit panoramas of the sky in real time. To further facilitate the integration and mining of spatial and non-spatial data, we introduce interactive trend images-compact visual representations for identifying outlier objects and for studying trends within large collections of spatial objects of a given class. In a demonstration, images from three sky surveys (SDSS, FIRST and simulated LSST results) are cross-registered and integrated as overlays, allowing cross-spectrum analysis of astronomy observations. Trend images are interactively generated from catalog data and used to visually mine astronomy observations of similar type. The front-end of the infrastructure uses the web technologies WebGL and HTML5 to enable cross-platform, web-based functionality. Our approach attains interactive rendering framerates; its power and flexibility enables it to serve the needs of the astronomy community. Evaluation on three case studies, as well as feedback from domain experts emphasize the benefits of this visual approach to the observational astronomy field; and its potential benefits to large scale geospatial visualization in general.

Heterogeneity in the distribution of genetically modified and conventional oilseed rape within fields and seed lots.

PubMed

Begg, Graham S; Elliott, Martin J; Cullen, Danny W; Iannetta, Pietro P M; Squire, Geoff R

2008-10-01

The implementation of co-existence in the commercialisation of GM crops requires GM and non-GM products to be segregated in production and supply. However, maintaining segregation in oilseed rape will be made difficult by the highly persistent nature of this species. An understanding of its population dynamics is needed to predict persistence and develop potential strategies for control, while to ensure segregation is being achieved, the production of GM oilseed rape must be accompanied by the monitoring of GM levels in crop or seed populations. Heterogeneity in the spatial distribution of oilseed rape has the potential to affect both control and monitoring and, although a universal phenomenon in arable weeds and harvested seed lots, spatial heterogeneity in oilseed rape populations remains to be demonstrated and quantified. Here we investigate the distribution of crop and volunteer populations in a commercial field before and during the cultivation of the first conventional oilseed rape (winter) crop since the cultivation of a GM glufosinate-tolerant oilseed rape crop (spring) three years previously. GM presence was detected by ELISA for the PAT protein in each of three morphologically distinguishable phenotypes: autumn germinating crop-type plants (3% GM), autumn-germinating 'regrowths' (72% GM) and spring germinating 'small-type' plants (17% GM). Statistical models (Poisson log-normal and binomial logit-normal) were used to describe the spatial distribution of these populations at multiple spatial scales in the field and of GM presence in the harvested seed lot. Heterogeneity was a consistent feature in the distribution of GM and conventional oilseed rape. Large trends across the field (50 x 400 m) and seed lot (4 x 1.5 x 1.5 m) were observed in addition to small-scale heterogeneity, less than 20 m in the field and 20 cm in the seed lot. The heterogeneity was greater for the 'regrowth' and 'small' phenotypes, which were likely to be volunteers and included most of the GM plants detected, than for the largely non-GM 'crop' phenotype. The implications of the volunteer heterogeneity for field management and GM-sampling are discussed.

Clustering, randomness, and regularity in cloud fields. 4. Stratocumulus cloud fields

NASA Astrophysics Data System (ADS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-07-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (>900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Hysteresis, phase transitions, and dangerous transients in electrical power distribution systems

NASA Astrophysics Data System (ADS)

Duclut, Charlie; Backhaus, Scott; Chertkov, Michael

2013-06-01

The majority of dynamical studies in power systems focus on the high-voltage transmission grids where models consider large generators interacting with crude aggregations of individual small loads. However, new phenomena have been observed indicating that the spatial distribution of collective, nonlinear contribution of these small loads in the low-voltage distribution grid is crucial to the outcome of these dynamical transients. To elucidate the phenomenon, we study the dynamics of voltage and power flows in a spatially extended distribution feeder (circuit) connecting many asynchronous induction motors and discover that this relatively simple 1+1 (space+time) dimensional system exhibits a plethora of nontrivial spatiotemporal effects, some of which may be dangerous for power system stability. Long-range motor-motor interactions mediated by circuit voltage and electrical power flows result in coexistence and segregation of spatially extended phases defined by individual motor states, a “normal” state where the motors’ mechanical (rotation) frequency is slightly smaller than the nominal frequency of the basic ac flows and a “stalled” state where the mechanical frequency is small. Transitions between the two states can be initiated by a perturbation of the voltage or base frequency at the head of the distribution feeder. Such behavior is typical of first-order phase transitions in physics, and this 1+1 dimensional model shows many other properties of a first-order phase transition with the spatial distribution of the motors’ mechanical frequency playing the role of the order parameter. In particular, we observe (a) propagation of the phase-transition front with the constant speed (in very long feeders) and (b) hysteresis in transitions between the normal and stalled (or partially stalled) phases.

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

NASA Technical Reports Server (NTRS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-01-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Seismicity and source spectra analysis in Salton Sea Geothermal Field

NASA Astrophysics Data System (ADS)

Cheng, Y.; Chen, X.

2016-12-01

The surge of "man-made" earthquakes in recent years has led to considerable concerns about the associated hazards. Improved monitoring of small earthquakes would significantly help understand such phenomena and the underlying physical mechanisms. In the Salton Sea Geothermal field in southern California, open access of a local borehole network provides a unique opportunity to better understand the seismicity characteristics, the related earthquake hazards, and the relationship with the geothermal system, tectonic faulting and other physical conditions. We obtain high-resolution earthquake locations in the Salton Sea Geothermal Field, analyze characteristics of spatiotemporal isolated earthquake clusters, magnitude-frequency distributions and spatial variation of stress drops. The analysis reveals spatial coherent distributions of different types of clustering, b-value distributions, and stress drop distribution. The mixture type clusters (short-duration rapid bursts with high aftershock productivity) are predominately located within active geothermal field that correlate with high b-value, low stress drop microearthquake clouds, while regular aftershock sequences and swarms are distributed throughout the study area. The differences between earthquakes inside and outside of geothermal operation field suggest a possible way to distinguish directly induced seismicity due to energy operation versus typical seismic slip driven sequences. The spatial coherent b-value distribution enables in-situ estimation of probabilities for M≥3 earthquakes, and shows that the high large-magnitude-event (LME) probability zones with high stress drop are likely associated with tectonic faulting. The high stress drop in shallow (1-3 km) depth indicates the existence of active faults, while low stress drops near injection wells likely corresponds to the seismic response to fluid injection. I interpret the spatial variation of seismicity and source characteristics as the result of fluid circulation, the fracture network, and tectonic faulting.

Hysteresis, phase transitions, and dangerous transients in electrical power distribution systems.

PubMed

Duclut, Charlie; Backhaus, Scott; Chertkov, Michael

2013-06-01

The majority of dynamical studies in power systems focus on the high-voltage transmission grids where models consider large generators interacting with crude aggregations of individual small loads. However, new phenomena have been observed indicating that the spatial distribution of collective, nonlinear contribution of these small loads in the low-voltage distribution grid is crucial to the outcome of these dynamical transients. To elucidate the phenomenon, we study the dynamics of voltage and power flows in a spatially extended distribution feeder (circuit) connecting many asynchronous induction motors and discover that this relatively simple 1+1 (space+time) dimensional system exhibits a plethora of nontrivial spatiotemporal effects, some of which may be dangerous for power system stability. Long-range motor-motor interactions mediated by circuit voltage and electrical power flows result in coexistence and segregation of spatially extended phases defined by individual motor states, a "normal" state where the motors' mechanical (rotation) frequency is slightly smaller than the nominal frequency of the basic ac flows and a "stalled" state where the mechanical frequency is small. Transitions between the two states can be initiated by a perturbation of the voltage or base frequency at the head of the distribution feeder. Such behavior is typical of first-order phase transitions in physics, and this 1+1 dimensional model shows many other properties of a first-order phase transition with the spatial distribution of the motors' mechanical frequency playing the role of the order parameter. In particular, we observe (a) propagation of the phase-transition front with the constant speed (in very long feeders) and (b) hysteresis in transitions between the normal and stalled (or partially stalled) phases.

Projecting future impacts of hurricanes on the carbon balance of eastern U.S. forests

NASA Astrophysics Data System (ADS)

Fisk, J. P.; Hurtt, G. C.; Chambers, J. Q.; Zeng, H.; Dolan, K.; Flanagan, S.; Rourke, O.; Negron Juarez, R. I.

2011-12-01

In U.S. Atlantic coastal areas, hurricanes are a principal agent of catastrophic wind damage, with dramatic impacts on the structure and functioning of forests. Substantial recent progress has been made to estimate the biomass loss and resulting carbon emissions caused by hurricanes impacting the U.S. Additionally, efforts to evaluate the net effects of hurricanes on the regional carbon balance have demonstrated the importance of viewing large disturbance events in the broader context of recovery from a mosaic of past events. Viewed over sufficiently long time scales and large spatial scales, regrowth from previous storms may largely offset new emissions; however, changes in number, strength or spatial distribution of extreme disturbance events will result in changes to the equilibrium state of the ecosystem and have the potential to result in a lasting carbon source or sink. Many recent studies have linked climate change to changes in the frequency and intensity of hurricanes. In this study, we use a mechanistic ecosystem model, the Ecosystem Demography (ED) model, driven by scenarios of future hurricane activity based on historic activity and future climate projections, to evaluate how changes in hurricane frequency, intensity and spatial distribution could affect regional carbon storage and flux over the coming century. We find a non-linear response where increased storm activity reduces standing biomass stocks reducing the impacts of future events. This effect is highly dependent on the spatial pattern and repeat interval of future hurricane activity. Developing this kind of predictive modeling capability that tracks disturbance events and recovery is key to our understanding and ability to predict the carbon balance of forests.

[Geostatistics analyzing to cause of formation of circle distribution of plant communities in Horqin Sandy Land].

PubMed

He, Xingdong; Gao, Yubao; Zhao, Wenzhi; Cong, Zili

2004-09-01

Investigation results in the present study showed that plant communities took typical concentric circles distribution patterns along habitat gradient from top, slope to interdune on a few large fixed dunes in middle part of Korqin Sandy Land. In order to explain this phenomenon, analysis of water content and its spatial heterogeneity in sand layers on different locations of dunes was conducted. In these dunes, water contents in sand layers of the tops were lower than those of the slopes; both of them were lower than those of the interdunes. According to the results of geostatistics analysis, whether shifting dune or fixed dune, spatial heterogeneity of water contents in sand layers took on regular changes, such as ratios between nugget and sill and ranges reduced gradually, fractal dimension increased gradually, the regular changes of these parameters indicated that random spatial heterogeneity reduced gradually, and autocorrelation spatial heterogeneity increased gradually from the top, the slope to the interdune. The regular changes of water contents in sand layers and their spatial heterogeneity of different locations of the dunes, thus, might be an important cause resulted in the formation of the concentric circles patterns of the plant communities on these fixed dunes.

Deconfounding the effects of local element spatial heterogeneity and sparsity on processing dominance.

PubMed

Montoro, Pedro R; Luna, Dolores

2009-10-01

Previous studies on the processing of hierarchical patterns (Luna & Montoro, 2008) have shown that altering the spatial relationships between the local elements affected processing dominance by decreasing global advantage. In the present article, the authors examine whether heterogeneity or a sparse distribution of the local elements was the responsible factor for this effect. In Experiments 1 and 2, the distance between the local elements was increased in a similar way, but between-element distance was homogeneous in Experiment 1 and heterogeneous in Experiment 2. In Experiment 3, local elements' size was varied by presenting global patterns composed of similar large or small local elements and of different large and small sizes. The results of the present research showed that, instead of element sparsity, spatial heterogeneity that could change the appearance of the global form as well as the salience of the local elements was the main determiner of impairing global processing.

Spatio-temporal distributions of piscivorous birds in a subarctic sound during the nonbreeding season

NASA Astrophysics Data System (ADS)

Stocking, Jessica; Bishop, Mary Anne; Arab, Ali

2018-01-01

Understanding bird distributions outside of the breeding season may help to identify important criteria for winter refuge. We surveyed marine birds in Prince William Sound, Alaska, USA over nine winters from 2007 to 2016. Our objectives were twofold: to examine the seasonal patterns of piscivorous species overwintering in Prince William Sound, and to explore the relationships between spatial covariates and bird distributions, accounting for inherent spatial structure. We used hurdle models to examine nine species groups of piscivorous seabirds: loons, grebes, cormorants, mergansers, large gulls, small gulls, kittiwakes, Brachyramphus murrelets, and murres. Seven groups showed pronounced seasonal patterns. The models with the most support identified water depth and distance to shore as key environmental covariates, while habitat type, wave exposure, sea surface temperature and seafloor slope had less support. Environmental associations are consistent with the available knowledge of forage fish distribution during this time, but studies that address habitat associations of prey fish in winter could strengthen our understanding of processes in Prince William Sound.

Spatial distribution of Eucalyptus roots in a deep sandy soil in the Congo: relationships with the ability of the stand to take up water and nutrients.

PubMed

Laclau, J P; Arnaud, M; Bouillet, J P; Ranger, J

2001-02-01

Spatial statistical analyses were performed to describe root distribution and changes in soil strength in a mature clonal plantation of Eucalyptus spp. in the Congo. The objective was to analyze spatial variability in root distribution. Relationships between root distribution, soil strength and the water and nutrient uptake by the stand were also investigated. We studied three, 2.35-m-wide, vertical soil profiles perpendicular to the planting row and at various distances from a representative tree. The soil profiles were divided into 25-cm2 grid cells and the number of roots in each of three diameter classes counted in each grid cell. Two profiles were 2-m deep and the third profile was 5-m deep. There was both vertical and horizontal anisotropy in the distribution of fine roots in the three profiles, with root density decreasing sharply with depth and increasing with distance from the stump. Roots were present in areas with high soil strength values (> 6,000 kPa). There was a close relationship between soil water content and soil strength in this sandy soil. Soil strength increased during the dry season mainly because of water uptake by fine roots. There were large areas with low root density, even in the topsoil. Below a depth of 3 m, fine roots were spatially concentrated and most of the soil volume was not explored by roots. This suggests the presence of drainage channels, resulting from the severe hydrophobicity of the upper soil.

A dam-reservoir module for a semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

de Lavenne, Alban; Thirel, Guillaume; Andréassian, Vazken; Perrin, Charles; Ramos, Maria-Helena

2017-04-01

Developing modeling tools that help to assess the spatial distribution of water resources is a key issue to achieve better solutions for the optimal management of water availability among users in a river basin. Streamflow dynamics depends on (i) the spatial variability of rainfall, (ii) the heterogeneity of catchment behavior and response, and (iii) local human regulations (e.g., reservoirs) that store and control surface water. These aspects can be successfully handled by distributed or semi-distributed hydrological models. In this study, we develop a dam-reservoir module within a semi-distributed rainfall-runoff model (de Lavenne et al. 2016). The model runs at the daily time step, and has five parameters for each sub-catchment as well as a streamflow velocity parameter for flow routing. Its structure is based on two stores, one for runoff production and one for routing. The calibration of the model is performed from upstream to downstream sub-catchments, which efficiently uses spatially-distributed streamflow measurements. In a previous study, Payan et al. (2008) described a strategy to implement a dam module within a lumped rainfall-runoff model. Here we propose to adapt this strategy to a semi-distributed hydrological modelling framework. In this way, the specific location of existing reservoirs inside a river basin is explicitly accounted for. Our goal is to develop a tool that can provide answers to the different issues involved in spatial water management in human-influenced contexts and at large modelling scales. The approach is tested for the Seine basin in France. Results are shown for model performance with and without the dam module. Also, a comparison with the lumped GR5J model highlights the improvements obtained in model performance by considering human influences more explicitly, and by facilitating parameter identifiability. This work opens up new perspectives for streamflow naturalization analyses and scenario-based spatial assessment of water resources under global change. References de Lavenne, A.; Thirel, G.; Andréassian, V.; Perrin, C. & Ramos, M.-H. (2016), 'Spatial variability of the parameters of a semi-distributed hydrological model', PIAHS 373, 87-94. Payan, J.-L.; Perrin, C.; Andréassian, V. & Michel, C. (2008), 'How can man-made water reservoirs be accounted for in a lumped rainfall-runoff model?', Water Resour. Res. 44(3), W03420.

A Web-based Distributed Voluntary Computing Platform for Large Scale Hydrological Computations

NASA Astrophysics Data System (ADS)

Demir, I.; Agliamzanov, R.

2014-12-01

Distributed volunteer computing can enable researchers and scientist to form large parallel computing environments to utilize the computing power of the millions of computers on the Internet, and use them towards running large scale environmental simulations and models to serve the common good of local communities and the world. Recent developments in web technologies and standards allow client-side scripting languages to run at speeds close to native application, and utilize the power of Graphics Processing Units (GPU). Using a client-side scripting language like JavaScript, we have developed an open distributed computing framework that makes it easy for researchers to write their own hydrologic models, and run them on volunteer computers. Users will easily enable their websites for visitors to volunteer sharing their computer resources to contribute running advanced hydrological models and simulations. Using a web-based system allows users to start volunteering their computational resources within seconds without installing any software. The framework distributes the model simulation to thousands of nodes in small spatial and computational sizes. A relational database system is utilized for managing data connections and queue management for the distributed computing nodes. In this paper, we present a web-based distributed volunteer computing platform to enable large scale hydrological simulations and model runs in an open and integrated environment.

Gravity modeling finds a large magma body in the deep crust below the Gulf of Naples, Italy.

PubMed

Fedi, M; Cella, F; D'Antonio, M; Florio, G; Paoletti, V; Morra, V

2018-05-29

We analyze a wide gravity low in the Campania Active Volcanic Area and interpret it by a large and deep source distribution of partially molten, low-density material from about 8 to 30 km depth. Given the complex spatial-temporal distribution of explosive volcanism in the area, we model the gravity data consistently with several volcanological and petrological constraints. We propose two possible models: one accounts for the coexistence, within the lower/intermediate crust, of large amounts of melts and cumulates besides country rocks. It implies a layered distribution of densities and, thus, a variation with depth of percentages of silicate liquids, cumulates and country rocks. The other reflects a fractal density distribution, based on the scaling exponent estimated from the gravity data. According to this model, the gravity low would be related to a distribution of melt pockets within solid rocks. Both density distributions account for the available volcanological and seismic constraints and can be considered as end-members of possible models compatible with gravity data. Such results agree with the general views about the roots of large areas of ignimbritic volcanism worldwide. Given the prolonged history of magmatism in the Campania area since Pliocene times, we interpret the detected low-density body as a developing batholith.

Using the Spatial Distribution of Installers to Define Solar Photovoltaic Markets

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

O'Shaughnessy, Eric; Nemet, Gregory F.; Darghouth, Naim

2016-09-01

Solar PV market research to date has largely relied on arbitrary jurisdictional boundaries, such as counties, to study solar PV market dynamics. This paper seeks to improve solar PV market research by developing a methodology to define solar PV markets. The methodology is based on the spatial distribution of solar PV installers. An algorithm is developed and applied to a rich dataset of solar PV installations to study the outcomes of the installer-based market definitions. The installer-based approach exhibits several desirable properties. Specifically, the higher market granularity of the installer-based approach will allow future PV market research to study themore » relationship between market dynamics and pricing with more precision.« less

[Evaluation on environmental quality of heavy metals in soils and vegetables based on geostatistics and GIS].

PubMed

Xie, Zheng-miao; Li, Jing; Wang, Bi-ling; Chen, Jian-jun

2006-10-01

Contents of heavy metals (Pb, Zn, Cd, Cu) in soils and vegetables from Dongguan town in Shangyu city, China were studied using geostatistical analysis and GIS technique to evaluate environmental quality. Based on the evaluation criteria, the distribution of the spatial variability of heavy metals in soil-vegetable system was mapped and analyzed. The results showed that the distribution of soil heavy metals in a large number of soil samples in Dongguan town was asymmetric. The contents of Zn and Cu were lower than those of Cd and Pb. The concentrations distribution of Pb, Zn, Cd and Cu in soils and vegetables were different in spatial variability. There was a close relationship between total and available contents of heavy metals in soil. The contents of Pb and Cd in green vegetables were higher than those of Zn and Cu and exceeded the national sanitation standards for vegetables.

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

NASA Astrophysics Data System (ADS)

Dobramysl, Ulrich; Tauber, Uwe C.

2012-02-01

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

Investigations on the droplet distributions in the atomization of kerosene jets in supersonic crossflows

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

Wu, Liyin; Wang, Zhen-guo, E-mail: wangzhenguo-wzg@163.com; Li, Qinglian

2015-09-07

Phase Doppler anemometry was applied to investigate the atomization processes of a kerosene jet injected into Ma = 1.86 crossflow. Physical behaviors, such as breakup and coalescence, are reproduced through the analysis of the spatial distribution of kerosene droplets' size. It is concluded that Sauter mean diameter distribution shape transforms into “I” type from “C” type as the atomization development. Simultaneously, the breakup of large droplets and the coalescence of small droplets can be observed throughout the whole atomization process.

Potential distribution dataset of honeybees in Indian Ocean Islands: Case study of Zanzibar Island.

PubMed

Mwalusepo, Sizah; Muli, Eliud; Nkoba, Kiatoko; Nguku, Everlyn; Kilonzo, Joseph; Abdel-Rahman, Elfatih M; Landmann, Tobias; Fakih, Asha; Raina, Suresh

2017-10-01

Honeybees ( Apis mellifera ) are principal insect pollinators, whose worldwide distribution and abundance is known to largely depend on climatic conditions. However, the presence records dataset on potential distribution of honeybees in Indian Ocean Islands remain less documented. Presence records in shape format and probability of occurrence of honeybees with different temperature change scenarios is provided in this article across Zanzibar Island. Maximum entropy (Maxent) package was used to analyse the potential distribution of honeybees. The dataset provides information on the current and future distribution of the honey bees in Zanzibar Island. The dataset is of great importance for improving stakeholders understanding of the role of temperature change on the spatial distribution of honeybees.

Hemispheric Connectivity and the Visual-Spatial Divergent-Thinking Component of Creativity

ERIC Educational Resources Information Center

Moore, Dana W.; Bhadelia, Rafeeque A.; Billings, Rebecca L.; Fulwiler, Carl; Heilman, Kenneth M.; Rood, Kenneth M. J.; Gansler, David A.

2009-01-01

Background/hypothesis: Divergent thinking is an important measurable component of creativity. This study tested the postulate that divergent thinking depends on large distributed inter- and intra-hemispheric networks. Although preliminary evidence supports increased brain connectivity during divergent thinking, the neural correlates of this…

Investigation of the near subsurface using acoustic to seismic coupling

USDA-ARS?s Scientific Manuscript database

Agricultural, hydrological and civil engineering applications have realized a need for information of the near subsurface over large areas. In order to obtain this spatially distributed data over such scales, the measurement technique must be highly mobile with a short acquisition time. Therefore, s...

ESTIMATING REGIONAL SPECIES RICHNESS USING A LIMITED NUMBER OF SURVEY UNITS

EPA Science Inventory

The accurate and precise estimation of species richness at large spatial scales using a limited number of survey units is of great significance for ecology and biodiversity conservation. We used the distribution data of native fish and resident breeding bird species compiled for ...

Terrestrial ecosystems and their change

Treesearch

Anatoly Z. Shvidenko; Eric Gustafson; A. David McGuire; Vjacheslav I. Kharuk; Dmitry G. Schepaschenko; Herman H. Shugart; Nadezhda M. Tchebakova; Natalia N. Vygodskaya; Alexander A. Onuchin; Daniel J. Hayes; Ian McCallum; Shamil Maksyutov; Ludmila V. Mukhortova; Amber J. Soja; Luca Belelli-Marchesini; Julia A. Kurbatova; Alexander V. Oltchev; Elena I. Parfenova; Jacquelyn K. Shuman

2012-01-01

This chapter considers the current state of Siberian terrestrial ecosystems, their spatial distribution, and major biometric characteristics. Ongoing climate change and the dramatic increase of accompanying anthropogenic pressure provide different but mostly negative impacts on Siberian ecosystems. Future climates of the region may lead to substantial drying on large...

Ricardo Oliveira | NREL

Science.gov Websites

the System Modeling & Geospatial Data Science Group in the Strategic Energy Analysis Center. Areas Publications Oliveira, R and Moreno, R. 2016. Harvesting, Integrating and Distributing Large Open Geospatial Datasets Using Free and Open-Source Software. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7

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

PubMed

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.

FRESHEM - Fresh-saline groundwater distribution in Zeeland (NL) derived from airborne EM

NASA Astrophysics Data System (ADS)

Siemon, Bernhard; van Baaren, Esther; Dabekaussen, Willem; Delsman, Joost; Gunnik, Jan; Karaoulis, Marios; de Louw, Perry; Oude Essink, Gualbert; Pauw, Pieter; Steuer, Annika; Meyer, Uwe

2017-04-01

In a setting of predominantly saline surface waters, the availability of fresh water for agricultural purposes is not obvious in Zeeland, The Netherlands. Canals and ditches are mainly brackish to saline due to saline seepage, which originates from old marine deposits and salt-water transgressions during historical times. The only available fresh groundwater is present in the form of freshwater lenses floating on top of the saline groundwater. This fresh groundwater is vital for agricultural, industrial, ecological, water conservation and drinking water functions. An essential first step for managing this fresh groundwater properly is to know the present spatial fresh-brackish-saline groundwater distribution. As traditional salinity monitoring is labour-intensive, airborne electromagnetics (AEM), which is fast and can cover large areas in short time, is an efficient alternative. A consortium of BGR, Deltares and TNO started FRESHEM Zeeland (FREsh Salt groundwater distribution by Helicopter ElectroMagnetic survey in the Province of Zeeland) in October 2014. Within 3x2 weeks of the first project year, the entire area of about 2000 km2 was surveyed using BGR's helicopter-borne geophysical system totalling to about 10,000 line-km. The HEM datasets of 17 subareas were carefully processed using advanced BGR in-house software and inverted to 2.5 Million resistivity-depth models. Ground truthing demonstrated that the large-scale HEM results fit very well with small-scale ground EM data (ECPT). Based on this spatial resistivity distribution, a 3D voxel model for Chloride concentration was derived for the entire province taking into account geological model data (GeoTOP) for the lithology correction and local in-situ groundwater measurements for the translation of water conductivity to Chloride concentration. The 3D voxel model enables stakeholders to implement spatial Chloride concentration in their groundwater models.

Prediction of Ba, Mn and Zn for tropical soils using iron oxides and magnetic susceptibility

NASA Astrophysics Data System (ADS)

Marques Júnior, José; Arantes Camargo, Livia; Reynaldo Ferracciú Alleoni, Luís; Tadeu Pereira, Gener; De Bortoli Teixeira, Daniel; Santos Rabelo de Souza Bahia, Angelica

2017-04-01

Agricultural activity is an important source of potentially toxic elements (PTEs) in soil worldwide but particularly in heavily farmed areas. Spatial distribution characterization of PTE contents in farming areas is crucial to assess further environmental impacts caused by soil contamination. Designing prediction models become quite useful to characterize the spatial variability of continuous variables, as it allows prediction of soil attributes that might be difficult to attain in a large number of samples through conventional methods. This study aimed to evaluate, in three geomorphic surfaces of Oxisols, the capacity for predicting PTEs (Ba, Mn, Zn) and their spatial variability using iron oxides and magnetic susceptibility (MS). Soil samples were collected from three geomorphic surfaces and analyzed for chemical, physical, mineralogical properties, as well as magnetic susceptibility (MS). PTE prediction models were calibrated by multiple linear regression (MLR). MLR calibration accuracy was evaluated using the coefficient of determination (R2). PTE spatial distribution maps were built using the values calculated by the calibrated models that reached the best accuracy by means of geostatistics. The high correlations between the attributes clay, MS, hematite (Hm), iron oxides extracted by sodium dithionite-citrate-bicarbonate (Fed), and iron oxides extracted using acid ammonium oxalate (Feo) with the elements Ba, Mn, and Zn enabled them to be selected as predictors for PTEs. Stepwise multiple linear regression showed that MS and Fed were the best PTE predictors individually, as they promoted no significant increase in R2 when two or more attributes were considered together. The MS-calibrated models for Ba, Mn, and Zn prediction exhibited R2 values of 0.88, 0.66, and 0.55, respectively. These are promising results since MS is a fast, cheap, and non-destructive tool, allowing the prediction of a large number of samples, which in turn enables detailed mapping of large areas. MS predicted values enabled the characterization and the understanding of spatial variability of the studied PTEs.

Temporal and spatial structure in a daily wildfire-start data set from the western United States (198696)

USGS Publications Warehouse

Bartlein, P.J.; Hostetler, S.W.; Shafer, S.L.; Holman, J.O.; Solomon, A.M.

2008-01-01

The temporal and spatial structure of 332 404 daily fire-start records from the western United States for the period 1986 through 1996 is illustrated using several complimentary visualisation techniques. We supplement maps and time series plots with Hovmo??ller diagrams that reduce the spatial dimensionality of the daily data in order to reveal the underlying space?time structure. The mapped distributions of all lightning- and human-started fires during the 11-year interval show similar first-order patterns that reflect the broad-scale distribution of vegetation across the West and the annual cycle of climate. Lightning-started fires are concentrated in the summer half-year and occur in widespread outbreaks that last a few days and reflect coherent weather-related controls. In contrast, fires started by humans occur throughout the year and tend to be concentrated in regions surrounding large-population centres or intensive-agricultural areas. Although the primary controls of human-started fires are their location relative to burnable fuel and the level of human activity, spatially coherent, weather-related variations in their incidence can also be noted. ?? IAWF 2008.

Distributions and Changes of Carbonate Parameters Along the U.S. East Coast

NASA Astrophysics Data System (ADS)

Xu, Y. Y.; Cai, W. J.; Wanninkhof, R. H.; Salisbury, J., II

2017-12-01

On top of anthropogenic climate change, upwelling, eutrophication, river discharge, and interactions with the open ocean have affected carbonate chemistry in coastal waters. In this study, we present the large-scale variations of carbonate parameters along the U.S. east coast using in situ observations obtained during an East Coast Ocean Acidification (ECOA) cruise in summer 2015. Compare with previous large-scale cruises along the east coast, the ECOA cruise increases spatial coverage in the Gulf of Marine region and has more offshore stations for a better understanding of carbon dynamics in coastal waters and their interactions with open ocean waters. Our results show that the spatial distribution of water mass properties set up the large-scale advection of salt and heat and the distribution of total alkalinity (TA). However, dissolved inorganic carbon (DIC) shows a distinct pattern. Coastal water pH displays high variability in the Gulf of Maine and the Mid-Atlantic Bight (MAB). But it is relatively homogeneous in the South Atlantic Bight (SAB). In contrast, the distribution of aragonite saturation state (Ω) has an increase pattern from north to south similar to those of TA, SST, and SSS. A mechanistic discussion will be presented to understand the controls on Ω in eastern coastal waters. A comparison with previous cruises also suggests very different changes of pH and Ω in the MAB and SAB. Preliminary analysis suggests an overall increase in surface pH and Ω in the MAB. In contrast, pH and Ω in the SAB surface waters decrease over the past two decades. This work serves as a platform for the monitoring of large-scale carbon cycling in the U.S. east coast. It is also important to identify the physical and biogeochemical processes that affect these distributions and changes over time for a better understanding of carbon cycling and ocean acidification in coastal waters.

Spatial correlation analysis of urban traffic state under a perspective of community detection

NASA Astrophysics Data System (ADS)

Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

2018-05-01

Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

Robustness of spatial micronetworks

NASA Astrophysics Data System (ADS)

McAndrew, Thomas C.; Danforth, Christopher M.; Bagrow, James P.

2015-04-01

Power lines, roadways, pipelines, and other physical infrastructure are critical to modern society. These structures may be viewed as spatial networks where geographic distances play a role in the functionality and construction cost of links. Traditionally, studies of network robustness have primarily considered the connectedness of large, random networks. Yet for spatial infrastructure, physical distances must also play a role in network robustness. Understanding the robustness of small spatial networks is particularly important with the increasing interest in microgrids, i.e., small-area distributed power grids that are well suited to using renewable energy resources. We study the random failures of links in small networks where functionality depends on both spatial distance and topological connectedness. By introducing a percolation model where the failure of each link is proportional to its spatial length, we find that when failures depend on spatial distances, networks are more fragile than expected. Accounting for spatial effects in both construction and robustness is important for designing efficient microgrids and other network infrastructure.

Spatial and temporal distribution of the vibrionaceae in coastal waters of Hawaii, Australia, and France.

PubMed

Jones, B W; Maruyama, A; Ouverney, C C; Nishiguchi, M K

2007-08-01

Relatively little is known about large-scale spatial and temporal fluctuations in bacterioplankton, especially within the bacterial families. In general, however, a number of abiotic factors (namely, nutrients and temperature) appear to influence distribution. Community dynamics within the Vibrionaceae are of particular interest to biologists because this family contains a number of important pathogenic, commensal, and mutualist species. Of special interest to this study is the mutualism between sepiolid squids and Vibrio fischeri and Vibrio logei, where host squids seed surrounding waters daily with their bacterial partners. This study seeks to examine the spatial and temporal distribution of the Vibrionaceae with respect to V. fischeri and V. logei in Hawaii, southeastern Australia, and southern France sampling sites. In particular, we examine how the presence of sepiolid squid hosts influences community population structure within the Vibrionaceae. We found that abiotic (temperature) and biotic (host distribution) factors both influence population dynamics. In Hawaii, three sites within squid host habitat contained communities of Vibrionaceae with higher proportions of V. fischeri. In Australia, V. fischeri numbers at host collection sites were greater than other populations; however, there were no spatial or temporal patterns seen at other sample sites. In France, host presence did not appear to influence Vibrio communities, although sampled populations were significantly greater in the winter than summer sampling periods. Results of this study demonstrate the importance of understanding how both abiotic and biotic factors interact to influence bacterial community structure within the Vibrionaceae.

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

PubMed Central

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

2011-01-01

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

Uncertainty in gridded CO 2 emissions estimates

DOE PAGES

Hogue, Susannah; Marland, Eric; Andres, Robert J.; ...

2016-05-19

We are interested in the spatial distribution of fossil-fuel-related emissions of CO 2 for both geochemical and geopolitical reasons, but it is important to understand the uncertainty that exists in spatially explicit emissions estimates. Working from one of the widely used gridded data sets of CO 2 emissions, we examine the elements of uncertainty, focusing on gridded data for the United States at the scale of 1° latitude by 1° longitude. Uncertainty is introduced in the magnitude of total United States emissions, the magnitude and location of large point sources, the magnitude and distribution of non-point sources, and from themore » use of proxy data to characterize emissions. For the United States, we develop estimates of the contribution of each component of uncertainty. At 1° resolution, in most grid cells, the largest contribution to uncertainty comes from how well the distribution of the proxy (in this case population density) represents the distribution of emissions. In other grid cells, the magnitude and location of large point sources make the major contribution to uncertainty. Uncertainty in population density can be important where a large gradient in population density occurs near a grid cell boundary. Uncertainty is strongly scale-dependent with uncertainty increasing as grid size decreases. In conclusion, uncertainty for our data set with 1° grid cells for the United States is typically on the order of ±150%, but this is perhaps not excessive in a data set where emissions per grid cell vary over 8 orders of magnitude.« less

Volcanic forcing for climate modeling: a new microphysics-based dataset covering years 1600-present

NASA Astrophysics Data System (ADS)

Arfeuille, F.; Weisenstein, D.; Mack, H.; Rozanov, E.; Peter, T.; Brönnimann, S.

2013-02-01

As the understanding and representation of the impacts of volcanic eruptions on climate have improved in the last decades, uncertainties in the stratospheric aerosol forcing from large eruptions are now not only linked to visible optical depth estimates on a global scale but also to details on the size, latitude and altitude distributions of the stratospheric aerosols. Based on our understanding of these uncertainties, we propose a new model-based approach to generating a volcanic forcing for General-Circulation-Model (GCM) and Chemistry-Climate-Model (CCM) simulations. This new volcanic forcing, covering the 1600-present period, uses an aerosol microphysical model to provide a realistic, physically consistent treatment of the stratospheric sulfate aerosols. Twenty-six eruptions were modeled individually using the latest available ice cores aerosol mass estimates and historical data on the latitude and date of eruptions. The evolution of aerosol spatial and size distribution after the sulfur dioxide discharge are hence characterized for each volcanic eruption. Large variations are seen in hemispheric partitioning and size distributions in relation to location/date of eruptions and injected SO2 masses. Results for recent eruptions are in good agreement with observations. By providing accurate amplitude and spatial distributions of shortwave and longwave radiative perturbations by volcanic sulfate aerosols, we argue that this volcanic forcing may help refine the climate model responses to the large volcanic eruptions since 1600. The final dataset consists of 3-D values (with constant longitude) of spectrally resolved extinction coefficients, single scattering albedos and asymmetry factors calculated for different wavelength bands upon request. Surface area densities for heterogeneous chemistry are also provided.

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

NASA Astrophysics Data System (ADS)

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

2007-02-01

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

ELECTRON ACCELERATION BY CASCADING RECONNECTION IN THE SOLAR CORONA. II. RESISTIVE ELECTRIC FIELD EFFECTS

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

Zhou, X.; Gan, W.; Liu, S.

We investigate electron acceleration by electric fields induced by cascading reconnections in current sheets trailing coronal mass ejections via a test particle approach in the framework of the guiding-center approximation. Although the resistive electric field is much weaker than the inductive electric field, the electron acceleration is still dominated by the former. Anomalous resistivity η is switched on only in regions where the current carrier’s drift velocity is large enough. As a consequence, electron acceleration is very sensitive to the spatial distribution of the resistive electric fields, and electrons accelerated in different segments of the current sheet have different characteristics.more » Due to the geometry of the 2.5-dimensional electromagnetic fields and strong resistive electric field accelerations, accelerated high-energy electrons can be trapped in the corona, precipitating into the chromosphere or escaping into interplanetary space. The trapped and precipitating electrons can reach a few MeV within 1 s and have a very hard energy distribution. Spatial structure of the acceleration sites may also introduce breaks in the electron energy distribution. Most of the interplanetary electrons reach hundreds of keV with a softer distribution. To compare with observations of solar flares and electrons in solar energetic particle events, we derive hard X-ray spectra produced by the trapped and precipitating electrons, fluxes of the precipitating and interplanetary electrons, and electron spatial distributions.« less

Coherence switching of a vertical-cavity semiconductor-laser for multimode biomedical imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cao, Hui; Knitter, Sebastian; Liu, Changgeng; Redding, Brandon; Khokha, Mustafa Kezar; Choma, Michael Andrew

2017-02-01

Speckle formation is a limiting factor when using coherent sources for imaging and sensing, but can provide useful information about the motion of an object. Illumination sources with tunable spatial coherence are therefore desirable as they can offer both speckled and speckle-free images. Efficient methods of coherence switching have been achieved with a solid-state degenerate laser, and here we demonstrate a semiconductor-based degenerate laser system that can be switched between a large number of mutually incoherent spatial modes and few-mode operation. Our system is designed around a semiconductor gain element, and overcomes barriers presented by previous low spatial coherence lasers. The gain medium is an electrically-pumped vertical external cavity surface emitting laser (VECSEL) with a large active area. The use of a degenerate external cavity enables either distributing the laser emission over a large ( 1000) number of mutually incoherent spatial modes or concentrating emission to few modes by using a pinhole in the Fourier plane of the self-imaging cavity. To demonstrate the unique potential of spatial coherence switching for multimodal biomedical imaging, we use both low and high spatial coherence light generated by our VECSEL-based degenerate laser for imaging embryo heart function in Xenopus, an important animal model of heart disease. The low-coherence illumination is used for high-speed (100 frames per second) speckle-free imaging of dynamic heart structure, while the high-coherence emission is used for laser speckle contrast imaging of the blood flow.

Properties and spatial distribution of galaxy superclusters

NASA Astrophysics Data System (ADS)

Liivamägi, Lauri Juhan

2017-01-01

Astronomy is a science that can offer plenty of unforgettable imagery, and the large-scale distribution of galaxies is no exception. Among the first features the viewer's eye is likely to be drawn to, are large concentrations of galaxies - galaxy superclusters, contrasting to the seemingly empty regions beside them. Superclusters can extend from tens to over hundred megaparsecs, they contain from hundreds to thousands of galaxies, and many galaxy groups and clusters. Unlike galaxy clusters, superclusters are clearly unrelaxed systems, not gravitationally bound as crossing times exceed the age of the universe, and show little to no radial symmetry. Superclusters, as part of the large-scale structure, are sensitive to the initial power spectrum and the following evolution. They are massive enough to leave an imprint on the cosmic microwave background radiation. Superclusters can also provide an unique environment for their constituent galaxies and galaxy clusters. In this study we used two different observational and one simulated galaxy samples to create several catalogues of structures that, we think, correspond to what are generally considered galaxy superclusters. Superclusters were delineated as continuous over-dense regions in galaxy luminosity density fields. When calculating density fields several corrections were applied to remove small-scale redshift distortions and distance-dependent selection effects. Resulting catalogues of objects display robust statistical properties, showing that flux-limited galaxy samples can be used to create nearly volume-limited catalogues of superstructures. Generally, large superclusters can be regarded as massive, often branching filamentary structures, that are mainly characterised by their length. Smaller superclusters, on the other hand, can display a variety of shapes. Spatial distribution of superclusters shows large-scale variations, with high-density concentrations often found in semi-regularly spaced groups. Future studies are needed to quantify the relations between superclusters and finer details of the galaxy distribution. Supercluster catalogues from this thesis have already been used in numerous other studies.

Behavioral response races, predator-prey shell games, ecology of fear, and patch use of pumas and their ungulate prey.

PubMed

Laundré, John W

2010-10-01

The predator-prey shell game predicts random movement of prey across the landscape, whereas the behavioral response race and landscape of fear models predict that there should be a negative relationship between the spatial distribution of a predator and its behaviorally active prey. Additionally, prey have imperfect information on the whereabouts of their predator, which the predator should incorporate in its patch use strategy. I used a one-predator-one-prey system, puma (Puma concolor)-mule deer (Odocoileus hemionus) to test the following predictions regarding predator-prey distribution and patch use by the predator. (1) Pumas will spend more time in high prey risk/low prey use habitat types, while deer will spend their time in low-risk habitats. Pumas should (2) select large forage patches more often, (3) remain in large patches longer, and (4) revisit individual large patches more often than individual smaller ones. I tested these predictions with an extensive telemetry data set collected over 16 years in a study area of patchy forested habitat. When active, pumas spent significantly less time in open areas of low intrinsic predation risk than did deer. Pumas used large patches more than expected, revisited individual large patches significantly more often than smaller ones, and stayed significantly longer in larger patches than in smaller ones. The results supported the prediction of a negative relationship in the spatial distribution of a predator and its prey and indicated that the predator is incorporating the prey's imperfect information about its presence. These results indicate a behavioral complexity on the landscape scale that can have far-reaching impacts on predator-prey interactions.

Efficient statistical mapping of avian count data

USGS Publications Warehouse

Royle, J. Andrew; Wikle, C.K.

2005-01-01

We develop a spatial modeling framework for count data that is efficient to implement in high-dimensional prediction problems. We consider spectral parameterizations for the spatially varying mean of a Poisson model. The spectral parameterization of the spatial process is very computationally efficient, enabling effective estimation and prediction in large problems using Markov chain Monte Carlo techniques. We apply this model to creating avian relative abundance maps from North American Breeding Bird Survey (BBS) data. Variation in the ability of observers to count birds is modeled as spatially independent noise, resulting in over-dispersion relative to the Poisson assumption. This approach represents an improvement over existing approaches used for spatial modeling of BBS data which are either inefficient for continental scale modeling and prediction or fail to accommodate important distributional features of count data thus leading to inaccurate accounting of prediction uncertainty.

Spatial abundance models and seasonal distribution for guanaco (Lama guanicoe) in central Tierra del Fuego, Argentina.

PubMed

Flores, Celina E; Deferrari, Guillermo; Collado, Leonardo; Escobar, Julio; Schiavini, Adrián

2018-01-01

Spatially explicit modelling allows to estimate population abundance and predict species' distribution in relation to environmental factors. Abiotic factors are the main determinants of a herbivore´s response to environmental heterogeneity on large spatiotemporal scales. We assessed the influence of elevation, geographic location and distance to the coast on the seasonal abundance and distribution of guanaco (Lama guanicoe) in central Tierra del Fuego, by means of spatially explicit modelling. The estimated abundance was 23,690 individuals for the non-breeding season and 33,928 individuals for the breeding season. The factors influencing distribution and abundance revealed to be the elevation for the non-breeding season, and the distance to the coast and geographic location for the breeding season. The southwest of the study area presented seasonal abundance variation and the southeast and northeast presented high abundance during both seasons. The elevation would be the driving factor of guanaco distribution, as individuals move to lower areas during the non-breeding season and ascend to high areas during the breeding season. Our results confirm that part of the guanaco population performs seasonal migratory movements and that the main valleys present important wintering habitats for guanacos as well as up-hill zones during summer. This type of study would help to avoid problems of scale mismatch and achieve better results in management actions and is an example of how to assess important seasonal habitats from evaluations of abundance and distribution patterns.

Spatial abundance models and seasonal distribution for guanaco (Lama guanicoe) in central Tierra del Fuego, Argentina

PubMed Central

Deferrari, Guillermo; Collado, Leonardo; Escobar, Julio; Schiavini, Adrián

2018-01-01

Spatially explicit modelling allows to estimate population abundance and predict species’ distribution in relation to environmental factors. Abiotic factors are the main determinants of a herbivore´s response to environmental heterogeneity on large spatiotemporal scales. We assessed the influence of elevation, geographic location and distance to the coast on the seasonal abundance and distribution of guanaco (Lama guanicoe) in central Tierra del Fuego, by means of spatially explicit modelling. The estimated abundance was 23,690 individuals for the non-breeding season and 33,928 individuals for the breeding season. The factors influencing distribution and abundance revealed to be the elevation for the non-breeding season, and the distance to the coast and geographic location for the breeding season. The southwest of the study area presented seasonal abundance variation and the southeast and northeast presented high abundance during both seasons. The elevation would be the driving factor of guanaco distribution, as individuals move to lower areas during the non-breeding season and ascend to high areas during the breeding season. Our results confirm that part of the guanaco population performs seasonal migratory movements and that the main valleys present important wintering habitats for guanacos as well as up-hill zones during summer. This type of study would help to avoid problems of scale mismatch and achieve better results in management actions and is an example of how to assess important seasonal habitats from evaluations of abundance and distribution patterns. PMID:29782523

Adapting geostatistics to analyze spatial and temporal trends in weed populations

USDA-ARS?s Scientific Manuscript database

Geostatistics were originally developed in mining to estimate the location, abundance and quality of ore over large areas from soil samples to optimize future mining efforts. Here, some of these methods were adapted to weeds to account for a limited distribution area (i.e., inside a field), variatio...

Efficient multi-objective calibration of a computationally intensive hydrologic model with parallel computing software in Python

USDA-ARS?s Scientific Manuscript database

With enhanced data availability, distributed watershed models for large areas with high spatial and temporal resolution are increasingly used to understand water budgets and examine effects of human activities and climate change/variability on water resources. Developing parallel computing software...

FOREST SOIL INFORMATION FOR ENVIRONMENTAL ASSESSMENT IN THE WESTERN OREGON CASCADES BASED ON LANDTYPE MAPPING

EPA Science Inventory

Forest health monitoring and other environmental assessments require information on the spatial distribution of basic soil physical and chemical properties. Traditional soil surveys are not available for large areas of forestland in the western US but there are some soil resour...

Spatial Structure of Seagrass Suggests That Size-Dependent Plant Traits Have a Strong Influence on the Distribution and Maintenance of Tropical Multispecies Meadows

PubMed Central

Ooi, Jillian L. S.; Van Niel, Kimberly P.; Kendrick, Gary A.; Holmes, Karen W.

2014-01-01

Background Seagrass species in the tropics occur in multispecies meadows. How these meadows are maintained through species co-existence and what their ecological drivers may be has been an overarching question in seagrass biogeography. In this study, we quantify the spatial structure of four co-existing species and infer potential ecological processes from these structures. Methods and Results Species presence/absence data were collected using underwater towed and dropped video cameras in Pulau Tinggi, Malaysia. The geostatistical method, utilizing semivariograms, was used to describe the spatial structure of Halophila spp, Halodule uninervis, Syringodium isoetifolium and Cymodocea serrulata. Species had spatial patterns that were oriented in the along-shore and across-shore directions, nested with larger species in meadow interiors, and consisted of multiple structures that indicate the influence of 2–3 underlying processes. The Linear Model of Coregionalization (LMC) was used to estimate the amount of variance contributing to the presence of a species at specific spatial scales. These distances were <2.5 m (micro-scale), 2.5–50 m (fine-scale) and >50 m (broad-scale) in the along-shore; and <2.5 m (micro-scale), 2.5–140 m (fine-scale) and >140 m (broad-scale) in the across-shore. The LMC suggests that smaller species (Halophila spp and H. uninervis) were most influenced by broad-scale processes such as hydrodynamics and water depth whereas large, localised species (S. isoetifolium and C. serrulata) were more influenced by finer-scale processes such as sediment burial, seagrass colonization and growth, and physical disturbance. Conclusion In this study, we provide evidence that spatial structure is distinct even when species occur in well-mixed multispecies meadows, and we suggest that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical marine plant communities. This study offers a contrast from previous spatial models of seagrasses which have largely focused on monospecific temperate meadows. PMID:24497978

Spatial structure of seagrass suggests that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical multispecies meadows.

PubMed

Ooi, Jillian L S; Van Niel, Kimberly P; Kendrick, Gary A; Holmes, Karen W

2014-01-01

Seagrass species in the tropics occur in multispecies meadows. How these meadows are maintained through species co-existence and what their ecological drivers may be has been an overarching question in seagrass biogeography. In this study, we quantify the spatial structure of four co-existing species and infer potential ecological processes from these structures. Species presence/absence data were collected using underwater towed and dropped video cameras in Pulau Tinggi, Malaysia. The geostatistical method, utilizing semivariograms, was used to describe the spatial structure of Halophila spp, Halodule uninervis, Syringodium isoetifolium and Cymodocea serrulata. Species had spatial patterns that were oriented in the along-shore and across-shore directions, nested with larger species in meadow interiors, and consisted of multiple structures that indicate the influence of 2-3 underlying processes. The Linear Model of Coregionalization (LMC) was used to estimate the amount of variance contributing to the presence of a species at specific spatial scales. These distances were <2.5 m (micro-scale), 2.5-50 m (fine-scale) and >50 m (broad-scale) in the along-shore; and <2.5 m (micro-scale), 2.5-140 m (fine-scale) and >140 m (broad-scale) in the across-shore. The LMC suggests that smaller species (Halophila spp and H. uninervis) were most influenced by broad-scale processes such as hydrodynamics and water depth whereas large, localised species (S. isoetifolium and C. serrulata) were more influenced by finer-scale processes such as sediment burial, seagrass colonization and growth, and physical disturbance. In this study, we provide evidence that spatial structure is distinct even when species occur in well-mixed multispecies meadows, and we suggest that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical marine plant communities. This study offers a contrast from previous spatial models of seagrasses which have largely focused on monospecific temperate meadows.

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

PubMed

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

2015-01-01

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

Lightning characteristics of derecho producing mesoscale convective systems

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Spatial Distribution of the Coefficient of Variation for the Paleo-Earthquakes in Japan

NASA Astrophysics Data System (ADS)

Nomura, S.; Ogata, Y.

2015-12-01

Renewal processes, point prccesses in which intervals between consecutive events are independently and identically distributed, are frequently used to describe this repeating earthquake mechanism and forecast the next earthquakes. However, one of the difficulties in applying recurrent earthquake models is the scarcity of the historical data. Most studied fault segments have few, or only one observed earthquake that often have poorly constrained historic and/or radiocarbon ages. The maximum likelihood estimate from such a small data set can have a large bias and error, which tends to yield high probability for the next event in a very short time span when the recurrence intervals have similar lengths. On the other hand, recurrence intervals at a fault depend on the long-term slip rate caused by the tectonic motion in average. In addition, recurrence times are also fluctuated by nearby earthquakes or fault activities which encourage or discourage surrounding seismicity. These factors have spatial trends due to the heterogeneity of tectonic motion and seismicity. Thus, this paper introduces a spatial structure on the key parameters of renewal processes for recurrent earthquakes and estimates it by using spatial statistics. Spatial variation of mean and variance parameters of recurrence times are estimated in Bayesian framework and the next earthquakes are forecasted by Bayesian predictive distributions. The proposal model is applied for recurrent earthquake catalog in Japan and its result is compared with the current forecast adopted by the Earthquake Research Committee of Japan.

Spatial scale, means and gradients of hydrographic variables define pelagic seascapes of bluefin and bullet tuna spawning distribution.

PubMed

Alvarez-Berastegui, Diego; Ciannelli, Lorenzo; Aparicio-Gonzalez, Alberto; Reglero, Patricia; Hidalgo, Manuel; López-Jurado, Jose Luis; Tintoré, Joaquín; Alemany, Francisco

2014-01-01

Seascape ecology is an emerging discipline focused on understanding how features of the marine habitat influence the spatial distribution of marine species. However, there is still a gap in the development of concepts and techniques for its application in the marine pelagic realm, where there are no clear boundaries delimitating habitats. Here we demonstrate that pelagic seascape metrics defined as a combination of hydrographic variables and their spatial gradients calculated at an appropriate spatial scale, improve our ability to model pelagic fish distribution. We apply the analysis to study the spawning locations of two tuna species: Atlantic bluefin and bullet tuna. These two species represent a gradient in life history strategies. Bluefin tuna has a large body size and is a long-distant migrant, while bullet tuna has a small body size and lives year-round in coastal waters within the Mediterranean Sea. The results show that the models performance incorporating the proposed seascape metrics increases significantly when compared with models that do not consider these metrics. This improvement is more important for Atlantic bluefin, whose spawning ecology is dependent on the local oceanographic scenario, than it is for bullet tuna, which is less influenced by the hydrographic conditions. Our study advances our understanding of how species perceive their habitat and confirms that the spatial scale at which the seascape metrics provide information is related to the spawning ecology and life history strategy of each species.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-01-01

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

Monitoring carnivore populations at the landscape scale: occupancy modelling of tigers from sign surveys

USGS Publications Warehouse

Karanth, Kota Ullas; Gopalaswamy, Arjun M.; Kumar, Narayanarao Samba; Vaidyanathan, Srinivas; Nichols, James D.; MacKenzie, Darryl I.

2011-01-01

1. Assessing spatial distributions of threatened large carnivores at landscape scales poses formidable challenges because of their rarity and elusiveness. As a consequence of logistical constraints, investigators typically rely on sign surveys. Most survey methods, however, do not explicitly address the central problem of imperfect detections of animal signs in the field, leading to underestimates of true habitat occupancy and distribution. 2. We assessed habitat occupancy for a tiger Panthera tigris metapopulation across a c. 38 000-km2 landscape in India, employing a spatially replicated survey to explicitly address imperfect detections. Ecological predictions about tiger presence were confronted with sign detection data generated from occupancy sampling of 205 sites, each of 188 km2. 3. A recent occupancy model that considers Markovian dependency among sign detections on spatial replicates performed better than the standard occupancy model (ΔAIC = 184·9). A formulation of this model that fitted the data best showed that density of ungulate prey and levels of human disturbance were key determinants of local tiger presence. Model averaging resulted in a replicate-level detection probability [inline image] = 0·17 (0·17) for signs and a tiger habitat occupancy estimate of [inline image] = 0·665 (0·0857) or 14 076 (1814) km2 of potential habitat of 21 167 km2. In contrast, a traditional presence-versus-absence approach underestimated occupancy by 47%. Maps of probabilities of local site occupancy clearly identified tiger source populations at higher densities and matched observed tiger density variations, suggesting their potential utility for population assessments at landscape scales. 4. Synthesis and applications. Landscape-scale sign surveys can efficiently assess large carnivore spatial distributions and elucidate the factors governing their local presence, provided ecological and observation processes are both explicitly modelled. Occupancy sampling using spatial replicates can be used to reliably and efficiently identify tiger population sources and help monitor metapopulations. Our results reinforce earlier findings that prey depletion and human disturbance are key drivers of local tiger extinctions and tigers can persist even in human-dominated landscapes through effective protection of source populations. Our approach facilitates efficient targeting of tiger conservation interventions and, more generally, provides a basis for the reliable integration of large carnivore monitoring data between local and landscape scales.

Understanding the brain through its spatial structure

NASA Astrophysics Data System (ADS)

Morrison, Will Zachary

The spatial location of cells in neural tissue can be easily extracted from many imaging modalities, but the information contained in spatial relationships between cells is seldom utilized. This is because of a lack of recognition of the importance of spatial relationships to some aspects of brain function, and the reflection in spatial statistics of other types of information. The mathematical tools necessary to describe spatial relationships are also unknown to many neuroscientists, and biologists in general. We analyze two cases, and show that spatial relationships can be used to understand the role of a particular type of cell, the astrocyte, in Alzheimer's disease, and that the geometry of axons in the brain's white matter sheds light on the process of establishing connectivity between areas of the brain. Astrocytes provide nutrients for neuronal metabolism, and regulate the chemical environment of the brain, activities that require manipulation of spatial distributions (of neurotransmitters, for example). We first show, through the use of a correlation function, that inter-astrocyte forces determine the size of independent regulatory domains in the cortex. By examining the spatial distribution of astrocytes in a mouse model of Alzheimer's Disease, we determine that astrocytes are not actively transported to fight the disease, as was previously thought. The paths axons take through the white matter determine which parts of the brain are connected, and how quickly signals are transmitted. The rules that determine these paths (i.e. shortest distance) are currently unknown. By measurement of axon orientation distributions using three-point correlation functions and the statistics of axon turning and branching, we reveal that axons are restricted to growth in three directions, like a taxicab traversing city blocks, albeit in three-dimensions. We show how geometric restrictions at the small scale are related to large-scale trajectories. Finally we discuss the implications of this finding for experimental and theoretical connectomics.

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

Kassianov, Evgueni I.; Riley, Erin A.; Kleiss, Jessica

Cloud amount is an essential and extensively used macrophysical parameter of cumulus clouds. It is commonly defined as a cloud fraction (CF) from zenith-pointing ground-based active and passive remote sensing. However, conventional retrievals of CF from the remote sensing data with very narrow field-of-view (FOV) may not be representative of the surrounding area. Here we assess its representativeness using an integrated dataset collected at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site in Oklahoma, USA. For our assessment with focus on selected days with single-layer cumulus clouds (2005-2016), we include the narrow-FOVmore » ARM Active Remotely Sensed Clouds Locations (ARSCL) and large-FOV Total Sky Imager (TSI) cloud products, the 915-MHz Radar Wind Profiler (RWP) measurements of wind speed and direction, and also high-resolution satellite images from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS). We demonstrate that a root-mean-square difference (RMSD) between the 15-min averaged ARSCL cloud fraction (CF) and the 15-min averaged TSI fractional sky cover (FSC) is large (up to 0.3). We also discuss how the horizontal distribution of clouds can modify the obtained large RMSD using a new uniformity metric. The latter utilizes the spatial distribution of the FSC over the 100° FOV TSI images obtained with high temporal resolution (30 sec sampling). We demonstrate that cases with more uniform spatial distribution of FSC show better agreement between the narrow-FOV CF and large-FOV FSC, reducing the RMSD by up to a factor of 2.« less

High-mass-resolution MALDI mass spectrometry imaging reveals detailed spatial distribution of metabolites and lipids in roots of barley seedlings in response to salinity stress.

PubMed

Sarabia, Lenin D; Boughton, Berin A; Rupasinghe, Thusitha; van de Meene, Allison M L; Callahan, Damien L; Hill, Camilla B; Roessner, Ute

2018-01-01

Mass spectrometry imaging (MSI) is a technology that enables the visualization of the spatial distribution of hundreds to thousands of metabolites in the same tissue section simultaneously. Roots are below-ground plant organs that anchor plants to the soil, take up water and nutrients, and sense and respond to external stresses. Physiological responses to salinity are multifaceted and have predominantly been studied using whole plant tissues that cannot resolve plant salinity responses spatially. This study aimed to use a comprehensive approach to study the spatial distribution and profiles of metabolites, and to quantify the changes in the elemental content in young developing barley seminal roots before and after salinity stress. Here, we used a combination of liquid chromatography-mass spectrometry (LC-MS), inductively coupled plasma mass spectrometry (ICP-MS), and matrix-assisted laser desorption/ionization (MALDI-MSI) platforms to profile and analyze the spatial distribution of ions, metabolites and lipids across three anatomically different barley root zones before and after a short-term salinity stress (150 mM NaCl). We localized, visualized and discriminated compounds in fine detail along longitudinal root sections and compared ion, metabolite, and lipid composition before and after salt stress. Large changes in the phosphatidylcholine (PC) profiles were observed as a response to salt stress with PC 34:n showing an overall reduction in salt treated roots. ICP-MS analysis quantified changes in the elemental content of roots with increases of Na + and decreases of K + content. Our results established the suitability of combining three mass spectrometry platforms to analyze and map ionic and metabolic responses to salinity stress in plant roots and to elucidate tolerance mechanisms in response to abiotic stress, such as salinity stress.

Molecular insights into seed dispersal mutualisms driving plant population recruitment

NASA Astrophysics Data System (ADS)

García, Cristina; Grivet, Delphine

2011-11-01

Most plant species require mutualistic interactions with animals to fulfil their demographic cycle. In this regard frugivory (i.e., the intake of fruits by animals) enhances natural regeneration by mobilizing a large amount of seeds from source trees to deposition sites across the landscape. By doing so, frugivores move propagules, and the genotypes they harbour creating the spatial, ecological, and genetic environment under which subsequent recruitment proceeds. Recruitment patterns can be envisioned as the result of two density- and distance-dependent processes: seed dispersal and seed/seedling survival (the Janzen-Connell model). Population genetic studies add another layer of complexity for understanding the fate of dispersed propagules: the genetic relatedness among neighbouring seeds within a seed clump, a major outcome of frugivore activity, modifies their chances of germinating and surviving. Yet, we virtually ignore how the spatial distribution of maternal progenies and recruitment patterns relate with each other in frugivore-generated seed rains. Here we focus on the critical role of frugivore-mediated seed dispersal in shaping the spatial distribution of maternal progenies in the seed rain. We first examine which genetic mechanisms underlying recruitment are influenced by the spatial distribution of maternal progenies. Next, we examine those studies depicting the spatial distribution of maternal progenies in a frugivore-generated seed rain. In doing so, we briefly review the most suitable analytical approaches applied to track the contribution of fruiting trees to the seed rain based on molecular data. Then we look more specifically at the role of distinct frugivore guilds in determining maternal genetic correlations and their expected consequences for recruitment patterns. Finally we posit some general conclusions and suggest future research directions that would provide a more comprehensive understanding of the ecological and evolutionary consequences of dispersal mutualisms in plant populations.

Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes

NASA Astrophysics Data System (ADS)

Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.

2017-12-01

Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), soil properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn affect the available soil moisture content. Interestingly, changes in soil properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation differences amplify the soil moisture variability of semi-arid landscapes.

Mapping the spatial distribution of star formation in cluster galaxies at z ~0.5 with the Grism Lens-Amplified Survey from Space (GLASS)

NASA Astrophysics Data System (ADS)

Vulcani, Benedetta

2015-08-01

What physical processes regulate star formation in dense environments? Understanding why galaxy evolution is environment dependent is one of the key questions of current astrophysics. I will present the first characterization of the spatial distribution of star formation in cluster galaxies at z~0.5, in order to quantify the role of different physical processes that are believed to be responsible for shutting down star formation. The analysis makes use of data from the Grism Lens-Amplified Survey from Space (GLASS), a large HST cycle-21 program targeting 10 massive galaxy clusters with extensive HST imaging from CLASH and the Frontier Field Initiative. The program consists of 140 primary and 140 parallel orbits of near-infrared WCF3 and optical ACS slitless grism observations, which result in 3D spectroscopy of hundreds of galaxies. The grism data are used to produce spatially resolved maps of the star formation density, while the stellar mass density and optical surface brightness are obtained from multiband imaging. I will describe quantitative measures of the spatial location and extend of the star formation rate, showing that about half of the cluster members with significant Halpha detection have diffused star formation, larger than the optical counterpart. This suggests that star formation occurs out to larger radii than the rest frame continuum. For some systems, nuclear star forming regions are found. I will also present a comparison between the Halpha distribution observed in cluster and field galaxies. The characterization of the spatial distribution of Halpha provides a new window, yet poorly exploited, on the mechanisms that regulate star formation and morphological transformation in dense environments.

Spatial Distribution, Structure, Biomass, and Physiology of Microbial Assemblages across the Southern Ocean Frontal Zones during the Late Austral Winter

PubMed Central

Hanson, Roger B.; Lowery, H. Kenneth

1985-01-01

We examined the spatial distributions of picoplankton, nanoplankton, and microplankton biomass and physiological state relative to the hydrography of the Southern Ocean along 90° W longitude and across the Drake Passage in the late austral winter. The eastern South Pacific Ocean showed some large-scale biogeographical differences and size class variability. Microbial ATP biomass was greatest in euphotic surface waters. The horizontal distributions of microbial biomass and physiological state (adenylate energy charge ratio) coincided with internal currents (fronts) of the Antarctic Circumpolar Current. In the Drake Passage, the biological scales in the euphotic and aphotic zones were complex, and ATP, total adenylate, and adenylate energy charge ratio isopleths were compressed due to the extension of the sea ice from Antarctica and constriction of the Circumpolar Current through the narrow passage. The physiological state of microbial assemblages and biomass were much higher in the Drake Passage than in the eastern South Pacific Ocean. The temperature of Antarctic waters, not dissolved organic carbon, was the major variable controlling picoplankton growth. Estimates of picoplankton production based on ATP increments with time suggest that production under reduced predation pressure was 1 to 10 μg of carbon per liter per day. Our results demonstrate the influence of large-scale hydrographic processes on the distribution and structure of microplankton, nanoplankton, and picoplankton across the Southern Ocean. PMID:16346777

Trends in Arctic Sea Ice Leads Detection

NASA Astrophysics Data System (ADS)

Ackerman, S. A.; Hoffman, J.; Liu, Y.; Key, J. R.

2016-12-01

Sea ice leads (fractures) play a critical role in the exchange of mass and energy between the ocean and atmosphere in the polar regions, particularly in the Arctic. Leads result in warming water and accelerated melting because leads absorb more solar energy than the surrounding ice. In the autumn, winter, and spring leads impact the local atmospheric structure and cloud properties because of the large flux of heat and moisture into the atmosphere. Given the rapid thinning and loss of Arctic sea ice over the last few decades, changes in the distribution of leads can be expected in response. Leads are largely wind driven, so their distributions will also be affected by the changes in atmospheric circulation that have occurred. From a climate perspective, identifying trends in lead characteristics (width, orientation, and spatial distribution) will advance our understanding of both thermodynamic and mechanical processes. This study presents the spatial and temporal distributions of Arctic sea ice leads since 2002 using a new method to detect and characterize sea ice leads with optical (visible, infrared) satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Using reflective and emissive channels, ice concentration is derived in cloud-free regions and used to create a mask of potential leads. An algorithm then uses a combination of image processing techniques to identify and characterizes leads. The results show interannual variability of leads positioning as well as parameters such as area, length, orientation and width.

Estimating occupancy and predicting numbers of gray wolf packs in Montana using hunter surveys

USGS Publications Warehouse

Rich, Lindsey N.; Russell, Robin E.; Glenn, Elizabeth M.; Mitchell, Michael S.; Gude, Justin A.; Podruzny, Kevin M.; Sime, Carolyn A.; Laudon, Kent; Ausband, David E.; Nichols, James D.

2013-01-01

Reliable knowledge of the status and trend of carnivore populations is critical to their conservation and management. Methods for monitoring carnivores, however, are challenging to conduct across large spatial scales. In the Northern Rocky Mountains, wildlife managers need a time- and cost-efficient method for monitoring gray wolf (Canis lupus) populations. Montana Fish, Wildlife and Parks (MFWP) conducts annual telephone surveys of >50,000 deer and elk hunters. We explored how survey data on hunters' sightings of wolves could be used to estimate the occupancy and distribution of wolf packs and predict their abundance in Montana for 2007–2009. We assessed model utility by comparing our predictions to MFWP minimum known number of wolf packs. We minimized false positive detections by identifying a patch as occupied if 2–25 wolves were detected by ≥3 hunters. Overall, estimates of the occupancy and distribution of wolf packs were generally consistent with known distributions. Our predictions of the total area occupied increased from 2007 to 2009 and predicted numbers of wolf packs were approximately 1.34–1.46 times the MFWP minimum counts for each year of the survey. Our results indicate that multi-season occupancy models based on public sightings can be used to monitor populations and changes in the spatial distribution of territorial carnivores across large areas where alternative methods may be limited by personnel, time, accessibility, and budget constraints.

Observation of sand waves in the Taiwan Banks using HJ-1A/1B sun glitter imagery

NASA Astrophysics Data System (ADS)

Zhang, Hua-guo; Lou, Xiu-lin; Shi, Ai-qin; He, Xie-kai; Guan, Wei-bing; Li, Dong-ling

2014-01-01

This study focuses on the large sand waves in the Taiwan Banks. Our goals are to observe the sand waves as completely as possible, to obtain their direction, wavelength, density, and ridge length, to analyze their spatial distributions, and to understand the effects of the current field and water depth on the sand waves. This study demonstrates the possibility of using HJ-1A/1B sun glitter imagery with a large swath width and rapid coverage in studying sand waves. Six cloud-free HJ-1A/1B optical images with sun glitter signals received during 2009 to 2011 were processed. The sand waves were mapped based on their features in the images; their direction, wavelength, density, and ridge length were measured and analyzed. We identified 4604 sand waves distributed in an area of 16,400 km2. The distributions of sand waves and their characteristics were analyzed, and the differences of sand waves between the northwestern subregion and the southeastern subregion are reported. Further analysis and discussion of the relationships between spatial distribution of the sand waves and both the tidal current field from a numerical simulation and water depth led to some interesting conclusions. The current field determines the orientation of the sand wave, while the hydrodynamic conditions and water depth influence the shape, size, and density of sand waves to a certain degree.

Connections between residence time distributions and watershed characteristics across the continental US

NASA Astrophysics Data System (ADS)

Condon, L. E.; Maxwell, R. M.; Kollet, S. J.; Maher, K.; Haggerty, R.; Forrester, M. M.

2016-12-01

Although previous studies have demonstrated fractal residence time distributions in small watersheds, analyzing residence time scaling over large spatial areas is difficult with existing observational methods. For this study we use a fully integrated groundwater surface water simulation combined with Lagrangian particle tracking to evaluate connections between residence time distributions and watershed characteristics such as geology, topography and climate. Our simulation spans more than six million square kilometers of the continental US, encompassing a broad range of watershed sizes and physiographic settings. Simulated results demonstrate power law residence time distributions with peak age rages from 1.5 to 10.5 years. These ranges agree well with previous observational work and demonstrate the feasibility of using integrated models to simulate residence times. Comparing behavior between eight major watersheds, we show spatial variability in both the peak and the variance of the residence time distributions that can be related to model inputs. Peak age is well correlated with basin averaged hydraulic conductivity and the semi-variance corresponds to aridity. While power law age distributions have previously been attributed to fractal topography, these results illustrate the importance of subsurface characteristics and macro climate as additional controls on groundwater configuration and residence times.

Macromolecular Crowding Induces Spatial Correlations That Control Gene Expression Bursting Patterns

DOE PAGES

Norred, Sarah Elizabeth; Caveney, Patrick M.; Chauhan, Gaurav; ...

2018-04-24

Recent superresolution microscopy studies in E. coli demonstrate that the cytoplasm has highly variable local concentrations where macromolecular crowding plays a central role in establishing membrane-less compartmentalization. This spatial inhomogeneity significantly influences molecular transport and association processes central to gene expression. Yet, little is known about how macromolecular crowding influences gene expression bursting—the episodic process where mRNA and proteins are produced in bursts. Here, we simultaneously measured mRNA and protein reporters in cell-free systems, showing that macromolecular crowding decoupled the well-known relationship between fluctuations in the protein population (noise) and mRNA population statistics. Crowded environments led to a 10-fold increasemore » in protein noise even though there were only modest changes in the mRNA population and fluctuations. Instead, cell-like macromolecular crowding created an inhomogeneous spatial distribution of mRNA (“spatial noise”) that led to large variability in the protein production burst size. As a result, the mRNA spatial noise created large temporal fluctuations in the protein population. Furthermore, these results highlight the interplay between macromolecular crowding, spatial inhomogeneities, and the resulting dynamics of gene expression, and provide insights into using these organizational principles in both cell-based and cell-free synthetic biology.« less

Macromolecular Crowding Induces Spatial Correlations That Control Gene Expression Bursting Patterns

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

Norred, Sarah Elizabeth; Caveney, Patrick M.; Chauhan, Gaurav

Recent superresolution microscopy studies in E. coli demonstrate that the cytoplasm has highly variable local concentrations where macromolecular crowding plays a central role in establishing membrane-less compartmentalization. This spatial inhomogeneity significantly influences molecular transport and association processes central to gene expression. Yet, little is known about how macromolecular crowding influences gene expression bursting—the episodic process where mRNA and proteins are produced in bursts. Here, we simultaneously measured mRNA and protein reporters in cell-free systems, showing that macromolecular crowding decoupled the well-known relationship between fluctuations in the protein population (noise) and mRNA population statistics. Crowded environments led to a 10-fold increasemore » in protein noise even though there were only modest changes in the mRNA population and fluctuations. Instead, cell-like macromolecular crowding created an inhomogeneous spatial distribution of mRNA (“spatial noise”) that led to large variability in the protein production burst size. As a result, the mRNA spatial noise created large temporal fluctuations in the protein population. Furthermore, these results highlight the interplay between macromolecular crowding, spatial inhomogeneities, and the resulting dynamics of gene expression, and provide insights into using these organizational principles in both cell-based and cell-free synthetic biology.« less

Identification of Volcanic Landforms and Processes on Earth and Mars using Geospatial Analysis (Invited)

NASA Astrophysics Data System (ADS)

Fagents, S. A.; Hamilton, C. W.

2009-12-01

Nearest neighbor (NN) analysis enables the identification of landforms using non-morphological parameters and can be useful for constraining the geological processes contributing to observed patterns of spatial distribution. Explosive interactions between lava and water can generate volcanic rootless cone (VRC) groups that are well suited to geospatial analyses because they consist of a large number of landforms that share a common formation mechanism. We have applied NN analysis tools to quantitatively compare the spatial distribution of VRCs in the Laki lava flow in Iceland to analogous landforms in the Tartarus Colles Region of eastern Elysium Planitia, Mars. Our results show that rootless eruption sites on both Earth and Mars exhibit systematic variations in spatial organization that are related to variations in the distribution of resources (lava and water) at different scales. Field observations in Iceland reveal that VRC groups are composite structures formed by the emplacement of chronologically and spatially distinct domains. Regionally, rootless cones cluster into groups and domains, but within domains NN distances exhibit random to repelled distributions. This suggests that on regional scales VRCs cluster in locations that contain sufficient resources, whereas on local scales rootless eruption sites tend to self-organize into distributions that maximize the utilization of limited resources (typically groundwater). Within the Laki lava flow, near-surface water is abundant and pre-eruption topography appears to exert the greatest control on both lava inundation regions and clustering of rootless eruption sites. In contrast, lava thickness appears to be the controlling factor in the formation of rootless eruption sites in the Tartarus Colles Region. A critical lava thickness may be required to initiate rootless eruptions on Mars because the lava flows must contain sufficient heat for transferred thermal energy to reach the underlying cryosphere and volatilize buried ground ice. In both environments, the spatial distribution of rootless eruption sites on local scales may either be random, which indicates that rootless eruption sites form independently of one another, or repelled, which implies resource limitation. Where competition for limited groundwater causes rootless eruption sites to develop greater than random NN separation, rootless eruption sites can be modeled as a system of pumping wells that extract water from a shared aquifer, thereby generating repelled distributions due to non-initiation or early cessation of rootless explosive activity at sites with insufficient access to groundwater. Thus statistical NN analyses can be combined with field observations and remote sensing to obtain information about self-organization processes within geological systems and the effects of environmental resource limitation on the spatial distribution of volcanic landforms. NN analyses may also be used to quantitatively compare the spatial distribution of landforms in different planetary environments and for supplying non-morphological evidence to discriminate between feature identities and geological formation mechanisms.

Spatial Patterns of Snow Cover in North Carolina: Surface and Satellite Perspectives

NASA Technical Reports Server (NTRS)

Fuhrmann, Christopher M.; Hall, Dorothy K.; Perry, L. Baker; Riggs, George A.

2010-01-01

Snow mapping is a common practice in regions that receive large amounts of snowfall annually, have seasonally-continuous snow cover, and where snowmelt contributes significantly to the hydrologic cycle. Although higher elevations in the southern Appalachian Mountains average upwards of 100 inches of snow annually, much of the remainder of the Southeast U.S. receives comparatively little snowfall (< 10 inches). Recent snowy winters in the region have provided an opportunity to assess the fine-grained spatial distribution of snow cover and the physical processes that act to limit or improve its detection across the Southeast. In the present work, both in situ and remote sensing data are utilized to assess the spatial distribution of snow cover for a sample of recent snowfall events in North Carolina. Specifically, this work seeks to determine how well ground measurements characterize the fine-grained patterns of snow cover in relation to Moderate- Resolution Imaging Spectroradiometer (MODIS) snow cover products (in this case, the MODIS Fractional Snow Cover product).

Coordination of genomic structure and transcription by the main bacterial nucleoid-associated protein HU

PubMed Central

Berger, Michael; Farcas, Anca; Geertz, Marcel; Zhelyazkova, Petya; Brix, Klaudia; Travers, Andrew; Muskhelishvili, Georgi

2010-01-01

The histone-like protein HU is a highly abundant DNA architectural protein that is involved in compacting the DNA of the bacterial nucleoid and in regulating the main DNA transactions, including gene transcription. However, the coordination of the genomic structure and function by HU is poorly understood. Here, we address this question by comparing transcript patterns and spatial distributions of RNA polymerase in Escherichia coli wild-type and hupA/B mutant cells. We demonstrate that, in mutant cells, upregulated genes are preferentially clustered in a large chromosomal domain comprising the ribosomal RNA operons organized on both sides of OriC. Furthermore, we show that, in parallel to this transcription asymmetry, mutant cells are also impaired in forming the transcription foci—spatially confined aggregations of RNA polymerase molecules transcribing strong ribosomal RNA operons. Our data thus implicate HU in coordinating the global genomic structure and function by regulating the spatial distribution of RNA polymerase in the nucleoid. PMID:20010798

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

USGS Publications Warehouse

Gebler, J.B.

2004-01-01

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

Spatial patterns of schistosomiasis in Burkina Faso: relevance of human mobility and water resources development

NASA Astrophysics Data System (ADS)

Perez-Saez, Javier; Bertuzzo, Enrico; Frohelich, Jean-Marc; Mande, Theophile; Ceperley, Natalie; Sou, Mariam; Yacouba, Hamma; Maiga, Hamadou; Sokolow, Susanne; De Leo, Giulio; Casagrandi, Renato; Gatto, Marino; Mari, Lorenzo; Rinaldo, Andrea

2015-04-01

We study the spatial geography of schistosomiasis in the african context of Burkina Faso by means of a spatially explicit model of disease dynamics and spread. The relevance of our work lies in its ability to describe quantitatively a geographic stratification of the disease burden capable of reproducing important spatial differences, and drivers/controls of disease spread. Among the latters, we consider specifically the development and management of water resources which have been singled out empirically as an important risk factor for schistosomiasis. The model includes remotely acquired and objectively manipulated information on the distributions of population, infrastructure, elevation and climatic drivers. It also includes a general description of human mobility and addresses a first-order characterization of the ecology of the intermediate host of the parasite causing the disease based on maximum entropy learning of relevant environmenal covariates. Spatial patterns of the disease were analyzed about their disease-free equilibrium by proper extraction and mapping of suitable eigenvectors of the Jacobian matrix subsuming all stability properties of the system. Human mobility was found to be a primary control of both pathogen invasion success and of the overall distribution of disease burden. The effects of water resources development were studied by accounting for the (prior and posterior) average distances of human settlements from water bodies that may serve as suitable habitats to the intermediate host of the parasite. Water developments, in combination with human mobility, were quantitatively related to disease spread into regions previously nearly disease-free and to large-scale empirical incidence patterns. We concluded that while the model still needs refinements based on field and epidemiological evidence, the framework proposed provides a powerful tool for large-scale, long-term public health planning and management of schistosomiasis.

Determining the spatial variability of wetland soil bulk density, organic matter, and the conversion factor between organic matter and organic carbon across coastal Louisiana, U.S.A.

USGS Publications Warehouse

Wang, Hongqing; Piazza, Sarai C.; Sharp, Leigh A.; Stagg, Camille L.; Couvillion, Brady R.; Steyer, Gregory D.; McGinnis, Thomas E.

2016-01-01

Soil bulk density (BD), soil organic matter (SOM) content, and a conversion factor between SOM and soil organic carbon (SOC) are often used in estimating SOC sequestration and storage. Spatial variability in BD, SOM, and the SOM–SOC conversion factor affects the ability to accurately estimate SOC sequestration, storage, and the benefits (e.g., land building area and vertical accretion) associated with wetland restoration efforts, such as marsh creation and sediment diversions. There are, however, only a few studies that have examined large-scale spatial variability in BD, SOM, and SOM–SOC conversion factors in coastal wetlands. In this study, soil cores, distributed across the entire coastal Louisiana (approximately 14,667 km2) were used to examine the regional-scale spatial variability in BD, SOM, and the SOM–SOC conversion factor. Soil cores for BD and SOM analyses were collected during 2006–09 from 331 spatially well-distributed sites in the Coastwide Reference Monitoring System network. Soil cores for the SOM–SOC conversion factor analysis were collected from 15 sites across coastal Louisiana during 2006–07. Results of a split-plot analysis of variance with incomplete block design indicated that BD and SOM varied significantly at a landscape level, defined by both hydrologic basins and vegetation types. Vertically, BD and SOM varied significantly among different vegetation types. The SOM–SOC conversion factor also varied significantly at the landscape level. This study provides critical information for the assessment of the role of coastal wetlands in large regional carbon budgets and the estimation of carbon credits from coastal restoration.

Investigation of microstructure in additive manufactured Inconel 625 by spatially resolved neutron transmission spectroscopy

DOE PAGES

Tremsin, Anton S.; Gao, Yan; Dial, Laura C.; ...

2016-07-08

Non-destructive testing techniques based on neutron imaging and diffraction can provide information on the internal structure of relatively thick metal samples (up to several cm), which are opaque to other conventional non-destructive methods. Spatially resolved neutron transmission spectroscopy is an extension of traditional neutron radiography, where multiple images are acquired simultaneously, each corresponding to a narrow range of energy. The analysis of transmission spectra enables studies of bulk microstructures at the spatial resolution comparable to the detector pixel. In this study we demonstrate the possibility of imaging (with ~100 μm resolution) distribution of some microstructure properties, such as residual strain,more » texture, voids and impurities in Inconel 625 samples manufactured with an additive manufacturing method called direct metal laser melting (DMLM). Although this imaging technique can be implemented only in a few large-scale facilities, it can be a valuable tool for optimization of additive manufacturing techniques and materials and for correlating bulk microstructure properties to manufacturing process parameters. Additionally, the experimental strain distribution can help validate finite element models which many industries use to predict the residual stress distributions in additive manufactured components.« less

Investigation of microstructure in additive manufactured Inconel 625 by spatially resolved neutron transmission spectroscopy.

PubMed

Tremsin, Anton S; Gao, Yan; Dial, Laura C; Grazzi, Francesco; Shinohara, Takenao

2016-01-01

Non-destructive testing techniques based on neutron imaging and diffraction can provide information on the internal structure of relatively thick metal samples (up to several cm), which are opaque to other conventional non-destructive methods. Spatially resolved neutron transmission spectroscopy is an extension of traditional neutron radiography, where multiple images are acquired simultaneously, each corresponding to a narrow range of energy. The analysis of transmission spectra enables studies of bulk microstructures at the spatial resolution comparable to the detector pixel. In this study we demonstrate the possibility of imaging (with ~100 μm resolution) distribution of some microstructure properties, such as residual strain, texture, voids and impurities in Inconel 625 samples manufactured with an additive manufacturing method called direct metal laser melting (DMLM). Although this imaging technique can be implemented only in a few large-scale facilities, it can be a valuable tool for optimization of additive manufacturing techniques and materials and for correlating bulk microstructure properties to manufacturing process parameters. In addition, the experimental strain distribution can help validate finite element models which many industries use to predict the residual stress distributions in additive manufactured components.

Investigation of microstructure in additive manufactured Inconel 625 by spatially resolved neutron transmission spectroscopy

NASA Astrophysics Data System (ADS)

Tremsin, Anton S.; Gao, Yan; Dial, Laura C.; Grazzi, Francesco; Shinohara, Takenao

2016-01-01

Non-destructive testing techniques based on neutron imaging and diffraction can provide information on the internal structure of relatively thick metal samples (up to several cm), which are opaque to other conventional non-destructive methods. Spatially resolved neutron transmission spectroscopy is an extension of traditional neutron radiography, where multiple images are acquired simultaneously, each corresponding to a narrow range of energy. The analysis of transmission spectra enables studies of bulk microstructures at the spatial resolution comparable to the detector pixel. In this study we demonstrate the possibility of imaging (with 100 μm resolution) distribution of some microstructure properties, such as residual strain, texture, voids and impurities in Inconel 625 samples manufactured with an additive manufacturing method called direct metal laser melting (DMLM). Although this imaging technique can be implemented only in a few large-scale facilities, it can be a valuable tool for optimization of additive manufacturing techniques and materials and for correlating bulk microstructure properties to manufacturing process parameters. In addition, the experimental strain distribution can help validate finite element models which many industries use to predict the residual stress distributions in additive manufactured components.

Investigation of microstructure in additive manufactured Inconel 625 by spatially resolved neutron transmission spectroscopy

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

Tremsin, Anton S.; Gao, Yan; Dial, Laura C.

Non-destructive testing techniques based on neutron imaging and diffraction can provide information on the internal structure of relatively thick metal samples (up to several cm), which are opaque to other conventional non-destructive methods. Spatially resolved neutron transmission spectroscopy is an extension of traditional neutron radiography, where multiple images are acquired simultaneously, each corresponding to a narrow range of energy. The analysis of transmission spectra enables studies of bulk microstructures at the spatial resolution comparable to the detector pixel. In this study we demonstrate the possibility of imaging (with ~100 μm resolution) distribution of some microstructure properties, such as residual strain,more » texture, voids and impurities in Inconel 625 samples manufactured with an additive manufacturing method called direct metal laser melting (DMLM). Although this imaging technique can be implemented only in a few large-scale facilities, it can be a valuable tool for optimization of additive manufacturing techniques and materials and for correlating bulk microstructure properties to manufacturing process parameters. Additionally, the experimental strain distribution can help validate finite element models which many industries use to predict the residual stress distributions in additive manufactured components.« less

Investigation of microstructure in additive manufactured Inconel 625 by spatially resolved neutron transmission spectroscopy

PubMed Central

Tremsin, Anton S.; Gao, Yan; Dial, Laura C.; Grazzi, Francesco; Shinohara, Takenao

2016-01-01

Abstract Non-destructive testing techniques based on neutron imaging and diffraction can provide information on the internal structure of relatively thick metal samples (up to several cm), which are opaque to other conventional non-destructive methods. Spatially resolved neutron transmission spectroscopy is an extension of traditional neutron radiography, where multiple images are acquired simultaneously, each corresponding to a narrow range of energy. The analysis of transmission spectra enables studies of bulk microstructures at the spatial resolution comparable to the detector pixel. In this study we demonstrate the possibility of imaging (with ~100 μm resolution) distribution of some microstructure properties, such as residual strain, texture, voids and impurities in Inconel 625 samples manufactured with an additive manufacturing method called direct metal laser melting (DMLM). Although this imaging technique can be implemented only in a few large-scale facilities, it can be a valuable tool for optimization of additive manufacturing techniques and materials and for correlating bulk microstructure properties to manufacturing process parameters. In addition, the experimental strain distribution can help validate finite element models which many industries use to predict the residual stress distributions in additive manufactured components. PMID:27877885

A statistical image analysis framework for pore-free islands derived from heterogeneity distribution of nuclear pore complexes.

PubMed

Mimura, Yasuhiro; Takemoto, Satoko; Tachibana, Taro; Ogawa, Yutaka; Nishimura, Masaomi; Yokota, Hideo; Imamoto, Naoko

2017-11-24

Nuclear pore complexes (NPCs) maintain cellular homeostasis by mediating nucleocytoplasmic transport. Although cyclin-dependent kinases (CDKs) regulate NPC assembly in interphase, the location of NPC assembly on the nuclear envelope is not clear. CDKs also regulate the disappearance of pore-free islands, which are nuclear envelope subdomains; this subdomain gradually disappears with increase in homogeneity of the NPC in response to CDK activity. However, a causal relationship between pore-free islands and NPC assembly remains unclear. Here, we elucidated mechanisms underlying NPC assembly from a new perspective by focusing on pore-free islands. We proposed a novel framework for image-based analysis to automatically determine the detailed 'landscape' of pore-free islands from a large quantity of images, leading to the identification of NPC intermediates that appear in pore-free islands with increased frequency in response to CDK activity. Comparison of the spatial distribution between simulated and the observed NPC intermediates within pore-free islands showed that their distribution was spatially biased. These results suggested that the disappearance of pore-free islands is highly related to de novo NPC assembly and indicated the existence of specific regulatory mechanisms for the spatial arrangement of NPC assembly on nuclear envelopes.

HESS Opinions: The need for process-based evaluation of large-domain hyper-resolution models

NASA Astrophysics Data System (ADS)

Melsen, Lieke A.; Teuling, Adriaan J.; Torfs, Paul J. J. F.; Uijlenhoet, Remko; Mizukami, Naoki; Clark, Martyn P.

2016-03-01

A meta-analysis on 192 peer-reviewed articles reporting on applications of the variable infiltration capacity (VIC) model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution. We identified six time concepts in hydrological models, which all impact the model results and conclusions. Process-based model evaluation is particularly relevant when models are applied at hyper-resolution, where stakeholders expect credible results both at a high spatial and temporal resolution.

HESS Opinions: The need for process-based evaluation of large-domain hyper-resolution models

NASA Astrophysics Data System (ADS)

Melsen, L. A.; Teuling, A. J.; Torfs, P. J. J. F.; Uijlenhoet, R.; Mizukami, N.; Clark, M. P.

2015-12-01

A meta-analysis on 192 peer-reviewed articles reporting applications of the Variable Infiltration Capacity (VIC) model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution. We identified six time concepts in hydrological models, which all impact the model results and conclusions. Process-based model evaluation is particularly relevant when models are applied at hyper-resolution, where stakeholders expect credible results both at a high spatial and temporal resolution.

Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate.

PubMed

Beer, Christian; Reichstein, Markus; Tomelleri, Enrico; Ciais, Philippe; Jung, Martin; Carvalhais, Nuno; Rödenbeck, Christian; Arain, M Altaf; Baldocchi, Dennis; Bonan, Gordon B; Bondeau, Alberte; Cescatti, Alessandro; Lasslop, Gitta; Lindroth, Anders; Lomas, Mark; Luyssaert, Sebastiaan; Margolis, Hank; Oleson, Keith W; Roupsard, Olivier; Veenendaal, Elmar; Viovy, Nicolas; Williams, Christopher; Woodward, F Ian; Papale, Dario

2010-08-13

Terrestrial gross primary production (GPP) is the largest global CO(2) flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.

Developing Automated Spectral Analysis Tools for Interstellar Features Extractionto Support Construction of the 3D ISM Map

NASA Astrophysics Data System (ADS)

Puspitarini, L.; Lallement, R.; Monreal-Ibero, A.; Chen, H.-C.; Malasan, H. L.; Aprilia; Arifyanto, M. I.; Irfan, M.

2018-04-01

One of the ways to obtain a detailed 3D ISM map is by gathering interstellar (IS) absorption data toward widely distributed background target stars at known distances (line-of-sight/LOS data). The radial and angular evolution of the LOS measurements allow the inference of the ISM spatial distribution. For a better spatial resolution, one needs a large number of the LOS data. It requires building fast tools to measure IS absorption. One of the tools is a global analysis that fit two different diffuse interstellar bands (DIBs) simultaneously. We derived the equivalent width (EW) ratio of the two DIBs recorded in each spectrum of target stars. The ratio variability can be used to study IS environmental conditions or to detect DIB family.

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

NASA Astrophysics Data System (ADS)

Felix, Simon; Bolzern, Roman; Battaglia, Marina

2017-11-01

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS_CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS_CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

Distributed temperature and strain discrimination with stimulated brillouin scattering and rayleigh backscatter in an optical fiber.

PubMed

Zhou, Da-Peng; Li, Wenhai; Chen, Liang; Bao, Xiaoyi

2013-01-31

A distributed optical fiber sensor with the capability of simultaneously measuring temperature and strain is proposed using a large effective area non-zero dispersion shifted fiber (LEAF) with sub-meter spatial resolution. The Brillouin frequency shift is measured using Brillouin optical time-domain analysis (BOTDA) with differential pulse-width pair technique, while the spectrum shift of the Rayleigh backscatter is measured using optical frequency-domain reflectometry (OFDR). These shifts are the functions of both temperature and strain, and can be used as two independent parameters for the discrimination of temperature and strain. A 92 m measurable range with the spatial resolution of 50 cm is demonstrated experimentally, and accuracies of ±1.2 °C in temperature and ±15 με in strain could be achieved.

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

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

Felix, Simon; Bolzern, Roman; Battaglia, Marina, E-mail: simon.felix@fhnw.ch, E-mail: roman.bolzern@fhnw.ch, E-mail: marina.battaglia@fhnw.ch

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS-CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS-CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation ofmore » quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.« less

Oscillations and waves in a spatially distributed system with a 1/f spectrum

NASA Astrophysics Data System (ADS)

Koverda, V. P.; Skokov, V. N.

2018-02-01

A spatially distributed system with a 1/f power spectrum is described by two nonlinear stochastic equations. Conditions for the formation of auto-oscillations have been found using numerical methods. The formation of a 1/f and 1/k spectrum simultaneously with the formation and motion of waves under the action of white noise has been demonstrated. The large extreme fluctuations with 1/f and 1/k spectra correspond to the maximum entropy, which points to the stability of such processes. It is shown that on the background of formation and motion of waves at an external periodic action there appears spatio-temporal stochastic resonance, at which one can observe the expansion of the region of periodic pulsations under the action of white noise.

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

NASA Technical Reports Server (NTRS)

Turner, Michael S.; Villumsen, Jens V.; Vittorio, Nicola; Silk, Joseph; Juszkiewicz, Roman

1987-01-01

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 Omega = 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 about 100 Mpc, while the small-scale structure over less than about 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.

Geotechnical parameter spatial distribution stochastic analysis based on multi-precision information assimilation

NASA Astrophysics Data System (ADS)

Wang, C.; Rubin, Y.

2014-12-01

Spatial distribution of important geotechnical parameter named compression modulus Es contributes considerably to the understanding of the underlying geological processes and the adequate assessment of the Es mechanics effects for differential settlement of large continuous structure foundation. These analyses should be derived using an assimilating approach that combines in-situ static cone penetration test (CPT) with borehole experiments. To achieve such a task, the Es distribution of stratum of silty clay in region A of China Expo Center (Shanghai) is studied using the Bayesian-maximum entropy method. This method integrates rigorously and efficiently multi-precision of different geotechnical investigations and sources of uncertainty. Single CPT samplings were modeled as a rational probability density curve by maximum entropy theory. Spatial prior multivariate probability density function (PDF) and likelihood PDF of the CPT positions were built by borehole experiments and the potential value of the prediction point, then, preceding numerical integration on the CPT probability density curves, the posterior probability density curve of the prediction point would be calculated by the Bayesian reverse interpolation framework. The results were compared between Gaussian Sequential Stochastic Simulation and Bayesian methods. The differences were also discussed between single CPT samplings of normal distribution and simulated probability density curve based on maximum entropy theory. It is shown that the study of Es spatial distributions can be improved by properly incorporating CPT sampling variation into interpolation process, whereas more informative estimations are generated by considering CPT Uncertainty for the estimation points. Calculation illustrates the significance of stochastic Es characterization in a stratum, and identifies limitations associated with inadequate geostatistical interpolation techniques. This characterization results will provide a multi-precision information assimilation method of other geotechnical parameters.

Mapping the Distribution of Anthrax in Mainland China, 2005-2013.

PubMed

Chen, Wan-Jun; Lai, Sheng-Jie; Yang, Yang; Liu, Kun; Li, Xin-Lou; Yao, Hong-Wu; Li, Yu; Zhou, Hang; Wang, Li-Ping; Mu, Di; Yin, Wen-Wu; Fang, Li-Qun; Yu, Hong-Jie; Cao, Wu-Chun

2016-04-01

Anthrax, a global re-emerging zoonotic disease in recent years is enzootic in mainland China. Despite its significance to the public health, spatiotemporal distributions of the disease in human and livestock and its potential driving factors remain poorly understood. Using the national surveillance data of human and livestock anthrax from 2005 to 2013, we conducted a retrospective epidemiological study and risk assessment of anthrax in mainland China. The potential determinants for the temporal and spatial distributions of human anthrax were also explored. We found that the majority of human anthrax cases were located in six provinces in western and northeastern China, and five clustering areas with higher incidences were identified. The disease mostly peaked in July or August, and males aged 30-49 years had higher incidence than other subgroups. Monthly incidence of human anthrax was positively correlated with monthly average temperature, relative humidity and monthly accumulative rainfall with lags of 0-2 months. A boosted regression trees (BRT) model at the county level reveals that densities of cattle, sheep and human, coverage of meadow, coverage of typical grassland, elevation, coverage of topsoil with pH > 6.1, concentration of organic carbon in topsoil, and the meteorological factors have contributed substantially to the spatial distribution of the disease. The model-predicted probability of occurrence of human cases in mainland China was mapped at the county level. Anthrax in China was characterized by significant seasonality and spatial clustering. The spatial distribution of human anthrax was largely driven by livestock husbandry, human density, land cover, elevation, topsoil features and climate. Enhanced surveillance and intervention for livestock and human anthrax in the high-risk regions, particularly on the Qinghai-Tibetan Plateau, is the key to the prevention of human infections.

Mapping the Distribution of Anthrax in Mainland China, 2005–2013

PubMed Central

Yang, Yang; Liu, Kun; Li, Xin-Lou; Yao, Hong-Wu; Li, Yu; Zhou, Hang; Wang, Li-Ping; Mu, Di; Yin, Wen-Wu; Fang, Li-Qun; Yu, Hong-Jie; Cao, Wu-Chun

2016-01-01

Background Anthrax, a global re-emerging zoonotic disease in recent years is enzootic in mainland China. Despite its significance to the public health, spatiotemporal distributions of the disease in human and livestock and its potential driving factors remain poorly understood. Methodology/Principal Findings Using the national surveillance data of human and livestock anthrax from 2005 to 2013, we conducted a retrospective epidemiological study and risk assessment of anthrax in mainland China. The potential determinants for the temporal and spatial distributions of human anthrax were also explored. We found that the majority of human anthrax cases were located in six provinces in western and northeastern China, and five clustering areas with higher incidences were identified. The disease mostly peaked in July or August, and males aged 30–49 years had higher incidence than other subgroups. Monthly incidence of human anthrax was positively correlated with monthly average temperature, relative humidity and monthly accumulative rainfall with lags of 0–2 months. A boosted regression trees (BRT) model at the county level reveals that densities of cattle, sheep and human, coverage of meadow, coverage of typical grassland, elevation, coverage of topsoil with pH > 6.1, concentration of organic carbon in topsoil, and the meteorological factors have contributed substantially to the spatial distribution of the disease. The model-predicted probability of occurrence of human cases in mainland China was mapped at the county level. Conclusions/Significance Anthrax in China was characterized by significant seasonality and spatial clustering. The spatial distribution of human anthrax was largely driven by livestock husbandry, human density, land cover, elevation, topsoil features and climate. Enhanced surveillance and intervention for livestock and human anthrax in the high-risk regions, particularly on the Qinghai-Tibetan Plateau, is the key to the prevention of human infections. PMID:27097318

Multivariate geostatistical modeling of the spatial sediment distribution in a large scale drainage basin, Upper Rhone, Switzerland

NASA Astrophysics Data System (ADS)

Schoch, Anna; Blöthe, Jan Henrik; Hoffmann, Thomas; Schrott, Lothar

2018-02-01

There is a notable discrepancy between detailed sediment budget studies in small headwater catchments (< 102 km2) focusing on the identification of sedimentary landforms in the field (e.g. talus cones, moraine deposits, fans) and large scale studies (> 103 km2) in higher order catchments applying modeling and/or remote sensing based approaches for major sediment storage delineation. To bridge the gap between these scales, we compiled an inventory of sediment and bedrock coverage from field mapping, remote sensing analysis and published data for five key sites in the Upper Rhone Basin (Val d'Illiez, Val de la Liène, Turtmanntal, Lötschental, Goms; 360.3 km2, equivalent to 6.7% of the Upper Rhone Basin). This inventory was used as training and testing data for the classification of sediment and bedrock cover. From a digital elevation model (2 × 2 m ground resolution) and Landsat imagery we derived 22 parameters characterizing local morphometry, topography and position, contributing area, and climatic and biotic factors on different spatial scales, which were used as inputs for different statistical models (logistic regression, principal component logistic regression, generalized additive model). Best prediction results with an excellent performance (mean AUROC: 0.8721 ± 0.0012) and both a high spatial and non-spatial transferability were achieved applying a generalized additive model. Since the model has a high thematic consistency, the independent input variables chosen based on their geomorphic relevance are suitable to model the spatial distribution of sediment. Our high-resolution classification shows that 53.5 ± 21.7% of the Upper Rhone Basin are covered with sediment. These are by no means evenly distributed: small headwaters (< 5 km2) feature a very strong variability in sediment coverage, with watersheds drowning in sediments juxtaposed to watersheds devoid of sediment cover. In contrast, larger watersheds predominantly show a bimodal distribution, with highest densities for bedrock (30-40%) being consistently lower than for sediment cover (60-65%). Earlier studies quantifying sedimentary cover and volume focus on the broad glacially overdeepened Rhone Valley that accounts for c. 9% of our study area. While our data support its importance, we conservatively estimate that the remaining 90% of sediment cover, mainly located outside trunk valleys, account for a volume of 2.6-13 km3, i.e. 2-16% of the estimated sediment volume stored in the Rhone Valley between Brig and Lake Geneva. Furthermore, our data reveal increased relative sediment cover in areas deglaciated since the Little Ice Age, as compared to headwater regions without this recent glacial imprint. We therefore conclude that sediment storage in low-order valleys, often neglected in large scale studies, constitutes a significant component of large scale sediment budgets that needs to be better included into future analysis.

Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

NASA Astrophysics Data System (ADS)

Žukovič, Milan; Hristopulos, Dionissios T.

2009-02-01

A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of discretization levels, and the initial conditions.

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

USGS Publications Warehouse

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

2005-01-01

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

Morphology and spatial patterns of Macrotermes mounds in the SE Katanga, D.R. Congo

NASA Astrophysics Data System (ADS)

Bazirake Mujinya, Basile; Mees, Florias; Erens, Hans; Baert, Geert; Van Ranst, Eric

2015-04-01

The spatial distribution patterns and morphological characteristics of Macrotermes falciger mounds were investigated in the Lubumbashi area, D.R. Congo. Examination of the spatial patterns of M. falciger mounds on high resolution satellite images reveals a mean areal number density of 2.9 ± 0.4 mounds ha-1. The high relative number of inactive mounds in the region, along with their regular distribution pattern, suggests that current termite mound occurrences are largely palaeostructures. Mound positions in the habitat are consistent with intraspecific competition rather than soil and substrate characteristics as controlling factor. Detailed morphological description of five deep termite-mound profiles (~7 m height/depth) shows that carbonate pedofeatures are present in all studied profiles, in contrast to the control soils. They mainly occur in the form of soft powdery masses, nodules and coatings on ped faces, all clearly pedogenic. Carbonate coatings occur mainly between 1 m above the soil surface and 1 m below that level in all mound profiles. Carbonate nodules do show a different distribution pattern at each site. Furthermore, when the studied profiles are considered to represent a toposequence, the stone layer occurs at greater depth in topographically low areas compared to crest and slope positions, which is mainly conditioned by erosion. The clay content of epigeal mounds increases from the summit to the toe slope, which can be largely related to differences in parent material. The Mn-Fe oxide concentrations occurring in all studied termite mound profiles reflect a seasonally high perched water table beneath the mound, which is more pronounced at the lower slope positions.

Genes mirror geography in Daphnia magna.

PubMed

Fields, Peter D; Reisser, Céline; Dukić, Marinela; Haag, Christoph R; Ebert, Dieter

2015-09-01

Identifying the presence and magnitude of population genetic structure remains a major consideration in evolutionary biology as doing so allows one to understand the demographic history of a species as well as make predictions of how the evolutionary process will proceed. Next-generation sequencing methods allow us to reconsider previous ideas and conclusions concerning the distribution of genetic variation, and what this distribution implies about a given species evolutionary history. A previous phylogeographic study of the crustacean Daphnia magna suggested that, despite strong genetic differentiation among populations at a local scale, the species shows only moderate genetic structure across its European range, with a spatially patchy occurrence of individual lineages. We apply RAD sequencing to a sample of D. magna collected across a wide swath of the species' Eurasian range and analyse the data using principle component analysis (PCA) of genetic variation and Procrustes analytical approaches, to quantify spatial genetic structure. We find remarkable consistency between the first two PCA axes and the geographic coordinates of individual sampling points, suggesting that, on a continent-wide scale, genetic differentiation is driven to a large extent by geographic distance. The observed pattern is consistent with unimpeded (i.e. no barriers, landscape or otherwise) migration at large spatial scales, despite the fragmented and patchy nature of favourable habitats at local scales. With high-resolution genetic data similar patterns may be uncovered for other species with wide geographic distributions, allowing an increased understanding of how genetic drift and selection have shaped their evolutionary history. © 2015 John Wiley & Sons Ltd.

Spatial interpolation of hourly precipitation and dew point temperature for the identification of precipitation phase and hydrologic response in a mountainous catchment

NASA Astrophysics Data System (ADS)

Garen, D. C.; Kahl, A.; Marks, D. G.; Winstral, A. H.

2012-12-01

In mountainous catchments, it is well known that meteorological inputs, such as precipitation, air temperature, humidity, etc. vary greatly with elevation, spatial location, and time. Understanding and monitoring catchment inputs is necessary in characterizing and predicting hydrologic response to these inputs. This is true all of the time, but it is the most dramatically critical during large storms, when the input to the stream system due to rain and snowmelt creates the potential for flooding. Besides such crisis events, however, proper estimation of catchment inputs and their spatial distribution is also needed in more prosaic but no less important water and related resource management activities. The first objective of this study is to apply a geostatistical spatial interpolation technique (elevationally detrended kriging) to precipitation and dew point temperature on an hourly basis and explore its characteristics, accuracy, and other issues. The second objective is to use these spatial fields to determine precipitation phase (rain or snow) during a large, dynamic winter storm. The catchment studied is the data-rich Reynolds Creek Experimental Watershed near Boise, Idaho. As part of this analysis, precipitation-elevation lapse rates are examined for spatial and temporal consistency. A clear dependence of lapse rate on precipitation amount exists. Certain stations, however, are outliers from these relationships, showing that significant local effects can be present and raising the question of whether such stations should be used for spatial interpolation. Experiments with selecting subsets of stations demonstrate the importance of elevation range and spatial placement on the interpolated fields. Hourly spatial fields of precipitation and dew point temperature are used to distinguish precipitation phase during a large rain-on-snow storm in December 2005. This application demonstrates the feasibility of producing hourly spatial fields and the importance of doing so to support an accurate determination of precipitation phase for assessing catchment hydrologic response to the storm.

Towards more accurate isoscapes encouraging results from wine, water and marijuana data/model and model/model comparisons.

NASA Astrophysics Data System (ADS)

West, J. B.; Ehleringer, J. R.; Cerling, T.

2006-12-01

Understanding how the biosphere responds to change it at the heart of biogeochemistry, ecology, and other Earth sciences. The dramatic increase in human population and technological capacity over the past 200 years or so has resulted in numerous, simultaneous changes to biosphere structure and function. This, then, has lead to increased urgency in the scientific community to try to understand how systems have already responded to these changes, and how they might do so in the future. Since all biospheric processes exhibit some patchiness or patterns over space, as well as time, we believe that understanding the dynamic interactions between natural systems and human technological manipulations can be improved if these systems are studied in an explicitly spatial context. We present here results of some of our efforts to model the spatial variation in the stable isotope ratios (δ2H and δ18O) of plants over large spatial extents, and how these spatial model predictions compare to spatially explicit data. Stable isotopes trace and record ecological processes and as such, if modeled correctly over Earth's surface allow us insights into changes in biosphere states and processes across spatial scales. The data-model comparisons show good agreement, in spite of the remaining uncertainties (e.g., plant source water isotopic composition). For example, inter-annual changes in climate are recorded in wine stable isotope ratios. Also, a much simpler model of leaf water enrichment driven with spatially continuous global rasters of precipitation and climate normals largely agrees with complex GCM modeling that includes leaf water δ18O. Our results suggest that modeling plant stable isotope ratios across large spatial extents may be done with reasonable accuracy, including over time. These spatial maps, or isoscapes, can now be utilized to help understand spatially distributed data, as well as to help guide future studies designed to understand ecological change across landscapes.

Use of radio-tagging to map spatial organization and social interactions in insects.

PubMed

Moreau, Mathieu; Arrufat, Patrick; Latil, Gérard; Jeanson, Raphaël

2011-01-01

Understanding of the organization of animal societies often requires knowledge of the identity of group members and their spatial location. We propose an original experimental design to track automatically the position of individuals using radio frequency identification technology (RFID). Ants equipped with passive transponders were detected by a reader mounted on a mobile arm moving across the nest surface. We developed an algorithm to accurately extract the positions of individuals moving in two dimensions. Our method was validated on synthetic test cases and then used for characterization of the spatial distribution of ants within nests. This approach provides an amenable system for monitoring large populations of individuals over long periods of time.

Modular and hierarchical structure of social contact networks

NASA Astrophysics Data System (ADS)

Ge, Yuanzheng; Song, Zhichao; Qiu, Xiaogang; Song, Hongbin; Wang, Yong

2013-10-01

Social contact networks exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated nature. We propose a mixing pattern of modular and growing hierarchical structures to reconstruct social contact networks by using an individual’s geospatial distribution information in the real world. The hierarchical structure of social contact networks is defined based on the spatial distance between individuals, and edges among individuals are added in turn from the modular layer to the highest layer. It is a gradual process to construct the hierarchical structure: from the basic modular model up to the global network. The proposed model not only shows hierarchically increasing degree distribution and large clustering coefficients in communities, but also exhibits spatial clustering features of individual distributions. As an evaluation of the method, we reconstruct a hierarchical contact network based on the investigation data of a university. Transmission experiments of influenza H1N1 are carried out on the generated social contact networks, and results show that the constructed network is efficient to reproduce the dynamic process of an outbreak and evaluate interventions. The reproduced spread process exhibits that the spatial clustering of infection is accordant with the clustering of network topology. Moreover, the effect of individual topological character on the spread of influenza is analyzed, and the experiment results indicate that the spread is limited by individual daily contact patterns and local clustering topology rather than individual degree.

Delineating ecological regions in marine systems: Integrating physical structure and community composition to inform spatial management in the eastern Bering Sea

NASA Astrophysics Data System (ADS)

Baker, Matthew R.; Hollowed, Anne B.

2014-11-01

Characterizing spatial structure and delineating meaningful spatial boundaries have useful applications to understanding regional dynamics in marine systems, and are integral to ecosystem approaches to fisheries management. Physical structure and drivers combine with biological responses and interactions to organize marine systems in unique ways at multiple scales. We apply multivariate statistical methods to define spatially coherent ecological units or ecoregions in the eastern Bering Sea. We also illustrate a practical approach to integrate data on species distribution, habitat structure and physical forcing mechanisms to distinguish areas with distinct biogeography as one means to define management units in large marine ecosystems. We use random forests to quantify the relative importance of habitat and environmental variables to the distribution of individual species, and to quantify shifts in multispecies assemblages or community composition along environmental gradients. Threshold shifts in community composition are used to identify regions with distinct physical and biological attributes, and to evaluate the relative importance of predictor variables to determining regional boundaries. Depth, bottom temperature and frontal boundaries were dominant factors delineating distinct biological communities in this system, with a latitudinal divide at approximately 60°N. Our results indicate that distinct climatic periods will shift habitat gradients and that dynamic physical variables such as temperature and stratification are important to understanding temporal stability of ecoregion boundaries. We note distinct distribution patterns among functional guilds and also evidence for resource partitioning among individual species within each guild. By integrating physical and biological data to determine spatial patterns in community composition, we partition ecosystems along ecologically significant gradients. This may provide a basis for defining spatial management units or serve as a baseline index for analyses of structural shifts in the physical environment, species abundance and distribution, and community dynamics over time.

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

NASA Astrophysics Data System (ADS)

Lobligeois, Florent; Andréassian, Vazken; Perrin, Charles

2013-04-01

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

Towards large dynamic range and ultrahigh measurement resolution in distributed fiber sensing based on multicore fiber.

PubMed

Dang, Yunli; Zhao, Zhiyong; Tang, Ming; Zhao, Can; Gan, Lin; Fu, Songnian; Liu, Tongqing; Tong, Weijun; Shum, Perry Ping; Liu, Deming

2017-08-21

Featuring a dependence of Brillouin frequency shift (BFS) on temperature and strain changes over a wide range, Brillouin distributed optical fiber sensors are however essentially subjected to the relatively poor temperature/strain measurement resolution. On the other hand, phase-sensitive optical time-domain reflectometry (Φ-OTDR) offers ultrahigh temperature/strain measurement resolution, but the available frequency scanning range is normally narrow thereby severely restricts its measurement dynamic range. In order to achieve large dynamic range and high measurement resolution simultaneously, we propose to employ both the Brillouin optical time domain analysis (BOTDA) and Φ-OTDR through space-division multiplexed (SDM) configuration based on the multicore fiber (MCF), in which the two sensors are spatially separately implemented in the central core and a side core, respectively. As a proof of concept, the temperature sensing has been performed for validation with 2.5 m spatial resolution over 1.565 km MCF. Large temperature range (10 °C) has been measured by BOTDA and the 0.1 °C small temperature variation is successfully identified by Φ-OTDR with ~0.001 °C resolution. Moreover, the temperature changing process has been recorded by continuously performing the measurement of Φ-OTDR with 80 s frequency scanning period, showing about 0.02 °C temperature spacing at the monitored profile. The proposed system enables the capability to see finer and/or farther upon requirement in distributed optical fiber sensing.

Anomalies in the GRBs' distribution

NASA Astrophysics Data System (ADS)

Bagoly, Zsolt; Horvath, Istvan; Hakkila, Jon; Toth, Viktor

2015-08-01

Gamma-ray bursts (GRBs) are the most luminous objects known: they outshine their host galaxies making them ideal candidates for probing large-scale structure. Earlier, the angular distribution of different GRBs (long, intermediate and short) has been studied in detail with different methods and it has been found that the short and intermediate groups showed deviation from the full randomness at different levels (e.g. Vavrek, R., et al. 2008). However these result based only angular measurements of the BATSE experiment, without any spatial distance indicator involved.Currently we have more than 361 GRBs with measured precise position, optical afterglow and redshift, mainly due to the observations of the Swift mission. This sample is getting large enough that it its homogeneous and isotropic distribution a large scale can be checked. We have recently (Horvath, I. et al., 2014) identified a large clustering of gamma-ray bursts at redshift z ~ 2 in the general direction of the constellations of Hercules and Corona Borealis. This angular excess cannot be entirely attributed to known selection biases, making its existence due to chance unlikely. The scale on which the clustering occurs is disturbingly large, about 2-3 Gpc: the underlying distribution of matter suggested by this cluster is big enough to question standard assumptions about Universal homogeneity and isotropy.

Direct measurement of the 3-dimensional DNA lesion distribution induced by energetic charged particles in a mouse model tissue

PubMed Central

Mirsch, Johanna; Tommasino, Francesco; Frohns, Antonia; Conrad, Sandro; Durante, Marco; Scholz, Michael; Friedrich, Thomas; Löbrich, Markus

2015-01-01

Charged particles are increasingly used in cancer radiotherapy and contribute significantly to the natural radiation risk. The difference in the biological effects of high-energy charged particles compared with X-rays or γ-rays is determined largely by the spatial distribution of their energy deposition events. Part of the energy is deposited in a densely ionizing manner in the inner part of the track, with the remainder spread out more sparsely over the outer track region. Our knowledge about the dose distribution is derived solely from modeling approaches and physical measurements in inorganic material. Here we exploited the exceptional sensitivity of γH2AX foci technology and quantified the spatial distribution of DNA lesions induced by charged particles in a mouse model tissue. We observed that charged particles damage tissue nonhomogenously, with single cells receiving high doses and many other cells exposed to isolated damage resulting from high-energy secondary electrons. Using calibration experiments, we transformed the 3D lesion distribution into a dose distribution and compared it with predictions from modeling approaches. We obtained a radial dose distribution with sub-micrometer resolution that decreased with increasing distance to the particle path following a 1/r2 dependency. The analysis further revealed the existence of a background dose at larger distances from the particle path arising from overlapping dose deposition events from independent particles. Our study provides, to our knowledge, the first quantification of the spatial dose distribution of charged particles in biologically relevant material, and will serve as a benchmark for biophysical models that predict the biological effects of these particles. PMID:26392532

Spatial distribution of impact craters on Deimos

NASA Astrophysics Data System (ADS)

Hirata, Naoyuki

2017-05-01

Deimos, one of the Martian moons, has numerous impact craters. However, it is unclear whether crater saturation has been reached on this satellite. To address this issue, we apply a statistical test known as nearest-neighbor analysis to analyze the crater distribution of Deimos. When a planetary surface such as the Moon is saturated with impact craters, the spatial distribution of craters is generally changed from random to more ordered. We measured impact craters on Deimos from Viking and HiRISE images and found (1) that the power law of the size-frequency distribution of the craters is approximately -1.7, which is significantly shallower than those of potential impactors, and (2) that the spatial distribution of craters over 30 m in diameter cannot be statistically distinguished from completely random distribution, which indicates that the surface of Deimos is inconsistent with a surface saturated with impact craters. Although a crater size-frequency distribution curve with a slope of -2 is generally interpreted as indicating saturation equilibrium, it is here proposed that two competing mechanisms, seismic shaking and ejecta emplacement, have played a major role in erasing craters on Deimos and are therefore responsible for the shallow slope of this curve. The observed crater density may have reached steady state owing to the obliterations induced by the two competing mechanisms. Such an occurrence indicates that the surface is saturated with impact craters despite the random distribution of craters on Deimos. Therefore, this work proposes that the age determined by the current craters on Deimos reflects neither the age of Deimos itself nor that of the formation of the large concavity centered at its south pole because craters should be removed by later impacts. However, a few of the largest craters on Deimos may be indicative of the age of the south pole event.

Decentralized diagnostics based on a distributed micro-genetic algorithm for transducer networks monitoring large experimental systems.

PubMed

Arpaia, P; Cimmino, P; Girone, M; La Commara, G; Maisto, D; Manna, C; Pezzetti, M

2014-09-01

Evolutionary approach to centralized multiple-faults diagnostics is extended to distributed transducer networks monitoring large experimental systems. Given a set of anomalies detected by the transducers, each instance of the multiple-fault problem is formulated as several parallel communicating sub-tasks running on different transducers, and thus solved one-by-one on spatially separated parallel processes. A micro-genetic algorithm merges evaluation time efficiency, arising from a small-size population distributed on parallel-synchronized processors, with the effectiveness of centralized evolutionary techniques due to optimal mix of exploitation and exploration. In this way, holistic view and effectiveness advantages of evolutionary global diagnostics are combined with reliability and efficiency benefits of distributed parallel architectures. The proposed approach was validated both (i) by simulation at CERN, on a case study of a cold box for enhancing the cryogeny diagnostics of the Large Hadron Collider, and (ii) by experiments, under the framework of the industrial research project MONDIEVOB (Building Remote Monitoring and Evolutionary Diagnostics), co-funded by EU and the company Del Bo srl, Napoli, Italy.

Trypsin and MALDI matrix pre-coated targets simplify sample preparation for mapping proteomic distributions within biological tissues by imaging mass spectrometry

PubMed Central

Zubair, Faizan; Laibinis, Paul E.; Swisher, William G.; Yang, Junhai; Spraggins, Jeffrey M.; Norris, Jeremy L.; Caprioli, Richard M.

2017-01-01

Prefabricated surfaces containing α-cyano-4-hydroxycinnamic acid and trypsin have been developed to facilitate enzymatic digestion of endogenous tissue proteins prior to matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS). Tissue sections are placed onto slides that were previously coated with α-cyano-4-hydroxycinnamic acid and trypsin. After incubation to promote enzymatic digestion, the tissue is analyzed by MALDI IMS to determine the spatial distribution of the tryptic fragments. The peptides detected in the MALDI IMS dataset were identified by Liquid chromatography-tandem mass spectrometry/mass spectrometry. Protein identification was further confirmed by correlating the localization of unique tryptic fragments originating from common parent proteins. Using this procedure, proteins with molecular weights as large as 300 kDa were identified and their distributions were imaged in sections of rat brain. In particular, large proteins such as myristoylated alanine-rich C-kinase substrate (29.8 kDa) and spectrin alpha chain, non-erythrocytic 1 (284 kDa) were detected that are not observed without trypsin. The pre-coated targets simplify workflow and increase sample throughput by decreasing the sample preparation time. Further, the approach allows imaging at higher spatial resolution compared with robotic spotters that apply one drop at a time. PMID:27676701

Understanding patterns of vegetation structure and distribution across Great Smoky Mountains National Park using LiDAR and meteorology data

NASA Astrophysics Data System (ADS)

Kumar, J.; Hargrove, W. W.; Norman, S. P.; Hoffman, F. M.

2017-12-01

Great Smoky Mountains National Park (GSMNP) in Tennessee is a biodiversity hotspot and home to a large number of plant, animal and bird species. Driven by gradients of climate (ex. temperature, precipitation regimes), topography (ex. elevation, slope, aspect), geology (ex. soil types, textures, depth), hydrology (ex. drainage, moisture availability) etc. GSMNP offers a diverse composition and distribution of vegetation which in turn supports an array of wildlife. Understanding the vegetation canopy structure is critical to understand, monitor and manage the complex forest ecosystems like the Great Smoky Mountain National Park (GSMNP). Vegetation canopies not only help understand the vegetation, but are also a critically important habitat characteristics of many threatened and endangered animal and bird species that GSMNP is home to. Using airborne Light Detection and Ranging (LiDAR) we characterize the three-dimensional structure of the vegetation. LiDAR based analysis gives detailed insight in the canopy structure (overstory and understory) and its spatial variability within and across forest types. Vegetation structure and spatial distribution show strong correlation with climate, topographic, and edaphic variables and our multivariate analysis not just mines rich and large LiDAR data but presents ecological insights and data for vegetation within the park that can be useful to forest managers in their management and conservation efforts.

Heat and mass transport during a groundwater replenishment trial in a highly heterogeneous aquifer

NASA Astrophysics Data System (ADS)

Seibert, Simone; Prommer, Henning; Siade, Adam; Harris, Brett; Trefry, Mike; Martin, Michael

2014-12-01

Changes in subsurface temperature distribution resulting from the injection of fluids into aquifers may impact physiochemical and microbial processes as well as basin resource management strategies. We have completed a 2 year field trial in a hydrogeologically and geochemically heterogeneous aquifer below Perth, Western Australia in which highly treated wastewater was injected for large-scale groundwater replenishment. During the trial, chloride and temperature data were collected from conventional monitoring wells and by time-lapse temperature logging. We used a joint inversion of these solute tracer and temperature data to parameterize a numerical flow and multispecies transport model and to analyze the solute and heat propagation characteristics that prevailed during the trial. The simulation results illustrate that while solute transport is largely confined to the most permeable lithological units, heat transport was also affected by heat exchange with lithological units that have a much lower hydraulic conductivity. Heat transfer by heat conduction was found to significantly influence the complex temporal and spatial temperature distribution, especially with growing radial distance and in aquifer sequences with a heterogeneous hydraulic conductivity distribution. We attempted to estimate spatially varying thermal transport parameters during the data inversion to illustrate the anticipated correlations of these parameters with lithological heterogeneities, but estimates could not be uniquely determined on the basis of the collected data.

Spatial trends in leaf size of Amazonian rainforest trees

NASA Astrophysics Data System (ADS)

Malhado, A. C. M.; Malhi, Y.; Whittaker, R. J.; Ladle, R. J.; Ter Steege, H.; Aragão, L. E. O. C.; Quesada, C. A.; Araujo-Murakami, A.; Phillips, O. L.; Peacock, J.; Lopez-Gonzalez, G.; Baker, T. R.; Butt, N.; Anderson, L. O.; Arroyo, L.; Almeida, S.; Higuchi, N.; Killeen, T. J.; Monteagudo, A.; Neill, D.; Pitman, N.; Prieto, A.; Salomão, R. P.; Silva, N.; Vásquez-Martínez, R.; Laurance, W. F.

2009-02-01

Leaf size influences many aspects of tree function such as rates of transpiration and photosynthesis and, consequently, often varies in a predictable way in response to environmental gradients. The recent development of pan-Amazonian databases based on permanent botanical plots (e.g. RAINFOR, ATDN) has now made it possible to assess trends in leaf size across environmental gradients in Amazonia. Previous plot-based studies have shown that the community structure of Amazonian trees breaks down into at least two major ecological gradients corresponding with variations in soil fertility (decreasing south to northeast) and length of the dry season (increasing from northwest to south and east). Here we describe the results of the geographic distribution of leaf size categories based on 121 plots distributed across eight South American countries. We find that, as predicted, the Amazon forest is predominantly populated by tree species and individuals in the mesophyll size class (20.25-182.25 cm2). The geographic distribution of species and individuals with large leaves (>20.25 cm2) is complex but is generally characterized by a higher proportion of such trees in the north-west of the region. Spatially corrected regressions reveal weak correlations between the proportion of large-leaved species and metrics of water availability. We also find a significant negative relationship between leaf size and wood density.

Spatial trends in leaf size of Amazonian rainforest trees

NASA Astrophysics Data System (ADS)

Malhado, A. C. M.; Malhi, Y.; Whittaker, R. J.; Ladle, R. J.; Ter Steege, H.; Phillips, O. L.; Butt, N.; Aragão, L. E. O. C.; Quesada, C. A.; Araujo-Murakami, A.; Arroyo, L.; Peacock, J.; Lopez-Gonzalez, G.; Baker, T. R.; Anderson, L. O.; Almeida, S.; Higuchi, N.; Killeen, T. J.; Monteagudo, A.; Neill, D.; Pitman, N.; Prieto, A.; Salomão, R. P.; Vásquez-Martínez, R.; Laurance, W. F.

2009-08-01

Leaf size influences many aspects of tree function such as rates of transpiration and photosynthesis and, consequently, often varies in a predictable way in response to environmental gradients. The recent development of pan-Amazonian databases based on permanent botanical plots has now made it possible to assess trends in leaf size across environmental gradients in Amazonia. Previous plot-based studies have shown that the community structure of Amazonian trees breaks down into at least two major ecological gradients corresponding with variations in soil fertility (decreasing from southwest to northeast) and length of the dry season (increasing from northwest to south and east). Here we describe the geographic distribution of leaf size categories based on 121 plots distributed across eight South American countries. We find that the Amazon forest is predominantly populated by tree species and individuals in the mesophyll size class (20.25-182.25 cm2). The geographic distribution of species and individuals with large leaves (>20.25 cm2) is complex but is generally characterized by a higher proportion of such trees in the northwest of the region. Spatially corrected regressions reveal weak correlations between the proportion of large-leaved species and metrics of water availability. We also find a significant negative relationship between leaf size and wood density.

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

PubMed

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

2018-02-01

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

Spatial distribution of vehicle emission inventories in the Federal District, Brazil

NASA Astrophysics Data System (ADS)

Réquia, Weeberb João; Koutrakis, Petros; Roig, Henrique Llacer

2015-07-01

Air pollution poses an important public health risk, especially in large urban areas. Information about the spatial distribution of air pollutants can be used as a tool for developing public policies to reduce source emissions. Air pollution monitoring networks provide information about pollutant concentrations; however, they are not available in every urban area. Among the 5570 cities in Brazil, for example, only 1.7% of them have air pollution monitoring networks. In this study we assess vehicle emissions for main traffic routes of the Federal District (state of Brazil) and characterize their spatial patterns. Toward this end, we used a bottom-up method to predict emissions and to characterize their spatial patterns using Global Moran's (Spatial autocorrelation analysis) and Getis-Ord General G (High/Low cluster analysis). Our findings suggested that light duty vehicles are primarily responsible for the vehicular emissions of CO (68.9%), CH4 (93.6%), and CO2 (57.9%), whereas heavy duty vehicles are primarily responsible for the vehicular emissions of NMHC (92.9%), NOx (90.7%), and PM (97.4%). Furthermore, CO2 is the pollutant with the highest emissions, over 30 million tons/year. In the spatial autocorrelation analysis was identified cluster (p < 0.01) for all types of vehicles and for all pollutants. However, we identified high cluster only for the light vehicles.

Space Use of African Wild Dogs in Relation to Other Large Carnivores

PubMed Central

Darnell, Angela M.; Graf, Jan A.; Somers, Michael J.; Slotow, Rob; Szykman Gunther, Micaela

2014-01-01

Interaction among species through competition is a principle process structuring ecological communities, affecting behavior, distribution, and ultimately the population dynamics of species. High competition among large African carnivores, associated with extensive diet overlap, manifests in interactions between subordinate African wild dogs (Lycaon pictus) and dominant lions (Panthera leo) and spotted hyenas (Crocuta crocuta). Using locations of large carnivores in Hluhluwe-iMfolozi Park, South Africa, we found different responses from wild dogs to their two main competitors. Wild dogs avoided lions, particularly during denning, through a combination of spatial and temporal avoidance. However, wild dogs did not exhibit spatial or temporal avoidance of spotted hyenas, likely because wild dog pack sizes were large enough to adequately defend their kills. Understanding that larger carnivores affect the movements and space use of other carnivores is important for managing current small and fragmented carnivore populations, especially as reintroductions and translocations are essential tools used for the survival of endangered species, as with African wild dogs. PMID:24896638

Space use of African wild dogs in relation to other large carnivores.

PubMed

Darnell, Angela M; Graf, Jan A; Somers, Michael J; Slotow, Rob; Szykman Gunther, Micaela

2014-01-01

Interaction among species through competition is a principle process structuring ecological communities, affecting behavior, distribution, and ultimately the population dynamics of species. High competition among large African carnivores, associated with extensive diet overlap, manifests in interactions between subordinate African wild dogs (Lycaon pictus) and dominant lions (Panthera leo) and spotted hyenas (Crocuta crocuta). Using locations of large carnivores in Hluhluwe-iMfolozi Park, South Africa, we found different responses from wild dogs to their two main competitors. Wild dogs avoided lions, particularly during denning, through a combination of spatial and temporal avoidance. However, wild dogs did not exhibit spatial or temporal avoidance of spotted hyenas, likely because wild dog pack sizes were large enough to adequately defend their kills. Understanding that larger carnivores affect the movements and space use of other carnivores is important for managing current small and fragmented carnivore populations, especially as reintroductions and translocations are essential tools used for the survival of endangered species, as with African wild dogs.

Visualization, documentation, analysis, and communication of large scale gene regulatory networks

PubMed Central

Longabaugh, William J.R.; Davidson, Eric H.; Bolouri, Hamid

2009-01-01

Summary Genetic regulatory networks (GRNs) are complex, large-scale, and spatially and temporally distributed. These characteristics impose challenging demands on computational GRN modeling tools, and there is a need for custom modeling tools. In this paper, we report on our ongoing development of BioTapestry, an open source, freely available computational tool designed specifically for GRN modeling. We also outline our future development plans, and give some examples of current applications of BioTapestry. PMID:18757046

Phase synchrony reveals organization in human atrial fibrillation

PubMed Central

Vidmar, David; Narayan, Sanjiv M.

2015-01-01

It remains unclear if human atrial fibrillation (AF) is spatially nonhierarchical or exhibits a hierarchy of organization sustained by sources. We utilize activation times obtained at discrete locations during AF to compute the phase synchrony between tissue regions, to examine underlying spatial dynamics throughout both atria. We construct a binary synchronization network and show that this network can accurately define regions of coherence in coarse-grained in silico data. Specifically, domains controlled by spiral waves exhibit regions of high phase synchrony. We then apply this analysis to clinical data from patients experiencing cardiac arrhythmias using multielectrode catheters to simultaneously record from a majority of both atria. We show that pharmaceutical intervention with ibutilide organizes activation by increasing the size of the synchronized domain in AF and quantify the increase in temporal organization when arrhythmia changes from fibrillation to tachycardia. Finally, in recordings from 24 patients in AF we show that the level of synchrony is spatially broad with some patients showing large spatially contiguous regions of synchronization, while in others synchrony is localized to small pockets. Using computer simulations, we show that this distribution is inconsistent with distributions obtained from simulations that mimic multiwavelet reentry but is consistent with mechanisms in which one or more spatially conserved spiral waves is surrounded by tissue in which activation is disorganized. PMID:26475585

Soil water content spatial pattern estimated by thermal inertia from air-borne sensors

NASA Astrophysics Data System (ADS)

Coppola, Antonio; Basile, Angelo; Esposito, Marco; Menenti, Massimo; Buonanno, Maurizio

2010-05-01

Remote sensing of soil water content from air- or space-borne platforms offer the possibility to provide large spatial coverage and temporal continuity. The water content can be actually monitored in a thin soil layer, usually up to a depth of 0.05m below the soil surface. To the contrary, difficulties arise in the estimation of the water content storage along the soil profile and its spatial (horizontal) distribution, which are closely connected to soil hydraulic properties and their spatial distribution. A promising approach for estimating soil water contents profiles is the integration of remote sensing of surface water content and hydrological modeling. A major goal of the scientific group is to develop a practical and robust procedure for estimating water contents throughout the soil profile from surface water content. As a first step, in this work, we will show some preliminary results from aircraft images analysis and their validation by field campaigns data. The data extracted from the airborne sensors provided the opportunity of retrieving land surface temperatures with a very high spatial resolution. The surface water content pattern, as deduced by the thermal inertia estimations, was compared to the surface water contents maps measured in situ by time domain reflectometry-based probes.

Task Dependence, Tissue Specificity, and Spatial Distribution of Widespread Activations in Large Single-Subject Functional MRI Datasets at 7T

PubMed Central

Gonzalez-Castillo, Javier; Hoy, Colin W.; Handwerker, Daniel A.; Roopchansingh, Vinai; Inati, Souheil J.; Saad, Ziad S.; Cox, Robert W.; Bandettini, Peter A.

2015-01-01

It was recently shown that when large amounts of task-based blood oxygen level–dependent (BOLD) data are combined to increase contrast- and temporal signal-to-noise ratios, the majority of the brain shows significant hemodynamic responses time-locked with the experimental paradigm. Here, we investigate the biological significance of such widespread activations. First, the relationship between activation extent and task demands was investigated by varying cognitive load across participants. Second, the tissue specificity of responses was probed using the better BOLD signal localization capabilities of a 7T scanner. Finally, the spatial distribution of 3 primary response types—namely positively sustained (pSUS), negatively sustained (nSUS), and transient—was evaluated using a newly defined voxel-wise waveshape index that permits separation of responses based on their temporal signature. About 86% of gray matter (GM) became significantly active when all data entered the analysis for the most complex task. Activation extent scaled with task load and largely followed the GM contour. The most common response type was nSUS BOLD, irrespective of the task. Our results suggest that widespread activations associated with extremely large single-subject functional magnetic resonance imaging datasets can provide valuable information about the functional organization of the brain that goes undetected in smaller sample sizes. PMID:25405938

A Study of Students' Reasoning about Probabilistic Causality: Implications for Understanding Complex Systems and for Instructional Design

ERIC Educational Resources Information Center

Grotzer, Tina A.; Solis, S. Lynneth; Tutwiler, M. Shane; Cuzzolino, Megan Powell

2017-01-01

Understanding complex systems requires reasoning about causal relationships that behave or appear to behave probabilistically. Features such as distributed agency, large spatial scales, and time delays obscure co-variation relationships and complex interactions can result in non-deterministic relationships between causes and effects that are best…

Defining surfaces for skewed, highly variable data

USGS Publications Warehouse

Helsel, D.R.; Ryker, S.J.

2002-01-01

Skewness of environmental data is often caused by more than simply a handful of outliers in an otherwise normal distribution. Statistical procedures for such datasets must be sufficiently robust to deal with distributions that are strongly non-normal, containing both a large proportion of outliers and a skewed main body of data. In the field of water quality, skewness is commonly associated with large variation over short distances. Spatial analysis of such data generally requires either considerable effort at modeling or the use of robust procedures not strongly affected by skewness and local variability. Using a skewed dataset of 675 nitrate measurements in ground water, commonly used methods for defining a surface (least-squares regression and kriging) are compared to a more robust method (loess). Three choices are critical in defining a surface: (i) is the surface to be a central mean or median surface? (ii) is either a well-fitting transformation or a robust and scale-independent measure of center used? (iii) does local spatial autocorrelation assist in or detract from addressing objectives? Published in 2002 by John Wiley & Sons, Ltd.

Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.

2015-03-01

The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which is to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.

Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.

2014-11-01

The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which are to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.

Effects of geometrical structure on spatial distribution of thermal energy in two-dimensional triangular lattices

NASA Astrophysics Data System (ADS)

Liu, Yong-Yang; Xu, Yu-Liang; Liu, Zhong-Qiang; Li, Jing; Wang, Chun-Yang; Kong, Xiang-Mu

2018-07-01

Employing the correlation matrix technique, the spatial distribution of thermal energy in two-dimensional triangular lattices in equilibrium, interacting with linear springs, is studied. It is found that the spatial distribution of thermal energy varies with the included angle of the springs. In addition, the average thermal energy of the longer springs is lower. Springs with different included angle and length will lead to an inhomogeneous spatial distribution of thermal energy. This suggests that the spatial distribution of thermal energy is affected by the geometrical structure of the system: the more asymmetric the geometrical structure of the system is, the more inhomogeneous is the spatial distribution of thermal energy.

Multi-approach assessment of the spatial distribution of the specific yield: application to the Crau plain aquifer, France

NASA Astrophysics Data System (ADS)

Seraphin, Pierre; Gonçalvès, Julio; Vallet-Coulomb, Christine; Champollion, Cédric

2018-06-01

Spatially distributed values of the specific yield, a fundamental parameter for transient groundwater mass balance calculations, were obtained by means of three independent methods for the Crau plain, France. In contrast to its traditional use to assess recharge based on a given specific yield, the water-table fluctuation (WTF) method, applied using major recharging events, gave a first set of reference values. Then, large infiltration processes recorded by monitored boreholes and caused by major precipitation events were interpreted in terms of specific yield by means of a one-dimensional vertical numerical model solving Richards' equations within the unsaturated zone. Finally, two gravity field campaigns, at low and high piezometric levels, were carried out to assess the groundwater mass variation and thus alternative specific yield values. The range obtained by the WTF method for this aquifer made of alluvial detrital material was 2.9- 26%, in line with the scarce data available so far. The average spatial value of specific yield by the WTF method (9.1%) is consistent with the aquifer scale value from the hydro-gravimetric approach. In this investigation, an estimate of the hitherto unknown spatial distribution of the specific yield over the Crau plain was obtained using the most reliable method (the WTF method). A groundwater mass balance calculation over the domain using this distribution yielded similar results to an independent quantification based on a stable isotope-mixing model. This agreement reinforces the relevance of such estimates, which can be used to build a more accurate transient hydrogeological model.

Identifying Aquifer Heterogeneities using the Level Set Method

NASA Astrophysics Data System (ADS)

Lu, Z.; Vesselinov, V. V.; Lei, H.

2016-12-01

Material interfaces between hydrostatigraphic units (HSU) with contrasting aquifer parameters (e.g., strata and facies with different hydraulic conductivity) have a great impact on flow and contaminant transport in subsurface. However, the identification of HSU shape in the subsurface is challenging and typically relies on tomographic approaches where a series of steady-state/transient head measurements at spatially distributed observation locations are analyzed using inverse models. In this study, we developed a mathematically rigorous approach for identifying material interfaces among any arbitrary number of HSUs using the level set method. The approach has been tested first with several synthetic cases, where the true spatial distribution of HSUs was assumed to be known and the head measurements were taken from the flow simulation with the true parameter fields. These synthetic inversion examples demonstrate that the level set method is capable of characterizing the spatial distribution of the heterogeneous. We then applied the methodology to a large-scale problem in which the spatial distribution of pumping wells and observation well screens is consistent with the actual aquifer contamination (chromium) site at the Los Alamos National Laboratory (LANL). In this way, we test the applicability of the methodology at an actual site. We also present preliminary results using the actual LANL site data. We also investigated the impact of the number of pumping/observation wells and the drawdown observation frequencies/intervals on the quality of the inversion results. We also examined the uncertainties associated with the estimated HSU shapes, and the accuracy of the results under different hydraulic-conductivity contrasts between the HSU's.

Informing Species Conservation at Multiple Scales Using Data Collected for Marine Mammal Stock Assessments

PubMed Central

Grech, Alana; Sheppard, James; Marsh, Helene

2011-01-01

Background Conservation planning and the design of marine protected areas (MPAs) requires spatially explicit information on the distribution of ecological features. Most species of marine mammals range over large areas and across multiple planning regions. The spatial distributions of marine mammals are difficult to predict using habitat modelling at ecological scales because of insufficient understanding of their habitat needs, however, relevant information may be available from surveys conducted to inform mandatory stock assessments. Methodology and Results We use a 20-year time series of systematic aerial surveys of dugong (Dugong dugong) abundance to create spatially-explicit models of dugong distribution and relative density at the scale of the coastal waters of northeast Australia (∼136,000 km2). We interpolated the corrected data at the scale of 2 km * 2 km planning units using geostatistics. Planning units were classified as low, medium, high and very high dugong density on the basis of the relative density of dugongs estimated from the models and a frequency analysis. Torres Strait was identified as the most significant dugong habitat in northeast Australia and the most globally significant habitat known for any member of the Order Sirenia. The models are used by local, State and Federal agencies to inform management decisions related to the Indigenous harvest of dugongs, gill-net fisheries and Australia's National Representative System of Marine Protected Areas. Conclusion/Significance In this paper we demonstrate that spatially-explicit population models add value to data collected for stock assessments, provide a robust alternative to predictive habitat distribution models, and inform species conservation at multiple scales. PMID:21464933

Multi-approach assessment of the spatial distribution of the specific yield: application to the Crau plain aquifer, France

NASA Astrophysics Data System (ADS)

Seraphin, Pierre; Gonçalvès, Julio; Vallet-Coulomb, Christine; Champollion, Cédric

2018-03-01

Spatially distributed values of the specific yield, a fundamental parameter for transient groundwater mass balance calculations, were obtained by means of three independent methods for the Crau plain, France. In contrast to its traditional use to assess recharge based on a given specific yield, the water-table fluctuation (WTF) method, applied using major recharging events, gave a first set of reference values. Then, large infiltration processes recorded by monitored boreholes and caused by major precipitation events were interpreted in terms of specific yield by means of a one-dimensional vertical numerical model solving Richards' equations within the unsaturated zone. Finally, two gravity field campaigns, at low and high piezometric levels, were carried out to assess the groundwater mass variation and thus alternative specific yield values. The range obtained by the WTF method for this aquifer made of alluvial detrital material was 2.9- 26%, in line with the scarce data available so far. The average spatial value of specific yield by the WTF method (9.1%) is consistent with the aquifer scale value from the hydro-gravimetric approach. In this investigation, an estimate of the hitherto unknown spatial distribution of the specific yield over the Crau plain was obtained using the most reliable method (the WTF method). A groundwater mass balance calculation over the domain using this distribution yielded similar results to an independent quantification based on a stable isotope-mixing model. This agreement reinforces the relevance of such estimates, which can be used to build a more accurate transient hydrogeological model.

Do morphometric parameters and geological conditions determine chemistry of glacier surface ice? Spatial distribution of contaminants present in the surface ice of Spitsbergen glaciers (European Arctic).

PubMed

Lehmann, Sara; Gajek, Grzegorz; Chmiel, Stanisław; Polkowska, Żaneta

2016-12-01

The chemism of the glaciers is strongly determined by long-distance transport of chemical substances and their wet and dry deposition on the glacier surface. This paper concerns spatial distribution of metals, ions, and dissolved organic carbon, as well as the differentiation of physicochemical parameters (pH, electrical conductivity) determined in ice surface samples collected from four Arctic glaciers during the summer season in 2012. The studied glaciers represent three different morphological types: ground based (Blomlibreen and Scottbreen), tidewater which evolved to ground based (Renardbreen), and typical tidewater glacier (Recherchebreen). All of the glaciers are functioning as a glacial system and hence are subject to the same physical processes (melting, freezing) and the process of ice flowing resulting from the cross-impact force of gravity and topographic conditions. According to this hypothesis, the article discusses the correlation between morphometric parameters, changes in mass balance, geological characteristics of the glaciers and the spatial distribution of analytes on the surface of ice. A strong correlation (r = 0.63) is recorded between the aspect of glaciers and values of pH and ions, whereas dissolved organic carbon (DOC) depends on the minimum elevation of glaciers (r = 0.55) and most probably also on the development of the accumulation area. The obtained results suggest that although certain morphometric parameters largely determine the spatial distribution of analytes, also the geology of the bed of glaciers strongly affects the chemism of the surface ice of glaciers in the phase of strong recession.

Spatially distributed modeling of soil organic carbon across China with improved accuracy

NASA Astrophysics Data System (ADS)

Li, Qi-quan; Zhang, Hao; Jiang, Xin-ye; Luo, Youlin; Wang, Chang-quan; Yue, Tian-xiang; Li, Bing; Gao, Xue-song

2017-06-01

There is a need for more detailed spatial information on soil organic carbon (SOC) for the accurate estimation of SOC stock and earth system models. As it is effective to use environmental factors as auxiliary variables to improve the prediction accuracy of spatially distributed modeling, a combined method (HASM_EF) was developed to predict the spatial pattern of SOC across China using high accuracy surface modeling (HASM), artificial neural network (ANN), and principal component analysis (PCA) to introduce land uses, soil types, climatic factors, topographic attributes, and vegetation cover as predictors. The performance of HASM_EF was compared with ordinary kriging (OK), OK, and HASM combined, respectively, with land uses and soil types (OK_LS and HASM_LS), and regression kriging combined with land uses and soil types (RK_LS). Results showed that HASM_EF obtained the lowest prediction errors and the ratio of performance to deviation (RPD) presented the relative improvements of 89.91%, 63.77%, 55.86%, and 42.14%, respectively, compared to the other four methods. Furthermore, HASM_EF generated more details and more realistic spatial information on SOC. The improved performance of HASM_EF can be attributed to the introduction of more environmental factors, to explicit consideration of the multicollinearity of selected factors and the spatial nonstationarity and nonlinearity of relationships between SOC and selected factors, and to the performance of HASM and ANN. This method may play a useful tool in providing more precise spatial information on soil parameters for global modeling across large areas.

The continuum spectral characteristics of gamma-ray bursts observed by BATSE

NASA Technical Reports Server (NTRS)

Pendleton, Geoffrey N.; Paciesas, William S.; Briggs, Michael S.; Mallozzi, Robert S.; Koshut, Tom M.; Fishman, Gerald J.; Meegan, Charles A.; Wilson, Robert B.; Harmon, Alan B.; Kouveliotou, Chryssa

1994-01-01

Distributions of the continuum spectral characteristics of 260 bursts in the first Burst And Transient Source Experiement (BATSE) catalog are presented. The data are derived from flux calculated from BATSE Large Area Detector (LAD) four-channel discriminator data. The data are converted from counts to protons using a direct spectral inversion technique to remove the effects of atmospheric scattering and the energy dependence of the detector angular response. Although there are intriguing clusters of bursts in the spectral hardness ratio distributions, no evidence for the presence of distinct burst classes based in spectral hardness ratios alone is found. All subsets of bursts selected for their spectral characteristics in this analysis exhibit spatial distributions consistent with isotropy. The spectral diversity of the burst population appears to be caused largely by the highly variable nature of the burst production mechanisms themselves.

Influence of the spatial distribution of cementation on the permeability and mechanical attributes of sedimentary and fault rocks

NASA Astrophysics Data System (ADS)

Mozley, P.; Yoon, H.; Williams, R. T.; Goodwin, L. B.

2015-12-01

The spatial distribution of pore-filling authigenic minerals (cements) is highly variable and controlled in large part by the mineralogy of the cements and host sediment grains. Two end-member distributions of cements that commonly occur in sedimentary material are: (1) concretionary, in which precipitation occurred in specific zones throughout the sediment, with intervening areas largely uncemented; and (2) grain-rimming, in which precipitation occurred on grain-surfaces relatively uniformly throughout the rock. Concretions form in rocks in which sediment grains have a different composition from the cement, whereas rim cements form in those that have the same composition. Both the mechanical attributes and permeability of a given volume of rock are affected to a much greater extent by grain rimming cements, which have a significant impact on properties at even low abundances. Concretionary cements have little impact on bulk properties until relatively large volumes have precipitated (~80% cemented) and concretions begin to link up. Precipitation of cement in fault zones also impacts both mechanical and hydrologic properties. Cementation will stiffen and strengthen unlithified sediment, thereby controlling the locus of fracturing in protolith or damage zones. Where fracture networks form in fault damage zones, they are initially high permeability elements. However, progressive cementation greatly diminishes fracture permeability, resulting in cyclical permeability variation linked to fault slip. To quantitatively describe the interactions of groundwater flow, permeability, and patterns and abundance of cements, we use pore-scale modeling of coupled fluid flow, reactive transport, and heterogeneous mineral-surface reactions. By exploring the effects of varying distributions of porosity and mineralogy, which impact patterns of cementation, we provide mechanistic explanations of the interactions of coupled processes under various flow and chemistry conditions.

Low leopard populations in protected areas of Maputaland: a consequence of poaching, habitat condition, abundance of prey, and a top predator.

PubMed

Ramesh, Tharmalingam; Kalle, Riddhika; Rosenlund, Havard; Downs, Colleen T

2017-03-01

Identifying the primary causes affecting population densities and distribution of flagship species are necessary in developing sustainable management strategies for large carnivore conservation. We modeled drivers of spatial density of the common leopard ( Panthera pardus ) using a spatially explicit capture-recapture-Bayesian approach to understand their population dynamics in the Maputaland Conservation Unit, South Africa. We camera-trapped leopards in four protected areas (PAs) of varying sizes and disturbance levels covering 198 camera stations. Ours is the first study to explore the effects of poaching level, abundance of prey species (small, medium, and large), competitors (lion Panthera leo and spotted hyenas Crocuta crocuta ), and habitat on the spatial distribution of common leopard density. Twenty-six male and 41 female leopards were individually identified and estimated leopard density ranged from 1.6 ± 0.62/100 km 2 (smallest PA-Ndumo) to 8.4 ± 1.03/100 km 2 (largest PA-western shores). Although dry forest thickets and plantation habitats largely represented the western shores, the plantation areas had extremely low leopard density compared to native forest. We found that leopard density increased in areas when low poaching levels/no poaching was recorded in dry forest thickets and with high abundance of medium-sized prey, but decreased with increasing abundance of lion. Because local leopard populations are vulnerable to extinction, particularly in smaller PAs, the long-term sustainability of leopard populations depend on developing appropriate management strategies that consider a combination of multiple factors to maintain their optimal habitats.

The Great Recession and America’s Geography of Unemployment

PubMed Central

Thiede, Brian C.; Monnat, Shannon M.

2017-01-01

Background The Great Recession of 2007–2009 was the most severe and lengthy economic crisis in the U.S. since the Great Depression. The impacts on the population were multi-dimensional, but operated largely through local labor markets. Objective To examine differences in recession-related changes in county unemployment rates and assess how population and place characteristics shaped these patterns. Methods We calculate and decompose Theil Indexes to describe recession-related changes in the distribution of unemployment rates between counties and states. We use exploratory spatial statistics to identify geographic clusters of counties that experienced similar changes in unemployment. We use spatial regression to evaluate associations between county-level recession impacts on unemployment and demographic composition, industrial structure, and state context. Results The recession was associated with increased inequality between county labor markets within states, but declining between-state differences. Counties that experienced disproportionate recession-related increases in unemployment were spatially clustered and characterized by large shares of historically disadvantaged racial and ethnic minority populations, low educational attainment, and heavy reliance on pro-cyclical industries. Associations between these sources of vulnerability were partially explained by unobserved state-level factors. Conclusions The local consequences of macroeconomic trends are associated with county population characteristics, as well as the structural contexts and policy environments in which they are embedded. The recession placed upward pressure on within-state inequality between local labor market conditions. Contribution To present new estimates of the recession’s impact on local labor markets, quantify how heterogeneous impacts affected the distribution of unemployment prevalence, and identify county characteristics associated with disproportionately large recession-related increases in unemployment. PMID:28663712

PBSM3D: A finite volume, scalar-transport blowing snow model for use with variable resolution meshes

NASA Astrophysics Data System (ADS)

Marsh, C.; Wayand, N. E.; Pomeroy, J. W.; Wheater, H. S.; Spiteri, R. J.

2017-12-01

Blowing snow redistribution results in heterogeneous snowcovers that are ubiquitous in cold, windswept environments. Capturing this spatial and temporal variability is important for melt and runoff simulations. Point scale blowing snow transport models are difficult to apply in fully distributed hydrological models due to landscape heterogeneity and complex wind fields. Many existing distributed snow transport models have empirical wind flow and/or simplified wind direction algorithms that perform poorly in calculating snow redistribution where there are divergent wind flows, sharp topography, and over large spatial extents. Herein, a steady-state scalar transport model is discretized using the finite volume method (FVM), using parameterizations from the Prairie Blowing Snow Model (PBSM). PBSM has been applied in hydrological response units and grids to prairie, arctic, glacier, and alpine terrain and shows a good capability to represent snow redistribution over complex terrain. The FVM discretization takes advantage of the variable resolution mesh in the Canadian Hydrological Model (CHM) to ensure efficient calculations over small and large spatial extents. Variable resolution unstructured meshes preserve surface heterogeneity but result in fewer computational elements versus high-resolution structured (raster) grids. Snowpack, soil moisture, and streamflow observations were used to evaluate CHM-modelled outputs in a sub-arctic and an alpine basin. Newly developed remotely sensed snowcover indices allowed for validation over large basins. CHM simulations of snow hydrology were improved by inclusion of the blowing snow model. The results demonstrate the key role of snow transport processes in creating pre-melt snowcover heterogeneity and therefore governing post-melt soil moisture and runoff generation dynamics.

Spatially balanced provision of health equipment: a cross-sectional study oriented to the identification of challenges to access promotion.

PubMed

Amaral, Pedro Vasconcelos; Rocha, Thiago Augusto Hernandes; Barbosa, Allan Claudius Queiroz; Lein, Adriana; Vissoci, João Ricardo Nickenig

2017-12-04

Access to health services is in part defined by the spatial distribution of healthcare equipment. To ensure equity in the provision of health services, it is important to examine availability across different health care providers taking into account population demand. Given the importance of the equitable provision of health equipment, we evaluate its spatial distribution in Brazil. This study is classified as cross-sectional with an ecological design. We evaluate Brazilian data on distance to available health equipment considering: dialysis machines (385), magnetic resonance imaging (MRI) (257), hospital beds (3675) and bone densitometers (429). We define two distance thresholds (50 km and 200 km) from a municipality to the center of services provision. The balance between infrastructure capacity and potential demand was evaluated to identify a lack or surplus of health services. The distribution of dialysis equipment and bone densitometers is not balanced across Brazilian states, and unmet demand is high. With respect to MRIs, the large capacity of this equipment results in a large excess of supply. However, this characteristic alone cannot account for excesses of supply of over 700%, as is the case of the Federal District when the range is limited to 50 km. At the same time, four states in the Northeastern region of Brazil show a net excess of demand. Some regions do not meet the standard amount of supply defined by Brazilian Ministry of Health. The quantity and distribution of hospital beds are not sufficient to provide full coverage to the population. Our main focus was to evaluate the network of the provision of health equipment in Brazil, considering both private and public sectors conjointly. We take into account two main aspects of a spatially balanced health system: the regional availability of health equipment and the geographic distance between its demand and supply at the municipality level. Some regions do not meet the minimum requirement defined by the Brazilian Ministry of Health regarding the supply of health services.

The Use of a Predictive Habitat Model and a Fuzzy Logic Approach for Marine Management and Planning

PubMed Central

Hattab, Tarek; Ben Rais Lasram, Frida; Albouy, Camille; Sammari, Chérif; Romdhane, Mohamed Salah; Cury, Philippe; Leprieur, Fabien; Le Loc’h, François

2013-01-01

Bottom trawl survey data are commonly used as a sampling technique to assess the spatial distribution of commercial species. However, this sampling technique does not always correctly detect a species even when it is present, and this can create significant limitations when fitting species distribution models. In this study, we aim to test the relevance of a mixed methodological approach that combines presence-only and presence-absence distribution models. We illustrate this approach using bottom trawl survey data to model the spatial distributions of 27 commercially targeted marine species. We use an environmentally- and geographically-weighted method to simulate pseudo-absence data. The species distributions are modelled using regression kriging, a technique that explicitly incorporates spatial dependence into predictions. Model outputs are then used to identify areas that met the conservation targets for the deployment of artificial anti-trawling reefs. To achieve this, we propose the use of a fuzzy logic framework that accounts for the uncertainty associated with different model predictions. For each species, the predictive accuracy of the model is classified as ‘high’. A better result is observed when a large number of occurrences are used to develop the model. The map resulting from the fuzzy overlay shows that three main areas have a high level of agreement with the conservation criteria. These results align with expert opinion, confirming the relevance of the proposed methodology in this study. PMID:24146867

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

PubMed

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

2016-08-02

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

Spatial and historical distribution of organic phosphorus driven by environment conditions in lake sediments.

PubMed

Lü, Changwei; He, Jiang; Wang, Bing

2018-02-01

The chemistry of sedimentary organic phosphorus (OP) and its fraction distribution in sediments are greatly influenced by environmental conditions such as terrestrial inputs and runoffs. The linkage of OP with environmental conditions was analyzed on the basis of OP spatial and historical distributions in lake sediments. The redundancy analysis and OP spatial distribution results suggested that both NaOH-OP (OP extracted by NaOH) and Re-OP (residual OP) in surface sediments from the selected 13 lakes reflected the gradient effects of environmental conditions and the autochthonous and/or allochthonous inputs driven by latitude zonality in China. The lake level and salinity of Lake Hulun and the runoff and precipitation of its drainage basin were reconstructed on the basis of the geochemistry index. This work showed that a gradient in weather conditions presented by the latitude zonality in China impacts the OP accumulation through multiple drivers and in many ways. The drivers are mainly precipitation and temperature, governing organic matter (OM) production, degradation rate and transportation in the watershed. Over a long temporal dimension (4000years), the vertical distributions of Re-OP and NaOH-OP based on a dated sediment profile from HLH were largely regulated by the autochthonous and/or allochthonous inputs, which depended on the environmental and climate conditions and anthropogenic activities in the drainage basin. This work provides useful environmental geochemistry information to understand the inherent linkage of OP fractionation with environmental conditions and lake evolution. Copyright © 2017. Published by Elsevier B.V.

On the role of grain boundary character distribution in grain growth of Al-Mg alloys

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

Matsumoto, K.; Shibayanagi, T.; Umakoshi, Y.

1997-02-01

Grain growth behavior of recrystallized Al-Mg alloys containing 0.3 and 2.7 mass% Mg was investigated, focusing on the interconnection between development of the texture and grain boundary character distribution. An Al-0.3 mass% Mg alloy showed two stages in the change of microstructure during grain growth: the frequency of cube oriented grains and the {Sigma}1 boundary significantly increased at an early stage and then decreased. In the second stage a small amount of isolated large grains with the non-cube component grew and consumed the surrounding cube grains. In contrast, the frequency of cube oriented grains and the grain boundary character distributionmore » showed no significant change during grain growth of Al-2.7 mass% Mg. Small clusters composed of several cube grains containing {Sigma}1 boundaries were formed and their spatial distribution played an important role in the change of microstructure during grain growth. The effect of the spatial distribution on the grain growth behavior was discussed considering the energy balance at triple junctions of grain boundaries.« less

Development of population structure and spatial distribution patterns of a restored forest during 17-year succession (1993-2010) in Pingshuo opencast mine spoil, China.

PubMed

Zhao, Zhongqiu; Wang, Lianhua; Bai, Zhongke; Pan, Ziguan; Wang, Yun

2015-07-01

Afforestation of native tree species is often recommended for ecological restoration in mining areas, but the understanding of the ecological processes of restored vegetation is quite limited. In order to provide insight of the ecological processes of restored vegetation, in this study, we investigate the development of the population structure and spatial distribution patterns of restored Robinia pseudoacacia (ROPS) and Pinus tabuliformis (PITA) mixed forests during the 17 years of the mine spoil period of the Pingshuo opencast mine, Shanxi Province, China. After a 17-year succession, apart from the two planted species, Ulmus pumila (ULPU), as an invasive species, settled in the plot along with a large number of small diameter at breast height (DBH) size. In total, there are 10,062 living individual plants, much more than that at the plantation (5105), and ROPS had become the dominant species with a section area with a breast height of 9.40 m(2) hm(-2) and a mean DBH of 6.72 cm, much higher than both PITA and ULPU. The DBH size classes of all the total species showed inverted J-shaped distributions, which may have been a result of the large number of small regenerated ULPU trees. The DBH size classes of both ROPS and PITA showed peak-type structures with individuals mainly gathering in the moderate DBH size class, indicating a relatively healthy DBH size class structure. Meanwhile, invasive ULPU were distributed in a clear L shape, concentrating on the small DBH size class, indicating a relatively low survival rate for adult trees. Both ROPS and PITA species survival in the plantation showed uniform and aggregated distribution at small scales and random with scales increasing. ULPU showed a strong aggregation at small scales as well as random with scales increasing. Both the population structure and spatial distribution indicated that ROPS dominates and will continue to dominate the community in the future succession, which should be continuously monitored.

Distributed Lag Models: Examining Associations between the Built Environment and Health

PubMed Central

Baek, Jonggyu; Sánchez, Brisa N.; Berrocal, Veronica J.; Sanchez-Vaznaugh, Emma V.

2016-01-01

Built environment factors constrain individual level behaviors and choices, and thus are receiving increasing attention to assess their influence on health. Traditional regression methods have been widely used to examine associations between built environment measures and health outcomes, where a fixed, pre-specified spatial scale (e.g., 1 mile buffer) is used to construct environment measures. However, the spatial scale for these associations remains largely unknown and misspecifying it introduces bias. We propose the use of distributed lag models (DLMs) to describe the association between built environment features and health as a function of distance from the locations of interest and circumvent a-priori selection of a spatial scale. Based on simulation studies, we demonstrate that traditional regression models produce associations biased away from the null when there is spatial correlation among the built environment features. Inference based on DLMs is robust under a range of scenarios of the built environment. We use this innovative application of DLMs to examine the association between the availability of convenience stores near California public schools, which may affect children’s dietary choices both through direct access to junk food and exposure to advertisement, and children’s body mass index z-scores (BMIz). PMID:26414942

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

PubMed

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

2017-01-01

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

Application of spatial time domain reflectometry measurements in heterogeneous, rocky substrates

NASA Astrophysics Data System (ADS)

Gonzales, C.; Scheuermann, A.; Arnold, S.; Baumgartl, T.

2016-10-01

Measurement of soil moisture across depths using sensors is currently limited to point measurements or remote sensing technologies. Point measurements have limitations on spatial resolution, while the latter, although covering large areas may not represent real-time hydrologic processes, especially near the surface. The objective of the study was to determine the efficacy of elongated soil moisture probes—spatial time domain reflectometry (STDR)—and to describe transient soil moisture dynamics of unconsolidated mine waste rock materials. The probes were calibrated under controlled conditions in the glasshouse. Transient soil moisture content was measured using the gravimetric method and STDR. Volumetric soil moisture content derived from weighing was compared with values generated from a numerical model simulating the drying process. A calibration function was generated and applied to STDR field data sets. The use of elongated probes effectively assists in the real-time determination of the spatial distribution of soil moisture. It also allows hydrologic processes to be uncovered in the unsaturated zone, especially for water balance calculations that are commonly based on point measurements. The elongated soil moisture probes can potentially describe transient substrate processes and delineate heterogeneity in terms of the pore size distribution in a seasonally wet but otherwise arid environment.

Persistence of canine distemper virus in the Greater Yellowstone ecosystem's carnivore community.

PubMed

Almberg, Emily S; Cross, Paul C; Smith, Douglas W

2010-10-01

Canine distemper virus (CDV) is an acute, highly immunizing pathogen that should require high densities and large populations of hosts for long-term persistence, yet CDV persists among terrestrial carnivores with small, patchily distributed groups. We used CDV in the Greater Yellowstone ecosystem's (GYE) wolves (Canis lupus) and coyotes (Canis latrans) as a case study for exploring how metapopulation structure, host demographics, and multi-host transmission affect the critical community size and spatial scale required for CDV persistence. We illustrate how host spatial connectivity and demographic turnover interact to affect both local epidemic dynamics, such as the length and variation in inter-epidemic periods, and pathogen persistence using stochastic, spatially explicit susceptible-exposed-infectious-recovered simulation models. Given the apparent absence of other known persistence mechanisms (e.g., a carrier or environmental state, densely populated host, chronic infection, or a vector), we suggest that CDV requires either large spatial scales or multi-host transmission for persistence. Current GYE wolf populations are probably too small to support endemic CDV. Coyotes are a plausible reservoir host, but CDV would still require 50000-100000 individuals for moderate persistence (> 50% over 10 years), which would equate to an area of 1-3 times the size of the GYE (60000-200000 km2). Coyotes, and carnivores in general, are not uniformly distributed; therefore, this is probably a gross underestimate of the spatial scale of CDV persistence. However, the presence of a second competent host species can greatly increase the probability of long-term CDV persistence at much smaller spatial scales. Although no management of CDV is currently recommended for the GYE, wolf managers in the region should expect periodic but unpredictable CDV-related population declines as often as every 2-5 years. Awareness and monitoring of such outbreaks will allow corresponding adjustments in management activities such as regulated public harvest, creating a smooth transition to state wolf management and conservation after > 30 years of being protected by the Endangered Species Act.

Examining the Suitability of a Sparse In Situ Soil Moisture Monitoring Network for Assimilation into a Spatially Distributed Hydrologic Model

NASA Astrophysics Data System (ADS)

De Vleeschouwer, N.; Verhoest, N.; Pauwels, V. R. N.

2015-12-01

The continuous monitoring of soil moisture in a permanent network can yield an interesting data product for use in hydrological data assimilation. Major advantages of in situ observations compared to remote sensing products are the potential vertical extent of the measurements, the finer temporal resolution of the observation time series, the smaller impact of land cover variability on the observation bias, etc. However, two major disadvantages are the typical small integration volume of in situ measurements and the often large spacing between monitoring locations. This causes only a small part of the modelling domain to be directly observed. Furthermore, the spatial configuration of the monitoring network is typically temporally non-dynamic. Therefore two questions can be raised. Do spatially sparse in situ soil moisture observations contain a sufficient data representativeness to successfully assimilate them into the largely unobserved spatial extent of a distributed hydrological model? And if so, how is this assimilation best performed? Consequently two important factors that can influence the success of assimilating in situ monitored soil moisture are the spatial configuration of the monitoring network and the applied assimilation algorithm. In this research the influence of those factors is examined by means of synthetic data-assimilation experiments. The study area is the ± 100 km² catchment of the Bellebeek in Flanders, Belgium. The influence of the spatial configuration is examined by varying the amount of locations and their position in the landscape. The latter is performed using several techniques including temporal stability analysis and clustering. Furthermore the observation depth is considered by comparing assimilation of surface layer (5 cm) and deeper layer (50 cm) observations. The impact of the assimilation algorithm is assessed by comparing the performance obtained with two well-known algorithms: Newtonian nudging and the Ensemble Kalman Filter.

High Performance Geostatistical Modeling of Biospheric Resources

NASA Astrophysics Data System (ADS)

Pedelty, J. A.; Morisette, J. T.; Smith, J. A.; Schnase, J. L.; Crosier, C. S.; Stohlgren, T. J.

2004-12-01

We are using parallel geostatistical codes to study spatial relationships among biospheric resources in several study areas. For example, spatial statistical models based on large- and small-scale variability have been used to predict species richness of both native and exotic plants (hot spots of diversity) and patterns of exotic plant invasion. However, broader use of geostastics in natural resource modeling, especially at regional and national scales, has been limited due to the large computing requirements of these applications. To address this problem, we implemented parallel versions of the kriging spatial interpolation algorithm. The first uses the Message Passing Interface (MPI) in a master/slave paradigm on an open source Linux Beowulf cluster, while the second is implemented with the new proprietary Xgrid distributed processing system on an Xserve G5 cluster from Apple Computer, Inc. These techniques are proving effective and provide the basis for a national decision support capability for invasive species management that is being jointly developed by NASA and the US Geological Survey.

Macroscopic Spatial Complexity of the Game of Life Cellular Automaton: A Simple Data Analysis

NASA Astrophysics Data System (ADS)

Hernández-Montoya, A. R.; Coronel-Brizio, H. F.; Rodríguez-Achach, M. E.

In this chapter we present a simple data analysis of an ensemble of 20 time series, generated by averaging the spatial positions of the living cells for each state of the Game of Life Cellular Automaton (GoL). We show that at the macroscopic level described by these time series, complexity properties of GoL are also presented and the following emergent properties, typical of data extracted complex systems such as financial or economical come out: variations of the generated time series following an asymptotic power law distribution, large fluctuations tending to be followed by large fluctuations, and small fluctuations tending to be followed by small ones, and fast decay of linear correlations, however, the correlations associated to their absolute variations exhibit a long range memory. Finally, a Detrended Fluctuation Analysis (DFA) of the generated time series, indicates that the GoL spatial macro states described by the time series are not either completely ordered or random, in a measurable and very interesting way.

Solution of the spatial neutral model yields new bounds on the Amazonian species richness

NASA Astrophysics Data System (ADS)

Shem-Tov, Yahav; Danino, Matan; Shnerb, Nadav M.

2017-02-01

Neutral models, in which individual agents with equal fitness undergo a birth-death-mutation process, are very popular in population genetics and community ecology. Usually these models are applied to populations and communities with spatial structure, but the analytic results presented so far are limited to well-mixed or mainland-island scenarios. Here we combine analytic results and numerics to obtain an approximate solution for the species abundance distribution and the species richness for the neutral model on continuous landscape. We show how the regional diversity increases when the recruitment length decreases and the spatial segregation of species grows. Our results are supported by extensive numerical simulations and allow one to probe the numerically inaccessible regime of large-scale systems with extremely small mutation/speciation rates. Model predictions are compared with the findings of recent large-scale surveys of tropical trees across the Amazon basin, yielding new bounds for the species richness (between 13100 and 15000) and the number of singleton species (between 455 and 690).

[Stochastic characteristics of daily precipitation and its spatiotemporal difference over China based on information entropy].

PubMed

Li, Xin Xin; Sang, Yan Fang; Xie, Ping; Liu, Chang Ming

2018-04-01

Daily precipitation process in China showed obvious randomness and spatiotemporal variation. It is important to accurately understand the influence of precipitation changes on control of flood and waterlogging disaster. Using the daily precipitation data measured at 520 stations in China during 1961-2013, we quantified the stochastic characteristics of daily precipitation over China based on the index of information entropy. Results showed that the randomness of daily precipitation in the southeast region were larger than that in the northwest region. Moreover, the spatial distribution of stochastic characteristics of precipitation was different at various grades. Stochastic characteri-stics of P 0 (precipitation at 0.1-10 mm) was large, but the spatial variation was not obvious. The stochastic characteristics of P 10 (precipitation at 10-25 mm) and P 25 (precipitation at 25-50 mm) were the largest and their spatial difference was obvious. P 50 (precipitation ≥50 mm) had the smallest stochastic characteristics and the most obviously spatial difference. Generally, the entropy values of precipitation obviously increased over the last five decades, indicating more significantly stochastic characteristics of precipitation (especially the obvious increase of heavy precipitation events) in most region over China under the scenarios of global climate change. Given that the spatial distribution and long-term trend of entropy values of daily precipitation could reflect thespatial distribution of stochastic characteristics of precipitation, our results could provide scientific basis for the control of flood and waterlogging disaster, the layout of agricultural planning, and the planning of ecological environment.

Sparse modeling of spatial environmental variables associated with asthma

PubMed Central

Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.

2014-01-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437

Sparse modeling of spatial environmental variables associated with asthma.

PubMed

Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

2015-02-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

Geostatistical and GIS analysis of the spatial variability of alluvial gold content in Ngoura-Colomines area, Eastern Cameroon: Implications for the exploration of primary gold deposit

NASA Astrophysics Data System (ADS)

Takodjou Wambo, Jonas Didero; Ganno, Sylvestre; Djonthu Lahe, Yannick Sthopira; Kouankap Nono, Gus Djibril; Fossi, Donald Hermann; Tchouatcha, Milan Stafford; Nzenti, Jean Paul

2018-06-01

Linear and nonlinear geostatistic is commonly used in ore grade estimation and seldom used in Geographical Information System (GIS) technology. In this study, we suggest an approach based on geostatistic linear ordinary kriging (OK) and Geographical Information System (GIS) techniques to investigate the spatial distribution of alluvial gold content, mineralized and gangue layers thicknesses from 73 pits at the Ngoura-Colomines area with the aim to determine controlling factors for the spatial distribution of mineralization and delineate the most prospective area for primary gold mineralization. Gold content varies between 0.1 and 4.6 g/m3 and has been broadly grouped into three statistical classes. These classes have been spatially subdivided into nine zones using ordinary kriging model based on physical and topographical characteristics. Both mineralized and barren layer thicknesses show randomly spatial distribution, and there is no correlation between these parameters and the gold content. This approach has shown that the Ngoura-Colomines area is located in a large shear zone compatible with the Riedel fault system composed of P and P‧ fractures oriented NE-SW and NNE-SSW respectively; E-W trending R fractures and R‧ fractures with NW-SE trends that could have contributed significantly to the establishment of this gold mineralization. The combined OK model and GIS analysis have led to the delineation of Colomines, Tissongo, Madubal and Boutou villages as the most prospective areas for the exploration of primary gold deposit in the study area.

Modeling elephant-mediated cascading effects of water point closure.

PubMed

Hilbers, Jelle P; Van Langevelde, Frank; Prins, Herbert H T; Grant, C C; Peel, Mike J S; Coughenour, Michael B; De Knegt, Henrik J; Slotow, Rob; Smit, Izak P J; Kiker, Greg A; De Boer, Willem F

2015-03-01

Wildlife management to reduce the impact of wildlife on their habitat can be done in several ways, among which removing animals (by either culling or translocation) is most often used. There are, however, alternative ways to control wildlife densities, such as opening or closing water points. The effects of these alternatives are poorly studied. In this paper, we focus on manipulating large herbivores through the closure of water points (WPs). Removal of artificial WPs has been suggested in order to change the distribution of African elephants, which occur in high densities in national parks in Southern Africa and are thought to have a destructive effect on the vegetation. Here, we modeled the long-term effects of different scenarios of WP closure on the spatial distribution of elephants, and consequential effects on the vegetation and other herbivores in Kruger National Park, South Africa. Using a dynamic ecosystem model, SAVANNA, scenarios were evaluated that varied in availability of artificial WPs; levels of natural water; and elephant densities. Our modeling results showed that elephants can indirectly negatively affect the distributions of meso-mixed feeders, meso-browsers, and some meso-grazers under wet conditions. The closure of artificial WPs hardly had any effect during these natural wet conditions. Under dry conditions, the spatial distribution of both elephant bulls and cows changed when the availability of artificial water was severely reduced in the model. These changes in spatial distribution triggered changes in the spatial availability of woody biomass over the simulation period of 80 years, and this led to changes in the rest of the herbivore community, resulting in increased densities of all herbivores, except for giraffe and steenbok, in areas close to rivers. The spatial distributions of elephant bulls and cows showed to be less affected by the closure of WPs than most of the other herbivore species. Our study contributes to ecologically informed decisions in wildlife management. The results from this modeling exercise imply that long-term effects of this intervention strategy should always be investigated at an ecosystem scale.

Characteristics of the horizontal and vertical distributions of dimethyl sulfide throughout the Amundsen Sea Polynya.

PubMed

Kim, Intae; Hahm, Doshik; Park, Keyhong; Lee, Youngju; Choi, Jung-Ok; Zhang, Miming; Chen, Liqi; Kim, Hyun-Cheol; Lee, SangHoon

2017-04-15

We investigated horizontal and vertical distributions of DMS in the upper water column of the Amundsen Sea Polynya and Pine Island Polynya during the austral summer (January-February) of 2016 using a membrane inlet mass spectrometer (MIMS) onboard the Korean icebreaker R/V Araon. The surface water concentrations of DMS varied from <1 to 400nM. The highest DMS (up to 300nM) were observed in sea ice-polynya transition zones and near the Getz ice shelf, where both the first local ice melting and high plankton productivity were observed. In other regions, high DMS concentration was generally accompanied by higher chlorophyll and ΔO 2 /Ar. The large spatial variability of DMS and primary productivity in the surface water of the Amundsen Sea seems to be attributed to melting conditions of sea ice, relative dominance of Phaeocystis Antarctica as a DMS producer, and timing differences between bloom and subsequent DMS productions. The depth profiles of DMS and ΔO 2 /Ar were consistent with the horizontal surface data, showing noticeable spatial variability. However, despite the large spatial variability, in contrast to the previous results from 2009, DMS concentrations and ΔO 2 /Ar in the surface water were indistinct between the two major domains: the sea ice zone and polynya region. The discrepancy may be associated with inter-annual variations of phytoplankton assemblages superimposed on differences in sea-ice conditions, blooming period, and spatial coverage along the vast surface area of the Amundsen Sea. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial distribution of traffic in a cellular mobile data network

NASA Astrophysics Data System (ADS)

Linnartz, J. P. M. G.

1987-02-01

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

Understanding the Distribution of Marine Megafauna in the English Channel Region: Identifying Key Habitats for Conservation within the Busiest Seaway on Earth

PubMed Central

McClellan, Catherine M.; Brereton, Tom; Dell'Amico, Florence; Johns, David G.; Cucknell, Anna-C.; Patrick, Samantha C.; Penrose, Rod; Ridoux, Vincent; Solandt, Jean-Luc; Stephan, Eric; Votier, Stephen C.; Williams, Ruth; Godley, Brendan J.

2014-01-01

The temperate waters of the North-Eastern Atlantic have a long history of maritime resource richness and, as a result, the European Union is endeavouring to maintain regional productivity and biodiversity. At the intersection of these aims lies potential conflict, signalling the need for integrated, cross-border management approaches. This paper focuses on the marine megafauna of the region. This guild of consumers was formerly abundant, but is now depleted and protected under various national and international legislative structures. We present a meta-analysis of available megafauna datasets using presence-only distribution models to characterise suitable habitat and identify spatially-important regions within the English Channel and southern bight of the North Sea. The integration of studies from dedicated and opportunistic observer programmes in the United Kingdom and France provide a valuable perspective on the spatial and seasonal distribution of various taxonomic groups, including large pelagic fishes and sharks, marine mammals, seabirds and marine turtles. The Western English Channel emerged as a hotspot of biodiversity for megafauna, while species richness was low in the Eastern English Channel. Spatial conservation planning is complicated by the highly mobile nature of marine megafauna, however they are important components of the marine environment and understanding their distribution is a first crucial step toward their inclusion into marine ecosystem management. PMID:24586985

Temporal and spatial variations of soil carbon dioxide, methane, and nitrous oxide fluxes in a Southeast Asian tropical rainforest

NASA Astrophysics Data System (ADS)

Itoh, M.; Kosugi, Y.; Takanashi, S.; Hayashi, Y.; Kanemitsu, S.; Osaka, K.; Tani, M.; Nik, A. R.

2010-09-01

To clarify the factors controlling temporal and spatial variations of soil carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes, we investigated these gas fluxes and environmental factors in a tropical rainforest in Peninsular Malaysia. Temporal variation of CO2 flux in a 2-ha plot was positively related to soil water condition and rainfall history. Spatially, CO2 flux was negatively related to soil water condition. When CO2 flux hotspots were included, no other environmental factors such as soil C or N concentrations showed any significant correlation. Although the larger area sampled in the present study complicates explanations of spatial variation of CO2 flux, our results support a previously reported bipolar relationship between the temporal and spatial patterns of CO2 flux and soil water condition observed at the study site in a smaller study plot. Flux of CH4 was usually negative with little variation, resulting in the soil at our study site functioning as a CH4 sink. Both temporal and spatial variations of CH4 flux were positively related to the soil water condition. Soil N concentration was also related to the spatial distribution of CH4 flux. Some hotspots were observed, probably due to CH4 production by termites, and these hotspots obscured the relationship between both temporal and spatial variations of CH4 flux and environmental factors. Temporal variation of N2O flux and soil N2O concentration was large and significantly related to the soil water condition, or in a strict sense, to rainfall history. Thus, the rainfall pattern controlled wet season N2O production in soil and its soil surface flux. Spatially, large N2O emissions were detected in wet periods at wetter and anaerobic locations, and were thus determined by soil physical properties. Our results showed that, even in Southeast Asian rainforests where distinct dry and wet seasons do not exist, variation in the soil water condition related to rainfall history controlled the temporal variations of soil CO2 flux, CH4 uptake, and N2O emission. The soil water condition associated with soil hydraulic properties was also the important controlling factor of the spatial distributions of these gas fluxes.

Mapping the spatial distribution of star formation in cluster galaxies at z ~0.5 with the Grism Lens-Amplified Survey from Space (GLASS)

NASA Astrophysics Data System (ADS)

Vulcani, B.; Treu, T.; Schmidt, K. B.; Poggianti, B. M.; Dressler, A.; Fontana, A.; Bradač, M.; Brammer, G. B.; Hoag, A.; Huang, K.; Malkan, M.; Pentericci, L.; Trenti, M.; von der Linden, A.; Abramson, L.; He, J.; Morris, G.

2016-06-01

What physical processes regulate star formation in dense environments? Understanding why galaxy evolution is environment dependent is one of the key questions of current astrophysics. I will present the first characterization of the spatial distribution of star formation in cluster galaxies at z~0.5, and compare to a field control sample, in order to quantify the role of different physical processes that are believed to be responsible for shutting down star formation (Vulcani et al. 2015, Vulcani et al. in prep). The analysis makes use of data from the Grism Lens-Amplified Survey from Space (GLASS), a large HST cycle-21 program targeting 10 massive galaxy clusters with extensive HST imaging from CLASH and the Frontier Field Initiative. The program consists of 140 primary and 140 parallel orbits of near-infrared WCF3 and optical ACS slitless grism observations, which result in 3D spectroscopy of hundreds of galaxies. The grism data are used to produce spatially resolved maps of the star formation density, while the stellar mass density and optical surface brightness are obtained from multiband imaging. I will describe quantitative measures of the spatial location and extent of the star formation rate. I will show that both in clusters and in the field, Hα is more extended than the rest-frame UV continuum in 60% of the cases, consistent with diffuse star formation and inside out growth. The Hα emission appears more extended in cluster galaxies than in the field, pointing perhaps to ionized gas being stripped and/or star formation being enhanced at large radii. The peak of the Hα emission and that of the continuum are offset by less than 1 kpc. I will also correlate the properties of the Hα maps to the cluster global properties, such as the hot gas density, and the surface mass density. The characterization of the spatial distribution of Halpha provides a new window, yet poorly exploited, on the mechanisms that regulate star formation and morphological transformation in dense environments.

Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps.

PubMed

Mitchard, Edward Ta; Saatchi, Sassan S; Baccini, Alessandro; Asner, Gregory P; Goetz, Scott J; Harris, Nancy L; Brown, Sandra

2013-10-26

Mapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m - 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by the same spaceborne LiDAR dataset providing systematic forest height and canopy structure estimates, but use different ground datasets for calibration and different spatial modelling methodologies. Here, we compare these two maps to each other, to the FAO's Forest Resource Assessment (FRA) 2010 country-level data, and to a high resolution (100 m) biomass map generated for a portion of the Colombian Amazon. We find substantial differences between the two maps, in particular in central Amazonia, the Congo basin, the south of Papua New Guinea, the Miombo woodlands of Africa, and the dry forests and savannas of South America. There is little consistency in the direction of the difference. However, when the maps are aggregated to the country or biome scale there is greater agreement, with differences cancelling out to a certain extent. When comparing country level biomass stocks, the two maps agree with each other to a much greater extent than to the FRA 2010 estimates. In the Colombian Amazon, both pantropical maps estimate higher biomass than the independent high resolution map, but show a similar spatial distribution of this biomass. Biomass mapping has progressed enormously over the past decade, to the stage where we can produce globally consistent maps of aboveground biomass. We show that there are still large uncertainties in these maps, in particular in areas with little field data. However, when used at a regional scale, different maps appear to converge, suggesting we can provide reasonable stock estimates when aggregated over large regions. Therefore we believe the largest uncertainties for REDD+ activities relate to the spatial distribution of biomass and to the spatial pattern of forest cover change, rather than to total globally or nationally summed carbon density.

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

NASA Astrophysics Data System (ADS)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

Declines in moose population density at Isle Royle National Park, MI, USA and accompanied changes in landscape patterns

USGS Publications Warehouse

De Jager, N. R.; Pastor, J.

2009-01-01

Ungulate herbivores create patterns of forage availability, plant species composition, and soil fertility as they range across large landscapes and consume large quantities of plant material. Over time, herbivore populations fluctuate, producing great potential for spatio-temporal landscape dynamics. In this study, we extend the spatial and temporal extent of a long-term investigation of the relationship of landscape patterns to moose foraging behavior at Isle Royale National Park, MI. We examined how patterns of browse availability and consumption, plant basal area, and soil fertility changed during a recent decline in the moose population. We used geostatistics to examine changes in the nature of spatial patterns in two valleys over 18 years and across short-range and long-range distance scales. Landscape patterns of available and consumed browse changed from either repeated patches or randomly distributed patches in 1988-1992 to random point distributions by 2007 after a recent record high peak followed by a rapid decline in the moose population. Patterns of available and consumed browse became decoupled during the moose population low, which is in contrast to coupled patterns during the earlier high moose population. Distributions of plant basal area and soil nitrogen availability also switched from repeated patches to randomly distributed patches in one valley and to random point distributions in the other valley. Rapid declines in moose population density may release vegetation and soil fertility from browsing pressure and in turn create random landscape patterns. ?? Springer Science+Business Media B.V. 2009.

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

Miller, Brian W.; Frost, Sophia; Frayo, Shani

Abstract Alpha emitting radionuclides exhibit a potential advantage for cancer treatments because they release large amounts of ionizing energy over a few cell diameters (50–80 μm) causing localized, irreparable double-strand DNA breaks that lead to cell death. Radioimmunotherapy (RIT) approaches using monoclonal antibodies labeled with alpha emitters may inactivate targeted cells with minimal radiation damage to surrounding tissues. For accurate dosimetry in alpha-RIT, tools are needed to visualize and quantify the radioactivity distribution and absorbed dose to targeted and non-targeted cells, especially for organs and tumors with heterogeneous radionuclide distributions. The aim of this study was to evaluate and characterizemore » a novel single-particle digital autoradiography imager, iQID (ionizing-radiation Quantum Imaging Detector), for use in alpha-RIT experiments. Methods: The iQID camera is a scintillator-based radiation detection technology that images and identifies charged-particle and gamma-ray/X-ray emissions spatially and temporally on an event-by-event basis. It employs recent advances in CCD/CMOS cameras and computing hardware for real-time imaging and activity quantification of tissue sections, approaching cellular resolutions. In this work, we evaluated this system’s characteristics for alpha particle imaging including measurements of spatial resolution and background count rates at various detector configurations and quantification of activity distributions. The technique was assessed for quantitative imaging of astatine-211 (211At) activity distributions in cryosections of murine and canine tissue samples. Results: The highest spatial resolution was measured at ~20 μm full width at half maximum (FWHM) and the alpha particle background was measured at a rate of (2.6 ± 0.5) × 10–4 cpm/cm2 (40 mm diameter detector area). Simultaneous imaging of multiple tissue sections was performed using a large-area iQID configuration (ø 11.5 cm). Estimation of the 211At activity distribution was demonstrated at mBq/μg levels. Conclusion: Single-particle digital autoradiography of alpha emitters has advantages over traditional autoradiographic techniques in terms of spatial resolution, sensitivity, and activity quantification capability. The system features and characterization results presented in this study show that iQID is a promising technology for microdosimetry, because it provides necessary information for interpreting alpha-RIT outcomes and for predicting the therapeutic efficacy of cell-targeted approaches using alpha emitters.« less

Isotopes, Inventories and Seasonality: Unraveling Methane Source Distribution in the Complex Landscapes of the United Kingdom.

NASA Astrophysics Data System (ADS)

Lowry, D.; Fisher, R. E.; Zazzeri, G.; Lanoisellé, M.; France, J.; Allen, G.; Nisbet, E. G.

2017-12-01

Unlike the big open landscapes of many continents with large area sources dominated by one particular methane emission type that can be isotopically characterized by flight measurements and sampling, the complex patchwork of urban, fossil and agricultural methane sources across NW Europe require detailed ground surveys for characterization (Zazzeri et al., 2017). Here we outline the findings from multiple seasonal urban and rural measurement campaigns in the United Kingdom. These surveys aim to: 1) Assess source distribution and baseline in regions of planned fracking, and relate to on-site continuous baseline climatology. 2) Characterize spatial and seasonal differences in the isotopic signatures of the UNFCCC source categories, and 3) Assess the spatial validity of the 1 x 1 km UK inventory for large continuous emitters, proposed point sources, and seasonal / ephemeral emissions. The UK inventory suggests that 90% of methane emissions are from 3 source categories, ruminants, landfill and gas distribution. Bag sampling and GC-IRMS delta13C analysis shows that landfill gives a constant signature of -57 ±3 ‰ throughout the year. Fugitive gas emissions are consistent regionally depending on the North Sea supply regions feeding the network (-41 ± 2 ‰ in N England, -37 ± 2 ‰ in SE England). Ruminant, mostly cattle, emissions are far more complex as these spend winters in barns and summers in fields, but are essentially a mix of 2 end members, breath at -68 ±3 ‰ and manure at -51 ±3 ‰, resulting in broad summer field emission plumes of -64 ‰ and point winter barn emission plumes of -58 ‰. The inventory correctly locates emission hotspots from landfill, larger sewage treatment plants and gas compressor stations, giving a broad overview of emission distribution for regional model validation. Mobile surveys are adding an extra layer of detail to this which, combined with isotopic characterization, has identified spatial distribution of gas pipe leaks, some persisting since 2013 (Zazzeri et al., 2015), and seasonality and spatial variability of livestock emissions. Importantly existing significant gas leaks close to proposed fracking sites have been characterized so that any emissions to atmosphere with a different isotopic signature will be detected. Zazzeri, G., Atm. Env. 110, 151-162 (2015); Zazzeri, G., Sci. Rep. 7, 4854 (2017).

Spatial and temporal distribution of pore gas concentrations during mainstream large-scale trough composting in China.

PubMed

Zeng, Jianfei; Shen, Xiuli; Sun, Xiaoxi; Liu, Ning; Han, Lujia; Huang, Guangqun

2018-05-01

With the advantages of high treatment capacity and low operational cost, large-scale trough composting has become one of the mainstream composting patterns in composting plants in China. This study measured concentrations of O 2 , CO 2 , CH 4 and NH 3 on-site to investigate the spatial and temporal distribution of pore gas concentrations during mainstream large-scale trough composting in China. The results showed that the temperature in the center of the pile was obviously higher than that in the side of the pile. Pore O 2 concentration rapidly decreased and maintained <5% (in volume) for 38 days or more in both the center and side of the pile and effective O 2 diffusion occurred at most in every two contiguous layers. Pore CO 2 and CH 4 concentrations at each measurement point were positively correlated (0.436 ≤ r ≤ 0.570, P < 0.01) and the concentrations in the side of the pile were obviously lower than those in the center. The top layer exhibited highest pore O 2 concentration and lowest CO 2 and CH 4 concentrations, and the bottom layer was on the contrary. No significant differences in pore NH 3 concentrations between different layers or between different measurement points in the same layer were found. Therefore, mixing the center and the side of the pile when mechanical turning and adjusting the height of the pile according to the physical properties of bulking agents are suggested to optimize the oxygen distribution and promote the composting process during large-scale trough composting when the pile was naturally aerated, which will contribute to improving the current undesirable atmosphere environment in China. Copyright © 2018 Elsevier Ltd. All rights reserved.

Large-Scale Spatial Distribution Patterns of Gastropod Assemblages in Rocky Shores

PubMed Central

Miloslavich, Patricia; Cruz-Motta, Juan José; Klein, Eduardo; Iken, Katrin; Weinberger, Vanessa; Konar, Brenda; Trott, Tom; Pohle, Gerhard; Bigatti, Gregorio; Benedetti-Cecchi, Lisandro; Shirayama, Yoshihisa; Mead, Angela; Palomo, Gabriela; Ortiz, Manuel; Gobin, Judith; Sardi, Adriana; Díaz, Juan Manuel; Knowlton, Ann; Wong, Melisa; Peralta, Ana C.

2013-01-01

Gastropod assemblages from nearshore rocky habitats were studied over large spatial scales to (1) describe broad-scale patterns in assemblage composition, including patterns by feeding modes, (2) identify latitudinal pattern of biodiversity, i.e., richness and abundance of gastropods and/or regional hotspots, and (3) identify potential environmental and anthropogenic drivers of these assemblages. Gastropods were sampled from 45 sites distributed within 12 Large Marine Ecosystem regions (LME) following the NaGISA (Natural Geography in Shore Areas) standard protocol (www.nagisa.coml.org). A total of 393 gastropod taxa from 87 families were collected. Eight of these families (9.2%) appeared in four or more different LMEs. Among these, the Littorinidae was the most widely distributed (8 LMEs) followed by the Trochidae and the Columbellidae (6 LMEs). In all regions, assemblages were dominated by few species, the most diverse and abundant of which were herbivores. No latitudinal gradients were evident in relation to species richness or densities among sampling sites. Highest diversity was found in the Mediterranean and in the Gulf of Alaska, while highest densities were found at different latitudes and represented by few species within one genus (e.g. Afrolittorina in the Agulhas Current, Littorina in the Scotian Shelf, and Lacuna in the Gulf of Alaska). No significant correlation was found between species composition and environmental variables (r≤0.355, p>0.05). Contributing variables to this low correlation included invasive species, inorganic pollution, SST anomalies, and chlorophyll-a anomalies. Despite data limitations in this study which restrict conclusions in a global context, this work represents the first effort to sample gastropod biodiversity on rocky shores using a standardized protocol across a wide scale. Our results will generate more work to build global databases allowing for large-scale diversity comparisons of rocky intertidal assemblages. PMID:23967204

The pattern of spatial flood disaster region in DKI Jakarta

NASA Astrophysics Data System (ADS)

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 in beach ridge, coastal alluvial plain, and alluvial plain; while the flood potential area on the slope is found flat and steep at alluvial fan, alluvial plain, beach ridge, and coastal alluvial plain in DKI Jakarta. Based on the result can be concluded that actual flood prone is not distributed on potential flood prone

Numerical Study of the Role of Microphysical Latent Heating and Surface Heat Fluxes in a Severe Precipitation Event in the Warm Sector over Southern China

NASA Astrophysics Data System (ADS)

Yin, Jin-Fang; Wang, Dong-Hai; Liang, Zhao-Ming; Liu, Chong-Jian; Zhai, Guo-Qing; Wang, Hong

2018-02-01

Simulations of the severe precipitation event that occurred in the warm sector over southern China on 08 May 2014 are conducted using the Advanced Weather Research and Forecasting (WRF-ARWv3.5.1) model to investigate the roles of microphysical latent heating and surface heat fluxes during the severe precipitation processes. At first, observations from surface rain gauges and ground-based weather radars are used to evaluate the model outputs. Results show that the spatial distribution of 24-h accumulated precipitation is well reproduced, and the temporal and spatial distributions of the simulated radar reflectivity agree well with the observations. Then, several sensitive simulations are performed with the identical model configurations, except for different options in microphysical latent heating and surface heat fluxes. From the results, one of the significant findings is that the latent heating from warm rain microphysical processes heats the atmosphere in the initial phase of the precipitation and thus convective systems start by self-triggering and self-organizing, despite the fact that the environmental conditions are not favorable to the occurrence of precipitation event at the initial phase. In the case of the severe precipitation event over the warm sector, both warm and ice microphysical processes are active with the ice microphysics processes activated almost two hours later. According to the sensitive results, there is a very weak precipitation without heavy rainfall belt when microphysical latent heating is turned off. In terms of this precipitation event, the warm microphysics processes play significant roles on precipitation intensity, while the ice microphysics processes have effects on the spatial distribution of precipitation. Both surface sensible and latent heating have effects on the precipitation intensity and spatial distribution. By comparison, the surface sensible heating has a strong influence on the spatial distribution of precipitation, and the surface latent heating has only a slight impact on the precipitation intensity. The results indicate that microphysical latent heating might be an important factor for severe precipitation forecast in the warm sector over southern China. Surface sensible heating can have considerable influence on the precipitation spatial distribution and should not be neglected in the case of weak large-scale conditions with abundant water vapor in the warm sector.

Geologic Mapping of the Lunar South Pole Quadrangle (LQ-30)

NASA Technical Reports Server (NTRS)

Mest, S. C.; Berman, D. C.; Petro, N. E.

2010-01-01

In this study we use recent image, spectral and topographic data to map the geology of the lunar South Pole quadrangle (LQ-30) at 1:2.5M scale [1-7]. The overall objective of this research is to constrain the geologic evolution of LQ-30 (60 -90 S, 0 - 180 ) with specific emphasis on evaluation of a) the regional effects of impact basin formation, and b) the spatial distribution of ejecta, in particular resulting from formation of the South Pole-Aitken (SPA) basin and other large basins. Key scientific objectives include: 1) Determining the geologic history of LQ-30 and examining the spatial and temporal variability of geologic processes within the map area. 2) Constraining the distribution of impact-generated materials, and determining the timing and effects of major basin-forming impacts on crustal structure and stratigraphy in the map area. And 3) assessing the distribution of potential resources (e.g., H, Fe, Th) and their relationships with surface materials.

Valley s'Asymmetric Characteristics of the Loess Plateau in Northwestern Shanxi Based on DEM

NASA Astrophysics Data System (ADS)

Duan, J.

2016-12-01

The valleys of the Loess Plateau in northwestern Shanxi show great asymmetry. This study using multi-scale DEMs, high-resolution satellite images and digital terrain analysis method, put forward a quantitative index to describe the asymmetric morphology. Several typical areas are selected to test and verify the spatial variability. Results show: (1) Considering the difference of spatial distribution, Pianguanhe basin, Xianchuanhe basin and Yangjiachuan basin are the areas where show most significant asymmetric characteristics . (2) Considering the difference of scale, the shape of large-scale valleys represents three characteristics: randomness, equilibrium and relative symmetry, while small-scale valleys show directionality and asymmetry. (3) Asymmetric morphology performs orientation, and the east-west valleys extremely obvious. Combined with field survey, its formation mechanism can be interpreted as follows :(1)Loess uneven distribution in the valleys. (2) The distribution diversities of vegetation, water , heat conditions and other factors, make a difference in water erosion capability which leads to asymmetric characteristics.

How selection structures species abundance distributions

PubMed Central

Magurran, Anne E.; Henderson, Peter A.

2012-01-01

How do species divide resources to produce the characteristic species abundance distributions seen in nature? One way to resolve this problem is to examine how the biomass (or capacity) of the spatial guilds that combine to produce an abundance distribution is allocated among species. Here we argue that selection on body size varies across guilds occupying spatially distinct habitats. Using an exceptionally well-characterized estuarine fish community, we show that biomass is concentrated in large bodied species in guilds where habitat structure provides protection from predators, but not in those guilds associated with open habitats and where safety in numbers is a mechanism for reducing predation risk. We further demonstrate that while there is temporal turnover in the abundances and identities of species that comprise these guilds, guild rank order is conserved across our 30-year time series. These results demonstrate that ecological communities are not randomly assembled but can be decomposed into guilds where capacity is predictably allocated among species. PMID:22787020

Novel measurement of spreading pattern of influenza epidemic by using weighted standard distance method: retrospective spatial statistical study of influenza, Japan, 1999-2009.

PubMed

Shobugawa, Yugo; Wiafe, Seth A; Saito, Reiko; Suzuki, Tsubasa; Inaida, Shinako; Taniguchi, Kiyosu; Suzuki, Hiroshi

2012-06-19

Annual influenza epidemics occur worldwide resulting in considerable morbidity and mortality. Spreading pattern of influenza is not well understood because it is often hampered by the quality of surveillance data that limits the reliability of analysis. In Japan, influenza is reported on a weekly basis from 5,000 hospitals and clinics nationwide under the scheme of the National Infectious Disease Surveillance. The collected data are available to the public as weekly reports which were summarized into number of patient visits per hospital or clinic in each of the 47 prefectures. From this surveillance data, we analyzed the spatial spreading patterns of influenza epidemics using weekly weighted standard distance (WSD) from the 1999/2000 through 2008/2009 influenza seasons in Japan. WSD is a single numerical value representing the spatial compactness of influenza outbreak, which is small in case of clustered distribution and large in case of dispersed distribution. We demonstrated that the weekly WSD value or the measure of spatial compactness of the distribution of reported influenza cases, decreased to its lowest value before each epidemic peak in nine out of ten seasons analyzed. The duration between the lowest WSD week and the peak week of influenza cases ranged from minus one week to twenty weeks. The duration showed significant negative association with the proportion of influenza A/H3N2 cases in early phase of each outbreak (correlation coefficient was -0.75, P = 0.012) and significant positive association with the proportion of influenza B cases in the early phase (correlation coefficient was 0.64, P = 0.045), but positively correlated with the proportion of influenza A/H1N1 strain cases (statistically not significant). It is assumed that the lowest WSD values just before influenza peaks are due to local outbreak which results in small standard distance values. As influenza cases disperse nationwide and an epidemic reaches its peak, WSD value changed to be a progressively increasing. The spatial distribution of nationwide influenza outbreak was measured by using a novel WSD method. We showed that spreading rate varied by type and subtypes of influenza virus using WSD as a spatial indicator. This study is the first to show a relationship between influenza epidemic trend by type/subtype and spatial distribution of influenza nationwide in Japan.

Visual Perception-Based Statistical Modeling of Complex Grain Image for Product Quality Monitoring and Supervision on Assembly Production Line

PubMed Central

Chen, Qing; Xu, Pengfei; Liu, Wenzhong

2016-01-01

Computer vision as a fast, low-cost, noncontact, and online monitoring technology has been an important tool to inspect product quality, particularly on a large-scale assembly production line. However, the current industrial vision system is far from satisfactory in the intelligent perception of complex grain images, comprising a large number of local homogeneous fragmentations or patches without distinct foreground and background. We attempt to solve this problem based on the statistical modeling of spatial structures of grain images. We present a physical explanation in advance to indicate that the spatial structures of the complex grain images are subject to a representative Weibull distribution according to the theory of sequential fragmentation, which is well known in the continued comminution of ore grinding. To delineate the spatial structure of the grain image, we present a method of multiscale and omnidirectional Gaussian derivative filtering. Then, a product quality classifier based on sparse multikernel–least squares support vector machine is proposed to solve the low-confidence classification problem of imbalanced data distribution. The proposed method is applied on the assembly line of a food-processing enterprise to classify (or identify) automatically the production quality of rice. The experiments on the real application case, compared with the commonly used methods, illustrate the validity of our method. PMID:26986726

Examining the influence of heterogeneous porosity fields on conservative solute transport

USGS Publications Warehouse

Hu, B.X.; Meerschaert, M.M.; Barrash, W.; Hyndman, D.W.; He, C.; Li, X.; Guo, Laodong

2009-01-01

It is widely recognized that groundwater flow and solute transport in natural media are largely controlled by heterogeneities. In the last three decades, many studies have examined the effects of heterogeneous hydraulic conductivity fields on flow and transport processes, but there has been much less attention to the influence of heterogeneous porosity fields. In this study, we use porosity and particle size measurements from boreholes at the Boise Hydrogeophysical Research Site (BHRS) to evaluate the importance of characterizing the spatial structure of porosity and grain size data for solute transport modeling. Then we develop synthetic hydraulic conductivity fields based on relatively simple measurements of porosity from borehole logs and grain size distributions from core samples to examine and compare the characteristics of tracer transport through these fields with and without inclusion of porosity heterogeneity. In particular, we develop horizontal 2D realizations based on data from one of the less heterogeneous units at the BHRS to examine effects where spatial variations in hydraulic parameters are not large. The results indicate that the distributions of porosity and the derived hydraulic conductivity in the study unit resemble fractal normal and lognormal fields respectively. We numerically simulate solute transport in stochastic fields and find that spatial variations in porosity have significant effects on the spread of an injected tracer plume including a significant delay in simulated tracer concentration histories.

Multilevel Analysis of Trachomatous Trichiasis and Corneal Opacity in Nigeria: The Role of Environmental and Climatic Risk Factors on the Distribution of Disease.

PubMed

Smith, Jennifer L; Sivasubramaniam, Selvaraj; Rabiu, Mansur M; Kyari, Fatima; Solomon, Anthony W; Gilbert, Clare

2015-01-01

The distribution of trachoma in Nigeria is spatially heterogeneous, with large-scale trends observed across the country and more local variation within areas. Relative contributions of individual and cluster-level risk factors to the geographic distribution of disease remain largely unknown. The primary aim of this analysis is to assess the relationship between climatic factors and trachomatous trichiasis (TT) and/or corneal opacity (CO) due to trachoma in Nigeria, while accounting for the effects of individual risk factors and spatial correlation. In addition, we explore the relative importance of variation in the risk of trichiasis and/or corneal opacity (TT/CO) at different levels. Data from the 2007 National Blindness and Visual Impairment Survey were used for this analysis, which included a nationally representative sample of adults aged 40 years and above. Complete data were available from 304 clusters selected using a multi-stage stratified cluster-random sampling strategy. All participants (13,543 individuals) were interviewed and examined by an ophthalmologist for the presence or absence of TT and CO. In addition to field-collected data, remotely sensed climatic data were extracted for each cluster and used to fit Bayesian hierarchical logistic models to disease outcome. The risk of TT/CO was associated with factors at both the individual and cluster levels, with approximately 14% of the total variation attributed to the cluster level. Beyond established individual risk factors (age, gender and occupation), there was strong evidence that environmental/climatic factors at the cluster-level (lower precipitation, higher land surface temperature, higher mean annual temperature and rural classification) were also associated with a greater risk of TT/CO. This study establishes the importance of large-scale risk factors in the geographical distribution of TT/CO in Nigeria, supporting anecdotal evidence that environmental conditions are associated with increased risk in this context and highlighting their potential use in improving estimates of disease burden at large scales.

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

PubMed

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

2018-04-17

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

Imaging doppler lidar for wind turbine wake profiling

DOEpatents

Bossert, David J.

2015-11-19

An imaging Doppler lidar (IDL) enables the measurement of the velocity distribution of a large volume, in parallel, and at high spatial resolution in the wake of a wind turbine. Because the IDL is non-scanning, it can be orders of magnitude faster than conventional coherent lidar approaches. Scattering can be obtained from naturally occurring aerosol particles. Furthermore, the wind velocity can be measured directly from Doppler shifts of the laser light, so the measurement can be accomplished at large standoff and at wide fields-of-view.

Evaluation of True Power Luminous Efficiency from Experimental Luminance Values

NASA Astrophysics Data System (ADS)

Tsutsui, Tetsuo; Yamamato, Kounosuke

1999-05-01

A method for obtaining true external power luminous efficiencyfrom experimentally obtained luminance in organic light-emittingdiodes (LEDs) wasdemonstrated. Conventional two-layer organic LEDs with different electron-transport layer thicknesses wereprepared. Spatial distributions of emission intensities wereobserved. The large deviation in both emission spectra and spatialemission patterns were observed when the electron-transport layerthickness was varied. The deviation of emission patterns from thestandard Lambertian pattern was found to cause overestimations ofpower luminous efficiencies as large as 30%. A method for evaluatingcorrection factors was proposed.

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

Treesearch

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

2013-01-01

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

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

PubMed

Yuan, Zheming; Fu, Wei; Li, Fangyi

2004-04-01

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

Cross-Scale Molecular Analysis of Chemical Heterogeneity in Shale Rocks

DOE PAGES

Hao, Zhao; Bechtel, Hans A.; Kneafsey, Timothy; ...

2018-02-07

The organic and mineralogical heterogeneity in shale at micrometer and nanometer spatial scales contributes to the quality of gas reserves, gas flow mechanisms and gas production. Here, we demonstrate two molecular imaging approaches based on infrared spectroscopy to obtain mineral and kerogen information at these mesoscale spatial resolutions in large-sized shale rock samples. The first method is a modified microscopic attenuated total reflectance measurement that utilizes a large germanium hemisphere combined with a focal plane array detector to rapidly capture chemical images of shale rock surfaces spanning hundreds of micrometers with micrometer spatial resolution. The second method, synchrotron infrared nano-spectroscopy,more » utilizes a metallic atomic force microscope tip to obtain chemical images of micrometer dimensions but with nanometer spatial resolution. This chemically "deconvoluted" imaging at the nano-pore scale is then used to build a machine learning model to generate a molecular distribution map across scales with a spatial span of 1000 times, which enables high-throughput geochemical characterization in greater details across the nano-pore and micro-grain scales and allows us to identify co-localization of mineral phases with chemically distinct organics and even with gas phase sorbents. Finally, this characterization is fundamental to understand mineral and organic compositions affecting the behavior of shales.« less

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

PubMed Central

Akkaynak, Derya; Siemann, Liese A.; Barbosa, Alexandra

2017-01-01

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. PMID:28405370

Cross-Scale Molecular Analysis of Chemical Heterogeneity in Shale Rocks

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

Hao, Zhao; Bechtel, Hans A.; Kneafsey, Timothy

The organic and mineralogical heterogeneity in shale at micrometer and nanometer spatial scales contributes to the quality of gas reserves, gas flow mechanisms and gas production. Here, we demonstrate two molecular imaging approaches based on infrared spectroscopy to obtain mineral and kerogen information at these mesoscale spatial resolutions in large-sized shale rock samples. The first method is a modified microscopic attenuated total reflectance measurement that utilizes a large germanium hemisphere combined with a focal plane array detector to rapidly capture chemical images of shale rock surfaces spanning hundreds of micrometers with micrometer spatial resolution. The second method, synchrotron infrared nano-spectroscopy,more » utilizes a metallic atomic force microscope tip to obtain chemical images of micrometer dimensions but with nanometer spatial resolution. This chemically "deconvoluted" imaging at the nano-pore scale is then used to build a machine learning model to generate a molecular distribution map across scales with a spatial span of 1000 times, which enables high-throughput geochemical characterization in greater details across the nano-pore and micro-grain scales and allows us to identify co-localization of mineral phases with chemically distinct organics and even with gas phase sorbents. Finally, this characterization is fundamental to understand mineral and organic compositions affecting the behavior of shales.« less

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

PubMed

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.

Spatial clustering of mental disorders and associated characteristics of the neighbourhood context in Malmö, Sweden, in 2001

PubMed Central

Chaix, Basile; Leyland, Alastair H; Sabel, Clive E; Chauvin, Pierre; Råstam, Lennart; Kristersson, Håkan; Merlo, Juan

2006-01-01

Study objective Previous research provides preliminary evidence of spatial variations of mental disorders and associations between neighbourhood social context and mental health. This study expands past literature by (1) using spatial techniques, rather than multilevel models, to compare the spatial distributions of two groups of mental disorders (that is, disorders due to psychoactive substance use, and neurotic, stress related, and somatoform disorders); and (2) investigating the independent impact of contextual deprivation and neighbourhood social disorganisation on mental health, while assessing both the magnitude and the spatial scale of these effects. Design Using different spatial techniques, the study investigated mental disorders due to psychoactive substance use, and neurotic disorders. Participants All 89 285 persons aged 40–69 years residing in Malmö, Sweden, in 2001, geolocated to their place of residence. Main results The spatial scan statistic identified a large cluster of increased prevalence in a similar location for the two mental disorders in the northern part of Malmö. However, hierarchical geostatistical models showed that the two groups of disorders exhibited a different spatial distribution, in terms of both magnitude and spatial scale. Mental disorders due to substance consumption showed larger neighbourhood variations, and varied in space on a larger scale, than neurotic disorders. After adjustment for individual factors, the risk of substance related disorders increased with neighbourhood deprivation and neighbourhood social disorganisation. The risk of neurotic disorders only increased with contextual deprivation. Measuring contextual factors across continuous space, it was found that these associations operated on a local scale. Conclusions Taking space into account in the analyses permitted deeper insight into the contextual determinants of mental disorders. PMID:16614334